Sirc-cvs cytotoxicity test: an alternative for predicting rodent acute systemic toxicity.

PubMed

Kitagaki, Masato; Wakuri, Shinobu; Hirota, Morihiko; Tanaka, Noriho; Itagaki, Hiroshi

2006-10-01

An in vitro crystal violet staining method using the rabbit cornea-derived cell line (SIRC-CVS) has been developed as an alternative to predict acute systemic toxicity in rodents. Seventy-nine chemicals, the in vitro cytotoxicity of which was already reported by the Multicenter Evaluation of In vitro Toxicity (MEIC) and ICCVAM/ECVAM, were selected as test compounds. The cells were incubated with the chemicals for 72 hrs and the IC(50) and IC(35) values (microg/mL) were obtained. The results were compared to the in vivo (rat or mouse) "most toxic" oral, intraperitoneal, subcutaneous and intravenous LD(50) values (mg/kg) taken from the RTECS database for each of the chemicals by using Pearson's correlation statistics. The following parameters were calculated: accuracy, sensitivity, specificity, prevalence, positive predictability, and negative predictability. Good linear correlations (Pearson's coefficient; r>0.6) were observed between either the IC(50) or the IC(35) values and all the LD(50) values. Among them, a statistically significant high correlation (r=0.8102, p<0.001) required for acute systemic toxicity prediction was obtained between the IC(50) values and the oral LD(50) values. By using the cut-off concentrations of 2,000 mg/kg (LD(50)) and 4,225 microg/mL (IC(50)), no false negatives were observed, and the accuracy was 84.8%. From this, it is concluded that this method could be used to predict the acute systemic toxicity potential of chemicals in rodents.

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.

Demographic influences on environmental value orientations and normative beliefs about national forest management

Treesearch

Jerry J. Vaske; Maureen P. Donnelly; Daniel R. Williams; Sandra Jonker

2001-01-01

Using the cognitive hierarchy as the theoretical foundation, this article examines the predictive influence of individuals' demographic characteristics on environmental value orientations and normative beliefs about national forest management. Data for this investigation were obtained from a random sample of Colorado residents (n = 960). As predicted by theory, a...

Using reflectance spectroscopy to predict beef tenderness.

PubMed

Bowling, M B; Vote, D J; Belk, K E; Scanga, J A; Tatum, J D; Smith, G C

2009-05-01

A study was conducted to determine if reflectance measurements made in the near-infrared region of the spectrum were additive to reflectance measurements made in the visible region of the spectrum for predicting Warner-Bratzler shear force (WBSF) values. Eighty seven strip loins were collected following fabrication over 3d at a commercial beef processing facility from heifer carcasses with Slight or Traces marbling scores. Spectroscopic measurements were made at approximately 50h postmortem using a Hunter-Lab UltraScan. Subsequently, all strip loins were aged for 14d, cooked to an internal temperature of 70°C, and sheared to obtain WBSF values. Reflectance measurements obtained in the near-infrared region of the spectrum were correlated with WBSF values, however, these measurements were not additive to the predictive ability of reflectance measurements (R(2) values did not differ) made in the visible portion of the spectrum when the use of broad-band wavelength filters were simulated. It was therefore determined, that both the visible and near-infrared spectra measure reflectance and that both methods are acceptable methods of tenderness prediction.

Life test results for the advanced very high resolution radiometer scanner

NASA Technical Reports Server (NTRS)

Lenz, James

1996-01-01

The following paper reports the results obtained during a 3.33-year life test on the TIROS Advanced Very High Resolution Radiometer/3 (AVHRR/3) Scanner. The bearing drag torque and lubricant loss over life will be compared to predicted values developed through modeling. The condition of the lubricant at the end of the test will be described and a theory presented to explain the results obtained. The differences (if any) in the predicted and measured values of drag torque and lubricant loss will be discussed and possible reasons for these examined.

Stock price prediction using geometric Brownian motion

NASA Astrophysics Data System (ADS)

Farida Agustini, W.; Restu Affianti, Ika; Putri, Endah RM

2018-03-01

Geometric Brownian motion is a mathematical model for predicting the future price of stock. The phase that done before stock price prediction is determine stock expected price formulation and determine the confidence level of 95%. On stock price prediction using geometric Brownian Motion model, the algorithm starts from calculating the value of return, followed by estimating value of volatility and drift, obtain the stock price forecast, calculating the forecast MAPE, calculating the stock expected price and calculating the confidence level of 95%. Based on the research, the output analysis shows that geometric Brownian motion model is the prediction technique with high rate of accuracy. It is proven with forecast MAPE value ≤ 20%.

Temperature and relative humidity estimation and prediction in the tobacco drying process using Artificial Neural Networks.

PubMed

Martínez-Martínez, Víctor; Baladrón, Carlos; Gomez-Gil, Jaime; Ruiz-Ruiz, Gonzalo; Navas-Gracia, Luis M; Aguiar, Javier M; Carro, Belén

2012-10-17

This paper presents a system based on an Artificial Neural Network (ANN) for estimating and predicting environmental variables related to tobacco drying processes. This system has been validated with temperature and relative humidity data obtained from a real tobacco dryer with a Wireless Sensor Network (WSN). A fitting ANN was used to estimate temperature and relative humidity in different locations inside the tobacco dryer and to predict them with different time horizons. An error under 2% can be achieved when estimating temperature as a function of temperature and relative humidity in other locations. Moreover, an error around 1.5 times lower than that obtained with an interpolation method can be achieved when predicting the temperature inside the tobacco mass as a function of its present and past values with time horizons over 150 minutes. These results show that the tobacco drying process can be improved taking into account the predicted future value of the monitored variables and the estimated actual value of other variables using a fitting ANN as proposed.

Prediction of wastewater quality indicators at the inflow to the wastewater treatment plant using data mining methods

NASA Astrophysics Data System (ADS)

Szeląg, Bartosz; Barbusiński, Krzysztof; Studziński, Jan; Bartkiewicz, Lidia

2017-11-01

In the study, models developed using data mining methods are proposed for predicting wastewater quality indicators: biochemical and chemical oxygen demand, total suspended solids, total nitrogen and total phosphorus at the inflow to wastewater treatment plant (WWTP). The models are based on values measured in previous time steps and daily wastewater inflows. Also, independent prediction systems that can be used in case of monitoring devices malfunction are provided. Models of wastewater quality indicators were developed using MARS (multivariate adaptive regression spline) method, artificial neural networks (ANN) of the multilayer perceptron type combined with the classification model (SOM) and cascade neural networks (CNN). The lowest values of absolute and relative errors were obtained using ANN+SOM, whereas the MARS method produced the highest error values. It was shown that for the analysed WWTP it is possible to obtain continuous prediction of selected wastewater quality indicators using the two developed independent prediction systems. Such models can ensure reliable WWTP work when wastewater quality monitoring systems become inoperable, or are under maintenance.

Temperature and Relative Humidity Estimation and Prediction in the Tobacco Drying Process Using Artificial Neural Networks

PubMed Central

Martínez-Martínez, Víctor; Baladrón, Carlos; Gomez-Gil, Jaime; Ruiz-Ruiz, Gonzalo; Navas-Gracia, Luis M.; Aguiar, Javier M.; Carro, Belén

2012-01-01

This paper presents a system based on an Artificial Neural Network (ANN) for estimating and predicting environmental variables related to tobacco drying processes. This system has been validated with temperature and relative humidity data obtained from a real tobacco dryer with a Wireless Sensor Network (WSN). A fitting ANN was used to estimate temperature and relative humidity in different locations inside the tobacco dryer and to predict them with different time horizons. An error under 2% can be achieved when estimating temperature as a function of temperature and relative humidity in other locations. Moreover, an error around 1.5 times lower than that obtained with an interpolation method can be achieved when predicting the temperature inside the tobacco mass as a function of its present and past values with time horizons over 150 minutes. These results show that the tobacco drying process can be improved taking into account the predicted future value of the monitored variables and the estimated actual value of other variables using a fitting ANN as proposed. PMID:23202032

Prediction of quantitative intrathoracic fluid volume to diagnose pulmonary oedema using LabVIEW.

PubMed

Urooj, Shabana; Khan, M; Ansari, A Q; Lay-Ekuakille, Aimé; Salhan, Ashok K

2012-01-01

Pulmonary oedema is a life-threatening disease that requires special attention in the area of research and clinical diagnosis. Computer-based techniques are rarely used to quantify the intrathoracic fluid volume (IFV) for diagnostic purposes. This paper discusses a software program developed to detect and diagnose pulmonary oedema using LabVIEW. The software runs on anthropometric dimensions and physiological parameters, mainly transthoracic electrical impedance (TEI). This technique is accurate and faster than existing manual techniques. The LabVIEW software was used to compute the parameters required to quantify IFV. An equation relating per cent control and IFV was obtained. The results of predicted TEI and measured TEI were compared with previously reported data to validate the developed program. It was found that the predicted values of TEI obtained from the computer-based technique were much closer to the measured values of TEI. Six new subjects were enrolled to measure and predict transthoracic impedance and hence to quantify IFV. A similar difference was also observed in the measured and predicted values of TEI for the new subjects.

How long the singular value decomposed entropy predicts the stock market? - Evidence from the Dow Jones Industrial Average Index

NASA Astrophysics Data System (ADS)

Gu, Rongbao; Shao, Yanmin

2016-07-01

In this paper, a new concept of multi-scales singular value decomposition entropy based on DCCA cross correlation analysis is proposed and its predictive power for the Dow Jones Industrial Average Index is studied. Using Granger causality analysis with different time scales, it is found that, the singular value decomposition entropy has predictive power for the Dow Jones Industrial Average Index for period less than one month, but not for more than one month. This shows how long the singular value decomposition entropy predicts the stock market that extends Caraiani's result obtained in Caraiani (2014). On the other hand, the result also shows an essential characteristic of stock market as a chaotic dynamic system.

Addendum to the article: Misuse of null hypothesis significance testing: Would estimation of positive and negative predictive values improve certainty of chemical risk assessment?

PubMed

Bundschuh, Mirco; Newman, Michael C; Zubrod, Jochen P; Seitz, Frank; Rosenfeldt, Ricki R; Schulz, Ralf

2015-03-01

We argued recently that the positive predictive value (PPV) and the negative predictive value (NPV) are valuable metrics to include during null hypothesis significance testing: They inform the researcher about the probability of statistically significant and non-significant test outcomes actually being true. Although commonly misunderstood, a reported p value estimates only the probability of obtaining the results or more extreme results if the null hypothesis of no effect was true. Calculations of the more informative PPV and NPV require a priori estimate of the probability (R). The present document discusses challenges of estimating R.

Circadian Macronutrients Variations over the First 7 Weeks of Human Milk Feeding of Preterm Infants.

PubMed

Moran-Lev, Hadar; Mimouni, Francis B; Ovental, Amit; Mangel, Laurence; Mandel, Dror; Lubetzky, Ronit

2015-09-01

Little is known about circadian variations of macronutrients content of expressed preterm human milk (HM). This study evaluated diurnal variations of macronutrients and energy content of preterm HM over the first 7 weeks of lactation and tested the hypothesis that values obtained during a morning sample are predictive of those obtained from an evening sample. Expressed HM was obtained from 32 mothers of preterm infants (26-33 weeks in gestational age), who routinely expressed all their milk every 3 hours from the beginning of the second to the seventh week after delivery. One aliquot was obtained from the first morning expression and the second from the evening expression. Energy and macronutrients contents were measured using an HM analyzer. Mean fat and energy contents of all samples obtained during the whole period were significantly higher in evening samples (p < 0.0001). There were no significant differences between morning and evening carbohydrates and protein contents. Concentrations of protein, carbohydrates, and fat from morning samples were predictive of evening concentrations to different extents (R(2) = 0.720, R(2) = 0.663, and R(2) = 0.20, respectively; p < 0.02). The predictability of evening values by morning values was not influenced by the week of lactation at sampling or by individual patients. In repeated-measures analysis of variance performed on 11 patients who completed the whole 7-week period, over time, there was a significant decrease in fat, energy, and protein contents, whereas carbohydrates content remained unchanged. Day-night differences remained significant only for fat content. Circadian variations in fat and energy concentrations of HM are consistent over the first 7 weeks of lactation. There are no consistent circadian variations in HM protein and carbohydrates. Over a given day, there are little variations in protein and carbohydrates content, but fat concentrations are more variable, and evening values are less well predicted by morning sample analysis than values for protein or carbohydrates.

Throat Swabs and Sputum Culture as Predictors of P. aeruginosa or S. aureus Lung Colonization in Adult Cystic Fibrosis Patients.

PubMed

Seidler, Darius; Griffin, Mary; Nymon, Amanda; Koeppen, Katja; Ashare, Alix

2016-01-01

Due to frequent infections in cystic fibrosis (CF) patients, repeated respiratory cultures are obtained to inform treatment. When patients are unable to expectorate sputum, clinicians obtain throat swabs as a surrogate for lower respiratory cultures. There is no clear data in adult subjects demonstrating the adequacy of throat swabs as a surrogate for sputum or BAL. Our study was designed to determine the utility of throat swabs in identifying lung colonization with common organisms in adults with CF. Adult CF subjects (n = 20) underwent bronchoscopy with BAL. Prior to bronchoscopy, a throat swab was obtained. A sputum sample was obtained from subjects who were able to spontaneously expectorate. All samples were sent for standard microbiology culture. Using BAL as the gold standard, we found the positive predictive value for Pseudomonas aeruginosa to be 100% in both sputum and throat swab compared to BAL. However, the negative predictive value for P. aeruginosa was 60% and 50% in sputum and throat swab, respectively. Conversely, the positive predictive value for Staphylococcus aureus was 57% in sputum and only 41% in throat swab and the negative predictive value of S. aureus was 100% in sputum and throat swab compared to BAL. Our data show that positive sputum and throat culture findings of P. aeruginosa reflect results found on BAL fluid analysis, suggesting these are reasonable surrogates to determine lung colonization with P. aeruginosa. However, sputum and throat culture findings of S. aureus do not appear to reflect S. aureus colonization of the lung.

Quantitative CT based radiomics as predictor of resectability of pancreatic adenocarcinoma

NASA Astrophysics Data System (ADS)

van der Putten, Joost; Zinger, Svitlana; van der Sommen, Fons; de With, Peter H. N.; Prokop, Mathias; Hermans, John

2018-02-01

In current clinical practice, the resectability of pancreatic ductal adenocarcinoma (PDA) is determined subjec- tively by a physician, which is an error-prone procedure. In this paper, we present a method for automated determination of resectability of PDA from a routine abdominal CT, to reduce such decision errors. The tumor features are extracted from a group of patients with both hypo- and iso-attenuating tumors, of which 29 were resectable and 21 were not. The tumor contours are supplied by a medical expert. We present an approach that uses intensity, shape, and texture features to determine tumor resectability. The best classification results are obtained with fine Gaussian SVM and the L0 Feature Selection algorithms. Compared to expert predictions made on the same dataset, our method achieves better classification results. We obtain significantly better results on correctly predicting non-resectability (+17%) compared to a expert, which is essential for patient treatment (negative prediction value). Moreover, our predictions of resectability exceed expert predictions by approximately 3% (positive prediction value).

Prediction of mechanical properties of composites of HDPE/HA/EAA.

PubMed

Albano, C; Perera, R; Cataño, L; Karam, A; González, G

2011-04-01

In this investigation, the behavior of the mechanical properties of composites of high-density polyethylene/hydroxyapatite (HDPE/HA) with and without ethylene-acrylic acid copolymer (EAA) as possible compatibilizer, was studied. Different mathematical models were used to predict their Young's modulus, tensile strength and elongation at break. A comparison with the experimental results shows that the theoretical models of Guth and Kerner modified can be used to predict the Young's modulus. On the other hand, the values obtained by the Verbeek model do not show a good agreement with the experimental data, since different factors that influence the mechanical properties are considered in this model such as: aspect ratio of the reinforcement, interfacial adhesion, porosity and binder content. TEM analysis confirms the discrepancies obtained between the experimental Young's modulus values and those predicted by the Verbeek model. The values of "P", "a" and "σ(A)" suggest that an interaction among the carboxylic groups of the copolymer and the hydroxyl groups of hydroxyapatite might be present. In composites with 20 and 30 wt% of filler, this interaction does not improve the Young's modulus values, since the deviations of the Verbeek model are significant. Copyright © 2010 Elsevier Ltd. All rights reserved.

Early pleural fluid dynamics following video-assisted thoracoscopic lobectomy has limited clinical value

PubMed Central

Holbek, Bo Laksáfoss; Petersen, René Horsleben; Kehlet, Henrik

2017-01-01

The objective of this study was to evaluate the potential of predicting the pleural fluid output in patients after video-assisted thoracoscopic lobectomy of the lung. Detailed measurements of continuous fluid output were obtained prospectively using an electronic thoracic drainage device (Thopaz+™, Medela AG, Switzerland). Patients were divided into high (≥500 mL) and low (<500 mL) 24-hour fluid output, and detailed flow curves were plotted graphically to identify arithmetic patterns predicting fluid output in the early (≤24 hours) and later (24–48 hours) post-operative phase. Furthermore, multiple logistic regression analysis was used to predict high 24-hour fluid output using baseline data. Data were obtained from 50 patients, where 52% had a fluid output of <500 mL/24 hours. From visual assessment of flow curves, patients were grouped according to fluid output 6 hours postoperatively. An output ≥200 mL/6 hours was predictive of ‘high 24-hour fluid output’ (P<0.0001). However, 33% of patients with <200 mL/6 hours ended with a ‘high 24-hour fluid output’. Baseline data showed no predictive value of fluid production, and 24-hour fluid output had no predictive value of fluid output between 24 and 48 hours. Assessment of initial fluid production may predict high 24-hour fluid output (≥500 mL) but seems to lack clinical value in drain removal criteria. PMID:28840021

Predictive models of alcohol use based on attitudes and individual values.

PubMed

García del Castillo Rodríguez, José A; López-Sánchez, Carmen; Quiles Soler, M Carmen; García del Castillo-López, Alvaro; Gázquez Pertusa, Mónica; Marzo Campos, Juan Carlos; Inglés, Candido J

2013-01-01

Two predictive models are developed in this article: the first is designed to predict people's attitudes to alcoholic drinks, while the second sets out to predict the use of alcohol in relation to selected individual values. University students (N = 1,500) were recruited through stratified sampling based on sex and academic discipline. The questionnaire used obtained information on participants' alcohol use, attitudes and personal values. The results show that the attitudes model correctly classifies 76.3% of cases. Likewise, the model for level of alcohol use correctly classifies 82% of cases. According to our results, we can conclude that there are a series of individual values that influence drinking and attitudes to alcohol use, which therefore provides us with a potentially powerful instrument for developing preventive intervention programs.

Modeling polyvinyl chloride Plasma Modification by Neural Networks

NASA Astrophysics Data System (ADS)

Wang, Changquan

2018-03-01

Neural networks model were constructed to analyze the connection between dielectric barrier discharge parameters and surface properties of material. The experiment data were generated from polyvinyl chloride plasma modification by using uniform design. Discharge voltage, discharge gas gap and treatment time were as neural network input layer parameters. The measured values of contact angle were as the output layer parameters. A nonlinear mathematical model of the surface modification for polyvinyl chloride was developed based upon the neural networks. The optimum model parameters were obtained by the simulation evaluation and error analysis. The results of the optimal model show that the predicted value is very close to the actual test value. The prediction model obtained here are useful for discharge plasma surface modification analysis.

Nonparametric functional data estimation applied to ozone data: prediction and extreme value analysis.

PubMed

Quintela-del-Río, Alejandro; Francisco-Fernández, Mario

2011-02-01

The study of extreme values and prediction of ozone data is an important topic of research when dealing with environmental problems. Classical extreme value theory is usually used in air-pollution studies. It consists in fitting a parametric generalised extreme value (GEV) distribution to a data set of extreme values, and using the estimated distribution to compute return levels and other quantities of interest. Here, we propose to estimate these values using nonparametric functional data methods. Functional data analysis is a relatively new statistical methodology that generally deals with data consisting of curves or multi-dimensional variables. In this paper, we use this technique, jointly with nonparametric curve estimation, to provide alternatives to the usual parametric statistical tools. The nonparametric estimators are applied to real samples of maximum ozone values obtained from several monitoring stations belonging to the Automatic Urban and Rural Network (AURN) in the UK. The results show that nonparametric estimators work satisfactorily, outperforming the behaviour of classical parametric estimators. Functional data analysis is also used to predict stratospheric ozone concentrations. We show an application, using the data set of mean monthly ozone concentrations in Arosa, Switzerland, and the results are compared with those obtained by classical time series (ARIMA) analysis. Copyright © 2010 Elsevier Ltd. All rights reserved.

[Validation of the abbreviated Zarit scales for measuring burden syndrome in the primary caregiver of an elderly patient].

PubMed

Vélez Lopera, Johana María; Berbesí Fernández, Dedsy; Cardona Arango, Doris; Segura Cardona, Angela; Ordóñez Molina, Jaime

2012-07-01

To determine which abbreviated Zarit Scale (ZS) better evaluates the burden of the caregiver of an elderly patient in Medellin, Colombia. Validation study. Primary Care setting in the city of Medellin. Primary caregiver of dependent elderly patients over 65 years old. Sensitivity, specificity, positive predictive value, and negative predictive value for the different abbreviated Zarit scales, plus performing a reliability analysis using the Cronbach Alpha coefficient. The abbreviated scales obtained a sensitivity of between 36.84 and 81.58%, specificity between 95.99 and 100%, positive predictive values between 71.05 and 100%, and negative predictive values of between 91.64 and 97.42%. The scale that better determined caregiver burden in Primary Care was the Bedard Screening scale, with a sensitivity of 81.58%, a specificity of 96.35% and positive and negative predictive values of 75.61% and 97.42%, respectively. Copyright © 2010 Elsevier España, S.L. All rights reserved.

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.

Behavior of respiratory muscle strength in morbidly obese women by using different predictive equations.

PubMed

Pazzianotto-Forti, Eli M; Peixoto-Souza, Fabiana S; Piconi-Mendes, Camila; Rasera-Junior, Irineu; Barbalho-Moulim, Marcela

2012-01-01

Studies on the behavior of respiratory muscle strength (RMS) in morbidly obese patients have found conflicting results. To evaluate RMS in morbidly obese women and to compare the results by using different predictive equations. This is a cross-sectional study that recruited 30 morbidly obese women and a control group of 30 normal-weight women. The subjects underwent anthropometric and maximal respiratory pressure measurement. Visual inspection of the Bland-Altman plots was performed to evaluate the correlation between the different equations, with a p value lower than 0.05 considered as statistically significant. The obese women showed a significant increase in maximal inspiratory pressure (MIP) values (-87.83±21.40 cmH(2)O) compared with normal-weight women (-72±15.23 cmH(2)O) and a significant reduction of MIP (-87.83±21.40 cmH(2)O) according to the values predicted by the EHarik equation (-130.71±11.98 cmH(2)O). Regarding the obtained maximal expiratory pressure (MEP), there were no between-group differences (p>0.05), and no agreeement was observed between obtained and predicted values of MEP and the ENeder and ECosta equations. Inspiratory muscle strength was greater in the morbidly obese subjects. The most appropriate equation for calculating the predicted MIP values for the morbidly obese seems to be Harik-Khan equation. There seem to be similarities between the respiratory muscle strength behavior of morbidly obese and normal-weight women, however, these findings are still inconclusive.

An equation for the prediction of human skin permeability of neutral molecules, ions and ionic species.

PubMed

Zhang, Keda; Abraham, Michael H; Liu, Xiangli

2017-04-15

Experimental values of permeability coefficients, as log K p , of chemical compounds across human skin were collected by carefully screening the literature, and adjusted to 37°C for the effect of temperature. The values of log K p for partially ionized acids and bases were separated into those for their neutral and ionic species, forming a total data set of 247 compounds and species (including 35 ionic species). The obtained log K p values have been regressed against Abraham solute descriptors to yield a correlation equation with R 2 =0.866 and SD=0.432 log units. The equation can provide valid predictions for log K p of neutral molecules, ions and ionic species, with predictive R 2 =0.858 and predictive SD=0.445 log units calculated by the leave-one-out statistics. The predicted log K p values for Na + and Et 4 N + are in good agreement with the observed values. We calculated the values of log K p of ketoprofen as a function of the pH of the donor solution, and found that log K p markedly varies only when ketoprofen is largely ionized. This explains why models that neglect ionization of permeants still yield reasonable statistical results. The effect of skin thickness on log K p was investigated by inclusion of two indicator variables, one for intermediate thickness skin and one for full thickness skin, into the above equation. The newly obtained equations were found to be statistically very close to the above equation. Therefore, the thickness of human skin used makes little difference to the experimental values of log K p . Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling of exposure to carbon monoxide in fires

NASA Technical Reports Server (NTRS)

Cagliostro, D. E.

1980-01-01

A mathematical model is developed to predict carboxyhemoglobin concentrations in regions of the body for short exposures to carbon monoxide levels expected during escape from aircraft fires. The model includes the respiratory and circulatory dynamics of absorption and distribution of carbon monoxide and carboxyhemoglobin. Predictions of carboxyhemoglobin concentrations are compared to experimental values obtained for human exposures to constant high carbon monoxide levels. Predictions are within 20% of experimental values. For short exposure times, transient concentration effects are predicted. The effect of stress is studied and found to increase carboxyhemoglobin levels substantially compared to a rest state.

Validating proposed migration equation and parameters' values as a tool to reproduce and predict 137Cs vertical migration activity in Spanish soils.

PubMed

Olondo, C; Legarda, F; Herranz, M; Idoeta, R

2017-04-01

This paper shows the procedure performed to validate the migration equation and the migration parameters' values presented in a previous paper (Legarda et al., 2011) regarding the migration of 137 Cs in Spanish mainland soils. In this paper, this model validation has been carried out checking experimentally obtained activity concentration values against those predicted by the model. This experimental data come from the measured vertical activity profiles of 8 new sampling points which are located in northern Spain. Before testing predicted values of the model, the uncertainty of those values has been assessed with the appropriate uncertainty analysis. Once establishing the uncertainty of the model, both activity concentration values, experimental versus model predicted ones, have been compared. Model validation has been performed analyzing its accuracy, studying it as a whole and also at different depth intervals. As a result, this model has been validated as a tool to predict 137 Cs behaviour in a Mediterranean environment. Copyright © 2017 Elsevier Ltd. All rights reserved.

Investigation of a liquid-fed water resistojet plume

NASA Technical Reports Server (NTRS)

Manzella, D. H.; Carney, L. M.

1989-01-01

Measurements of mass flux and flow angle were taken throughout the forward flow region of the exhaust of a liquid-fed water resistojet using a quartz crystal microbalance (QCM). The resistojet operated at a mass flow rate of 0.1 g/s with a power input of 330 Watts. Measured values were compared to theoretical predictions obtained by employing a source flow approximation. Excellent agreement between predicted and measured mass flux values was attained; however, this agreement was highly dependent on knowledge of nozzle flow conditions. Measurements of the temperature at which the exhaust condensed on the QCM were obtained as a function of incident mass flux.

Measurement of pH in whole blood by near-infrared spectroscopy

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

Alam, M. Kathleen; Maynard, John D.; Robinson, M. Ries

1999-03-01

Whole blood pH has been determined {ital in vitro} by using near-infrared spectroscopy over the wavelength range of 1500 to 1785 nm with multivariate calibration modeling of the spectral data obtained from two different sample sets. In the first sample set, the pH of whole blood was varied without controlling cell size and oxygen saturation (O{sub 2} Sat) variation. The result was that the red blood cell (RBC) size and O{sub 2} Sat correlated with pH. Although the partial least-squares (PLS) multivariate calibration of these data produced a good pH prediction cross-validation standard error of prediction (CVSEP)=0.046, R{sup 2}=0.982, themore » spectral data were dominated by scattering changes due to changing RBC size that correlated with the pH changes. A second experiment was carried out where the RBC size and O{sub 2} Sat were varied orthogonally to the pH variation. A PLS calibration of the spectral data obtained from these samples produced a pH prediction with an R{sup 2} of 0.954 and a cross-validated standard error of prediction of 0.064 pH units. The robustness of the PLS calibration models was tested by predicting the data obtained from the other sets. The predicted pH values obtained from both data sets yielded R{sup 2} values greater than 0.9 once the data were corrected for differences in hemoglobin concentration. For example, with the use of the calibration produced from the second sample set, the pH values from the first sample set were predicted with an R{sup 2} of 0.92 after the predictions were corrected for bias and slope. It is shown that spectral information specific to pH-induced chemical changes in the hemoglobin molecule is contained within the PLS loading vectors developed for both the first and second data sets. It is this pH specific information that allows the spectra dominated by pH-correlated scattering changes to provide robust pH predictive ability in the uncorrelated data, and visa versa. {copyright} {ital 1999} {ital Society for Applied Spectroscopy}« less

Synchrophasor-Assisted Prediction of Stability/Instability of a Power System

NASA Astrophysics Data System (ADS)

Saha Roy, Biman Kumar; Sinha, Avinash Kumar; Pradhan, Ashok Kumar

2013-05-01

This paper presents a technique for real-time prediction of stability/instability of a power system based on synchrophasor measurements obtained from phasor measurement units (PMUs) at generator buses. For stability assessment the technique makes use of system severity indices developed using bus voltage magnitude obtained from PMUs and generator electrical power. Generator power is computed using system information and PMU information like voltage and current phasors obtained from PMU. System stability/instability is predicted when the indices exceeds a threshold value. A case study is carried out on New England 10-generator, 39-bus system to validate the performance of the technique.

Research on dynamic creep strain and settlement prediction under the subway vibration loading.

PubMed

Luo, Junhui; Miao, Linchang

2016-01-01

This research aims to explore the dynamic characteristics and settlement prediction of soft soil. Accordingly, the dynamic shear modulus formula considering the vibration frequency was utilized and the dynamic triaxial test conducted to verify the validity of the formula. Subsequently, the formula was applied to the dynamic creep strain function, with the factors influencing the improved dynamic creep strain curve of soft soil being analyzed. Meanwhile, the variation law of dynamic stress with sampling depth was obtained through the finite element simulation of subway foundation. Furthermore, the improved dynamic creep strain curve of soil layer was determined based on the dynamic stress. Thereafter, it could to estimate the long-term settlement under subway vibration loading by norms. The results revealed that the dynamic shear modulus formula is straightforward and practical in terms of its application to the vibration frequency. The values predicted using the improved dynamic creep strain formula closed to the experimental values, whilst the estimating settlement closed to the measured values obtained in the field test.

Very-short-term wind power prediction by a hybrid model with single- and multi-step approaches

NASA Astrophysics Data System (ADS)

Mohammed, E.; Wang, S.; Yu, J.

2017-05-01

Very-short-term wind power prediction (VSTWPP) has played an essential role for the operation of electric power systems. This paper aims at improving and applying a hybrid method of VSTWPP based on historical data. The hybrid method is combined by multiple linear regressions and least square (MLR&LS), which is intended for reducing prediction errors. The predicted values are obtained through two sub-processes:1) transform the time-series data of actual wind power into the power ratio, and then predict the power ratio;2) use the predicted power ratio to predict the wind power. Besides, the proposed method can include two prediction approaches: single-step prediction (SSP) and multi-step prediction (MSP). WPP is tested comparatively by auto-regressive moving average (ARMA) model from the predicted values and errors. The validity of the proposed hybrid method is confirmed in terms of error analysis by using probability density function (PDF), mean absolute percent error (MAPE) and means square error (MSE). Meanwhile, comparison of the correlation coefficients between the actual values and the predicted values for different prediction times and window has confirmed that MSP approach by using the hybrid model is the most accurate while comparing to SSP approach and ARMA. The MLR&LS is accurate and promising for solving problems in WPP.

First trimester prediction of maternal glycemic status.

PubMed

Gabbay-Benziv, Rinat; Doyle, Lauren E; Blitzer, Miriam; Baschat, Ahmet A

2015-05-01

To predict gestational diabetes mellitus (GDM) or normoglycemic status using first trimester maternal characteristics. We used data from a prospective cohort study. First trimester maternal characteristics were compared between women with and without GDM. Association of these variables with sugar values at glucose challenge test (GCT) and subsequent GDM was tested to identify key parameters. A predictive algorithm for GDM was developed and receiver operating characteristics (ROC) statistics was used to derive the optimal risk score. We defined normoglycemic state, when GCT and all four sugar values at oral glucose tolerance test, whenever obtained, were normal. Using same statistical approach, we developed an algorithm to predict the normoglycemic state. Maternal age, race, prior GDM, first trimester BMI, and systolic blood pressure (SBP) were all significantly associated with GDM. Age, BMI, and SBP were also associated with GCT values. The logistic regression analysis constructed equation and the calculated risk score yielded sensitivity, specificity, positive predictive value, and negative predictive value of 85%, 62%, 13.8%, and 98.3% for a cut-off value of 0.042, respectively (ROC-AUC - area under the curve 0.819, CI - confidence interval 0.769-0.868). The model constructed for normoglycemia prediction demonstrated lower performance (ROC-AUC 0.707, CI 0.668-0.746). GDM prediction can be achieved during the first trimester encounter by integration of maternal characteristics and basic measurements while normoglycemic status prediction is less effective.

Information-theoretic indices usage for the prediction and calculation of octanol-water partition coefficient.

PubMed

Persona, Marek; Kutarov, Vladimir V; Kats, Boris M; Persona, Andrzej; Marczewska, Barbara

2007-01-01

The paper describes the new prediction method of octanol-water partition coefficient, which is based on molecular graph theory. The results obtained using the new method are well correlated with experimental values. These results were compared with the ones obtained by use of ten other structure correlated methods. The comparison shows that graph theory can be very useful in structure correlation research.

Predictive Performance Assessment: Trait and State Dimensions Should not be Confused

NASA Astrophysics Data System (ADS)

Pattyn, N.; Migeotte, P.-F.; Morais, J.; Cluydts, R.; Soetens, E.; Meeusen, R.; de Schutter, G.; Nederhof, E.; Kolinsky, R.

2008-06-01

One of the major aims of performance investigation is to obtain a measure predicting real-life performance, in order to prevent consequences of a potential decrement. Whereas the predictive validity of such assessment has been extensively described for long-term outcomes, as is the case for testing in selection context, equivalent evidence is lacking regarding the short-term predictive value of cognitive testing, i.e., whether these results reflect real-life performance on an immediately subsequent task. In this series of experiments, we investigated both medium-term and short-term predictive value of psychophysiological testing with regard to real-life performance in two operational settings: military student pilots with regard to their success on an evaluation flight, and special forces candidates with regard to their performance on their training course. Our results showed some relationships between test performance and medium-term outcomes. However, no short-term predictive value could be identified for cognitive testing, despite the fact physiological data showed interesting trends. We recommend a critical distinction between "state" and "trait" dimensions of performance with regard to the predictive value of testing.

Proximate analyses and predicting HHV of chars obtained from cocracking of petroleum vacuum residue with coal, plastics and biomass.

PubMed

Ahmaruzzaman, M

2008-07-01

Higher heating value (HHV) and analysis of chars obtained from cocracking of petroleum vacuum residue (XVR) with coal (SC), biomass (BG, CL) and plastics (PP, PS, BL) are important which define the energy content and determine the clean and efficient use of these chars. The main aim of the present study is to analyze the char obtained from cocracking in terms of their proximate analysis data and determination of the HHV of the chars. The char obtained from XVR+PP cocracking showed a HHV of 32.84 MJ/kg, whereas that from CL cracking showed a HHV of 18.52 MJ/kg. The experimentally determined heating values of the char samples obtained from cocracking have been correlated with the theoretical equation based on proximate analysis data. There exists a variety of correlations for predicting HHV from proximate analysis of fuels. Based upon proximate analysis data, the models were tested. The best results show coefficient of determination (R2) of 0.965 and average absolute and bias error of 3.07% and 0.41%, respectively. The heating values obtained from the model were in good agreement with that obtained by experiment. Proximate analysis of the chars obtained from the cocracking of XVR with coal, biomass and plastics showed that there exists a definite interaction of the reactive species, when they were cocracked together.

Improving the Accuracy of a Heliocentric Potential (HCP) Prediction Model for the Aviation Radiation Dose

NASA Astrophysics Data System (ADS)

Hwang, Junga; Yoon, Kyoung-Won; Jo, Gyeongbok; Noh, Sung-Jun

2016-12-01

The space radiation dose over air routes including polar routes should be carefully considered, especially when space weather shows sudden disturbances such as coronal mass ejections (CMEs), flares, and accompanying solar energetic particle events. We recently established a heliocentric potential (HCP) prediction model for real-time operation of the CARI-6 and CARI-6M programs. Specifically, the HCP value is used as a critical input value in the CARI-6/6M programs, which estimate the aviation route dose based on the effective dose rate. The CARI-6/6M approach is the most widely used technique, and the programs can be obtained from the U.S. Federal Aviation Administration (FAA). However, HCP values are given at a one month delay on the FAA official webpage, which makes it difficult to obtain real-time information on the aviation route dose. In order to overcome this critical limitation regarding the time delay for space weather customers, we developed a HCP prediction model based on sunspot number variations (Hwang et al. 2015). In this paper, we focus on improvements to our HCP prediction model and update it with neutron monitoring data. We found that the most accurate method to derive the HCP value involves (1) real-time daily sunspot assessments, (2) predictions of the daily HCP by our prediction algorithm, and (3) calculations of the resultant daily effective dose rate. Additionally, we also derived the HCP prediction algorithm in this paper by using ground neutron counts. With the compensation stemming from the use of ground neutron count data, the newly developed HCP prediction model was improved.

Comparison between presepsin and procalcitonin in early diagnosis of neonatal sepsis.

PubMed

Iskandar, Agustin; Arthamin, Maimun Z; Indriana, Kristin; Anshory, Muhammad; Hur, Mina; Di Somma, Salvatore

2018-05-09

Neonatal sepsis remains worldwide one of the leading causes of morbidity and mortality in both term and preterm infants. Lower mortality rates are related to timely diagnostic evaluation and prompt initiation of empiric antibiotic therapy. Blood culture, as gold standard examination for sepsis, has several limitations for early diagnosis, so that sepsis biomarkers could play an important role in this regard. This study was aimed to compare the value of the two biomarkers presepsin and procalcitonin in early diagnosis of neonatal sepsis. This was a prospective cross-sectional study performed, in Saiful Anwar General Hospital Malang, Indonesia, in 51 neonates that fulfill the criteria of systemic inflammatory response syndrome (SIRS) with blood culture as diagnostic gold standard for sepsis. At reviewer operating characteristic (ROC) curve analyses, using a presepsin cutoff of 706,5 pg/mL, the obtained area under the curve (AUCs) were: sensitivity = 85.7%, specificity = 68.8%, positive predictive value = 85.7%, negative predictive value = 68.8%, positive likelihood ratio = 2.75, negative likelihood ratio = 0.21, and accuracy = 80.4%. On the other hand, with a procalcitonin cutoff value of 161.33 pg/mL the obtained AUCs showed: sensitivity = 68.6%, specificity = 62.5%, positive predictive value = 80%, negative predictive value = 47.6%, positive likelihood ratio = 1.83, the odds ratio negative = 0.5, and accuracy = 66.7%. In early diagnosis of neonatal sepsis, compared with procalcitonin, presepsin seems to provide better early diagnostic value with consequent possible faster therapeutical decision making and possible positive impact on outcome of neonates.

Theoretical and observational assessments of flare efficiencies.

PubMed

Leahey, D M; Preston, K; Strosher, M

2001-12-01

Flaring of waste gases is a common practice in the processing of hydrocarbon (HC) materials. It is assumed that flaring achieves complete combustion with relatively innocuous byproducts such as CO2 and H2O. However, flaring is rarely successful in the attainment of complete combustion, because entrainment of air into the region of combusting gases restricts flame sizes to less than optimum values. The resulting flames are too small to dissipate the amount of heat associated with 100% combustion efficiency. Equations were employed to estimate flame lengths, areas, and volumes as functions of flare stack exit velocity, stoichiometric mixing ratio, and wind speed. Heats released as part of the combustion process were then estimated from a knowledge of the flame dimensions together with an assumed flame temperature of 1200 K. Combustion efficiencies were subsequently obtained by taking the ratio of estimated actual heat release values to those associated with 100% complete combustion. Results of the calculations showed that combustion efficiencies decreased rapidly as wind speed increased from 1 to 6 m/sec. As wind speeds increased beyond 6 m/sec, combustion efficiencies tended to level off at values between 10 and 15%. Propane and ethane tend to burn more efficiently than do methane or hydrogen sulfide because of their lower stoichiometric mixing ratios. Results of theoretical predictions were compared to nine values of local combustion efficiencies obtained as part of an observational study into flaring activity conducted by the Alberta Research Council (ARC). All values were obtained during wind speed conditions of less than 4 m/sec. There was generally good agreement between predicted and observed values. The mean and standard deviation of observed combustion efficiencies were 68 +/- 7%. Comparable predicted values were 69 +/- 7%.

Use of differential scanning calorimetry to detect canola oil (Brassica napus L.) adulterated with lard stearin.

PubMed

Marikkar, Jalaldeen Mohammed Nazrim; Rana, Sohel

2014-01-01

A study was conducted to detect and quantify lard stearin (LS) content in canola oil (CaO) using differential scanning calorimetry (DSC). Authentic samples of CaO were obtained from a reliable supplier and the adulterant LS were obtained through a fractional crystallization procedure as reported previously. Pure CaO samples spiked with LS in levels ranging from 5 to 15% (w/w) were analyzed using DSC to obtain their cooling and heating profiles. The results showed that samples contaminated with LS at 5% (w/w) level can be detected using characteristic contaminant peaks appearing in the higher temperature regions (0 to 70°C) of the cooling and heating curves. Pearson correlation analysis of LS content against individual DSC parameters of the adulterant peak namely peak temperature, peak area, peak onset temperature indicated that there were strong correlations between these with the LS content of the CaO admixtures. When these three parameters were engaged as variables in the execution of the stepwise regression procedure, predictive models for determination of LS content in CaO were obtained. The predictive models obtained with single DSC parameter had relatively lower coefficient of determination (R(2) value) and higher standard error than the models obtained using two DSC parameters in combination. This study concluded that the predictive models obtained with peak area and peak onset temperature of the adulteration peak would be more accurate for prediction of LS content in CaO based on the highest coefficient of determination (R(2) value) and smallest standard error.

Low-Complexity Lossless and Near-Lossless Data Compression Technique for Multispectral Imagery

NASA Technical Reports Server (NTRS)

Xie, Hua; Klimesh, Matthew A.

2009-01-01

This work extends the lossless data compression technique described in Fast Lossless Compression of Multispectral- Image Data, (NPO-42517) NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26. The original technique was extended to include a near-lossless compression option, allowing substantially smaller compressed file sizes when a small amount of distortion can be tolerated. Near-lossless compression is obtained by including a quantization step prior to encoding of prediction residuals. The original technique uses lossless predictive compression and is designed for use on multispectral imagery. A lossless predictive data compression algorithm compresses a digitized signal one sample at a time as follows: First, a sample value is predicted from previously encoded samples. The difference between the actual sample value and the prediction is called the prediction residual. The prediction residual is encoded into the compressed file. The decompressor can form the same predicted sample and can decode the prediction residual from the compressed file, and so can reconstruct the original sample. A lossless predictive compression algorithm can generally be converted to a near-lossless compression algorithm by quantizing the prediction residuals prior to encoding them. In this case, since the reconstructed sample values will not be identical to the original sample values, the encoder must determine the values that will be reconstructed and use these values for predicting later sample values. The technique described here uses this method, starting with the original technique, to allow near-lossless compression. The extension to allow near-lossless compression adds the ability to achieve much more compression when small amounts of distortion are tolerable, while retaining the low complexity and good overall compression effectiveness of the original algorithm.

[Evaluation of thermal comfort in a student population: predictive value of an integrated index (Fanger's predicted mean value].

PubMed

Catenacci, G; Terzi, R; Marcaletti, G; Tringali, S

1989-01-01

Practical applications and predictive values of a thermal comfort index (Fanger's PRV) were verified on a sample school population (1236 subjects) by studying the relationships between thermal sensations (subjective analysis), determined by means of an individual questionnaire, and the values of thermal comfort index (objective analysis) obtained by calculating the PMV index individually in the subjects under study. In homogeneous conditions of metabolic expenditure rate and thermal impedence from clothing, significant differences were found between the two kinds of analyses. At 22 degrees C mean radiant and operative temperature, the PMV values averaged 0 and the percentage of subjects who experienced thermal comfort did not exceed 60%. The high level of subjects who were dissatisfied with their environmental thermal conditions confirms the doubts regarding the use of the PMV index as a predictive indicator of thermal comfort, especially considering that the negative answers were not homogeneous nor attributable to the small thermal fluctuations (less than 0.5 degree C) measured in the classrooms.

Construction of prediction intervals for Palmer Drought Severity Index using bootstrap

NASA Astrophysics Data System (ADS)

Beyaztas, Ufuk; Bickici Arikan, Bugrayhan; Beyaztas, Beste Hamiye; Kahya, Ercan

2018-04-01

In this study, we propose an approach based on the residual-based bootstrap method to obtain valid prediction intervals using monthly, short-term (three-months) and mid-term (six-months) drought observations. The effects of North Atlantic and Arctic Oscillation indexes on the constructed prediction intervals are also examined. Performance of the proposed approach is evaluated for the Palmer Drought Severity Index (PDSI) obtained from Konya closed basin located in Central Anatolia, Turkey. The finite sample properties of the proposed method are further illustrated by an extensive simulation study. Our results revealed that the proposed approach is capable of producing valid prediction intervals for future PDSI values.

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.

The predicted influence of climate change on lesser prairie-chicken reproductive parameters

USGS Publications Warehouse

Grisham, Blake A.; Boal, Clint W.; Haukos, David A.; Davis, D.; Boydston, Kathy K.; Dixon, Charles; Heck, Willard R.

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Nina events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

The predicted influence of climate change on lesser prairie-chicken reproductive parameters.

PubMed

Grisham, Blake A; Boal, Clint W; Haukos, David A; Davis, Dawn M; Boydston, Kathy K; Dixon, Charles; Heck, Willard R

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001-2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter's linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Niña events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

A Gaussian Processes Technique for Short-term Load Forecasting with Considerations of Uncertainty

NASA Astrophysics Data System (ADS)

Ohmi, Masataro; Mori, Hiroyuki

In this paper, an efficient method is proposed to deal with short-term load forecasting with the Gaussian Processes. Short-term load forecasting plays a key role to smooth power system operation such as economic load dispatching, unit commitment, etc. Recently, the deregulated and competitive power market increases the degree of uncertainty. As a result, it is more important to obtain better prediction results to save the cost. One of the most important aspects is that power system operator needs the upper and lower bounds of the predicted load to deal with the uncertainty while they require more accurate predicted values. The proposed method is based on the Bayes model in which output is expressed in a distribution rather than a point. To realize the model efficiently, this paper proposes the Gaussian Processes that consists of the Bayes linear model and kernel machine to obtain the distribution of the predicted value. The proposed method is successively applied to real data of daily maximum load forecasting.

Rapid monitoring of the fermentation process for Korean traditional rice wine 'Makgeolli' using FT-NIR spectroscopy

NASA Astrophysics Data System (ADS)

Kim, Dae-Yong; Cho, Byoung-Kwan

2015-11-01

The quality parameters of the Korean traditional rice wine "Makgeolli" were monitored using Fourier transform near-infrared (FT-NIR) spectroscopy with multivariate statistical analysis (MSA) during fermentation. Alcohol, reducing sugar, and titratable acid were the parameters assessed to determine the quality index of fermentation substrates and products. The acquired spectra were analyzed with partial least squares regression (PLSR). The best prediction model for alcohol was obtained with maximum normalization, showing a coefficient of determination (Rp2) of 0.973 and a standard error of prediction (SEP) of 0.760%. In addition, the best prediction model for reducing sugar was obtained with no data preprocessing, with a Rp2 value of 0.945 and a SEP of 1.233%. The prediction of titratable acidity was best with mean normalization, showing a Rp2 value of 0.882 and a SEP of 0.045%. These results demonstrate that FT-NIR spectroscopy can be used for rapid measurements of quality parameters during Makgeolli fermentation.

Correcting the anion gap for hypoalbuminaemia does not improve detection of hyperlactataemia

PubMed Central

Dinh, C H; Ng, R; Grandinetti, A; Joffe, A; Chow, D C

2006-01-01

Background An elevated lactate level reflects impaired tissue oxygenation and is a predictor of mortality. Studies have shown that the anion gap is inadequate as a screen for hyperlactataemia, particularly in critically ill and trauma patients. A proposed explanation for the anion gap's poor sensitivity and specificity in detecting hyperlactataemia is that the serum albumin is frequently low. This study therefore, sought to compare the predictive values of the anion gap and the anion gap corrected for albumin (cAG) as an indicator of hyperlactataemia as defined by a lactate ⩾2.5 mmol/l. Methods A retrospective review of 639 sets of laboratory values from a tertiary care hospital. Patients' laboratory results were included in the study if serum chemistries and lactate were drawn consecutively. The sensitivity, specificity, and predictive values were obtained. A receiver operator characteristics curve (ROC) was drawn and the area under the curve (AUC) was calculated. Results An anion gap ⩾12 provided a sensitivity, specificity, positive predictive value, and negative predictive value of 39%, 89%, 79%, and 58%, respectively, and a cAG ⩾12 provided a sensitivity, specificity, positive predictive value, and negative predictive value of 75%, 59%, 66%, and 69%, respectively. The ROC curves between anion gap and cAG as a predictor of hyperlactataemia were almost identical. The AUC was 0.757 and 0.750, respectively. Conclusions The sensitivities, specificities, and predictive values of the anion gap and cAG were inadequate in predicting the presence of hyperlactataemia. The cAG provides no additional advantage over the anion gap in the detection of hyperlactataemia. PMID:16858097

Hadronic Leading Order Contribution to the Muon g-2

NASA Astrophysics Data System (ADS)

Nomura, Daisuke

2018-05-01

We calculate the Standard Model (SM) prediction for the muon anomalous magnetic moment. By using the latest experimental data for e+e- → hadrons as input to dispersive integrals, we obtain the values of the leading order (LO) and the next-to-leading-order (NLO) hadronic vacuum polarisation contributions as ahad, LO VPμ = (693:27 ± 2:46) × 10-10 and ahad, NLO VP μ = (_9.82 ± 0:04) × 1010-10, respectively. When combined with other contributions to the SM prediction, we obtain aμ(SM) = (11659182:05 ± 3.56) × 10-10; which is deviated from the experimental value by Δaμ(exp) _ aμ(SM) = (27.05 ± 7.26) × 10-10. This means that there is a 3.7 σ discrepancy between the experimental value and the SM prediction. We also discuss another closely related quantity, the running QED coupling at the Z-pole, α(M2 Z). By using the same e+e- → hadrons data as input, our result for the 5-flavour quark contribution to the running QED coupling at the Z pole is Δ(5)had(M2 Z) = (276.11 ± 1.11) × 10-4, from which we obtain Δ(M2 Z) = 128.946 ± 0.015.

Changes in the yield of chlorophyll a from dissolved available inorganic nitrogen after an enrichment event—applications for predicting eutrophication in coastal waters

NASA Astrophysics Data System (ADS)

Edwards, V. R.; Tett, P.; Jones, K. J.

2003-11-01

An understanding of the dynamic relationship between nitrogen supply and the formation of phytoplankton biomass is important in predicting and avoiding marine eutrophication. This relationship can be expressed as the short-term yield q of chlorophyll from dissolved available inorganic nitrogen (DAIN), the sum of nitrate, nitrite and ammonium. This paper communicates the results of a continuous culture nitrate enrichment experiment undertaken to investigate the cumulative yield of chlorophyll from DAIN ( q). The purposes of the study were: to acquire a better understanding of the relationship between chlorophyll formation and DAIN; to obtain values that could be used in models for predicting eutrophication. The results of a time series experiment carried out using microplankton (all organisms <200 μm in size) indicate that the parameter q does not have a single value but is affected by the ecophysiological response of phytoplankton to changing nutrient status after an enrichment event. It is also dependent on changes in the allocation of nitrogen between autotrophs and heterotrophs. The value of yield obtained at the height of the bloom can be represented by q (max) (2.35 μg chl (μmol N) -1). The post-bloom, steady state value of q can be represented by qeq (0.95 μg chl (μmol N) -1). The microcosm steady state yield was not significantly different from the median value obtained from synoptic studies of Scottish west coast waters. It is proposed that qeq is the most appropriate value for assessing the general potential for eutrophication resulting from continuous nutrient enrichment into coastal waters. It is further proposed that q (max) be used for cases of sporadic enrichment and where a short burst of unrestricted growth may be detrimental.

Comparison between genetic parameters of cheese yield and nutrient recovery or whey loss traits measured from individual model cheese-making methods or predicted from unprocessed bovine milk samples using Fourier-transform infrared spectroscopy.

PubMed

Bittante, G; Ferragina, A; Cipolat-Gotet, C; Cecchinato, A

2014-10-01

Cheese yield is an important technological trait in the dairy industry. The aim of this study was to infer the genetic parameters of some cheese yield-related traits predicted using Fourier-transform infrared (FTIR) spectral analysis and compare the results with those obtained using an individual model cheese-producing procedure. A total of 1,264 model cheeses were produced using 1,500-mL milk samples collected from individual Brown Swiss cows, and individual measurements were taken for 10 traits: 3 cheese yield traits (fresh curd, curd total solids, and curd water as a percent of the weight of the processed milk), 4 milk nutrient recovery traits (fat, protein, total solids, and energy of the curd as a percent of the same nutrient in the processed milk), and 3 daily cheese production traits per cow (fresh curd, total solids, and water weight of the curd). Each unprocessed milk sample was analyzed using a MilkoScan FT6000 (Foss, Hillerød, Denmark) over the spectral range, from 5,000 to 900 wavenumber × cm(-1). The FTIR spectrum-based prediction models for the previously mentioned traits were developed using modified partial least-square regression. Cross-validation of the whole data set yielded coefficients of determination between the predicted and measured values in cross-validation of 0.65 to 0.95 for all traits, except for the recovery of fat (0.41). A 3-fold external validation was also used, in which the available data were partitioned into 2 subsets: a training set (one-third of the herds) and a testing set (two-thirds). The training set was used to develop calibration equations, whereas the testing subsets were used for external validation of the calibration equations and to estimate the heritabilities and genetic correlations of the measured and FTIR-predicted phenotypes. The coefficients of determination between the predicted and measured values in cross-validation results obtained from the training sets were very similar to those obtained from the whole data set, but the coefficient of determination of validation values for the external validation sets were much lower for all traits (0.30 to 0.73), and particularly for fat recovery (0.05 to 0.18), for the training sets compared with the full data set. For each testing subset, the (co)variance components for the measured and FTIR-predicted phenotypes were estimated using bivariate Bayesian analyses and linear models. The intraherd heritabilities for the predicted traits obtained from our internal cross-validation using the whole data set ranged from 0.085 for daily yield of curd solids to 0.576 for protein recovery, and were similar to those obtained from the measured traits (0.079 to 0.586, respectively). The heritabilities estimated from the testing data set used for external validation were more variable but similar (on average) to the corresponding values obtained from the whole data set. Moreover, the genetic correlations between the predicted and measured traits were high in general (0.791 to 0.996), and they were always higher than the corresponding phenotypic correlations (0.383 to 0.995), especially for the external validation subset. In conclusion, we herein report that application of the cross-validation technique to the whole data set tended to overestimate the predictive ability of FTIR spectra, give more precise phenotypic predictions than the calibrations obtained using smaller data sets, and yield genetic correlations similar to those obtained from the measured traits. Collectively, our findings indicate that FTIR predictions have the potential to be used as indicator traits for the rapid and inexpensive selection of dairy populations for improvement of cheese yield, milk nutrient recovery in curd, and daily cheese production per cow. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Prediction of kinase-inhibitor binding affinity using energetic parameters

PubMed Central

Usha, Singaravelu; Selvaraj, Samuel

2016-01-01

The combination of physicochemical properties and energetic parameters derived from protein-ligand complexes play a vital role in determining the biological activity of a molecule. In the present work, protein-ligand interaction energy along with logP values was used to predict the experimental log (IC50) values of 25 different kinase-inhibitors using multiple regressions which gave a correlation coefficient of 0.93. The regression equation obtained was tested on 93 kinase-inhibitor complexes and an average deviation of 0.92 from the experimental log IC50 values was shown. The same set of descriptors was used to predict binding affinities for a test set of five individual kinase families, with correlation values > 0.9. We show that the protein-ligand interaction energies and partition coefficient values form the major deterministic factors for binding affinity of the ligand for its receptor. PMID:28149052

Model for predicting peak expiratory flow rate of Nigerian workers in a cement factory in Itori, Ogun State, Nigeria.

PubMed

Ismaila, Salami Olasunkanmi; Akanbi, Olusegun Gabriel; Olaoniye, Wasiu

2015-01-01

The main aim of the study was to propose a model for predicting the peak expiratory flow rate (PEFR) of Nigerian workers in a cement factory. Sixty randomly selected non-smoker and healthy workers (30 in production sections, 30 in the administrative section of the factory) participated in the study. Their physical characteristics and PEFR were measured. Multiple correlations using SPSS version 16.0 were performed on the data. The values of PEFR, using the obtained model, were compared with the measured values using a two-tailed t test. There were positive correlations among age, height and PEFR. A prediction equation for PEFR based on age, height, weight and years of exposure (experience) was obtained with R² = .843 (p < 0.001). The developed model will be useful for the management in determining PEFR of workers in the cement industry for possible medical attention.

Organic carbonates: experiment and ab initio calculations for prediction of thermochemical properties.

PubMed

Verevkin, Sergey P; Emel'yanenko, Vladimir N; Kozlova, Svetlana A

2008-10-23

This work has been undertaken in order to obtain data on thermodynamic properties of organic carbonates and to revise the group-additivity values necessary for predicting their standard enthalpies of formation and enthalpies of vaporization. The standard molar enthalpies of formation of dibenzyl carbonate, tert-butyl phenyl carbonate, and diphenyl carbonate were measured using combustion calorimetry. Molar enthalpies of vaporization of these compounds were obtained from the temperature dependence of the vapor pressure measured by the transpiration method. Molar enthalpy of sublimation of diphenyl carbonate was measured in the same way. Ab initio calculations of molar enthalpies of formation of organic carbonates have been performed using the G3MP2 method, and results are in excellent agreement with the available experiment. Then the group-contribution method has been developed to predict values of the enthalpies of formation and enthalpies of vaporization of organic carbonates.

Sampling the Airway: Improving the Predictive and Toxicological Value of Bronchoalveolar Lavage

EPA Science Inventory

Bronchoalveolar lavage (BAL) is a relatively simple technique to obtain biological material in the form of BAL fluid (BALF) from airways of humans and laboratory animals. Numerous predictive biomarkers of pulmonary injury and diseases can be detected in BALF which aid in diagnosi...

[ETAP: A smoking scale for Primary Health Care].

PubMed

González Romero, Pilar María; Cuevas Fernández, Francisco Javier; Marcelino Rodríguez, Itahisa; Rodríguez Pérez, María Del Cristo; Cabrera de León, Antonio; Aguirre-Jaime, Armando

2016-05-01

To obtain a scale of tobacco exposure to address smoking cessation. Follow-up of a cohort. Scale validation. Primary Care Research Unit. Tenerife. A total of 6729 participants from the "CDC de Canarias" cohort. A scale was constructed under the assumption that the time of exposure to tobacco is the key factor to express accumulated risk. Discriminant validity was tested on prevalent cases of acute myocardial infarction (AMI; n=171), and its best cut-off for preventive screening was obtained. Its predictive validity was tested with incident cases of AMI (n=46), comparing the predictive power with markers (age, sex) and classic risk factors of AMI (hypertension, diabetes, dyslipidaemia), including the pack-years index (PYI). The scale obtained was the sum of three times the years that they had smoked plus years exposed to smoking at home and at work. The frequency of AMI increased with the values of the scale, with the value 20 years of exposure being the most appropriate cut-off for preventive action, as it provided adequate predictive values for incident AMI. The scale surpassed PYI in predicting AMI, and competed with the known markers and risk factors. The proposed scale allows a valid measurement of exposure to smoking and provides a useful and simple approach that can help promote a willingness to change, as well as prevention. It still needs to demonstrate its validity, taking as reference other problems associated with smoking. Copyright © 2015 Elsevier España, S.L.U. All rights reserved.

In-situ intestinal rat perfusions for human Fabs prediction and BCS permeability class determination: Investigation of the single-pass vs. the Doluisio experimental approaches.

PubMed

Lozoya-Agullo, Isabel; Zur, Moran; Wolk, Omri; Beig, Avital; González-Álvarez, Isabel; González-Álvarez, Marta; Merino-Sanjuán, Matilde; Bermejo, Marival; Dahan, Arik

2015-03-01

Intestinal drug permeability has been recognized as a critical determinant of the fraction dose absorbed, with direct influence on bioavailability, bioequivalence and biowaiver. The purpose of this research was to compare intestinal permeability values obtained by two different intestinal rat perfusion methods: the single-pass intestinal perfusion (SPIP) model and the Doluisio (closed-loop) rat perfusion method. A list of 15 model drugs with different permeability characteristics (low, moderate, and high, as well as passively and actively absorbed) was constructed. We assessed the rat intestinal permeability of these 15 model drugs in both SPIP and the Doluisio methods, and evaluated the correlation between them. We then evaluated the ability of each of these methods to predict the fraction dose absorbed (Fabs) in humans, and to assign the correct BCS permeability class membership. Excellent correlation was obtained between the two experimental methods (r(2)=0.93). An excellent correlation was also shown between literature Fabs values and the predictions made by both rat perfusion techniques. Similar BCS permeability class membership was designated by literature data and by both SPIP and Doluisio methods for all compounds. In conclusion, the SPIP model and the Doluisio (closed-loop) rat perfusion method are both equally useful for obtaining intestinal permeability values that can be used for Fabs prediction and BCS classification. Copyright © 2015 Elsevier B.V. All rights reserved.

Grand European and Asian-Pacific multi-model seasonal forecasts: maximization of skill and of potential economical value to end-users

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Felice, Matteo De; Catalano, Franco; Lee, June-Yi; Wang, Bin; Lee, Doo Young; Yoo, Jin-Ho; Weisheimer, Antije

2018-04-01

Multi-model ensembles (MMEs) are powerful tools in dynamical climate prediction as they account for the overconfidence and the uncertainties related to single-model ensembles. Previous works suggested that the potential benefit that can be expected by using a MME amplifies with the increase of the independence of the contributing Seasonal Prediction Systems. In this work we combine the two MME Seasonal Prediction Systems (SPSs) independently developed by the European (ENSEMBLES) and by the Asian-Pacific (APCC/CliPAS) communities. To this aim, all the possible multi-model combinations obtained by putting together the 5 models from ENSEMBLES and the 11 models from APCC/CliPAS have been evaluated. The grand ENSEMBLES-APCC/CliPAS MME enhances significantly the skill in predicting 2m temperature and precipitation compared to previous estimates from the contributing MMEs. Our results show that, in general, the better combinations of SPSs are obtained by mixing ENSEMBLES and APCC/CliPAS models and that only a limited number of SPSs is required to obtain the maximum performance. The number and selection of models that perform better is usually different depending on the region/phenomenon under consideration so that all models are useful in some cases. It is shown that the incremental performance contribution tends to be higher when adding one model from ENSEMBLES to APCC/CliPAS MMEs and vice versa, confirming that the benefit of using MMEs amplifies with the increase of the independence the contributing models. To verify the above results for a real world application, the Grand ENSEMBLES-APCC/CliPAS MME is used to predict retrospective energy demand over Italy as provided by TERNA (Italian Transmission System Operator) for the period 1990-2007. The results demonstrate the useful application of MME seasonal predictions for energy demand forecasting over Italy. It is shown a significant enhancement of the potential economic value of forecasting energy demand when using the better combinations from the Grand MME by comparison to the maximum value obtained from the better combinations of each of the two contributing MMEs. The above results demonstrate for the first time the potential of the Grand MME to significantly contribute in obtaining useful predictions at the seasonal time-scale.

Grand European and Asian-Pacific multi-model seasonal forecasts: maximization of skill and of potential economical value to end-users

NASA Astrophysics Data System (ADS)

Alessandri, A.; De Felice, M.; Catalano, F.; Lee, J. Y.; Wang, B.; Lee, D. Y.; Yoo, J. H.; Weisheimer, A.

2017-12-01

By initiating a novel cooperation between the European and the Asian-Pacific climate-prediction communities, this work demonstrates the potential of gathering together their Multi-Model Ensembles (MMEs) to obtain useful climate predictions at seasonal time-scale.MMEs are powerful tools in dynamical climate prediction as they account for the overconfidence and the uncertainties related to single-model ensembles and increasing benefit is expected with the increase of the independence of the contributing Seasonal Prediction Systems (SPSs). In this work we combine the two MME SPSs independently developed by the European (ENSEMBLES) and by the Asian-Pacific (APCC/CliPAS) communities by establishing an unprecedented partnerships. To this aim, all the possible MME combinations obtained by putting together the 5 models from ENSEMBLES and the 11 models from APCC/CliPAS have been evaluated. The Grand ENSEMBLES-APCC/CliPAS MME enhances significantly the skill in predicting 2m temperature and precipitation. Our results show that, in general, the better combinations of SPSs are obtained by mixing ENSEMBLES and APCC/CliPAS models and that only a limited number of SPSs is required to obtain the maximum performance. The selection of models that perform better is usually different depending on the region/phenomenon under consideration so that all models are useful in some cases. It is shown that the incremental performance contribution tends to be higher when adding one model from ENSEMBLES to APCC/CliPAS MMEs and vice versa, confirming that the benefit of using MMEs amplifies with the increase of the independence the contributing models.To verify the above results for a real world application, the Grand MME is used to predict energy demand over Italy as provided by TERNA (Italian Transmission System Operator) for the period 1990-2007. The results demonstrate the useful application of MME seasonal predictions for energy demand forecasting over Italy. It is shown a significant enhancement of the potential economic value of forecasting energy demand when using the better combinations from the Grand MME by comparison to the maximum value obtained from the better combinations of each of the two contributing MMEs. Above results are discussed in a Clim Dyn paper (Alessandri et al., 2017; doi:10.1007/s00382-016-3372-4).

Salient value similarity, social trust, and attitudes toward wildland fire management strategies

Treesearch

Jerry J. Vaske; James D. Absher; Alan D. Bright

2007-01-01

Using the salient value similarity (SVS) model, we predicted that social trust mediated the relationship between SVS and attitudes toward prescribed burns and mechanical thinning. Data were obtained from a mail survey (n = 532) of Colorado residents living in the wildland-urban interface. Results indicated that respondents shared the same values as U...

Use of Landsat data to predict the trophic state of Minnesota lakes

NASA Technical Reports Server (NTRS)

Lillesand, T. M.; Johnson, W. L.; Deuell, R. L.; Lindstrom, O. M.; Meisner, D. E.

1983-01-01

Near-concurrent Landsat Multispectral Scanner (MSS) and ground data were obtained for 60 lakes distributed in two Landsat scene areas. The ground data included measurement of secchi disk depth, chlorophyll-a, total phosphorous, turbidity, color, and total nitrogen, as well as Carlson Trophic State Index (TSI) values derived from the first three parameters. The Landsat data best correlated with the TSI values. Prediction models were developed to classify some 100 'test' lakes appearing in the two analysis scenes on the basis of TSI estimates. Clouds, wind, poor image data, small lake size, and shallow lake depth caused some problems in lake TSI prediction. Overall, however, the Landsat-predicted TSI estimates were judged to be very reliable for the secchi-derived TSI estimation, moderately reliable for prediction of the chlorophyll-a TSI, and unreliable for the phosphorous value. Numerous Landsat data extraction procedures were compared, and the success of the Landsat TSI prediction models was a strong function of the procedure employed.

Estimating the Accuracy of the Chedoke-McMaster Stroke Assessment Predictive Equations for Stroke Rehabilitation.

PubMed

Dang, Mia; Ramsaran, Kalinda D; Street, Melissa E; Syed, S Noreen; Barclay-Goddard, Ruth; Stratford, Paul W; Miller, Patricia A

2011-01-01

To estimate the predictive accuracy and clinical usefulness of the Chedoke-McMaster Stroke Assessment (CMSA) predictive equations. A longitudinal prognostic study using historical data obtained from 104 patients admitted post cerebrovascular accident was undertaken. Data were abstracted for all patients undergoing rehabilitation post stroke who also had documented admission and discharge CMSA scores. Published predictive equations were used to determine predicted outcomes. To determine the accuracy and clinical usefulness of the predictive model, shrinkage coefficients and predictions with 95% confidence bands were calculated. Complete data were available for 74 patients with a mean age of 65.3±12.4 years. The shrinkage values for the six Impairment Inventory (II) dimensions varied from -0.05 to 0.09; the shrinkage value for the Activity Inventory (AI) was 0.21. The error associated with predictive values was greater than ±1.5 stages for the II dimensions and greater than ±24 points for the AI. This study shows that the large error associated with the predictions (as defined by the confidence band) for the CMSA II and AI limits their clinical usefulness as a predictive measure. Further research to establish predictive models using alternative statistical procedures is warranted.

A new threshold of apparent diffusion coefficient values in white matter after successful tissue plasminogen activator treatment for acute brain ischemia.

PubMed

Sato, Atsushi; Shimizu, Yusaku; Koyama, Junichi; Hongo, Kazuhiro

2017-06-01

Tissue plasminogen activator (tPA) is effective for the treatment of acute brain ischemia, but may trigger fatal brain edema or hemorrhage if the brain ischemia results in a large infarct. Herein, we attempted to predict the extent of infarcts by determining the optimal threshold of ADC values on DWI that predictively distinguishes between infarct and reversible areas, and by reconstructing color-coded images based on this threshold. The study subjects consisted of 36 patients with acute brain ischemia in whom MRA had confirmed reopening of the occluded arteries in a short time (mean: 99min) after tPA treatment. We measured the apparetnt diffusion coefficient (ADC) values in several small regions of interest over the white matter within high-intensity areas on the initial diffusion weighted image (DWI); then, by comparing the findings to the follow-up images, we obtained the optimal threshold of ADC values using receiver-operating characteristic analysis. The threshold obtained (583×10 -6 m 2 /s) was lower than those previously reported; this threshold could distinguish between infarct and reversible areas with considerable accuracy (sensitivity: 0.87, specificity: 0.94). The threshold obtained and the reconstructed images were predictive of the final radiological result of tPA treatment, and this threshold may be helpful in determining the appropriate management of patients with acute brain ischemia. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Assessment of inhibitory effects on major human cytochrome P450 enzymes by spasmolytics used in the treatment of overactive bladder syndrome.

PubMed

Dahlinger, Dominik; Aslan, Sevinc; Pietsch, Markus; Frechen, Sebastian; Fuhr, Uwe

2017-07-01

The objective of this study was to examine the inhibitory potential of darifenacin, fesoterodine, oxybutynin, propiverine, solifenacin, tolterodine and trospium chloride on the seven major human cytochrome P450 enzymes (CYP) by using a standardized and validated seven-in-one cytochrome P450 cocktail inhibition assay. An in vitro cocktail of seven highly selective probe substrates was incubated with human liver microsomes and varying concentrations of the seven test compounds. The major metabolites of the probe substrates were simultaneously analysed using a validated liquid chromatography tandem mass spectrometry (LC-MS/MS) method. Enzyme kinetics were estimated by determining IC 50 and K i values via nonlinear regression. Obtained K i values were used for predictions of potential clinical impact of the inhibition using a static mechanistic prediction model. In this study, 49 IC 50 experiments were conducted. In six cases, IC 50 values lower than the calculated threshold for drug-drug interactions (DDIs) in the gut wall were observed. In these cases, no increase in inhibition was determined after a 30 min preincubation. Considering a typical dosing regimen and applying the obtained K i values of 0.72 µM (darifenacin, 15 mg daily) and 7.2 µM [propiverine, 30 mg daily, immediate release (IR)] for the inhibition of CYP2D6 yielded a predicted 1.9-fold and 1.4-fold increase in the area under the curve (AUC) of debrisoquine (CYP2D6 substrate), respectively. Due to the inhibition of the particular intestinal CYP3A4, the obtained K i values of 14 µM of propiverine (30 mg daily, IR) resulted in a predicted doubling of the AUC for midazolam (CYP3A4 substrate). In vitro / in vivo extrapolation based on pharmacokinetic data and the conducted screening experiments yielded similar effects of darifenacin on CYP2D6 and propiverine on CYP3A4 as obtained in separately conducted in vivo DDI studies. As a novel finding, propiverine was identified to potentially inhibit CYP2D6 at clinically occurring concentrations.

Assessment of inhibitory effects on major human cytochrome P450 enzymes by spasmolytics used in the treatment of overactive bladder syndrome

PubMed Central

Dahlinger, Dominik; Aslan, Sevinc; Pietsch, Markus; Frechen, Sebastian; Fuhr, Uwe

2017-01-01

Background: The objective of this study was to examine the inhibitory potential of darifenacin, fesoterodine, oxybutynin, propiverine, solifenacin, tolterodine and trospium chloride on the seven major human cytochrome P450 enzymes (CYP) by using a standardized and validated seven-in-one cytochrome P450 cocktail inhibition assay. Methods: An in vitro cocktail of seven highly selective probe substrates was incubated with human liver microsomes and varying concentrations of the seven test compounds. The major metabolites of the probe substrates were simultaneously analysed using a validated liquid chromatography tandem mass spectrometry (LC-MS/MS) method. Enzyme kinetics were estimated by determining IC50 and Ki values via nonlinear regression. Obtained Ki values were used for predictions of potential clinical impact of the inhibition using a static mechanistic prediction model. Results: In this study, 49 IC50 experiments were conducted. In six cases, IC50 values lower than the calculated threshold for drug–drug interactions (DDIs) in the gut wall were observed. In these cases, no increase in inhibition was determined after a 30 min preincubation. Considering a typical dosing regimen and applying the obtained Ki values of 0.72 µM (darifenacin, 15 mg daily) and 7.2 µM [propiverine, 30 mg daily, immediate release (IR)] for the inhibition of CYP2D6 yielded a predicted 1.9-fold and 1.4-fold increase in the area under the curve (AUC) of debrisoquine (CYP2D6 substrate), respectively. Due to the inhibition of the particular intestinal CYP3A4, the obtained Ki values of 14 µM of propiverine (30 mg daily, IR) resulted in a predicted doubling of the AUC for midazolam (CYP3A4 substrate). Conclusions: In vitro/in vivo extrapolation based on pharmacokinetic data and the conducted screening experiments yielded similar effects of darifenacin on CYP2D6 and propiverine on CYP3A4 as obtained in separately conducted in vivo DDI studies. As a novel finding, propiverine was identified to potentially inhibit CYP2D6 at clinically occurring concentrations. PMID:28747995

Prediction models for CO2 emission in Malaysia using best subsets regression and multi-linear regression

NASA Astrophysics Data System (ADS)

Tan, C. H.; Matjafri, M. Z.; Lim, H. S.

2015-10-01

This paper presents the prediction models which analyze and compute the CO2 emission in Malaysia. Each prediction model for CO2 emission will be analyzed based on three main groups which is transportation, electricity and heat production as well as residential buildings and commercial and public services. The prediction models were generated using data obtained from World Bank Open Data. Best subset method will be used to remove irrelevant data and followed by multi linear regression to produce the prediction models. From the results, high R-square (prediction) value was obtained and this implies that the models are reliable to predict the CO2 emission by using specific data. In addition, the CO2 emissions from these three groups are forecasted using trend analysis plots for observation purpose.

Predicting charmonium and bottomonium spectra with a quark harmonic oscillator

NASA Technical Reports Server (NTRS)

Norbury, J. W.; Badavi, F. F.; Townsend, L. W.

1986-01-01

The nonrelativistic quark model is applied to heavy (nonrelativistic) meson (two-body) systems to obtain sufficiently accurate predictions of the spin-averaged mass levels of the charmonium and bottomonium spectra as an example of the three-dimensional harmonic oscillator. The present calculations do not include any spin dependence, but rather, mass values are averaged for different spins. Results for a charmed quark mass value of 1500 MeV/c-squared show that the simple harmonic oscillator model provides good agreement with experimental values for 3P states, and adequate agreement for the 3S1 states.

Predictive modeling of surimi cake shelf life at different storage temperatures

NASA Astrophysics Data System (ADS)

Wang, Yatong; Hou, Yanhua; Wang, Quanfu; Cui, Bingqing; Zhang, Xiangyu; Li, Xuepeng; Li, Yujin; Liu, Yuanping

2017-04-01

The Arrhenius model of the shelf life prediction which based on the TBARS index was established in this study. The results showed that the significant changed of AV, POV, COV and TBARS with temperature increased, and the reaction rate constants k was obtained by the first order reaction kinetics model. Then the secondary model fitting was based on the Arrhenius equation. There was the optimal fitting accuracy of TBARS in the first and the secondary model fitting (R2≥0.95). The verification test indicated that the relative error between the shelf life model prediction value and actual value was within ±10%, suggesting the model could predict the shelf life of surimi cake.

Expert System Diagnosis of Cataract Eyes Using Fuzzy Mamdani Method

NASA Astrophysics Data System (ADS)

Santosa, I.; Romla, L.; Herawati, S.

2018-01-01

Cataracts are eye diseases characterized by cloudy or opacity of the lens of the eye by changing the colour of black into grey-white which slowly continues to grow and develop without feeling pain and pain that can cause blindness in human vision. Therefore, researchers make an expert system of cataract eye disease diagnosis by using Fuzzy Mamdani and how to care. The fuzzy method can convert the crisp value to linguistic value by fuzzification and includes in the rule. So this system produces an application program that can help the public in knowing cataract eye disease and how to care based on the symptoms suffered. From the results of the design implementation and testing of expert system applications to diagnose eye disease cataracts, it can be concluded that from a trial of 50 cases of data, obtained test results accuracy between system predictions with expert predictions obtained a value of 78% truth.

Analysis and prediction of operating vehicle load effects on Highway bridges under the weight charge policy

NASA Astrophysics Data System (ADS)

Huang, Haiyun; Zhang, Junping; Li, Yonghe

2018-05-01

Under the weight charge policy, the weigh in motion data at a toll station on the Jing-Zhu Expressway were collected. The statistic analysis of vehicle load data was carried out. For calculating the operating vehicle load effects on bridges, by Monte Carlo method used to generate random traffic flow and influence line loading method, the maximum bending moment effect of simple supported beams were obtained. The extreme value I distribution and normal distribution were used to simulate the distribution of the maximum bending moment effect. By the extrapolation of Rice formula and the extreme value I distribution, the predicted values of the maximum load effects were obtained. By comparing with vehicle load effect according to current specification, some references were provided for the management of the operating vehicles and the revision of the bridge specifications.

Effect of initial phase on error in electron energy obtained using paraxial approximation for a focused laser pulse in vacuum

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

Singh, Kunwar Pal, E-mail: k-psingh@yahoo.com; Department of Physics, Shri Venkateshwara University, Gajraula, Amroha, Uttar Pradesh 244236; Arya, Rashmi

2015-09-14

We have investigated the effect of initial phase on error in electron energy obtained using paraxial approximation to study electron acceleration by a focused laser pulse in vacuum using a three dimensional test-particle simulation code. The error is obtained by comparing the energy of the electron for paraxial approximation and seventh-order correction description of the fields of Gaussian laser. The paraxial approximation predicts wrong laser divergence and wrong electron escape time from the pulse which leads to prediction of higher energy. The error shows strong phase dependence for the electrons lying along the axis of the laser for linearly polarizedmore » laser pulse. The relative error may be significant for some specific values of initial phase even at moderate values of laser spot sizes. The error does not show initial phase dependence for a circularly laser pulse.« less

Keratometry obtained by corneal mapping versus the IOLMaster in the prediction of postoperative refraction in routine cataract surgery.

PubMed

Dulku, Simon; Smith, Henry B; Antcliff, Richard J

2013-01-01

To establish whether simulated keratometry values obtained by corneal mapping (videokeratography) would provide a superior refractive outcome to those obtained by Zeiss IOLMaster (partial coherence interferometry) in routine cataract surgery. Prospective, non-randomized, single-surgeon study set at the The Royal United Hospital, Bath, UK, District General Hospital. Thirty-three patients undergoing routine cataract surgery in the absence of significant ocular comorbidity. Conventional biometry was recorded using the Zeiss IOLMaster. Postoperative refraction was calculated using the SRK/T formula and the most appropriate power of lens implanted. Preoperative keratometry values were also obtained using Humphrey Instruments Atlas Version A6 corneal mapping. Achieved refraction was compared with predicted refraction for the two methods of keratometry after the A-constants were optimized to obtain a mean arithmetic error of zero dioptres for each device. The mean absolute prediction error was 0.39 dioptres (standard deviation 0.29) for IOLMaster and 0.48 dioptres (standard deviation 0.31) for corneal mapping (P = 0.0015). Keratometry readings between the devices were highly correlated by Spearman correlation (0.97). The Bland-Altman plot demonstrated close agreement between keratometers, with a bias of 0.0079 dioptres and 95% limits of agreement of -0.48-0.49 dioptres. The IOLMaster was superior to Humphrey Atlas A6 corneal mapping in the prediction of postoperative refraction. This difference could not have been predicted from the keratometry readings alone. When comparing biometry devices, close agreement between readings should not be considered a substitute for actual postoperative refraction data. © 2012 The Authors. Clinical and Experimental Ophthalmology © 2012 Royal Australian and New Zealand College of Ophthalmologists.

Communication: Limitations of the stochastic quasi-steady-state approximation in open biochemical reaction networks

NASA Astrophysics Data System (ADS)

Thomas, Philipp; Straube, Arthur V.; Grima, Ramon

2011-11-01

It is commonly believed that, whenever timescale separation holds, the predictions of reduced chemical master equations obtained using the stochastic quasi-steady-state approximation are in very good agreement with the predictions of the full master equations. We use the linear noise approximation to obtain a simple formula for the relative error between the predictions of the two master equations for the Michaelis-Menten reaction with substrate input. The reduced approach is predicted to overestimate the variance of the substrate concentration fluctuations by as much as 30%. The theoretical results are validated by stochastic simulations using experimental parameter values for enzymes involved in proteolysis, gluconeogenesis, and fermentation.

File Usage Analysis and Resource Usage Prediction: a Measurement-Based Study. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Devarakonda, Murthy V.-S.

1987-01-01

A probabilistic scheme was developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The coefficient of correlation between the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82% of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Predictability of process resource usage - A measurement-based study on UNIX

NASA Technical Reports Server (NTRS)

Devarakonda, Murthy V.; Iyer, Ravishankar K.

1989-01-01

A probabilistic scheme is developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The correlation coefficient betweeen the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82 percent of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

Predictability of process resource usage: A measurement-based study of UNIX

NASA Technical Reports Server (NTRS)

Devarakonda, Murthy V.; Iyer, Ravishankar K.

1987-01-01

A probabilistic scheme is developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The correlation coefficient between the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82% of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.

MEASUREMENT AND PREDICTION OF THE RESISTIVITY OF ASH/SORBENT MIXTURES PRODUCED BY SULFUR OXIDE CONTROL PROCESSES

EPA Science Inventory

The report describes the development of (1) a modified procedure for obtaining consistent and reproducible laboratory resistivity values for mixtures of coal fly ash and partially spent sorbent, and (2) an approach for predicting resistivity based on the chemical composition of t...

FDG-PET Response Prediction in Pediatric Hodgkin's Lymphoma: Impact of Metabolically Defined Tumor Volumes and Individualized SUV Measurements on the Positive Predictive Value.

PubMed

Hussien, Amr Elsayed M; Furth, Christian; Schönberger, Stefan; Hundsdoerfer, Patrick; Steffen, Ingo G; Amthauer, Holger; Müller, Hans-Wilhelm; Hautzel, Hubertus

2015-01-28

In pediatric Hodgkin's lymphoma (pHL) early response-to-therapy prediction is metabolically assessed by (18)F-FDG PET carrying an excellent negative predictive value (NPV) but an impaired positive predictive value (PPV). Aim of this study was to improve the PPV while keeping the optimal NPV. A comparison of different PET data analyses was performed applying individualized standardized uptake values (SUV), PET-derived metabolic tumor volume (MTV) and the product of both parameters, termed total lesion glycolysis (TLG); One-hundred-eight PET datasets (PET1, n = 54; PET2, n = 54) of 54 children were analysed by visual and semi-quantitative means. SUVmax, SUVmean, MTV and TLG were obtained the results of both PETs and the relative change from PET1 to PET2 (Δ in %) were compared for their capability of identifying responders and non-responders using receiver operating characteristics (ROC)-curves. In consideration of individual variations in noise and contrasts levels all parameters were additionally obtained after threshold correction to lean body mass and background; All semi-quantitative SUV estimates obtained at PET2 were significantly superior to the visual PET2 analysis. However, ΔSUVmax revealed the best results (area under the curve, 0.92; p < 0.001; sensitivity 100%; specificity 85.4%; PPV 46.2%; NPV 100%; accuracy, 87.0%) but was not significantly superior to SUVmax-estimation at PET2 and ΔTLGmax. Likewise, the lean body mass and background individualization of the datasets did not impove the results of the ROC analyses; Sophisticated semi-quantitative PET measures in early response assessment of pHL patients do not perform significantly better than the previously proposed ΔSUVmax. All analytical strategies failed to improve the impaired PPV to a clinically acceptable level while preserving the excellent NPV.

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.

Numerical study of single and two interacting turbulent plumes in atmospheric cross flow

NASA Astrophysics Data System (ADS)

Mokhtarzadeh-Dehghan, M. R.; König, C. S.; Robins, A. G.

The paper presents a numerical study of two interacting full-scale dry plumes issued into neutral boundary layer cross flow. The study simulates plumes from a mechanical draught cooling tower. The plumes are placed in tandem or side-by-side. Results are first presented for plumes with a density ratio of 0.74 and plume-to-crosswind speed ratio of 2.33, for which data from a small-scale wind tunnel experiment were available and were used to assess the accuracy of the numerical results. Further results are then presented for the more physically realistic density ratio of 0.95, maintaining the same speed ratio. The sensitivity of the results with respect to three turbulence models, namely, the standard k- ɛ model, the RNG k- ɛ model and the Differential Flux Model (DFM) is presented. Comparisons are also made between the predicted rise height and the values obtained from existing integral models. The formation of two counter-rotating vortices is well predicted. The results show good agreement for the rise height predicted by different turbulence models, but the DFM predicts temperature profiles more accurately. The values of predicted rise height are also in general agreement. However, discrepancies between the present results for the rise height for single and multiple plumes and the values obtained from known analytical relations are apparent and possible reasons for these are discussed.

The Predicted Influence of Climate Change on Lesser Prairie-Chicken Reproductive Parameters

PubMed Central

Grisham, Blake A.; Boal, Clint W.; Haukos, David A.; Davis, Dawn M.; Boydston, Kathy K.; Dixon, Charles; Heck, Willard R.

2013-01-01

The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001–2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter’s linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Niña events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival. PMID:23874549

Cytomegalovirus frequency in neonatal intrahepatic cholestasis determined by serology, histology, immunohistochemistry and PCR

PubMed Central

Bellomo-Brandao, Maria Angela; Andrade, Paula D; Costa, Sandra CB; Escanhoela, Cecilia AF; Vassallo, Jose; Porta, Gilda; De Tommaso, Adriana MA; Hessel, Gabriel

2009-01-01

AIM: To determine cytomegalovirus (CMV) frequency in neonatal intrahepatic cholestasis by serology, histological revision (searching for cytomegalic cells), immunohistochemistry, and polymerase chain reaction (PCR), and to verify the relationships among these methods. METHODS: The study comprised 101 non-consecutive infants submitted for hepatic biopsy between March 1982 and December 2005. Serological results were obtained from the patient’s files and the other methods were performed on paraffin-embedded liver samples from hepatic biopsies. The following statistical measures were calculated: frequency, sensibility, specific positive predictive value, negative predictive value, and accuracy. RESULTS: The frequencies of positive results were as follows: serology, 7/64 (11%); histological revision, 0/84; immunohistochemistry, 1/44 (2%), and PCR, 6/77 (8%). Only one patient had positive immunohistochemical findings and a positive PCR. The following statistical measures were calculated between PCR and serology: sensitivity, 33.3%; specificity, 88.89%; positive predictive value, 28.57%; negative predictive value, 90.91%; and accuracy, 82.35%. CONCLUSION: The frequency of positive CMV varied among the tests. Serology presented the highest positive frequency. When compared to PCR, the sensitivity and positive predictive value of serology were low. PMID:19610143

Prediction possibilities of Arosa total ozone

NASA Astrophysics Data System (ADS)

Kane, R. P.

1987-01-01

Using the periodicities obtained by a Maximum Entropy Spectral Analysis (MESA) of the Arosa total ozone data ( CC') series for 1932 1971, the values predicted for 1972 onwards were compared with the observed values of the ( AD) series. A change of level was noticed, with the observed ( AD) values lower by about 7 D.U. Also, the matching was poor in 1980, 1981, 1982. In the monthly values, the most prominent periodicity was the annual wave, comprising some 80% variance. In the 12 month running averages, the annual wave was eliminated and the most prominent periodicity was T=3.7 years, encompassing roundly 20% variance. This and other periodicities at T=4.7, 5.4, 6.2, 10 and 16 years were all statistically significant at a 3.5δ a priori i.e., 2δ a posteriori level. However, the predictions from these were unsatisfactory, probably because some of these periodicities may be transient i.e., changing amplitudes and/or phases with time. Thus, no meaningful prediction seem possible for Arosa total ozone.

Anticipatory Monitoring and Control of Complex Systems using a Fuzzy based Fusion of Support Vector Regressors

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

Miltiadis Alamaniotis; Vivek Agarwal

This paper places itself in the realm of anticipatory systems and envisions monitoring and control methods being capable of making predictions over system critical parameters. Anticipatory systems allow intelligent control of complex systems by predicting their future state. In the current work, an intelligent model aimed at implementing anticipatory monitoring and control in energy industry is presented and tested. More particularly, a set of support vector regressors (SVRs) are trained using both historical and observed data. The trained SVRs are used to predict the future value of the system based on current operational system parameter. The predicted values are thenmore » inputted to a fuzzy logic based module where the values are fused to obtain a single value, i.e., final system output prediction. The methodology is tested on real turbine degradation datasets. The outcome of the approach presented in this paper highlights the superiority over single support vector regressors. In addition, it is shown that appropriate selection of fuzzy sets and fuzzy rules plays an important role in improving system performance.« less

Survival Regression Modeling Strategies in CVD Prediction.

PubMed

Barkhordari, Mahnaz; Padyab, Mojgan; Sardarinia, Mahsa; Hadaegh, Farzad; Azizi, Fereidoun; Bozorgmanesh, Mohammadreza

2016-04-01

A fundamental part of prevention is prediction. Potential predictors are the sine qua non of prediction models. However, whether incorporating novel predictors to prediction models could be directly translated to added predictive value remains an area of dispute. The difference between the predictive power of a predictive model with (enhanced model) and without (baseline model) a certain predictor is generally regarded as an indicator of the predictive value added by that predictor. Indices such as discrimination and calibration have long been used in this regard. Recently, the use of added predictive value has been suggested while comparing the predictive performances of the predictive models with and without novel biomarkers. User-friendly statistical software capable of implementing novel statistical procedures is conspicuously lacking. This shortcoming has restricted implementation of such novel model assessment methods. We aimed to construct Stata commands to help researchers obtain the aforementioned statistical indices. We have written Stata commands that are intended to help researchers obtain the following. 1, Nam-D'Agostino X 2 goodness of fit test; 2, Cut point-free and cut point-based net reclassification improvement index (NRI), relative absolute integrated discriminatory improvement index (IDI), and survival-based regression analyses. We applied the commands to real data on women participating in the Tehran lipid and glucose study (TLGS) to examine if information relating to a family history of premature cardiovascular disease (CVD), waist circumference, and fasting plasma glucose can improve predictive performance of Framingham's general CVD risk algorithm. The command is adpredsurv for survival models. Herein we have described the Stata package "adpredsurv" for calculation of the Nam-D'Agostino X 2 goodness of fit test as well as cut point-free and cut point-based NRI, relative and absolute IDI, and survival-based regression analyses. We hope this work encourages the use of novel methods in examining predictive capacity of the emerging plethora of novel biomarkers.

An investigation of new toxicity test method performance in validation studies: 1. Toxicity test methods that have predictive capacity no greater than chance.

PubMed

Bruner, L H; Carr, G J; Harbell, J W; Curren, R D

2002-06-01

An approach commonly used to measure new toxicity test method (NTM) performance in validation studies is to divide toxicity results into positive and negative classifications, and the identify true positive (TP), true negative (TN), false positive (FP) and false negative (FN) results. After this step is completed, the contingent probability statistics (CPS), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) are calculated. Although these statistics are widely used and often the only statistics used to assess the performance of toxicity test methods, there is little specific guidance in the validation literature on what values for these statistics indicate adequate performance. The purpose of this study was to begin developing data-based answers to this question by characterizing the CPS obtained from an NTM whose data have a completely random association with a reference test method (RTM). Determining the CPS of this worst-case scenario is useful because it provides a lower baseline from which the performance of an NTM can be judged in future validation studies. It also provides an indication of relationships in the CPS that help identify random or near-random relationships in the data. The results from this study of randomly associated tests show that the values obtained for the statistics vary significantly depending on the cut-offs chosen, that high values can be obtained for individual statistics, and that the different measures cannot be considered independently when evaluating the performance of an NTM. When the association between results of an NTM and RTM is random the sum of the complementary pairs of statistics (sensitivity + specificity, NPV + PPV) is approximately 1, and the prevalence (i.e., the proportion of toxic chemicals in the population of chemicals) and PPV are equal. Given that combinations of high sensitivity-low specificity or low specificity-high sensitivity (i.e., the sum of the sensitivity and specificity equal to approximately 1) indicate lack of predictive capacity, an NTM having these performance characteristics should be considered no better for predicting toxicity than by chance alone.

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.

Spatial epidemiology of bovine tuberculosis in Mexico.

PubMed

Martínez, Horacio Zendejas; Suazo, Feliciano Milián; Cuador Gil, José Quintín; Bello, Gustavo Cruz; Anaya Escalera, Ana María; Márquez, Gabriel Huitrón; Casanova, Leticia García

2007-01-01

The purpose of this study was to use geographic information systems (GIS) and geo-statistical methods of ordinary kriging to predict the prevalence and distribution of bovine tuberculosis (TB) in Jalisco, Mexico. A random sample of 2 287 herds selected from a set of 48 766 was used for the analysis. Spatial location of herds was obtained by either a personal global positioning system (GPS), a database from the Instituto Nacional de Estadìstica Geografìa e Informàtica (INEGI) or Google Earth. Information on TB prevalence was provided by the Jalisco Commission for the Control and Eradication of Tuberculosis (COEETB). Prediction of TB was obtained using ordinary kriging in the geostatistical analyst module in ArcView8. A predicted high prevalence area of TB matching the distribution of dairy cattle was observed. This prediction was in agreement with the prevalence calculated on the total 48 766 herds. Validation was performed taking estimated values of TB prevalence at each municipality, extracted from the kriging surface and then compared with the real prevalence values using a correlation test, giving a value of 0.78, indicating that GIS and kriging are reliable tools for the estimation of TB distribution based on a random sample. This resulted in a significant savings of resources.

[Evaluation of serology as a diagnostic method for Helicobacter pylori infection in the local population of Guayaquil].

PubMed

Zapatier, Jorge A; Gómez, Néstor A; Vargas, Paola E; Maya, Susana V

2007-06-01

The infection with Helicobacter pylori (H. pylori), and the diagnostic efficacy of the serologic tests has certain variability among the different geographic regions. The objective of the present work was to find the local validation of serological methods for diagnosis of H. pylori infection and to determine the best cutoff value for the local population. Forty-eight patients were evaluated, 27 males and 21 females, with a mean age of 29.2 years. On each patient, 3 tests for H. pylori diagnosis were performed: IgG serology, IgA serology and histology. We performed IgG and IgA serologic test for H. pylori infection and a histological examination for each patient. Efficacy parameters as well as the ROC curve were obtained for the IgG and IgA serology using histology as the gold standard. The cutoff point with the highest efficacy for IgG serology was 16 U/ml (sensitivity 81%, specificity 65%, positive predictive value 81%, negative predictive value 65%, and accuracy 75%), and for IgA serology was 17 U/ml (sensitivity 61%, specificity 53%, positive predictive value 70%, negative predictive value 43%, and accuracy 58%). The area under the curve was 67.1% (CI 95%: 50 to 84.1) and 54.4% (CI 95%: 38.3 to 72.5) for IgG and IgA respectively. The serology is a valuable tool in our population with high prevalence of H. pylori, especially due to its low cost and easy performance, but a reduction ofthe cutoff value was necessary to obtain more sensibility and a more adequate identification of true positives cases.

Analysing News for Stock Market Prediction

NASA Astrophysics Data System (ADS)

Ramalingam, V. V.; Pandian, A.; Dwivedi, shivam; Bhatt, Jigar P.

2018-04-01

Stock market means the aggregation of all sellers and buyers of stocks representing their ownership claims on the business. To be completely absolute about the investment on these stocks, proper knowledge about them as well as their pricing, for both present and future is very essential. Large amount of data is collected and parsed to obtain this essential information regarding the fluctuations in the stock market. This data can be any news or public opinions in general. Recently, many methods have been used, especially big unstructured data methods to predict the stock market values. We introduce another method of focusing on deriving the best statistical learning model for predicting the future values. The data set used is very large unstructured data collected from an online social platform, commonly known as Quindl. The data from this platform is then linked to a csv fie and cleaned to obtain the essential information for stock market prediction. The method consists of carrying out the NLP (Natural Language Processing) of the data and then making it easier for the system to understand, finds and identifies the correlation in between this data and the stock market fluctuations. The model is implemented using Python Programming Language throughout the entire project to obtain flexibility and convenience of the system.

Machine learning landscapes and predictions for patient outcomes

NASA Astrophysics Data System (ADS)

Das, Ritankar; Wales, David J.

2017-07-01

The theory and computational tools developed to interpret and explore energy landscapes in molecular science are applied to the landscapes defined by local minima for neural networks. These machine learning landscapes correspond to fits of training data, where the inputs are vital signs and laboratory measurements for a database of patients, and the objective is to predict a clinical outcome. In this contribution, we test the predictions obtained by fitting to single measurements, and then to combinations of between 2 and 10 different patient medical data items. The effect of including measurements over different time intervals from the 48 h period in question is analysed, and the most recent values are found to be the most important. We also compare results obtained for neural networks as a function of the number of hidden nodes, and for different values of a regularization parameter. The predictions are compared with an alternative convex fitting function, and a strong correlation is observed. The dependence of these results on the patients randomly selected for training and testing decreases systematically with the size of the database available. The machine learning landscapes defined by neural network fits in this investigation have single-funnel character, which probably explains why it is relatively straightforward to obtain the global minimum solution, or a fit that behaves similarly to this optimal parameterization.

Attitude Control of Flexible Structures.

DTIC Science & Technology

1990-09-01

arm has been determined experimentally and compared with analytical * predictions obtained by using the GIFTS finite element analysis program. The...frequencies of the flexible arm have been determined experimentally and compared with analytical predictiens obtained by using the GIFTS finite element...exception of the first mode. Table V shows the difference between the frequencies obtained from the GIFTS program and the experimental values. TABLE

Displacement prediction of Baijiabao landslide based on empirical mode decomposition and long short-term memory neural network in Three Gorges area, China

NASA Astrophysics Data System (ADS)

Xu, Shiluo; Niu, Ruiqing

2018-02-01

Every year, landslides pose huge threats to thousands of people in China, especially those in the Three Gorges area. It is thus necessary to establish an early warning system to help prevent property damage and save peoples' lives. Most of the landslide displacement prediction models that have been proposed are static models. However, landslides are dynamic systems. In this paper, the total accumulative displacement of the Baijiabao landslide is divided into trend and periodic components using empirical mode decomposition. The trend component is predicted using an S-curve estimation, and the total periodic component is predicted using a long short-term memory neural network (LSTM). LSTM is a dynamic model that can remember historical information and apply it to the current output. Six triggering factors are chosen to predict the periodic term using the Pearson cross-correlation coefficient and mutual information. These factors include the cumulative precipitation during the previous month, the cumulative precipitation during a two-month period, the reservoir level during the current month, the change in the reservoir level during the previous month, the cumulative increment of the reservoir level during the current month, and the cumulative displacement during the previous month. When using one-step-ahead prediction, LSTM yields a root mean squared error (RMSE) value of 6.112 mm, while the support vector machine for regression (SVR) and the back-propagation neural network (BP) yield values of 10.686 mm and 8.237 mm, respectively. Meanwhile, the Elman network (Elman) yields an RMSE value of 6.579 mm. In addition, when using multi-step-ahead prediction, LSTM obtains an RMSE value of 8.648 mm, while SVR, BP and the Elman network obtains RSME values of 13.418 mm, 13.014 mm, and 13.370 mm. The predicted results indicate that, to some extent, the dynamic model (LSTM) achieves results that are more accurate than those of the static models (i.e., SVR and BP). LSTM even displays better performance than the Elman network, which is also a dynamic method.

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

Sadhukhan, Jhilam; Pal, Santanu

An expression for stationary fission width is obtained for systems with steep shape-dependent nuclear collective inertia by extending the work of Kramers, which was originally derived for a fixed value of the inertia. The domain of validity of the present expression is examined by comparing its predictions with widths obtained from the corresponding Langevin equations.

Differential encoding of factors influencing predicted reward value in monkey rostral anterior cingulate cortex.

PubMed

Toda, Koji; Sugase-Miyamoto, Yasuko; Mizuhiki, Takashi; Inaba, Kiyonori; Richmond, Barry J; Shidara, Munetaka

2012-01-01

The value of a predicted reward can be estimated based on the conjunction of both the intrinsic reward value and the length of time to obtain it. The question we addressed is how the two aspects, reward size and proximity to reward, influence the responses of neurons in rostral anterior cingulate cortex (rACC), a brain region thought to play an important role in reward processing. We recorded from single neurons while two monkeys performed a multi-trial reward schedule task. The monkeys performed 1-4 sequential color discrimination trials to obtain a reward of 1-3 liquid drops. There were two task conditions, a valid cue condition, where the number of trials and reward amount were associated with visual cues, and a random cue condition, where the cue was picked from the cue set at random. In the valid cue condition, the neuronal firing is strongly modulated by the predicted reward proximity during the trials. Information about the predicted reward amount is almost absent at those times. In substantial subpopulations, the neuronal responses decreased or increased gradually through schedule progress to the predicted outcome. These two gradually modulating signals could be used to calculate the effect of time on the perception of reward value. In the random cue condition, little information about the reward proximity or reward amount is encoded during the course of the trial before reward delivery, but when the reward is actually delivered the responses reflect both the reward proximity and reward amount. Our results suggest that the rACC neurons encode information about reward proximity and amount in a manner that is dependent on utility of reward information. The manner in which the information is represented could be used in the moment-to-moment calculation of the effect of time and amount on predicted outcome value.

Prognostic significance of contrast-enhanced CT attenuation value in extrahepatic cholangiocarcinoma.

PubMed

Asayama, Yoshiki; Nishie, Akihiro; Ishigami, Kousei; Ushijima, Yasuhiro; Takayama, Yukihisa; Okamoto, Daisuke; Fujita, Nobuhiro; Ohtsuka, Takao; Yoshizumi, Tomoharu; Aishima, Shinichi; Oda, Yoshinao; Honda, Hiroshi

2017-06-01

To determine whether washout characteristics of dynamic contrast-enhanced computed tomography (CT) could predict survival in patients with extrahepatic cholangiocarcinoma (EHC). This study collected 46 resected cases. All cases were examined by dynamic contrast study on multidetector-row CT. Region-of-interest measurements were obtained at the non-enhanced, portal venous phase and delayed phase in the tumour and were used to calculate the washout ratio as follows: [(attenuation value at portal venous phase CT - attenuation value at delayed enhanced CT)/(attenuation value at portal venous phase CT - attenuation value at unenhanced CT)] × 100. On the basis of the median washout ratio, we classified the cases into two groups, a high-washout group and low-washout group. Associations between overall survival and various factors including washout rates were analysed. The median washout ratio was 29.4 %. Univariate analysis revealed that a lower washout ratio, venous invasion, lymphatic permeation and lymph node metastasis were associated with shorter survival. Multivariate analysis identified the lower washout ratio as an independent prognostic factor (hazard ratio, 3.768; p value, 0.027). The washout ratio obtained from the contrast-enhanced CT may be a useful imaging biomarker for the prediction of survival of patients with EHC. • Dynamic contrast study can evaluate the aggressiveness of extrahepatic cholangiocarcinoma. • A lower washout ratio was an independent prognostic factor for overall survival. • CT can predict survival and inform decisions on surgical options or chemotherapy.

Application of a computer model to predict optimum slaughter end points for different biological types of feeder cattle.

PubMed

Williams, C B; Bennett, G L

1995-10-01

A bioeconomic model was developed to predict slaughter end points of different genotypes of feeder cattle, where profit/rotation and profit/day were maximized. Growth, feed intake, and carcass weight and composition were simulated for 17 biological types of steers. Distribution of carcass weight and proportion in four USDA quality and five USDA yield grades were obtained from predicted carcass weights and composition. Average carcass value for each genotype was calculated from these distributions under four carcass pricing systems that varied from value determined on quality grade alone to value determined on yield grade alone. Under profitable market conditions, rotation length was shorter and carcass weights lighter when the producer's goal was maximum profit/day, compared with maximum profit/rotation. A carcass value system based on yield grade alone resulted in greater profit/rotation and in lighter and leaner carcasses than a system based on quality grade alone. High correlations ( > .97) were obtained between breed profits obtained with different sets of input/output prices and carcass price discount weight ranges. This suggests that breed rankings on the basis of breed profits may not be sensitive to changes in input/output market prices. Steers that were on a grower-stocker system had leaner carcasses, heavier optimum carcass weight, greater profits, and less variation in optimum carcass weights between genotypes than steers that were started on a high-energy finishing diet at weaning. Overall results suggest that breed choices may change with different carcass grading and value systems and postweaning production systems. This model has potential to provide decision support in marketing fed cattle.

Evapotranspiration using a satellite-based surface energy balance with standardized ground control

NASA Astrophysics Data System (ADS)

Trezza, Ricardo

This study evaluated the potential of using the S&barbelow;urface E&barbelow;nergy Ḇalance A&barbelow;lgorithm for Ḻand (SEBAL) as a means for estimating evapotranspiration (ET) for local and regional scales in Southern Idaho. The original SEBAL model was refined during this study to provide better estimation of ET in agricultural areas and to make more reliable estimates of ET from other surfaces as well, including mountainous terrain. The modified version of SEBAL used in this study, termed as SEBALID (ID stands for Idaho) includes standardization of the two SEBAL "anchor" pixels, the use of a water balance model to track top soil moisture, adaptation of components of SEBAL for better prediction of the surface energy balance in mountains and sloping terrain, and use of the ratio between actual ET and alfalfa reference evapotranspiration (ET r) as a means for obtaining the temporal integration of instantaneous ET to daily and seasonal values. Validation of the SEBALID model at a local scale was performed by comparing lysimeter ET measurements from the USDA-ARS facility at Kimberly, Idaho, with ET predictions by SEBAL using Landsat 5 TM imagery. Comparison of measured and predicted ET values was challenging due to the resolution of the Landsat thermal band (120m x 120m) and the relatively small size of the lysimeter fields. In the cases where thermal information was adequate, SEBALID predictions were close to the measured values of ET in the lysimeters. Application of SEBALID at a regional scale was performed using Landsat 7 ETM+ and Landsat 5 TM imagery for the Eastern Snake Plain Aquifer (ESPA) region in Idaho during 2000. The results indicated that SEBALID performed well for predicting daily and seasonal ET for agricultural areas. Some unreasonable results were obtained for desert and basalt areas, due to uncertainties of the prediction of surface parameters. In mountains, even though validation of results was not possible, the values of ET obtained reflected the progress produced by the refinements made to the original SEBAL algorithm.

Prediction of human dietary δ15N intake from standardised food records: validity and precision of single meal and 24-h diet data.

PubMed

Hülsemann, Frank; Koehler, Karsten; Wittsiepe, Jürgen; Wilhelm, Michael; Hilbig, Annett; Kersting, Mathilde; Braun, Hans; Flenker, Ulrich; Schänzer, Wilhelm

2017-08-01

Natural stable isotope ratios (δ 15 N) of humans can be used for nutritional analyses and dietary reconstruction of modern and historic individuals and populations. Information about an individual's metabolic state can be obtained by comparison of tissue and dietary δ 15 N. Different methods have been used to estimate dietary δ 15 N in the past; however, the validity of such predictions has not been compared to experimental values. For a total of 56 meals and 21 samples of 24-h diets, predicted and experimental δ 15 N values were compared. The δ 15 N values were predicted from self-recorded food intake and compared with experimental δ 15 N values. Predicted and experimental δ 15 N values were in good agreement for meals and preparations (r = 0.89, p < .001) as well as for the 24-h diets (r = 0.76, p < .001). Dietary δ 15 N was mainly determined by the amount of fish, whereas the contribution of meat to dietary δ 15 N values was less pronounced. Prediction of human dietary δ 15 N values using standardised food records and representative δ 15 N data sets yields reliable data for dietary δ 15 N intake. A differentiated analysis of the primary protein sources is necessary when relating the proportion of animal-derived protein in the diet by δ 15 N analysis.

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.

A dynamo theory prediction for solar cycle 22: Sunspot number, radio flux, exospheric temperature, and total density at 400 km

NASA Technical Reports Server (NTRS)

Schatten, K. H.; Hedin, A. E.

1986-01-01

Using the dynamo theory method to predict solar activity, a value for the smoothed sunspot number of 109 + or - 20 is obtained for solar cycle 22. The predicted cycle is expected to peak near December, 1990 + or - 1 year. Concommitantly, F(10.7) radio flux is expected to reach a smoothed value of 158 + or - 18 flux units. Global mean exospheric temperature is expected to reach 1060 + or - 50 K and global total average total thermospheric density at 400 km is expected to reach 4.3 x 10 to the -15th gm/cu cm + or - 25 percent.

Flight test evaluation of predicted light aircraft drag, performance, and stability

NASA Technical Reports Server (NTRS)

Smetana, F. O.; Fox, S. R.

1979-01-01

A technique was developed which permits simultaneous extraction of complete lift, drag, and thrust power curves from time histories of a single aircraft maneuver such as a pullup (from V sub max to V sub stall) and pushover (to sub V max for level flight.) The technique is an extension to non-linear equations of motion of the parameter identification methods of lliff and Taylor and includes provisions for internal data compatibility improvement as well. The technique was show to be capable of correcting random errors in the most sensitive data channel and yielding highly accurate results. This technique was applied to flight data taken on the ATLIT aircraft. The drag and power values obtained from the initial least squares estimate are about 15% less than the 'true' values. If one takes into account the rather dirty wing and fuselage existing at the time of the tests, however, the predictions are reasonably accurate. The steady state lift measurements agree well with the extracted values only for small values of alpha. The predicted value of the lift at alpha = 0 is about 33% below that found in steady state tests while the predicted lift slope is 13% below the steady state value.

PARTS: Probabilistic Alignment for RNA joinT Secondary structure prediction

PubMed Central

Harmanci, Arif Ozgun; Sharma, Gaurav; Mathews, David H.

2008-01-01

A novel method is presented for joint prediction of alignment and common secondary structures of two RNA sequences. The joint consideration of common secondary structures and alignment is accomplished by structural alignment over a search space defined by the newly introduced motif called matched helical regions. The matched helical region formulation generalizes previously employed constraints for structural alignment and thereby better accommodates the structural variability within RNA families. A probabilistic model based on pseudo free energies obtained from precomputed base pairing and alignment probabilities is utilized for scoring structural alignments. Maximum a posteriori (MAP) common secondary structures, sequence alignment and joint posterior probabilities of base pairing are obtained from the model via a dynamic programming algorithm called PARTS. The advantage of the more general structural alignment of PARTS is seen in secondary structure predictions for the RNase P family. For this family, the PARTS MAP predictions of secondary structures and alignment perform significantly better than prior methods that utilize a more restrictive structural alignment model. For the tRNA and 5S rRNA families, the richer structural alignment model of PARTS does not offer a benefit and the method therefore performs comparably with existing alternatives. For all RNA families studied, the posterior probability estimates obtained from PARTS offer an improvement over posterior probability estimates from a single sequence prediction. When considering the base pairings predicted over a threshold value of confidence, the combination of sensitivity and positive predictive value is superior for PARTS than for the single sequence prediction. PARTS source code is available for download under the GNU public license at http://rna.urmc.rochester.edu. PMID:18304945

An evaluation of string theory for the prediction of dynamic tire properties using scale model aircraft tires

NASA Technical Reports Server (NTRS)

Clark, S. K.; Dodge, R. N.; Nybakken, G. H.

1972-01-01

The string theory was evaluated for predicting lateral tire dynamic properties as obtained from scaled model tests. The experimental data and string theory predictions are in generally good agreement using lateral stiffness and relaxation length values obtained from the static or slowly rolling tire. The results indicate that lateral forces and self-aligning torques are linearly proportional to tire lateral stiffness and to the amplitude of either steer or lateral displacement. In addition, the results show that the ratio of input excitation frequency to road speed is the proper independent variable by which frequency should be measured.

Revision of the experimental electron affinity of BO

NASA Astrophysics Data System (ADS)

Rienstra, Jonathan C.; Schaefer, Henry F., III

1997-05-01

The experimental electron affinity of BO has proven questionable. We obtained the electron affinity of BO using the large aug-cc-pVQZ basis with SCF, CISD, CISD+Q, CCSD, and CCSD(T) methods and predict a value of 2.57 eV, or 0.55 eV smaller than the latest experimental value. The 2∑+ to 2Π excitation energy of BO has also been obtained with the CCSD(T) method and found to be 2.82 eV.

[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.

Discrimination and prediction of cultivation age and parts of Panax ginseng by Fourier-transform infrared spectroscopy combined with multivariate statistical analysis.

PubMed

Lee, Byeong-Ju; Kim, Hye-Youn; Lim, Sa Rang; Huang, Linfang; Choi, Hyung-Kyoon

2017-01-01

Panax ginseng C.A. Meyer is a herb used for medicinal purposes, and its discrimination according to cultivation age has been an important and practical issue. This study employed Fourier-transform infrared (FT-IR) spectroscopy with multivariate statistical analysis to obtain a prediction model for discriminating cultivation ages (5 and 6 years) and three different parts (rhizome, tap root, and lateral root) of P. ginseng. The optimal partial-least-squares regression (PLSR) models for discriminating ginseng samples were determined by selecting normalization methods, number of partial-least-squares (PLS) components, and variable influence on projection (VIP) cutoff values. The best prediction model for discriminating 5- and 6-year-old ginseng was developed using tap root, vector normalization applied after the second differentiation, one PLS component, and a VIP cutoff of 1.0 (based on the lowest root-mean-square error of prediction value). In addition, for discriminating among the three parts of P. ginseng, optimized PLSR models were established using data sets obtained from vector normalization, two PLS components, and VIP cutoff values of 1.5 (for 5-year-old ginseng) and 1.3 (for 6-year-old ginseng). To our knowledge, this is the first study to provide a novel strategy for rapidly discriminating the cultivation ages and parts of P. ginseng using FT-IR by selected normalization methods, number of PLS components, and VIP cutoff values.

Discrimination and prediction of cultivation age and parts of Panax ginseng by Fourier-transform infrared spectroscopy combined with multivariate statistical analysis

PubMed Central

Lim, Sa Rang; Huang, Linfang

2017-01-01

Panax ginseng C.A. Meyer is a herb used for medicinal purposes, and its discrimination according to cultivation age has been an important and practical issue. This study employed Fourier-transform infrared (FT-IR) spectroscopy with multivariate statistical analysis to obtain a prediction model for discriminating cultivation ages (5 and 6 years) and three different parts (rhizome, tap root, and lateral root) of P. ginseng. The optimal partial-least-squares regression (PLSR) models for discriminating ginseng samples were determined by selecting normalization methods, number of partial-least-squares (PLS) components, and variable influence on projection (VIP) cutoff values. The best prediction model for discriminating 5- and 6-year-old ginseng was developed using tap root, vector normalization applied after the second differentiation, one PLS component, and a VIP cutoff of 1.0 (based on the lowest root-mean-square error of prediction value). In addition, for discriminating among the three parts of P. ginseng, optimized PLSR models were established using data sets obtained from vector normalization, two PLS components, and VIP cutoff values of 1.5 (for 5-year-old ginseng) and 1.3 (for 6-year-old ginseng). To our knowledge, this is the first study to provide a novel strategy for rapidly discriminating the cultivation ages and parts of P. ginseng using FT-IR by selected normalization methods, number of PLS components, and VIP cutoff values. PMID:29049369

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 breakdown strength of cellulosic insulating materials using artificial neural networks

NASA Astrophysics Data System (ADS)

Singh, Sakshi; Mohsin, M. M.; Masood, Aejaz

In this research work, a few sets of experiments have been performed in high voltage laboratory on various cellulosic insulating materials like diamond-dotted paper, paper phenolic sheets, cotton phenolic sheets, leatheroid, and presspaper, to measure different electrical parameters like breakdown strength, relative permittivity, loss tangent, etc. Considering the dependency of breakdown strength on other physical parameters, different Artificial Neural Network (ANN) models are proposed for the prediction of breakdown strength. The ANN model results are compared with those obtained experimentally and also with the values already predicted from an empirical relation suggested by Swanson and Dall. The reported results indicated that the breakdown strength predicted from the ANN model is in good agreement with the experimental values.

Predicting Flory-Huggins χ from Simulations

NASA Astrophysics Data System (ADS)

Zhang, Wenlin; Gomez, Enrique D.; Milner, Scott T.

2017-07-01

We introduce a method, based on a novel thermodynamic integration scheme, to extract the Flory-Huggins χ parameter as small as 10-3k T for polymer blends from molecular dynamics (MD) simulations. We obtain χ for the archetypical coarse-grained model of nonpolar polymer blends: flexible bead-spring chains with different Lennard-Jones interactions between A and B monomers. Using these χ values and a lattice version of self-consistent field theory (SCFT), we predict the shape of planar interfaces for phase-separated binary blends. Our SCFT results agree with MD simulations, validating both the predicted χ values and our thermodynamic integration method. Combined with atomistic simulations, our method can be applied to predict χ for new polymers from their chemical structures.

Estimating the Accuracy of the Chedoke–McMaster Stroke Assessment Predictive Equations for Stroke Rehabilitation

PubMed Central

Dang, Mia; Ramsaran, Kalinda D.; Street, Melissa E.; Syed, S. Noreen; Barclay-Goddard, Ruth; Miller, Patricia A.

2011-01-01

ABSTRACT Purpose: To estimate the predictive accuracy and clinical usefulness of the Chedoke–McMaster Stroke Assessment (CMSA) predictive equations. Method: A longitudinal prognostic study using historical data obtained from 104 patients admitted post cerebrovascular accident was undertaken. Data were abstracted for all patients undergoing rehabilitation post stroke who also had documented admission and discharge CMSA scores. Published predictive equations were used to determine predicted outcomes. To determine the accuracy and clinical usefulness of the predictive model, shrinkage coefficients and predictions with 95% confidence bands were calculated. Results: Complete data were available for 74 patients with a mean age of 65.3±12.4 years. The shrinkage values for the six Impairment Inventory (II) dimensions varied from −0.05 to 0.09; the shrinkage value for the Activity Inventory (AI) was 0.21. The error associated with predictive values was greater than ±1.5 stages for the II dimensions and greater than ±24 points for the AI. Conclusions: This study shows that the large error associated with the predictions (as defined by the confidence band) for the CMSA II and AI limits their clinical usefulness as a predictive measure. Further research to establish predictive models using alternative statistical procedures is warranted. PMID:22654239

Time-Aware Service Ranking Prediction in the Internet of Things Environment

PubMed Central

Huang, Yuze; Huang, Jiwei; Cheng, Bo; He, Shuqing; Chen, Junliang

2017-01-01

With the rapid development of the Internet of things (IoT), building IoT systems with high quality of service (QoS) has become an urgent requirement in both academia and industry. During the procedures of building IoT systems, QoS-aware service selection is an important concern, which requires the ranking of a set of functionally similar services according to their QoS values. In reality, however, it is quite expensive and even impractical to evaluate all geographically-dispersed IoT services at a single client to obtain such a ranking. Nevertheless, distributed measurement and ranking aggregation have to deal with the high dynamics of QoS values and the inconsistency of partial rankings. To address these challenges, we propose a time-aware service ranking prediction approach named TSRPred for obtaining the global ranking from the collection of partial rankings. Specifically, a pairwise comparison model is constructed to describe the relationships between different services, where the partial rankings are obtained by time series forecasting on QoS values. The comparisons of IoT services are formulated by random walks, and thus, the global ranking can be obtained by sorting the steady-state probabilities of the underlying Markov chain. Finally, the efficacy of TSRPred is validated by simulation experiments based on large-scale real-world datasets. PMID:28448451

Time-Aware Service Ranking Prediction in the Internet of Things Environment.

PubMed

Huang, Yuze; Huang, Jiwei; Cheng, Bo; He, Shuqing; Chen, Junliang

2017-04-27

With the rapid development of the Internet of things (IoT), building IoT systems with high quality of service (QoS) has become an urgent requirement in both academia and industry. During the procedures of building IoT systems, QoS-aware service selection is an important concern, which requires the ranking of a set of functionally similar services according to their QoS values. In reality, however, it is quite expensive and even impractical to evaluate all geographically-dispersed IoT services at a single client to obtain such a ranking. Nevertheless, distributed measurement and ranking aggregation have to deal with the high dynamics of QoS values and the inconsistency of partial rankings. To address these challenges, we propose a time-aware service ranking prediction approach named TSRPred for obtaining the global ranking from the collection of partial rankings. Specifically, a pairwise comparison model is constructed to describe the relationships between different services, where the partial rankings are obtained by time series forecasting on QoS values. The comparisons of IoT services are formulated by random walks, and thus, the global ranking can be obtained by sorting the steady-state probabilities of the underlying Markov chain. Finally, the efficacy of TSRPred is validated by simulation experiments based on large-scale real-world datasets.

Choice from non-choice: Predicting consumer preferences from BOLD signals obtained during passive viewing

PubMed Central

Levy, Ifat; Lazzaro, Stephanie C.; Rutledge, Robb B.; Glimcher, Paul W.

2011-01-01

Decision-making is often viewed as a two-stage process, where subjective values are first assigned to each option and then the option of the highest value is selected. Converging evidence suggests that these subjective values are represented in the striatum and medial prefrontal cortex (MPFC). A separate line of evidence suggests that activation in the same areas represents the values of rewards even when choice is not required, as in classical conditioning tasks. However, it is unclear whether the same neural mechanism is engaged in both cases. To address this question we measured brain activation with fMRI while human subjects passively viewed individual consumer goods. We then sampled activation from predefined regions of interest and used it to predict subsequent choices between the same items made outside of the scanner. Our results show that activation in the striatum and MPFC in the absence of choice predicts subsequent choices, suggesting that these brain areas represent value in a similar manner whether or not choice is required. PMID:21209196

QSPR models for various physical properties of carbohydrates based on molecular mechanics and quantum chemical calculations.

PubMed

Dyekjaer, Jane Dannow; Jónsdóttir, Svava Osk

2004-01-22

Quantitative Structure-Property Relationships (QSPR) have been developed for a series of monosaccharides, including the physical properties of partial molar heat capacity, heat of solution, melting point, heat of fusion, glass-transition temperature, and solid state density. The models were based on molecular descriptors obtained from molecular mechanics and quantum chemical calculations, combined with other types of descriptors. Saccharides exhibit a large degree of conformational flexibility, therefore a methodology for selecting the energetically most favorable conformers has been developed, and was used for the development of the QSPR models. In most cases good correlations were obtained for monosaccharides. For five of the properties predictions were made for disaccharides, and the predicted values for the partial molar heat capacities were in excellent agreement with experimental values.

The application of the statistical theory of extreme values to gust-load problems

NASA Technical Reports Server (NTRS)

Press, Harry

1950-01-01

An analysis is presented which indicates that the statistical theory of extreme values is applicable to the problems of predicting the frequency of encountering the larger gust loads and gust velocities for both specific test conditions as well as commercial transport operations. The extreme-value theory provides an analytic form for the distributions of maximum values of gust load and velocity. Methods of fitting the distribution are given along with a method of estimating the reliability of the predictions. The theory of extreme values is applied to available load data from commercial transport operations. The results indicate that the estimates of the frequency of encountering the larger loads are more consistent with the data and more reliable than those obtained in previous analyses. (author)

Heart imaging: the accuracy of the 64-MSCT in the detection of coronary artery disease.

PubMed

Alessandri, N; Di Matteo, A; Rondoni, G; Petrassi, M; Tufani, F; Ferrari, R; Laghi, A

2009-01-01

At present, coronary angiography represents the gold standard technique for the diagnosis of coronary artery disease. Our aim is to compare the conventional coronary angiography to the coronary 64-multislice spiral computed tomography (64-MSCT), a new and non-invasive cardiac imaging technique. The last generation of MSCT scanners show a better imaging quality, due to a greater spatial and temporal resolution. Four expert observers (two cardiologists and two radiologists) have compared the angiographic data with the accuracy of the 64-MSCT in the detection and evaluation of coronary vessels stenoses. From the data obtained, the sensibility, the specificity and the accuracy of the coronary 64-MSCT have been defined. We have enrolled 75 patients (57 male, 18 female, mean age 61.83 +/- 10.38; range 30-80 years) with known or suspected coronary artery disease. The above population has been divided into 3 groups: Group A (Gr. A) with 40 patients (mean age 60.7 +/- 12.5) affected by both non-significant and significant coronary artery disease; Group B (Gr. B) with 25 patients (mean age 60.3 +/- 14.6) who underwent to percutaneous coronary intervention (PCI); Group C (Gr. C) with 10 patients (mean age 54.20 +/- 13.7) without any coronary angiographic stenoses. All the patients underwent non-invasive exams, conventional coronary angiography and coronary 64-MSCT. The comparison of the data obtained has been carried out according to a per group analysis, per patient analysis and per segment analysis. Moreover, the accuracy of the 64-MSCT has been defined for the detection of >75%, 50-75% and <50% coronary stenoses. Coronary angiography has identified significant coronary artery disease in 75% of the patients in the Gr. A and in 73% of the patients in the Gr. B. No coronary stenoses have been detected in Gr. C. According to a per segment analysis, in Gr. A, 36% of the segments analysed have shown a coronary stenosis (37% stenoses >75%, 32% stenoses 50-75% and 31% stenoses <50%). In Gr. B, 32% of the segments have shown a coronary stenosis (33% stenoses >75%, 29% stenoses 50-75% and 38% stenoses <50%). In-stent disease has been shown in only 4 of the 29 coronary stents identified. In Gr. A, coronary 64-MSCT has confirmed the angiographic results in the 93% of cases (sensibility 93%, specificity 100%, positive predictive value 100% and negative predictive value 83%) while, in Gr. B, this confirm has been obtained only in 64% of cases (sensibility 64%, specificity 100%, positive predictive value 100% and negative predictive value 50%). In Gr. C, we have observed a complete agreement between angiographic and CT data (sensibility, specificity, positive predictive value and negative predictive value 100%). According to a per segment analysis, the angiographic results have been confirmed in 98% of cases in Gr. A (sensibility 98%, specificity 94%, positive predictive value 90% and negative predictive value 94%) but only in 55% of cases in Gr. B (sensibility 55%, specificity 90%, positive predictive value 71% and negative predictive value 81%). Moreover, only 1 of the 4 in-stent restenoses has been detected (sensibility 25%, specificity 100%, positive predictive value 100% and negative predictive value 77%). Coronary angiography has detected a greater number of coronary stenoses than the 64-MSCT. 64-MSCT has demonstrated better accuracy in the study of coronary vessels wider than 2 mm, while its accuracy is lower for smaller vessels (diameter < 2.5 mm) and for the identification of in-stent restenosis, because there is a reduced image quality for these vessels and therefore a lower accuracy in the coronary stenosis detection. Nevertheless, 64-MSCT shows high accuracy and it can be considered a comparative but not a substitutive exam of the coronary angiography. Several technical limitations of the 64-MSCT are responsible of its lower accuracy versus the conventional coronary angiography, but solving these technical problems could give us a new non-invasive imaging technique for the study of coronary stents.

The Role of Personal Values in Social Entrepreneurship

ERIC Educational Resources Information Center

Akar, Hüseyin; Dogan, Yildiz Burcu

2018-01-01

The purpose of this research is to examine to what extent pre-service teachers' personal values predict their social entrepreneurship characteristics. In this context, statistical analysis was conducted on the data obtained from 393 pre-service teachers studying at the Faculty of Muallim Rifat Education at Kilis 7 Aralik University in 2016-2017…

Estimation of soil hydraulic properties with microwave techniques

NASA Technical Reports Server (NTRS)

Oneill, P. E.; Gurney, R. J.; Camillo, P. J.

1985-01-01

Useful quantitative information about soil properties may be obtained by calibrating energy and moisture balance models with remotely sensed data. A soil physics model solves heat and moisture flux equations in the soil profile and is driven by the surface energy balance. Model generated surface temperature and soil moisture and temperature profiles are then used in a microwave emission model to predict the soil brightness temperature. The model hydraulic parameters are varied until the predicted temperatures agree with the remotely sensed values. This method is used to estimate values for saturated hydraulic conductivity, saturated matrix potential, and a soil texture parameter. The conductivity agreed well with a value measured with an infiltration ring and the other parameters agreed with values in the literature.

Prediction of genomic breeding values for dairy traits in Italian Brown and Simmental bulls using a principal component approach.

PubMed

Pintus, M A; Gaspa, G; Nicolazzi, E L; Vicario, D; Rossoni, A; Ajmone-Marsan, P; Nardone, A; Dimauro, C; Macciotta, N P P

2012-06-01

The large number of markers available compared with phenotypes represents one of the main issues in genomic selection. In this work, principal component analysis was used to reduce the number of predictors for calculating genomic breeding values (GEBV). Bulls of 2 cattle breeds farmed in Italy (634 Brown and 469 Simmental) were genotyped with the 54K Illumina beadchip (Illumina Inc., San Diego, CA). After data editing, 37,254 and 40,179 single nucleotide polymorphisms (SNP) were retained for Brown and Simmental, respectively. Principal component analysis carried out on the SNP genotype matrix extracted 2,257 and 3,596 new variables in the 2 breeds, respectively. Bulls were sorted by birth year to create reference and prediction populations. The effect of principal components on deregressed proofs in reference animals was estimated with a BLUP model. Results were compared with those obtained by using SNP genotypes as predictors with either the BLUP or Bayes_A method. Traits considered were milk, fat, and protein yields, fat and protein percentages, and somatic cell score. The GEBV were obtained for prediction population by blending direct genomic prediction and pedigree indexes. No substantial differences were observed in squared correlations between GEBV and EBV in prediction animals between the 3 methods in the 2 breeds. The principal component analysis method allowed for a reduction of about 90% in the number of independent variables when predicting direct genomic values, with a substantial decrease in calculation time and without loss of accuracy. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Binding site and affinity prediction of general anesthetics to protein targets using docking.

PubMed

Liu, Renyu; Perez-Aguilar, Jose Manuel; Liang, David; Saven, Jeffery G

2012-05-01

The protein targets for general anesthetics remain unclear. A tool to predict anesthetic binding for potential binding targets is needed. In this study, we explored whether a computational method, AutoDock, could serve as such a tool. High-resolution crystal data of water-soluble proteins (cytochrome C, apoferritin, and human serum albumin), and a membrane protein (a pentameric ligand-gated ion channel from Gloeobacter violaceus [GLIC]) were used. Isothermal titration calorimetry (ITC) experiments were performed to determine anesthetic affinity in solution conditions for apoferritin. Docking calculations were performed using DockingServer with the Lamarckian genetic algorithm and the Solis and Wets local search method (http://www.dockingserver.com/web). Twenty general anesthetics were docked into apoferritin. The predicted binding constants were compared with those obtained from ITC experiments for potential correlations. In the case of apoferritin, details of the binding site and their interactions were compared with recent cocrystallization data. Docking calculations for 6 general anesthetics currently used in clinical settings (isoflurane, sevoflurane, desflurane, halothane, propofol, and etomidate) with known 50% effective concentration (EC(50)) values were also performed in all tested proteins. The binding constants derived from docking experiments were compared with known EC(50) values and octanol/water partition coefficients for the 6 general anesthetics. All 20 general anesthetics docked unambiguously into the anesthetic binding site identified in the crystal structure of apoferritin. The binding constants for 20 anesthetics obtained from the docking calculations correlate significantly with those obtained from ITC experiments (P = 0.04). In the case of GLIC, the identified anesthetic binding sites in the crystal structure are among the docking predicted binding sites, but not the top ranked site. Docking calculations suggest a most probable binding site located in the extracellular domain of GLIC. The predicted affinities correlated significantly with the known EC(50) values for the 6 frequently used anesthetics in GLIC for the site identified in the experimental crystal data (P = 0.006). However, predicted affinities in apoferritin, human serum albumin, and cytochrome C did not correlate with these 6 anesthetics' known experimental EC(50) values. A weak correlation between the predicted affinities and the octanol/water partition coefficients was observed for the sites in GLIC. We demonstrated that anesthetic binding sites and relative affinities can be predicted using docking calculations in an automatic docking server (AutoDock) for both water-soluble and membrane proteins. Correlation of predicted affinity and EC(50) for 6 frequently used general anesthetics was only observed in GLIC, a member of a protein family relevant to anesthetic mechanism.

Prediction of parenteral nutrition osmolarity by digital refractometry.

PubMed

Chang, Wei-Kuo; Yeh, Ming-Kung

2011-05-01

Infusion of high-osmolarity parenteral nutrition (PN) formulations into a peripheral vein will damage the vessel. In this study, the authors developed a refractometric method to predict PN formulation osmolarity for patients receiving PN. Nutrients in PN formulations were prepared for Brix value and osmolality measurement. Brix value and osmolality measurement of the dextrose, amino acids, and electrolytes were used to evaluate the limiting factor of PN osmolarity prediction. A best-fit equation was generated to predict PN osmolarity (mOsm/L): 81.05 × Brix value--116.33 (R(2) > 0.99). To validate the PN osmolarity prediction by these 4 equations, a total of 500 PN admixtures were tested. The authors found strong linear relationships between the Brix values and the osmolality measurement of dextrose (R(2) = 0.97), amino acids (R(2) = 0.99), and electrolytes (R(2) > 0.96). When PN-measured osmolality was between 600 and 900 mOsm/kg, approximately 43%, 29%, 43%, and 0% of the predicted osmolarity obtained by equations 1, 2, 3, and 4 were outside the acceptable 90% to 110% confidence interval range, respectively. When measured osmolality was between 900 and 1,500 mOsm/kg, 31%, 100%, 85%, and 15% of the predicted osmolarity by equations 1, 2, 3, and 4 were outside the acceptable 90% to 110% confidence interval range, respectively. The refractive method permits accurate PN osmolarity prediction and reasonable quality assurance before PN formulation administration.

The use of artificial neural networks and multiple linear regression to predict rate of medical waste generation

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

Jahandideh, Sepideh; Jahandideh, Samad; Asadabadi, Ebrahim Barzegari

2009-11-15

Prediction of the amount of hospital waste production will be helpful in the storage, transportation and disposal of hospital waste management. Based on this fact, two predictor models including artificial neural networks (ANNs) and multiple linear regression (MLR) were applied to predict the rate of medical waste generation totally and in different types of sharp, infectious and general. In this study, a 5-fold cross-validation procedure on a database containing total of 50 hospitals of Fars province (Iran) were used to verify the performance of the models. Three performance measures including MAR, RMSE and R{sup 2} were used to evaluate performancemore » of models. The MLR as a conventional model obtained poor prediction performance measure values. However, MLR distinguished hospital capacity and bed occupancy as more significant parameters. On the other hand, ANNs as a more powerful model, which has not been introduced in predicting rate of medical waste generation, showed high performance measure values, especially 0.99 value of R{sup 2} confirming the good fit of the data. Such satisfactory results could be attributed to the non-linear nature of ANNs in problem solving which provides the opportunity for relating independent variables to dependent ones non-linearly. In conclusion, the obtained results showed that our ANN-based model approach is very promising and may play a useful role in developing a better cost-effective strategy for waste management in future.« less

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.

Predicting drug-induced liver injury in human with Naïve Bayes classifier approach.

PubMed

Zhang, Hui; Ding, Lan; Zou, Yi; Hu, Shui-Qing; Huang, Hai-Guo; Kong, Wei-Bao; Zhang, Ji

2016-10-01

Drug-induced liver injury (DILI) is one of the major safety concerns in drug development. Although various toxicological studies assessing DILI risk have been developed, these methods were not sufficient in predicting DILI in humans. Thus, developing new tools and approaches to better predict DILI risk in humans has become an important and urgent task. In this study, we aimed to develop a computational model for assessment of the DILI risk with using a larger scale human dataset and Naïve Bayes classifier. The established Naïve Bayes prediction model was evaluated by 5-fold cross validation and an external test set. For the training set, the overall prediction accuracy of the 5-fold cross validation was 94.0 %. The sensitivity, specificity, positive predictive value and negative predictive value were 97.1, 89.2, 93.5 and 95.1 %, respectively. The test set with the concordance of 72.6 %, sensitivity of 72.5 %, specificity of 72.7 %, positive predictive value of 80.4 %, negative predictive value of 63.2 %. Furthermore, some important molecular descriptors related to DILI risk and some toxic/non-toxic fragments were identified. Thus, we hope the prediction model established here would be employed for the assessment of human DILI risk, and the obtained molecular descriptors and substructures should be taken into consideration in the design of new candidate compounds to help medicinal chemists rationally select the chemicals with the best prospects to be effective and safe.

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.

A comparison of the calculated and experimental off-design performance of a radial flow turbine

NASA Technical Reports Server (NTRS)

Tirres, Lizet

1992-01-01

Off design aerodynamic performance of the solid version of a cooled radial inflow turbine is analyzed. Rotor surface static pressure data and other performance parameters were obtained experimentally. Overall stage performance and turbine blade surface static to inlet total pressure ratios were calculated by using a quasi-three dimensional inviscid code. The off design prediction capability of this code for radial inflow turbines shows accurate static pressure prediction. Solutions show a difference of 3 to 5 points between the experimentally obtained efficiencies and the calculated values.

A comparison of the calculated and experimental off-design performance of a radial flow turbine

NASA Technical Reports Server (NTRS)

Tirres, Lizet

1991-01-01

Off design aerodynamic performance of the solid version of a cooled radial inflow turbine is analyzed. Rotor surface static pressure data and other performance parameters were obtained experimentally. Overall stage performance and turbine blade surface static to inlet total pressure ratios were calculated by using a quasi-three dimensional inviscid code. The off design prediction capability of this code for radial inflow turbines shows accurate static pressure prediction. Solutions show a difference of 3 to 5 points between the experimentally obtained efficiencies and the calculated values.

Bayesian inference based on dual generalized order statistics from the exponentiated Weibull model

NASA Astrophysics Data System (ADS)

Al Sobhi, Mashail M.

2015-02-01

Bayesian estimation for the two parameters and the reliability function of the exponentiated Weibull model are obtained based on dual generalized order statistics (DGOS). Also, Bayesian prediction bounds for future DGOS from exponentiated Weibull model are obtained. The symmetric and asymmetric loss functions are considered for Bayesian computations. The Markov chain Monte Carlo (MCMC) methods are used for computing the Bayes estimates and prediction bounds. The results have been specialized to the lower record values. Comparisons are made between Bayesian and maximum likelihood estimators via Monte Carlo simulation.

Plateletpheresis efficiency and mathematical correction of software-derived platelet yield prediction: A linear regression and ROC modeling approach.

PubMed

Jaime-Pérez, José Carlos; Jiménez-Castillo, Raúl Alberto; Vázquez-Hernández, Karina Elizabeth; Salazar-Riojas, Rosario; Méndez-Ramírez, Nereida; Gómez-Almaguer, David

2017-10-01

Advances in automated cell separators have improved the efficiency of plateletpheresis and the possibility of obtaining double products (DP). We assessed cell processor accuracy of predicted platelet (PLT) yields with the goal of a better prediction of DP collections. This retrospective proof-of-concept study included 302 plateletpheresis procedures performed on a Trima Accel v6.0 at the apheresis unit of a hematology department. Donor variables, software predicted yield and actual PLT yield were statistically evaluated. Software prediction was optimized by linear regression analysis and its optimal cut-off to obtain a DP assessed by receiver operating characteristic curve (ROC) modeling. Three hundred and two plateletpheresis procedures were performed; in 271 (89.7%) occasions, donors were men and in 31 (10.3%) women. Pre-donation PLT count had the best direct correlation with actual PLT yield (r = 0.486. P < .001). Means of software machine-derived values differed significantly from actual PLT yield, 4.72 × 10 11 vs.6.12 × 10 11 , respectively, (P < .001). The following equation was developed to adjust these values: actual PLT yield= 0.221 + (1.254 × theoretical platelet yield). ROC curve model showed an optimal apheresis device software prediction cut-off of 4.65 × 10 11 to obtain a DP, with a sensitivity of 82.2%, specificity of 93.3%, and an area under the curve (AUC) of 0.909. Trima Accel v6.0 software consistently underestimated PLT yields. Simple correction derived from linear regression analysis accurately corrected this underestimation and ROC analysis identified a precise cut-off to reliably predict a DP. © 2016 Wiley Periodicals, Inc.

Key Technology of Real-Time Road Navigation Method Based on Intelligent Data Research

PubMed Central

Tang, Haijing; Liang, Yu; Huang, Zhongnan; Wang, Taoyi; He, Lin; Du, Yicong; Ding, Gangyi

2016-01-01

The effect of traffic flow prediction plays an important role in routing selection. Traditional traffic flow forecasting methods mainly include linear, nonlinear, neural network, and Time Series Analysis method. However, all of them have some shortcomings. This paper analyzes the existing algorithms on traffic flow prediction and characteristics of city traffic flow and proposes a road traffic flow prediction method based on transfer probability. This method first analyzes the transfer probability of upstream of the target road and then makes the prediction of the traffic flow at the next time by using the traffic flow equation. Newton Interior-Point Method is used to obtain the optimal value of parameters. Finally, it uses the proposed model to predict the traffic flow at the next time. By comparing the existing prediction methods, the proposed model has proven to have good performance. It can fast get the optimal value of parameters faster and has higher prediction accuracy, which can be used to make real-time traffic flow prediction. PMID:27872637

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

Evaluation of the impact of computed high b-value diffusion-weighted imaging on prostate cancer detection.

PubMed

Verma, Sadhna; Sarkar, Saradwata; Young, Jason; Venkataraman, Rajesh; Yang, Xu; Bhavsar, Anil; Patil, Nilesh; Donovan, James; Gaitonde, Krishnanath

2016-05-01

The purpose of this study was to compare high b-value (b = 2000 s/mm(2)) acquired diffusion-weighted imaging (aDWI) with computed DWI (cDWI) obtained using four diffusion models-mono-exponential (ME), intra-voxel incoherent motion (IVIM), stretched exponential (SE), and diffusional kurtosis (DK)-with respect to lesion visibility, conspicuity, contrast, and ability to predict significant prostate cancer (PCa). Ninety four patients underwent 3 T MRI including acquisition of b = 2000 s/mm(2) aDWI and low b-value DWI. High b = 2000 s/mm(2) cDWI was obtained using ME, IVIM, SE, and DK models. All images were scored on quality independently by three radiologists. Lesions were identified on all images and graded for lesion conspicuity. For a subset of lesions for which pathological truth was established, lesion-to-background contrast ratios (LBCRs) were computed and binomial generalized linear mixed model analysis was conducted to compare clinically significant PCa predictive capabilities of all DWI. For all readers and all models, cDWI demonstrated higher ratings for image quality and lesion conspicuity than aDWI except DK (p < 0.001). The LBCRs of ME, IVIM, and SE were significantly higher than LBCR of aDWI (p < 0.001). Receiver Operating Characteristic curves obtained from binomial generalized linear mixed model analysis demonstrated higher Area Under the Curves for ME, SE, IVIM, and aDWI compared to DK or PSAD alone in predicting significant PCa. High b-value cDWI using ME, IVIM, and SE diffusion models provide better image quality, lesion conspicuity, and increased LBCR than high b-value aDWI. Using cDWI can potentially provide comparable sensitivity and specificity for detecting significant PCa as high b-value aDWI without increased scan times and image degradation artifacts.

Determination of the Spatial Distribution in Hydraulic Conductivity Using Genetic Algorithm Optimization

NASA Astrophysics Data System (ADS)

Aksoy, A.; Lee, J. H.; Kitanidis, P. K.

2016-12-01

Heterogeneity in hydraulic conductivity (K) impacts the transport and fate of contaminants in subsurface as well as design and operation of managed aquifer recharge (MAR) systems. Recently, improvements in computational resources and availability of big data through electrical resistivity tomography (ERT) and remote sensing have provided opportunities to better characterize the subsurface. Yet, there is need to improve prediction and evaluation methods in order to obtain information from field measurements for better field characterization. In this study, genetic algorithm optimization, which has been widely used in optimal aquifer remediation designs, was used to determine the spatial distribution of K. A hypothetical 2 km by 2 km aquifer was considered. A genetic algorithm library, PGAPack, was linked with a fast Fourier transform based random field generator as well as a groundwater flow and contaminant transport simulation model (BIO2D-KE). The objective of the optimization model was to minimize the total squared error between measured and predicted field values. It was assumed measured K values were available through ERT. Performance of genetic algorithm in predicting the distribution of K was tested for different cases. In the first one, it was assumed that observed K values were evaluated using the random field generator only as the forward model. In the second case, as well as K-values obtained through ERT, measured head values were incorporated into evaluation in which BIO2D-KE and random field generator were used as the forward models. Lastly, tracer concentrations were used as additional information in the optimization model. Initial results indicated enhanced performance when random field generator and BIO2D-KE are used in combination in predicting the spatial distribution in K.

Colossal dielectric response in all-ceramic percolative composite 0.65Pb(Mg1/3Nb2/3)O3-0.35PbTiO3-Pb2Ru2O6.5

NASA Astrophysics Data System (ADS)

Bobnar, V.; Hrovat, M.; Holc, J.; Filipič, C.; Levstik, A.; Kosec, M.

2009-02-01

An exceptionally high dielectric constant was obtained by making use of the conductive percolative phenomenon in all-ceramic composite, comprising of Pb2Ru2O6.5 with high electrical conductivity denoted as the conductive phase and ferroelectric 0.65Pb(Mg1/3Nb2/3)O3-0.35PbTiO3 (PMN-PT) perovskite systems. Structural analysis revealed a uniform distribution of conductive ceramic grains within the PMN-PT matrix. Consequently, the dielectric response in the PMN-PT-Pb2Ru2O6.5 composite follows the predictions of the percolation theory. Thus, close to the percolation point exceptionally high values of the dielectric constant were obtained—values higher than 105 were detected at room temperature at 1 kHz. Fit of the data, obtained for samples of different compositions, revealed critical exponent and percolation point, which reasonably agree with the theoretically predicted values.

Preparation of Curcumin Loaded Egg Albumin Nanoparticles Using Acetone and Optimization of Desolvation Process.

PubMed

Aniesrani Delfiya, D S; Thangavel, K; Amirtham, D

2016-04-01

In this study, acetone was used as a desolvating agent to prepare the curcumin-loaded egg albumin nanoparticles. Response surface methodology was employed to analyze the influence of process parameters namely concentration (5-15%w/v) and pH (5-7) of egg albumin solution on solubility, curcumin loading and entrapment efficiency, nanoparticles yield and particle size. Optimum processing conditions obtained from response surface analysis were found to be the egg albumin solution concentration of 8.85%w/v and pH of 5. At this optimum condition, the solubility of 33.57%, curcumin loading of 4.125%, curcumin entrapment efficiency of 55.23%, yield of 72.85% and particles size of 232.6 nm were obtained and these values were related to the values which are predicted using polynomial model equations. Thus, the model equations generated for each response was validated and it can be used to predict the response values at any concentration and pH.

Application of Fluorescence Spectrometry With Multivariate Calibration to the Enantiomeric Recognition of Fluoxetine in Pharmaceutical Preparations.

PubMed

Poláček, Roman; Májek, Pavel; Hroboňová, Katarína; Sádecká, Jana

2016-04-01

Fluoxetine is the most prescribed antidepressant chiral drug worldwide. Its enantiomers have a different duration of serotonin inhibition. A novel simple and rapid method for determination of the enantiomeric composition of fluoxetine in pharmaceutical pills is presented. Specifically, emission, excitation, and synchronous fluorescence techniques were employed to obtain the spectral data, which with multivariate calibration methods, namely, principal component regression (PCR) and partial least square (PLS), were investigated. The chiral recognition of fluoxetine enantiomers in the presence of β-cyclodextrin was based on diastereomeric complexes. The results of the multivariate calibration modeling indicated good prediction abilities. The obtained results for tablets were compared with those from chiral HPLC and no significant differences are shown by Fisher's (F) test and Student's t-test. The smallest residuals between reference or nominal values and predicted values were achieved by multivariate calibration of synchronous fluorescence spectral data. This conclusion is supported by calculated values of the figure of merit.

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.

EVALUATING RISK-PREDICTION MODELS USING DATA FROM ELECTRONIC HEALTH RECORDS.

PubMed

Wang, L E; Shaw, Pamela A; Mathelier, Hansie M; Kimmel, Stephen E; French, Benjamin

2016-03-01

The availability of data from electronic health records facilitates the development and evaluation of risk-prediction models, but estimation of prediction accuracy could be limited by outcome misclassification, which can arise if events are not captured. We evaluate the robustness of prediction accuracy summaries, obtained from receiver operating characteristic curves and risk-reclassification methods, if events are not captured (i.e., "false negatives"). We derive estimators for sensitivity and specificity if misclassification is independent of marker values. In simulation studies, we quantify the potential for bias in prediction accuracy summaries if misclassification depends on marker values. We compare the accuracy of alternative prognostic models for 30-day all-cause hospital readmission among 4548 patients discharged from the University of Pennsylvania Health System with a primary diagnosis of heart failure. Simulation studies indicate that if misclassification depends on marker values, then the estimated accuracy improvement is also biased, but the direction of the bias depends on the direction of the association between markers and the probability of misclassification. In our application, 29% of the 1143 readmitted patients were readmitted to a hospital elsewhere in Pennsylvania, which reduced prediction accuracy. Outcome misclassification can result in erroneous conclusions regarding the accuracy of risk-prediction models.

[Prediction of soil nutrients spatial distribution based on neural network model combined with goestatistics].

PubMed

Li, Qi-Quan; Wang, Chang-Quan; Zhang, Wen-Jiang; Yu, Yong; Li, Bing; Yang, Juan; Bai, Gen-Chuan; Cai, Yan

2013-02-01

In this study, a radial basis function neural network model combined with ordinary kriging (RBFNN_OK) was adopted to predict the spatial distribution of soil nutrients (organic matter and total N) in a typical hilly region of Sichuan Basin, Southwest China, and the performance of this method was compared with that of ordinary kriging (OK) and regression kriging (RK). All the three methods produced the similar soil nutrient maps. However, as compared with those obtained by multiple linear regression model, the correlation coefficients between the measured values and the predicted values of soil organic matter and total N obtained by neural network model increased by 12. 3% and 16. 5% , respectively, suggesting that neural network model could more accurately capture the complicated relationships between soil nutrients and quantitative environmental factors. The error analyses of the prediction values of 469 validation points indicated that the mean absolute error (MAE) , mean relative error (MRE), and root mean squared error (RMSE) of RBFNN_OK were 6.9%, 7.4%, and 5. 1% (for soil organic matter), and 4.9%, 6.1% , and 4.6% (for soil total N) smaller than those of OK (P<0.01), and 2.4%, 2.6% , and 1.8% (for soil organic matter), and 2.1%, 2.8%, and 2.2% (for soil total N) smaller than those of RK, respectively (P<0.05).

Promising thermoelectric properties of phosphorenes.

PubMed

Sevik, Cem; Sevinçli, Hâldun

2016-09-02

Electronic, phononic, and thermoelectric transport properties of single layer black- and blue-phosphorene structures are investigated with first-principles based ballistic electron and phonon transport calculations employing hybrid functionals. The maximum values of room temperature thermoelectric figure of merit, ZT corresponding to armchair and zigzag directions of black-phosphorene, ∼0.5 and ∼0.25, are calculated as rather smaller than those obtained with first-principles based semiclassical Boltzmann transport theory calculations. On the other hand, the maximum value of room temperature ZT of blue-phosphorene is predicted to be substantially high and remarkable values as high as 2.5 are obtained for elevated temperatures. Besides the fact that these figures are obtained at the ballistic limit, our findings mark the strong possibility of high thermoelectric performance of blue-phosphorene in new generation thermoelectric applications.

Semi-empirical correlation for binary interaction parameters of the Peng-Robinson equation of state with the van der Waals mixing rules for the prediction of high-pressure vapor-liquid equilibrium.

PubMed

Fateen, Seif-Eddeen K; Khalil, Menna M; Elnabawy, Ahmed O

2013-03-01

Peng-Robinson equation of state is widely used with the classical van der Waals mixing rules to predict vapor liquid equilibria for systems containing hydrocarbons and related compounds. This model requires good values of the binary interaction parameter kij . In this work, we developed a semi-empirical correlation for kij partly based on the Huron-Vidal mixing rules. We obtained values for the adjustable parameters of the developed formula for over 60 binary systems and over 10 categories of components. The predictions of the new equation system were slightly better than the constant-kij model in most cases, except for 10 systems whose predictions were considerably improved with the new correlation.

Forgetting in Reinforcement Learning Links Sustained Dopamine Signals to Motivation

PubMed Central

Morita, Kenji

2016-01-01

It has been suggested that dopamine (DA) represents reward-prediction-error (RPE) defined in reinforcement learning and therefore DA responds to unpredicted but not predicted reward. However, recent studies have found DA response sustained towards predictable reward in tasks involving self-paced behavior, and suggested that this response represents a motivational signal. We have previously shown that RPE can sustain if there is decay/forgetting of learned-values, which can be implemented as decay of synaptic strengths storing learned-values. This account, however, did not explain the suggested link between tonic/sustained DA and motivation. In the present work, we explored the motivational effects of the value-decay in self-paced approach behavior, modeled as a series of ‘Go’ or ‘No-Go’ selections towards a goal. Through simulations, we found that the value-decay can enhance motivation, specifically, facilitate fast goal-reaching, albeit counterintuitively. Mathematical analyses revealed that underlying potential mechanisms are twofold: (1) decay-induced sustained RPE creates a gradient of ‘Go’ values towards a goal, and (2) value-contrasts between ‘Go’ and ‘No-Go’ are generated because while chosen values are continually updated, unchosen values simply decay. Our model provides potential explanations for the key experimental findings that suggest DA's roles in motivation: (i) slowdown of behavior by post-training blockade of DA signaling, (ii) observations that DA blockade severely impairs effortful actions to obtain rewards while largely sparing seeking of easily obtainable rewards, and (iii) relationships between the reward amount, the level of motivation reflected in the speed of behavior, and the average level of DA. These results indicate that reinforcement learning with value-decay, or forgetting, provides a parsimonious mechanistic account for the DA's roles in value-learning and motivation. Our results also suggest that when biological systems for value-learning are active even though learning has apparently converged, the systems might be in a state of dynamic equilibrium, where learning and forgetting are balanced. PMID:27736881

Forgetting in Reinforcement Learning Links Sustained Dopamine Signals to Motivation.

PubMed

Kato, Ayaka; Morita, Kenji

2016-10-01

It has been suggested that dopamine (DA) represents reward-prediction-error (RPE) defined in reinforcement learning and therefore DA responds to unpredicted but not predicted reward. However, recent studies have found DA response sustained towards predictable reward in tasks involving self-paced behavior, and suggested that this response represents a motivational signal. We have previously shown that RPE can sustain if there is decay/forgetting of learned-values, which can be implemented as decay of synaptic strengths storing learned-values. This account, however, did not explain the suggested link between tonic/sustained DA and motivation. In the present work, we explored the motivational effects of the value-decay in self-paced approach behavior, modeled as a series of 'Go' or 'No-Go' selections towards a goal. Through simulations, we found that the value-decay can enhance motivation, specifically, facilitate fast goal-reaching, albeit counterintuitively. Mathematical analyses revealed that underlying potential mechanisms are twofold: (1) decay-induced sustained RPE creates a gradient of 'Go' values towards a goal, and (2) value-contrasts between 'Go' and 'No-Go' are generated because while chosen values are continually updated, unchosen values simply decay. Our model provides potential explanations for the key experimental findings that suggest DA's roles in motivation: (i) slowdown of behavior by post-training blockade of DA signaling, (ii) observations that DA blockade severely impairs effortful actions to obtain rewards while largely sparing seeking of easily obtainable rewards, and (iii) relationships between the reward amount, the level of motivation reflected in the speed of behavior, and the average level of DA. These results indicate that reinforcement learning with value-decay, or forgetting, provides a parsimonious mechanistic account for the DA's roles in value-learning and motivation. Our results also suggest that when biological systems for value-learning are active even though learning has apparently converged, the systems might be in a state of dynamic equilibrium, where learning and forgetting are balanced.

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.

Vehicle dynamic prediction systems with on-line identification of vehicle parameters and road conditions.

PubMed

Hsu, Ling-Yuan; Chen, Tsung-Lin

2012-11-13

This paper presents a vehicle dynamics prediction system, which consists of a sensor fusion system and a vehicle parameter identification system. This sensor fusion system can obtain the six degree-of-freedom vehicle dynamics and two road angles without using a vehicle model. The vehicle parameter identification system uses the vehicle dynamics from the sensor fusion system to identify ten vehicle parameters in real time, including vehicle mass, moment of inertial, and road friction coefficients. With above two systems, the future vehicle dynamics is predicted by using a vehicle dynamics model, obtained from the parameter identification system, to propagate with time the current vehicle state values, obtained from the sensor fusion system. Comparing with most existing literatures in this field, the proposed approach improves the prediction accuracy both by incorporating more vehicle dynamics to the prediction system and by on-line identification to minimize the vehicle modeling errors. Simulation results show that the proposed method successfully predicts the vehicle dynamics in a left-hand turn event and a rollover event. The prediction inaccuracy is 0.51% in a left-hand turn event and 27.3% in a rollover event.

Vehicle Dynamic Prediction Systems with On-Line Identification of Vehicle Parameters and Road Conditions

PubMed Central

Hsu, Ling-Yuan; Chen, Tsung-Lin

2012-01-01

This paper presents a vehicle dynamics prediction system, which consists of a sensor fusion system and a vehicle parameter identification system. This sensor fusion system can obtain the six degree-of-freedom vehicle dynamics and two road angles without using a vehicle model. The vehicle parameter identification system uses the vehicle dynamics from the sensor fusion system to identify ten vehicle parameters in real time, including vehicle mass, moment of inertial, and road friction coefficients. With above two systems, the future vehicle dynamics is predicted by using a vehicle dynamics model, obtained from the parameter identification system, to propagate with time the current vehicle state values, obtained from the sensor fusion system. Comparing with most existing literatures in this field, the proposed approach improves the prediction accuracy both by incorporating more vehicle dynamics to the prediction system and by on-line identification to minimize the vehicle modeling errors. Simulation results show that the proposed method successfully predicts the vehicle dynamics in a left-hand turn event and a rollover event. The prediction inaccuracy is 0.51% in a left-hand turn event and 27.3% in a rollover event. PMID:23202231

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.

Efficient visual coding and the predictability of eye movements on natural movies.

PubMed

Vig, Eleonora; Dorr, Michael; Barth, Erhardt

2009-01-01

We deal with the analysis of eye movements made on natural movies in free-viewing conditions. Saccades are detected and used to label two classes of movie patches as attended and non-attended. Machine learning techniques are then used to determine how well the two classes can be separated, i.e., how predictable saccade targets are. Although very simple saliency measures are used and then averaged to obtain just one average value per scale, the two classes can be separated with an ROC score of around 0.7, which is higher than previously reported results. Moreover, predictability is analysed for different representations to obtain indirect evidence for the likelihood of a particular representation. It is shown that the predictability correlates with the local intrinsic dimension in a movie.

Determination of the acid value of instant noodles: interlaboratory study.

PubMed

Hakoda, Akiko; Sakaida, Kenichi; Suzuki, Tadanao; Yasui, Akemi

2006-01-01

An interlaboratory study was performed to evaluate the method for determining the acid value of instant noodles, based on the Japanese Agricultural Standard (JAS), with extraction of lipid using petroleum ether at a volume of 100 mL to the test portion of 25 g. Thirteen laboratories participated and analyzed 5 test samples as blind duplicates. Statistical treatment revealed that the repeatability (RSDr) of acid value was <6.5%, and the reproducibility (RSDR) of acid value was <9.6%. The HorRat values (RSDR/predicted RSDR) were 1.2-1.8, where the RSDR and the predicted RSDR were obtained in terms of free fatty acids in the noodles per unit weight, using the equation [acid value = percent free fatty acids (as oleic) x 1.99] and the extracted lipid contents. This method was shown to have acceptable precision by the present study.

Friction torque in thrust ball bearings grease lubricated

NASA Astrophysics Data System (ADS)

Ianuş, G.; Dumitraşcu, A. C.; Cârlescu, V.; Olaru, D. N.

2016-08-01

The authors investigated experimentally and theoretically the friction torque in a modified thrust ball bearing having only 3 balls operating at low axial load and lubricated with NGLI-00 and NGLI-2 greases. The experiments were made by using spin-down methodology and the results were compared with the theoretical values based on Biboulet&Houpert's rolling friction equations. Also, the results were compared with the theoretical values obtained with SKF friction model adapted for 3 balls. A very good correlation between experiments and Biboulet_&_Houpert's predicted results was obtained for the two greases. Also was observed that the theoretical values for the friction torque calculated with SKF model adapted for a thrust ball bearing having only 3 balls are smaller that the experimental values.

A novel clinical index for the assessment of RVD in acute pulmonary embolism: Blood pressure index.

PubMed

Ates, Hale; Ates, Ihsan; Kundi, Harun; Arikan, Mehmet Fettah; Yilmaz, Fatma Meric

2017-10-01

This study aims to investigate the role of the blood pressure index (BPI), which is a new index that we developed, in detection of right ventricular dysfunction (RVD) in acute pulmonary embolism (APE). A total of 539 patients, (253 males and 286 females), diagnosed with APE using computer tomography pulmonary angiography were included in the study. The BPI was obtained by dividing systolic blood pressure (SBP) by diastolic blood pressure (DBP). Mean DBP (75±11mmHg vs 63±15mmHg; p<0.001, respectively) was found to be higher in RVD patients compared to those without RVD, whereas BPI (1.5±0.1 vs 1.9±0.2; p<0.001, respectively) was lower. Examining the performance of BPI in prediction of RVD using receiver operating characteristic curve analysis (area under curve±SE=0.975±0.006; p<0.001), it was found that BPI could predict RVD with very high sensitivity (92.8%) and specificity (100%) and had a positive predictive value of 100% and a negative predictive value of 42.1%. According to the analysis, the highest youden index for the optimal prediction value was found to be 0.478 and the BPI≤1.4 was found to predict mortality 68.6% sensitivity and 80.8% specificity (Area under curve±SE=0.777±0.051; p<0.001). We found that BPI was an index with high positive predictive value and low negative predictive value in detection of RVD. Copyright © 2017 Elsevier Inc. All rights reserved.

New regression model for predicting hand-arm vibration (HAV) of Malaysian Army (MA) three-tonne truck steering wheels.

PubMed

Aziz, Shamsul Akmar Ab; Nuawi, Mohd Zaki; Nor, Mohd Jailani Mohd

2015-01-01

The objective of this study was to present a new method for determination of hand-arm vibration (HAV) in Malaysian Army (MA) three-tonne truck steering wheels based on changes in vehicle speed using regression model and the statistical analysis method known as Integrated Kurtosis-Based Algorithm for Z-Notch Filter Technique Vibro (I-kaz Vibro). The test was conducted for two different road conditions, tarmac and dirt roads. HAV exposure was measured using a Brüel & Kjær Type 3649 vibration analyzer, which is capable of recording HAV exposures from steering wheels. The data was analyzed using I-kaz Vibro to determine the HAV values in relation to varying speeds of a truck and to determine the degree of data scattering for HAV data signals. Based on the results obtained, HAV experienced by drivers can be determined using the daily vibration exposure A(8), I-kaz Vibro coefficient (Ƶ(v)(∞)), and the I-kaz Vibro display. The I-kaz Vibro displays also showed greater scatterings, indicating that the values of Ƶ(v)(∞) and A(8) were increasing. Prediction of HAV exposure was done using the developed regression model and graphical representations of Ƶ(v)(∞). The results of the regression model showed that Ƶ(v)(∞) increased when the vehicle speed and HAV exposure increased. For model validation, predicted and measured noise exposures were compared, and high coefficient of correlation (R(2)) values were obtained, indicating that good agreement was obtained between them. By using the developed regression model, we can easily predict HAV exposure from steering wheels for HAV exposure monitoring.

Semiquantitative culture of Gardnerella vaginalis in laboratory determination of nonspecific vaginitis.

PubMed Central

Ratnam, S; Fitzgerald, B L

1983-01-01

To evaluate the usefulness of quantitative cultures of Gardnerella vaginalis in the laboratory determination of nonspecific vaginitis, the actual and relative numbers of G. vaginalis in genital cultures of a general patient population were assessed semiquantitatively, and the laboratory results were then correlated with the clinical findings. Of the 1,585 women studied, 417 (26.3%) yielded G. vaginalis in culture. Of these, only 113 (27.1%) were found to have symptoms and signs consistent with nonspecific vaginitis. G. vaginalis was obtained in pure or predominant growth from 87 of 100 consecutive cases with nonspecific vaginitis and 32 of 100 consecutive cases without the symptoms or signs of vaginitis (P less than 0.001). Hence, the positive predictive value of isolation of G. vaginalis in pure and predominant growths was determined to be 73% (87 of 119). Conversely, G. vaginalis was isolated in mixed or light growth significantly more often from asymptomatic women than from symptomatic patients, i.e., 68 versus 13 cases. Therefore, the negative predictive value of isolation of G. vaginalis in mixed and light growths was found to be 84% (68 of 81). Quantitation of the relative amount of G. vaginalis growth had higher predictive values as compared with the assessment of G. vaginalis growth alone. We conclude that quantitative culture of G. vaginalis is essential to obtain maximum reliability of culture results in the laboratory determination of nonspecific vaginitis. Although quantitated cultures of G. vaginalis have high predictive values, laboratory results must be interpreted in conjunction with the clinical findings. PMID:6604735

The statistical properties and possible causes of polar motion prediction errors

NASA Astrophysics Data System (ADS)

Kosek, Wieslaw; Kalarus, Maciej; Wnek, Agnieszka; Zbylut-Gorska, Maria

2015-08-01

The pole coordinate data predictions from different prediction contributors of the Earth Orientation Parameters Combination of Prediction Pilot Project (EOPCPPP) were studied to determine the statistical properties of polar motion forecasts by looking at the time series of differences between them and the future IERS pole coordinates data. The mean absolute errors, standard deviations as well as the skewness and kurtosis of these differences were computed together with their error bars as a function of prediction length. The ensemble predictions show a little smaller mean absolute errors or standard deviations however their skewness and kurtosis values are similar as the for predictions from different contributors. The skewness and kurtosis enable to check whether these prediction differences satisfy normal distribution. The kurtosis values diminish with the prediction length which means that the probability distribution of these prediction differences is becoming more platykurtic than letptokurtic. Non zero skewness values result from oscillating character of these differences for particular prediction lengths which can be due to the irregular change of the annual oscillation phase in the joint fluid (atmospheric + ocean + land hydrology) excitation functions. The variations of the annual oscillation phase computed by the combination of the Fourier transform band pass filter and the Hilbert transform from pole coordinates data as well as from pole coordinates model data obtained from fluid excitations are in a good agreement.

Thermodynamics of enzyme-catalyzed esterifications: II. Levulinic acid esterification with short-chain alcohols.

PubMed

Altuntepe, Emrah; Emel'yanenko, Vladimir N; Forster-Rotgers, Maximilian; Sadowski, Gabriele; Verevkin, Sergey P; Held, Christoph

2017-10-01

Levulinic acid was esterified with methanol, ethanol, and 1-butanol with the final goal to predict the maximum yield of these equilibrium-limited reactions as function of medium composition. In a first step, standard reaction data (standard Gibbs energy of reaction Δ R g 0 ) were determined from experimental formation properties. Unexpectedly, these Δ R g 0 values strongly deviated from data obtained with classical group contribution methods that are typically used if experimental standard data is not available. In a second step, reaction equilibrium concentrations obtained from esterification catalyzed by Novozym 435 at 323.15 K were measured, and the corresponding activity coefficients of the reacting agents were predicted with perturbed-chain statistical associating fluid theory (PC-SAFT). The so-obtained thermodynamic activities were used to determine Δ R g 0 at 323.15 K. These results could be used to cross-validate Δ R g 0 from experimental formation data. In a third step, reaction-equilibrium experiments showed that equilibrium position of the reactions under consideration depends strongly on the concentration of water and on the ratio of levulinic acid: alcohol in the initial reaction mixtures. The maximum yield of the esters was calculated using Δ R g 0 data from this work and activity coefficients of the reacting agents predicted with PC-SAFT for varying feed composition of the reaction mixtures. The use of the new Δ R g 0 data combined with PC-SAFT allowed good agreement to the measured yields, while predictions based on Δ R g 0 values obtained with group contribution methods showed high deviations to experimental yields.

Application of common y-intercept regression parameters for log Kp vs 1/ T for predicting gas-particle partitioning in the urban environment

NASA Astrophysics Data System (ADS)

Pankow, James F.

Gas-particle partitioning is examined using a partitioning constant Kp = ( F/ TSP)/ A, where F (ng m -3) and A (ng m -3) are the particulate-associated and gas-phase concentrations, respectively, and TSP is the total suspended particulate matter level (μg m -3). Compound-dependent values of Kp depend on temperature ( T) according to Kp = mp/ T + bp. Limitations in data quality can cause errors in estimates of mp and bp obtained by simple linear regression (SLR). However, within a group of similar compounds, the bp values will be similar. By pooling data, an improved set of mp and a single bp can be obtained by common y-intercept regression (CYIR). SLR estimates for mp and bp for polycyclic aromatic hydrocarbons (PAHs) sorbing to urban Osaka particulate matter are available (Yamasaki et al., 1982, Envir. Sci. Technol.16, 189-194), as are CYIR estimates for the same particulate matter (Pankow, 1991, Atmospheric Environment25A, 2229-2239). In this work, a comparison was conducted of the ability of these two sets of mp and bp to predict A/ F ratios for PAHs based on measured T and TSP values for data obtained in other urban locations, specifically: (1) in and near the Baltimore Harbor Tunnel by Benner (1988, Ph.D thesis, University of Maryland) and Benner et al. (1989, Envir. Sci. Technol.23, 1269-1278); and (2) in Chicago by Cotham (1990, Ph.D. thesis, University of South Carolina). In general, the CYIR estimates for mp and bp obtained for Osaka particulate matter were found to be at least as reliable, and for some compounds more reliable than their SLR counterparts in predicting gas-particle ratios for PAHs. This result provides further evidence of the utility of the CYIR approach in quantitating the dependence of log Kp values on 1/ T.

The incremental value of self-reported mental health measures in predicting functional outcomes of veterans.

PubMed

Eisen, Susan V; Bottonari, Kathryn A; Glickman, Mark E; Spiro, Avron; Schultz, Mark R; Herz, Lawrence; Rosenheck, Robert; Rofman, Ethan S

2011-04-01

Research on patient-centered care supports use of patient/consumer self-report measures in monitoring health outcomes. This study examined the incremental value of self-report mental health measures relative to a clinician-rated measure in predicting functional outcomes among mental health service recipients. Participants (n = 446) completed the Behavior and Symptom Identification Scale, the Brief Symptom Inventory, and the Veterans/Rand Short Form-36 at enrollment in the study (T1) and 3 months later (T2). Global Assessment of Functioning (GAF) ratings, mental health service utilization, and psychiatric diagnoses were obtained from administrative data files. Controlling for demographic and clinical variables, results indicated that improvement based on the self-report measures significantly predicted one or more functional outcomes (i.e., decreased likelihood of post-enrollment psychiatric hospitalization and increased likelihood of paid employment), above and beyond the predictive value of the GAF. Inclusion of self-report measures may be a useful addition to performance measurement efforts.

Large calf circumference indicates non-sarcopenia despite body mass

PubMed Central

Kusaka, Satomi; Takahashi, Tetsuya; Hiyama, Yoshinori; Kusumoto, Yasuaki; Tsuchiya, Junko; Umeda, Masaru

2017-01-01

[Purpose] The purpose of this study is to evaluate the applicability of the calf circumference as a tool for screening sarcopenia. [Subjects and Methods] One hundred sixteen community-dwelling elderly females were enrolled. Calf circumference of the dominant leg was measured using a plastic measuring tape. Subjects were divided into 3 groups based on body mass index (BMI); subjects with the values for BMI <18.5 kg/m2; those with BMI 18.5 to 25.0; those with BMI ≥25.0 kg/m2. Positive predictive value and negative predictive value of sarcopenia were calculated based on the obtained cut off values of calf circumference and the diagnosis of sarcopenia in each group. [Results] Prevalence rate of sarcopenia was 9.4% (n=10). Cut off value of the calf circumference was 32.8 cm (sensitivity: 73.0%, specificity: 80.0%, AUC: 0.792). Each BMI group showed high negative predictive value of sarcopenia based on the calf circumference cut off value of 32.8 cm. [Conclusion] These results suggested that to identify non-sarcopenia by larger calf circumference is more reasonable and useful than to identify sarcopenia due to the smaller calf circumference regardless of BMI. PMID:29200625

Alternative metrics for real-ear-to-coupler difference average values in children.

PubMed

Blumsack, Judith T; Clark-Lewis, Sandra; Watts, Kelli M; Wilson, Martha W; Ross, Margaret E; Soles, Lindsey; Ennis, Cydney

2014-10-01

Ideally, individual real-ear-to-coupler difference (RECD) measurements are obtained for pediatric hearing instrument-fitting purposes. When RECD measurements cannot be obtained, age-related average RECDs based on typically developing North American children are used. Evidence suggests that these values may not be appropriate for populations of children with retarded growth patterns. The purpose of this study was to determine if another metric, such as head circumference, height, or weight, can be used for prediction of RECDs in children. Design was a correlational study. For all participants, RECD values in both ears, head circumference, height, and weight were measured. The sample consisted of 68 North American children (ages 3-11 yr). Height, weight, head circumference, and RECDs were measured and were analyzed for both ears at 500, 750, 1000, 1500, 2000, 3000, 4000, and 6000 Hz. A backward elimination multiple-regression analysis was used to determine if age, height, weight, and/or head circumference are significant predictors of RECDs. For the left ear, head circumference was retained as the only statistically significant variable in the final model. For the right ear, head circumference was retained as the only statistically significant independent variable at all frequencies except at 2000 and 4000 Hz. At these latter frequencies, weight was retained as the only statistically significant independent variable after all other variables were eliminated. Head circumference can be considered as a metric for RECD prediction in children when individual measurements cannot be obtained. In developing countries where equipment is often unavailable and stunted growth can reduce the value of using age as a metric, head circumference can be considered as an alternative metric in the prediction of RECDs. American Academy of Audiology.

Evaluation of white blood cell count, neutrophil percentage, and elevated temperature as predictors of bloodstream infection in burn patients.

PubMed

Murray, Clinton K; Hoffmaster, Roselle M; Schmit, David R; Hospenthal, Duane R; Ward, John A; Cancio, Leopoldo C; Wolf, Steven E

2007-07-01

To investigate whether specific values of or changes in temperature, white blood cell count, or neutrophil percentage were predictive of bloodstream infection in burn patients. Retrospective review of electronic records. Intensive care center at the US Army Institute of Surgical Research Burn Center. Burn patients with blood cultures obtained from 2001 to 2004. Temperature recorded at the time blood cultures were obtained; highest temperature in each 6-hour interval during the 24 hours prior to this; white blood cell count and neutrophil percentage at the time of obtaining the blood culture and during the 24 hours preceding the blood culture; demographic data; and total body surface area burned. A total of 1063 blood cultures were obtained from 223 patients. Seventy-three people had 140 blood cultures from which microorganisms were recovered. Organisms that were recovered from blood cultures included 80 that were gram negative, 54 that were gram positive, 3 that were mixed gram positive/gram negative, and 3 yeasts. Although white blood cell count and neutrophil percentage at the time of the culture were statistically different between patients with and patients without bloodstream infection, receiver operating characteristic curve analysis revealed these values to be poor discriminators (receiver operating characteristic curve area = 0.624). Temperature or alterations in temperature in the preceding 24-hour period did not predict presence, absence, or type of bloodstream infection. Temperature, white blood cell count, neutrophil percentage, or changes in these values were not clinically reliable in predicting bloodstream infection. Further work is needed to identify alternative clinical parameters, which should prompt blood culture evaluations in this population.

A two-component rain model for the prediction of attenuation and diversity improvement

NASA Technical Reports Server (NTRS)

Crane, R. K.

1982-01-01

A new model was developed to predict attenuation statistics for a single Earth-satellite or terrestrial propagation path. The model was extended to provide predictions of the joint occurrences of specified or higher attenuation values on two closely spaced Earth-satellite paths. The joint statistics provide the information required to obtain diversity gain or diversity advantage estimates. The new model is meteorologically based. It was tested against available Earth-satellite beacon observations and terrestrial path measurements. The model employs the rain climate region descriptions of the Global rain model. The rms deviation between the predicted and observed attenuation values for the terrestrial path data was 35 percent, a result consistent with the expectations of the Global model when the rain rate distribution for the path is not used in the calculation. Within the United States the rms deviation between measurement and prediction was 36 percent but worldwide it was 79 percent.

Relative value of diverse brain MRI and blood-based biomarkers for predicting cognitive decline in the elderly

NASA Astrophysics Data System (ADS)

Madsen, Sarah K.; Ver Steeg, Greg; Daianu, Madelaine; Mezher, Adam; Jahanshad, Neda; Nir, Talia M.; Hua, Xue; Gutman, Boris A.; Galstyan, Aram; Thompson, Paul M.

2016-03-01

Cognitive decline accompanies many debilitating illnesses, including Alzheimer's disease (AD). In old age, brain tissue loss also occurs along with cognitive decline. Although blood tests are easier to perform than brain MRI, few studies compare brain scans to standard blood tests to see which kinds of information best predict future decline. In 504 older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we first used linear regression to assess the relative value of different types of data to predict cognitive decline, including 196 blood panel biomarkers, 249 MRI biomarkers obtained from the FreeSurfer software, demographics, and the AD-risk gene APOE. A subset of MRI biomarkers was the strongest predictor. There was no specific blood marker that increased predictive accuracy on its own, we found that a novel unsupervised learning method, CorEx, captured weak correlations among blood markers, and the resulting clusters offered unique predictive power.

Binding free energy prediction in strongly hydrophobic biomolecular systems.

PubMed

Charlier, Landry; Nespoulous, Claude; Fiorucci, Sébastien; Antonczak, Serge; Golebiowski, Jérome

2007-11-21

We present a comparison of various computational approaches aiming at predicting the binding free energy in ligand-protein systems where the ligand is located within a highly hydrophobic cavity. The relative binding free energy between similar ligands is obtained by means of the thermodynamic integration (TI) method and compared to experimental data obtained through isothermal titration calorimetry measurements. The absolute free energy of binding prediction was obtained on a similar system (a pyrazine derivative bound to a lipocalin) by TI, potential of mean force (PMF) and also by means of the MMPBSA protocols. Although the TI protocol performs poorly either with an explicit or an implicit solvation scheme, the PMF calculation using an implicit solvation scheme leads to encouraging results, with a prediction of the binding affinity being 2 kcal mol(-1) lower than the experimental value. The use of an implicit solvation scheme appears to be well suited for the study of such hydrophobic systems, due to the lack of water molecules within the binding site.

Suboptimal choice in rats: incentive salience attribution promotes maladaptive decision-making

PubMed Central

Chow, Jonathan J; Smith, Aaron P; Wilson, A George; Zentall, Thomas R; Beckmann, Joshua S

2016-01-01

Stimuli that are more predictive of subsequent reward also function as better conditioned reinforcers. Moreover, stimuli attributed with incentive salience function as more robust conditioned reinforcers. Some theories have suggested that conditioned reinforcement plays an important role in promoting suboptimal choice behavior, like gambling. The present experiments examined how different stimuli, those attributed with incentive salience versus those without, can function in tandem with stimulus-reward predictive utility to promote maladaptive decision-making in rats. One group of rats had lights associated with goal-tracking as the reward-predictive stimuli and another had levers associated with sign-tracking as the reward-predictive stimuli. All rats were first trained on a choice procedure in which the expected value across both alternatives was equivalent but differed in their stimulus-reward predictive utility. Next, the expected value across both alternatives was systematically changed so that the alternative with greater stimulus-reward predictive utility was suboptimal in regard to primary reinforcement. The results demonstrate that in order to obtain suboptimal choice behavior, incentive salience alongside strong stimulus-reward predictive utility may be necessary; thus, maladaptive decision-making can be driven more by the value attributed to stimuli imbued with incentive salience that reliably predict a reward rather than the reward itself. PMID:27993692

Suboptimal choice in rats: Incentive salience attribution promotes maladaptive decision-making.

PubMed

Chow, Jonathan J; Smith, Aaron P; Wilson, A George; Zentall, Thomas R; Beckmann, Joshua S

2017-03-01

Stimuli that are more predictive of subsequent reward also function as better conditioned reinforcers. Moreover, stimuli attributed with incentive salience function as more robust conditioned reinforcers. Some theories have suggested that conditioned reinforcement plays an important role in promoting suboptimal choice behavior, like gambling. The present experiments examined how different stimuli, those attributed with incentive salience versus those without, can function in tandem with stimulus-reward predictive utility to promote maladaptive decision-making in rats. One group of rats had lights associated with goal-tracking as the reward-predictive stimuli and another had levers associated with sign-tracking as the reward-predictive stimuli. All rats were first trained on a choice procedure in which the expected value across both alternatives was equivalent but differed in their stimulus-reward predictive utility. Next, the expected value across both alternatives was systematically changed so that the alternative with greater stimulus-reward predictive utility was suboptimal in regard to primary reinforcement. The results demonstrate that in order to obtain suboptimal choice behavior, incentive salience alongside strong stimulus-reward predictive utility may be necessary; thus, maladaptive decision-making can be driven more by the value attributed to stimuli imbued with incentive salience that reliably predict a reward rather than the reward itself. Copyright © 2016 Elsevier B.V. All rights reserved.

The stopping power and energy straggling of heavy ions in silicon nitride and polypropylene

NASA Astrophysics Data System (ADS)

Mikšová, R.; Hnatowicz, V.; Macková, A.; Malinský, P.; Slepička, P.

2015-07-01

The stopping power and energy straggling of 12C3+ and 16O3+ ions with energies between 4.5 and 7.8 MeV in a 0.166-μm-thin silicon nitride and in 4-μm-thin polypropylene foils were measured by means of an indirect transmission method using a half-covered PIPS detector. Ions scattered from a thin gold layer under a scattering angle of 150° were used. The energy spectra of back-scattered and decelerated ions were registered and evaluated simultaneously. The measured stopping powers were compared with the theoretical predictions simulated by SRIM-2008 and MSTAR codes. SRIM prediction of energy stopping is reasonably close to the experimentally obtained values comparing to MSTAR values. Better agreement between experimental and predicted data was observed for C3+ ion energy losses comparing to O3+ ions. The experimental data from Paul's database and our previous experimental data were also discussed. The obtained experimental energy-straggling data were compared to those calculated by using Bohr's, Yang's models etc. The predictions by Yang are in good agreement with our experiment within a frame of uncertainty of 25%.

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

[Determination of acidity and vitamin C in apples using portable NIR analyzer].

PubMed

Yang, Fan; Li, Ya-Ting; Gu, Xuan; Ma, Jiang; Fan, Xing; Wang, Xiao-Xuan; Zhang, Zhuo-Yong

2011-09-01

Near infrared (NIR) spectroscopy technology based on a portable NIR analyzer, combined with kernel Isomap algorithm and generalized regression neural network (GRNN) has been applied to establishing quantitative models for prediction of acidity and vitamin C in six kinds of apple samples. The obtained results demonstrated that the fitting and the predictive accuracy of the models with kernel Isomap algorithm were satisfactory. The correlation between actual and predicted values of calibration samples (R(c)) obtained by the acidity model was 0.999 4, and for prediction samples (R(p)) was 0.979 9. The root mean square error of prediction set (RMSEP) was 0.055 8. For the vitamin C model, R(c) was 0.989 1, R(p) was 0.927 2, and RMSEP was 4.043 1. Results proved that the portable NIR analyzer can be a feasible tool for the determination of acidity and vitamin C in apples.

Prediction of resilient modulus from soil index properties.

DOT National Transportation Integrated Search

2004-11-01

Subgrade soil characterization in terms of Resilient Modulus (MR) has become crucial for pavement design. For a new : design, MR values are generally obtained by conducting repeated load triaxial tests on reconstituted/undisturbed cylindrical : speci...

Prediction of resilient modulus from soil index properties

DOT National Transportation Integrated Search

2004-11-01

Subgrade soil characterization in terms of Resilient Modulus (MR) has become crucial for pavement design. For a new design, MR values are generally obtained by conducting repeated load triaxial tests on reconstituted/undisturbed cylindrical specimens...

[Efficacy of stool antigen and serologic tests in the diagnosis of Helicobacter pylori in Ecuadorian population].

PubMed

Gómez, Néstor A; Alvarez, Ludwig R; Zapatier, Jorge A; Vargas, Paola E

2005-01-01

To assess the effectiveness in the Ecuadorian population of 2 non-invasive methods for the detection of the Helicobacter pylori: the stool antigens immunoassay (HpSAg) and the determination IgG serum of'antibodies. Eighty six dyspeptic patients were evaluated. In each, Helicobacter pylori presence was investigated with three methods: histology, HpSAg and serology. Sensibility and specificity values were obtained, as well as the positive and negative predictive values. The prevalence of Helicobacter pylori with the 3 tests was 89.53%. The sensibility, specificity, positive predictive value, and negative predictive value were: 42.5%, 69.2%, 88.6% and 17.6% with histology; 69.2%, 42.9%, 78.9% and 31% with HpSAg; 64.2%, 47.7%, 81.1% and 27.3% with serology. In the highly prevalent Ecuadorian setting, HpSAg and serology have relative low sensibility and specificity values. Based on our results, it is necessary to assess for conditions that could alter their results, and strategies to increase the sensibility of these tests, including the histology.

Choice from non-choice: predicting consumer preferences from blood oxygenation level-dependent signals obtained during passive viewing.

PubMed

Levy, Ifat; Lazzaro, Stephanie C; Rutledge, Robb B; Glimcher, Paul W

2011-01-05

Decision-making is often viewed as a two-stage process, where subjective values are first assigned to each option and then the option of the highest value is selected. Converging evidence suggests that these subjective values are represented in the striatum and medial prefrontal cortex (MPFC). A separate line of evidence suggests that activation in the same areas represents the values of rewards even when choice is not required, as in classical conditioning tasks. However, it is unclear whether the same neural mechanism is engaged in both cases. To address this question we measured brain activation with functional magnetic resonance imaging while human subjects passively viewed individual consumer goods. We then sampled activation from predefined regions of interest and used it to predict subsequent choices between the same items made outside of the scanner. Our results show that activation in the striatum and MPFC in the absence of choice predicts subsequent choices, suggesting that these brain areas represent value in a similar manner whether or not choice is required.

Ovarian response to 150 µg corifollitropin alfa in a GnRH-antagonist multiple-dose protocol: a prospective cohort study.

PubMed

Lerman, Tamara; Depenbusch, Marion; Schultze-Mosgau, Askan; von Otte, Soeren; Scheinhardt, Markus; Koenig, Inke; Kamischke, Axel; Macek, Milan; Schwennicke, Arne; Segerer, Sabine; Griesinger, Georg

2017-05-01

The incidence of low (<6 oocytes) and high (>18 oocytes) ovarian response to 150 µg corifollitropin alfa in relation to anti-Müllerian hormone (AMH) and other biomarkers was studied in a multi-centre (n = 5), multi-national, prospective, investigator-initiated, observational cohort study. Infertile women (n = 212), body weight >60 kg, underwent controlled ovarian stimulation in a gonadotrophin-releasing hormone-antagonist multiple-dose protocol. Demographic, sonographic and endocrine parameters were prospectively assessed on cycle day 2 or 3 of a spontaneous menstruation before the administration of 150 µg corifollitropin alfa. Serum AMH showed the best correlation with the number of oocytes obtained among all predictor variables. In receiver-operating characteristic analysis, AMH at a threshold of 0.91 ng/ml showed a sensitivity of 82.4%, specificity of 82.4%, positive predictive value 52.9%and negative predictive value 95.1% for predicting low response (area under the curve [AUC], 95% CI; P-value: 0.853, 0.769-0.936; <0.0001). For predicting high response, the optimal threshold for AMH was 2.58 ng/ml, relating to a sensitivity of 80.0%, specificity 82.1%, positive predictive value 42.5% and negative predictive value 96.1% (AUC, 95% CI; P-value: 0.871, 0.787-0.955; <0.0001). In conclusion, patients with serum AMH concentrations between approximately 0.9 and 2.6 ng/ml were unlikely to show extremes of response. Copyright © 2017. Published by Elsevier Ltd.

A simple model to predict the biodiesel blend density as simultaneous function of blend percent and temperature.

PubMed

Gaonkar, Narayan; Vaidya, R G

2016-05-01

A simple method to estimate the density of biodiesel blend as simultaneous function of temperature and volume percent of biodiesel is proposed. Employing the Kay's mixing rule, we developed a model and investigated theoretically the density of different vegetable oil biodiesel blends as a simultaneous function of temperature and volume percent of biodiesel. Key advantage of the proposed model is that it requires only a single set of density values of components of biodiesel blends at any two different temperatures. We notice that the density of blend linearly decreases with increase in temperature and increases with increase in volume percent of the biodiesel. The lower values of standard estimate of error (SEE = 0.0003-0.0022) and absolute average deviation (AAD = 0.03-0.15 %) obtained using the proposed model indicate the predictive capability. The predicted values found good agreement with the recent available experimental data.

EPRB Gedankenexperiment and Entanglement with Classical Light Waves

NASA Astrophysics Data System (ADS)

Rashkovskiy, Sergey A.

2018-06-01

In this article we show that results similar to those of the Einstein-Podolsky-Rosen-Bohm (EPRB) Gedankenexperiment and entanglement of photons can be obtained using weak classical light waves if we take into account the discrete (atomic) structure of the detectors and a specific nature of the light-atom interaction. We show that the CHSH (Clauser, Horne, Shimony, and Holt) criterion in the EPRB Gedankenexperiment with classical light waves can exceed not only the maximum value SHV=2 that is predicted by the local hidden-variable theories but also the maximum value S_{QM} = 2√2 predicted by quantum mechanics.

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.

Variable selection models for genomic selection using whole-genome sequence data and singular value decomposition.

PubMed

Meuwissen, Theo H E; Indahl, Ulf G; Ødegård, Jørgen

2017-12-27

Non-linear Bayesian genomic prediction models such as BayesA/B/C/R involve iteration and mostly Markov chain Monte Carlo (MCMC) algorithms, which are computationally expensive, especially when whole-genome sequence (WGS) data are analyzed. Singular value decomposition (SVD) of the genotype matrix can facilitate genomic prediction in large datasets, and can be used to estimate marker effects and their prediction error variances (PEV) in a computationally efficient manner. Here, we developed, implemented, and evaluated a direct, non-iterative method for the estimation of marker effects for the BayesC genomic prediction model. The BayesC model assumes a priori that markers have normally distributed effects with probability [Formula: see text] and no effect with probability (1 - [Formula: see text]). Marker effects and their PEV are estimated by using SVD and the posterior probability of the marker having a non-zero effect is calculated. These posterior probabilities are used to obtain marker-specific effect variances, which are subsequently used to approximate BayesC estimates of marker effects in a linear model. A computer simulation study was conducted to compare alternative genomic prediction methods, where a single reference generation was used to estimate marker effects, which were subsequently used for 10 generations of forward prediction, for which accuracies were evaluated. SVD-based posterior probabilities of markers having non-zero effects were generally lower than MCMC-based posterior probabilities, but for some regions the opposite occurred, resulting in clear signals for QTL-rich regions. The accuracies of breeding values estimated using SVD- and MCMC-based BayesC analyses were similar across the 10 generations of forward prediction. For an intermediate number of generations (2 to 5) of forward prediction, accuracies obtained with the BayesC model tended to be slightly higher than accuracies obtained using the best linear unbiased prediction of SNP effects (SNP-BLUP model). When reducing marker density from WGS data to 30 K, SNP-BLUP tended to yield the highest accuracies, at least in the short term. Based on SVD of the genotype matrix, we developed a direct method for the calculation of BayesC estimates of marker effects. Although SVD- and MCMC-based marker effects differed slightly, their prediction accuracies were similar. Assuming that the SVD of the marker genotype matrix is already performed for other reasons (e.g. for SNP-BLUP), computation times for the BayesC predictions were comparable to those of SNP-BLUP.

Evaluation of stroke volume variation obtained by arterial pulse contour analysis to predict fluid responsiveness intraoperatively.

PubMed

Lahner, D; Kabon, B; Marschalek, C; Chiari, A; Pestel, G; Kaider, A; Fleischmann, E; Hetz, H

2009-09-01

Fluid management guided by oesophageal Doppler monitor has been reported to improve perioperative outcome. Stroke volume variation (SVV) is considered a reliable clinical predictor of fluid responsiveness. Consequently, the aim of the present trial was to evaluate the accuracy of SVV determined by arterial pulse contour (APCO) analysis, using the FloTrac/Vigileo system, to predict fluid responsiveness as measured by the oesophageal Doppler. Patients undergoing major abdominal surgery received intraoperative fluid management guided by oesophageal Doppler monitoring. Fluid boluses of 250 ml each were administered in case of a decrease in corrected flow time (FTc) to <350 ms. Patients were connected to a monitoring device, obtaining SVV by APCO. Haemodynamic variables were recorded before and after fluid bolus application. Fluid responsiveness was defined as an increase in stroke volume index >10%. The ability of SVV to predict fluid responsiveness was assessed by calculation of the area under the receiver operating characteristic (ROC) curve. Twenty patients received 67 fluid boluses. Fifty-two of the 67 fluid boluses administered resulted in fluid responsiveness. SVV achieved an area under the ROC curve of 0.512 [confidence interval (CI) 0.32-0.70]. A cut-off point for fluid responsiveness was found for SVV > or =8.5% (sensitivity: 77%; specificity: 43%; positive predictive value: 84%; and negative predictive value: 33%). This prospective, interventional observer-blinded study demonstrates that SVV obtained by APCO, using the FloTrac/Vigileo system, is not a reliable predictor of fluid responsiveness in the setting of major abdominal surgery.

Evaluating Oral Fluid as a Screening Tool for Lead Poisoning.

PubMed

Gardner, Sher Lynn; Geller, Robert J; Hannigan, Robyn; Sun, Yu; Mangla, Anil

2016-11-01

Screening for lead poisoning is necessary in young children, but obtaining the needed blood sample is unpleasant and sometimes very difficult. Use of an alternative screening method that is less unpleasant and less difficult would likely help to increase the percent of children receiving screening. To evaluate the correlation of oral fluid and blood lead in a clinical setting, and to ascertain the acceptability and feasibility of obtaining oral fluid from a young child in the clinical setting. Oral fluid samples were collected from a convenience sample of 431 children aged 6 months to 5 years already due to receive a blood lead test in a primary care clinic. Blood lead results obtained at the same time were available for 407 children. The results of the two tests were compared with the blood lead test considered to be the "gold standard". Data analysis used Pearson correlations, scatter plots, linear regression, ANOVA and Bland-Altman analysis. 431 patients had oral fluid samples available for analysis, and 407 patients had blood samples available. Patients who had both blood concentrations <5 µg/dL and oral fluid values below the screening cutoff value were 223, while eight had both blood concentrations ≥ 5 µg/dL and oral fluid values above the screening threshold. Elevated oral fluid but blood lead values less than the value recommended for further intervention occurred in 176; no patients had elevated blood lead values with below-intervention oral fluid values. The negative predictive value of an oral fluid lead below the screening cutoff value was 100%. The use of oral fluid to screen for elevated body burdens of lead instead of the usual blood lead sample is feasible with a negative predictive value of 100%, while eliminating the need for blood for lead screening in more than half of these children. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Investigation on the Accuracy of Superposition Predictions of Film Cooling Effectiveness

NASA Astrophysics Data System (ADS)

Meng, Tong; Zhu, Hui-ren; Liu, Cun-liang; Wei, Jian-sheng

2018-05-01

Film cooling effectiveness on flat plates with double rows of holes has been studied experimentally and numerically in this paper. This configuration is widely used to simulate the multi-row film cooling on turbine vane. Film cooling effectiveness of double rows of holes and each single row was used to study the accuracy of superposition predictions. Method of stable infrared measurement technique was used to measure the surface temperature on the flat plate. This paper analyzed the factors that affect the film cooling effectiveness including hole shape, hole arrangement, row-to-row spacing and blowing ratio. Numerical simulations were performed to analyze the flow structure and film cooling mechanisms between each film cooling row. Results show that the blowing ratio within the range of 0.5 to 2 has a significant influence on the accuracy of superposition predictions. At low blowing ratios, results obtained by superposition method agree well with the experimental data. While at high blowing ratios, the accuracy of superposition prediction decreases. Another significant factor is hole arrangement. Results obtained by superposition prediction are nearly the same as experimental values of staggered arrangement structures. For in-line configurations, the superposition values of film cooling effectiveness are much higher than experimental data. For different hole shapes, the accuracy of superposition predictions on converging-expanding holes is better than cylinder holes and compound angle holes. For two different hole spacing structures in this paper, predictions show good agreement with the experiment results.

Correlation of MFOLD-predicted DNA secondary structures with separation patterns obtained by capillary electrophoresis single-strand conformation polymorphism (CE-SSCP) analysis.

PubMed

Glavac, Damjan; Potocnik, Uros; Podpecnik, Darja; Zizek, Teofil; Smerkolj, Sava; Ravnik-Glavac, Metka

2002-04-01

We have studied 57 different mutations within three beta-globin gene promoter fragments with sizes 52 bp, 77 bp, and 193 bp by fluorescent capillary electrophoresis CE-SSCP analysis. For each mutation and wild type, energetically most-favorable predicted secondary structures were calculated for sense and antisense strands using the MFOLD DNA-folding algorithm in order to investigate if any correlation exists between predicted DNA structures and actual CE migration time shifts. The overall CE-SSCP detection rate was 100% for all mutations in three studied DNA fragments. For shorter 52 bp and 77 bp DNA fragments we obtained a positive correlation between the migration time shifts and difference in free energy values of predicted secondary structures at all temperatures. For longer 193 bp beta-globin gene fragments with 46 mutations MFOLD predicted different secondary structures for 89% of mutated strands at 25 degrees C and 40 degrees C. However, the magnitude of the mobility shifts did not necessarily correlate with their secondary structures and free energy values except for the sense strand at 40 degrees C where this correlation was statistically significant (r = 0.312, p = 0.033). Results of this study provided more direct insight into the mechanism of CE-SSCP and showed that MFOLD prediction could be helpful in making decisions about the running temperatures and in prediction of CE-SSCP data patterns, especially for shorter (50-100 bp) DNA fragments. Copyright 2002 Wiley-Liss, Inc.

Predictive values of BI-RADS(®) magnetic resonance imaging (MRI) in the detection of breast ductal carcinoma in situ (DCIS).

PubMed

Badan, Gustavo Machado; Piato, Sebastião; Roveda, Décio; de Faria Castro Fleury, Eduardo

2016-10-01

The purpose of this study was to evaluate BI-RADS indicators in the detection of DCIS by MRI. Prospective observational study that started in 2014 and lasted 24 months. A total of 110 consecutive patients were evaluated, who presented with suspicious or highly suspicious microcalcifications on screening mammography (BI-RADS categories 4 and 5) and underwent stereotactic-guided breast biopsy, having had an MRI scan performed prior to biopsy. Altogether, 38 cases were characterized as positive for malignancy, of which 25 were DCIS and 13 were invasive ductal carcinoma cases. MRI had a sensitivity of 96%; specificity of 75.67%; positive predictive value (PPV) for DCIS detection of 57.14%; negative predictive value (NPV) in the detection of DCIS of 98.24%; and an accuracy of 80.80%. BI-RADS as a tool for the detection of DCIS by MRI is a powerful instrument whose sensitivity was higher when compared to that observed for mammography in the literature. Likewise, the PPV obtained by MRI was higher than that observed in the present study for mammography, and the high NPV obtained on MRI scans can provide early evidence to discourage breast biopsy in selected cases. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Estimating forest biomass and volume using airborne laser data

NASA Technical Reports Server (NTRS)

Nelson, Ross; Krabill, William; Tonelli, John

1988-01-01

An airborne pulsed laser system was used to obtain canopy height data over a southern pine forest in Georgia in order to predict ground-measured forest biomass and timber volume. Although biomass and volume estimates obtained from the laser data were variable when compared with the corresponding ground measurements site by site, the present models are found to predict mean total tree volume within 2.6 percent of the ground value, and mean biomass within 2.0 percent. The results indicate that species stratification did not consistently improve regression relationships for four southern pine species.

Space Shuttle third flight /STS-3/ entry RCS analysis. [Reaction Control System

NASA Technical Reports Server (NTRS)

Scallion, W. I.; Compton, H. R.; Suit, W. T.; Powell, R. W.; Blackstock, T. A.; Bates, B. L.

1983-01-01

Flight data obtained from three Space Transportation System orbiter entries (STS-1, 2, and 3) are processed and analyzed to determine the roll interactions caused by the firing of the entry reaction control system (RCS). Comparisons between the flight-derived parameters and the predicted derivatives without interaction effects are made. The flight-derived RCS Plume flow-field interaction effects are independently deduced by direct integration of the incremental changes in the wing upper surface pressures induced by RCS side thruster firings. The separately obtained interaction effects are compared to the predicted values and the differences are discussed.

Melting of genomic DNA: Predictive modeling by nonlinear lattice dynamics

NASA Astrophysics Data System (ADS)

Theodorakopoulos, Nikos

2010-08-01

The melting behavior of long, heterogeneous DNA chains is examined within the framework of the nonlinear lattice dynamics based Peyrard-Bishop-Dauxois (PBD) model. Data for the pBR322 plasmid and the complete T7 phage have been used to obtain model fits and determine parameter dependence on salt content. Melting curves predicted for the complete fd phage and the Y1 and Y2 fragments of the ϕX174 phage without any adjustable parameters are in good agreement with experiment. The calculated probabilities for single base-pair opening are consistent with values obtained from imino proton exchange experiments.

Using Rényi parameter to improve the predictive power of singular value decomposition entropy on stock market

NASA Astrophysics Data System (ADS)

Jiang, Jiaqi; Gu, Rongbao

2016-04-01

This paper generalizes the method of traditional singular value decomposition entropy by incorporating orders q of Rényi entropy. We analyze the predictive power of the entropy based on trajectory matrix using Shanghai Composite Index and Dow Jones Index data in both static test and dynamic test. In the static test on SCI, results of global granger causality tests all turn out to be significant regardless of orders selected. But this entropy fails to show much predictability in American stock market. In the dynamic test, we find that the predictive power can be significantly improved in SCI by our generalized method but not in DJI. This suggests that noises and errors affect SCI more frequently than DJI. In the end, results obtained using different length of sliding window also corroborate this finding.

Earth Observing System/Advanced Microwave Sounding Unit-A (EOS/AMSU-A): Reliability prediction report for module A1 (channels 3 through 15) and module A2 (channels 1 and 2)

NASA Technical Reports Server (NTRS)

Geimer, W.

1995-01-01

This report documents the final reliability prediction performed on the Earth Observing System/Advanced Microwave Sounding Unit-A (EOS/AMSU-A). The A1 Module contains Channels 3 through 15, and is referred to herein as 'EOS/AMSU-A1'. The A2 Module contains Channels 1 and 2, and is referred herein as 'EOS/AMSU-A2'. The 'specified' figures were obtained from Aerojet Reports 8897-1 and 9116-1. The predicted reliability figure for the EOS/AMSU-A1 meets the specified value and provides a Mean Time Between Failures (MTBF) of 74,390 hours. The predicted reliability figure for the EOS/AMSU-A2 meets the specified value and provides a MTBF of 193,110 hours.

Conditional nonlinear optimal perturbations based on the particle swarm optimization and their applications to the predictability problems

NASA Astrophysics Data System (ADS)

Zheng, Qin; Yang, Zubin; Sha, Jianxin; Yan, Jun

2017-02-01

In predictability problem research, the conditional nonlinear optimal perturbation (CNOP) describes the initial perturbation that satisfies a certain constraint condition and causes the largest prediction error at the prediction time. The CNOP has been successfully applied in estimation of the lower bound of maximum predictable time (LBMPT). Generally, CNOPs are calculated by a gradient descent algorithm based on the adjoint model, which is called ADJ-CNOP. This study, through the two-dimensional Ikeda model, investigates the impacts of the nonlinearity on ADJ-CNOP and the corresponding precision problems when using ADJ-CNOP to estimate the LBMPT. Our conclusions are that (1) when the initial perturbation is large or the prediction time is long, the strong nonlinearity of the dynamical model in the prediction variable will lead to failure of the ADJ-CNOP method, and (2) when the objective function has multiple extreme values, ADJ-CNOP has a large probability of producing local CNOPs, hence making a false estimation of the LBMPT. Furthermore, the particle swarm optimization (PSO) algorithm, one kind of intelligent algorithm, is introduced to solve this problem. The method using PSO to compute CNOP is called PSO-CNOP. The results of numerical experiments show that even with a large initial perturbation and long prediction time, or when the objective function has multiple extreme values, PSO-CNOP can always obtain the global CNOP. Since the PSO algorithm is a heuristic search algorithm based on the population, it can overcome the impact of nonlinearity and the disturbance from multiple extremes of the objective function. In addition, to check the estimation accuracy of the LBMPT presented by PSO-CNOP and ADJ-CNOP, we partition the constraint domain of initial perturbations into sufficiently fine grid meshes and take the LBMPT obtained by the filtering method as a benchmark. The result shows that the estimation presented by PSO-CNOP is closer to the true value than the one by ADJ-CNOP with the forecast time increasing.

Salient value similarity, social trust and attitudes toward wildland fire management strategies

Treesearch

J.J. Vaske; J.D. Absher; A.D. Bright

2007-01-01

We predicted that social trust in the USDA Forest Service would mediate the relationship between shared value similarity (SVS) and attitudes toward prescribed burning and mechanical thinning. Data were obtained from a mail survey (n = 532) of rural Colorado residents living in the wildland urban interface (WUI). A structural equation analysis was used to assess the...

Determination of pKa values of new phenacyl-piperidine derivatives by potentiometric titration method in aqueous medium at room temperature (25±0.5oC).

PubMed

Zafar, Shaista; Akhtar, Shamim; Tariq, Talat; Mushtaq, Noushin; Akram, Arfa; Ahmed, Ahsaan; Arif, Muhammad; Naeem, Sabahat; Anwar, Sana

2014-07-01

Dissociation constant (pKa) of ten novel phenacyl derivatives of piperidine were determined by potentiometric titration method in aqueous medium at room temperature (25 ±0.5°C). The sample solutions were prepared in deionized water with ionic strength 0.01M and titrated with 0.1M NaOH solution. In addition, ΔG values were also calculated. Different prediction software programs were used to calculate pKa values too and compared to the experimentally observed pKa values. The experimental and theoretical values were found in close agreement. The results obtained in this research would help to predict the good absorption of the studied compounds and can be selected as lead molecules for the synthesis of CNS active agents because of their lipophilic nature especially compound VII.

Single point estimation of phenytoin dosing: a reappraisal.

PubMed

Koup, J R; Gibaldi, M; Godolphin, W

1981-11-01

A previously proposed method for estimation of phenytoin dosing requirement using a single serum sample obtained 24 hours after intravenous loading dose (18 mg/Kg) has been re-evaluated. Using more realistic values for the volume of distribution of phenytoin (0.4 to 1.2 L/Kg), simulations indicate that the proposed method will fail to consistently predict dosage requirements. Additional simulations indicate that two samples obtained during the 24 hour interval following the iv loading dose could be used to more reliably predict phenytoin dose requirement. Because of the nonlinear relationship which exists between phenytoin dose administration rate (RO) and the mean steady state serum concentration (CSS), small errors in prediction of the required RO result in much larger errors in CSS.

Biot theory and acoustical properties of high porosity fibrous materials and plastic foams

NASA Technical Reports Server (NTRS)

Allard, J.; Aknine, A.

1987-01-01

Experimental values of acoustic wave propagation constant and characteristic impedance in fibrous materials, and normal absorption for two plastic foams, were compared to theoretical predictions obtained with Biot's theory. The best agreement was observed for fibrous materials between Biot's theory and Delany and Bazley experiments for a nearly zero mass coupling parameter. For foams, the lambda/4 structure resonance effect on absorption was calculated by using four-pole modelling of the medium. A significant mass coupling parameter is then necessary for obtaining agreement between the behavior of the measured absorption coefficients and the theoretical predictions. It is shown how the formalism used for predicting foams absorption coefficients may be used for studying the acoustic behavior of multi-layered media.

A comparison of in-cloud HCl concentrations from the NASA/MSFC MDM to measurements for the space shuttle launch

NASA Technical Reports Server (NTRS)

Glasser, M. E.

1981-01-01

The Multilevel Diffusion Model (MDM) Version 5 was modified to include features of more recent versions. The MDM was used to predict in-cloud HCl concentrations for the April 12 launch of the space Shuttle (STS-1). The maximum centerline predictions were compared with measurements of maximum gaseous HCl obtained from aircraft passes through two segments of the fragmented shuttle ground cloud. The model over-predicted the maximum values for gaseous HCl in the lower cloud segment and portrayed the same rate of decay with time as the observed values. However, the decay with time of HCl maximum predicted by the MDM was more rapid than the observed decay for the higher cloud segment, causing the model to under-predict concentrations which were measured late in the life of the cloud. The causes of the tendency for the MDM to be conservative in over-estimating the HCl concentrations in the one case while tending to under-predict concentrations in the other case are discussed.

Predictive value and efficiency of laboratory testing.

PubMed

Galen, R S

1980-11-01

Literature on determining reference values and reference intervals on "normal" or "healthy" individuals is abundant. It is impossible, however, to evaluate a data set of reference values and select a suitable reference interval that will be meaningful for the practice of medicine. The reference interval, no matter how derived statistically, tells us nothing about disease. This is the main reason the concepts of "normal values" have failed us and why "reference values" will prove similarly disappointing. By studying these same constituents in a variety of disease states as well, it will be possible to select "referent values" that will make the test procedure meaningful for diagnostic purposes. In order to obtain meaningful referent values for predicting disease, it is necessary to study not only the "healthy" reference population, but patients with the disease in question, and patients who are free of the disease in question but who have other diseases. Studies of this type are not frequently found for laboratory tests that are in common use today.

Predicting out-of-office blood pressure level using repeated measurements in the clinic: an observational cohort study

PubMed Central

Sheppard, James P.; Holder, Roger; Nichols, Linda; Bray, Emma; Hobbs, F.D. Richard; Mant, Jonathan; Little, Paul; Williams, Bryan; Greenfield, Sheila; McManus, Richard J.

2014-01-01

Objectives: Identification of people with lower (white-coat effect) or higher (masked effect) blood pressure at home compared to the clinic usually requires ambulatory or home monitoring. This study assessed whether changes in SBP with repeated measurement at a single clinic predict subsequent differences between clinic and home measurements. Methods: This study used an observational cohort design and included 220 individuals aged 35–84 years, receiving treatment for hypertension, but whose SBP was not controlled. The characteristics of change in SBP over six clinic readings were defined as the SBP drop, the slope and the quadratic coefficient using polynomial regression modelling. The predictive abilities of these characteristics for lower or higher home SBP readings were investigated with logistic regression and repeated operating characteristic analysis. Results: The single clinic SBP drop was predictive of the white-coat effect with a sensitivity of 90%, specificity of 50%, positive predictive value of 56% and negative predictive value of 88%. Predictive values for the masked effect and those of the slope and quadratic coefficient were slightly lower, but when the slope and quadratic variables were combined, the sensitivity, specificity, positive and negative predictive values for the masked effect were improved to 91, 48, 24 and 97%, respectively. Conclusion: Characteristics obtainable from multiple SBP measurements in a single clinic in patients with treated hypertension appear to reasonably predict those unlikely to have a large white-coat or masked effect, potentially allowing better targeting of out-of-office monitoring in routine clinical practice. PMID:25144295

Development of an enzyme-linked immunosorbent assay for serodiagnosis of ringworm infection in cattle.

PubMed

Bagut, Elena Tatiana; Cambier, Ludivine; Heinen, Marie-Pierre; Cozma, Vasile; Monod, Michel; Mignon, Bernard

2013-08-01

The aim of this study was to develop an in-house enzyme-linked immunosorbent assay (ELISA) for the serological diagnosis of ringworm infection in cattle. We used available recombinant forms of Trichophyton rubrum dipeptidyl peptidase V (TruDppV) and T. rubrum leucin aminopeptidase 2 (TruLap2), which are 98% identical to Trichophyton verrucosum orthologues. Field serum samples from 135 cattle with ringworm infection, as confirmed by direct microscopy, fluorescence microscopy, and PCR, and from 55 cattle without any apparent skin lesions or history of ringworm infection that served as negative controls were used. Sensitivities, specificities, and positive and negative predictive values were determined to evaluate the diagnostic value of our ELISA. Overall, the ELISAs based on recombinant TruDppV and TruLap2 discriminated well between infected animals and healthy controls. Highly significant differences (P < 0.0001, Mann-Whitney U test) were noted between optical density values obtained when sera from infected versus control cattle were tested. The ELISA developed for the detection of specific antibodies against DppV gave 89.6% sensitivity, 92.7% specificity, a 96.8% positive predictive value, and a 78.4% negative predictive value. The recombinant TruLap2-based ELISA displayed 88.1% sensitivity, 90.9% specificity, a 95.9% positive predictive value, and a 75.7% negative predictive value. To the best of our knowledge, this is the first ELISA based on recombinant antigens for assessing immune responses to ringworm infection in cattle; it is particularly suitable for epidemiological studies and also for the evaluation of vaccines and/or vaccination procedures.

Single- and mixture toxicity of three organic UV-filters, ethylhexyl methoxycinnamate, octocrylene, and avobenzone on Daphnia magna.

PubMed

Park, Chang-Beom; Jang, Jiyi; Kim, Sanghun; Kim, Young Jun

2017-03-01

In freshwater environments, aquatic organisms are generally exposed to mixtures of various chemical substances. In this study, we tested the toxicity of three organic UV-filters (ethylhexyl methoxycinnamate, octocrylene, and avobenzone) to Daphnia magna in order to evaluate the combined toxicity of these substances when in they occur in a mixture. The values of effective concentrations (ECx) for each UV-filter were calculated by concentration-response curves; concentration-combinations of three different UV-filters in a mixture were determined by the fraction of components based on EC 25 values predicted by concentration addition (CA) model. The interaction between the UV-filters were also assessed by model deviation ratio (MDR) using observed and predicted toxicity values obtained from mixture-exposure tests and CA model. The results from this study indicated that observed ECx mix (e.g., EC 10mix , EC 25mix , or EC 50mix ) values obtained from mixture-exposure tests were higher than predicted ECx mix (e.g., EC 10mix , EC 25mix , or EC 50mix ) values calculated by CA model. MDR values were also less than a factor of 1.0 in a mixtures of three different UV-filters. Based on these results, we suggest for the first time a reduction of toxic effects in the mixtures of three UV-filters, caused by antagonistic action of the components. Our findings from this study will provide important information for hazard or risk assessment of organic UV-filters, when they existed together in the aquatic environment. To better understand the mixture toxicity and the interaction of components in a mixture, further studies for various combinations of mixture components are also required. Copyright © 2016 Elsevier Inc. All rights reserved.

Uniaxial Drawing of Graphene-PVA Nanocomposites: Improvement in Mechanical Characteristics via Strain-Induced Exfoliation of Graphene

NASA Astrophysics Data System (ADS)

Jan, Rahim; Habib, Amir; Akram, Muhammad Aftab; Zia, Tanveer-ul-Haq; Khan, Ahmad Nawaz

2016-08-01

Polyvinyl alcohol (PVA)-stabilized graphene nanosheets (GNS) of lateral dimension ( L) ~1 μm are obtained via liquid phase exfoliation technique to prepare its composites in the PVA matrix. These composites show low levels of reinforcements due to poor alignment of GNS within the matrix as predicted by the modified Halpin-Tsai model. Drawing these composites up to 200 % strain, a significant improvement in mechanical properties is observed. Maximum values for Young's modulus and strength are ~×4 and ~×2 higher respectively than that of neat PVA. Moreover, the rate of increase of the modulus with GNS volume fraction is up to 700 GPa, higher than the values predicted using the Halpin-Tsai theory. However, alignment along with strain-induced de-aggregation of GNS within composites accounts well for the obtained results as confirmed by X-ray diffraction (XRD) characterization.

Uniaxial Drawing of Graphene-PVA Nanocomposites: Improvement in Mechanical Characteristics via Strain-Induced Exfoliation of Graphene.

PubMed

Jan, Rahim; Habib, Amir; Akram, Muhammad Aftab; Zia, Tanveer-Ul-Haq; Khan, Ahmad Nawaz

2016-12-01

Polyvinyl alcohol (PVA)-stabilized graphene nanosheets (GNS) of lateral dimension (L) ~1 μm are obtained via liquid phase exfoliation technique to prepare its composites in the PVA matrix. These composites show low levels of reinforcements due to poor alignment of GNS within the matrix as predicted by the modified Halpin-Tsai model. Drawing these composites up to 200 % strain, a significant improvement in mechanical properties is observed. Maximum values for Young's modulus and strength are ~×4 and ~×2 higher respectively than that of neat PVA. Moreover, the rate of increase of the modulus with GNS volume fraction is up to 700 GPa, higher than the values predicted using the Halpin-Tsai theory. However, alignment along with strain-induced de-aggregation of GNS within composites accounts well for the obtained results as confirmed by X-ray diffraction (XRD) characterization.

Predictive methods of some optoelectronic properties for blends based on quaternized polysulfones

NASA Astrophysics Data System (ADS)

Dobos, Adina Maria; Filimon, Anca

2017-11-01

Blends based on quaternized polysulfones were investigated in terms of optical and electronic properties. By applying the Bicerano formalism the refractive index and dielectric constant were evaluated. Also, the dielectric constant of these blends was studied as a function of temperature and frequency. As the result of the main chain structure and charged groups, an increase in theoretical values of the refractive index and dielectric constant with increasing of the ionic quaternized units content in the polymer blend occurs. Additionally, decrease in the dielectric constant with the increase of frequency and decrease of temperature was observed. Refractive index and dielectric constant values indicate that the analyzed samples are transparent and can be used in obtaining of materials with applications involving a small polarizability. Thus, the results are important in prediction of the special optoelectronic features of new polymers blends to obtain high-performance materials with applications in electronic and biomedical fields.

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.

Comparison of the Walz Nomogram and Presence of Secondary Circulating Prostate Cells for Predicting Early Biochemical Failure after Radical Prostatectomy for Prostate Cancer in Chilean Men.

PubMed

Murray, Nigel P; Reyes, Eduardo; Orellana, Nelson; Fuentealba, Cynthia; Jacob, Omar

2015-01-01

To determine the utility of secondary circulating prostate cells for predicting early biochemical failure after radical prostatectomy for prostate cancer and compare the results with the Walz nomagram. A single centre, prospective study of men with prostate cancer treated with radical prostatectomy between 2004 and 2014 was conducted, with registration of clinical-pathological details, total serum PSA pre-surgery, Gleason score, extracapsular extension, positive surgical margins, infiltration of lymph nodes, seminal vesicles and pathological stage. Secondary circulating prostate cells were obtained using differential gel centrifugation and assessed using standard immunocytochemistry with anti-PSA. Biochemical failure was defined as a PSA >0.2ng/ml, predictive values werecalculated using the Walz nomagram and CPC detection. A total of 326 men participated, with a median follow up of 5 years; 64 had biochemical failure within two years. Extracapsular extension, positive surgical margins, pathological stage, Gleason score ≥ 8, infiltration of seminal vesicles and lymph nodes were all associated with higher risk of biochemical failure. The discriminative value for the nomogram and circulating prostate cells was high (AUC >0.80), predictive values were higher for circulating prostate cell detection, with a negative predictive value of 99%, sensitivity of 96% and specificity of 75%. The nomagram had good predictive power to identify men with a high risk of biochemical failure within two years. The presence of circulating prostate cells had the same predictive power, with a higher sensitivity and negative predictive value. The presence of secondary circulating prostate cells identifies a group of men with a high risk of early biochemical failure. Those negative for secondary CPCs have a very low risk of early biochemical failure.

Performance evaluation of 4 measuring methods of ground-glass opacities for predicting the 5-year relapse-free survival of patients with peripheral nonsmall cell lung cancer: a multicenter study.

PubMed

Kakinuma, Ryutaro; Kodama, Ken; Yamada, Kouzo; Yokoyama, Akira; Adachi, Shuji; Mori, Kiyoshi; Fukuyama, Yasuro; Fukuda, Yasuro; Kuriyama, Keiko; Oda, Junichi; Oda, Junji; Noguchi, Masayuki; Matsuno, Yoshihiro; Yokose, Tomoyuki; Ohmatsu, Hironobu; Nishiwaki, Yutaka

2008-01-01

To evaluate the performance of 4 methods of measuring the extent of ground-glass opacities as a means of predicting the 5-year relapse-free survival of patients with peripheral nonsmall cell lung cancer (NSLC). Ground-glass opacities on thin-section computed tomographic images of 120 peripheral NSLCs were measured at 7 medical institutions by the length, area, modified length, and vanishing ratio (VR) methods. The performance (Az) of each method in predicting the 5-year relapse-free survival was evaluated using receiver operating characteristic analysis. The mean Az value obtained by the length, area, modified length, and VR methods in the receiver operating characteristic analyses was 0.683, 0.702, 0.728, and 0.784, respectively. The differences between the mean Az value obtained by the VR method and by the other 3 methods were significant. Vanishing ratio method was the most accurate predictor of the 5-year relapse-free survival of patients with peripheral NSLC.

Tensile and compressive modulus of elasticity of pultruded fiber-reinforced polymer composite materials

NASA Astrophysics Data System (ADS)

Lee, J. H.; Kim, S. H.; Park, J. K.; Choi, W. C.; Yoon, S. J.

2018-06-01

Many researches focused on the mechanical properties of steel and concrete have been carried out for applications in the construction industry. However, in order to clarify the mechanical properties of pultruded fiber-reinforced polymer (PFRP) structural members for construction, testing is needed. Deriving the mechanical properties of PFRP structural members through testing is difficult, however, because some members cannot be tested easily due to their cross-section dimensions. This paper reports a part of studies that attempt to present conservative results in the case of members that cannot be tested reasonably. The authors obtained and compared experimental and theoretical modulus of elasticity values. If the mechanical properties of PFRP members can be predicted using reasonable and conservative values, then the structure can be designed economically and safely even in the early design stages. To this end, this paper proposes a strain energy approach as a conservative and convenient way to predict the mechanical properties of PFRP structural members. The strain energy data obtained can be used to predict the mechanical properties of PFRP members in the construction field.

A simplified heat transfer model for predicting temperature change inside food package kept in cold room.

PubMed

Raval, A H; Solanki, S C; Yadav, Rajvir

2013-04-01

A simple analytical heat flow model for a closed rectangular food package containing fruits or vegetables is proposed for predicting time temperature distribution during transient cooling in a controlled environment cold room. It is based on the assumption of only conductive heat transfer inside a closed food package with effective thermal properties, and convective and radiative heat transfer at the outside of the package. The effective thermal conductivity of the food package is determined by evaluating its effective thermal resistance to heat conduction in the packages. Food packages both as an infinite slab and a finite slab have been investigated. The finite slab solution has been obtained as the product of three infinite slab solutions describe in ASHRAE guide and data book. Time temperature variation has been determined and is presented graphically. The cooling rate and the half cooling time were also obtained. These predicted values, are compared with the experimentally measured values for both the finite and infinite closed packages containing oranges. An excellent agreement between them validated the simple proposed model.

Engineering Test Report Paint Waste Reduction Fluidized Bed Process Demonstration at Letterkenny Army Depot Chambersburg, Pennsylvania

DTIC Science & Technology

1991-07-01

predicted by equation using actual chart response obtained from each calibration gas response. (Concentration of cal. gas,l Calibration error, % span • ppm...Analyzer predicted by cali- Col. gas Chart divisions equation* bration Cylinder conc., error,** Drift,***INo. ppm or % Pretest Posttest Pretest Posttest...2m ~J * Correlation coef. * qgq’jq **Analyzer ca.error, % spn (Cal. gas conc. conc. predicted ) x 1003 cal spanSpan value Acceptable limit x ɚ% of

An Intelligent Ensemble Neural Network Model for Wind Speed Prediction in Renewable Energy Systems.

PubMed

Ranganayaki, V; Deepa, S N

2016-01-01

Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural network models which includes multilayer perceptron (MLP), multilayer adaptive linear neuron (Madaline), back propagation neural network (BPN), and probabilistic neural network (PNN) so as to obtain better accuracy in wind speed prediction with minimum error. The random selection of hidden neurons numbers in artificial neural network results in overfitting or underfitting problem. This paper aims to avoid the occurrence of overfitting and underfitting problems. The selection of number of hidden neurons is done in this paper employing 102 criteria; these evolved criteria are verified by the computed various error values. The proposed criteria for fixing hidden neurons are validated employing the convergence theorem. The proposed intelligent ensemble neural model is applied for wind speed prediction application considering the real time wind data collected from the nearby locations. The obtained simulation results substantiate that the proposed ensemble model reduces the error value to minimum and enhances the accuracy. The computed results prove the effectiveness of the proposed ensemble neural network (ENN) model with respect to the considered error factors in comparison with that of the earlier models available in the literature.

An Intelligent Ensemble Neural Network Model for Wind Speed Prediction in Renewable Energy Systems

PubMed Central

Ranganayaki, V.; Deepa, S. N.

2016-01-01

Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural network models which includes multilayer perceptron (MLP), multilayer adaptive linear neuron (Madaline), back propagation neural network (BPN), and probabilistic neural network (PNN) so as to obtain better accuracy in wind speed prediction with minimum error. The random selection of hidden neurons numbers in artificial neural network results in overfitting or underfitting problem. This paper aims to avoid the occurrence of overfitting and underfitting problems. The selection of number of hidden neurons is done in this paper employing 102 criteria; these evolved criteria are verified by the computed various error values. The proposed criteria for fixing hidden neurons are validated employing the convergence theorem. The proposed intelligent ensemble neural model is applied for wind speed prediction application considering the real time wind data collected from the nearby locations. The obtained simulation results substantiate that the proposed ensemble model reduces the error value to minimum and enhances the accuracy. The computed results prove the effectiveness of the proposed ensemble neural network (ENN) model with respect to the considered error factors in comparison with that of the earlier models available in the literature. PMID:27034973

Impact of Chemical Structure on Conjunctival Drug Permeability: Adopting Porcine Conjunctiva and Cassette Dosing for Construction of In Silico Model.

PubMed

Ramsay, Eva; Ruponen, Marika; Picardat, Théo; Tengvall, Unni; Tuomainen, Marjo; Auriola, Seppo; Toropainen, Elisa; Urtti, Arto; Del Amo, Eva M

2017-09-01

Conjunctiva occupies most of the ocular surface area, and conjunctival permeability affects ocular and systemic drug absorption of topical ocular medications. Therefore, the aim of this study was to obtain a computational in silico model for structure-based prediction of conjunctival drug permeability. This was done by employing cassette dosing and quantitative structure-property relationship (QSPR) approach. Permeability studies were performed ex vivo across fresh porcine conjunctiva and simultaneous dosing of a cassette mixture composed of 32 clinically relevant drug molecules with wide chemical space. The apparent permeability values were obtained using drug concentrations that were quantified with liquid chromatography tandem-mass spectrometry. The experimental data were utilized for building a QSPR model for conjunctival permeability predictions. The conjunctival permeability values presented a 17-fold range (0.63-10.74 × 10 -6 cm/s). The final QSPR had a Q 2 value of 0.62 and predicted the external test set with a mean fold error of 1.34. The polar surface area, hydrogen bond donor, and halogen ratio were the most relevant descriptors for defining conjunctival permeability. This work presents for the first time a predictive QSPR model of conjunctival drug permeability and a comprehensive description on conjunctival isolation from the porcine eye. The model can be used for developing new ocular drugs. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

[The trial of business data analysis at the Department of Radiology by constructing the auto-regressive integrated moving-average (ARIMA) model].

PubMed

Tani, Yuji; Ogasawara, Katsuhiko

2012-01-01

This study aimed to contribute to the management of a healthcare organization by providing management information using time-series analysis of business data accumulated in the hospital information system, which has not been utilized thus far. In this study, we examined the performance of the prediction method using the auto-regressive integrated moving-average (ARIMA) model, using the business data obtained at the Radiology Department. We made the model using the data used for analysis, which was the number of radiological examinations in the past 9 years, and we predicted the number of radiological examinations in the last 1 year. Then, we compared the actual value with the forecast value. We were able to establish that the performance prediction method was simple and cost-effective by using free software. In addition, we were able to build the simple model by pre-processing the removal of trend components using the data. The difference between predicted values and actual values was 10%; however, it was more important to understand the chronological change rather than the individual time-series values. Furthermore, our method was highly versatile and adaptable compared to the general time-series data. Therefore, different healthcare organizations can use our method for the analysis and forecasting of their business data.

Prediction of Central Burst Defects in Copper Wire Drawing Process

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

Vega, G.; NEXANS France, NMC Nexans Metallurgy Centre, Boulevard du Marais, BP39, F-62301 Lens; Haddi, A.

2011-01-17

In this study, the prediction of chevron cracks (central bursts) in copper wire drawing process is investigated using experimental and numerical approaches. The conditions of the chevron cracks creation along the wire axis depend on (i) the die angle, the friction coefficient between the die and the wire, (ii) the reduction in crosssectional area of the wire, (iii) the material properties and (iv) the drawing velocity or strain rate. Under various drawing conditions, a numerical simulation for the prediction of central burst defects is presented using an axisymmetric finite element model. This model is based on the application of themore » Cockcroft and Latham fracture criterion. This criterion was used as the damage value to estimate if and where defects will occur during the copper wire drawing. The critical damage value of the material is obtained from a uniaxial tensile test. The results show that the die angle and the reduction ratio have a significant effect on the stress distribution and the maximum damage value. The central bursts are expected to occur when the die angle and reduction ratio reach a critical value. Numerical predictions are compared with experimental observations.« less

Surface Protonation at the Rutile (110) Interface: Explicit Incorporation of Solvation Structure within the Refined MUSIC Model Framework

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

Machesky, Michael L.; Predota, M.; Wesolowski, David J

The detailed solvation structure at the (110) surface of rutile ({alpha}-TiO{sub 2}) in contact with bulk liquid water has been obtained primarily from experimentally verified classical molecular dynamics (CMD) simulations of the ab initio-optimized surface in contact with SPC/E water. The results are used to explicitly quantify H-bonding interactions, which are then used within the refined MUSIC model framework to predict surface oxygen protonation constants. Quantum mechanical molecular dynamics (QMD) simulations in the presence of freely dissociable water molecules produced H-bond distributions around deprotonated surface oxygens very similar to those obtained by CMD with nondissociable SPC/E water, thereby confirming thatmore » the less computationally intensive CMD simulations provide accurate H-bond information. Utilizing this H-bond information within the refined MUSIC model, along with manually adjusted Ti-O surface bond lengths that are nonetheless within 0.05 {angstrom} of those obtained from static density functional theory (DFT) calculations and measured in X-ray reflectivity experiments (as well as bulk crystal values), give surface protonation constants that result in a calculated zero net proton charge pH value (pHznpc) at 25 C that agrees quantitatively with the experimentally determined value (5.4 {+-} 0.2) for a specific rutile powder dominated by the (110) crystal face. Moreover, the predicted pH{sub znpc} values agree to within 0.1 pH unit with those measured at all temperatures between 10 and 250 C. A slightly smaller manual adjustment of the DFT-derived Ti-O surface bond lengths was sufficient to bring the predicted pH{sub znpc} value of the rutile (110) surface at 25 C into quantitative agreement with the experimental value (4.8 {+-} 0.3) obtained from a polished and annealed rutile (110) single crystal surface in contact with dilute sodium nitrate solutions using second harmonic generation (SHG) intensity measurements as a function of ionic strength. Additionally, the H-bond interactions between protolyzable surface oxygen groups and water were found to be stronger than those between bulk water molecules at all temperatures investigated in our CMD simulations (25, 150 and 250 C). Comparison with the protonation scheme previously determined for the (110) surface of isostructural cassiterite ({alpha}-SnO{sub 2}) reveals that the greater extent of H-bonding on the latter surface, and in particular between water and the terminal hydroxyl group (Sn-OH) results in the predicted protonation constant for that group being lower than for the bridged oxygen (Sn-O-Sn), while the reverse is true for the rutile (110) surface. These results demonstrate the importance of H-bond structure in dictating surface protonation behavior, and that explicit use of this solvation structure within the refined MUSIC model framework results in predicted surface protonation constants that are also consistent with a variety of other experimental and computational data.« less

Model estimation of claim risk and premium for motor vehicle insurance by using Bayesian method

NASA Astrophysics Data System (ADS)

Sukono; Riaman; Lesmana, E.; Wulandari, R.; Napitupulu, H.; Supian, S.

2018-01-01

Risk models need to be estimated by the insurance company in order to predict the magnitude of the claim and determine the premiums charged to the insured. This is intended to prevent losses in the future. In this paper, we discuss the estimation of risk model claims and motor vehicle insurance premiums using Bayesian methods approach. It is assumed that the frequency of claims follow a Poisson distribution, while a number of claims assumed to follow a Gamma distribution. The estimation of parameters of the distribution of the frequency and amount of claims are made by using Bayesian methods. Furthermore, the estimator distribution of frequency and amount of claims are used to estimate the aggregate risk models as well as the value of the mean and variance. The mean and variance estimator that aggregate risk, was used to predict the premium eligible to be charged to the insured. Based on the analysis results, it is shown that the frequency of claims follow a Poisson distribution with parameter values λ is 5.827. While a number of claims follow the Gamma distribution with parameter values p is 7.922 and θ is 1.414. Therefore, the obtained values of the mean and variance of the aggregate claims respectively are IDR 32,667,489.88 and IDR 38,453,900,000,000.00. In this paper the prediction of the pure premium eligible charged to the insured is obtained, which amounting to IDR 2,722,290.82. The prediction of the claims and premiums aggregate can be used as a reference for the insurance company’s decision-making in management of reserves and premiums of motor vehicle insurance.

Performance and cost analysis of Siriraj liquid-based cytology: a direct-to-vial study.

PubMed

Laiwejpithaya, Somsak; Benjapibal, Mongkol; Laiwejpithaya, Sujera; Wongtiraporn, Weerasak; Sangkarat, Suthi; Rattanachaiyanont, Manee

2009-12-01

To compare the cytological diagnoses, specimen adequacy, and cost of the Siriraj liquid-based cytology (LBC) with those of the conventional smear technique. An observational study with historical comparison was conducted in a tertiary university hospital. Cytological reports of 23,676 Siriraj-LBC specimens obtained in 2006 were compared with those of 25,510 conventional smears obtained in 2004. Overall prevalence of abnormal cervical cytology detected by conventional smear was 1.76% and by Siriraj-LBC was 3.70%. Compared with the conventional method, the Siriraj-LBC yielded a significantly higher overall detection rate of abnormal cervical cytology, with a 110.23% increase in the detection rate (P<0.001), mainly due to the increase in diagnosis of squamous intraepithelial lesions (SIL), both low and high grade, together with atypical squamous cells of undetermined significance, "atypical squamous cells cannot exclude HSIL", and malignancies, but not atypical glandular cells. The Siriraj-LBC had a smaller proportion of unsatisfactory slides (4.94% vs. 18.60%, P<0.001) and a higher negative predictive value (96.33% vs. 92.74%, P=0.001), but no difference in positive predictive value (83.03% vs. 86.83%, P=0.285). The cost of Siriraj-LBC was approximately 67% higher than that of the conventional cytology used in Siriraj Hospital and 50-70% lower than that of the commercially available LBC techniques in Thailand. The Siriraj-LBC increases the detection rate of abnormal cytology, improves specimen adequacy, and enhances the negative predictive value without compromising the positive predictive value. For centers where conventional Pap smear does not perform well, the introduction of a low cost Siriraj-LBC might help to improve performance and it may be an economical alternative to the commercially available liquid-based cytology.

Clinical utility of magnetic resonance imaging radiographs for suspected organic syndromes in adult psychiatry.

PubMed

Erhart, Stephen M; Young, Alexander S; Marder, Stephen R; Mintz, Jim

2005-08-01

In psychiatric practice, adult patients are most commonly referred for magnetic resonance imaging (MRI) to screen for suspected organic medical diseases of the central nervous system that can mimic psychiatric syndromes. We identified the most common signs and symptoms prompting MRIs to establish the predictive value of these signs and symptoms for clinically pertinent organic syndromes. This study was a retrospective chart review of psychiatric patients at the Veterans Affairs Greater Los Angeles Health Care Center (Los Angeles, Calif.) who were referred for MRI of the brain between 1996 and 2002. Patients referred for evaluation of dementia were excluded. The specific indications leading clinicians to obtain MRI were identified and grouped. In order to offset the uncertain significance of many MRI findings, for this study, the predictive value of each indication was calculated based on the percentage of patients in whom clinical management changed in response to MRI findings rather than on the percentage with any abnormal MRI results. Of 253 patients who had MRIs, 38 (15%) incurred some degree of treatment modification as a result of MRI findings, including 6 patients in whom MRI identified a medical condition that became the focus of treatment. Six indications appeared most likely to prompt clinicians to obtain MRIs. Because pertinent results were associated with each of these indications, statistical evaluation did not reveal significant differences in their predictive values (chi(2) = 4.32, df = 5, p = .505). Unlike prior studies showing no value to screening radioimaging, this study shows MRI can be a useful screening test among patients suspected of having organic psychiatric disorders and that the common indications for MRI employed at one institution were predictive.

Application of visible/near-infrared reflectance spectroscopy for predicting internal and external quality in pepper.

PubMed

Toledo-Martín, Eva María; García-García, María Carmen; Font, Rafael; Moreno-Rojas, José Manuel; Gómez, Pedro; Salinas-Navarro, María; Del Río-Celestino, Mercedes

2016-07-01

The characterization of internal (°Brix, pH, malic acid, total phenolic compounds, ascorbic acid and total carotenoid content) and external (color, firmness and pericarp wall thickness) pepper quality is necessary to better understand its possible applications and increase consumer awareness of its benefits. The main aim of this work was to examine the feasibility of using visible/near-infrared reflectance spectroscopy (VIS-NIRS) to predict quality parameters in different pepper types. Commercially available spectrophotometers were evaluated for this purpose: a Polychromix Phazir spectrometer for intact raw pepper, and a scanning monochromator for freeze-dried pepper. The RPD values (ratio of the standard deviation of the reference data to the standard error of prediction) obtained from the external validation exceeded a value of 3 for chlorophyll a and total carotenoid content; values ranging between 2.5 < RPD < 3 for total phenolic compounds; between 1.5 < RPD <2.5 for °Brix, pH, color parameters a* and h* and chlorophyll b; and RPD values below 1.5 for fruit firmness, pericarp wall thickness, color parameters C*, b* and L*, vitamin C and malic acid content. The present work has led to the development of multi-type calibrations for pepper quality parameters in intact and freeze-dried peppers. The majority of NIRS equations obtained were suitable for screening purposes in pepper breeding programs. Components such as pigments (xanthophyll, carotenes and chlorophyll), glucides, lipids, cellulose and water were used by modified partial least-squares regression for modeling the predicting equations. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

[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

2016-10-13

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 RESULTS: 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%. 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. Copyright © 2016 Sociedad Chilena de Pediatría. Publicado por Elsevier España, S.L.U. All rights reserved.

Dissolution assessment of allopurinol immediate release tablets by near infrared spectroscopy.

PubMed

Smetiško, Jelena; Miljanić, Snežana

2017-10-25

The purpose of this study was to develop a NIR spectroscopic method for assessment of drug dissolution from allopurinol immediate release tablets. Thirty three different batches of allopurinol immediate release tablets containing constant amount of the active ingredient, but varying in excipients content and physical properties were introduced in a PLS calibration model. Correlating allopurinol dissolution reference values measured by the routinely used UV/Vis method, with the data extracted from the NIR spectra, values of correlation coefficient, bias, slope, residual prediction determination and root mean square error of prediction (0.9632, 0.328%, 1.001, 3.58, 3.75%) were evaluated. The obtained values implied that the NIR diffuse reflectance spectroscopy could serve as a faster and simpler alternative to the conventional dissolution procedure, even for the tablets with a very fast dissolution rate (>85% in 15minutes). Apart from the possibility of prediction of the allopurinol dissolution rate, the other multivariate technique, PCA, provided additional data on the non-chemical characteristics of the product, which could not be obtained from the reference dissolution values. Analysis on an independent set of samples confirmed that a difference between the UV/Vis reference method and the proposed NIR method was not significant. According to the presented results, the proposed NIR method may be suitable for practical application in routine analysis and for continuously monitoring the product's chemical and physical properties responsible for expected quality. Copyright © 2017 Elsevier B.V. All rights reserved.

The reproducibility and predictive value on outcome of renal biopsies from expanded criteria donors.

PubMed

Azancot, M Antonieta; Moreso, Francesc; Salcedo, Maite; Cantarell, Carme; Perello, Manel; Torres, Irina B; Montero, Angeles; Trilla, Enric; Sellarés, Joana; Morote, Joan; Seron, Daniel

2014-05-01

Reproducibility and predictive value on outcome are the main criteria to evaluate the utility of histological scores. Here we analyze the reproducibility of donor biopsy assessment by different on-call pathologists and the retrospective evaluation by a single renal pathologist blinded to clinical outcomes. We also evaluate the predictive value on graft outcome of both evaluations. A biopsy was performed in donors with any of the following: age≥55 years, hypertension, diabetes, creatinine>1.5 mg/dl, or stroke. Glomerulosclerosis, interstitial fibrosis, tubular atrophy, intimal thickening, and arteriolar hyalinosis evaluated according to the Banff criteria were added to obtain a chronic score. Biopsies were classified as mild (≥3), intermediate (4-5), or advanced (6-7) damage, and unacceptable (≥8) for transplantation of 127 kidneys biopsied. Weighted κ value between both readings was 0.41 (95% CI: 0.28-0.54). Evaluation of biopsies by the renal pathologist was significantly and independently associated with estimated 12-month glomerular filtration rate and a significant composite outcome variable, including death-censored graft survival and time to reach an estimated glomerular filtration rate<30 ml/min per 1.73 m2. Thus, there was no association between readings of on-call pathologists and outcome. The lack of association between histological scores obtained by the on-call pathologists and graft outcome suggests that a specific training on renal pathology is recommended to optimize the use of kidneys retrieved from expanded criteria donors.

FOCUSING OF HIGH POWER ULTRASOUND BEAMS AND LIMITING VALUES OF SHOCK WAVE PARAMETERS

PubMed Central

Bessonova, O.V.; Khokhlova, V.A.; Bailey, M.R.; Canney, M.S.; Crum, L.A.

2009-01-01

In this work, the influence of nonlinear and diffraction effects on amplification factors of focused ultrasound systems is investigated. The limiting values of acoustic field parameters obtained by focusing of high power ultrasound are studied. The Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation was used for the numerical modeling. Solutions for the nonlinear acoustic field were obtained at output levels corresponding to both pre- and post- shock formation conditions in the focal area of the beam in a weakly dissipative medium. Numerical solutions were compared with experimental data as well as with known analytic predictions. PMID:20161349

FOCUSING OF HIGH POWER ULTRASOUND BEAMS AND LIMITING VALUES OF SHOCK WAVE PARAMETERS.

PubMed

Bessonova, O V; Khokhlova, V A; Bailey, M R; Canney, M S; Crum, L A

2009-07-21

In this work, the influence of nonlinear and diffraction effects on amplification factors of focused ultrasound systems is investigated. The limiting values of acoustic field parameters obtained by focusing of high power ultrasound are studied. The Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation was used for the numerical modeling. Solutions for the nonlinear acoustic field were obtained at output levels corresponding to both pre- and post- shock formation conditions in the focal area of the beam in a weakly dissipative medium. Numerical solutions were compared with experimental data as well as with known analytic predictions.

Focusing of high power ultrasound beams and limiting values of shock wave parameters

NASA Astrophysics Data System (ADS)

Bessonova, O. V.; Khokhlova, V. A.; Bailey, M. R.; Canney, M. S.; Crum, L. A.

2009-10-01

In this work, the influence of nonlinear and diffraction effects on amplification factors of focused ultrasound systems is investigated. The limiting values of acoustic field parameters obtained by focusing of high power ultrasound are studied. The Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation was used for the numerical modeling. Solutions for the nonlinear acoustic field were obtained at output levels corresponding to both pre- and post-shock formation conditions in the focal area of the beam in a weakly dissipative medium. Numerical solutions were compared with experimental data as well as with known analytic predictions.

Measurement of the Angular Distribution of the Electron from $$W \\to e + \

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

Ramos, Manuel Martin

1996-10-01

The goal of this thesis is to scan the extensive literature dealing with the properties of the W and Z bosons. Iit is clear that, besides the measurements confirming the weak interactions theory, no specific work related to the angular distributions of the emerging particles from the leptonic decay of the boson has been done. The aim of the work is to obtain experimentally the values of α 2, as function of the transverse momentum of the W, that appear in the expression 0.3 and to compare the values obtained with the theoretical predictions.

Estimation of leaf area index using WorldView-2 and Aster satellite image: a case study from Turkey.

PubMed

Günlü, Alkan; Keleş, Sedat; Ercanlı, İlker; Şenyurt, Muammer

2017-10-04

The objective of this study is to estimate the leaf area index (LAI) of a forest ecosystem using two different satellite images, WorldView-2 and Aster. For this purpose, 108 sample plots were taken from pure Crimean pine forest stands of Yenice Forest Management Planning Unit in Ilgaz Forest Management Enterprise, Turkey. Each sample plot was imaged with hemispherical photographs with a fish-eye camera to determine the LAI. These photographs were analyzed with the help of Hemisfer Hemiview software program, and thus, the LAI of each sample plot was estimated. Furthermore, multiple regression analysis method was used to model the statistical relationships between the LAI values and band spectral reflection values and some vegetation indices (Vis) obtained from satellite images. The results show that the high-resolution WorldView-2 satellite image is better than the medium-resolution Aster satellite image in predicting the LAI. It was also seen that the results obtained by using the VIs are better than the bands when the LAI value is predicted with satellite images.

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.

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

Evaluation of chemical parameters in soft mold-ripened cheese during ripening by mid-infrared spectroscopy.

PubMed

Martín-del-Campo, S T; Picque, D; Cosío-Ramírez, R; Corrieu, G

2007-06-01

The suitability of mid-infrared spectroscopy (MIR) to follow the evolution throughout ripening of specific physicochemical parameters in Camembert-type cheeses was evaluated. The infrared spectra were obtained directly from raw cheese samples deposited on an attenuated total reflectance crystal. Significant correlations were observed between physicochemical data, pH, acid-soluble nitrogen, nonprotein nitrogen, ammonia (NH4+), lactose, and lactic acid. Dry matter showed significant correlation only with lactose and nonprotein nitrogen. Principal components analysis factorial maps of physicochemical data showed a ripening evolution in 2 steps, from d 1 to d 7 and from d 8 to d 27, similar to that observed previously from infrared spectral data. Partial least squares regressions made it possible to obtain good prediction models for dry matter, acid-soluble nitrogen, nonprotein nitrogen, lactose, lactic acid, and NH4+ values from spectral data of raw cheese. The values of 3 statistical parameters (coefficient of determination, root mean square error of cross validation, and ratio prediction deviation) are satisfactory. Less precise models were obtained for pH.

Comparison of Code Predictions to Test Measurements for Two Orifice Compensated Hydrostatic Bearings at High Reynolds Numbers

NASA Technical Reports Server (NTRS)

Keba, John E.

1996-01-01

Rotordynamic coefficients obtained from testing two different hydrostatic bearings are compared to values predicted by two different computer programs. The first set of test data is from a relatively long (L/D=1) orifice compensated hydrostatic bearing tested in water by Texas A&M University (TAMU Bearing No.9). The second bearing is a shorter (L/D=.37) bearing and was tested in a lower viscosity fluid by Rocketdyne Division of Rockwell (Rocketdyne 'Generic' Bearing) at similar rotating speeds and pressures. Computed predictions of bearing rotordynamic coefficients were obtained from the cylindrical seal code 'ICYL', one of the industrial seal codes developed for NASA-LeRC by Mechanical Technology Inc., and from the hydrodynamic bearing code 'HYDROPAD'. The comparison highlights the difference the bearing has on the accuracy of the predictions. The TAMU Bearing No. 9 test data is closely matched by the predictions obtained for the HYDROPAD code (except for added mass terms) whereas significant differences exist between the data from the Rocketdyne 'Generic' bearing the code predictions. The results suggest that some aspects of the fluid behavior in the shorter, higher Reynolds Number 'Generic' bearing may not be modeled accurately in the codes. The ICYL code predictions for flowrate and direct stiffness approximately equal those of HYDROPAD. Significant differences in cross-coupled stiffness and the damping terms were obtained relative to HYDROPAD and both sets of test data. Several observations are included concerning application of the ICYL code.

Climate predictability and prediction skill on seasonal time scales over South America from CHFP models

NASA Astrophysics Data System (ADS)

Osman, Marisol; Vera, C. S.

2017-10-01

This work presents an assessment of the predictability and skill of climate anomalies over South America. The study was made considering a multi-model ensemble of seasonal forecasts for surface air temperature, precipitation and regional circulation, from coupled global circulation models included in the Climate Historical Forecast Project. Predictability was evaluated through the estimation of the signal-to-total variance ratio while prediction skill was assessed computing anomaly correlation coefficients. Both indicators present over the continent higher values at the tropics than at the extratropics for both, surface air temperature and precipitation. Moreover, predictability and prediction skill for temperature are slightly higher in DJF than in JJA while for precipitation they exhibit similar levels in both seasons. The largest values of predictability and skill for both variables and seasons are found over northwestern South America while modest but still significant values for extratropical precipitation at southeastern South America and the extratropical Andes. The predictability levels in ENSO years of both variables are slightly higher, although with the same spatial distribution, than that obtained considering all years. Nevertheless, predictability at the tropics for both variables and seasons diminishes in both warm and cold ENSO years respect to that in all years. The latter can be attributed to changes in signal rather than in the noise. Predictability and prediction skill for low-level winds and upper-level zonal winds over South America was also assessed. Maximum levels of predictability for low-level winds were found were maximum mean values are observed, i.e. the regions associated with the equatorial trade winds, the midlatitudes westerlies and the South American Low-Level Jet. Predictability maxima for upper-level zonal winds locate where the subtropical jet peaks. Seasonal changes in wind predictability are observed that seem to be related to those associated with the signal, especially at the extratropics.

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.

The use of genomic information increases the accuracy of breeding value predictions for sea louse (Caligus rogercresseyi) resistance in Atlantic salmon (Salmo salar).

PubMed

Correa, Katharina; Bangera, Rama; Figueroa, René; Lhorente, Jean P; Yáñez, José M

2017-01-31

Sea lice infestations caused by Caligus rogercresseyi are a main concern to the salmon farming industry due to associated economic losses. Resistance to this parasite was shown to have low to moderate genetic variation and its genetic architecture was suggested to be polygenic. The aim of this study was to compare accuracies of breeding value predictions obtained with pedigree-based best linear unbiased prediction (P-BLUP) methodology against different genomic prediction approaches: genomic BLUP (G-BLUP), Bayesian Lasso, and Bayes C. To achieve this, 2404 individuals from 118 families were measured for C. rogercresseyi count after a challenge and genotyped using 37 K single nucleotide polymorphisms. Accuracies were assessed using fivefold cross-validation and SNP densities of 0.5, 1, 5, 10, 25 and 37 K. Accuracy of genomic predictions increased with increasing SNP density and was higher than pedigree-based BLUP predictions by up to 22%. Both Bayesian and G-BLUP methods can predict breeding values with higher accuracies than pedigree-based BLUP, however, G-BLUP may be the preferred method because of reduced computation time and ease of implementation. A relatively low marker density (i.e. 10 K) is sufficient for maximal increase in accuracy when using G-BLUP or Bayesian methods for genomic prediction of C. rogercresseyi resistance in Atlantic salmon.

Application of matrix singular value properties for evaluating gain and phase margins of multiloop systems. [stability margins for wing flutter suppression and drone lateral attitude control

NASA Technical Reports Server (NTRS)

Mukhopadhyay, V.; Newsom, J. R.

1982-01-01

A stability margin evaluation method in terms of simultaneous gain and phase changes in all loops of a multiloop system is presented. A universal gain-phase margin evaluation diagram is constructed by generalizing an existing method using matrix singular value properties. Using this diagram and computing the minimum singular value of the system return difference matrix over the operating frequency range, regions of guaranteed stability margins can be obtained. Singular values are computed for a wing flutter suppression and a drone lateral attitude control problem. The numerical results indicate that this method predicts quite conservative stability margins. In the second example if the eigenvalue magnitude is used instead of the singular value, as a measure of nearness to singularity, more realistic stability margins are obtained. However, this relaxed measure generally cannot guarantee global stability.

Production of biodiesel from bioethanol and Brassica carinata oil: oxidation stability study.

PubMed

Bouaid, Abderrahim; Martinez, Mercedes; Aracil, Jose

2009-04-01

In the present work the synthesis from bioethanol and Brassica carinata, as alternative vegetable oil, using KOH as catalyst, has been developed and optimized by application of the factorial design and response surface methodology (RSM). Temperature and catalyst concentration were found to have significant influence on conversion. A second-order model was obtained to predict conversions as a function of temperature and catalyst concentration. The maximum yield of ester (98.04%) was obtained working with an initial concentration of catalyst (1.5%) and an operation temperature of (35 degrees C). Results show that the acid value, peroxide value, and viscosity, increased while the iodine value decreased with increasing storage time of the biodiesel sample. Fatty acid ethyl esters (biodiesel) from B. carinata oil were very stable because they did not demonstrate rapid increase in peroxide value, acid value, and viscosity with increasing storage time to a period of 12 months.

Application of simple mathematical expressions to relate the half-lives of xenobiotics in rats to values in humans.

PubMed

Ward, Keith W; Erhardt, Paul; Bachmann, Kenneth

2005-01-01

Previous publications from GlaxoSmithKline and University of Toledo laboratories convey our independent attempts to predict the half-lives of xenobiotics in humans using data obtained from rats. The present investigation was conducted to compare the performance of our published models against a common dataset obtained by merging the two sets of rat versus human half-life (hHL) data previously used by each laboratory. After combining data, mathematical analyses were undertaken by deploying both of our previous models, namely the use of an empirical algorithm based on a best-fit model and the use of rat-to-human liver blood flow ratios as a half-life correction factor. Both qualitative and quantitative analyses were performed, as well as evaluation of the impact of molecular properties on predictability. The merged dataset was remarkably diverse with respect to physiochemical and pharmacokinetic (PK) properties. Application of both models revealed similar predictability, depending upon the measure of stipulated accuracy. Certain molecular features, particularly rotatable bond count and pK(a), appeared to influence the accuracy of prediction. This collaborative effort has resulted in an improved understanding and appreciation of the value of rats to serve as a surrogate for the prediction of xenobiotic half-lives in humans when clinical pharmacokinetic studies are not possible or practicable.

Transonic Drag Prediction Using an Unstructured Multigrid Solver

NASA Technical Reports Server (NTRS)

Mavriplis, D. J.; Levy, David W.

2001-01-01

This paper summarizes the results obtained with the NSU-3D unstructured multigrid solver for the AIAA Drag Prediction Workshop held in Anaheim, CA, June 2001. The test case for the workshop consists of a wing-body configuration at transonic flow conditions. Flow analyses for a complete test matrix of lift coefficient values and Mach numbers at a constant Reynolds number are performed, thus producing a set of drag polars and drag rise curves which are compared with experimental data. Results were obtained independently by both authors using an identical baseline grid and different refined grids. Most cases were run in parallel on commodity cluster-type machines while the largest cases were run on an SGI Origin machine using 128 processors. The objective of this paper is to study the accuracy of the subject unstructured grid solver for predicting drag in the transonic cruise regime, to assess the efficiency of the method in terms of convergence, cpu time, and memory, and to determine the effects of grid resolution on this predictive ability and its computational efficiency. A good predictive ability is demonstrated over a wide range of conditions, although accuracy was found to degrade for cases at higher Mach numbers and lift values where increasing amounts of flow separation occur. The ability to rapidly compute large numbers of cases at varying flow conditions using an unstructured solver on inexpensive clusters of commodity computers is also demonstrated.

One-hour glucose value as a long-term predictor of cardiovascular morbidity and mortality: the Malmö Preventive Project.

PubMed

Nielsen, Mette L; Pareek, Manan; Leósdóttir, Margrét; Eriksson, Karl-Fredrik; Nilsson, Peter M; Olsen, Michael H

2018-03-01

To examine the predictive capability of a 1-h vs 2-h postload glucose value for cardiovascular morbidity and mortality. Prospective, population-based cohort study (Malmö Preventive Project) with subject inclusion 1974-1992. 4934 men without known diabetes and cardiovascular disease, who had blood glucose (BG) measured at 0, 20, 40, 60, 90 and 120 min during an OGTT (30 g glucose per m 2 body surface area), were followed for 27 years. Data on cardiovascular events and death were obtained through national and local registries. Predictive capabilities of fasting BG (FBG) and glucose values obtained during OGTT alone and added to a clinical prediction model comprising traditional cardiovascular risk factors were assessed using Harrell's concordance index (C-index) and integrated discrimination improvement (IDI). Median age was 48 (25th-75th percentile: 48-49) years and mean FBG 4.6 ± 0.6 mmol/L. FBG and 2-h postload BG did not independently predict cardiovascular events or death. Conversely, 1-h postload BG predicted cardiovascular morbidity and mortality and remained an independent predictor of cardiovascular death (HR: 1.09, 95% CI: 1.01-1.17, P  = 0.02) and all-cause mortality (HR: 1.10, 95% CI: 1.05-1.16, P  < 0.0001) after adjusting for various traditional risk factors. Clinical risk factors with added 1-h postload BG performed better than clinical risk factors alone, in predicting cardiovascular death (likelihood-ratio test, P  = 0.02) and all-cause mortality (likelihood-ratio test, P  = 0.0001; significant IDI, P  = 0.0003). Among men without known diabetes, addition of 1-h BG, but not FBG or 2-h BG, to clinical risk factors provided incremental prognostic yield for prediction of cardiovascular death and all-cause mortality. © 2018 European Society of Endocrinology.

k-Nearest neighbour local linear prediction of scalp EEG activity during intermittent photic stimulation.

PubMed

Erla, Silvia; Faes, Luca; Tranquillini, Enzo; Orrico, Daniele; Nollo, Giandomenico

2011-05-01

The characterization of the EEG response to photic stimulation (PS) is an important issue with significant clinical relevance. This study aims to quantify and map the complexity of the EEG during PS, where complexity is measured as the degree of unpredictability resulting from local linear prediction. EEG activity was recorded with eyes closed (EC) and eyes open (EO) during resting and PS at 5, 10, and 15 Hz in a group of 30 healthy subjects and in a case-report of a patient suffering from cerebral ischemia. The mean squared prediction error (MSPE) resulting from k-nearest neighbour local linear prediction was calculated in each condition as an index of EEG unpredictability. The linear or nonlinear nature of the system underlying EEG activity was evaluated quantifying MSPE as a function of the neighbourhood size during local linear prediction, and by surrogate data analysis as well. Unpredictability maps were obtained for each subject interpolating MSPE values over a schematic head representation. Results on healthy subjects evidenced: (i) the prevalence of linear mechanisms in the generation of EEG dynamics, (ii) the lower predictability of EO EEG, (iii) the desynchronization of oscillatory mechanisms during PS leading to increased EEG complexity, (iv) the entrainment of alpha rhythm during EC obtained by 10 Hz PS, and (v) differences of EEG predictability among different scalp regions. Ischemic patient showed different MSPE values in healthy and damaged regions. The EEG predictability decreased moving from the early acute stage to a stage of partial recovery. These results suggest that nonlinear prediction can be a useful tool to characterize EEG dynamics during PS protocols, and may consequently constitute a complement of quantitative EEG analysis in clinical applications. Copyright © 2010 IPEM. Published by Elsevier Ltd. All rights reserved.

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.

Gradient retention prediction of acid-base analytes in reversed phase liquid chromatography: a simplified approach for acetonitrile-water mobile phases.

PubMed

Andrés, Axel; Rosés, Martí; Bosch, Elisabeth

2014-11-28

In previous work, a two-parameter model to predict chromatographic retention of ionizable analytes in gradient mode was proposed. However, the procedure required some previous experimental work to get a suitable description of the pKa change with the mobile phase composition. In the present study this previous experimental work has been simplified. The analyte pKa values have been calculated through equations whose coefficients vary depending on their functional group. Forced by this new approach, other simplifications regarding the retention of the totally neutral and totally ionized species also had to be performed. After the simplifications were applied, new prediction values were obtained and compared with the previously acquired experimental data. The simplified model gave pretty good predictions while saving a significant amount of time and resources. Copyright © 2014 Elsevier B.V. All rights reserved.

47 annual records of allergenic fungi spore: predictive models from the NW Iberian Peninsula.

PubMed

Aira, M Jesus; Rodriguez-Rajo, F; Jato, Victoria

2008-01-01

An analysis was carried out of the atmospheric representivity of Cladosporium and Alternaria spores in the north-western Iberian Peninsula, registering mean annual concentrations in excess of 300,000 spores/m(3). During the main sporulation period, the highest average daily concentrations corresponded to Cladosporium herbarum type (1,197 spores/m(3)) while the highest daily value was 7,556 spores/m(3) (Cladosporium cladosporioides type). Alternaria only represents between 0.1-1% of the total spores identified. In these spore types, the intraday variation was more acute inland than along the coastline due to oceanic influence. In the predictive models proposed that use the meteorological parameters with which a higher correlation was obtained (mean and maximum temperature) as predictive variables, it was seen that the predicted values did not reveal any significant differences as compared to those observed in 2006, data that was only used for verification purposes.

The incorrect usage of singular spectral analysis and discrete wavelet transform in hybrid models to predict hydrological time series

NASA Astrophysics Data System (ADS)

Du, Kongchang; Zhao, Ying; Lei, Jiaqiang

2017-09-01

In hydrological time series prediction, singular spectrum analysis (SSA) and discrete wavelet transform (DWT) are widely used as preprocessing techniques for artificial neural network (ANN) and support vector machine (SVM) predictors. These hybrid or ensemble models seem to largely reduce the prediction error. In current literature researchers apply these techniques to the whole observed time series and then obtain a set of reconstructed or decomposed time series as inputs to ANN or SVM. However, through two comparative experiments and mathematical deduction we found the usage of SSA and DWT in building hybrid models is incorrect. Since SSA and DWT adopt 'future' values to perform the calculation, the series generated by SSA reconstruction or DWT decomposition contain information of 'future' values. These hybrid models caused incorrect 'high' prediction performance and may cause large errors in practice.

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

Variation and Grey GM(1, 1) Prediction of Melting Peak Temperature of Polypropylene During Ultraviolet Radiation Aging

NASA Astrophysics Data System (ADS)

Chen, K.; Y Zhang, T.; Zhang, F.; Zhang, Z. R.

2017-12-01

Grey system theory regards uncertain system in which information is known partly and unknown partly as research object, extracts useful information from part known, and thereby revealing the potential variation rule of the system. In order to research the applicability of data-driven modelling method in melting peak temperature (T m) fitting and prediction of polypropylene (PP) during ultraviolet radiation aging, the T m of homo-polypropylene after different ultraviolet radiation exposure time investigated by differential scanning calorimeter was fitted and predicted by grey GM(1, 1) model based on grey system theory. The results show that the T m of PP declines with the prolong of aging time, and fitting and prediction equation obtained by grey GM(1, 1) model is T m = 166.567472exp(-0.00012t). Fitting effect of the above equation is excellent and the maximum relative error between prediction value and actual value of T m is 0.32%. Grey system theory needs less original data, has high prediction accuracy, and can be used to predict aging behaviour of PP.

USE OF SCORE AND CEREBROSPINAL FLUID LACTATE DOSAGE IN DIFFERENTIAL DIAGNOSIS OF BACTERIAL AND ASEPTIC MENINGITIS.

PubMed

Pires, Frederico Ribeiro; Franco, Andréia Christine Bonotto Farias; Gilio, Alfredo Elias; Troster, Eduardo Juan

2017-01-01

To evaluate Bacterial Meningitis Score (BMS) on its own and in association with Cerebrospinal Fluid (CSF) lactate dosage in order to distinguish bacterial from aseptic meningitis. Children diagnosed with meningitis at a tertiary hospital between January/2011 and December/2014 were selected. All data were obtained upon admission. BMS was applied and included: CSF Gram staining (2 points); CSF neutrophil count ≥1,000 cells/mm3 (1 point); CSF protein ≥80 mg/dL (1 point); peripheral blood neutrophil count ≥10,000 cells/mm3 (1 point) and seizures upon/before arrival (1 point). Cutoff value for CSF lactate was ≥30 mg/dL. Sensitivity, specificity and negative predictive value of several BMS cutoffs and BMS associated with high CSF lactate were evaluated for prediction of bacterial meningitis. Among 439 eligible patients, 94 did not have all data available to complete the score, and 345 patients were included: 7 in bacterial meningitis group and 338 in aseptic meningitis group. As predictive factors of bacterial meningitis, BMS ≥1 had 100% sensitivity (95%CI 47.3-100), 64.2% specificity (58.8-100) and 100% negative predictive value (97.5-100); BMS ≥2 or BMS ≥1 associated with high CSF lactate also showed 100% sensitivity (47.3-100); but 98.5% specificity (96.6-99.5) and 100% negative predictive value (98.3-100). 2 point BMS in association with CSF lactate dosage had the same sensitivity and negative predictive value, with increased specificity for diagnosis of bacterial meningitis when compared with 1-point BMS.

Simulation of CO2 Solubility in Polystyrene-b-Polybutadieneb-Polystyrene (SEBS) by artificial intelligence network (ANN) method

NASA Astrophysics Data System (ADS)

Sharudin, R. W.; AbdulBari Ali, S.; Zulkarnain, M.; Shukri, M. A.

2018-05-01

This study reports on the integration of Artificial Neural Network (ANNs) with experimental data in predicting the solubility of carbon dioxide (CO2) blowing agent in SEBS by generating highest possible value for Regression coefficient (R2). Basically, foaming of thermoplastic elastomer with CO2 is highly affected by the CO2 solubility. The ability of ANN in predicting interpolated data of CO2 solubility was investigated by comparing training results via different method of network training. Regards to the final prediction result for CO2 solubility by ANN, the prediction trend (output generate) was corroborated with the experimental results. The obtained result of different method of training showed the trend of output generated by Gradient Descent with Momentum & Adaptive LR (traingdx) required longer training time and required more accurate input to produce better output with final Regression Value of 0.88. However, it goes vice versa with Levenberg-Marquardt (trainlm) technique as it produced better output in quick detention time with final Regression Value of 0.91.

Quantum chemical study of the inhibition of the corrosion of mild steel in H2SO4 by some antibiotics.

PubMed

Eddy, Nnabuk O; Ibok, Udo J; Ebenso, Eno E; El Nemr, Ahmed; El Ashry, El Sayed H

2009-09-01

The inhibition efficiency of some antibiotics against mild steel corrosion was studied using weight loss and quantum chemical techniques. Values of inhibition efficiency obtained from weight loss measurements correlated strongly with theoretical values obtained through semi empirical calculations. High correlation coefficients were also obtained between inhibition efficiency of the antibiotics and some quantum chemical parameters, including frontier orbital (E (HOMO) and E (LUMO)), dipole moment, log P, TNC and LSER parameters (critical volume and dipolar-polarisability factor), which indicated that these parameters affect the inhibition efficiency of the compounds. It was also found that quantitative structure activity relation can be used to adequately predict the inhibition effectiveness of these compounds.

Pore morphology effect in microlog for porosity prediction in a mature field

USGS Publications Warehouse

Teh, W.J.; Willhite, G.P.; Doveton, J.H.; Tsau, J.S.

2011-01-01

In an matured field, developed during the 1950s, no porosity logs were available from sources other than invaded zone resistivity Rxo . The microresistivity porosity is calibrated with the core porosity to yield an accurate estimate of the porosity. However, the procedure of calibrating the porosity with Rxo for a linear regression model may not be predictive without an understanding of the pore types in the reservoir interval. A thorough investigation of the pore types, based on the lithofacies description obtained from the core analysis, and its role in obtaining a good estimate of porosity is demonstrated in the Ogallah field. Therefore, the objective of this paper is to separate the porosity-microlog data into pore-type based zones with characteristic cementation exponents (m) in this multi-petrotype reservoir with a complex mixture of Arbuckle dolomite and sandstone rock. The value of m is critical in making estimates of water saturation. "Rule of thumb" values of cementation might lead to errors in water saturation on either the optimistic or the pessimistic side. The rock types in the Ogallah contain interparticle/intercrystalline, vugs and fractures distributed through the rock-facies, which influence the values of cementation factor. We use the modern typed well to shed light on the Archie's equation parameter values. Rock fabric numbers and flow zone indices have been identified for classification of dolomite and sandstone, respectively. The analysis brings out characteristic cementation factors for distinct pore types in the Arbuckle rock. The porosity predictions The analysis results also compliment the petrofacies delineation using LDA in this complicated rock layout as a quality control of the statistical application. The comparison between the predicted and core porosities shows a significant improvement over using a single m value for carbonates and sandstones which will lead to improved description of a matured field. Copyright 2011, Society of Petroleum Engineers.

GenoMatrix: A Software Package for Pedigree-Based and Genomic Prediction Analyses on Complex Traits.

PubMed

Nazarian, Alireza; Gezan, Salvador Alejandro

2016-07-01

Genomic and pedigree-based best linear unbiased prediction methodologies (G-BLUP and P-BLUP) have proven themselves efficient for partitioning the phenotypic variance of complex traits into its components, estimating the individuals' genetic merits, and predicting unobserved (or yet-to-be observed) phenotypes in many species and fields of study. The GenoMatrix software, presented here, is a user-friendly package to facilitate the process of using genome-wide marker data and parentage information for G-BLUP and P-BLUP analyses on complex traits. It provides users with a collection of applications which help them on a set of tasks from performing quality control on data to constructing and manipulating the genomic and pedigree-based relationship matrices and obtaining their inverses. Such matrices will be then used in downstream analyses by other statistical packages. The package also enables users to obtain predicted values for unobserved individuals based on the genetic values of observed related individuals. GenoMatrix is available to the research community as a Windows 64bit executable and can be downloaded free of charge at: http://compbio.ufl.edu/software/genomatrix/. © The American Genetic Association. 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Wet tropospheric delays forecast based on Vienna Mapping Function time series analysis

NASA Astrophysics Data System (ADS)

Rzepecka, Zofia; Kalita, Jakub

2016-04-01

It is well known that the dry part of the zenith tropospheric delay (ZTD) is much easier to model than the wet part (ZTW). The aim of the research is applying stochastic modeling and prediction of ZTW using time series analysis tools. Application of time series analysis enables closer understanding of ZTW behavior as well as short-term prediction of future ZTW values. The ZTW data used for the studies were obtained from the GGOS service hold by Vienna technical University. The resolution of the data is six hours. ZTW for the years 2010 -2013 were adopted for the study. The International GNSS Service (IGS) permanent stations LAMA and GOPE, located in mid-latitudes, were admitted for the investigations. Initially the seasonal part was separated and modeled using periodic signals and frequency analysis. The prominent annual and semi-annual signals were removed using sines and consines functions. The autocorrelation of the resulting signal is significant for several days (20-30 samples). The residuals of this fitting were further analyzed and modeled with ARIMA processes. For both the stations optimal ARMA processes based on several criterions were obtained. On this basis predicted ZTW values were computed for one day ahead, leaving the white process residuals. Accuracy of the prediction can be estimated at about 3 cm.

Theoretical and experimental prediction of the redox potentials of metallocene compounds

NASA Astrophysics Data System (ADS)

Li, Ya-Ping; Liu, Hai-Bo; Liu, Tao; Yu, Zhang-Yu

2017-11-01

The standard redox electrode potential ( E°) values of metallocene compounds are obtained theoretically with density functional theory (DFT) method at B3LYP/6-311++G( d, p) level and experimentally with cyclic voltammetry (CV). The theoretical E° values of metallocene compounds are in good agreement with experimental ones. We investigate the substituent effects on the redox properties of metallocene compounds. Among the four metallocene compounds, the E° values is largest for titanocene dichloride and smallest for ferrocene.

Genomic selection in sugar beet breeding populations.

PubMed

Würschum, Tobias; Reif, Jochen C; Kraft, Thomas; Janssen, Geert; Zhao, Yusheng

2013-09-18

Genomic selection exploits dense genome-wide marker data to predict breeding values. In this study we used a large sugar beet population of 924 lines representing different germplasm types present in breeding populations: unselected segregating families and diverse lines from more advanced stages of selection. All lines have been intensively phenotyped in multi-location field trials for six agronomically important traits and genotyped with 677 SNP markers. We used ridge regression best linear unbiased prediction in combination with fivefold cross-validation and obtained high prediction accuracies for all except one trait. In addition, we investigated whether a calibration developed based on a training population composed of diverse lines is suited to predict the phenotypic performance within families. Our results show that the prediction accuracy is lower than that obtained within the diverse set of lines, but comparable to that obtained by cross-validation within the respective families. The results presented in this study suggest that a training population derived from intensively phenotyped and genotyped diverse lines from a breeding program does hold potential to build up robust calibration models for genomic selection. Taken together, our results indicate that genomic selection is a valuable tool and can thus complement the genomics toolbox in sugar beet breeding.

Ratio of ovarian stroma and total ovarian area by ultrasound in prediction of hyperandrogenemia in reproductive-aged Thai women with polycystic ovary syndrome: a diagnostic test.

PubMed

Leerasiri, Pichai; Wongwananuruk, Thanyarat; Rattanachaiyanont, Manee; Indhavivadhana, Suchada; Techatraisak, Kitirat; Angsuwathana, Surasak

2015-02-01

To evaluate the performance of ovarian stromal area to total ovarian area (S/A) ratio for the prediction of biochemical hyperandrogenism in Thai women with polycystic ovary syndrome (PCOS). A cross-sectional study was performed in 222 reproductive-aged Thai women with PCOS attending the Gynecologic Endocrinology Unit (GEU), Department of Obstetrics and Gynecology, Faculty of Medicine Siriraj Hospital from May 2007 to January 2009. The patients were interviewed for medical history and examined for anthropometry and clinical hyperandrogenism. Venous blood samples were obtained for androgen profiles. An ovarian ultrasonogram was obtained via transvaginal or transrectal ultrasonography. The prevalences of clinical and biochemical hyperandrogenism were 48.6% and 81.1%, respectively. The S/A ratio at a cut-off point of 0.33 had modest predictability for hyperandrogenism, namely, 0.537 area under the receiver-operator curve, 36.6% sensitivity, 72.1% specificity, 83.8% positive predictive value (PPV) and 20.9% negative predictive value (NPV). The combination of clinical hyperandrogenism and S/A ratio improved the predictability for biochemical hyperandrogenism, with sensitivity, specificity, PPV and NPV of 72.1%, 58.1%, 87.8% and 33.3%, respectively. The S/A ratio alone is not a good predictor for biochemical hyperandrogenism in Thai PCOS women attending GEU for menstrual dysfunction. The combination of S/A ratio and clinical hyperandrogenism has better performance than the S/A ratio alone to predict biochemical hyperandrogenism. © 2014 The Authors. Journal of Obstetrics and Gynaecology Research © 2014 Japan Society of Obstetrics and Gynecology.

Ultrasound-enhanced bioscouring of greige cotton: regression analysis of process factors

USDA-ARS?s Scientific Manuscript database

Ultrasound-enhanced bioscouring process factors for greige cotton fabric are examined using custom experimental design utilizing statistical principles. An equation is presented which predicts bioscouring performance based upon percent reflectance values obtained from UV-Vis measurements of rutheniu...

A novel multi-target regression framework for time-series prediction of drug efficacy.

PubMed

Li, Haiqing; Zhang, Wei; Chen, Ying; Guo, Yumeng; Li, Guo-Zheng; Zhu, Xiaoxin

2017-01-18

Excavating from small samples is a challenging pharmacokinetic problem, where statistical methods can be applied. Pharmacokinetic data is special due to the small samples of high dimensionality, which makes it difficult to adopt conventional methods to predict the efficacy of traditional Chinese medicine (TCM) prescription. The main purpose of our study is to obtain some knowledge of the correlation in TCM prescription. Here, a novel method named Multi-target Regression Framework to deal with the problem of efficacy prediction is proposed. We employ the correlation between the values of different time sequences and add predictive targets of previous time as features to predict the value of current time. Several experiments are conducted to test the validity of our method and the results of leave-one-out cross-validation clearly manifest the competitiveness of our framework. Compared with linear regression, artificial neural networks, and partial least squares, support vector regression combined with our framework demonstrates the best performance, and appears to be more suitable for this task.

A novel multi-target regression framework for time-series prediction of drug efficacy

PubMed Central

Li, Haiqing; Zhang, Wei; Chen, Ying; Guo, Yumeng; Li, Guo-Zheng; Zhu, Xiaoxin

2017-01-01

Excavating from small samples is a challenging pharmacokinetic problem, where statistical methods can be applied. Pharmacokinetic data is special due to the small samples of high dimensionality, which makes it difficult to adopt conventional methods to predict the efficacy of traditional Chinese medicine (TCM) prescription. The main purpose of our study is to obtain some knowledge of the correlation in TCM prescription. Here, a novel method named Multi-target Regression Framework to deal with the problem of efficacy prediction is proposed. We employ the correlation between the values of different time sequences and add predictive targets of previous time as features to predict the value of current time. Several experiments are conducted to test the validity of our method and the results of leave-one-out cross-validation clearly manifest the competitiveness of our framework. Compared with linear regression, artificial neural networks, and partial least squares, support vector regression combined with our framework demonstrates the best performance, and appears to be more suitable for this task. PMID:28098186

Prediction of friction pressure drop for low pressure two-phase flows on the basis of approximate analytical models

NASA Astrophysics Data System (ADS)

Zubov, N. O.; Kaban'kov, O. N.; Yagov, V. V.; Sukomel, L. A.

2017-12-01

Wide use of natural circulation loops operating at low redused pressures generates the real need to develop reliable methods for predicting flow regimes and friction pressure drop for two-phase flows in this region of parameters. Although water-air flows at close-to-atmospheric pressures are the most widely studied subject in the field of two-phase hydrodynamics, the problem of reliably calculating friction pressure drop can hardly be regarded to have been fully solved. The specific volumes of liquid differ very much from those of steam (gas) under such conditions, due to which even a small change in flow quality may cause the flow pattern to alter very significantly. Frequently made attempts to use some or another universal approach to calculating friction pressure drop in a wide range of steam quality values do not seem to be justified and yield predicted values that are poorly consistent with experimentally measured data. The article analyzes the existing methods used to calculate friction pressure drop for two-phase flows at low pressures by comparing their results with the experimentally obtained data. The advisability of elaborating calculation procedures for determining the friction pressure drop and void fraction for two-phase flows taking their pattern (flow regime) into account is demonstrated. It is shown that, for flows characterized by low reduced pressures, satisfactory results are obtained from using a homogeneous model for quasi-homogeneous flows, whereas satisfactory results are obtained from using an annular flow model for flows characterized by high values of void fraction. Recommendations for making a shift from one model to another in carrying out engineering calculations are formulated and tested. By using the modified annular flow model, it is possible to obtain reliable predictions for not only the pressure gradient but also for the liquid film thickness; the consideration of droplet entrainment and deposition phenomena allows reasonable corrections to be introduced into calculations. To the best of the authors' knowledge, it is for the first time that the entrainment of droplets from the film surface is taken into consideration in the dispersed-annular flow model.

Summary of longitudinal stability and control parameters as determined from Space Shuttle Challenger flight test data

NASA Technical Reports Server (NTRS)

Suit, William T.

1989-01-01

Estimates of longitudinal stability and control parameters for the space shuttle were determined by applying a maximum likelihood parameter estimation technique to Challenger flight test data. The parameters for pitching moment coefficient, C(m sub alpha), (at different angles of attack), pitching moment coefficient, C(m sub delta e), (at different elevator deflections) and the normal force coefficient, C(z sub alpha), (at different angles of attack) describe 90 percent of the response to longitudinal inputs during Space Shuttle Challenger flights with C(m sub delta e) being the dominant parameter. The values of C(z sub alpha) were found to be input dependent for these tests. However, when C(z sub alpha) was set at preflight predictions, the values determined for C(m sub delta e) changed less than 10 percent from the values obtained when C(z sub alpha) was estimated as well. The preflight predictions for C(z sub alpha) and C(m sub alpha) are acceptable values, while the values of C(z sub delta e) should be about 30 percent less negative than the preflight predictions near Mach 1, and 10 percent less negative, otherwise.

Monthly prediction of air temperature in Australia and New Zealand with machine learning algorithms

NASA Astrophysics Data System (ADS)

Salcedo-Sanz, S.; Deo, R. C.; Carro-Calvo, L.; Saavedra-Moreno, B.

2016-07-01

Long-term air temperature prediction is of major importance in a large number of applications, including climate-related studies, energy, agricultural, or medical. This paper examines the performance of two Machine Learning algorithms (Support Vector Regression (SVR) and Multi-layer Perceptron (MLP)) in a problem of monthly mean air temperature prediction, from the previous measured values in observational stations of Australia and New Zealand, and climate indices of importance in the region. The performance of the two considered algorithms is discussed in the paper and compared to alternative approaches. The results indicate that the SVR algorithm is able to obtain the best prediction performance among all the algorithms compared in the paper. Moreover, the results obtained have shown that the mean absolute error made by the two algorithms considered is significantly larger for the last 20 years than in the previous decades, in what can be interpreted as a change in the relationship among the prediction variables involved in the training of the algorithms.

NIR spectroscopy for the quality control of Moringa oleifera (Lam.) leaf powders: Prediction of minerals, protein and moisture contents.

PubMed

Rébufa, Catherine; Pany, Inès; Bombarda, Isabelle

2018-09-30

A rapid methodology was developed to simultaneously predict water content and activity values (a w ) of Moringa oleifera leaf powders (MOLP) using near infrared (NIR) signatures and experimental sorption isotherms. NIR spectra of MOLP samples (n = 181) were recorded. A Partial Least Square Regression model (PLS2) was obtained with low standard errors of prediction (SEP of 1.8% and 0.07 for water content and a w respectively). Experimental sorption isotherms obtained at 20, 30 and 40 °C showed similar profiles. This result is particularly important to use MOLP in food industry. In fact, a temperature variation of the drying process will not affect their available water content (self-life). Nutrient contents based on protein and selected minerals (Ca, Fe, K) were also predicted from PLS1 models. Protein contents were well predicted (SEP of 2.3%). This methodology allowed for an improvement in MOLP safety, quality control and traceability. Published by Elsevier Ltd.

Evaluation of Computational Fluid Dynamics and Coupled Fluid-Solid Modeling for a Direct Transfer Preswirl System.

PubMed

Javiya, Umesh; Chew, John; Hills, Nick; Dullenkopf, Klaus; Scanlon, Timothy

2013-05-01

The prediction of the preswirl cooling air delivery and disk metal temperature are important for the cooling system performance and the rotor disk thermal stresses and life assessment. In this paper, standalone 3D steady and unsteady computation fluid dynamics (CFD), and coupled FE-CFD calculations are presented for prediction of these temperatures. CFD results are compared with previous measurements from a direct transfer preswirl test rig. The predicted cooling air temperatures agree well with the measurement, but the nozzle discharge coefficients are under predicted. Results from the coupled FE-CFD analyses are compared directly with thermocouple temperature measurements and with heat transfer coefficients on the rotor disk previously obtained from a rotor disk heat conduction solution. Considering the modeling limitations, the coupled approach predicted the solid metal temperatures well. Heat transfer coefficients on the rotor disk from CFD show some effect of the temperature variations on the heat transfer coefficients. Reasonable agreement is obtained with values deduced from the previous heat conduction solution.

Magnetic resonance spectroscopy and brain volumetry in mild cognitive impairment. A prospective study.

PubMed

Fayed, Nicolás; Modrego, Pedro J; García-Martí, Gracián; Sanz-Requena, Roberto; Marti-Bonmatí, Luis

2017-05-01

To assess the accuracy of magnetic resonance spectroscopy (1H-MRS) and brain volumetry in mild cognitive impairment (MCI) to predict conversion to probable Alzheimer's disease (AD). Forty-eight patients fulfilling the criteria of amnestic MCI who underwent a conventional magnetic resonance imaging (MRI) followed by MRS, and T1-3D on 1.5 Tesla MR unit. At baseline the patients underwent neuropsychological examination. 1H-MRS of the brain was carried out by exploring the left medial occipital lobe and ventral posterior cingulated cortex (vPCC) using the LCModel software. A high resolution T1-3D sequence was acquired to carry out the volumetric measurement. A cortical and subcortical parcellation strategy was used to obtain the volumes of each area within the brain. The patients were followed up to detect conversion to probable AD. After a 3-year follow-up, 15 (31.2%) patients converted to AD. The myo-inositol in the occipital cortex and glutamate+glutamine (Glx) in the posterior cingulate cortex predicted conversion to probable AD at 46.1% sensitivity and 90.6% specificity. The positive predictive value was 66.7%, and the negative predictive value was 80.6%, with an overall cross-validated classification accuracy of 77.8%. The volume of the third ventricle, the total white matter and entorhinal cortex predict conversion to probable AD at 46.7% sensitivity and 90.9% specificity. The positive predictive value was 70%, and the negative predictive value was 78.9%, with an overall cross-validated classification accuracy of 77.1%. Combining volumetric measures in addition to the MRS measures the prediction to probable AD has a 38.5% sensitivity and 87.5% specificity, with a positive predictive value of 55.6%, a negative predictive value of 77.8% and an overall accuracy of 73.3%. Either MRS or brain volumetric measures are markers separately of cognitive decline and may serve as a noninvasive tool to monitor cognitive changes and progression to dementia in patients with amnestic MCI, but the results do not support the routine use in the clinical settings. Copyright © 2016 Elsevier Inc. All rights reserved.

Fetal gender prediction based on maternal plasma testosterone and insulin-like peptide 3 concentrations at midgestation and late gestation in cattle.

PubMed

Kibushi, M; Kawate, N; Kaminogo, Y; Hannan, M A; Weerakoon, W W P N; Sakase, M; Fukushima, M; Seyama, T; Inaba, T; Tamada, H

2016-10-15

We compared maternal plasma testosterone and insulin-like peptide 3 (INSL3) concentrations between dams carrying a male versus female fetus from early to late gestation and examined the application of maternal hormonal concentrations to fetal gender prediction in dairy and beef cattle. Blood samples were collected from Holstein cows or heifers (N = 31) and Japanese Black beef cows (N = 33) at 1-month intervals at 2 to 8 months of gestation. Fetal gender was confirmed by visual observation of external genitalia of calves just after birth. Plasma testosterone and INSL3 concentrations were determined by enzyme-immunoassay. Fetal genders were judged based on cutoff values of maternal testosterone and INSL3 concentrations (male, if it was ≥ cutoff value; female, if < cutoff value), which we set for each hormone at each gestational month using receiver operating characteristic curves. Plasma testosterone concentrations were higher for dams with a male fetus than those with a female at 4, 5, 7, and 8 months for the dairy cattle (P < 0.05) and at 4, 5, 6, and 8 months for the beef cows (P < 0.05). Plasma INSL3 concentrations were higher for dams with a male fetus than those with a female at 2 and 6 months for the dairy cattle (P < 0.05) and at 4 to 8 months for the beef cows (P < 0.05). The predictive values and detection rates for fetal gender prediction based on maternal testosterone concentrations were 75.8% to 79.3% for dairy cattle at 5 and 7 months and for beef cows at 5 and 6 months, whereas those values by maternal INSL3 concentrations were 71.0% to 72.4% for the dairy cattle at 6 months and beef cows at 4 and 8 months. When multiple time points of testosterone and INSL3 concentrations at several midgestation and late gestation months were considered for fetal gender prediction, predictive values were 89.3% (5-7 months) and 85.7% to 88.0% (4-6, 8 months) for the dairy and beef breeds, respectively. Maternal testosterone and INSL3 concentrations in dams carrying a male fetus were higher than those carrying a female at midgestation and/or late gestation in Holstein and Japanese Black beef cattle. Nearly, 80% accuracy was obtained for fetal gender prediction by a single time point of maternal plasma testosterone concentrations at midgestation. Nearly 90% accuracy for the prediction was obtained when multiple time points of testosterone and INSL3 concentrations from midgestation to late gestation were considered. Copyright © 2016 Elsevier Inc. All rights reserved.

Could texture features from preoperative CT image be used for predicting occult peritoneal carcinomatosis in patients with advanced gastric cancer?

PubMed

Kim, Hae Young; Kim, Young Hoon; Yun, Gabin; Chang, Won; Lee, Yoon Jin; Kim, Bohyoung

2018-01-01

To retrospectively investigate whether texture features obtained from preoperative CT images of advanced gastric cancer (AGC) patients could be used for the prediction of occult peritoneal carcinomatosis (PC) detected during operation. 51 AGC patients with occult PC detected during operation from January 2009 to December 2012 were included as occult PC group. For the control group, other 51 AGC patients without evidence of distant metastasis including PC, and whose clinical T and N stage could be matched to those of the patients of the occult PC group, were selected from the period of January 2011 to July 2012. Each group was divided into test (n = 41) and validation cohort (n = 10). Demographic and clinical data of these patients were acquired from the hospital database. Texture features including average, standard deviation, kurtosis, skewness, entropy, correlation, and contrast were obtained from manually drawn region of interest (ROI) over the omentum on the axial CT image showing the omentum at its largest cross sectional area. After using Fisher's exact and Wilcoxon signed-rank test for comparison of the clinical and texture features between the two groups of the test cohort, conditional logistic regression analysis was performed to determine significant independent predictor for occult PC. Using the optimal cut-off value from receiver operating characteristic (ROC) analysis for the significant variables, diagnostic sensitivity and specificity were determined in the test cohort. The cut-off value of the significant variables obtained from the test cohort was then applied to the validation cohort. Bonferroni correction was used to adjust P value for multiple comparisons. Between the two groups, there was no significant difference in the clinical features. Regarding the texture features, the occult PC group showed significantly higher average, entropy, standard deviation, and significantly lower correlation (P value < 0.004 for all). Conditional logistic regression analysis demonstrated that entropy was significant independent predictor for occult PC. When the cut-off value of entropy (> 7.141) was applied to the validation cohort, sensitivity and specificity for the prediction of occult PC were 80% and 90%, respectively. For AGC patients whose PC cannot be detected with routine imaging such as CT, texture analysis may be a useful adjunct for the prediction of occult PC.

Validation of Medicaid claims-based diagnosis of myocardial infarction using an HIV clinical cohort

PubMed Central

Brouwer, Emily S.; Napravnik, Sonia; Eron, Joseph J; Simpson, Ross J; Brookhart, M. Alan; Stalzer, Brant; Vinikoor, Michael; Floris-Moore, Michelle; Stürmer, Til

2014-01-01

Background In non-experimental comparative effectiveness research using healthcare databases, outcome measurements must be validated to evaluate and potentially adjust for misclassification bias. We aimed to validate claims-based myocardial infarction algorithms in a Medicaid population using an HIV clinical cohort as the gold standard. Methods Medicaid administrative data were obtained for the years 2002–2008 and linked to the UNC CFAR HIV Clinical Cohort based on social security number, first name and last name and myocardial infarction were adjudicated. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated. Results There were 1,063 individuals included. Over a median observed time of 2.5 years, 17 had a myocardial infarction. Specificity ranged from 0.979–0.993 with the highest specificity obtained using criteria with the ICD-9 code in the primary and secondary position and a length of stay ≥ 3 days. Sensitivity of myocardial infarction ascertainment varied from 0.588–0.824 depending on algorithm. Conclusion: Specificities of varying claims-based myocardial infarction ascertainment criteria are high but small changes impact positive predictive value in a cohort with low incidence. Sensitivities vary based on ascertainment criteria. Type of algorithm used should be prioritized based on study question and maximization of specific validation parameters that will minimize bias while also considering precision. PMID:23604043

Stochastic Theory for the Clustering of Rapidly Settling, Low-Inertia Particle Pairs in Isotropic Turbulence - II

NASA Astrophysics Data System (ADS)

Rani, Sarma; Gupta, Vijay; Koch, Donald

2017-11-01

A stochastic theory is developed to predict the Radial Distribution Function (RDF) of monodisperse, rapidly settling, low-inertia particle pairs in isotropic turbulence. In the second version of the theory (T2), the dimensionless strain-rate and rotation-rate tensors ``seen'' by the primary particle are assumed to be Gaussian distributed, where the strain-rate and rotation-rate tensors are non-dimensionlized using the instantaneous dissipation rate and enstrophy, respectively. Accordingly, closure is again derived for the drift flux driving particle clustering, in the asympotic limits of Stokes number St =τp /τη << 1 , and settling paramater Sv = gτp /uη >> 1 . Only the drift flux differs for T1 and T2, while the diffusive flux remains the same. The RDFs for rapidly settling pairs again show an inverse power dependency on pair separation r with an exponent, c1, that is proportional to St2 . However, in contrast to T1, the c1 values predicted by T2 show good qualitative and resonable quantitative agreement with the c1 values obtained from DNS of settling particles in isotropic turbulence. Further, the T2-predicted c1 values are smaller than those obtained from DNS of non-settling particles in isotropic turbulence. Funding from the CBET Division of the National Science Foundation is gratefully acknowledged.

Prediction of glass transition temperature of freeze-dried formulations by molecular dynamics simulation.

PubMed

Yoshioka, Sumie; Aso, Yukio; Kojima, Shigeo

2003-06-01

To examine whether the glass transition temperature (Tg) of freeze-dried formulations containing polymer excipients can be accurately predicted by molecular dynamics simulation using software currently available on the market. Molecular dynamics simulations were carried out for isomaltodecaose, a fragment of dextran, and alpha-glucose, the repeated unit of dextran. in the presence or absence of water molecules. Estimated values of Tg were compared with experimental values obtained by differential scanning calorimetry (DSC). Isothermal-isobaric molecular dynamics simulations (NPTMD) and isothermal molecular dynamics simulations at a constant volume (NVTMD) were carried out using the software package DISCOVER (Material Studio) with the Polymer Consortium Force Field. Mean-squared displacement and radial distribution function were calculated. NVTMD using the values of density obtained by NPTMD provided the diffusivity of glucose-ring oxygen and water oxygen in amorphous alpha-glucose and isomaltodecaose, which exhibited a discontinuity in temperature dependence due to glass transition. Tg was estimated to be approximately 400K and 500K for pure amorphous a-glucose and isomaltodecaose, respectively, and in the presence of one water molecule per glucose unit, Tg was 340K and 360K, respectively. Estimated Tg values were higher than experimentally determined values because of the very fast cooling rates in the simulations. However, decreases in Tg on hydration and increases in Tg associated with larger fragment size could be demonstrated. The results indicate that molecular dynamics simulation is a useful method for investigating the effects of hydration and molecular weight on the Tg of lyophilized formulations containing polymer excipients. although the relationship between cooling rates and Tg must first be elucidated to predict Tg vales observed by DSC measurement. January 16.

Influence of cone beam CT enhancement filters on diagnosis ability of longitudinal root fractures

PubMed Central

Nascimento, M C C; Nejaim, Y; de Almeida, S M; Bóscolo, F N; Haiter-Neto, F; Sobrinho, L C

2014-01-01

Objectives: To determine whether cone beam CT (CBCT) enhancement filters influence the diagnosis of longitudinal root fractures. Methods: 40 extracted human posterior teeth were endodontically prepared, and fractures with no separation of fragments were made in 20 teeth of this sample. The teeth were placed in a dry mandible and scanned using a Classic i-CAT® CBCT device (Imaging Sciences International, Inc., Hatfield, PA). Evaluations were performed with and without CBCT filters (Sharpen Mild, Sharpen Super Mild, S9, Sharpen, Sharpen 3 × 3, Angio Sharpen Medium 5 × 5, Angio Sharpen High 5 × 5 and Shadow 3 × 3) by three oral radiologists. Inter- and intraobserver agreement was calculated by the kappa test. Accuracy, sensitivity, specificity and positive and negative predictive values were determined. McNemar test was applied for agreement between all images vs the gold standard and original images vs images with filters (p < 0.05). Results: Means of intraobserver agreement ranged from good to excellent. Angio Sharpen Medium 5 × 5 filter obtained the highest positive predictive value (80.0%) and specificity value (76.5%). Angio Sharpen High 5 × 5 filter obtained the highest sensitivity (78.9%) and accuracy (77.5%) value. Negative predictive value was the highest (82.9%) for S9 filter. The McNemar test showed no statistically significant differences between images with and without CBCT filters (p > 0.05). Conclusions: Although no statistical differences was observed in the diagnosis of root fractures when using filters, these filters seem to improve diagnostic capacity for longitudinal root fractures. Further in vitro studies with endodontic-treated teeth and research in vivo should be considered. PMID:24408819

Artificial neural network modeling and optimization of ultrahigh pressure extraction of green tea polyphenols.

PubMed

Xi, Jun; Xue, Yujing; Xu, Yinxiang; Shen, Yuhong

2013-11-01

In this study, the ultrahigh pressure extraction of green tea polyphenols was modeled and optimized by a three-layer artificial neural network. A feed-forward neural network trained with an error back-propagation algorithm was used to evaluate the effects of pressure, liquid/solid ratio and ethanol concentration on the total phenolic content of green tea extracts. The neural network coupled with genetic algorithms was also used to optimize the conditions needed to obtain the highest yield of tea polyphenols. The obtained optimal architecture of artificial neural network model involved a feed-forward neural network with three input neurons, one hidden layer with eight neurons and one output layer including single neuron. The trained network gave the minimum value in the MSE of 0.03 and the maximum value in the R(2) of 0.9571, which implied a good agreement between the predicted value and the actual value, and confirmed a good generalization of the network. Based on the combination of neural network and genetic algorithms, the optimum extraction conditions for the highest yield of green tea polyphenols were determined as follows: 498.8 MPa for pressure, 20.8 mL/g for liquid/solid ratio and 53.6% for ethanol concentration. The total phenolic content of the actual measurement under the optimum predicated extraction conditions was 582.4 ± 0.63 mg/g DW, which was well matched with the predicted value (597.2mg/g DW). This suggests that the artificial neural network model described in this work is an efficient quantitative tool to predict the extraction efficiency of green tea polyphenols. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Prediction of drug intestinal absorption in human using the Ussing chamber system: A comparison of intestinal tissues from animals and humans.

PubMed

Miyake, Masateru; Koga, Toshihisa; Kondo, Satoshi; Yoda, Noriaki; Emoto, Chie; Mukai, Tadashi; Toguchi, Hajime

2017-01-01

An adequate evaluation system for drug intestinal absorption is essential in the pharmaceutical industry. Previously, we established a novel prediction system of drug intestinal absorption in humans, using the mini-Ussing chamber equipped with human intestinal tissues. In this system, the TI value was defined as the sum of drug amounts transported to the basal-side component (X corr ) and drug amounts accumulated in the tissue (T corr ), which are normalized by AUC of a drug in the apical compartment, as an index for drug absorption. In order to apply this system to the screening assay, it is important to understand the differences between animal and human tissues in the intestinal absorption of drugs. In this study, the transport index (TI) values of three drugs, with different levels of membrane permeability, were determined to evaluate the rank order of drug absorbability in intestinal tissues from rats, dogs, and monkeys. The TI values in small intestinal tissues in rats and dogs showed a good correlation with those in humans. On the other hand, the correlation of TI values in monkeys was lower compared to rats and dogs. The rank order of the correlation coefficient between human and investigated animal tissues was as follows: dog (r 2 =0.978), rat (r 2 =0.955), and monkey (r 2 =0.620). TI values in large intestinal tissues from rats (r 2 =0.929) and dogs (r 2 =0.808) also showed a good correlation. The obtained TI values in small intestinal tissues in rats and dogs were well correlated with the fraction of drug absorbed (F a ) in humans. From these results, the mini-Ussing chamber, equipped with intestinal tissues in rats and dogs, would be useful as a screening tool in the drug discovery stage. In addition, the obtained TI values can be used for the prediction of the F a in humans. Copyright © 2016 Elsevier B.V. All rights reserved.

A study to ascertain the viability of ultrasonic nondestructive testing to determine the mechanical characteristics of wood/agricultural hardboards with soybean based adhesives

NASA Astrophysics Data System (ADS)

Colen, Charles Raymond, Jr.

There have been numerous studies with ultrasonic nondestructive testing and wood fiber composites. The problem of the study was to ascertain whether ultrasonic nondestructive testing can be used in place of destructive testing to obtain the modulus of elasticity (MOE) of the wood/agricultural material with comparable results. The uniqueness of this research is that it addressed the type of content (cornstalks and switchgrass) being used with the wood fibers and the type of adhesives (soybean-based) associated with the production of these composite materials. Two research questions were addressed in the study. The major objective was to determine if one can predict the destructive test MOE value based on the nondestructive test MOE value. The population of the study was wood/agricultural fiberboards made from wood fibers, cornstalks, and switchgrass bonded together with soybean-based, urea-formaldehyde, and phenol-formaldehyde adhesives. Correlational analysis was used to determine if there was a relationship between the two tests. Regression analysis was performed to determine a prediction equation for the destructive test MOE value. Data were collected on both procedures using ultrasonic nondestructing testing and 3-point destructive testing. The results produced a simple linear regression model for this study which was adequate in the prediction of destructive MOE values if the nondestructive MOE value is known. An approximation very close to the entire error in the model equation was explained from the destructive test MOE values for the composites. The nondestructive MOE values used to produce a linear regression model explained 83% of the variability in the destructive test MOE values. The study also showed that, for the particular destructive test values obtained with the equipment used, the model associated with the study is as good as it could be due to the variability in the results from the destructive tests. In this study, an ultrasonic signal was used to determine the MOE values on nondestructive tests. Future research studies could use the same or other hardboards to examine how the resins affect the ultrasonic signal.

Repopulation of calibrations with samples from the target site: effect of the size of the calibration.

NASA Astrophysics Data System (ADS)

Guerrero, C.; Zornoza, R.; Gómez, I.; Mataix-Solera, J.; Navarro-Pedreño, J.; Mataix-Beneyto, J.; García-Orenes, F.

2009-04-01

Near infrared (NIR) reflectance spectroscopy offers important advantages because is a non-destructive technique, the pre-treatments needed in samples are minimal, and the spectrum of the sample is obtained in less than 1 minute without the needs of chemical reagents. For these reasons, NIR is a fast and cost-effective method. Moreover, NIR allows the analysis of several constituents or parameters simultaneously from the same spectrum once it is obtained. For this, a needed steep is the development of soil spectral libraries (set of samples analysed and scanned) and calibrations (using multivariate techniques). The calibrations should contain the variability of the target site soils in which the calibration is to be used. Many times this premise is not easy to fulfil, especially in libraries recently developed. A classical way to solve this problem is through the repopulation of libraries and the subsequent recalibration of the models. In this work we studied the changes in the accuracy of the predictions as a consequence of the successive addition of samples to repopulation. In general, calibrations with high number of samples and high diversity are desired. But we hypothesized that calibrations with lower quantities of samples (lower size) will absorb more easily the spectral characteristics of the target site. Thus, we suspect that the size of the calibration (model) that will be repopulated could be important. For this reason we also studied this effect in the accuracy of predictions of the repopulated models. In this study we used those spectra of our library which contained data of soil Kjeldahl Nitrogen (NKj) content (near to 1500 samples). First, those spectra from the target site were removed from the spectral library. Then, different quantities of samples of the library were selected (representing the 5, 10, 25, 50, 75 and 100% of the total library). These samples were used to develop calibrations with different sizes (%) of samples. We used partial least squares regression, and leave-one-out cross validation as methods of calibration. Two methods were used to select the different quantities (size of models) of samples: (1) Based on Characteristics of Spectra (BCS), and (2) Based on NKj Values of Samples (BVS). Both methods tried to select representative samples. Each of the calibrations (containing the 5, 10, 25, 50, 75 or 100% of the total samples of the library) was repopulated with samples from the target site and then recalibrated (by leave-one-out cross validation). This procedure was sequential. In each step, 2 samples from the target site were added to the models, and then recalibrated. This process was repeated successively 10 times, being 20 the total number of samples added. A local model was also created with the 20 samples used for repopulation. The repopulated, non-repopulated and local calibrations were used to predict the NKj content in those samples from the target site not included in repopulations. For the measurement of the accuracy of the predictions, the r2, RMSEP and slopes were calculated comparing predicted with analysed NKj values. This scheme was repeated for each of the four target sites studied. In general, scarce differences can be found between results obtained with BCS and BVS models. We observed that the repopulation of models increased the r2 of the predictions in sites 1 and 3. The repopulation caused scarce changes of the r2 of the predictions in sites 2 and 4, maybe due to the high initial values (using non-repopulated models r2 >0.90). As consequence of repopulation, the RMSEP decreased in all the sites except in site 2, where a very low RMESP was obtained before the repopulation (0.4 g×kg-1). The slopes trended to approximate to 1, but this value was reached only in site 4 and after the repopulation with 20 samples. In sites 3 and 4, accurate predictions were obtained using the local models. Predictions obtained with models using similar size of samples (similar %) were averaged with the aim to describe the main patterns. The r2 of predictions obtained with models of higher size were not more accurate than those obtained with models of lower size. After repopulation, the RMSEP of predictions using models with lower sizes (5, 10 and 25% of samples of the library) were lower than RMSEP obtained with higher sizes (75 and 100%), indicating that small models can easily integrate the variability of the soils from the target site. The results suggest that calibrations of small size could be repopulated and "converted" in local calibrations. According to this, we can focus most of the efforts in the obtainment of highly accurate analytical values in a reduced set of samples (including some samples from the target sites). The patterns observed here are in opposition with the idea of global models. These results could encourage the expansion of this technique, because very large data based seems not to be needed. Future studies with very different samples will help to confirm the robustness of the patterns observed. Authors acknowledge to "Bancaja-UMH" for the financial support of the project "NIRPROS".

Quantitative analysis of essential oils in perfume using multivariate curve resolution combined with comprehensive two-dimensional gas chromatography.

PubMed

de Godoy, Luiz Antonio Fonseca; Hantao, Leandro Wang; Pedroso, Marcio Pozzobon; Poppi, Ronei Jesus; Augusto, Fabio

2011-08-05

The use of multivariate curve resolution (MCR) to build multivariate quantitative models using data obtained from comprehensive two-dimensional gas chromatography with flame ionization detection (GC×GC-FID) is presented and evaluated. The MCR algorithm presents some important features, such as second order advantage and the recovery of the instrumental response for each pure component after optimization by an alternating least squares (ALS) procedure. A model to quantify the essential oil of rosemary was built using a calibration set containing only known concentrations of the essential oil and cereal alcohol as solvent. A calibration curve correlating the concentration of the essential oil of rosemary and the instrumental response obtained from the MCR-ALS algorithm was obtained, and this calibration model was applied to predict the concentration of the oil in complex samples (mixtures of the essential oil, pineapple essence and commercial perfume). The values of the root mean square error of prediction (RMSEP) and of the root mean square error of the percentage deviation (RMSPD) obtained were 0.4% (v/v) and 7.2%, respectively. Additionally, a second model was built and used to evaluate the accuracy of the method. A model to quantify the essential oil of lemon grass was built and its concentration was predicted in the validation set and real perfume samples. The RMSEP and RMSPD obtained were 0.5% (v/v) and 6.9%, respectively, and the concentration of the essential oil of lemon grass in perfume agreed to the value informed by the manufacturer. The result indicates that the MCR algorithm is adequate to resolve the target chromatogram from the complex sample and to build multivariate models of GC×GC-FID data. Copyright © 2011 Elsevier B.V. All rights reserved.

Growth parameters of Penicillium expansum calculated from mixed inocula as an alternative to account for intraspecies variability.

PubMed

Garcia, Daiana; Ramos, Antonio J; Sanchis, Vicente; Marín, Sonia

2014-09-01

The aim of this work was to compare the radial growth rate (μ) and the lag time (λ) for growth of 25 isolates of Penicillium expansum at 1 and 20 ºC with those of the mixed inoculum of the 25 isolates. Moreover, the evolution of probability of growth through time was also compared for the single strains and mixed inoculum. Working with a mixed inoculum would require less work, time and consumables than if a range of single strains has to be used in order to represent a given species. Suitable predictive models developed for a given species should represent as much as possible the behavior of all strains belonging to this species. The results suggested, on one hand, that the predictions based on growth parameters calculated on the basis of mixed inocula may not accurately predict the behavior of all possible strains but may represent a percentage of them, and the median/mean values of μ and λ obtained by the 25 strains may be substituted by the value obtained with the mixed inoculum. Moreover, the predictions may be biased, in particular, the predictions of λ which may be underestimated (fail-safe). Moreover, the prediction of time for a given probability of growth through a mixed inoculum may not be accurate for all single inocula, but it may represent 92% and 60% of them at 20 and 1 ºC, respectively, and also their overall mean and median values. In conclusion, mixed inoculum could be a good alternative to estimate the mean or median values of high number of isolates, but not to account for those strains with marginal behavior. In particular, estimation of radial growth rate, and time for 0.10 and 0.50 probability of growth using a cocktail inoculum accounted for the estimates of most single isolates tested. For the particular case of probability models, this is an interesting result as for practical applications in the food industry the estimation of t10 or lower probability may be required. Copyright © 2014 Elsevier B.V. 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.

Development and validation of an electronic phenotyping algorithm for chronic kidney disease

PubMed Central

Nadkarni, Girish N; Gottesman, Omri; Linneman, James G; Chase, Herbert; Berg, Richard L; Farouk, Samira; Nadukuru, Rajiv; Lotay, Vaneet; Ellis, Steve; Hripcsak, George; Peissig, Peggy; Weng, Chunhua; Bottinger, Erwin P

2014-01-01

Twenty-six million Americans are estimated to have chronic kidney disease (CKD) with increased risk for cardiovascular disease and end stage renal disease. CKD is frequently undiagnosed and patients are unaware, hampering intervention. A tool for accurate and timely identification of CKD from electronic medical records (EMR) could improve healthcare quality and identify patients for research. As members of eMERGE (electronic medical records and genomics) Network, we developed an automated phenotyping algorithm that can be deployed to identify rapidly diabetic and/or hypertensive CKD cases and controls in health systems with EMRs It uses diagnostic codes, laboratory results, medication and blood pressure records, and textual information culled from notes. Validation statistics demonstrated positive predictive values of 96% and negative predictive values of 93.3. Similar results were obtained on implementation by two independent eMERGE member institutions. The algorithm dramatically outperformed identification by ICD-9-CM codes with 63% positive and 54% negative predictive values, respectively. PMID:25954398

Thermomechanical Modeling of Sintered Silver - A Fracture Mechanics-based Approach: Extended Abstract: Preprint

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

Paret, Paul P; DeVoto, Douglas J; Narumanchi, Sreekant V

Sintered silver has proven to be a promising candidate for use as a die-attach and substrate-attach material in automotive power electronics components. It holds promise of greater reliability than lead-based and lead-free solders, especially at higher temperatures (less than 200 degrees Celcius). Accurate predictive lifetime models of sintered silver need to be developed and its failure mechanisms thoroughly characterized before it can be deployed as a die-attach or substrate-attach material in wide-bandgap device-based packages. We present a finite element method (FEM) modeling methodology that can offer greater accuracy in predicting the failure of sintered silver under accelerated thermal cycling. Amore » fracture mechanics-based approach is adopted in the FEM model, and J-integral/thermal cycle values are computed. In this paper, we outline the procedures for obtaining the J-integral/thermal cycle values in a computational model and report on the possible advantage of using these values as modeling parameters in a predictive lifetime model.« less

Analysis of loss of time value during road maintenance project

NASA Astrophysics Data System (ADS)

Sudarsana, Dewa Ketut; Sanjaya, Putu Ari

2017-06-01

Lane closure is frequently performed in the execution of the road maintenance project. It has a negative impact on road users such as the loss of vehicle operating costs and the loss of time value. Nevertheless, analysis on loss of time value in Indonesia has not been carried out. The parameter of time value for the road users was the minimum wage city/region approach. Vehicle speed of pre-construction was obtained by observation, while the speed during the road maintenance project was predicted by the speed of the pre-construction by multiplying it with the speed adjustment factor. In the case of execution of the National road maintenance project in the two-lane two-way urban and interurban road types in the fiscal year of 2015 in Bali province, the loss of time value was at the average of IDR 12,789,000/day/link road. The relationship of traffic volume and loss of time value of the road users was obtained by a logarithm model.

Can adaptive threshold-based metabolic tumor volume (MTV) and lean body mass corrected standard uptake value (SUL) predict prognosis in head and neck cancer patients treated with definitive radiotherapy/chemoradiotherapy?

PubMed

Akagunduz, Ozlem Ozkaya; Savas, Recep; Yalman, Deniz; Kocacelebi, Kenan; Esassolak, Mustafa

2015-11-01

To evaluate the predictive value of adaptive threshold-based metabolic tumor volume (MTV), maximum standardized uptake value (SUVmax) and maximum lean body mass corrected SUV (SULmax) measured on pretreatment positron emission tomography and computed tomography (PET/CT) imaging in head and neck cancer patients treated with definitive radiotherapy/chemoradiotherapy. Pretreatment PET/CT of the 62 patients with locally advanced head and neck cancer who were treated consecutively between May 2010 and February 2013 were reviewed retrospectively. The maximum FDG uptake of the primary tumor was defined according to SUVmax and SULmax. Multiple threshold levels between 60% and 10% of the SUVmax and SULmax were tested with intervals of 5% to 10% in order to define the most suitable threshold value for the metabolic activity of each patient's tumor (adaptive threshold). MTV was calculated according to this value. We evaluated the relationship of mean values of MTV, SUVmax and SULmax with treatment response, local recurrence, distant metastasis and disease-related death. Receiver-operating characteristic (ROC) curve analysis was done to obtain optimal predictive cut-off values for MTV and SULmax which were found to have a predictive value. Local recurrence-free (LRFS), disease-free (DFS) and overall survival (OS) were examined according to these cut-offs. Forty six patients had complete response, 15 had partial response, and 1 had stable disease 6 weeks after the completion of treatment. Median follow-up of the entire cohort was 18 months. Of 46 complete responders 10 had local recurrence, and of 16 partial or no responders 10 had local progression. Eighteen patients died. Adaptive threshold-based MTV had significant predictive value for treatment response (p=0.011), local recurrence/progression (p=0.050), and disease-related death (p=0.024). SULmax had a predictive value for local recurrence/progression (p=0.030). ROC curves analysis revealed a cut-off value of 14.00 mL for MTV and 10.15 for SULmax. Three-year LRFS and DFS rates were significantly lower in patients with MTV ≥ 14.00 mL (p=0.026, p=0.018 respectively), and SULmax≥10.15 (p=0.017, p=0.022 respectively). SULmax did not have a significant predictive value for OS whereas MTV had (p=0.025). Adaptive threshold-based MTV and SULmax could have a role in predicting local control and survival in head and neck cancer patients. Copyright © 2015 Elsevier Inc. All rights reserved.

Left atrial strain predicts hemodynamic parameters in cardiovascular patients.

PubMed

Hewing, Bernd; Theres, Lena; Spethmann, Sebastian; Stangl, Karl; Dreger, Henryk; Knebel, Fabian

2017-08-01

We aimed to evaluate the predictive value of left atrial (LA) reservoir, conduit, and contractile function parameters as assessed by speckle tracking echocardiography (STE) for invasively measured hemodynamic parameters in a patient cohort with myocardial and valvular diseases. Sixty-nine patients undergoing invasive hemodynamic assessment were enrolled into the study. Invasive hemodynamic parameters were obtained by left and right heart catheterization. Transthoracic echocardiography assessment of LA reservoir, conduit, and contractile function was performed by STE. Forty-nine patients had sinus rhythm (SR) and 20 patients had permanent atrial fibrillation (AF). AF patients had significantly reduced LA reservoir function compared to SR patients. In patients with SR, LA reservoir, conduit, and contractile function inversely correlated with pulmonary capillary wedge pressure (PCWP), left ventricular end-diastolic pressure, and mean pulmonary artery pressure (PAP), and showed a moderate association with cardiac index. In AF patients, there were no significant correlations between LA reservoir function and invasively obtained hemodynamic parameters. In SR patients, LA contractile function with a cutoff value of 16.0% had the highest diagnostic accuracy (area under the curve, AUC: 0.895) to predict PCWP ≥18 mm Hg compared to the weaker diagnostic accuracy of average E/E' ratio with an AUC of 0.786 at a cutoff value of 14.3. In multivariate analysis, LA contractile function remained significantly associated with PCWP ≥18 mm Hg. In a cohort of patients with a broad spectrum of cardiovascular diseases LA strain shows a valuable prediction of hemodynamic parameters, specifically LV filling pressures, in the presence of SR. © 2017, Wiley Periodicals, Inc.

Retention modeling under organic modifier gradient conditions in ion-pair reversed-phase chromatography. Application to the separation of a set of underivatized amino acids.

PubMed

Pappa-Louisi, A; Agrafiotou, P; Papachristos, K

2010-07-01

The combined effect of the ion-pairing reagent concentration, C(ipr), and organic modifier content, phi, on the retention under phi-gradient conditions at different constant C(ipr) was treated in this study by using two approaches. In the first approach, the prediction of the retention time of a sample solute is based on a direct fitting procedure of a proper retention model to 3-D phi-gradient retention data obtained under the same phi-linear variation but with different slope and time duration of the initial isocratic part and in the presence of various constant C(ipr) values in the eluent. The second approach is based on a retention model describing the combined effect of C(ipr) and phi on the retention of solutes in isocratic mode and consequently analyzes isocratic data obtained in mobile phases containing different C(ipr) values. The effectiveness of the above approaches was tested in the retention prediction of a mixture of 16 underivatized amino acids using mobile phases containing acetonitrile as organic modifier and sodium dodecyl sulfate as ion-pairing reagent. From these approaches, only the first one gives satisfactory predictions and can be successfully used in optimization of ion-pair chromatographic separations under gradient conditions. The failure of the second approach to predict the retention of solutes in the gradient elution mode in the presence of different C(ipr) values was attributed to slow changes in the distribution equilibrium of ion-pairing reagents caused by phi-variation.

Optimization of torrefaction conditions of coffee industry residues using desirability function approach.

PubMed

Buratti, C; Barbanera, M; Lascaro, E; Cotana, F

2018-03-01

The aim of the present study is to analyze the influence of independent process variables such as temperature, residence time, and heating rate on the torrefaction process of coffee chaff (CC) and spent coffee grounds (SCGs). Response surface methodology and a three-factor and three-level Box-Behnken design were used in order to evaluate the effects of the process variables on the weight loss (W L ) and the Higher Heating Value (HHV) of the torrefied materials. Results showed that the effects of the three factors on both responses were sequenced as follows: temperature>residence time>heating rate. Data obtained from the experiments were analyzed by analysis of variance (ANOVA) and fitted to second-order polynomial models by using multiple regression analysis. Predictive models were determined, able to obtain satisfactory fittings of the experimental data, with coefficient of determination (R 2 ) values higher than 0.95. An optimization study using Derringer's desired function methodology was also carried out and the optimal torrefaction conditions were found: temperature 271.7°C, residence time 20min, heating rate 5°C/min for CC and 256.0°C, 20min, 25°C/min for SCGs. The experimental values closely agree with the corresponding predicted values. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison between fine needle aspiration cytology (FNAC) and core needle biopsy (CNB) in the diagnosis of breast lesions.

PubMed

Moschetta, M; Telegrafo, M; Carluccio, D A; Jablonska, J P; Rella, L; Serio, Gabriella; Carrozzo, M; Stabile Ianora, A A; Angelelli, G

2014-01-01

To compare the diagnostic accuracy of fine-needle aspiration cytology (FNAC) and core needle biopsy (CNB) in patients with USdetected breast lesions. Between September 2011 and May 2013, 3469 consecutive breast US examinations were performed. 400 breast nodules were detected in 398 patients. 210 FNACs and 190 CNBs were performed. 183 out of 400 (46%) lesions were surgically removed within 30 days form diagnosis; in the remaining cases, a six month follow up US examination was performed. Sensitivity, specificity, diagnostic accuracy, positive predictive (PPV) and negative predictive (NPV) values were calculated for FNAC and CNB. 174 out of 400 (43%) malignant lesions were found while the remaining 226 resulted to be benign lesions. 166 out of 210 (79%) FNACs and 154 out of 190 (81%) CNBs provided diagnostic specimens. Sensitivity, specificity, diagnostic accuracy, PPV and NPV of 97%, 94%, 95%, 91% and 98% were found for FNAC, and values of 92%, 82%, 89%, 92% and 82% were obtained for CNB. Sensitivity, specificity, diagnostic accuracy, PPV and NPV of 97%, 96%, 96%, 97% and 96% were found for FNAC, and values of 97%, 96%, 96%, 97% and 96% were obtained for CNB. FNAC and CNB provide similar values of diagnostic accuracy.

Comparing Utility of Anthropometric Indices Based on Gender Differences in Predicting Dyslipidaemia in Healthy Adults.

PubMed

Pawaskar, Priyanka N; Shirali, Arun; Prabhu, M Venkatraya; Pai, Sheila R; Kumar, Nayanatara Arun; Pawaskar, Niwas G

2015-08-01

Anthropometry is a simple reliable method for quantifying body proportions by measuring body length, weight and circumferences. Our intention in this study was to compare sensitivities and positive predictive values of waist circumference (WC), waist-hip ratio (WHR), waist-height ratio (WHtR) and body mass index (BMI) in identifying healthy subjects, males and females separately for identifying obesity associated dyslipidemia. We analysed randomly selected 100 healthy subjects (males:58%, females:42%) between 25 and 60 years of age attending tertiary health care center in South India, after obtaining informed consent and Institutional Ethical Clearance. WC, WHR, WHtR and BMI of all the enrolled subjects were measured and estimated. Their fasting serum lipid profile was assessed. Subjects were divided based on their gender and each group was then categorized as obese and non-obese using anthropometric parameters and their individual serum lipid profile values depending on the cut off standards as per WHO and ATP III guidelines and compared. Data obtained was statistically analysed. Mean values of WC, WHR, WHtR and BMI were highly significant (p<0.000) in obese in both males (97.43 ± 6.21cm, 0.96 ± 0.04, 0.61 ± 0.05, 27.72 ± 2.45kg/m(2)) and females (91.82 ± 5.18cm, 0.92 ± 0.06, 0.60 ± 0.04, 27.70 ± 3.44kg/m(2)) when considered separately compared to non-obese males (82.27 ± 5.33cm, 0.83 ± 0.033, 0.51 ± 0.03, 22.80 ± 2.11kg/m(2)) and females (71.68 ± 7.33cm, 0.78 ± 0.03, 0.48 ± 0.03, 21.82 ± 1.98kg/m(2) respectively). WC was more sensitive for predicting the altered lipid profile (85%) in females and WHR (65%) in males. WHR showed higher ability to correctly predict the occurrence of dyslipidemia in the obese males (90% positive predictive value) and WHtR in females (92%). The present study inferred that WC, WHR are more sensitive while WHR and WHtR have a higher positive predictive value than BMI in identifying dyslipidemia in healthy males and females.

Prediction of Breast Cancer Risk by Aberrant Methylation in Mammary Duct Lavage

DTIC Science & Technology

2006-07-01

Assessment of breast epithelial cells obtained by nipple duct lavage (NDL) may have value for breast cancer risk stratification. NDL was performed in 150...contribute to risk stratification. 15. SUBJECT TERMS breast cancer, DNA methylation, Methylation Specific PCR, Nipple Duct Lavage, Risk assessment 16...carcinogenesis. Nipple duct lavage (NDL) is a minimally invasive approach for obtaining breast epithelial cells. Cytological atypia identified in nipple

Liver Stiffness Measured by Two-Dimensional Shear-Wave Elastography: Prognostic Value after Radiofrequency Ablation for Hepatocellular Carcinoma.

PubMed

Lee, Dong Ho; Lee, Jeong Min; Yoon, Jung-Hwan; Kim, Yoon Jun; Lee, Jeong-Hoon; Yu, Su Jong; Han, Joon Koo

2018-03-01

To evaluate the prognostic value of liver stiffness (LS) measured using two-dimensional (2D) shear-wave elastography (SWE) in patients with hepatocellular carcinoma (HCC) treated by radiofrequency ablation (RFA). The Institutional Review Board approved this retrospective study and informed consent was obtained from all patients. A total of 134 patients with up to 3 HCCs ≤5 cm who had undergone pre-procedural 2D-SWE prior to RFA treatment between January 2012 and December 2013 were enrolled. LS values were measured using real-time 2D-SWE before RFA on the procedural day. After a mean follow-up of 33.8 ± 9.9 months, we analyzed the overall survival after RFA using the Kaplan-Meier method and Cox proportional hazard regression model. The optimal cutoff LS value to predict overall survival was determined using the minimal p value approach. During the follow-up period, 22 patients died, and the estimated 1- and 3-year overall survival rates were 96.4 and 85.8%, respectively. LS measured by 2D-SWE was found to be a significant predictive factor for overall survival after RFA of HCCs, as was the presence of extrahepatic metastases. As for the optimal cutoff LS value for the prediction of overall survival, it was determined to be 13.3 kPa. In our study, 71 patients had LS values ≥13.3 kPa, and the estimated 3-year overall survival was 76.8% compared to 96.3% in 63 patients with LS values <13.3 kPa. This difference was statistically significant (hazard ratio = 4.30 [1.26-14.7]; p = 0.020). LS values measured by 2D-SWE was a significant predictive factor for overall survival after RFA for HCC.

A theoretical relation between the celerity and trace velocity of infrasonic phases.

PubMed

Lonzaga, Joel B

2015-09-01

This paper presents a relationship between the celerity and trace velocity of infrasound signals propagating in a stratified, windy atmosphere. Despite their importance, known celerity values have only been determined empirically. An infrasonic phase (I-phase) diagram is developed which is useful in identifying different I-phases. Such an I-phase diagram allows for the prediction of the range of values of the celerity and trace velocity for each I-phase. The phase diagram can easily be extended to underwater acoustic and acoustic-gravity waves. An I-phase diagram is compared with data obtained from a ground-truth event where qualitative agreement is obtained.

Simple relationship between the virial-route hypernetted-chain and the compressibility-route Percus-Yevick values of the fourth virial coefficient.

PubMed

Santos, Andrés; Manzano, Gema

2010-04-14

As is well known, approximate integral equations for liquids, such as the hypernetted chain (HNC) and Percus-Yevick (PY) theories, are in general thermodynamically inconsistent in the sense that the macroscopic properties obtained from the spatial correlation functions depend on the route followed. In particular, the values of the fourth virial coefficient B(4) predicted by the HNC and PY approximations via the virial route differ from those obtained via the compressibility route. Despite this, it is shown in this paper that the value of B(4) obtained from the virial route in the HNC theory is exactly three halves the value obtained from the compressibility route in the PY theory, irrespective of the interaction potential (whether isotropic or not), the number of components, and the dimensionality of the system. This simple relationship is confirmed in one-component systems by analytical results for the one-dimensional penetrable-square-well model and the three-dimensional penetrable-sphere model, as well as by numerical results for the one-dimensional Lennard-Jones model, the one-dimensional Gaussian core model, and the three-dimensional square-well model.

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.

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.

TiC growth in C fiber/Ti alloy composites during liquid infiltration

NASA Technical Reports Server (NTRS)

Warrier, S. G.; Lin, R. Y.

1993-01-01

A cylindrical model is developed for predicting the reaction zone thickness of carbon fiber-reinforced Ti-matrix composites, and good agreement is obtained between its predicted values and experimental results. The reaction-rate constant for TiC formation is estimated to be 1.5 x 10 exp -9 sq cm/sec. The model is extended to evaluate the relationship between C-coating thicknesses on SiC fibers and processing times.

The sensitivity and negative predictive value of a pediatric cervical spine clearance algorithm that minimizes computerized tomography.

PubMed

Arbuthnot, Mary; Mooney, David P

2017-01-01

It is crucial to identify cervical spine injuries while minimizing ionizing radiation. This study analyzes the sensitivity and negative predictive value of a pediatric cervical spine clearance algorithm. We performed a retrospective review of all children <21years old who were admitted following blunt trauma and underwent cervical spine clearance utilizing our institution's cervical spine clearance algorithm over a 10-year period. Age, gender, International Classification of Diseases 9th Edition diagnosis codes, presence or absence of cervical collar on arrival, Injury Severity Score, and type of cervical spine imaging obtained were extracted from the trauma registry and electronic medical record. Descriptive statistics were used and the sensitivity and negative predictive value of the algorithm were calculated. Approximately 125,000 children were evaluated in the Emergency Department and 11,331 were admitted. Of the admitted children, 1023 patients arrived in a cervical collar without advanced cervical spine imaging and were evaluated using the cervical spine clearance algorithm. Algorithm sensitivity was 94.4% and the negative predictive value was 99.9%. There was one missed injury, a spinous process tip fracture in a teenager maintained in a collar. Our algorithm was associated with a low missed injury rate and low CT utilization rate, even in children <3years old. IV. Published by Elsevier Inc.

How Many Oral and Maxillofacial Surgeons Does It Take to Perform Virtual Orthognathic Surgical Planning?

PubMed

Borba, Alexandre Meireles; Haupt, Dustin; de Almeida Romualdo, Leiliane Teresinha; da Silva, André Luis Fernandes; da Graça Naclério-Homem, Maria; Miloro, Michael

2016-09-01

Virtual surgical planning (VSP) has become routine practice in orthognathic treatment planning; however, most surgeons do not perform the planning without technical assistance, nor do they routinely evaluate the accuracy of the postoperative outcomes. The purpose of the present study was to propose a reproducible method that would allow surgeons to have an improved understanding of VSP orthognathic planning and to compare the planned surgical movements with the results obtained. A retrospective cohort of bimaxillary orthognathic surgery cases was used to evaluate the variability between the predicted and obtained movements using craniofacial landmarks and McNamara 3-dimensional cephalometric analysis from computed tomography scans. The demographic data (age, gender, and skeletal deformity type) were gathered from the medical records. The data analysis included the level of variability from the predicted to obtained surgical movements as assessed by the mean and standard deviation. For the overall sample, statistical analysis was performed using the 1-sample t test. The statistical analysis between the Class II and III patient groups used an unpaired t test. The study sample consisted of 50 patients who had undergone bimaxillary orthognathic surgery. The overall evaluation of the mean values revealed a discrepancy between the predicted and obtained values of less than 2.0 ± 2.0 mm for all maxillary landmarks, although some mandibular landmarks were greater than this value. An evaluation of the influence of gender and deformity type on the accuracy of surgical movements did not demonstrate statistical significance for most landmarks (P > .05). The method provides a reproducible tool for surgeons who use orthognathic VSP to perform routine evaluation of the postoperative outcomes, permitting the identification of specific variables that could assist in improving the accuracy of surgical planning and execution. Copyright © 2016 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

Comparison of the diagnostic performance of bacterial culture of nasopharyngeal swab and bronchoalveolar lavage fluid samples obtained from calves with bovine respiratory disease.

PubMed

Capik, Sarah F; White, Brad J; Lubbers, Brian V; Apley, Michael D; DeDonder, Keith D; Larson, Robert L; Harhay, Greg P; Chitko-McKown, Carol G; Harhay, Dayna M; Kalbfleisch, Ted S; Schuller, Gennie; Clawson, Michael L

2017-03-01

OBJECTIVE To compare predictive values, extent of agreement, and gamithromycin susceptibility between bacterial culture results of nasopharyngeal swab (NPS) and bronchoalveolar lavage fluid (BALF) samples obtained from calves with bovine respiratory disease (BRD). ANIMALS 28 beef calves with clinical BRD. PROCEDURES Pooled bilateral NPS samples and BALF samples were obtained for bacterial culture from calves immediately before and at various times during the 5 days after gamithromycin (6 mg/kg, SC, once) administration. For each culture-positive sample, up to 12 Mannheimia haemolytica, 6 Pasteurella multocida, and 6 Histophilus somni colonies underwent gamithromycin susceptibility testing. Whole-genome sequencing was performed on all M haemolytica isolates. For paired NPS and BALF samples collected 5 days after gamithromycin administration, the positive and negative predictive values for culture results of NPS samples relative to those of BALF samples and the extent of agreement between the sampling methods were determined. RESULTS Positive and negative predictive values of NPS samples were 67% and 100% for M haemolytica, 75% and 100% for P multocida, and 100% and 96% for H somni. Extent of agreement between results for NPS and BALF samples was substantial for M haemolytica (κ, 0.71) and H somni (κ, 0.78) and almost perfect for P multocida (κ, 0.81). Gamithromycin susceptibility varied within the same sample and between paired NPS and BALF samples. CONCLUSIONS AND CLINICAL RELEVANCE Results indicated culture results of NPS and BALF samples from calves with BRD should be interpreted cautiously considering disease prevalence within the population, sample collection relative to antimicrobial administration, and limitations of diagnostic testing methods.

Near infrared spectroscopy (NIRS) for on-line determination of quality parameters in intact olives.

PubMed

Salguero-Chaparro, Lourdes; Baeten, Vincent; Fernández-Pierna, Juan A; Peña-Rodríguez, Francisco

2013-08-15

The acidity, moisture and fat content in intact olive fruits were determined on-line using a NIR diode array instrument, operating on a conveyor belt. Four sets of calibrations models were obtained by means of different combinations from samples collected during 2009-2010 and 2010-2011, using full-cross and external validation. Several preprocessing treatments such as derivatives and scatter correction were investigated by using the root mean square error of cross-validation (RMSECV) and prediction (RMSEP), as control parameters. The results obtained showed RMSECV values of 2.54-3.26 for moisture, 2.35-2.71 for fat content and 2.50-3.26 for acidity parameters, depending on the calibration model developed. Calibrations for moisture, fat content and acidity gave residual predictive deviation (RPD) values of 2.76, 2.37 and 1.60, respectively. Although, it is concluded that the on-line NIRS prediction results were acceptable for the three parameters measured in intact olive samples in movement, the models developed must be improved in order to increase their accuracy before final NIRS implementation at mills. Copyright © 2013 Elsevier Ltd. All rights reserved.

Antigenic fractions from Taenia crassiceps metacestodes obtained by hydrophobicity for the immunodiagnosis of active and inactive forms of neurocysticercosis in human cerebrospinal fluid samples.

PubMed

da Silva, Gabriela B; Nunes, Daniela S; de Sousa, José Eduardo N; Gonçalves-Pires, Maria do R F; Levenhagen, Marcelo A; Costa-Cruz, Julia M

2017-04-01

This study aimed to evaluate the total extract of Taenia crassiceps metacestodes (TC) and its antigenic fractions obtained by Triton X-114 fractionation techniques, such as detergent (DC) and aqueous (AC), in the immunodiagnosis of human neurocysticercosis (NCC). Cerebrospinal fluid samples were divided into two groups: Group 1 (n=40), which was further divided into active (n=20) and inactive (n=20) NCC, and Group 2 (control group), which comprised 39 CSF samples from patients who had another neurological disorder, were suffering from other infectious diseases of the brain or had other parasitic infections. The total extracts and antigenic fractions were tested by enzyme-linked immunosorbent assay (ELISA) to detect human IgG anti-Taenia solium. T. crassiceps fractions (DC and AC) showed the same value of sensitivity (Se), 100%, for active and inactive NCC and a specificity (Sp) of 97.4%. The DS fraction obtained from T. solium showed 100% Se for active NCC, 95% Se for inactive NCC and a 92.3% Sp. The AS fraction obtained from T. solium showed 100% Se for both active and inactive NCC and a 94.9% Sp. There was a positive correlation between the total saline extract of T. crassiceps (TC) and T. solium (TS) and their fractions (DC, AC, DS and AS). Positive predictive value, negative predictive value, diagnostic efficiency and Youden index were calculated. In conclusion, these results demonstrated that detergent and aqueous fractions obtained from T. crassiceps metacestodes are important sources of specific antigens and are efficient for immunodiagnosis of active and inactive NCC. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

The interrelationship between preoperative anemia and N-terminal pro-B-type natriuretic peptide: the effect on predicting postoperative cardiac outcome in vascular surgery patients.

PubMed

Goei, Dustin; Flu, Willem-Jan; Hoeks, Sanne E; Galal, Wael; Dunkelgrun, Martin; Boersma, Eric; Kuijper, Ruud; van Kuijk, Jan-Peter; Winkel, Tamara A; Schouten, Olaf; Bax, Jeroen J; Poldermans, Don

2009-11-01

N-terminal pro-B-type natriuretic peptide (NT-proBNP) predicts adverse cardiac outcome in patients undergoing vascular surgery. However, several conditions might influence this prognostic value, including anemia. In this study, we evaluated whether anemia confounds the prognostic value of NT-proBNP for predicting cardiac events in patients undergoing vascular surgery. A detailed cardiac history, resting echocardiography, and hemoglobin and NT-proBNP levels were obtained in 666 patients before vascular surgery. Anemia was defined as serum hemoglobin <13 g/dL for men and <12 g/dL for women. Troponin T measurements and 12-lead electrocardiograms were performed on postoperative days 1, 3, 7, and 30 and whenever clinically indicated. The primary end point of the study was the composite of 30-day postoperative cardiovascular death, nonfatal myocardial infarction, and troponin T release. Receiver operating characteristic curve analysis was used to assess the optimal cutoff value of NT-proBNP for the prediction of the composite end point. Multivariable regression analysis was used to assess the additional value of NT-proBNP for the prediction of postoperative cardiac events in nonanemic and anemic patients. Anemia was present in 206 patients (31%) before surgery. Hemoglobin level was inversely related with the NT-proBNP levels (beta coefficient = -2.242; P = 0.025). The optimal predictive cutoff value of NT-proBNP for predicting the composite cardiovascular outcome was 350 pg/mL. After adjustment for clinical cardiac risk factors, both anemia (odds ratio [OR] 1.53; 95% confidence interval [CI]: 1.07-2.99) and increased levels of NT-proBNP (OR 4.09; 95% CI: 2.19-7.64) remained independent predictors for postoperative cardiac events. However, increased levels of NT-proBNP were not predictive for the risk of adverse cardiac events in the subgroup of anemic patients (OR 2.16; 95% CI: 0.90-5.21). Both anemia and NT-proBNP are independently associated with an increased risk for postoperative cardiac events in patients undergoing vascular surgery. NT-proBNP has less predictive value in anemic patients.

Predicting umbilical artery pH during labour: Development and validation of a nomogram using fetal heart rate patterns.

PubMed

Ramanah, Rajeev; Omar, Sikiyah; Guillien, Alicia; Pugin, Aurore; Martin, Alain; Riethmuller, Didier; Mottet, Nicolas

2018-06-01

Nomograms are statistical models that combine variables to obtain the most accurate and reliable prediction for a particular risk. Fetal heart rate (FHR) interpretation alone has been found to be poorly predictive for fetal acidosis while other clinical risk factors exist. The aim of this study was to create and validate a nomogram based on FHR patterns and relevant clinical parameters to provide a non-invasive individualized prediction of umbilical artery pH during labour. A retrospective observational study was conducted on 4071 patients in labour presenting singleton pregnancies at >34 gestational weeks and delivering vaginally. Clinical characteristics, FHR patterns and umbilical cord gas of 1913 patients were used to construct a nomogram predicting an umbilical artery (Ua) pH <7.18 (10th centile of the study population) after an univariate and multivariate stepwise logistic regression analysis. External validation was obtained from an independent cohort of 2158 patients. Area under the receiver operating characteristics (ROC) curve, sensitivity, specificity, positive and negative predictive values of the nomogram were determined. Upon multivariate analysis, parity (p < 0.01), induction of labour (p = 0.01), a prior uterine scar (p = 0.02), maternal fever (p = 0.02) and the type of FHR (p < 0.01) were significantly associated with an Ua pH <7.18 (p < 0.05). Apgar score at 1, 5 and 10 min were significantly lower in the group with an Ua pH <7.18 (p < 0.01). The nomogram constructed had a Concordance Index of 0.75 (area under the curve) with a sensitivity of 57%, a specificity of 91%, a negative predictive value of 5% and a positive predictive value of 99%. Calibration found no difference between the predicted probabilities and the observed rate of Ua pH <7.18 (p = 0.63). The validation set had a Concordance Index of 0.72 and calibration with a p < 0.77. We successfully developed and validated a nomogram to predict Ua pH by combining easily available clinical variables and FHR. Discrimination and calibration of the model were statistically good. This mathematical tool can help clinicians in the management of labour by predicting umbilical artery pH based on FHR tracings. Copyright © 2018 Elsevier B.V. All rights reserved.

Possibility of Predicting Serotonin Transporter Occupancy From the In Vitro Inhibition Constant for Serotonin Transporter, the Clinically Relevant Plasma Concentration of Unbound Drugs, and Their Profiles for Substrates of Transporters.

PubMed

Yahata, Masahiro; Chiba, Koji; Watanabe, Takao; Sugiyama, Yuichi

2017-09-01

Accurate prediction of target occupancy facilitates central nervous system drug development. In this review, we discuss the predictability of serotonin transporter (SERT) occupancy in human brain estimated from in vitro K i values for human SERT and plasma concentrations of unbound drug (C u,plasma ), as well as the impact of drug transporters in the blood-brain barrier. First, the geometric means of in vitro K i values were compared with the means of in vivo K i values (K i,u,plasma ) which were calculated as C u,plasma values at 50% occupancy of SERT obtained from previous clinical positron emission tomography/single photon emission computed tomography imaging studies for 6 selective serotonin transporter reuptake inhibitors and 3 serotonin norepinephrine reuptake inhibitors. The in vitro K i values for 7 drugs were comparable to their in vivo K i,u,plasma values within 3-fold difference. SERT occupancy was overestimated for 5 drugs (P-glycoprotein substrates) and underestimated for 2 drugs (presumably uptake transporter substrates, although no evidence exists as yet). In conclusion, prediction of human SERT occupancy from in vitro K i values and C u,plasma was successful for drugs that are not transporter substrates and will become possible in future even for transporter substrates, once the transporter activities will be accurately estimated from in vitro experiments. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Surface protonation at the rutile (110) interface: explicit incorporation of solvation structure within the refined MUSIC model framework.

PubMed

Machesky, Michael L; Predota, Milan; Wesolowski, David J; Vlcek, Lukas; Cummings, Peter T; Rosenqvist, Jörgen; Ridley, Moira K; Kubicki, James D; Bandura, Andrei V; Kumar, Nitin; Sofo, Jorge O

2008-11-04

The detailed solvation structure at the (110) surface of rutile (alpha-TiO2) in contact with bulk liquid water has been obtained primarily from experimentally verified classical molecular dynamics (CMD) simulations of the ab initio-optimized surface in contact with SPC/E water. The results are used to explicitly quantify H-bonding interactions, which are then used within the refined MUSIC model framework to predict surface oxygen protonation constants. Quantum mechanical molecular dynamics (QMD) simulations in the presence of freely dissociable water molecules produced H-bond distributions around deprotonated surface oxygens very similar to those obtained by CMD with nondissociable SPC/E water, thereby confirming that the less computationally intensive CMD simulations provide accurate H-bond information. Utilizing this H-bond information within the refined MUSIC model, along with manually adjusted Ti-O surface bond lengths that are nonetheless within 0.05 A of those obtained from static density functional theory (DFT) calculations and measured in X-ray reflectivity experiments (as well as bulk crystal values), give surface protonation constants that result in a calculated zero net proton charge pH value (pHznpc) at 25 degrees C that agrees quantitatively with the experimentally determined value (5.4+/-0.2) for a specific rutile powder dominated by the (110) crystal face. Moreover, the predicted pHznpc values agree to within 0.1 pH unit with those measured at all temperatures between 10 and 250 degrees C. A slightly smaller manual adjustment of the DFT-derived Ti-O surface bond lengths was sufficient to bring the predicted pHznpcvalue of the rutile (110) surface at 25 degrees C into quantitative agreement with the experimental value (4.8+/-0.3) obtained from a polished and annealed rutile (110) single crystal surface in contact with dilute sodium nitrate solutions using second harmonic generation (SHG) intensity measurements as a function of ionic strength. Additionally, the H-bond interactions between protolyzable surface oxygen groups and water were found to be stronger than those between bulk water molecules at all temperatures investigated in our CMD simulations (25, 150 and 250 degrees C). Comparison with the protonation scheme previously determined for the (110) surface of isostructural cassiterite (alpha-SnO2) reveals that the greater extent of H-bonding on the latter surface, and in particular between water and the terminal hydroxyl group (Sn-OH) results in the predicted protonation constant for that group being lower than for the bridged oxygen (Sn-O-Sn), while the reverse is true for the rutile (110) surface. These results demonstrate the importance of H-bond structure in dictating surface protonation behavior, and that explicit use of this solvation structure within the refined MUSIC model framework results in predicted surface protonation constants that are also consistent with a variety of other experimental and computational data.

USE OF SCORE AND CEREBROSPINAL FLUID LACTATE DOSAGE IN DIFFERENTIAL DIAGNOSIS OF BACTERIAL AND ASEPTIC MENINGITIS

PubMed Central

Pires, Frederico Ribeiro; Franco, Andréia Christine Bonotto Farias; Gilio, Alfredo Elias; Troster, Eduardo Juan

2017-01-01

ABSTRACT Objective: To evaluate Bacterial Meningitis Score (BMS) on its own and in association with Cerebrospinal Fluid (CSF) lactate dosage in order to distinguish bacterial from aseptic meningitis. Methods: Children diagnosed with meningitis at a tertiary hospital between January/2011 and December/2014 were selected. All data were obtained upon admission. BMS was applied and included: CSF Gram staining (2 points); CSF neutrophil count ≥1,000 cells/mm3 (1 point); CSF protein ≥80 mg/dL (1 point); peripheral blood neutrophil count ≥10,000 cells/mm3 (1 point) and seizures upon/before arrival (1 point). Cutoff value for CSF lactate was ≥30 mg/dL. Sensitivity, specificity and negative predictive value of several BMS cutoffs and BMS associated with high CSF lactate were evaluated for prediction of bacterial meningitis. Results: Among 439 eligible patients, 94 did not have all data available to complete the score, and 345 patients were included: 7 in bacterial meningitis group and 338 in aseptic meningitis group. As predictive factors of bacterial meningitis, BMS ≥1 had 100% sensitivity (95%CI 47.3-100), 64.2% specificity (58.8-100) and 100% negative predictive value (97.5-100); BMS ≥2 or BMS ≥1 associated with high CSF lactate also showed 100% sensitivity (47.3-100); but 98.5% specificity (96.6-99.5) and 100% negative predictive value (98.3-100). Conclusions: 2 point BMS in association with CSF lactate dosage had the same sensitivity and negative predictive value, with increased specificity for diagnosis of bacterial meningitis when compared with 1-point BMS. PMID:29185620

[Fire behavior of ground surface fuels in Pinus koraiensis and Quercus mongolica mixed forest under no wind and zero slope condition: a prediction with extended Rothermel model].

PubMed

Zhang, Ji-Li; Liu, Bo-Fei; Chu, Teng-Fei; Di, Xue-Ying; Jin, Sen

2012-06-01

A laboratory burning experiment was conducted to measure the fire spread speed, residual time, reaction intensity, fireline intensity, and flame length of the ground surface fuels collected from a Korean pine (Pinus koraiensis) and Mongolian oak (Quercus mongolica) mixed stand in Maoer Mountains of Northeast China under the conditions of no wind, zero slope, and different moisture content, load, and mixture ratio of the fuels. The results measured were compared with those predicted by the extended Rothermel model to test the performance of the model, especially for the effects of two different weighting methods on the fire behavior modeling of the mixed fuels. With the prediction of the model, the mean absolute errors of the fire spread speed and reaction intensity of the fuels were 0.04 m X min(-1) and 77 kW X m(-2), their mean relative errors were 16% and 22%, while the mean absolute errors of residual time, fireline intensity and flame length were 15.5 s, 17.3 kW X m(-1), and 9.7 cm, and their mean relative errors were 55.5%, 48.7%, and 24%, respectively, indicating that the predicted values of residual time, fireline intensity, and flame length were lower than the observed ones. These errors could be regarded as the lower limits for the application of the extended Rothermel model in predicting the fire behavior of similar fuel types, and provide valuable information for using the model to predict the fire behavior under the similar field conditions. As a whole, the two different weighting methods did not show significant difference in predicting the fire behavior of the mixed fuels by extended Rothermel model. When the proportion of Korean pine fuels was lower, the predicted values of spread speed and reaction intensity obtained by surface area weighting method and those of fireline intensity and flame length obtained by load weighting method were higher; when the proportion of Korean pine needles was higher, the contrary results were obtained.

[Anthropometric model for the prediction of appendicular skeletal muscle mass in Chilean older adults].

PubMed

Lera, Lydia; Albala, Cecilia; Ángel, Bárbara; Sánchez, Hugo; Picrin, Yaisy; Hormazabal, María José; Quiero, Andrea

2014-03-01

To develop a predictive model of appendicular skeletal muscle mass (ASM) based on anthropometric measurements in elderly from Santiago, Chile. 616 community dwelling, non-disabled subjects ≥ 60 years (mean 69.9 ± 5.2 years) living in Santiago, 64.6% female, participating in ALEXANDROS study. Anthropometric measurements, handgrip strength, mobility tests and DEXA were performed. Step by step linear regression models were used to associate ASM from DEXA with anthropometric variables, age and sex. The sample was divided at random into two to obtain prediction equations for both subsamples, which were mutually validated by double cross-validation. The high correlation between the values of observed and predicted MMAE in both sub-samples and the low degree of shrinkage allowed developing the final prediction equation with the total sample. The cross-validity coefficient between prediction models from the subsamples (0.941 and 0.9409) and the shrinkage (0.004 and 0.006) were similar in both equations. The final prediction model obtained from the total sample was: ASM (kg) = 0.107(weight in kg) + 0.251( knee height in cm) + 0.197 (Calf Circumference in cm) +0.047 (dynamometry in kg) - 0.034 (Hip Circumference in cm) + 3.417 (Man) - 0.020 (age years) - 7.646 (R2 = 0.89). The mean ASM obtained by the prediction equation and the DEXA measurement were similar (16.8 ± 4.0 vs 16.9 ± 3.7) and highly concordant according Bland and Altman (95% CI: -2.6 -2.7) and Lin (concordance correlation coefficient = 0.94) methods. We obtained a low cost anthropometric equation to determine the appendicular skeletal muscle mass useful for the screening of sarcopenia in older adults. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Calculations of reliability predictions for the Apollo spacecraft

NASA Technical Reports Server (NTRS)

Amstadter, B. L.

1966-01-01

A new method of reliability prediction for complex systems is defined. Calculation of both upper and lower bounds are involved, and a procedure for combining the two to yield an approximately true prediction value is presented. Both mission success and crew safety predictions can be calculated, and success probabilities can be obtained for individual mission phases or subsystems. Primary consideration is given to evaluating cases involving zero or one failure per subsystem, and the results of these evaluations are then used for analyzing multiple failure cases. Extensive development is provided for the overall mission success and crew safety equations for both the upper and lower bounds.

The electrochemistry of carbon steel in simulated concrete pore water in boom clay repository environments

NASA Astrophysics Data System (ADS)

MacDonald, D. D.; Saleh, A.; Lee, S. K.; Azizi, O.; Rosas-Camacho, O.; Al-Marzooqi, A.; Taylor, M.

2011-04-01

The prediction of corrosion damage of canisters to experimentally inaccessible times is vitally important in assessing various concepts for the disposal of High Level Nuclear Waste. Such prediction can only be made using deterministic models, whose predictions are constrained by the time-invariant natural laws. In this paper, we describe the measurement of experimental electrochemical data that will allow the prediction of damage to the carbon steel overpack of the super container in Belgium's proposed Boom Clay repository by using the Point Defect Model (PDM). PDM parameter values are obtained by optimizing the model on experimental, wide-band electrochemical impedance spectroscopy data.

Studying the properties of a predicted tetragonal silicon by first principles

NASA Astrophysics Data System (ADS)

Xue, Han-Yu; Zhang, Can; Pang, Dong-Dong; Huang, Xue-Qian; Lv, Zhen-Long; Duan, Man-Yi

2018-03-01

Silicon is a very important material in many technological fields. It also has a complicated phase diagram of scientific interest. Here we reported a new allotrope of silicon obtained from crystal structure prediction. We studied its electronic, vibrational, dielectric, elastic and hardness properties by first-principles calculations. The results indicate that it is an indirect narrow-band-gap semiconductor. It is dynamically stable with a doubly degenerate infrared-active mode at its Brillouin zone center. Born effective charges of the constituent element are very small, resulting in a negligible ionic dielectric contribution. Calculated elasticity-related quantities imply that it is mechanically stable but anisotropic. There exist slowly increasing stages in the stress-strain curves of this crystal, which make it difficult to estimate the hardness of the crystal by calculating its ideal strengths. Taking advantage of the hardness model proposed by Šimůnek, we obtained a value of 12.0 GPa as its hardness. This value is lower than that of the cubic diamond-structural Si by about 5.5%.

Subharmonic generation, chaos, and subharmonic resurrection in an acoustically driven fluid-filled cavity.

PubMed

Cantrell, John H; Adler, Laszlo; Yost, William T

2015-02-01

Traveling wave solutions of the nonlinear acoustic wave equation are obtained for the fundamental and second harmonic resonances of a fluid-filled cavity. The solutions lead to the development of a non-autonomous toy model for cavity oscillations. Application of the Melnikov method to the model equation predicts homoclinic bifurcation of the Smale horseshoe type leading to a cascade of period doublings with increasing drive displacement amplitude culminating in chaos. The threshold value of the drive displacement amplitude at tangency is obtained in terms of the acoustic drive frequency and fluid attenuation coefficient. The model prediction of subharmonic generation leading to chaos is validated from acousto-optic diffraction measurements in a water-filled cavity using a 5 MHz acoustic drive frequency and from the measured frequency spectrum in the bifurcation cascade regime. The calculated resonant threshold amplitude of 0.2 nm for tangency is consistent with values estimated for the experimental set-up. Experimental evidence for the appearance of a stable subharmonic beyond chaos is reported.

The effect of constraints on the analytical figures of merit achieved by extended multivariate curve resolution-alternating least-squares.

PubMed

Pellegrino Vidal, Rocío B; Allegrini, Franco; Olivieri, Alejandro C

2018-03-20

Multivariate curve resolution-alternating least-squares (MCR-ALS) is the model of choice when dealing with some non-trilinear arrays, specifically when the data are of chromatographic origin. To drive the iterative procedure to chemically interpretable solutions, the use of constraints becomes essential. In this work, both simulated and experimental data have been analyzed by MCR-ALS, applying chemically reasonable constraints, and investigating the relationship between selectivity, analytical sensitivity (γ) and root mean square error of prediction (RMSEP). As the selectivity in the instrumental modes decreases, the estimated values for γ did not fully represent the predictive model capabilities, judged from the obtained RMSEP values. Since the available sensitivity expressions have been developed by error propagation theory in unconstrained systems, there is a need of developing new expressions or analytical indicators. They should not only consider the specific profiles retrieved by MCR-ALS, but also the constraints under which the latter ones have been obtained. Copyright © 2017 Elsevier B.V. All rights reserved.

Event generator tunes obtained from underlying event and multiparton scattering measurements.

PubMed

Khachatryan, V; Sirunyan, A M; Tumasyan, A; Adam, W; Asilar, E; Bergauer, T; Brandstetter, J; Brondolin, E; Dragicevic, M; Erö, J; Friedl, M; Frühwirth, R; Ghete, V M; Hartl, C; Hörmann, N; Hrubec, J; Jeitler, M; Knünz, V; König, A; Krammer, M; Krätschmer, I; Liko, D; Matsushita, T; Mikulec, I; Rabady, D; Rahbaran, B; Rohringer, H; Schieck, J; Schöfbeck, R; Strauss, J; Treberer-Treberspurg, W; Waltenberger, W; Wulz, C-E; Mossolov, V; Shumeiko, N; Suarez Gonzalez, J; Alderweireldt, S; Cornelis, T; De Wolf, E A; Janssen, X; Knutsson, A; Lauwers, J; Luyckx, S; Van De Klundert, M; Van Haevermaet, H; Van Mechelen, P; Van Remortel, N; Van Spilbeeck, A; Abu Zeid, S; Blekman, F; D'Hondt, J; Daci, N; De Bruyn, I; Deroover, K; Heracleous, N; Keaveney, J; Lowette, S; Moreels, L; Olbrechts, A; Python, Q; Strom, D; Tavernier, S; Van Doninck, W; Van Mulders, P; Van Onsem, G P; Van Parijs, I; Barria, P; Brun, H; Caillol, C; Clerbaux, B; De Lentdecker, G; Fasanella, G; Favart, L; Grebenyuk, A; Karapostoli, G; Lenzi, T; Léonard, A; Maerschalk, T; Marinov, A; Perniè, L; Randle-Conde, A; Seva, T; Vander Velde, C; Yonamine, R; Vanlaer, P; Yonamine, R; Zenoni, F; Zhang, F; Adler, V; Beernaert, K; Benucci, L; Cimmino, A; Crucy, S; Dobur, D; Fagot, A; Garcia, G; Gul, M; Mccartin, J; Ocampo Rios, A A; Poyraz, D; Ryckbosch, D; Salva, S; Sigamani, M; Tytgat, M; Van Driessche, W; Yazgan, E; Zaganidis, N; Basegmez, S; Beluffi, C; Bondu, O; Brochet, S; Bruno, G; Caudron, A; Ceard, L; Da Silveira, G G; Delaere, C; Favart, D; Forthomme, L; Giammanco, A; Hollar, J; Jafari, A; Jez, P; Komm, M; Lemaitre, V; Mertens, A; Musich, M; Nuttens, C; Perrini, L; Pin, A; Piotrzkowski, K; Popov, A; Quertenmont, L; Selvaggi, M; Vidal Marono, M; Beliy, N; Hammad, G H; Júnior, W L Aldá; Alves, F L; Alves, G A; Brito, L; Correa Martins Junior, M; Hamer, M; Hensel, C; Moraes, A; Pol, M E; Rebello Teles, P; Belchior Batista Das Chagas, E; Carvalho, W; Chinellato, J; Custódio, A; Da Costa, E M; De Jesus Damiao, D; De Oliveira Martins, C; Fonseca De Souza, S; Huertas Guativa, L M; Malbouisson, H; Matos Figueiredo, D; Mora Herrera, C; Mundim, L; Nogima, H; Prado Da Silva, W L; Santoro, A; Sznajder, A; Tonelli Manganote, E J; Vilela Pereira, A; Ahuja, S; Bernardes, C A; De Souza Santos, A; Dogra, S; Fernandez Perez Tomei, T R; Gregores, E M; Mercadante, P G; Moon, C S; Novaes, S F; Padula, Sandra S; Romero Abad, D; Ruiz Vargas, J C; Aleksandrov, A; Hadjiiska, R; Iaydjiev, P; Rodozov, M; Stoykova, S; Sultanov, G; Vutova, M; Dimitrov, A; Glushkov, I; Litov, L; Pavlov, B; Petkov, P; Ahmad, M; Bian, J G; Chen, G M; Chen, H S; Chen, M; Cheng, T; Du, R; Jiang, C H; Plestina, R; Romeo, F; Shaheen, S M; Spiezia, A; Tao, J; Wang, C; Wang, Z; Zhang, H; Asawatangtrakuldee, C; Ban, Y; Li, Q; Liu, S; Mao, Y; Qian, S J; Wang, D; Xu, Z; Avila, C; Cabrera, A; Chaparro Sierra, L F; Florez, C; Gomez, J P; Gomez Moreno, B; Sanabria, J C; Godinovic, N; Lelas, D; Puljak, I; Ribeiro Cipriano, P M; Antunovic, Z; Kovac, M; Brigljevic, V; Kadija, K; Luetic, J; Micanovic, S; Sudic, L; Attikis, A; Mavromanolakis, G; Mousa, J; Nicolaou, C; Ptochos, F; Razis, P A; Rykaczewski, H; Bodlak, M; Finger, M; Finger, M; Abdelalim, A A; Awad, A; Mahrous, A; Mohammed, Y; Radi, A; Calpas, B; Kadastik, M; Murumaa, M; Raidal, M; Tiko, A; Veelken, C; Eerola, P; Pekkanen, J; Voutilainen, M; Härkönen, J; Karimäki, V; Kinnunen, R; Lampén, T; Lassila-Perini, K; Lehti, S; Lindén, T; Luukka, P; Mäenpää, T; Peltola, T; Tuominen, E; Tuominiemi, J; Tuovinen, E; Wendland, L; Talvitie, J; Tuuva, T; Besancon, M; Couderc, F; Dejardin, M; Denegri, D; Fabbro, B; Faure, J L; Favaro, C; Ferri, F; Ganjour, S; Givernaud, A; Gras, P; Hamel de Monchenault, G; Jarry, P; Locci, E; Machet, M; Malcles, J; Rander, J; Rosowsky, A; Titov, M; Zghiche, A; Antropov, I; Baffioni, S; Beaudette, F; Busson, P; Cadamuro, L; Chapon, E; Charlot, C; Dahms, T; Davignon, O; Filipovic, N; Granier de Cassagnac, R; Jo, M; Lisniak, S; Mastrolorenzo, L; Miné, P; Naranjo, I N; Nguyen, M; Ochando, C; Ortona, G; Paganini, P; Pigard, P; Regnard, S; Salerno, R; Sauvan, J B; Sirois, Y; Strebler, T; Yilmaz, Y; Zabi, A; Agram, J-L; Andrea, J; Aubin, A; Bloch, D; Brom, J-M; Buttignol, M; Chabert, E C; Chanon, N; Collard, C; Conte, E; Coubez, X; Fontaine, J-C; Gelé, D; Goerlach, U; Goetzmann, C; Le Bihan, A-C; Merlin, J A; Skovpen, K; Van Hove, P; Gadrat, S; Beauceron, S; Bernet, C; Boudoul, G; Bouvier, E; Carrillo Montoya, C A; Chierici, R; Contardo, D; Courbon, B; Depasse, P; El Mamouni, H; Fan, J; Fay, J; Gascon, S; Gouzevitch, M; Ille, B; Lagarde, F; Laktineh, I B; Lethuillier, M; Mirabito, L; Pequegnot, A L; Perries, S; Ruiz Alvarez, J D; Sabes, D; Sgandurra, L; Sordini, V; Vander Donckt, M; Verdier, P; Viret, S; Toriashvili, T; Lomidze, D; Autermann, C; Beranek, S; Edelhoff, M; Feld, L; Heister, A; Kiesel, M K; Klein, K; Lipinski, M; Ostapchuk, A; Preuten, M; Raupach, F; Schael, S; Schulte, J F; Verlage, T; Weber, H; Wittmer, B; Zhukov, V; Ata, M; Brodski, M; Dietz-Laursonn, E; Duchardt, D; Endres, M; Erdmann, M; Erdweg, S; Esch, T; Fischer, R; Güth, A; Hebbeker, T; Heidemann, C; Hoepfner, K; Knutzen, S; Kreuzer, P; Merschmeyer, M; Meyer, A; Millet, P; Olschewski, M; Padeken, K; Papacz, P; Pook, T; Radziej, M; Reithler, H; Rieger, M; Scheuch, F; Sonnenschein, L; Teyssier, D; Thüer, S; Cherepanov, V; Erdogan, Y; Flügge, G; Geenen, H; Geisler, M; Hoehle, F; Kargoll, B; Kress, T; Kuessel, Y; Künsken, A; Lingemann, J; Nehrkorn, A; Nowack, A; Nugent, I M; Pistone, C; Pooth, O; Stahl, A; Aldaya Martin, M; Asin, I; Bartosik, N; Behnke, O; Behrens, U; Bell, A J; Borras, K; Burgmeier, A; Campbell, A; Choudhury, S; Costanza, F; Diez Pardos, C; Dolinska, G; Dooling, S; Dorland, T; Eckerlin, G; Eckstein, D; Eichhorn, T; Flucke, G; Gallo, E; Garcia, J Garay; Geiser, A; Gizhko, A; Gunnellini, P; Hauk, J; Hempel, M; Jung, H; Kalogeropoulos, A; Karacheban, O; Kasemann, M; Katsas, P; Kieseler, J; Kleinwort, C; Korol, I; Lange, W; Leonard, J; Lipka, K; Lobanov, A; Lohmann, W; Mankel, R; Marfin, I; Melzer-Pellmann, I-A; Meyer, A B; Mittag, G; Mnich, J; Mussgiller, A; Naumann-Emme, S; Nayak, A; Ntomari, E; Perrey, H; Pitzl, D; Placakyte, R; Raspereza, A; Roland, B; Sahin, M Ö; Saxena, P; Schoerner-Sadenius, T; Schröder, M; Seitz, C; Spannagel, S; Trippkewitz, K D; Walsh, R; Wissing, C; Blobel, V; Centis Vignali, M; Draeger, A R; Erfle, J; Garutti, E; Goebel, K; Gonzalez, D; Görner, M; Haller, J; Hoffmann, M; Höing, R S; Junkes, A; Klanner, R; Kogler, R; Kovalchuk, N; Lapsien, T; Lenz, T; Marchesini, I; Marconi, D; Meyer, M; Nowatschin, D; Ott, J; Pantaleo, F; Peiffer, T; Perieanu, A; Pietsch, N; Poehlsen, J; Rathjens, D; Sander, C; Scharf, C; Schettler, H; Schleper, P; Schlieckau, E; Schmidt, A; Schwandt, J; Sola, V; Stadie, H; Steinbrück, G; Tholen, H; Troendle, D; Usai, E; Vanelderen, L; Vanhoefer, A; Vormwald, B; Barth, C; Baus, C; Berger, J; Böser, C; Butz, E; Chwalek, T; Colombo, F; De Boer, W; Descroix, A; Dierlamm, A; Fink, S; Frensch, F; Friese, R; Giffels, M; Gilbert, A; Haitz, D; Hartmann, F; Heindl, S M; Husemann, U; Katkov, I; Kornmayer, A; Lobelle Pardo, P; Maier, B; Mildner, H; Mozer, M U; Müller, T; Müller, Th; Plagge, M; Quast, G; Rabbertz, K; Röcker, S; Roscher, F; Sieber, G; Simonis, H J; Stober, F M; Ulrich, R; Wagner-Kuhr, J; Wayand, S; Weber, M; Weiler, T; Williamson, S; Wöhrmann, C; Wolf, R; Anagnostou, G; Daskalakis, G; Geralis, T; Giakoumopoulou, V A; Kyriakis, A; Loukas, D; Psallidas, A; Topsis-Giotis, I; Agapitos, A; Kesisoglou, S; Panagiotou, A; Saoulidou, N; Tziaferi, E; Evangelou, I; Flouris, G; Foudas, C; Kokkas, P; Loukas, N; Manthos, N; Papadopoulos, I; Paradas, E; Strologas, J; Bencze, G; Hajdu, C; Hazi, A; Hidas, P; Horvath, D; Sikler, F; Veszpremi, V; Vesztergombi, G; Zsigmond, A J; Beni, N; Czellar, S; Karancsi, J; Molnar, J; Szillasi, Z; Bartók, M; Makovec, A; Raics, P; Trocsanyi, Z L; Ujvari, B; Mal, P; Mandal, K; Sahoo, D K; Sahoo, N; Swain, S K; Bansal, S; Beri, S B; Bhatnagar, V; Chawla, R; Gupta, R; Bhawandeep, U; Kalsi, A K; Kaur, A; Kaur, M; Kumar, R; Mehta, A; Mittal, M; Singh, J B; Walia, G; Kumar, Ashok; Bhardwaj, A; Choudhary, B C; Garg, R B; Kumar, A; Malhotra, S; Naimuddin, M; Nishu, N; Ranjan, K; Sharma, R; Sharma, V; Bhattacharya, S; Chatterjee, K; Dey, S; Dutta, S; Jain, Sa; Majumdar, N; Modak, A; Mondal, K; Mukherjee, S; Mukhopadhyay, S; Roy, A; Roy, D; Roy Chowdhury, S; Sarkar, S; Sharan, M; Abdulsalam, A; Chudasama, R; Dutta, D; Jha, V; Kumar, V; Mohanty, A K; Pant, L M; Shukla, P; Topkar, A; Aziz, T; Banerjee, S; Bhowmik, S; Chatterjee, R M; Dewanjee, R K; Dugad, S; Ganguly, S; Ghosh, S; Guchait, M; Gurtu, A; Kole, G; Kumar, S; Mahakud, B; Maity, M; Majumder, G; Mazumdar, K; Mitra, S; Mohanty, G B; Parida, B; Sarkar, T; Sur, N; Sutar, B; Wickramage, N; Chauhan, S; Dube, S; Kapoor, A; Kothekar, K; Sharma, S; Bakhshiansohi, H; Behnamian, H; Etesami, S M; Fahim, A; Goldouzian, R; Khakzad, M; Mohammadi Najafabadi, M; Naseri, M; Paktinat Mehdiabadi, S; Rezaei Hosseinabadi, F; Safarzadeh, B; Zeinali, M; Felcini, M; Grunewald, M; Abbrescia, M; Calabria, C; Caputo, C; Colaleo, A; Creanza, D; Cristella, L; De Filippis, N; De Palma, M; Fiore, L; Iaselli, G; Maggi, G; Miniello, G; Maggi, M; My, S; Nuzzo, S; Pompili, A; Pugliese, G; Radogna, R; Ranieri, A; Selvaggi, G; Silvestris, L; Venditti, R; Verwilligen, P; Abbiendi, G; Battilana, C; Benvenuti, A C; Bonacorsi, D; Braibant-Giacomelli, S; Brigliadori, L; Campanini, R; Capiluppi, P; Castro, A; Cavallo, F R; Chhibra, S S; Codispoti, G; Cuffiani, M; Dallavalle, G M; Fabbri, F; Fanfani, A; Fasanella, D; Giacomelli, P; Grandi, C; Guiducci, L; Marcellini, S; Masetti, G; Montanari, A; Navarria, F L; Perrotta, A; Rossi, A M; Primavera, F; Rovelli, T; Siroli, G P; Tosi, N; Travaglini, R; Cappello, G; Chiorboli, M; Costa, S; Mattia, A Di; Giordano, F; Potenza, R; Tricomi, A; Tuve, C; Barbagli, G; Ciulli, V; Civinini, C; D'Alessandro, R; Focardi, E; Gonzi, S; Gori, V; Lenzi, P; Meschini, M; Paoletti, S; Sguazzoni, G; Tropiano, A; Viliani, L; Benussi, L; Bianco, S; Fabbri, F; Piccolo, D; Primavera, F; Calvelli, V; Ferro, F; Lo Vetere, M; Monge, M R; Robutti, E; Tosi, S; Brianza, L; Dinardo, M E; Fiorendi, S; Gennai, S; Gerosa, R; Ghezzi, A; Govoni, P; Malvezzi, S; Manzoni, R A; Marzocchi, B; Menasce, D; Moroni, L; Paganoni, M; Pedrini, D; Ragazzi, S; Redaelli, N; Tabarelli de Fatis, T; Buontempo, S; Cavallo, N; Di Guida, S; Esposito, M; Fabozzi, F; Iorio, A O M; Lanza, G; Lista, L; Meola, S; Merola, M; Paolucci, P; Sciacca, C; Thyssen, F; Azzi, P; Bacchetta, N; Benato, L; Bisello, D; Boletti, A; Branca, A; Carlin, R; Checchia, P; Dall'Osso, M; Dorigo, T; Dosselli, U; Fantinel, S; Fanzago, F; Gasparini, F; Gasparini, U; Gozzelino, A; Kanishchev, K; Lacaprara, S; Margoni, M; Meneguzzo, A T; Pazzini, J; Pozzobon, N; Ronchese, P; Simonetto, F; Torassa, E; Tosi, M; Zanetti, M; Zotto, P; Zucchetta, A; Braghieri, A; Magnani, A; Montagna, P; Ratti, S P; Re, V; Riccardi, C; Salvini, P; Vai, I; Vitulo, P; Alunni Solestizi, L; Bilei, G M; Ciangottini, D; Fanò, L; Lariccia, P; Mantovani, G; Menichelli, M; Saha, A; Santocchia, A; Androsov, K; Azzurri, P; Bagliesi, G; Bernardini, J; Boccali, T; Castaldi, R; Ciocci, M A; Dell'Orso, R; Donato, S; Fedi, G; Fiori, F; Foà, L; Giassi, A; Grippo, M T; Ligabue, F; Lomtadze, T; Martini, L; Messineo, A; Palla, F; Rizzi, A; Savoy-Navarro, A; Serban, A T; Spagnolo, P; Tenchini, R; Tonelli, G; Venturi, A; Verdini, P G; Barone, L; Cavallari, F; D'imperio, G; Del Re, D; Diemoz, M; Gelli, S; Jorda, C; Longo, E; Margaroli, F; Meridiani, P; Organtini, G; Paramatti, R; Preiato, F; Rahatlou, S; Rovelli, C; Santanastasio, F; Traczyk, P; Amapane, N; Arcidiacono, R; Argiro, S; Arneodo, M; Bellan, R; Biino, C; Cartiglia, N; Costa, M; Covarelli, R; Degano, A; Demaria, N; Finco, L; Kiani, B; Mariotti, C; Maselli, S; Migliore, E; Monaco, V; Monteil, E; Obertino, M M; Pacher, L; Pastrone, N; Pelliccioni, M; Pinna Angioni, G L; Ravera, F; Potenza, A; Romero, A; Ruspa, M; Sacchi, R; Solano, A; Staiano, A; Belforte, S; Candelise, V; Casarsa, M; Cossutti, F; Della Ricca, G; Gobbo, B; La Licata, C; Marone, M; Schizzi, A; Zanetti, A; Kropivnitskaya, T A; Nam, S K; Kim, D H; Kim, G N; Kim, M S; Kim, M S; Kong, D J; Lee, S; Oh, Y D; Sakharov, A; Son, D C; Brochero Cifuentes, J A; Kim, H; Kim, T J; Song, S; Choi, S; Go, Y; Gyun, D; Hong, B; Kim, H; Kim, Y; Lee, B; Lee, K; Lee, K S; Lee, S; Lee, S; Park, S K; Roh, Y; Yoo, H D; Choi, M; Kim, H; Kim, J H; Lee, J S H; Park, I C; Ryu, G; Ryu, M S; Choi, Y; Goh, J; Kim, D; Kwon, E; Lee, J; Yu, I; Dudenas, V; Juodagalvis, A; Vaitkus, J; Ahmed, I; Ibrahim, Z A; Komaragiri, J R; Md Ali, M A B; Mohamad Idris, F; Wan Abdullah, W A T; Yusli, M N; Wan Abdullah, W A T; Casimiro Linares, E; Castilla-Valdez, H; De La Cruz-Burelo, E; Heredia-De La Cruz, I; Hernandez-Almada, A; Lopez-Fernandez, R; Sanchez-Hernandez, A; Carrillo Moreno, S; Vazquez Valencia, F; Pedraza, I; Salazar Ibarguen, H A; Morelos Pineda, A; Krofcheck, D; Butler, P H; Ahmad, A; Ahmad, M; Hassan, Q; Hoorani, H R; Khan, W A; Khurshid, T; Shoaib, M; Bialkowska, H; Bluj, M; Boimska, B; Frueboes, T; Górski, M; Kazana, M; Nawrocki, K; Romanowska-Rybinska, K; Szleper, M; Zalewski, P; Brona, G; Bunkowski, K; Byszuk, A; Doroba, K; Kalinowski, A; Konecki, M; Krolikowski, J; Misiura, M; Olszewski, M; Walczak, M; Bargassa, P; Da Cruz E Silva, C Beir Ao; Di Francesco, A; Faccioli, P; Parracho, P G Ferreira; Gallinaro, M; Leonardo, N; Lloret Iglesias, L; Nguyen, F; Rodrigues Antunes, J; Seixas, J; Toldaiev, O; Vadruccio, D; Varela, J; Vischia, P; Afanasiev, S; Bunin, P; Gavrilenko, M; Golutvin, I; Gorbunov, I; Kamenev, A; Karjavin, V; Konoplyanikov, V; Lanev, A; Malakhov, A; Matveev, V; Moisenz, P; Palichik, V; Perelygin, V; Savina, M; Shmatov, S; Shulha, S; Smirnov, V; Zarubin, A; Golovtsov, V; Ivanov, Y; Kim, V; Kuznetsova, E; Levchenko, P; Murzin, V; Oreshkin, V; Smirnov, I; Sulimov, V; Uvarov, L; Vavilov, S; Vorobyev, A; Andreev, Yu; Dermenev, A; Gninenko, S; Golubev, N; Karneyeu, A; Kirsanov, M; Krasnikov, N; Pashenkov, A; Tlisov, D; Toropin, A; Epshteyn, V; Gavrilov, V; Lychkovskaya, N; Popov, V; Pozdnyakov, L; Safronov, G; Spiridonov, A; Vlasov, E; Zhokin, A; Bylinkin, A; Andreev, V; Azarkin, M; Dremin, I; Kirakosyan, M; Leonidov, A; Mesyats, G; Rusakov, S V; Baskakov, A; Belyaev, A; Boos, E; Dubinin, M; Dudko, L; Ershov, A; Gribushin, A; Klyukhin, V; Kodolova, O; Lokhtin, I; Myagkov, I; Obraztsov, S; Petrushanko, S; Savrin, V; Snigirev, A; Azhgirey, I; Bayshev, I; Bitioukov, S; Kachanov, V; Kalinin, A; Konstantinov, D; Krychkine, V; Petrov, V; Ryutin, R; Sobol, A; Tourtchanovitch, L; Troshin, S; Tyurin, N; Uzunian, A; Volkov, A; Adzic, P; Cirkovic, P; Milosevic, J; Rekovic, V; Alcaraz Maestre, J; Battilana, C; Calvo, E; Cerrada, M; Chamizo Llatas, M; Colino, N; De La Cruz, B; Delgado Peris, A; Escalante Del Valle, A; Fernandez Bedoya, C; Ramos, J P Fernández; Flix, J; Fouz, M C; Garcia-Abia, P; Gonzalez Lopez, O; Goy Lopez, S; Hernandez, J M; Josa, M I; Navarro De Martino, E; Yzquierdo, A Pérez-Calero; Puerta Pelayo, J; Quintario Olmeda, A; Redondo, I; Romero, L; Santaolalla, J; Soares, M S; Albajar, C; de Trocóniz, J F; Missiroli, M; Moran, D; Cuevas, J; Fernandez Menendez, J; Folgueras, S; Gonzalez Caballero, I; Palencia Cortezon, E; Vizan Garcia, J M; Cabrillo, I J; Calderon, A; Castiñeiras De Saa, J R; De Castro Manzano, P; Fernandez, M; Garcia-Ferrero, J; Gomez, G; Lopez Virto, A; Marco, J; Marco, R; Martinez Rivero, C; Matorras, F; Piedra Gomez, J; Rodrigo, T; Rodríguez-Marrero, A Y; Ruiz-Jimeno, A; Scodellaro, L; Trevisani, N; Vila, I; Vilar Cortabitarte, R; Abbaneo, D; Auffray, E; Auzinger, G; Bachtis, M; Baillon, P; Ball, A H; Barney, D; Benaglia, A; Bendavid, J; Benhabib, L; Benitez, J F; Berruti, G M; Bloch, P; Bocci, A; Bonato, A; Botta, C; Breuker, H; Camporesi, T; Castello, R; Cerminara, G; D'Alfonso, M; d'Enterria, D; Dabrowski, A; Daponte, V; David, A; De Gruttola, M; De Guio, F; De Roeck, A; De Visscher, S; Di Marco, E; Dobson, M; Dordevic, M; Dorney, B; du Pree, T; Duggan, D; Dünser, M; Dupont, N; Elliott-Peisert, A; Franzoni, G; Fulcher, J; Funk, W; Gigi, D; Gill, K; Giordano, D; Girone, M; Glege, F; Guida, R; Gundacker, S; Guthoff, M; Hammer, J; Harris, P; Hegeman, J; Innocente, V; Janot, P; Kirschenmann, H; Kortelainen, M J; Kousouris, K; Krajczar, K; Lecoq, P; Lourenço, C; Lucchini, M T; Magini, N; Malgeri, L; Mannelli, M; Martelli, A; Masetti, L; Meijers, F; Mersi, S; Meschi, E; Moortgat, F; Morovic, S; Mulders, M; Nemallapudi, M V; Neugebauer, H; Orfanelli, S; Orsini, L; Pape, L; Perez, E; Peruzzi, M; Petrilli, A; Petrucciani, G; Pfeiffer, A; Piparo, D; Racz, A; Reis, T; Rolandi, G; Rovere, M; Ruan, M; Sakulin, H; Schäfer, C; Schwick, C; Seidel, M; Sharma, A; Silva, P; Simon, M; Sphicas, P; Steggemann, J; Stieger, B; Stoye, M; Takahashi, Y; Treille, D; Triossi, A; Tsirou, A; Veres, G I; Wardle, N; Wöhri, H K; Zagozdzinska, A; Zeuner, W D; Bertl, W; Deiters, K; Erdmann, W; Horisberger, R; Ingram, Q; Kaestli, H C; Kotlinski, D; Langenegger, U; Renker, D; Rohe, T; Bachmair, F; Bäni, L; Bianchini, L; Casal, B; Dissertori, G; Dittmar, M; Donegà, M; Eller, P; Grab, C; Heidegger, C; Hits, D; Hoss, J; Kasieczka, G; Lustermann, W; Mangano, B; Marionneau, M; Martinez Ruiz Del Arbol, P; Masciovecchio, M; Meister, D; Micheli, F; Musella, P; Nessi-Tedaldi, F; Pandolfi, F; Pata, J; Pauss, F; Perrozzi, L; Quittnat, M; Rossini, M; Starodumov, A; Takahashi, M; Tavolaro, V R; Theofilatos, K; Wallny, R; Aarrestad, T K; Amsler, C; Caminada, L; Canelli, M F; Chiochia, V; De Cosa, A; Galloni, C; Hinzmann, A; Hreus, T; Kilminster, B; Lange, C; Ngadiuba, J; Pinna, D; Robmann, P; Ronga, F J; Salerno, D; Yang, Y; Cardaci, M; Chen, K H; Doan, T H; Jain, Sh; Khurana, R; Konyushikhin, M; Kuo, C M; Lin, W; Lu, Y J; Yu, S S; Kumar, Arun; Bartek, R; Chang, P; Chang, Y H; Chao, Y; Chen, K F; Chen, P H; Dietz, C; Fiori, F; Grundler, U; Hou, W-S; Hsiung, Y; Liu, Y F; Lu, R-S; Miñano Moya, M; Petrakou, E; Tsai, J F; Tzeng, Y M; Asavapibhop, B; Kovitanggoon, K; Singh, G; Srimanobhas, N; Suwonjandee, N; Adiguzel, A; Bakirci, M N; Cerci, S; Demiroglu, Z S; Dozen, C; Eskut, E; Gecit, F H; Girgis, S; Gokbulut, G; Guler, Y; Guler, Y; Gurpinar, E; Hos, I; Kangal, E E; Onengut, G; Ozcan, M; Ozdemir, K; Polatoz, A; Sunar Cerci, D; Topakli, H; Vergili, M; Zorbilmez, C; Akin, I V; Bilin, B; Bilmis, S; Isildak, B; Karapinar, G; Yalvac, M; Zeyrek, M; Gülmez, E; Kaya, M; Kaya, O; Yetkin, E A; Yetkin, T; Cakir, A; Cankocak, K; Sen, S; Vardarlı, F I; Grynyov, B; Levchuk, L; Sorokin, P; Aggleton, R; Ball, F; Beck, L; Brooke, J J; Clement, E; Cussans, D; Flacher, H; Goldstein, J; Grimes, M; Heath, G P; Heath, H F; Jacob, J; Kreczko, L; Lucas, C; Meng, Z; Newbold, D M; Paramesvaran, S; Poll, A; Sakuma, T; Seif El Nasr-Storey, S; Senkin, S; Smith, D; Smith, V J; Bell, K W; Belyaev, A; Brew, C; Brown, R M; Calligaris, L; Cieri, D; Cockerill, D J A; Coughlan, J A; Harder, K; Harper, S; Olaiya, E; Petyt, D; Shepherd-Themistocleous, C H; Thea, A; Tomalin, I R; Williams, T; Worm, S D; Baber, M; Bainbridge, R; Buchmuller, O; Bundock, A; Burton, D; Casasso, S; Citron, M; Colling, D; Corpe, L; Cripps, N; Dauncey, P; Davies, G; De Wit, A; Della Negra, M; Dunne, P; Elwood, A; Elwood, A; Ferguson, W; Futyan, D; Hall, G; Iles, G; Kenzie, M; Lane, R; Lucas, R; Lyons, L; Magnan, A-M; Malik, S; Nash, J; Nikitenko, A; Pela, J; Pesaresi, M; Petridis, K; Raymond, D M; Richards, A; Rose, A; Seez, C; Tapper, A; Uchida, K; Vazquez Acosta, M; Virdee, T; Zenz, S C; Cole, J E; Hobson, P R; Khan, A; Kyberd, P; Leggat, D; Leslie, D; Reid, I D; Symonds, P; Teodorescu, L; Turner, M; Borzou, A; Call, K; Dittmann, J; Hatakeyama, K; Liu, H; Pastika, N; Scarborough, T; Wu, Z; Charaf, O; Cooper, S I; Henderson, C; Rumerio, P; Arcaro, D; Avetisyan, A; Bose, T; Fantasia, C; Gastler, D; Lawson, P; Rankin, D; Richardson, C; Rohlf, J; St John, J; Sulak, L; Zou, D; Alimena, J; Berry, E; Bhattacharya, S; Cutts, D; Dhingra, N; Ferapontov, A; Garabedian, A; Hakala, J; Heintz, U; Laird, E; Landsberg, G; Mao, Z; Narain, M; Piperov, S; Sagir, S; Syarif, R; Breedon, R; Breto, G; De La Barca Sanchez, M Calderon; Chauhan, S; Chertok, M; Conway, J; Conway, R; Cox, P T; Erbacher, R; Funk, G; Gardner, M; Ko, W; Lander, R; Mulhearn, M; Pellett, D; Pilot, J; Ricci-Tam, F; Shalhout, S; Smith, J; Squires, M; Stolp, D; Tripathi, M; Wilbur, S; Yohay, R; Bravo, C; Cousins, R; Everaerts, P; Farrell, C; Florent, A; Hauser, J; Ignatenko, M; Saltzberg, D; Schnaible, C; Valuev, V; Weber, M; Burt, K; Clare, R; Ellison, J; Gary, J W; Hanson, G; Heilman, J; Ivova Paneva, M; Jandir, P; Kennedy, E; Lacroix, F; Long, O R; Luthra, A; Malberti, M; Negrete, M Olmedo; Shrinivas, A; Wei, H; Wimpenny, S; Yates, B R; Branson, J G; Cerati, G B; Cittolin, S; D'Agnolo, R T; Derdzinski, M; Holzner, A; Kelley, R; Klein, D; Letts, J; Macneill, I; Olivito, D; Padhi, S; Pieri, M; Sani, M; Sharma, V; Simon, S; Tadel, M; Tu, Y; Vartak, A; Wasserbaech, S; Welke, C; Würthwein, F; Yagil, A; Zevi Della Porta, G; Bradmiller-Feld, J; Campagnari, C; Dishaw, A; Dutta, V; Flowers, K; Franco Sevilla, M; Geffert, P; George, C; Golf, F; Gouskos, L; Gran, J; Incandela, J; Mccoll, N; Mullin, S D; Mullin, S D; Richman, J; Stuart, D; Suarez, I; West, C; Yoo, J; Anderson, D; Apresyan, A; Bornheim, A; Bunn, J; Chen, Y; Duarte, J; Mott, A; Newman, H B; Pena, C; Pierini, M; Spiropulu, M; Vlimant, J R; Xie, S; Zhu, R Y; Andrews, M B; Azzolini, V; Calamba, A; Carlson, B; Ferguson, T; Paulini, M; Russ, J; Sun, M; Vogel, H; Vorobiev, I; Cumalat, J P; Ford, W T; Gaz, A; Jensen, F; Johnson, A; Krohn, M; Mulholland, T; Nauenberg, U; Stenson, K; Wagner, S R; Alexander, J; Chatterjee, A; Chaves, J; Chu, J; Dittmer, S; Eggert, N; Mirman, N; Nicolas Kaufman, G; Patterson, J R; Rinkevicius, A; Ryd, A; Skinnari, L; Soffi, L; Sun, W; Tan, S M; Teo, W D; Thom, J; Thompson, J; Tucker, J; Weng, Y; Wittich, P; Abdullin, S; Albrow, M; Apollinari, G; Banerjee, S; Bauerdick, L A T; Beretvas, A; Berryhill, J; Bhat, P C; Bolla, G; Burkett, K; Butler, J N; Cheung, H W K; Chlebana, F; Cihangir, S; Elvira, V D; Fisk, I; Freeman, J; Gottschalk, E; Gray, L; Green, D; Grünendahl, S; Gutsche, O; Hanlon, J; Hare, D; Harris, R M; Hasegawa, S; Hirschauer, J; Hu, Z; Jayatilaka, B; Jindariani, S; Johnson, M; Joshi, U; Jung, A W; Klima, B; Kreis, B; Lammel, S; Linacre, J; Lincoln, D; Lipton, R; Liu, T; Lopes De Sá, R; Lykken, J; Maeshima, K; Marraffino, J M; Martinez Outschoorn, V I; Maruyama, S; Mason, D; McBride, P; Merkel, P; Mishra, K; Mrenna, S; Nahn, S; Newman-Holmes, C; O'Dell, V; Pedro, K; Prokofyev, O; Rakness, G; Sexton-Kennedy, E; Soha, A; Spalding, W J; Spiegel, L; Strobbe, N; Taylor, L; Tkaczyk, S; Tran, N V; Uplegger, L; Vaandering, E W; Vernieri, C; Verzocchi, M; Vidal, R; Weber, H A; Whitbeck, A; Acosta, D; Avery, P; Bortignon, P; Bourilkov, D; Carnes, A; Carver, M; Curry, D; Das, S; Field, R D; Furic, I K; Gleyzer, S V; Hugon, J; Konigsberg, J; Korytov, A; Kotov, K; Low, J F; Ma, P; Matchev, K; Mei, H; Milenovic, P; Mitselmakher, G; Rank, D; Rossin, R; Shchutska, L; Snowball, M; Sperka, D; Terentyev, N; Thomas, L; Wang, J; Wang, S; Yelton, J; Hewamanage, S; Linn, S; Markowitz, P; Martinez, G; Rodriguez, J L; Adams, J R; Ackert, A; Adams, T; Askew, A; Bein, S; Bochenek, J; Diamond, B; Haas, J; Hagopian, S; Hagopian, V; Johnson, K F; Khatiwada, A; Prosper, H; Weinberg, M; Baarmand, M M; Bhopatkar, V; Colafranceschi, S; Hohlmann, M; Kalakhety, H; Noonan, D; Roy, T; Yumiceva, F; Adams, M R; Apanasevich, L; Berry, D; Betts, R R; Bucinskaite, I; Cavanaugh, R; Evdokimov, O; Gauthier, L; Gerber, C E; Hofman, D J; Kurt, P; O'Brien, C; Sandoval Gonzalez, L D; Silkworth, C; Turner, P; Varelas, N; Wu, Z; Zakaria, M; Bilki, B; Clarida, W; Dilsiz, K; Durgut, S; Gandrajula, R P; Haytmyradov, M; Khristenko, V; Merlo, J-P; Mermerkaya, H; Mestvirishvili, A; Moeller, A; Nachtman, J; Ogul, H; Onel, Y; Ozok, F; Penzo, A; Snyder, C; Tiras, E; Wetzel, J; Yi, K; Anderson, I; Anderson, I; Barnett, B A; Blumenfeld, B; Eminizer, N; Fehling, D; Feng, L; Gritsan, A V; Maksimovic, P; Martin, C; Osherson, M; Roskes, J; Sady, A; Sarica, U; Swartz, M; Xiao, M; Xin, Y; You, C; Xiao, M; Baringer, P; Bean, A; Benelli, G; Bruner, C; Kenny, R P; Majumder, D; Majumder, D; Malek, M; Murray, M; Sanders, S; Stringer, R; Wang, Q; Ivanov, A; Kaadze, K; Khalil, S; Makouski, M; Maravin, Y; Mohammadi, A; Saini, L K; Skhirtladze, N; Toda, S; Lange, D; Rebassoo, F; Wright, D; Anelli, C; Baden, A; Baron, O; Belloni, A; Calvert, B; Eno, S C; Ferraioli, C; Gomez, J A; Hadley, N J; Jabeen, S; Jabeen, S; Kellogg, R G; Kolberg, T; Kunkle, J; Lu, Y; Mignerey, A C; Shin, Y H; Skuja, A; Tonjes, M B; Tonwar, S C; Apyan, A; Barbieri, R; Baty, A; Bierwagen, K; Brandt, S; Bierwagen, K; Busza, W; Cali, I A; Demiragli, Z; Di Matteo, L; Gomez Ceballos, G; Goncharov, M; Gulhan, D; Iiyama, Y; Innocenti, G M; Klute, M; Kovalskyi, D; Lai, Y S; Lee, Y-J; Levin, A; Luckey, P D; Marini, A C; Mcginn, C; Mironov, C; Narayanan, S; Niu, X; Paus, C; Ralph, D; Roland, C; Roland, G; Salfeld-Nebgen, J; Stephans, G S F; Sumorok, K; Varma, M; Velicanu, D; Veverka, J; Wang, J; Wang, T W; Wyslouch, B; Yang, M; Zhukova, V; Dahmes, B; Evans, A; Finkel, A; Gude, A; Hansen, P; Kalafut, S; Kao, S C; Klapoetke, K; Kubota, Y; Lesko, Z; Mans, J; Nourbakhsh, S; Ruckstuhl, N; Rusack, R; Tambe, N; Turkewitz, J; Acosta, J G; Oliveros, S; Avdeeva, E; Bloom, K; Bose, S; Claes, D R; Dominguez, A; Fangmeier, C; Gonzalez Suarez, R; Kamalieddin, R; Keller, J; Knowlton, D; Kravchenko, I; Meier, F; Monroy, J; Ratnikov, F; Siado, J E; Snow, G R; Alyari, M; Dolen, J; George, J; Godshalk, A; Harrington, C; Iashvili, I; Kaisen, J; Kharchilava, A; Kumar, A; Rappoccio, S; Roozbahani, B; Alverson, G; Barberis, E; Baumgartel, D; Chasco, M; Hortiangtham, A; Massironi, A; Morse, D M; Nash, D; Orimoto, T; Teixeira De Lima, R; Trocino, D; Wang, R-J; Wood, D; Zhang, J; Hahn, K A; Kubik, A; Mucia, N; Odell, N; Pollack, B; Pozdnyakov, A; Schmitt, M; Stoynev, S; Sung, K; Trovato, M; Velasco, M; Brinkerhoff, A; Dev, N; Hildreth, M; Jessop, C; Karmgard, D J; Kellams, N; Lannon, K; Marinelli, N; Meng, F; Mueller, C; Musienko, Y; Planer, M; Reinsvold, A; Ruchti, R; Smith, G; Taroni, S; Valls, N; Wayne, M; Wolf, M; Woodard, A; Antonelli, L; Brinson, J; Bylsma, B; Durkin, L S; Flowers, S; Hart, A; Hill, C; Hughes, R; Ji, W; Ling, T Y; Liu, B; Luo, W; Puigh, D; Rodenburg, M; Winer, B L; Wulsin, H W; Driga, O; Elmer, P; Hardenbrook, J; Hebda, P; Koay, S A; Lujan, P; Marlow, D; Medvedeva, T; Mooney, M; Olsen, J; Palmer, C; Piroué, P; Saka, H; Stickland, D; Tully, C; Zuranski, A; Malik, S; Barnes, V E; Benedetti, D; Bortoletto, D; Gutay, L; Jha, M K; Jones, M; Jung, K; Miller, D H; Neumeister, N; Primavera, F; Radburn-Smith, B C; Shi, X; Shipsey, I; Silvers, D; Sun, J; Svyatkovskiy, A; Wang, F; Xie, W; Xu, L; Parashar, N; Stupak, J; Adair, A; Akgun, B; Chen, Z; Ecklund, K M; Geurts, F J M; Guilbaud, M; Li, W; Michlin, B; Northup, M; Padley, B P; Redjimi, R; Roberts, J; Rorie, J; Tu, Z; Zabel, J; Betchart, B; Bodek, A; de Barbaro, P; Demina, R; Eshaq, Y; Ferbel, T; Galanti, M; Galanti, M; Garcia-Bellido, A; Han, J; Harel, A; Hindrichs, O; Hindrichs, O; Khukhunaishvili, A; Petrillo, G; Tan, P; Verzetti, M; Arora, S; Barker, A; Chou, J P; Contreras-Campana, C; Contreras-Campana, E; Ferencek, D; Gershtein, Y; Gray, R; Halkiadakis, E; Hidas, D; Hughes, E; Kaplan, S; Kunnawalkam Elayavalli, R; Lath, A; Nash, K; Panwalkar, S; Park, M; Salur, S; Schnetzer, S; Sheffield, D; Somalwar, S; Stone, R; Thomas, S; Thomassen, P; Walker, M; Foerster, M; Riley, G; Rose, K; Spanier, S; York, A; Bouhali, O; Castaneda Hernandez, A; Celik, A; Dalchenko, M; De Mattia, M; Delgado, A; Dildick, S; Dildick, S; Eusebi, R; Gilmore, J; Huang, T; Kamon, T; Krutelyov, V; Krutelyov, V; Mueller, R; Osipenkov, I; Pakhotin, Y; Patel, R; Patel, R; Perloff, A; Rose, A; Safonov, A; Tatarinov, A; Ulmer, K A; Akchurin, N; Cowden, C; Damgov, J; Dragoiu, C; Dudero, P R; Faulkner, J; Kunori, S; Lamichhane, K; Lee, S W; Libeiro, T; Undleeb, S; Volobouev, I; Appelt, E; Delannoy, A G; Greene, S; Gurrola, A; Janjam, R; Johns, W; Maguire, C; Mao, Y; Melo, A; Ni, H; Sheldon, P; Snook, B; Tuo, S; Velkovska, J; Xu, Q; Arenton, M W; Cox, B; Francis, B; Goodell, J; Hirosky, R; Ledovskoy, A; Li, H; Lin, C; Neu, C; Sinthuprasith, T; Sun, X; Wang, Y; Wolfe, E; Wood, J; Xia, F; Clarke, C; Harr, R; Karchin, P E; Kottachchi Kankanamge Don, C; Lamichhane, P; Sturdy, J; Belknap, D A; Carlsmith, D; Cepeda, M; Dasu, S; Dodd, L; Duric, S; Gomber, B; Grothe, M; Hall-Wilton, R; Herndon, M; Hervé, A; Klabbers, P; Lanaro, A; Levine, A; Long, K; Loveless, R; Mohapatra, A; Ojalvo, I; Perry, T; Pierro, G A; Polese, G; Ruggles, T; Sarangi, T; Savin, A; Sharma, A; Smith, N; Smith, W H; Taylor, D; Woods, N

New sets of parameters ("tunes") for the underlying-event (UE) modelling of the pythia8, pythia6 and herwig++ Monte Carlo event generators are constructed using different parton distribution functions. Combined fits to CMS UE proton-proton ([Formula: see text]) data at [Formula: see text] and to UE proton-antiproton ([Formula: see text]) data from the CDF experiment at lower [Formula: see text], are used to study the UE models and constrain their parameters, providing thereby improved predictions for proton-proton collisions at 13[Formula: see text]. In addition, it is investigated whether the values of the parameters obtained from fits to UE observables are consistent with the values determined from fitting observables sensitive to double-parton scattering processes. Finally, comparisons are presented of the UE tunes to "minimum bias" (MB) events, multijet, and Drell-Yan ([Formula: see text] lepton-antilepton+jets) observables at 7 and 8[Formula: see text], as well as predictions for MB and UE observables at 13[Formula: see text].

Simplified adsorption method for detection of antibodies to Candida albicans germ tubes.

PubMed Central

Ponton, J; Quindos, G; Arilla, M C; Mackenzie, D W

1994-01-01

Two modifications that simplify and shorten a method for adsorption of the antibodies against the antigens expressed on both blastospore and germ tube cell wall surfaces (methods 2 and 3) were compared with the original method of adsorption (method 1) to detect anti-Candida albicans germ tube antibodies in 154 serum specimens. Adsorption of the sera by both modified methods resulted in titers very similar to those obtained by the original method. Only 5.2% of serum specimens tested by method 2 and 5.8% of serum specimens tested by method 3 presented greater than one dilution discrepancies in the titers with respect to the titer observed by method 1. When a test based on method 2 was evaluated with sera from patients with invasive candidiasis, the best discriminatory results (sensitivity, 84.6%; specificity, 87.9%; positive predictive value, 75.9%; negative predictive value, 92.7%; efficiency, 86.9%) were obtained when a titer of > or = 1:160 was considered positive. PMID:8126184

Antioxidant Compound Extraction from Maqui (Aristotelia chilensis [Mol] Stuntz) Berries: Optimization by Response Surface Methodology

PubMed Central

Quispe-Fuentes, Issis; Vega-Gálvez, Antonio; Campos-Requena, Víctor H.

2017-01-01

The optimum conditions for the antioxidant extraction from maqui berry were determined using a response surface methodology. A three level D-optimal design was used to investigate the effects of three independent variables namely, solvent type (methanol, acetone and ethanol), solvent concentration and extraction time over total antioxidant capacity by using the oxygen radical absorbance capacity (ORAC) method. The D-optimal design considered 42 experiments including 10 central point replicates. A second-order polynomial model showed that more than 89% of the variation is explained with a satisfactory prediction (78%). ORAC values are higher when acetone was used as a solvent at lower concentrations, and the extraction time range studied showed no significant influence on ORAC values. The optimal conditions for antioxidant extraction obtained were 29% of acetone for 159 min under agitation. From the results obtained it can be concluded that the given predictive model describes an antioxidant extraction process from maqui berry.

Physical function and self-rated health status as predictors of mortality: results from longitudinal analysis in the ilSIRENTE study.

PubMed

Cesari, Matteo; Onder, Graziano; Zamboni, Valentina; Manini, Todd; Shorr, Ronald I; Russo, Andrea; Bernabei, Roberto; Pahor, Marco; Landi, Francesco

2008-12-22

Physical function measures have been shown to predict negative health-related events in older persons, including mortality. These markers of functioning may interact with the self-rated health (SRH) in the prediction of events. Aim of the present study is to compare the predictive value for mortality of measures of physical function and SRH status, and test their possible interactions. Data are from 335 older persons aged >or= 80 years (mean age 85.6 years) enrolled in the "Invecchiamento e Longevità nel Sirente" (ilSIRENTE) study. The predictive values for mortality of 4-meter walk test, Short Physical Performance Battery (SPPB), hand grip strength, Activities of Daily Living (ADL) scale, Instrumental ADL (IADL) scale, and a SRH scale were compared using proportional hazard models. Kaplan-Meier survival curves for mortality and Receiver Operating Characteristic (ROC) curve analyses were also computed to estimate the predictive value of the independent variables of interest for mortality (alone and in combination). During the 24-month follow-up (mean 1.8 years), 71 (21.2%) events occurred in the study sample. All the tested variables were able to significantly predict mortality. No significant interaction was reported between physical function measures and SRH. The SPPB score was the strongest predictor of overall mortality after adjustment for potential confounders (per SD increase; HR 0.64; 95%CI 0.48-0.86). A similar predictive value was showed by the SRH (per SD increase; HR 0.76; 95%CI 0.59-0.97). The chair stand test was the SPPB subtask showing the highest prognostic value. All the tested measures are able to predict mortality with different extents, but strongest results were obtained from the SPPB and the SRH. The chair stand test may be as useful as the complete SPPB in estimating the mortality risk.

Ratio of platelet count/spleen diameter predicted the presence of esophageal varices in patients with schistosomiasis liver cirrhosis.

PubMed

Xu, Xiao-Dan; Xu, Chun-Fang; Dai, Jian-Jun; Qian, Jian-Qing; Pin, Xun

2016-05-01

To examine the platelet count (PC)/spleen diameter (SD) ratio in predicting the presence of esophageal varices (EV) in patients with schistosomiasis liver cirrhosis. A total of 95 consecutive patients with EV induced by schistosomiasis liver cirrhosis were enrolled in this trial. A total of 141 schistosomiasis liver cirrhosis patients without EV were enrolled as controls. All patients were diagnosed by endoscopy. Demographic, laboratory, and Doppler ultrasound parameters were collected and analyzed. Binary logistic regression analysis was carried out to identify independent risk factors associated with EV occurrence. Receiver operating curves were generated to obtain the PC/SD ratio cutoff values for the optimal sensitivity and specificity with respect to EV. The accuracy was increased in diagnosing for EV using the ratio of PC/SD compared with the SD alone [area under the curve: 0.891 95% confidence interval (CI): 0.844-0.928 vs. 0.764 95% CI: 0.705-0.817; P<0.01]. The optimal cutoff value was 1004, with a 77.1% (95% CI: 67.9-84.8%) positive-predictive value and an 89.3% (95% CI: 82.7-94.0%) negative-predictive value. Using a cutoff of 1004, it was determined that 117/141 (83.0%) patients without EV could avoid undergoing unnecessary endoscopy, whereas 14/95 (14.7%) patients with EV would be misdiagnosed. In contrast, when the ratio was set at 909, the positive-predictive and negative-predictive values were 79.5% (95% CI: 69.5-87.4%) and 83.1% (95% CI: 76.1-88.8%), respectively. A ratio of 909 would accurately predict the absence of EV in 123/141 (87.2%) patients; however, 24/95 (25.3%) patients with EV would miss the necessary screening endoscopy. The ratio of PC/SD was a useful marker in predicting the presence of EV in patients with schistosomiasis liver cirrhosis.

Inspiratory muscular weakness is most evident in chronic stroke survivors with lower walking speeds.

PubMed

Pinheiro, M B; Polese, J C; Faria, C D; Machado, G C; Parreira, V F; Britto, R R; Teixeira-Salmela, L F

2014-06-01

Respiratory muscular weakness and associated changes in thoracoabdominal motion have been poorly studied in stroke subjects, since the individuals' functional levels were not previously considered in the investigations. To investigate the breathing patterns, thoracoabdominal motion, and respiratory muscular strength in chronic stroke subjects, who were stratified into two groups, according to their walking speeds. Cross-sectional, observational study. University laboratory. Eighty-nine community-dwelling chronic stroke subjects The subjects, according to their gait speeds, were stratified into community (gait speed ≥0.8 m/s) and non-community ambulators (gait speed <0.8 m/s). Variables related to pulmonary function, breathing patterns, and thoracoabdominal motions were assessed. Measures of maximal inspiratory pressure (MIP) and maximal expiratory pressure (MEP) were obtained and were compared with the reference values for the Brazilian population. The MIP and MEP values were expressed as percentages of the predicted values. Mann-Whitney-U or independent Student t-tests were employed to compare the differences between the two groups for the selected variables. No significant between-group differences were found for the variables related to the breathing patterns and thoracoabdominal motions (0.01 < z/t < 1.51; 0.14

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

Attempt to model laboratory-scale diffusion and retardation data.

PubMed

Hölttä, P; Siitari-Kauppi, M; Hakanen, M; Tukiainen, V

2001-02-01

Different approaches for measuring the interaction between radionuclides and rock matrix are needed to test the compatibility of experimental retardation parameters and transport models used in assessing the safety of the underground repositories for the spent nuclear fuel. In this work, the retardation of sodium, calcium and strontium was studied on mica gneiss, unaltered, moderately altered and strongly altered tonalite using dynamic fracture column method. In-diffusion of calcium into rock cubes was determined to predict retardation in columns. In-diffusion of calcium into moderately and strongly altered tonalite was interpreted using a numerical code FTRANS. The code was able to interprete in-diffusion of weakly sorbing calcium into the saturated porous matrix. Elution curves of calcium for the moderately and strongly altered tonalite fracture columns were explained adequately using FTRANS code and parameters obtained from in-diffusion calculations. In this paper, mass distribution ratio values of sodium, calcium and strontium for intact rock are compared to values, previously obtained for crushed rock from batch and crushed rock column experiments. Kd values obtained from fracture column experiments were one order of magnitude lower than Kd values from batch experiments.

[Design of a preoperative predictive score for choledocholithiasis].

PubMed

Bueno Lledó, Jose; Ibáñez Cirión, Jose Luis; Torregrosa Gallud, Antonio; López Andújar, Rafael

2014-11-01

Choledocholithiasis is the most common cause of obstructive jaundice and occurs in 5-10% of patients with cholelithiasis. To design a preoperative predictive score for choledocholithiasis. A prospective study was carried out in 556 patients admitted to our department for biliary disease. Preoperative clinical, laboratory, and ultrasound variables were compared between patients without choledocholithiasis and 65 patients with this diagnosis. A multivariate logistic analysis was performed to obtain a predictive model of choledocholithiasis, determining sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Predictors of choledocholithiasis were the presence of a prior history of biliary disease (history of biliary colic, acute cholecystitis, choledocholithiasis or acute biliary pancreatitis) (p=0.021, OR=2.225, 95% CI: 1.130-4.381), total bilirubin values >4mg/dl (p=0.046, OR=2.403, 95% CI: 1.106-5.685), alkaline phosphatase values >150mg/dl (p=0.022 income, OR=2.631, 95%: 1.386-6.231), gamma-glutamyltransferase (GGT) values >100mg/dl (p=0.035, OR=2.10, 95% CI: 1.345-5.850), and an ultrasound finding of biliary duct >8mm (p=0.034, OR=3.063 95% CI: 1086-8649). A score superior to 5 had a specificity and PPV of 100% for detecting choledocholithiasis and a score less than 3 had a sensitivity and NPV of 100% for excluding this diagnosis. The preoperative score can exclude or confirm the presence of choledocholithiasis and allows patients to directly benefit from laparoscopic cholecystectomy (LC) or prior endoscopic retrograde cholangiopancreatography (ERCP). Copyright © 2014 Elsevier España, S.L.U. and AEEH y AEG. All rights reserved.

The development of a Kalman filter clock predictor

NASA Technical Reports Server (NTRS)

Davis, John A.; Greenhall, Charles A.; Boudjemaa, Redoane

2005-01-01

A Kalman filter based clock predictor is developed, and its performance evaluated using both simulated and real data. The clock predictor is shown to possess a neat to optimal Prediction Error Variance (PEV) when the underlying noise consists of one of the power law noise processes commonly encountered in time and frequency measurements. The predictor's performance is the presence of multiple noise processes is also examined. The relationship between the PEV obtained in the presence of multiple noise processes and those obtained for the individual component noise processes is examined. Comparisons are made with a simple linear clock predictor. The clock predictor is used to predict future values of the time offset between pairs of NPL's active hydrogen masers.

Theoretical colours for F and G dwarf stars.

NASA Technical Reports Server (NTRS)

Bell, R. A.

1971-01-01

Synthetic spectra have been computed for F and G dwarf stars, using a number of values of chemical abundance, Doppler broadening velocity, and damping constant. Metal abundances for a number of such stars have been obtained using computed and observed m(sub 1) and 40-52 colors. These abundances are in good agreement with spectroscopically determined ones. The c(sub 1) colors of such stars with exactly known trigonometric parallaxes have been used in order to determine how accurately absolute magnitudes can be predicted from the colors. Generally reasonable agreement can be obtained between observed and predicted absolute magnitudes for certain of these stars. The effects of interstellar reddening on the colors of the models are examined.

A Method of Calculating Functional Independence Measure at Discharge from Functional Independence Measure Effectiveness Predicted by Multiple Regression Analysis Has a High Degree of Predictive Accuracy.

PubMed

Tokunaga, Makoto; Watanabe, Susumu; Sonoda, Shigeru

2017-09-01

Multiple linear regression analysis is often used to predict the outcome of stroke rehabilitation. However, the predictive accuracy may not be satisfactory. The objective of this study was to elucidate the predictive accuracy of a method of calculating motor Functional Independence Measure (mFIM) at discharge from mFIM effectiveness predicted by multiple regression analysis. The subjects were 505 patients with stroke who were hospitalized in a convalescent rehabilitation hospital. The formula "mFIM at discharge = mFIM effectiveness × (91 points - mFIM at admission) + mFIM at admission" was used. By including the predicted mFIM effectiveness obtained through multiple regression analysis in this formula, we obtained the predicted mFIM at discharge (A). We also used multiple regression analysis to directly predict mFIM at discharge (B). The correlation between the predicted and the measured values of mFIM at discharge was compared between A and B. The correlation coefficients were .916 for A and .878 for B. Calculating mFIM at discharge from mFIM effectiveness predicted by multiple regression analysis had a higher degree of predictive accuracy of mFIM at discharge than that directly predicted. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Quantifying Additive Interactions of the Osmolyte Proline with Individual Functional Groups of Proteins: Comparisons with Urea and Glycine Betaine, Interpretation of m-Values

PubMed Central

Diehl, Roger C.; Guinn, Emily J.; Capp, Michael W.; Tsodikov, Oleg V.; Record, M. Thomas

2013-01-01

To quantify interactions of the osmolyte L-proline with protein functional groups and predict its effects on protein processes, we use vapor pressure osmometry to determine chemical potential derivatives dµ2/dm3 = µ23 quantifying preferential interactions of proline (component 3) with 21 solutes (component 2) selected to display different combinations of aliphatic or aromatic C, amide, carboxylate, phosphate or hydroxyl O, and/or amide or cationic N surface. Solubility data yield µ23 values for 4 less-soluble solutes. Values of µ23 are dissected using an ASA-based analysis to test the hypothesis of additivity and obtain α-values (proline interaction potentials) for these eight surface types and three inorganic ions. Values of µ23 predicted from these α-values agree with experiment, demonstrating additivity. Molecular interpretation of α-values using the solute partitioning model yields partition coefficients (Kp) quantifying the local accumulation or exclusion of proline in the hydration water of each functional group. Interactions of proline with native protein surface and effects of proline on protein unfolding are predicted from α-values and ASA information and compared with experimental data, with results for glycine betaine and urea, and with predictions from transfer free energy analysis. We conclude that proline stabilizes proteins because of its unfavorable interactions with (exclusion from) amide oxygens and aliphatic hydrocarbon surface exposed in unfolding, and that proline is an effective in vivo osmolyte because of the osmolality increase resulting from its unfavorable interactions with anionic (carboxylate and phosphate) and amide oxygens and aliphatic hydrocarbon groups on the surface of cytoplasmic proteins and nucleic acids. PMID:23909383

Prediction of Chl-a concentrations in an eutrophic lake using ANN models with hybrid inputs

NASA Astrophysics Data System (ADS)

Aksoy, A.; Yuzugullu, O.

2017-12-01

Chlorophyll-a (Chl-a) concentrations in water bodies exhibit both spatial and temporal variations. As a result, frequent sampling is required with higher number of samples. This motivates the use of remote sensing as a monitoring tool. Yet, prediction performances of models that convert radiance values into Chl-a concentrations can be poor in shallow lakes. In this study, Chl-a concentrations in Lake Eymir, a shallow eutrophic lake in Ankara (Turkey), are determined using artificial neural network (ANN) models that use hybrid inputs composed of water quality and meteorological data as well as remotely sensed radiance values to improve prediction performance. Following a screening based on multi-collinearity and principal component analysis (PCA), dissolved-oxygen concentration (DO), pH, turbidity, and humidity were selected among several parameters as the constituents of the hybrid input dataset. Radiance values were obtained from QuickBird-2 satellite. Conversion of the hybrid input into Chl-a concentrations were studied for two different periods in the lake. ANN models were successful in predicting Chl-a concentrations. Yet, prediction performance declined for low Chl-a concentrations in the lake. In general, models with hybrid inputs were superior over the ones that solely used remotely sensed data.

Analysis of the Mechanism of Prolonged Persistence of Drug Interaction between Terbinafine and Amitriptyline or Nortriptyline.

PubMed

Mikami, Akiko; Hori, Satoko; Ohtani, Hisakazu; Sawada, Yasufumi

2017-01-01

The purpose of the study was to quantitatively estimate and predict drug interactions between terbinafine and tricyclic antidepressants (TCAs), amitriptyline or nortriptyline, based on in vitro studies. Inhibition of TCA-metabolizing activity by terbinafine was investigated using human liver microsomes. Based on the unbound K i values obtained in vitro and reported pharmacokinetic parameters, a pharmacokinetic model of drug interaction was fitted to the reported plasma concentration profiles of TCAs administered concomitantly with terbinafine to obtain the drug-drug interaction parameters. Then, the model was used to predict nortriptyline plasma concentration with concomitant administration of terbinafine and changes of area under the curve (AUC) of nortriptyline after cessation of terbinafine. The CYP2D6 inhibitory potency of terbinafine was unaffected by preincubation, so the inhibition seems to be reversible. Terbinafine competitively inhibited amitriptyline or nortriptyline E-10-hydroxylation, with unbound K i values of 13.7 and 12.4 nM, respectively. Observed plasma concentrations of TCAs administered concomitantly with terbinafine were successfully simulated with the drug interaction model using the in vitro parameters. Model-predicted nortriptyline plasma concentration after concomitant nortriptylene/terbinafine administration for two weeks exceeded the toxic level, and drug interaction was predicted to be prolonged; the AUC of nortriptyline was predicted to be increased by 2.5- or 2.0- and 1.5-fold at 0, 3 and 6 months after cessation of terbinafine, respectively. The developed model enables us to quantitatively predict the prolonged drug interaction between terbinafine and TCAs. The model should be helpful for clinical management of terbinafine-CYP2D6 substrate drug interactions, which are difficult to predict due to their time-dependency.

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

Nøst, Therese Haugdahl; Breivik, Knut; Wania, Frank; Rylander, Charlotta; Odland, Jon Øyvind; Sandanger, Torkjel Manning

2016-03-01

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. 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. 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. 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. 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.

A generalized model for estimating the energy density of invertebrates

USGS Publications Warehouse

James, Daniel A.; Csargo, Isak J.; Von Eschen, Aaron; Thul, Megan D.; Baker, James M.; Hayer, Cari-Ann; Howell, Jessica; Krause, Jacob; Letvin, Alex; Chipps, Steven R.

2012-01-01

Invertebrate energy density (ED) values are traditionally measured using bomb calorimetry. However, many researchers rely on a few published literature sources to obtain ED values because of time and sampling constraints on measuring ED with bomb calorimetry. Literature values often do not account for spatial or temporal variability associated with invertebrate ED. Thus, these values can be unreliable for use in models and other ecological applications. We evaluated the generality of the relationship between invertebrate ED and proportion of dry-to-wet mass (pDM). We then developed and tested a regression model to predict ED from pDM based on a taxonomically, spatially, and temporally diverse sample of invertebrates representing 28 orders in aquatic (freshwater, estuarine, and marine) and terrestrial (temperate and arid) habitats from 4 continents and 2 oceans. Samples included invertebrates collected in all seasons over the last 19 y. Evaluation of these data revealed a significant relationship between ED and pDM (r2  =  0.96, p < 0.0001), where ED (as J/g wet mass) was estimated from pDM as ED  =  22,960pDM − 174.2. Model evaluation showed that nearly all (98.8%) of the variability between observed and predicted values for invertebrate ED could be attributed to residual error in the model. Regression of observed on predicted values revealed that the 97.5% joint confidence region included the intercept of 0 (−103.0 ± 707.9) and slope of 1 (1.01 ± 0.12). Use of this model requires that only dry and wet mass measurements be obtained, resulting in significant time, sample size, and cost savings compared to traditional bomb calorimetry approaches. This model should prove useful for a wide range of ecological studies because it is unaffected by taxonomic, seasonal, or spatial variability.

Three-dimensional (3D) structure prediction of the American and African oil-palms β-ketoacyl-[ACP] synthase-II protein by comparative modelling

PubMed Central

Wang, Edina; Chinni, Suresh; Bhore, Subhash Janardhan

2014-01-01

Background: The fatty-acid profile of the vegetable oils determines its properties and nutritional value. Palm-oil obtained from the African oil-palm [Elaeis guineensis Jacq. (Tenera)] contains 44% palmitic acid (C16:0), but, palm-oil obtained from the American oilpalm [Elaeis oleifera] contains only 25% C16:0. In part, the b-ketoacyl-[ACP] synthase II (KASII) [EC: 2.3.1.179] protein is responsible for the high level of C16:0 in palm-oil derived from the African oil-palm. To understand more about E. guineensis KASII (EgKASII) and E. oleifera KASII (EoKASII) proteins, it is essential to know its structures. Hence, this study was undertaken. Objective: The objective of this study was to predict three-dimensional (3D) structure of EgKASII and EoKASII proteins using molecular modelling tools. Materials and Methods: The amino-acid sequences for KASII proteins were retrieved from the protein database of National Center for Biotechnology Information (NCBI), USA. The 3D structures were predicted for both proteins using homology modelling and ab-initio technique approach of protein structure prediction. The molecular dynamics (MD) simulation was performed to refine the predicted structures. The predicted structure models were evaluated and root mean square deviation (RMSD) and root mean square fluctuation (RMSF) values were calculated. Results: The homology modelling showed that EgKASII and EoKASII proteins are 78% and 74% similar with Streptococcus pneumonia KASII and Brucella melitensis KASII, respectively. The EgKASII and EoKASII structures predicted by using ab-initio technique approach shows 6% and 9% deviation to its structures predicted by homology modelling, respectively. The structure refinement and validation confirmed that the predicted structures are accurate. Conclusion: The 3D structures for EgKASII and EoKASII proteins were predicted. However, further research is essential to understand the interaction of EgKASII and EoKASII proteins with its substrates. PMID:24748752

Three-dimensional (3D) structure prediction of the American and African oil-palms β-ketoacyl-[ACP] synthase-II protein by comparative modelling.

PubMed

Wang, Edina; Chinni, Suresh; Bhore, Subhash Janardhan

2014-01-01

The fatty-acid profile of the vegetable oils determines its properties and nutritional value. Palm-oil obtained from the African oil-palm [Elaeis guineensis Jacq. (Tenera)] contains 44% palmitic acid (C16:0), but, palm-oil obtained from the American oilpalm [Elaeis oleifera] contains only 25% C16:0. In part, the b-ketoacyl-[ACP] synthase II (KASII) [EC: 2.3.1.179] protein is responsible for the high level of C16:0 in palm-oil derived from the African oil-palm. To understand more about E. guineensis KASII (EgKASII) and E. oleifera KASII (EoKASII) proteins, it is essential to know its structures. Hence, this study was undertaken. The objective of this study was to predict three-dimensional (3D) structure of EgKASII and EoKASII proteins using molecular modelling tools. The amino-acid sequences for KASII proteins were retrieved from the protein database of National Center for Biotechnology Information (NCBI), USA. The 3D structures were predicted for both proteins using homology modelling and ab-initio technique approach of protein structure prediction. The molecular dynamics (MD) simulation was performed to refine the predicted structures. The predicted structure models were evaluated and root mean square deviation (RMSD) and root mean square fluctuation (RMSF) values were calculated. The homology modelling showed that EgKASII and EoKASII proteins are 78% and 74% similar with Streptococcus pneumonia KASII and Brucella melitensis KASII, respectively. The EgKASII and EoKASII structures predicted by using ab-initio technique approach shows 6% and 9% deviation to its structures predicted by homology modelling, respectively. The structure refinement and validation confirmed that the predicted structures are accurate. The 3D structures for EgKASII and EoKASII proteins were predicted. However, further research is essential to understand the interaction of EgKASII and EoKASII proteins with its substrates.

Evaluation of AUC(0-4) predictive methods for cyclosporine in kidney transplant patients.

PubMed

Aoyama, Takahiko; Matsumoto, Yoshiaki; Shimizu, Makiko; Fukuoka, Masamichi; Kimura, Toshimi; Kokubun, Hideya; Yoshida, Kazunari; Yago, Kazuo

2005-05-01

Cyclosporine (CyA) is the most commonly used immunosuppressive agent in patients who undergo kidney transplantation. Dosage adjustment of CyA is usually based on trough levels. Recently, trough levels have been replacing the area under the concentration-time curve during the first 4 h after CyA administration (AUC(0-4)). The aim of this study was to compare the predictive values obtained using three different methods of AUC(0-4) monitoring. AUC(0-4) was calculated from 0 to 4 h in early and stable renal transplant patients using the trapezoidal rule. The predicted AUC(0-4) was calculated using three different methods: the multiple regression equation reported by Uchida et al.; Bayesian estimation for modified population pharmacokinetic parameters reported by Yoshida et al.; and modified population pharmacokinetic parameters reported by Cremers et al. The predicted AUC(0-4) was assessed on the basis of predictive bias, precision, and correlation coefficient. The predicted AUC(0-4) values obtained using three methods through measurement of three blood samples showed small differences in predictive bias, precision, and correlation coefficient. In the prediction of AUC(0-4) measurement of one blood sample from stable renal transplant patients, the performance of the regression equation reported by Uchida depended on sampling time. On the other hand, the performance of Bayesian estimation with modified pharmacokinetic parameters reported by Yoshida through measurement of one blood sample, which is not dependent on sampling time, showed a small difference in the correlation coefficient. The prediction of AUC(0-4) using a regression equation required accurate sampling time. In this study, the prediction of AUC(0-4) using Bayesian estimation did not require accurate sampling time in the AUC(0-4) monitoring of CyA. Thus Bayesian estimation is assumed to be clinically useful in the dosage adjustment of CyA.

Prediction of residual feed intake for first-lactation dairy cows using orthogonal polynomial random regression.

PubMed

Manafiazar, G; McFadden, T; Goonewardene, L; Okine, E; Basarab, J; Li, P; Wang, Z

2013-01-01

Residual Feed Intake (RFI) is a measure of energy efficiency. Developing an appropriate model to predict expected energy intake while accounting for multifunctional energy requirements of metabolic body weight (MBW), empty body weight (EBW), milk production energy requirements (MPER), and their nonlinear lactation profiles, is the key to successful prediction of RFI in dairy cattle. Individual daily actual energy intake and monthly body weight of 281 first-lactation dairy cows from 1 to 305 d in milk were recorded at the Dairy Research and Technology Centre of the University of Alberta (Edmonton, AB, Canada); individual monthly milk yield and compositions were obtained from the Dairy Herd Improvement Program. Combinations of different orders (1-5) of fixed (F) and random (R) factors were fitted using Legendre polynomial regression to model the nonlinear lactation profiles of MBW, EBW, and MPER over 301 d. The F5R3, F5R3, and F5R2 (subscripts indicate the order fitted) models were selected, based on the combination of the log-likelihood ratio test and the Bayesian information criterion, as the best prediction equations for MBW, EBW, and MPER, respectively. The selected models were used to predict daily individual values for these traits. To consider the body reserve changes, the differences of predicted EBW between 2 consecutive days were considered as the EBW change between these days. The smoothed total 301-d actual energy intake was then linearly regressed on the total 301-d predicted traits of MBW, EBW change, and MPER to obtain the first-lactation RFI (coefficient of determination=0.68). The mean of predicted daily average lactation RFI was 0 and ranged from -6.58 to 8.64 Mcal of NE(L)/d. Fifty-one percent of the animals had an RFI value below the mean (efficient) and 49% of them had an RFI value above the mean (inefficient). These results indicate that the first-lactation RFI can be predicted from its component traits with a reasonable coefficient of determination. The predicted RFI could be used in the dairy breeding program to increase profitability by selecting animals that are genetically superior in energy efficiency based on RFI, or through routinely measured traits, which are genetically correlated with RFI. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Modelling of the 10-micrometer natural laser emission from the mesospheres of Mars and Venus

NASA Technical Reports Server (NTRS)

Deming, D.; Mumma, M. J.

1983-01-01

The NLTE radiative transfer problem is solved to obtain the 00 deg 1 vibrational state population. This model successfully reproduces the existing center-to-limb observations, although higher spatial resolution observations are needed for a definitive test. The model also predicts total fluxes which are close to the observed values. The strength of the emission is predicted to be closely related to the instantaneous near-IR solar heating rate.

Modeling of the 10-micron natural laser emission from the mesospheres of Mars and Venus

NASA Technical Reports Server (NTRS)

Deming, D.; Mumma, M. J.

1983-01-01

The NLTE radiative transfer problem is solved to obtain the 00 deg 1 vibrational state population. This model successfully reproduces the existing center-to-limb observations, although higher spatial resolution observations are needed for a definitive test. The model also predicts total fluxes which are close to the observed values. The strength of the emission is predicted to be closely related to the instantaneous near-IR solar heating rate.

Genomic selection in sugar beet breeding populations

PubMed Central

2013-01-01

Background Genomic selection exploits dense genome-wide marker data to predict breeding values. In this study we used a large sugar beet population of 924 lines representing different germplasm types present in breeding populations: unselected segregating families and diverse lines from more advanced stages of selection. All lines have been intensively phenotyped in multi-location field trials for six agronomically important traits and genotyped with 677 SNP markers. Results We used ridge regression best linear unbiased prediction in combination with fivefold cross-validation and obtained high prediction accuracies for all except one trait. In addition, we investigated whether a calibration developed based on a training population composed of diverse lines is suited to predict the phenotypic performance within families. Our results show that the prediction accuracy is lower than that obtained within the diverse set of lines, but comparable to that obtained by cross-validation within the respective families. Conclusions The results presented in this study suggest that a training population derived from intensively phenotyped and genotyped diverse lines from a breeding program does hold potential to build up robust calibration models for genomic selection. Taken together, our results indicate that genomic selection is a valuable tool and can thus complement the genomics toolbox in sugar beet breeding. PMID:24047500

Plasma Free Amino Acid Profiles Predict Four-Year Risk of Developing Diabetes, Metabolic Syndrome, Dyslipidemia, and Hypertension in Japanese Population

PubMed Central

Yamakado, Minoru; Nagao, Kenji; Imaizumi, Akira; Tani, Mizuki; Toda, Akiko; Tanaka, Takayuki; Jinzu, Hiroko; Miyano, Hiroshi; Yamamoto, Hiroshi; Daimon, Takashi; Horimoto, Katsuhisa; Ishizaka, Yuko

2015-01-01

Plasma free amino acid (PFAA) profile is highlighted in its association with visceral obesity and hyperinsulinemia, and future diabetes. Indeed PFAA profiling potentially can evaluate individuals’ future risks of developing lifestyle-related diseases, in addition to diabetes. However, few studies have been performed especially in Asian populations, about the optimal combination of PFAAs for evaluating health risks. We quantified PFAA levels in 3,701 Japanese subjects, and determined visceral fat area (VFA) and two-hour post-challenge insulin (Ins120 min) values in 865 and 1,160 subjects, respectively. Then, models between PFAA levels and the VFA or Ins120 min values were constructed by multiple linear regression analysis with variable selection. Finally, a cohort study of 2,984 subjects to examine capabilities of the obtained models for predicting four-year risk of developing new-onset lifestyle-related diseases was conducted. The correlation coefficients of the obtained PFAA models against VFA or Ins120 min were higher than single PFAA level. Our models work well for future risk prediction. Even after adjusting for commonly accepted multiple risk factors, these models can predict future development of diabetes, metabolic syndrome, and dyslipidemia. PFAA profiles confer independent and differing contributions to increasing the lifestyle-related disease risks in addition to the currently known factors in a general Japanese population. PMID:26156880

Relative stability of DNA as a generic criterion for promoter prediction: whole genome annotation of microbial genomes with varying nucleotide base composition.

PubMed

Rangannan, Vetriselvi; Bansal, Manju

2009-12-01

The rapid increase in genome sequence information has necessitated the annotation of their functional elements, particularly those occurring in the non-coding regions, in the genomic context. Promoter region is the key regulatory region, which enables the gene to be transcribed or repressed, but it is difficult to determine experimentally. Hence an in silico identification of promoters is crucial in order to guide experimental work and to pin point the key region that controls the transcription initiation of a gene. In this analysis, we demonstrate that while the promoter regions are in general less stable than the flanking regions, their average free energy varies depending on the GC composition of the flanking genomic sequence. We have therefore obtained a set of free energy threshold values, for genomic DNA with varying GC content and used them as generic criteria for predicting promoter regions in several microbial genomes, using an in-house developed tool PromPredict. On applying it to predict promoter regions corresponding to the 1144 and 612 experimentally validated TSSs in E. coli (50.8% GC) and B. subtilis (43.5% GC) sensitivity of 99% and 95% and precision values of 58% and 60%, respectively, were achieved. For the limited data set of 81 TSSs available for M. tuberculosis (65.6% GC) a sensitivity of 100% and precision of 49% was obtained.

Mechanisms governing the visco-elastic responses of living cells assessed by foam and tensegrity models.

PubMed

Cañadas, P; Laurent, V M; Chabrand, P; Isabey, D; Wendling-Mansuy, S

2003-11-01

The visco-elastic properties of living cells, measured to date by various authors, vary considerably, depending on the experimental methods and/or on the theoretical models used. In the present study, two mechanisms thought to be involved in cellular visco-elastic responses were analysed, based on the idea that the cytoskeleton plays a fundamental role in cellular mechanical responses. For this purpose, the predictions of an open unit-cell model and a 30-element visco-elastic tensegrity model were tested, taking into consideration similar properties of the constitutive F-actin. The quantitative predictions of the time constant and viscosity modulus obtained by both models were compared with previously published experimental data obtained from living cells. The small viscosity modulus values (10(0)-10(3) Pa x s) predicted by the tensegrity model may reflect the combined contributions of the spatially rearranged constitutive filaments and the internal tension to the overall cytoskeleton response to external loading. In contrast, the high viscosity modulus values (10(3)-10(5) Pa x s) predicted by the unit-cell model may rather reflect the mechanical response of the cytoskeleton to the bending of the constitutive filaments and/or to the deformation of internal components. The present results suggest the existence of a close link between the overall visco-elastic response of micromanipulated cells and the underlying architecture.

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.

The reliable solution and computation time of variable parameters logistic model

NASA Astrophysics Data System (ADS)

Wang, Pengfei; Pan, Xinnong

2018-05-01

The study investigates the reliable computation time (RCT, termed as T c) by applying a double-precision computation of a variable parameters logistic map (VPLM). Firstly, by using the proposed method, we obtain the reliable solutions for the logistic map. Secondly, we construct 10,000 samples of reliable experiments from a time-dependent non-stationary parameters VPLM and then calculate the mean T c. The results indicate that, for each different initial value, the T cs of the VPLM are generally different. However, the mean T c trends to a constant value when the sample number is large enough. The maximum, minimum, and probable distribution functions of T c are also obtained, which can help us to identify the robustness of applying a nonlinear time series theory to forecasting by using the VPLM output. In addition, the T c of the fixed parameter experiments of the logistic map is obtained, and the results suggest that this T c matches the theoretical formula-predicted value.

Nondestructive prediction of pork freshness parameters using multispectral scattering images

NASA Astrophysics Data System (ADS)

Tang, Xiuying; Li, Cuiling; Peng, Yankun; Chao, Kuanglin; Wang, Mingwu

2012-05-01

Optical technology is an important and immerging technology for non-destructive and rapid detection of pork freshness. This paper studied on the possibility of using multispectral imaging technique and scattering characteristics to predict the freshness parameters of pork meat. The pork freshness parameters selected for prediction included total volatile basic nitrogen (TVB-N), color parameters (L *, a *, b *), and pH value. Multispectral scattering images were obtained from pork sample surface by a multispectral imaging system developed by ourselves; they were acquired at the selected narrow wavebands whose center wavelengths were 517,550, 560, 580, 600, 760, 810 and 910nm. In order to extract scattering characteristics from multispectral images at multiple wavelengths, a Lorentzian distribution (LD) function with four parameters (a: scattering asymptotic value; b: scattering peak; c: scattering width; d: scattering slope) was used to fit the scattering curves at the selected wavelengths. The results show that the multispectral imaging technique combined with scattering characteristics is promising for predicting the freshness parameters of pork meat.

Curiosity and reward: Valence predicts choice and information prediction errors enhance learning.

PubMed

Marvin, Caroline B; Shohamy, Daphna

2016-03-01

Curiosity drives many of our daily pursuits and interactions; yet, we know surprisingly little about how it works. Here, we harness an idea implied in many conceptualizations of curiosity: that information has value in and of itself. Reframing curiosity as the motivation to obtain reward-where the reward is information-allows one to leverage major advances in theoretical and computational mechanisms of reward-motivated learning. We provide new evidence supporting 2 predictions that emerge from this framework. First, we find an asymmetric effect of positive versus negative information, with positive information enhancing both curiosity and long-term memory for information. Second, we find that it is not the absolute value of information that drives learning but, rather, the gap between the reward expected and reward received, an "information prediction error." These results support the idea that information functions as a reward, much like money or food, guiding choices and driving learning in systematic ways. (c) 2016 APA, all rights reserved).

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.

Modeling of short fiber reinforced injection moulded composite

NASA Astrophysics Data System (ADS)

Kulkarni, A.; Aswini, N.; Dandekar, C. R.; Makhe, S.

2012-09-01

A micromechanics based finite element model (FEM) is developed to facilitate the design of a new production quality fiber reinforced plastic injection molded part. The composite part under study is composed of a polyetheretherketone (PEEK) matrix reinforced with 30% by volume fraction of short carbon fibers. The constitutive material models are obtained by using micromechanics based homogenization theories. The analysis is carried out by successfully coupling two commercial codes, Moldflow and ANSYS. Moldflow software is used to predict the fiber orientation by considering the flow kinetics and molding parameters. Material models are inputted into the commercial software ANSYS as per the predicted fiber orientation and the structural analysis is carried out. Thus in the present approach a coupling between two commercial codes namely Moldflow and ANSYS has been established to enable the analysis of the short fiber reinforced injection moulded composite parts. The load-deflection curve is obtained based on three constitutive material model namely an isotropy, transversely isotropy and orthotropy. Average values of the predicted quantities are compared to experimental results, obtaining a good correlation. In this manner, the coupled Moldflow-ANSYS model successfully predicts the load deflection curve of a composite injection molded part.

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.

Autism spectrum disorder etiology: Lay beliefs and the role of cultural values and social axioms.

PubMed

Qi, Xin; Zaroff, Charles M; Bernardo, Allan Bi

2016-08-01

Recent research examining the explanations given by the public (i.e. lay beliefs) for autism spectrum disorder often reveals a reasonably accurate understanding of the biogenetic basis of the disorder. However, lay beliefs often manifest aspects of culture, and much of this work has been conducted in western cultures. In this study, 215 undergraduate university students in Macau, a Special Administrative Region of China, completed self-report measures assessing two beliefs concerning autism spectrum disorder etiology: (1) a belief in parental factors and (2) a belief in genetic factors. Potential correlates of lay beliefs were sought in culture-specific values, and more universal social axioms. Participants were significantly more likely to endorse parenting, relative to genetic factors, as etiological. A perceived parental etiology was predicted by values of mind-body holism. Beliefs in a parental etiology were not predicted by values assessing collectivism, conformity to norms, a belief in a family's ability to obtain recognition through a child's achievement, or interpersonal harmony, nor by the social axioms measured (e.g. social cynicism, reward for application, social complexity, fate control, and religiosity). Beliefs in a genetic etiology were not predicted by either culture-specific values or social axioms. Implications of the current results are discussed. © The Author(s) 2015.

Dopamine Reward Prediction Error Responses Reflect Marginal Utility

PubMed Central

Stauffer, William R.; Lak, Armin; Schultz, Wolfram

2014-01-01

Summary Background Optimal choices require an accurate neuronal representation of economic value. In economics, utility functions are mathematical representations of subjective value that can be constructed from choices under risk. Utility usually exhibits a nonlinear relationship to physical reward value that corresponds to risk attitudes and reflects the increasing or decreasing marginal utility obtained with each additional unit of reward. Accordingly, neuronal reward responses coding utility should robustly reflect this nonlinearity. Results In two monkeys, we measured utility as a function of physical reward value from meaningful choices under risk (that adhered to first- and second-order stochastic dominance). The resulting nonlinear utility functions predicted the certainty equivalents for new gambles, indicating that the functions’ shapes were meaningful. The monkeys were risk seeking (convex utility function) for low reward and risk avoiding (concave utility function) with higher amounts. Critically, the dopamine prediction error responses at the time of reward itself reflected the nonlinear utility functions measured at the time of choices. In particular, the reward response magnitude depended on the first derivative of the utility function and thus reflected the marginal utility. Furthermore, dopamine responses recorded outside of the task reflected the marginal utility of unpredicted reward. Accordingly, these responses were sufficient to train reinforcement learning models to predict the behaviorally defined expected utility of gambles. Conclusions These data suggest a neuronal manifestation of marginal utility in dopamine neurons and indicate a common neuronal basis for fundamental explanatory constructs in animal learning theory (prediction error) and economic decision theory (marginal utility). PMID:25283778

Reinforcement Learning Models and Their Neural Correlates: An Activation Likelihood Estimation Meta-Analysis

PubMed Central

Kumar, Poornima; Eickhoff, Simon B.; Dombrovski, Alexandre Y.

2015-01-01

Reinforcement learning describes motivated behavior in terms of two abstract signals. The representation of discrepancies between expected and actual rewards/punishments – prediction error – is thought to update the expected value of actions and predictive stimuli. Electrophysiological and lesion studies suggest that mesostriatal prediction error signals control behavior through synaptic modification of cortico-striato-thalamic networks. Signals in the ventromedial prefrontal and orbitofrontal cortex are implicated in representing expected value. To obtain unbiased maps of these representations in the human brain, we performed a meta-analysis of functional magnetic resonance imaging studies that employed algorithmic reinforcement learning models, across a variety of experimental paradigms. We found that the ventral striatum (medial and lateral) and midbrain/thalamus represented reward prediction errors, consistent with animal studies. Prediction error signals were also seen in the frontal operculum/insula, particularly for social rewards. In Pavlovian studies, striatal prediction error signals extended into the amygdala, while instrumental tasks engaged the caudate. Prediction error maps were sensitive to the model-fitting procedure (fixed or individually-estimated) and to the extent of spatial smoothing. A correlate of expected value was found in a posterior region of the ventromedial prefrontal cortex, caudal and medial to the orbitofrontal regions identified in animal studies. These findings highlight a reproducible motif of reinforcement learning in the cortico-striatal loops and identify methodological dimensions that may influence the reproducibility of activation patterns across studies. PMID:25665667

Magnetic resonance spectroscopic determination of a neuronal and axonal marker in white matter predicts reversibility of deficits in secondary normal pressure hydrocephalus

PubMed Central

Shiino, A; Nishida, Y; Yasuda, H; Suzuki, M; Matsuda, M; Inubushi, T

2004-01-01

Background: Normal pressure hydrocephalus (NPH) is considered to be a treatable form of dementia, because cerebrospinal fluid (CSF) shunting can lessen symptoms. However, neuroimaging has failed to predict when shunting will be effective. Objective: To investigate whether 1H (proton) magnetic resonance (MR) spectroscopy could predict functional outcome in patients after shunting. Methods: Neurological state including Hasegawa's dementia scale, gait, continence, and the modified Rankin scale were evaluated in 21 patients with secondary NPH who underwent ventriculo-peritoneal shunting. Outcomes were measured postoperatively at one and 12 months and were classified as excellent, fair, or poor. MR spectra were obtained from left hemispheric white matter. Results: Significant preoperative differences in N-acetyl aspartate (NAA)/creatine (Cr) and NAA/choline (Cho) were noted between patients with excellent and poor outcome at one month (p = 0.0014 and 0.0036, respectively). Multiple regression analysis linked higher preoperative NAA/Cr ratio, gait score, and modified Rankin scale to better one month outcome. Predictive value, sensitivity, and specificity for excellent outcome following shunting were 95.2%, 100%, and 87.5%. Multiple regression analysis indicated that NAA/Cho had the best predictive value for one year outcome (p = 0.0032); predictive value, sensitivity, and specificity were 89.5%, 90.0%, and 88.9%. Conclusions: MR spectroscopy predicted long term post-shunting outcomes in patients with secondary NPH, and it would be a useful assessment tool before lumbar drainage. PMID:15258216

[Theoretical modeling and experimental research on direct compaction characteristics of multi-component pharmaceutical powders based on the Kawakita equation].

PubMed

Si, Guo-Ning; Chen, Lan; Li, Bao-Guo

2014-04-01

Base on the Kawakita powder compression equation, a general theoretical model for predicting the compression characteristics of multi-components pharmaceutical powders with different mass ratios was developed. The uniaxial flat-face compression tests of powder lactose, starch and microcrystalline cellulose were carried out, separately. Therefore, the Kawakita equation parameters of the powder materials were obtained. The uniaxial flat-face compression tests of the powder mixtures of lactose, starch, microcrystalline cellulose and sodium stearyl fumarate with five mass ratios were conducted, through which, the correlation between mixture density and loading pressure and the Kawakita equation curves were obtained. Finally, the theoretical prediction values were compared with experimental results. The analysis showed that the errors in predicting mixture densities were less than 5.0% and the errors of Kawakita vertical coordinate were within 4.6%, which indicated that the theoretical model could be used to predict the direct compaction characteristics of multi-component pharmaceutical powders.

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.

Usefulness of conventional transbronchial needle aspiration in the diagnosis, staging and molecular characterization of pulmonary neoplasias by thin-prep based cytology: experience of a single oncological institute.

PubMed

Ramieri, Maria Teresa; Marandino, Ferdinando; Visca, Paolo; Salvitti, Tommaso; Gallo, Enzo; Casini, Beatrice; Giordano, Francesca Romana; Frigieri, Claudia; Caterino, Mauro; Carlini, Sandro; Rinaldi, Massimo; Ceribelli, Anna; Pennetti, Annarita; Alò, Pier Luigi; Marino, Mirella; Pescarmona, Edoardo; Filippetti, Massimo

2016-08-01

Conventional transbronchial needle aspiration (c-TBNA) contributed to improve the bronchoscopic examination, allowing to sample lesions located even outside the tracheo-bronchial tree and in the hilo-mediastinal district, both for diagnostic and staging purposes. We have evaluated the sensitivity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of the c-TBNA performed during the 2005-2015 period for suspicious lung neoplasia and/or hilar and mediastinal lymphadenopathy at the Thoracic endoscopy of the Thoracic Surgery Department of the Regina Elena National Cancer Institute, Rome. Data from 273 consecutive patients (205 males and 68 females) were analyzed. Among 158 (58%) adequate specimens, 112 (41%) were neoplastic or contained atypical cells, 46 (17%) were negative or not diagnostic. We considered in the analysis first the overall period; then we compared the findings of the first [2005-2011] and second period [2012-2015] and, finally, only those of adequate specimens. During the overall period, sensibility and accuracy values were respectively of 53% and 63%, in the first period they reached 41% and 53% respectively; in the second period sensibility and accuracy reached 60% and 68%. Considering only the adequate specimens, sensibility and accuracy during the overall period were respectively of 80% and 82%; the values obtained for the first period were 68% and 72%. Finally, in the second period, sensibility reached 86% and accuracy 89%. Carcinoma-subtyping was possible in 112 cases, adenocarcinomas being diagnosed in 50 cases; further, in 30 cases molecular predictive data could be obtained. The c-TBNA proved to be an efficient method for the diagnosis/staging of lung neoplasms and for the diagnosis of mediastinal lymphadenopathy. Endoscopist's skill and technical development, associated to thin-prep cytology and to a rapid on site examination (ROSE), were able to provide by c-TBNA a high diagnostic yield and molecular predictive data in advanced lung carcinomas.

Interferon-γ-inducible protein-10 in chronic hepatitis C: Correlations with insulin resistance, histological features & sustained virological response.

PubMed

Crisan, Dana; Grigorescu, Mircea Dan; Radu, Corina; Suciu, Alina; Grigorescu, Mircea

2017-04-01

One of the multiple factors contributing to virological response in chronic hepatitis C (CHC) is interferon-gamma-inducible protein-10 (IP-10). Its level reflects the status of interferon-stimulated genes, which in turn is associated with virological response to antiviral therapy. The aim of this study was to evaluate the role of serum IP-10 levels on sustained virological response (SVR) and the association of this parameter with insulin resistance (IR) and liver histology. Two hundred and three consecutive biopsy proven CHC patients were included in the study. Serum levels of IP-10 were determined using ELISA method. IR was evaluated by homeostasis model assessment-IR (HOMA-IR). Histological features were assessed invasively by liver biopsy and noninvasively using FibroTest, ActiTest and SteatoTest. Predictive factors for SVR and their interrelations were assessed. A cut-off value for IP-10 of 392 pg/ml was obtained to discriminate between responders and non-responders. SVR was obtained in 107 patients (52.70%). Area under the receiver operating characteristic curve for SVR was 0.875 with a sensitivity of 91.6 per cent, specificity 74.7 per cent, positive predictive value 80.3 per cent and negative predictive value 88.7 per cent. Higher values of IP-10 were associated with increasing stages of fibrosis (P<0.01) and higher grades of inflammation (P=0.02, P=0.07) assessed morphologically and noninvasively through FibroTest and ActiTest. Significant steatosis and IR were also associated with increased levels of IP-10 (P=0.01 and P=0.02). In multivariate analysis, IP-10 levels and fibrosis stages were independently associated with SVR. Our findings showed that the assessment of serum IP-10 level could be a predictive factor for SVR and it was associated with fibrosis, necroinflammatory activity, significant steatosis and IR in patients with chronic HCV infection.

Revised and improved value of the QED tenth-order electron anomalous magnetic moment

NASA Astrophysics Data System (ADS)

Aoyama, Tatsumi; Kinoshita, Toichiro; Nio, Makiko

2018-02-01

In order to improve the theoretical prediction of the electron anomalous magnetic moment ae we have carried out a new numerical evaluation of the 389 integrals of Set V, which represent 6,354 Feynman vertex diagrams without lepton loops. During this work, we found that one of the integrals, called X 024 , was given a wrong value in the previous calculation due to an incorrect assignment of integration variables. The correction of this error causes a shift of -1.26 to the Set V contribution, and hence to the tenth-order universal (i.e., mass-independent) term A1(10 ). The previous evaluation of all other 388 integrals is free from errors and consistent with the new evaluation. Combining the new and the old (excluding X 024 ) calculations statistically, we obtain 7.606 (192 )(α /π )5 as the best estimate of the Set V contribution. Including the contribution of the diagrams with fermion loops, the improved tenth-order universal term becomes A1(10 )=6.675 (192 ) . Adding hadronic and electroweak contributions leads to the theoretical prediction ae(theory)=1 159 652 182.032 (720 )×10-12 . From this and the best measurement of ae, we obtain the inverse fine-structure constant α-1(ae)=137.035 999 1491 (331 ) . The theoretical prediction of the muon anomalous magnetic moment is also affected by the update of QED contribution and the new value of α , but the shift is much smaller than the theoretical uncertainty.

Cold-air investigation of a 4 1/2 stage turbine with stage-loading factor of 4.66 and high specific work output. 2: Stage group performance

NASA Technical Reports Server (NTRS)

Whitney, W. J.; Behning, F. P.; Moffitt, T. P.; Hotz, G. M.

1980-01-01

The stage group performance of a 4 1/2 stage turbine with an average stage loading factor of 4.66 and high specific work output was determined in cold air at design equivalent speed. The four stage turbine configuration produced design equivalent work output with an efficiency of 0.856; a barely discernible difference from the 0.855 obtained for the complete 4 1/2 stage turbine in a previous investigation. The turbine was designed and the procedure embodied the following design features: (1) controlled vortex flow, (2) tailored radial work distribution, and (3) control of the location of the boundary-layer transition point on the airfoil suction surface. The efficiency forecast for the 4 1/2 stage turbine was 0.886, and the value predicted using a reference method was 0.862. The stage group performance results were used to determine the individual stage efficiencies for the condition at which design 4 1/2 stage work output was obtained. The efficiencies of stages one and four were about 0.020 lower than the predicted value, that of stage two was 0.014 lower, and that of stage three was about equal to the predicted value. Thus all the stages operated reasonably close to their expected performance levels, and the overall (4 1/2 stage) performance was not degraded by any particularly inefficient component.

Predictive value of early brain atrophy on response in patients treated with interferon β

PubMed Central

Pérez-Miralles, Francisco Carlos; Vidal-Jordana, Angela; Río, Jordi; Auger, Cristina; Pareto, Deborah; Tintoré, Mar; Rovira, Alex; Montalban, Xavier

2015-01-01

Objective: To investigate the association between brain volume loss during the first year of interferon treatment and clinical outcome at 4 years. Methods: Patients with multiple sclerosis initiating interferon β were clinically evaluated every 6 months for the presence of relapses and assessment of global disability using the Expanded Disability Status Scale (EDSS). MRI scans were performed at baseline and after 12 months, and the percentage of brain volume change (PBVC), brain parenchymal volume change (BPVc%), gray matter volume change (GMVc%), and white matter volume change (WMVc%) were estimated. Patients were divided based on the cutoff values for predicting confirmed EDSS worsening obtained by receiver operating characteristic analysis for all atrophy measurements. Survival curves and Cox proportional hazards regression to predict disability worsening at last observation were applied, adjusting for demographic, clinical, and radiologic variables. Results: Larger PBVC and WMVc% decreases were observed in patients with disability worsening at 4 years of follow-up, whereas no differences were found in BPVc% or GMVc%. Cutoff points were obtained for PBVC (−0.86%; sensitivity 65.5%, specificity 71.4%) and WMVc% (−2.49%; sensitivity 85.3%, specificity 43.8%). Patients with decreases of PBVC and WMVc% below cutoff values were more prone to develop disability worsening (unadjusted hazard ratio [HR] 3.875, p = 0.005; HR 4.246, p = 0.004, respectively). PBVC (HR 4.751, p = 0.008) and the interaction of new T2 lesions with WMVc% (HR 1.086, p = 0.005) were found to be independent predictors of disability worsening in the multivariate analysis. Conclusions: At the patient level, whole-brain and white matter volume changes in the first year of interferon β therapy are predictive of subsequent clinical evolution under treatment. PMID:26185778

Predictive value of early brain atrophy on response in patients treated with interferon β.

PubMed

Pérez-Miralles, Francisco Carlos; Sastre-Garriga, Jaume; Vidal-Jordana, Angela; Río, Jordi; Auger, Cristina; Pareto, Deborah; Tintoré, Mar; Rovira, Alex; Montalban, Xavier

2015-08-01

To investigate the association between brain volume loss during the first year of interferon treatment and clinical outcome at 4 years. Patients with multiple sclerosis initiating interferon β were clinically evaluated every 6 months for the presence of relapses and assessment of global disability using the Expanded Disability Status Scale (EDSS). MRI scans were performed at baseline and after 12 months, and the percentage of brain volume change (PBVC), brain parenchymal volume change (BPVc%), gray matter volume change (GMVc%), and white matter volume change (WMVc%) were estimated. Patients were divided based on the cutoff values for predicting confirmed EDSS worsening obtained by receiver operating characteristic analysis for all atrophy measurements. Survival curves and Cox proportional hazards regression to predict disability worsening at last observation were applied, adjusting for demographic, clinical, and radiologic variables. Larger PBVC and WMVc% decreases were observed in patients with disability worsening at 4 years of follow-up, whereas no differences were found in BPVc% or GMVc%. Cutoff points were obtained for PBVC (-0.86%; sensitivity 65.5%, specificity 71.4%) and WMVc% (-2.49%; sensitivity 85.3%, specificity 43.8%). Patients with decreases of PBVC and WMVc% below cutoff values were more prone to develop disability worsening (unadjusted hazard ratio [HR] 3.875, p = 0.005; HR 4.246, p = 0.004, respectively). PBVC (HR 4.751, p = 0.008) and the interaction of new T2 lesions with WMVc% (HR 1.086, p = 0.005) were found to be independent predictors of disability worsening in the multivariate analysis. At the patient level, whole-brain and white matter volume changes in the first year of interferon β therapy are predictive of subsequent clinical evolution under treatment.

Prediction of the distillation temperatures of crude oils using ¹H NMR and support vector regression with estimated confidence intervals.

PubMed

Filgueiras, Paulo R; Terra, Luciana A; Castro, Eustáquio V R; Oliveira, Lize M S L; Dias, Júlio C M; Poppi, Ronei J

2015-09-01

This paper aims to estimate the temperature equivalent to 10% (T10%), 50% (T50%) and 90% (T90%) of distilled volume in crude oils using (1)H NMR and support vector regression (SVR). Confidence intervals for the predicted values were calculated using a boosting-type ensemble method in a procedure called ensemble support vector regression (eSVR). The estimated confidence intervals obtained by eSVR were compared with previously accepted calculations from partial least squares (PLS) models and a boosting-type ensemble applied in the PLS method (ePLS). By using the proposed boosting strategy, it was possible to identify outliers in the T10% property dataset. The eSVR procedure improved the accuracy of the distillation temperature predictions in relation to standard PLS, ePLS and SVR. For T10%, a root mean square error of prediction (RMSEP) of 11.6°C was obtained in comparison with 15.6°C for PLS, 15.1°C for ePLS and 28.4°C for SVR. The RMSEPs for T50% were 24.2°C, 23.4°C, 22.8°C and 14.4°C for PLS, ePLS, SVR and eSVR, respectively. For T90%, the values of RMSEP were 39.0°C, 39.9°C and 39.9°C for PLS, ePLS, SVR and eSVR, respectively. The confidence intervals calculated by the proposed boosting methodology presented acceptable values for the three properties analyzed; however, they were lower than those calculated by the standard methodology for PLS. Copyright © 2015 Elsevier B.V. All rights reserved.

Predicting the emissive power of hydrocarbon pool fires.

PubMed

Muñoz, Miguel; Planas, Eulàlia; Ferrero, Fabio; Casal, Joaquim

2007-06-18

The emissive power (E) of a flame depends on the size of the fire and the type of fuel. In fact, it changes significantly over the flame surface: the zones of luminous flame have high emittance, while those covered by smoke have low E values. The emissive power of each zone (that is, the luminous or clear flame and the non-luminous or smoky flame) and the portion of total flame area they occupy must be assessed when a two-zone model is used. In this study, data obtained from an experimental set-up were used to estimate the emissive power of fires and its behaviour as a function of pool size. The experiments were performed using gasoline and diesel oil as fuel. Five concentric circular pools (1.5, 3, 4, 5 and 6m in diameter) were used. Appropriate instruments were employed to determine the main features of the fires. By superimposing IR and VHS images it was possible to accurately identify the luminous and non-luminous zones of the fire. Mathematical expressions were obtained that give a more accurate prediction of E(lum), E(soot) and the average emissive power of a fire as a function of its luminous and smoky zones. These expressions can be used in a two-zone model to obtain a better prediction of the thermal radiation. The value of the radiative fraction was determined from the thermal flux measured with radiometers. An expression is also proposed for estimating the radiative fraction.

Comparison of pH and refractometry index with calcium concentrations in preparturient mammary gland secretions of mares.

PubMed

Korosue, Kenji; Murase, Harutaka; Sato, Fumio; Ishimaru, Mutsuki; Kotoyori, Yasumitsu; Tsujimura, Koji; Nambo, Yasuo

2013-01-15

To test the usefulness of measuring pH and refractometry index, compared with measuring calcium carbonate concentration, of preparturient mammary gland secretions for predicting parturition in mares. Evaluation study. 27 pregnant Thoroughbred mares. Preparturient mammary gland secretion samples were obtained once or twice daily 10 days prior to foaling until parturition. The samples were analyzed for calcium carbonate concentration with a water hardness kit (151 samples), pH with pH test paper (222 samples), and refractometry index with a Brix refractometer (214 samples). The sensitivity, specificity, and positive and negative predictive values for each test were calculated for evaluation of predicting parturition. The PPV within 72 hours and the NPV within 24 hours for calcium carbonate concentration determination (standard value set to 400 μg/g) were 93.8% and 98.3%, respectively. The PPV within 72 hours and the NPV within 24 hours for the pH test (standard value set at 6.4) were 97.9% and 99.4%, respectively. The PPV within 72 hours and the NPV within 24 hours for the Brix test (standard value set to 20%) were 73.2% and 96.5%, respectively. Results suggested that the pH test with the standard value set at a pH of 6.4 would be useful in the management of preparturient mares by predicting when mares are not ready to foal. This was accomplished with equal effectiveness of measuring calcium carbonate concentration with a water hardness kit.

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.

Beta value coupled wave theory for nonslanted reflection gratings.

PubMed

Neipp, Cristian; Francés, Jorge; Gallego, Sergi; Bleda, Sergio; Martínez, Francisco Javier; Pascual, Inmaculada; Beléndez, Augusto

2014-01-01

We present a modified coupled wave theory to describe the properties of nonslanted reflection volume diffraction gratings. The method is based on the beta value coupled wave theory, which will be corrected by using appropriate boundary conditions. The use of this correction allows predicting the efficiency of the reflected order for nonslanted reflection gratings embedded in two media with different refractive indices. The results obtained by using this method will be compared to those obtained using a matrix method, which gives exact solutions in terms of Mathieu functions, and also to Kogelnik's coupled wave theory. As will be demonstrated, the technique presented in this paper means a significant improvement over Kogelnik's coupled wave theory.

Beta Value Coupled Wave Theory for Nonslanted Reflection Gratings

PubMed Central

Neipp, Cristian; Francés, Jorge; Gallego, Sergi; Bleda, Sergio; Martínez, Francisco Javier; Pascual, Inmaculada; Beléndez, Augusto

2014-01-01

We present a modified coupled wave theory to describe the properties of nonslanted reflection volume diffraction gratings. The method is based on the beta value coupled wave theory, which will be corrected by using appropriate boundary conditions. The use of this correction allows predicting the efficiency of the reflected order for nonslanted reflection gratings embedded in two media with different refractive indices. The results obtained by using this method will be compared to those obtained using a matrix method, which gives exact solutions in terms of Mathieu functions, and also to Kogelnik's coupled wave theory. As will be demonstrated, the technique presented in this paper means a significant improvement over Kogelnik's coupled wave theory. PMID:24723811

Solvent-Free Microwave-Assisted Extraction of Polyphenols from Olive Tree Leaves: Antioxidant and Antimicrobial Properties.

PubMed

Şahin, Selin; Samli, Ruya; Tan, Ayşe Seher Birteksöz; Barba, Francisco J; Chemat, Farid; Cravotto, Giancarlo; Lorenzo, José M

2017-06-24

Response surface methodology (RSM) and artificial neural networks (ANN) were evaluated and compared in order to decide which method was the most appropriate to predict and optimize total phenolic content (TPC) and oleuropein yields in olive tree leaf ( Olea europaea ) extracts, obtained after solvent-free microwave-assisted extraction (SFMAE). The SFMAE processing conditions were: microwave irradiation power 250-350 W, extraction time 2-3 min, and the amount of sample 5-10 g. Furthermore, the antioxidant and antimicrobial activities of the olive leaf extracts, obtained under optimal extraction conditions, were assessed by several in vitro assays. ANN had better prediction performance for TPC and oleuropein yields compared to RSM. The optimum extraction conditions to recover both TPC and oleuropein were: irradiation power 250 W, extraction time 2 min, and amount of sample 5 g, independent of the method used for prediction. Under these conditions, the maximal yield of oleuropein (0.060 ± 0.012 ppm) was obtained and the amount of TPC was 2.480 ± 0.060 ppm. Moreover, olive leaf extracts obtained under optimum SFMAE conditions showed antibacterial activity against S. aureus and S. epidermidis , with a minimum inhibitory concentration (MIC) value of 1.25 mg/mL.

Assessment of heart rate, acidosis, consciousness, oxygenation, and respiratory rate to predict noninvasive ventilation failure in hypoxemic patients.

PubMed

Duan, Jun; Han, Xiaoli; Bai, Linfu; Zhou, Lintong; Huang, Shicong

2017-02-01

To develop and validate a scale using variables easily obtained at the bedside for prediction of failure of noninvasive ventilation (NIV) in hypoxemic patients. The test cohort comprised 449 patients with hypoxemia who were receiving NIV. This cohort was used to develop a scale that considers heart rate, acidosis, consciousness, oxygenation, and respiratory rate (referred to as the HACOR scale) to predict NIV failure, defined as need for intubation after NIV intervention. The highest possible score was 25 points. To validate the scale, a separate group of 358 hypoxemic patients were enrolled in the validation cohort. The failure rate of NIV was 47.8 and 39.4% in the test and validation cohorts, respectively. In the test cohort, patients with NIV failure had higher HACOR scores at initiation and after 1, 12, 24, and 48 h of NIV than those with successful NIV. At 1 h of NIV the area under the receiver operating characteristic curve was 0.88, showing good predictive power for NIV failure. Using 5 points as the cutoff value, the sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy for NIV failure were 72.6, 90.2, 87.2, 78.1, and 81.8%, respectively. These results were confirmed in the validation cohort. Moreover, the diagnostic accuracy for NIV failure exceeded 80% in subgroups classified by diagnosis, age, or disease severity and also at 1, 12, 24, and 48 h of NIV. Among patients with NIV failure with a HACOR score of >5 at 1 h of NIV, hospital mortality was lower in those who received intubation at ≤12 h of NIV than in those intubated later [58/88 (66%) vs. 138/175 (79%); p = 0.03). The HACOR scale variables are easily obtained at the bedside. The scale appears to be an effective way of predicting NIV failure in hypoxemic patients. Early intubation in high-risk patients may reduce hospital mortality.

Structure-based CoMFA as a predictive model - CYP2C9 inhibitors as a test case.

PubMed

Yasuo, Kazuya; Yamaotsu, Noriyuki; Gouda, Hiroaki; Tsujishita, Hideki; Hirono, Shuichi

2009-04-01

In this study, we tried to establish a general scheme to create a model that could predict the affinity of small compounds to their target proteins. This scheme consists of a search for ligand-binding sites on a protein, a generation of bound conformations (poses) of ligands in each of the sites by docking, identifications of the correct poses of each ligand by consensus scoring and MM-PBSA analysis, and a construction of a CoMFA model with the obtained poses to predict the affinity of the ligands. By using a crystal structure of CYP 2C9 and the twenty known CYP inhibitors as a test case, we obtained a CoMFA model with a good statistics, which suggested that the classification of the binding sites as well as the predicted bound poses of the ligands should be reasonable enough. The scheme described here would give a method to predict the affinity of small compounds with a reasonable accuracy, which is expected to heighten the value of computational chemistry in the drug design process.

Organic particulate matter formation at varying relative humidity using surrogate secondary and primary organic compounds with activity corrections in the condensed phase obtained using a method based on the Wilson equation

NASA Astrophysics Data System (ADS)

Chang, E. I.; Pankow, J. F.

2008-01-01

Secondary organic aerosol (SOA) formation in the atmosphere is currently often modeled using a multiple lumped "two-product" (N·2p) approach. The N·2p approach neglects: 1) variation of activity coefficient (ζi) values and mean molecular weight MW in the particulate matter (PM) phase; 2) water uptake into the PM; and 3) the possibility of phase separation in the PM. This study considers these effects by adopting an (N·2p)ζ, MW ,θ approach (θ is a phase index). Specific chemical structures are assigned to 25 lumped SOA compounds and to 15 representative primary organic aerosol (POA) compounds to allow calculation of ζi and MW values. The SOA structure assignments are based on chamber-derived 2p gas/particle partition coefficient values coupled with known effects of structure on vapor pressure pL,i° (atm). To facilitate adoption of the (N·2p)ζ, MW, θ approach in large-scale models, this study also develops CP-Wilson.1, a group-contribution ζi-prediction method that is more computationally economical than the UNIFAC model of Fredenslund et al. (1975). Group parameter values required by CP-Wilson.1 are obtained by fitting ζi values to predictions from UNIFAC. The (N·2p)ζ,MW, θ approach is applied (using CP-Wilson.1) to several real α-pinene/O3 chamber cases for high reacted hydrocarbon levels (ΔHC≍400 to 1000 μg m-3) when relative humidity (RH) ≍50%. Good agreement between the chamber and predicted results is obtained using both the (N·2p)ζ, MW, θ and N·2p approaches, indicating relatively small water effects under these conditions. However, for a hypothetical α-pinene/O3 case at ΔHC=30 μg m-3 and RH=50%, the (N·2p)ζ, MW, θ approach predicts that water uptake will lead to an organic PM level that is more double that predicted by the N·2p approach. Adoption of the (N·2p)ζ, MW, θ approach using reasonable lumped structures for SOA and POA compounds is recommended for ambient PM modeling.

Direct and indirect predictions of enteric methane daily production, yield, and intensity per unit of milk and cheese, from fatty acids and milk Fourier-transform infrared spectra.

PubMed

Bittante, Giovanni; Cipolat-Gotet, Claudio

2018-05-23

Mitigating the dairy chain's contribution to climate change requires cheap, rapid methods of predicting enteric CH 4 emissions (EME) of dairy cows in the field. Such methods may also be useful for genetically improving cows to reduce EME. Our objective was to evaluate different procedures for predicting EME traits from infrared spectra of milk samples taken at routine milk recording of cows. As a reference method, we used EME traits estimated from published equations developed from a meta-analysis of data from respiration chambers through analysis of various fatty acids in milk fat by gas chromatography (FA GC ). We analyzed individual milk samples of 1,150 Brown Swiss cows from 85 farms operating different dairy systems (from very traditional to modern), and obtained the cheese yields of individual model cheeses from these samples. We also obtained Fourier-transform infrared absorbance spectra on 1,060 wavelengths (5,000 to 930 waves/cm) from the same samples. Five reference enteric CH 4 traits were calculated: CH 4 yield (CH 4 /DMI, g/kg) per unit of dry matter intake (DMI), and CH 4 intensity (CH 4 /CM, g/kg) per unit of corrected milk (CM) from the FA GC profiles; CH 4 intensity per unit of fresh cheese (CH 4 /CY CURD , g/kg) and cheese solids (CH 4 /CY SOLIDS , g/kg) from individual cheese yields (CY); and daily CH 4 production (dCH 4 , g/d). Direct infrared (IR) calibrations were obtained by BayesB modeling; the determination coefficients of cross-validation varied from 0.36 for dCH 4 to 0.57 for CH 4 /CM, and were similar to the coefficient of determination values of the equations based on FA GC used as the reference method (0.47 for CH 4 /DMI and 0.54 for CH 4 /CM). The models allowed us to select the most informative wavelengths for each EME trait and to infer the milk chemical features underlying the predictions. Aside from the 5 direct infrared prediction calibrations, we tested another 8 indirect prediction models. Using IR-predicted informative fatty acids (FA IR ) instead of FA GC , we were able to obtain indirect predictions with about the same precision (correlation with reference values) as direct IR predictions of CH 4 /DMI (0.78 vs. 0.76, respectively) and CH 4 /CM (0.82 vs. 0.83). The indirect EME predictions based on IR-predicted CY were less precise than the direct IR predictions of both CH 4 /CY CURD (0.67 vs. 0.81) and CH 4 /CY SOLIDS (0.62 vs. 0.78). Four indirect dCH 4 predictions were obtained by multiplying the measured or IR-predicted daily CM production by the direct or indirect CH 4 /CM. Combining recorded daily CM and predicted CH 4 /CM greatly increased precision over direct dCH 4 predictions (0.96-0.96 vs. 0.68). The estimates obtained from the majority of direct and indirect IR-based prediction models exhibited herd and individual cow variability and effects of the main sources of variation (dairy system, parity, days in milk) similar to the reference data. Some rapid, cheap, direct and indirect IR prediction models appear to be useful for monitoring EME in the field and possibly for genetic/genomic selection, but future studies directly measuring CH 4 with different breeds and dairy systems are needed to validate our findings. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Preliminary measurement of the airframe noise from an F-106B delta wing aircraft at low flyover speeds. [establishment of lower limit for noise level of supersonic transport aircraft

NASA Technical Reports Server (NTRS)

Burley, R. R.

1974-01-01

To establish a realistic lower limit for the noise level of advanced supersonic transport aircraft will require knowledge concerning the amount of noise generated by the airframe itself as it moves through the air. The airframe noise level of an F-106B aircraft was determined and was compared to that predicted from an existing empirical relationship. The data were obtained from flyover and static tests conducted to determine the background noise level of the F-106B aircraft. Preliminary results indicate that the spectrum associated with airframe noise was broadband and peaked at a frequency of about 570 hertz. An existing empirical method successfully predicted the frequency where the spectrum peaked. However, the predicted OASPL value of 105 db was considerably greater than the measures value of 83 db.

[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.

Comparison of the diagnostic performance of bacterial culture of nasopharyngeal swab and bronchoalveolar lavage fluid samples obtained from calves with bovine respiratory disease

USDA-ARS?s Scientific Manuscript database

Objective: Examine the culture results, gamithromycin susceptibility, predictive values, and agreement of pooled bilateral nasopharyngeal swabs (NPS) and bronchoalveolar lavages (BAL) for identification of Mannheimia haemolytica genotypes, Pasteurella multocida, and Histophilus somni in calves treat...

Prediction of Phase Separation of Immiscible Ga-Tl Alloys

NASA Astrophysics Data System (ADS)

Kim, Yunkyum; Kim, Han Gyeol; Kang, Youn-Bae; Kaptay, George; Lee, Joonho

2017-06-01

Phase separation temperature of Ga-Tl liquid alloys was investigated using the constrained drop method. With this method, density and surface tension were investigated together. Despite strong repulsive interactions, molar volume showed ideal mixing behavior, whereas surface tension of the alloy was close to that of pure Tl due to preferential adsorption of Tl. Phase separation temperatures and surface tension values obtained with this method were close to the theoretically calculated values using three different thermodynamic models.

Assessing the capacity of social determinants of health data to augment predictive models identifying patients in need of wraparound social services.

PubMed

Kasthurirathne, Suranga N; Vest, Joshua R; Menachemi, Nir; Halverson, Paul K; Grannis, Shaun J

2018-01-01

A growing variety of diverse data sources is emerging to better inform health care delivery and health outcomes. We sought to evaluate the capacity for clinical, socioeconomic, and public health data sources to predict the need for various social service referrals among patients at a safety-net hospital. We integrated patient clinical data and community-level data representing patients' social determinants of health (SDH) obtained from multiple sources to build random forest decision models to predict the need for any, mental health, dietitian, social work, or other SDH service referrals. To assess the impact of SDH on improving performance, we built separate decision models using clinical and SDH determinants and clinical data only. Decision models predicting the need for any, mental health, and dietitian referrals yielded sensitivity, specificity, and accuracy measures ranging between 60% and 75%. Specificity and accuracy scores for social work and other SDH services ranged between 67% and 77%, while sensitivity scores were between 50% and 63%. Area under the receiver operating characteristic curve values for the decision models ranged between 70% and 78%. Models for predicting the need for any services reported positive predictive values between 65% and 73%. Positive predictive values for predicting individual outcomes were below 40%. The need for various social service referrals can be predicted with considerable accuracy using a wide range of readily available clinical and community data that measure socioeconomic and public health conditions. While the use of SDH did not result in significant performance improvements, our approach represents a novel and important application of risk predictive modeling. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Improved RMR Rock Mass Classification Using Artificial Intelligence Algorithms

NASA Astrophysics Data System (ADS)

Gholami, Raoof; Rasouli, Vamegh; Alimoradi, Andisheh

2013-09-01

Rock mass classification systems such as rock mass rating (RMR) are very reliable means to provide information about the quality of rocks surrounding a structure as well as to propose suitable support systems for unstable regions. Many correlations have been proposed to relate measured quantities such as wave velocity to rock mass classification systems to limit the associated time and cost of conducting the sampling and mechanical tests conventionally used to calculate RMR values. However, these empirical correlations have been found to be unreliable, as they usually overestimate or underestimate the RMR value. The aim of this paper is to compare the results of RMR classification obtained from the use of empirical correlations versus machine-learning methodologies based on artificial intelligence algorithms. The proposed methods were verified based on two case studies located in northern Iran. Relevance vector regression (RVR) and support vector regression (SVR), as two robust machine-learning methodologies, were used to predict the RMR for tunnel host rocks. RMR values already obtained by sampling and site investigation at one tunnel were taken into account as the output of the artificial networks during training and testing phases. The results reveal that use of empirical correlations overestimates the predicted RMR values. RVR and SVR, however, showed more reliable results, and are therefore suggested for use in RMR classification for design purposes of rock structures.

The effect of random matter density perturbations on the large mixing angle solution to the solar neutrino problem

NASA Astrophysics Data System (ADS)

Guzzo, M. M.; Holanda, P. C.; Reggiani, N.

2003-08-01

The neutrino energy spectrum observed in KamLAND is compatible with the predictions based on the Large Mixing Angle realization of the MSW (Mikheyev-Smirnov-Wolfenstein) mechanism, which provides the best solution to the solar neutrino anomaly. From the agreement between solar neutrino data and KamLAND observations, we can obtain the best fit values of the mixing angle and square difference mass. When doing the fitting of the MSW predictions to the solar neutrino data, it is assumed the solar matter do not have any kind of perturbations, that is, it is assumed the the matter density monothonically decays from the center to the surface of the Sun. There are reasons to believe, nevertheless, that the solar matter density fluctuates around the equilibrium profile. In this work, we analysed the effect on the Large Mixing Angle parameters when the density matter randomically fluctuates around the equilibrium profile, solving the evolution equation in this case. We find that, in the presence of these density perturbations, the best fit values of the mixing angle and the square difference mass assume smaller values, compared with the values obtained for the standard Large Mixing Angle Solution without noise. Considering this effect of the random perturbations, the lowest island of allowed region for KamLAND spectral data in the parameter space must be considered and we call it very-low region.

Software-based on-site estimation of fractional flow reserve using standard coronary CT angiography data.

PubMed

De Geer, Jakob; Sandstedt, Mårten; Björkholm, Anders; Alfredsson, Joakim; Janzon, Magnus; Engvall, Jan; Persson, Anders

2016-10-01

The significance of a coronary stenosis can be determined by measuring the fractional flow reserve (FFR) during invasive coronary angiography. Recently, methods have been developed which claim to be able to estimate FFR using image data from standard coronary computed tomography angiography (CCTA) exams. To evaluate the accuracy of non-invasively computed fractional flow reserve (cFFR) from CCTA. A total of 23 vessels in 21 patients who had undergone both CCTA and invasive angiography with FFR measurement were evaluated using a cFFR software prototype. The cFFR results were compared to the invasively obtained FFR values. Correlation was calculated using Spearman's rank correlation, and agreement using intraclass correlation coefficient (ICC). Sensitivity, specificity, accuracy, negative predictive value, and positive predictive value for significant stenosis (defined as both FFR ≤0.80 and FFR ≤0.75) were calculated. The mean cFFR value for the whole group was 0.81 and the corresponding mean invFFR value was 0.84. The cFFR sensitivity for significant stenosis (FFR ≤0.80/0.75) on a per-lesion basis was 0.83/0.80, specificity was 0.76/0.89, and accuracy 0.78/0.87. The positive predictive value was 0.56/0.67 and the negative predictive value was 0.93/0.94. The Spearman rank correlation coefficient was ρ = 0.77 (P < 0.001) and ICC = 0.73 (P < 0.001). This particular CCTA-based cFFR software prototype allows for a rapid, non-invasive on-site evaluation of cFFR. The results are encouraging and cFFR may in the future be of help in the triage to invasive coronary angiography. © The Foundation Acta Radiologica 2015.

Accuracy of genomic selection models in a large population of open-pollinated families in white spruce

PubMed Central

Beaulieu, J; Doerksen, T; Clément, S; MacKay, J; Bousquet, J

2014-01-01

Genomic selection (GS) is of interest in breeding because of its potential for predicting the genetic value of individuals and increasing genetic gains per unit of time. To date, very few studies have reported empirical results of GS potential in the context of large population sizes and long breeding cycles such as for boreal trees. In this study, we assessed the effectiveness of marker-aided selection in an undomesticated white spruce (Picea glauca (Moench) Voss) population of large effective size using a GS approach. A discovery population of 1694 trees representative of 214 open-pollinated families from 43 natural populations was phenotyped for 12 wood and growth traits and genotyped for 6385 single-nucleotide polymorphisms (SNPs) mined in 2660 gene sequences. GS models were built to predict estimated breeding values using all the available SNPs or SNP subsets of the largest absolute effects, and they were validated using various cross-validation schemes. The accuracy of genomic estimated breeding values (GEBVs) varied from 0.327 to 0.435 when the training and the validation data sets shared half-sibs that were on average 90% of the accuracies achieved through traditionally estimated breeding values. The trend was also the same for validation across sites. As expected, the accuracy of GEBVs obtained after cross-validation with individuals of unknown relatedness was lower with about half of the accuracy achieved when half-sibs were present. We showed that with the marker densities used in the current study, predictions with low to moderate accuracy could be obtained within a large undomesticated population of related individuals, potentially resulting in larger gains per unit of time with GS than with the traditional approach. PMID:24781808

Calculations on the half-lives of Cluster decay in two-potential approach

NASA Astrophysics Data System (ADS)

Soylu, A.

The half-lives of the cluster decay (CD) from the isotopes having the known experimental values, the half-lives of the α-decay (AD) of same nuclei and also the branching ratios are obtained, within the framework of two-potential approach with cosh potential including with and without the isospin effects. Using two-potential approach and taking into account the isospin effects in the calculations decrease the rms values and they improve the results. The obtained branching ratios are in good agreement with the experimental ones for some isotopes. It is obtained that the isospin-dependent potentials have an influence on the half-lives of the cluster decays of nuclei. Present calculations would be important for predicting the experimental half-lives and branching ratios for the cluster decays of different types of isotopes.

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.

Henry's Constants of Persistent Organic Pollutants by a Group-Contribution Method Based on Scaled-Particle Theory.

PubMed

Razdan, Neil K; Koshy, David M; Prausnitz, John M

2017-11-07

A group-contribution method based on scaled-particle theory was developed to predict Henry's constants for six families of persistent organic pollutants: polychlorinated benzenes, polychlorinated biphenyls, polychlorinated dibenzodioxins, polychlorinated dibenzofurans, polychlorinated naphthalenes, and polybrominated diphenyl ethers. The group-contribution model uses limited experimental data to obtain group-interaction parameters for an easy-to-use method to predict Henry's constants for systems where reliable experimental data are scarce. By using group-interaction parameters obtained from data reduction, scaled-particle theory gives the partial molar Gibbs energy of dissolution, Δg̅ 2 , allowing calculation of Henry's constant, H 2 , for more than 700 organic pollutants. The average deviation between predicted values of log H 2 and experiment is 4%. Application of an approximate van't Hoff equation gives the temperature dependence of Henry's constants for polychlorinated biphenyls, polychlorinated naphthalenes, and polybrominated diphenyl ethers in the environmentally relevant range 0-40 °C.

Assessment of insulin resistance in Chinese PCOS patients with normal glucose tolerance.

PubMed

Gao, Jing; Zhou, Li; Hong, Jie; Chen, Chen

2017-11-01

The study aimed to investigate insulin resistance (IR) status in polycystic ovary syndrome (PCOS) women with normal glucose tolerance (NGT), and further to evaluate feasible diagnostic method for those patients. Three hundred and twenty-five PCOS women with NGT and ninety-five healthy age-matched controls were recruited with Rotterdam criterion and 75 g oral glucose tolerance test (OGTT). IR status was estimated following a glycemic and insulinemic OGTT (0, 30, 60, 120, and 180 min). A modified HOMA-IR formula was applied to each time-course value of glycemia and insulinemia. The predictive performance of each IR index was analyzed with the use of ROC curves. Compared with healthy controls, both non-obese and obese PCOS patients with NGT had a higher BMI, serum glucose, insulin value (p < .05). The best predictive index of IR in non-obese PCOS-NGT was a HOMA-M30 value of 20.36 or more (AUC: 0.753). In obese PCOS-NGT population, the best predictive performance was obtained by a HOMA-M60 value of 32.17 or more (AUC: 0.868). IR was common in Chinese PCOS women with NGT, and the early assessment of IR should be heeded. We recommended HOMA-M30 (Cutoff: 20.36) and HOMA-M60 (Cutoff: 32.17) as the best predictive parameters for non-obese and obese PCOS-NGT patients, respectively.

Predicting the Performance of Chain Saw Machines Based on Shore Scleroscope Hardness

NASA Astrophysics Data System (ADS)

Tumac, Deniz

2014-03-01

Shore hardness has been used to estimate several physical and mechanical properties of rocks over the last few decades. However, the number of researches correlating Shore hardness with rock cutting performance is quite limited. Also, rather limited researches have been carried out on predicting the performance of chain saw machines. This study differs from the previous investigations in the way that Shore hardness values (SH1, SH2, and deformation coefficient) are used to determine the field performance of chain saw machines. The measured Shore hardness values are correlated with the physical and mechanical properties of natural stone samples, cutting parameters (normal force, cutting force, and specific energy) obtained from linear cutting tests in unrelieved cutting mode, and areal net cutting rate of chain saw machines. Two empirical models developed previously are improved for the prediction of the areal net cutting rate of chain saw machines. The first model is based on a revised chain saw penetration index, which uses SH1, machine weight, and useful arm cutting depth as predictors. The second model is based on the power consumed for only cutting the stone, arm thickness, and specific energy as a function of the deformation coefficient. While cutting force has a strong relationship with Shore hardness values, the normal force has a weak or moderate correlation. Uniaxial compressive strength, Cerchar abrasivity index, and density can also be predicted by Shore hardness values.

Performance in the 6-minute walk test and postoperative pulmonary complications in pulmonary surgery: an observational study.

PubMed

Santos, Bruna F A; Souza, Hugo C D; Miranda, Aline P B; Cipriano, Federico G; Gastaldi, Ada C

2016-01-01

To assess functional capacity in the preoperative phase of pulmonary surgery by comparing predicted and obtained values for the six-minute walk test (6MWT) in patients with and without postoperative pulmonary complication (PPC) METHOD: Twenty-one patients in the preoperative phase of open thoracotomy were evaluated using the 6MWT, followed by monitoring of the postoperative evolution of each participant who underwent the routine treatment. Participants were then divided into two groups: the group with PPC and the group without PPC. The results were also compared with the predicted values using reference equations for the 6MWT RESULTS: Over half (57.14%) of patients developed PPC. The 6MWT was associated with the odds for PPC (odds ratio=22, p=0.01); the group without PPC in the postoperative period walked 422.38 (SD=72.18) meters during the 6MWT, while the group with PPC walked an average of 340.89 (SD=100.93) meters (p=0.02). The distance traveled by the group without PPC was 80% of the predicted value, whereas the group with PPC averaged less than 70% (p=0.03), with more appropriate predicted values for the reference equations The 6MWT is an easy, safe, and feasible test for routine preoperative evaluation in pulmonary surgery and may indicate patients with a higher chance of developing PPC.

Stability of Gradient Field Corrections for Quantitative Diffusion MRI.

PubMed

Rogers, Baxter P; Blaber, Justin; Welch, E Brian; Ding, Zhaohua; Anderson, Adam W; Landman, Bennett A

2017-02-11

In magnetic resonance diffusion imaging, gradient nonlinearity causes significant bias in the estimation of quantitative diffusion parameters such as diffusivity, anisotropy, and diffusion direction in areas away from the magnet isocenter. This bias can be substantially reduced if the scanner- and coil-specific gradient field nonlinearities are known. Using a set of field map calibration scans on a large (29 cm diameter) phantom combined with a solid harmonic approximation of the gradient fields, we predicted the obtained b-values and applied gradient directions throughout a typical field of view for brain imaging for a typical 32-direction diffusion imaging sequence. We measured the stability of these predictions over time. At 80 mm from scanner isocenter, predicted b-value was 1-6% different than intended due to gradient nonlinearity, and predicted gradient directions were in error by up to 1 degree. Over the course of one month the change in these quantities due to calibration-related factors such as scanner drift and variation in phantom placement was <0.5% for b-values, and <0.5 degrees for angular deviation. The proposed calibration procedure allows the estimation of gradient nonlinearity to correct b-values and gradient directions ahead of advanced diffusion image processing for high angular resolution data, and requires only a five-minute phantom scan that can be included in a weekly or monthly quality assurance protocol.

An empirical model for parameters affecting energy consumption in boron removal from boron-containing wastewaters by electrocoagulation.

PubMed

Yilmaz, A Erdem; Boncukcuoğlu, Recep; Kocakerim, M Muhtar

2007-06-01

In this study, it was investigated parameters affecting energy consumption in boron removal from boron containing wastewaters prepared synthetically, via electrocoagulation method. The solution pH, initial boron concentration, dose of supporting electrolyte, current density and temperature of solution were selected as experimental parameters affecting energy consumption. The obtained experimental results showed that boron removal efficiency reached up to 99% under optimum conditions, in which solution pH was 8.0, current density 6.0 mA/cm(2), initial boron concentration 100mg/L and solution temperature 293 K. The current density was an important parameter affecting energy consumption too. High current density applied to electrocoagulation cell increased energy consumption. Increasing solution temperature caused to decrease energy consumption that high temperature decreased potential applied under constant current density. That increasing initial boron concentration and dose of supporting electrolyte caused to increase specific conductivity of solution decreased energy consumption. As a result, it was seen that energy consumption for boron removal via electrocoagulation method could be minimized at optimum conditions. An empirical model was predicted by statistically. Experimentally obtained values were fitted with values predicted from empirical model being as following; [formula in text]. Unfortunately, the conditions obtained for optimum boron removal were not the conditions obtained for minimum energy consumption. It was determined that support electrolyte must be used for increase boron removal and decrease electrical energy consumption.

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.

Solar activity prediction

NASA Technical Reports Server (NTRS)

Slutz, R. J.; Gray, T. B.; West, M. L.; Stewart, F. G.; Leftin, M.

1971-01-01

A statistical study of formulas for predicting the sunspot number several years in advance is reported. By using a data lineup with cycle maxima coinciding, and by using multiple and nonlinear predictors, a new formula which gives better error estimates than former formulas derived from the work of McNish and Lincoln is obtained. A statistical analysis is conducted to determine which of several mathematical expressions best describes the relationship between 10.7 cm solar flux and Zurich sunspot numbers. Attention is given to the autocorrelation of the observations, and confidence intervals for the derived relationships are presented. The accuracy of predicting a value of 10.7 cm solar flux from a predicted sunspot number is dicussed.

Estimation of the Viscosities of Liquid Sn-Based Binary Lead-Free Solder Alloys

NASA Astrophysics Data System (ADS)

Wu, Min; Li, Jinquan

2018-01-01

The viscosity of a binary Sn-based lead-free solder alloy was calculated by combining the predicted model with the Miedema model. The viscosity factor was proposed and the relationship between the viscosity and surface tension was analyzed as well. The investigation result shows that the viscosity of Sn-based lead-free solders predicted from the predicted model shows excellent agreement with the reported values. The viscosity factor is determined by three physical parameters: atomic volume, electronic density, and electro-negativity. In addition, the apparent correlation between the surface tension and viscosity of the binary Sn-based Pb-free solder was obtained based on the predicted model.

Determination of cohesive and normal stresses and simulation of fluidization using kinetic theory

NASA Astrophysics Data System (ADS)

Bezbaruah, R.

1991-08-01

The general objective of this study is focused on the solid stresses involved in gas-solid flow. These stresses are generally included in the momentum conservation equations, essentially for stability and to prevent particles from collapsing to unreasonably low values of gas volume fraction. The first half of this work undertakes the measurement of the stresses in various powders by direct means, while the second part uses a newly developed kinetic theory constitutive equation for stress to predict the flow and also the solid's viscosity in a CFB. The cohesive or tensile stress found to exist in some classes of powders is measured using a Cohetester, based on which a cohesive force model is derived, which is sensitive to the characteristic properties of the powder material. The normal stress is measured using a Consolidometer, and the powder solid's modulus is obtained as a function of the volume fraction. The solid's modulus is seen to vary with particle size and particle type, with the smaller size particles being more compressible. The simulation of flow in the CFB using Gidaspow's (1991) extension of Ding's (1990) kinetic theory model to dilute phase flow, predicts realistic values of solids' viscosity that are comparable to viscosities obtained experimentally by Miller (1991). However, to obtain a match between the two, the value of the restitution coefficient has to be close to unity. The flow behavior showed periodic oscillations of flow (turbulence) as seen in a real system.

Study of the structure of yrast bands of neutron-rich 114-124Pd isotopes

NASA Astrophysics Data System (ADS)

Chaudhary, Ritu; Devi, Rani; Khosa, S. K.

2018-02-01

The projected shell model calculations have been carried out in the neutron-rich 114-124Pd isotopic mass chain. The results have been obtained for the deformation systematics of E(2+1) and E(4+1)/E({2}+1) values, BCS subshell occupation numbers, yrast spectra, backbending phenomena, B( E2) transition probabilities and g-factors in these nuclei. The observed systematics of E(2+1) values and R_{42} ratios in the 114-124Pd isotopic mass chain indicate that there is a decrease of collectivity as the neutron number increases from 68 to 78. The occurrence of backbending in these nuclei as well as the changes in the calculated B( E2) transition probabilities and g -factors predict that there are changes in the structure of yrast bands in these nuclei. These changes occur at the spin where there is crossing of g-band by 2-qp bands. The predicted backbendings and predicted values of B( E2)s and g-factors in some of the isotopes need to be confirmed experimentally.

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.

Modeling of spectral signatures of littoral waters

NASA Astrophysics Data System (ADS)

Haltrin, Vladimir I.

1997-12-01

The spectral values of remotely obtained radiance reflectance coefficient (RRC) are compared with the values of RRC computed from inherent optical properties measured during the shipborne experiment near the West Florida coast. The model calculations are based on the algorithm developed at the Naval Research Laboratory at Stennis Space Center and presented here. The algorithm is based on the radiation transfer theory and uses regression relationships derived from experimental data. Overall comparison of derived and measured RRCs shows that this algorithm is suitable for processing ground truth data for the purposes of remote data calibration. The second part of this work consists of the evaluation of the predictive visibility model (PVM). The simulated three-dimensional values of optical properties are compared with the measured ones. Preliminary results of comparison are encouraging and show that the PVM can qualitatively predict the evolution of inherent optical properties in littoral waters.

Anomalous electrical conductivity of nanoscale colloidal suspensions.

PubMed

Chakraborty, Suman; Padhy, Sourav

2008-10-28

The electrical conductivity of colloidal suspensions containing nanoscale conducting particles is nontrivially related to the particle volume fraction and the electrical double layer thickness. Classical electrochemical models, however, tend to grossly overpredict the pertinent effective electrical conductivity values, as compared to those obtained under experimental conditions. We attempt to address this discrepancy by appealing to the complex interconnection between the aggregation kinetics of the nanoscale particles and the electrodynamics within the double layer. In particular, we model the consequent alterations in the effective electrophoretic mobility values of the suspension by addressing the fundamentals of agglomeration-deagglomeration mechanisms through the pertinent variations in the effective particulate dimensions, solid fractions, as well as the equivalent suspension viscosity. The consequent alterations in the electrical conductivity values provide a substantially improved prediction of the corresponding experimental findings and explain the apparent anomalous behavior predicted by the classical theoretical postulates.

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.

Pre-selection and assessment of green organic solvents by clustering chemometric tools.

PubMed

Tobiszewski, Marek; Nedyalkova, Miroslava; Madurga, Sergio; Pena-Pereira, Francisco; Namieśnik, Jacek; Simeonov, Vasil

2018-01-01

The study presents the result of the application of chemometric tools for selection of physicochemical parameters of solvents for predicting missing variables - bioconcentration factors, water-octanol and octanol-air partitioning constants. EPI Suite software was successfully applied to predict missing values for solvents commonly considered as "green". Values for logBCF, logK OW and logK OA were modelled for 43 rather nonpolar solvents and 69 polar ones. Application of multivariate statistics was also proved to be useful in the assessment of the obtained modelling results. The presented approach can be one of the first steps and support tools in the assessment of chemicals in terms of their greenness. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Soil sail content estimation in the yellow river delta with satellite hyperspectral data

USGS Publications Warehouse

Weng, Yongling; Gong, Peng; Zhu, Zhi-Liang

2008-01-01

Soil salinization is one of the most common land degradation processes and is a severe environmental hazard. The primary objective of this study is to investigate the potential of predicting salt content in soils with hyperspectral data acquired with EO-1 Hyperion. Both partial least-squares regression (PLSR) and conventional multiple linear regression (MLR), such as stepwise regression (SWR), were tested as the prediction model. PLSR is commonly used to overcome the problem caused by high-dimensional and correlated predictors. Chemical analysis of 95 samples collected from the top layer of soils in the Yellow River delta area shows that salt content was high on average, and the dominant chemicals in the saline soil were NaCl and MgCl2. Multivariate models were established between soil contents and hyperspectral data. Our results indicate that the PLSR technique with laboratory spectral data has a strong prediction capacity. Spectral bands at 1487-1527, 1971-1991, 2032-2092, and 2163-2355 nm possessed large absolute values of regression coefficients, with the largest coefficient at 2203 nm. We obtained a root mean squared error (RMSE) for calibration (with 61 samples) of RMSEC = 0.753 (R2 = 0.893) and a root mean squared error for validation (with 30 samples) of RMSEV = 0.574. The prediction model was applied on a pixel-by-pixel basis to a Hyperion reflectance image to yield a quantitative surface distribution map of soil salt content. The result was validated successfully from 38 sampling points. We obtained an RMSE estimate of 1.037 (R2 = 0.784) for the soil salt content map derived by the PLSR model. The salinity map derived from the SWR model shows that the predicted value is higher than the true value. These results demonstrate that the PLSR method is a more suitable technique than stepwise regression for quantitative estimation of soil salt content in a large area. ?? 2008 CASI.

Prediction of individual clinical scores in patients with Parkinson's disease using resting-state functional magnetic resonance imaging.

PubMed

Hou, YanBing; Luo, ChunYan; Yang, Jing; Ou, RuWei; Song, Wei; Wei, QianQian; Cao, Bei; Zhao, Bi; Wu, Ying; Shang, Hui-Fang; Gong, QiYong

2016-07-15

Neuroimaging holds the promise that it may one day aid the clinical assessment. However, the vast majority of studies using resting-state functional magnetic resonance imaging (fMRI) have reported average differences between Parkinson's disease (PD) patients and healthy controls, which do not permit inferences at the level of individuals. This study was to develop a model for the prediction of PD illness severity ratings from individual fMRI brain scan. The resting-state fMRI scans were obtained from 84 patients with PD and the Unified Parkinson's Disease Rating Scale-III (UPDRS-III) scores were obtained before scanning. The RVR method was used to predict clinical scores (UPDRS-III) from fMRI scans. The application of RVR to whole-brain resting-state fMRI data allowed prediction of UPDRS-III scores with statistically significant accuracy (correlation=0.35, P-value=0.001; mean sum of squares=222.17, P-value=0.002). This prediction was informed strongly by negative weight areas including prefrontal lobe and medial occipital lobe, and positive weight areas including medial parietal lobe. It was suggested that fMRI scans contained sufficient information about neurobiological change in patients with PD to permit accurate prediction about illness severity, on an individual subject basis. Our results provided preliminary evidence, as proof-of-concept, to support that fMRI might be possible to be a clinically useful quantitative assessment aid in PD at individual level. This may enable clinicians to target those uncooperative patients and machines to replace human for a more efficient use of health care resources. Copyright © 2016 Elsevier B.V. All rights reserved.

Strain- and stress-based forming limit curves for DP 590 steel sheet using Marciniak-Kuczynski method

NASA Astrophysics Data System (ADS)

Kumar, Gautam; Maji, Kuntal

2018-04-01

This article deals with the prediction of strain-and stress-based forming limit curves for advanced high strength steel DP590 sheet using Marciniak-Kuczynski (M-K) method. Three yield criteria namely Von-Mises, Hill's 48 and Yld2000-2d and two hardening laws i.e., Hollomon power and Swift hardening laws were considered to predict the forming limit curves (FLCs) for DP590 steel sheet. The effects of imperfection factor and initial groove angle on prediction of FLC were also investigated. It was observed that the FLCs shifted upward with the increase of imperfection factor value. The initial groove angle was found to have significant effects on limit strains in the left side of FLC, and insignificant effect for the right side of FLC for certain range of strain paths. The limit strains were calculated at zero groove angle for the right side of FLC, and a critical groove angle was used for the left side of FLC. The numerically predicted FLCs considering the different combinations of yield criteria and hardening laws were compared with the published experimental results of FLCs for DP590 steel sheet. The FLC predicted using the combination of Yld2000-2d yield criterion and swift hardening law was in better coorelation with the experimental data. Stress based forming limit curves (SFLCs) were also calculated from the limiting strain values obtained by M-K model. Theoretically predicted SFLCs were compared with that obtained from the experimental forming limit strains. Stress based forming limit curves were seen to better represent the forming limits of DP590 steel sheet compared to that by strain-based forming limit curves.

Should gram stains have a role in diagnosing hip arthroplasty infections?

PubMed

Johnson, Aaron J; Zywiel, Michael G; Stroh, D Alex; Marker, David R; Mont, Michael A

2010-09-01

The utility of Gram stains in diagnosing periprosthetic infections following total hip arthroplasty has recently been questioned. Several studies report low sensitivity of the test, and its poor ability to either confirm or rule out infection in patients undergoing revision total hip arthroplasty. Despite this, many institutions including that of the senior author continue to perform Gram stains during revision total hip arthroplasty. We assessed the sensitivity, specificity, accuracy, and positive and negative predictive values of Gram stains from surgical-site samplings taken from procedures on patients with both infected and aseptic revision total hip arthroplasties. A review was performed on patients who underwent revision total hip arthroplasty between 2000 and 2007. Eighty-two Gram stains were performed on patients who had infected total hip arthroplasties and underwent revision procedures. Additionally, of the 410 revision total hip arthroplasties performed on patients who were confirmed infection-free, 120 Gram stains were performed. Patients were diagnosed as infected using multiple criteria at the time of surgery. Sensitivity, specificity, positive and negative predictive values, and accuracy were calculated from these Gram stain results. The Gram stain demonstrated a sensitivity and specificity of 9.8% and 100%, respectively. In this series, the Gram stain had a negative predictive value of 62%, a positive predictive value of 100%, and an accuracy of 63%. Gram stains obtained from surgical-site samples had poor sensitivity and poor negative predictive value. Based on these findings, as well as those of other authors, we believe that Gram stains should no longer be considered for diagnosing infections in revision total hip arthroplasty. Level III, diagnostic study. See Guidelines for Authors for a complete description of levels of evidence.

Systematized water content calculation in cartilage using T1-mapping MR estimations: design and validation of a mathematical model.

PubMed

Shiguetomi-Medina, J M; Ramirez-Gl, J L; Stødkilde-Jørgensen, H; Møller-Madsen, B

2017-09-01

Up to 80 % of cartilage is water; the rest is collagen fibers and proteoglycans. Magnetic resonance (MR) T1-weighted measurements can be employed to calculate the water content of a tissue using T1 mapping. In this study, a method that translates T1 values into water content data was tested statistically. To develop a predictive equation, T1 values were obtained for tissue-mimicking gelatin samples. 1.5 T MRI was performed using inverse angle phase and an inverse sequence at 37 (±0.5) °C. Regions of interest were manually delineated and the mean T1 value was estimated in arbitrary units. Data were collected and modeled using linear regression. To validate the method, articular cartilage from six healthy pigs was used. The experiment was conducted in accordance with the Danish Animal Experiment Committee. Double measurements were performed for each animal. Ex vivo, all water in the tissue was extracted by lyophilization, thus allowing the volume of water to be measured. This was then compared with the predicted water content via Lin's concordance correlation coefficient at the 95 % confidence level. The mathematical model was highly significant when compared to a null model (p < 0.0001). 97.3 % of the variation in water content can be explained by absolute T1 values. Percentage water content could be predicted as 0.476 + (T1 value) × 0.000193 × 100 %. We found that there was 98 % concordance between the actual and predicted water contents. The results of this study demonstrate that MR data can be used to predict percentage water contents of cartilage samples. 3 (case-control study).

Comparison of various tool wear prediction methods during end milling of metal matrix composite

NASA Astrophysics Data System (ADS)

Wiciak, Martyna; Twardowski, Paweł; Wojciechowski, Szymon

2018-02-01

In this paper, the problem of tool wear prediction during milling of hard-to-cut metal matrix composite Duralcan™ was presented. The conducted research involved the measurements of acceleration of vibrations during milling with constant cutting conditions, and evaluation of the flank wear. Subsequently, the analysis of vibrations in time and frequency domain, as well as the correlation of the obtained measures with the tool wear values were conducted. The validation of tool wear diagnosis in relation to selected diagnostic measures was carried out with the use of one variable and two variables regression models, as well as with the application of artificial neural networks (ANN). The comparative analysis of the obtained results enable.

Perceived noisiness under anechoic, semi-reverberant and earphone listening conditions

NASA Technical Reports Server (NTRS)

Clarke, F. R.; Kryter, K. D.

1972-01-01

Magnitude estimates by each of 31 listeners were obtained for a variety of noise sources under three methods of stimuli presentation: loudspeaker presentation in an anechoic chamber, loudspeaker presentation in a normal semi-reverberant room, and earphone presentation. Comparability of ratings obtained in these environments were evaluated with respect to predictability of ratings from physical measures, reliability of ratings, and to the scale values assigned to various noise stimuli. Acoustic environment was found to have little effect upon physical predictive measures and ratings of perceived noisiness were little affected by the acoustic environment in which they were obtained. The need for further study of possible differing interactions between judged noisiness of steady state sound and the methods of magnitude estimation and paired comparisons is indicated by the finding that in these tests the subjects, though instructed otherwise, apparently judged the maximum rather than the effective magnitude of steady-state noises.

Validity of pre and post-term birth rates based on the date of last menstrual period compared to early obstetric ultrasonography.

PubMed

Medeiros, Maria Nilza Lima; Cavalcante, Nádia Carenina Nunes; Mesquita, Fabrício José Alencar; Batista, Rosângela Lucena Fernandes; Simões, Vanda Maria Ferreira; Cavalli, Ricardo de Carvalho; Cardoso, Viviane Cunha; Bettiol, Heloisa; Barbieri, Marco Antonio; Silva, Antônio Augusto Moura da

2015-04-01

The aim of this study was to assess the validity of the last menstrual period (LMP) estimate in determining pre and post-term birth rates, in a prenatal cohort from two Brazilian cities, São Luís and Ribeirão Preto. Pregnant women with a single fetus and less than 20 weeks' gestation by obstetric ultrasonography who received prenatal care in 2010 and 2011 were included. The LMP was obtained on two occasions (at 22-25 weeks gestation and after birth). The sensitivity of LMP obtained prenatally to estimate the preterm birth rate was 65.6% in São Luís and 78.7% in Ribeirão Preto and the positive predictive value was 57.3% in São Luís and 73.3% in Ribeirão Preto. LMP errors in identifying preterm birth were lower in the more developed city, Ribeirão Preto. The sensitivity and positive predictive value of LMP for the estimate of the post-term birth rate was very low and tended to overestimate it. LMP can be used with some errors to identify the preterm birth rate when obstetric ultrasonography is not available, but is not suitable for predicting post-term birth.

[Reevaluation of the time course of the effect of propofol described with the Schnider pharmacokinetic model].

PubMed

Sepúlveda, P O; Mora, X

2012-12-01

The first order plasma-effect-site equilibration rate constant (k(e0)) links the pharmacokinetics (PK) and pharmacodynamics (PD) of a given drug. This constant, calculated for each specific PK drug model, allowed us to predict the course of the effect in a target controlled infusion (TCI). The PK-PD model of propofol, published by Schnider et al., calculated a k(e0) value of 0.456min(-1) and a corresponding time to peak effect (t peak) of 1.6min. The aim of this study was to reevaluate the k(e0) value for the predicted Schnider model of propofol, with data from a complete effect curve obtained by monitoring the bispectral index (BIS). The study included 35 healthy adult patients (18-90 years) scheduled for elective surgery with standard monitoring and using the BIS XP(®) (Aspect), and who received a propofol infusion to reach a plasma target of 12 μg/ml in 4min. The infusion was then stopped, obtaining a complete effect curve when the patient woke up. The Anestfusor™ (University of Chile) software was used to control the infusion pumps, calculate the plasma concentration plotted by Schnider PK model, and to store the BIS data every second. Loss (LOC) and recovery (ROC) of consciousness was assessed and recorded. Using a traditional parametric method using the "k(e0) Objective function" of the PK-PD tools for Excel, the individual and population k(e0) was calculated. Predictive Smith tests (Pk) and Student t test were used for statistical analysis. A P<.05 indicated significance. The evaluation included 21 male and 14 female patients (18 to 90 years). We obtained 1,001 (±182) EEG data and the corresponding calculated plasma concentration for each case. The population k(e0) obtained was 0.144min(-1) (SD±0.048), very different from the original model (P<.001). This value corresponds with a t peak of 2.45min. The predictive performance (Pk) for the new model was 0.9 (SD±0.03), but only 0.78 (SD±0.06) for the original (P<.001). With a baseline BIS of 95.8 (SD±2.34), the BIS at LOC was 77.48 (SD±9.6) and 74.65(SD±6.3) at ROC (P=.027). The calculated Ce in the original model at LOC and ROC were 5.9 (SD±1.35)/1.08 μg/ml (SD±0.32) (P<.001), respectively, and 2.3 (SD±0.63)/2.0 μg/ml (SD±0.65) (NS) for the new model. The values between LOC/ROC were significantly different between the 2 models (P<.001). No differences in k(e0) value were found between males and females, but in the new model the k(e0) was affected by age as a covariable (0.26-[age×0.0022]) (P<.05). The dynamic relationship between propofol plasma concentrations predicted by Schnider's pharmacokinetic model and its hypnotic effect measured with BIS was better characterized with a smaller k(e0) value (slower t½k(e0)) than that present in the original model, with an age effect also not described before. Copyright © 2011 Sociedad Española de Anestesiología, Reanimación y Terapéutica del Dolor. Published by Elsevier España. All rights reserved.

Application of a Physiologically Based Pharmacokinetic Model to Assess Propofol Hepatic and Renal Glucuronidation in Isolation: Utility of In Vitro and In Vivo Data

PubMed Central

Gill, Katherine L.; Gertz, Michael; Houston, J. Brian

2013-01-01

A physiologically based pharmacokinetic (PBPK) modeling approach was used to assess the prediction accuracy of propofol hepatic and extrahepatic metabolic clearance and to address previously reported underprediction of in vivo clearance based on static in vitro–in vivo extrapolation methods. The predictive capacity of propofol intrinsic clearance data (CLint) obtained in human hepatocytes and liver and kidney microsomes was assessed using the PBPK model developed in MATLAB software. Microsomal data obtained by both substrate depletion and metabolite formation methods and in the presence of 2% bovine serum albumin were considered in the analysis. Incorporation of hepatic and renal in vitro metabolic clearance in the PBPK model resulted in underprediction of propofol clearance regardless of the source of in vitro data; the predicted value did not exceed 35% of the observed clearance. Subsequently, propofol clinical data from three dose levels in intact patients and anhepatic subjects were used for the optimization of hepatic and renal CLint in a simultaneous fitting routine. Optimization process highlighted that renal glucuronidation clearance was underpredicted to a greater extent than liver clearance, requiring empirical scaling factors of 17 and 9, respectively. The use of optimized clearance parameters predicted hepatic and renal extraction ratios within 20% of the observed values, reported in an additional independent clinical study. This study highlights the complexity involved in assessing the contribution of extrahepatic clearance mechanisms and illustrates the application of PBPK modeling, in conjunction with clinical data, to assess prediction of clearance from in vitro data for each tissue individually. PMID:23303442

[Formulation of combined predictive indicators using logistic regression model in predicting sepsis and prognosis].

PubMed

Duan, Liwei; Zhang, Sheng; Lin, Zhaofen

2017-02-01

To explore the method and performance of using multiple indices to diagnose sepsis and to predict the prognosis of severe ill patients. Critically ill patients at first admission to intensive care unit (ICU) of Changzheng Hospital, Second Military Medical University, from January 2014 to September 2015 were enrolled if the following conditions were satisfied: (1) patients were 18-75 years old; (2) the length of ICU stay was more than 24 hours; (3) All records of the patients were available. Data of the patients was collected by searching the electronic medical record system. Logistic regression model was formulated to create the new combined predictive indicator and the receiver operating characteristic (ROC) curve for the new predictive indicator was built. The area under the ROC curve (AUC) for both the new indicator and original ones were compared. The optimal cut-off point was obtained where the Youden index reached the maximum value. Diagnostic parameters such as sensitivity, specificity and predictive accuracy were also calculated for comparison. Finally, individual values were substituted into the equation to test the performance in predicting clinical outcomes. A total of 362 patients (218 males and 144 females) were enrolled in our study and 66 patients died. The average age was (48.3±19.3) years old. (1) For the predictive model only containing categorical covariants [including procalcitonin (PCT), lipopolysaccharide (LPS), infection, white blood cells count (WBC) and fever], increased PCT, increased WBC and fever were demonstrated to be independent risk factors for sepsis in the logistic equation. The AUC for the new combined predictive indicator was higher than that of any other indictor, including PCT, LPS, infection, WBC and fever (0.930 vs. 0.661, 0.503, 0.570, 0.837, 0.800). The optimal cut-off value for the new combined predictive indicator was 0.518. Using the new indicator to diagnose sepsis, the sensitivity, specificity and diagnostic accuracy rate were 78.00%, 93.36% and 87.47%, respectively. One patient was randomly selected, and the clinical data was substituted into the probability equation for prediction. The calculated value was 0.015, which was less than the cut-off value (0.518), indicating that the prognosis was non-sepsis at an accuracy of 87.47%. (2) For the predictive model only containing continuous covariants, the logistic model which combined acute physiology and chronic health evaluation II (APACHE II) score and sequential organ failure assessment (SOFA) score to predict in-hospital death events, both APACHE II score and SOFA score were independent risk factors for death. The AUC for the new predictive indicator was higher than that of APACHE II score and SOFA score (0.834 vs. 0.812, 0.813). The optimal cut-off value for the new combined predictive indicator in predicting in-hospital death events was 0.236, and the corresponding sensitivity, specificity and diagnostic accuracy for the combined predictive indicator were 73.12%, 76.51% and 75.70%, respectively. One patient was randomly selected, and the APACHE II score and SOFA score was substituted into the probability equation for prediction. The calculated value was 0.570, which was higher than the cut-off value (0.236), indicating that the death prognosis at an accuracy of 75.70%. The combined predictive indicator, which is formulated by logistic regression models, is superior to any single indicator in predicting sepsis or in-hospital death events.

Correlation between radio-induced lymphocyte apoptosis measurements obtained from two French centres.

PubMed

Mirjolet, C; Merlin, J L; Dalban, C; Maingon, P; Azria, D

2016-07-01

In the era of modern treatment delivery, increasing the dose delivered to the target to improve local control might be modulated by the patient's intrinsic radio-sensitivity. A predictive assay based on radio-induced lymphocyte apoptosis quantification highlighted the significant correlation between CD4 and CD8 T-lymphocyte apoptosis and grade 2 or 3 radiation-induced late toxicities. By conducting this assay at several technical platforms, the aim of this study was to demonstrate that radio-induced lymphocyte apoptosis values obtained from two different platforms were comparable. For 25 patients included in the PARATOXOR trial running in Dijon the radio-induced lymphocyte apoptosis results obtained from the laboratory of Montpellier (IRCM, Inserm U1194, France), considered as the reference (referred to as Lab 1), were compared with those from the laboratory located at the Institut de cancérologie de Lorraine (ICL, France), referred to as Lab 2. Different statistical methods were used to measure the agreement between the radio-induced lymphocyte apoptosis data from the two laboratories (quantitative data). The Bland-Altman plot was used to identify potential bias. All statistical tests demonstrated good agreement between radio-induced lymphocyte apoptosis values obtained from both sites and no major bias was identified. Since radio-induced lymphocyte apoptosis values, which predict tolerance to radiotherapy, could be assessed by two laboratories and showed a high level of robustness and consistency, we can suggest that this assay be extended to any laboratories that use the same technique. Copyright © 2016 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

Quantitative analysis applied to contrast medium extravasation by using the computed-tomography number within the region of interest

NASA Astrophysics Data System (ADS)

Lee, Jae-Seung; Im, In-Chul; Kim, Moon-Jib; Goo, Eun-Hoe; Kim, Sun-Ju; Kim, Kwang; Kwak, Byung-Joon

2014-02-01

The present study was carried out to present a method to analyze extravasation quantitatively by measuring the computed tomography (CT) number after determining the region of interest (ROI) in the CT images obtained from patients suspected of extravasation induced by contrast medium auto-injection. To achieve this, we divided the study subjects into a group of patients who incurred extravasation and a group of patients who underwent routine scans without incurring extravasation. The CT numbers at IV sites were obtained as reference values, and CT numbers at extravasation sites and hepatic portal veins, respectively, were obtained as relative values. Thereupon, the predicted time for extravasation ( T EP ) and the predicted ratio for extravasation ( R EP ) of an extravasation site were obtained and analyzed quantitatively. In the case of extravasation induced by a dual auto-injector, the values of the CT numbers were confirmed to be lower and the extravasation site to be enlarged when compared to the extravasation induced by a single autoinjector. This is because the physiological saline introduced after the injection of the contrast agent diluted the concentration of the extravasated contrast agent. Additionally, the T EP caused by the auto-injector was about 40 seconds, and we could perform a precise quantitative assessment of the site suspected of extravasation. In conclusion, the dual auto-injection method, despite its advantage of reducing the volume of contrast agent and improving the quality of images for patients with good vascular integrity, was judged to be likely to increase the risk of extravasation and aggravate outcomes for patients with poor vascular integrity by enlarging extravasation sites.

Optimization and kinetic modeling of esterification of the oil obtained from waste plum stones as a pretreatment step in biodiesel production.

PubMed

Kostić, Milan D; Veličković, Ana V; Joković, Nataša M; Stamenković, Olivera S; Veljković, Vlada B

2016-02-01

This study reports on the use of oil obtained from waste plum stones as a low-cost feedstock for biodiesel production. Because of high free fatty acid (FFA) level (15.8%), the oil was processed through the two-step process including esterification of FFA and methanolysis of the esterified oil catalyzed by H2SO4 and CaO, respectively. Esterification was optimized by response surface methodology combined with a central composite design. The second-order polynomial equation predicted the lowest acid value of 0.53mgKOH/g under the following optimal reaction conditions: the methanol:oil molar ratio of 8.5:1, the catalyst amount of 2% and the reaction temperature of 45°C. The predicted acid value agreed with the experimental acid value (0.47mgKOH/g). The kinetics of FFA esterification was described by the irreversible pseudo first-order reaction rate law. The apparent kinetic constant was correlated with the initial methanol and catalyst concentrations and reaction temperature. The activation energy of the esterification reaction slightly decreased from 13.23 to 11.55kJ/mol with increasing the catalyst concentration from 0.049 to 0.172mol/dm(3). In the second step, the esterified oil reacted with methanol (methanol:oil molar ratio of 9:1) in the presence of CaO (5% to the oil mass) at 60°C. The properties of the obtained biodiesel were within the EN 14214 standard limits. Hence, waste plum stones might be valuable raw material for obtaining fatty oil for the use as alternative feedstock in biodiesel production. Copyright © 2015 Elsevier Ltd. All rights reserved.

3D-QSAR and docking studies on 4-anilinoquinazoline and 4-anilinoquinoline epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors

NASA Astrophysics Data System (ADS)

Assefa, Haregewein; Kamath, Shantaram; Buolamwini, John K.

2003-08-01

The overexpression and/or mutation of the epidermal growth factor receptor (EGFR) tyrosine kinase has been observed in many human solid tumors, and is under intense investigation as a novel anticancer molecular target. Comparative 3D-QSAR analyses using different alignments were undertaken employing comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) for 122 anilinoquinazoline and 50 anilinoquinoline inhibitors of EGFR kinase. The SYBYL multifit alignment rule was applied to three different conformational templates, two obtained from a MacroModel Monte Carlo conformational search, and one from the bound conformation of erlotinib in complex with EGFR in the X-ray crystal structure. In addition, a flexible ligand docking alignment obtained with the GOLD docking program, and a novel flexible receptor-guided consensus dynamics alignment obtained with the DISCOVER program in the INSIGHTII modeling package were also investigated. 3D-QSAR models with q2 values up to 0.70 and r2 values up to 0.97 were obtained. Among the 4-anilinoquinazoline set, the q2 values were similar, but the ability of the different conformational models to predict the activities of an external test set varied considerably. In this regard, the model derived using the X-ray crystallographically determined bioactive conformation of erlotinib afforded the best predictive model. Electrostatic, hydrophobic and H-bond donor descriptors contributed the most to the QSAR models of the 4-anilinoquinazolines, whereas electrostatic, hydrophobic and H-bond acceptor descriptors contributed the most to the 4-anilinoquinoline QSAR, particularly the H-bond acceptor descriptor. A novel receptor-guided consensus dynamics alignment has also been introduced for 3D-QSAR studies. This new alignment method may incorporate to some extent ligand-receptor induced fit effects into 3D-QSAR models.

Validity of Predicting Left Ventricular End Systolic Pressure Changes Following An Acute Bout of Exercise

PubMed Central

Kappus, Rebecca M.; Ranadive, Sushant M.; Yan, Huimin; Lane, Abbi D.; Cook, Marc D.; Hall, Grenita; Harvey, I. Shevon; Wilund, Kenneth R.; Woods, Jeffrey A.; Fernhall, Bo

2012-01-01

Objective Left ventricular end systolic pressure (LV ESP) is important in assessing left ventricular performance. LV ESP is usually derived from prediction equations. It is unknown whether these equations are accurate at rest or following exercise in a young, healthy population. Design We compared measured LV ESP versus LV ESP values from the prediction equations at rest, 15 minutes and 30 minutes following peak aerobic exercise in 60 participants. Methods LV ESP was obtained by applanation tonometry at rest, 15 minutes post and 30 minutes post peak cycle exercise. Results Measured LV ESP was significantly lower (p<0.05) at all time points in comparison to the two calculated values. Measured LV ESP decreased significantly from rest at both the post15 and post30 time points (p<0.05) and changed differently in comparison to the calculated values (significant interaction; p<0.05). The two LV ESP equations were also significantly different from each other (p<0.05) and changed differently over time (significant interaction; p<0.05). Conclusions These data indicate that the two prediction equations commonly used did not accurately predict either resting or post exercise LV ESP in a young, healthy population. Thus, LV ESP needs to be individually determined in young healthy participants. Non-invasive measurement through applanation tonometry appears to allow for a more accurate determination of LV ESP. PMID:22721862

Validity of predicting left ventricular end systolic pressure changes following an acute bout of exercise.

PubMed

Kappus, Rebecca M; Ranadive, Sushant M; Yan, Huimin; Lane, Abbi D; Cook, Marc D; Hall, Grenita; Harvey, I Shevon; Wilund, Kenneth R; Woods, Jeffrey A; Fernhall, Bo

2013-01-01

Left ventricular end systolic pressure (LV ESP) is important in assessing left ventricular performance and is usually derived from prediction equations. It is unknown whether these equations are accurate at rest or following exercise in a young, healthy population. Measured LV ESP vs. LV ESP values from the prediction equations were compared at rest, 15 min and 30 min following peak aerobic exercise in 60 participants. LV ESP was obtained by applanation tonometry at rest, 15 min post and 30 min post peak cycle exercise. Measured LV ESP was significantly lower (p<0.05) at all time points in comparison to the two calculated values. Measured LV ESP decreased significantly from rest at both the post15 and post30 time points (p<0.05) and changed differently in comparison to the calculated values (significant interaction; p<0.05). The two LV ESP equations were also significantly different from each other (p<0.05) and changed differently over time (significant interaction; p<0.05). The two commonly used prediction equations did not accurately predict either resting or post exercise LV ESP in a young, healthy population. Thus, LV ESP needs to be individually determined in young, healthy participants. Non-invasive measurement through applanation tonometry appears to allow for a more accurate determination of LV ESP. Copyright © 2012 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Predictive Value of an Early Amplitude Integrated Electroencephalogram and Neurologic Examination

PubMed Central

Pappas, Athina; McDonald, Scott A.; Laptook, Abbot R.; Bara, Rebecca; Ehrenkranz, Richard A.; Tyson, Jon E.; Goldberg, Ronald; Donovan, Edward F.; Fanaroff, Avroy A.; Das, Abhik; Poole, W. Kenneth; Walsh, Michele; Higgins, Rosemary D.; Welsh, Cherie; Salhab, Walid; Carlo, Waldemar A.; Poindexter, Brenda; Stoll, Barbara J.; Guillet, Ronnie; Finer, Neil N.; Stevenson, David K.; Bauer, Charles R.

2011-01-01

OBJECTIVE: To examine the predictive validity of the amplitude integrated electroencephalogram (aEEG) and stage of encephalopathy among infants with hypoxic-ischemic encephalopathy (HIE) eligible for therapeutic whole-body hypothermia. DESIGN: Neonates were eligible for this prospective study if moderate or severe HIE occurred at <6 hours and an aEEG was obtained at <9 hours of age. The primary outcome was death or moderate/severe disability at 18 months. RESULTS: There were 108 infants (71 with moderate HIE and 37 with severe HIE) enrolled in the study. aEEG findings were categorized as normal, with continuous normal voltage (n = 12) or discontinuous normal voltage (n = 12), or abnormal, with burst suppression (n = 22), continuous low voltage (n = 26), or flat tracing (n = 36). At 18 months, 53 infants (49%) experienced death or disability. Severe HIE and an abnormal aEEG were related to the primary outcome with univariate analysis, whereas severe HIE alone was predictive of outcome with multivariate analysis. Addition of aEEG pattern to HIE stage did not add to the predictive value of the model; the area under the curve changed from 0.72 to 0.75 (P = .19). CONCLUSIONS: The aEEG background pattern did not significantly enhance the value of the stage of encephalopathy at study entry in predicting death and disability among infants with HIE. PMID:21669899

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 tailored approach to BRAF and MLH1 methylation testing in a universal screening program for Lynch syndrome.

PubMed

Adar, Tomer; Rodgers, Linda H; Shannon, Kristen M; Yoshida, Makoto; Ma, Tianle; Mattia, Anthony; Lauwers, Gregory Y; Iafrate, Anthony J; Chung, Daniel C

2017-03-01

To determine the correlation between BRAF genotype and MLH1 promoter methylation in a screening program for Lynch syndrome (LS), a universal screening program for LS was established in two medical centers. Tumors with abnormal MLH1 staining were evaluated for both BRAF V600E genotype and MLH1 promoter methylation. Tumors positive for both were considered sporadic, and genetic testing was recommended for all others. A total 1011 colorectal cancer cases were screened for Lynch syndrome, and 148 (14.6%) exhibited absent MLH1 immunostaining. Both BRAF and MLH1 methylation testing were completed in 126 cases. Concordant results (both positive or both negative) were obtained in 86 (68.3%) and 16 (12.7%) cases, respectively, with 81% concordance overall. The positive and negative predictive values for a BRAF mutation in predicting MLH1 promoter methylation were 98.9% and 41%, respectively, and the negative predictive value fell to 15% in patients ≥70 years old. Using BRAF genotyping as a sole test to evaluate cases with absent MLH1 staining would have increased referral rates for genetic testing by 2.3-fold compared with MLH1 methylation testing alone (31% vs 13.5%, respectively, P<0.01). However, a hybrid approach that reserves MLH1 methylation testing for BRAF wild-type cases only would significantly decrease the number of methylation assays performed and reduce the referral rate for genetic testing to 12.7%. A BRAF mutation has an excellent positive predictive value but poor negative predictive value in predicting MLH1 promoter methylation. A hybrid use of these tests may reduce the number of low-risk patients referred to genetic counseling and facilitate wider implementation of Lynch syndrome screening programs.

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.

The value of novel invasive hemodynamic parameters added to the TIMI risk score for short-term prognosis assessment in patients with ST segment elevation myocardial infarction.

PubMed

Tesak, Martin; Kala, Petr; Jarkovsky, Jiri; Poloczek, Martin; Bocek, Otakar; Jerabek, Petr; Kubková, Lenka; Manousek, Jan; Spinar, Jindrich; Mebazaa, Alexandre; Parenica, Jiri; Cohen-Solal, Alain

2016-07-01

We compared the prognostic capacity of conventional and novel invasive parameters derived from the slope of the preload recruitable stroke work relationship (PRSW) in STEMI patients and assessed their contribution to the TIMI risk score. Left ventricular end-diastolic pressure (EDP), ejection fraction (EF), pressure adjusted maximum rate of pressure change in the left ventricle (dP/dt/P), aortic systolic pressure to EDP ratio (SBP/EDP) and end-diastolic volume adjusted stroke work (EW), derived from the slope of the PRSW relationship, were obtained during the emergency cardiac catheterization in 523 STEMI patients. The predictive power of the analyzed parameters for 30-day and 1-year mortality was evaluated using C-statistics and reclassification analysis was adopted to assess the improvement in TIMI score. The highest area under the curve (AUC) values for 30-day mortality were observed for EW (0.872(95% confidence interval 0.801-0.943)), SBP/EDP (0.843(0.758-0.928)) and EF (0.833(0.735-0.931)); p<0.001 for all values. For 1-year mortality the best predictive value was found for EW (0.806(0.724-0.887) and EF (0.793(0.703-0.883)); p<0.001 for both. The addition of EDP, SBP/EDP ratio and EW to TIMI score significantly increased the AUC according to De Long's test. For 30-day mortality, increased discriminative power following addition to the TIMI score was observed for EW and SBP/EDP (Integrated Discrimination Improvement was 0.086(0.033-0.140), p=0.002 and 0.078(0.028-0.128), p=0.002, respectively). EW and SBP/EDP are prognostic markers with high predictive value for 30-day and 1-year mortality. Both parameters, easily obtained during emergency catheterization, improve the discriminatory capacity of the TIMI score for 30-day mortality. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Predicting outcome of Morris water maze test in vascular dementia mouse model with deep learning

PubMed Central

Mogi, Masaki; Iwanami, Jun; Min, Li-Juan; Bai, Hui-Yu; Shan, Bao-Shuai; Kukida, Masayoshi; Kan-no, Harumi; Ikeda, Shuntaro; Higaki, Jitsuo; Horiuchi, Masatsugu

2018-01-01

The Morris water maze test (MWM) is one of the most popular and established behavioral tests to evaluate rodents’ spatial learning ability. The conventional training period is around 5 days, but there is no clear evidence or guidelines about the appropriate duration. In many cases, the final outcome of the MWM seems predicable from previous data and their trend. So, we assumed that if we can predict the final result with high accuracy, the experimental period could be shortened and the burden on testers reduced. An artificial neural network (ANN) is a useful modeling method for datasets that enables us to obtain an accurate mathematical model. Therefore, we constructed an ANN system to estimate the final outcome in MWM from the previously obtained 4 days of data in both normal mice and vascular dementia model mice. Ten-week-old male C57B1/6 mice (wild type, WT) were subjected to bilateral common carotid artery stenosis (WT-BCAS) or sham-operation (WT-sham). At 6 weeks after surgery, we evaluated their cognitive function with MWM. Mean escape latency was significantly longer in WT-BCAS than in WT-sham. All data were collected and used as training data and test data for the ANN system. We defined a multiple layer perceptron (MLP) as a prediction model using an open source framework for deep learning, Chainer. After a certain number of updates, we compared the predicted values and actual measured values with test data. A significant correlation coefficient was derived form the updated ANN model in both WT-sham and WT-BCAS. Next, we analyzed the predictive capability of human testers with the same datasets. There was no significant difference in the prediction accuracy between human testers and ANN models in both WT-sham and WT-BCAS. In conclusion, deep learning method with ANN could predict the final outcome in MWM from 4 days of data with high predictive accuracy in a vascular dementia model. PMID:29415035

Predicting outcome of Morris water maze test in vascular dementia mouse model with deep learning.

PubMed

Higaki, Akinori; Mogi, Masaki; Iwanami, Jun; Min, Li-Juan; Bai, Hui-Yu; Shan, Bao-Shuai; Kukida, Masayoshi; Kan-No, Harumi; Ikeda, Shuntaro; Higaki, Jitsuo; Horiuchi, Masatsugu

2018-01-01

The Morris water maze test (MWM) is one of the most popular and established behavioral tests to evaluate rodents' spatial learning ability. The conventional training period is around 5 days, but there is no clear evidence or guidelines about the appropriate duration. In many cases, the final outcome of the MWM seems predicable from previous data and their trend. So, we assumed that if we can predict the final result with high accuracy, the experimental period could be shortened and the burden on testers reduced. An artificial neural network (ANN) is a useful modeling method for datasets that enables us to obtain an accurate mathematical model. Therefore, we constructed an ANN system to estimate the final outcome in MWM from the previously obtained 4 days of data in both normal mice and vascular dementia model mice. Ten-week-old male C57B1/6 mice (wild type, WT) were subjected to bilateral common carotid artery stenosis (WT-BCAS) or sham-operation (WT-sham). At 6 weeks after surgery, we evaluated their cognitive function with MWM. Mean escape latency was significantly longer in WT-BCAS than in WT-sham. All data were collected and used as training data and test data for the ANN system. We defined a multiple layer perceptron (MLP) as a prediction model using an open source framework for deep learning, Chainer. After a certain number of updates, we compared the predicted values and actual measured values with test data. A significant correlation coefficient was derived form the updated ANN model in both WT-sham and WT-BCAS. Next, we analyzed the predictive capability of human testers with the same datasets. There was no significant difference in the prediction accuracy between human testers and ANN models in both WT-sham and WT-BCAS. In conclusion, deep learning method with ANN could predict the final outcome in MWM from 4 days of data with high predictive accuracy in a vascular dementia model.

A Comparison of Theory and Experiment for High-speed Free-molecule Flow

NASA Technical Reports Server (NTRS)

Stalder, Jackson R; Goodwin, Glen; Creager, Marcus O

1951-01-01

A comparison is made of free-molecule-flow theory with the results of wind-tunnel tests performed to determine the drag and temperature-rise characteristics of a transverse circular cylinder. The measured values of the cylinder center-point temperature confirmed the salient point of the heat-transfer analysis which was the prediction that an insulated cylinder would attain a temperature higher than the stagnation temperature of the stream. Good agreement was obtained between the theoretical and the experimental values for the drag coefficient.

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.

A hybrid approach to predict the relationship between tablet tensile strength and compaction pressure using analytical powder compression.

PubMed

Persson, Ann-Sofie; Alderborn, Göran

2018-04-01

The objective was to present a hybrid approach to predict the strength-pressure relationship (SPR) of tablets using common compression parameters and a single measurement of tablet tensile strength. Experimental SPR were derived for six pharmaceutical powders with brittle and ductile properties and compared to predicted SPR based on a three-stage approach. The prediction was based on the Kawakita b -1 parameter and the in-die Heckel yield stress, an estimate of maximal tensile strength, and a parameter proportionality factor α. Three values of α were used to investigate the influence of the parameter on the SPR. The experimental SPR could satisfactorily be described by the three stage model, however for sodium bicarbonate the tensile strength plateau could not be observed experimentally. The shape of the predicted SPR was to a minor extent influenced by the Kawakita b -1 but the width of the linear region was highly influenced by α. An increased α increased the width of the linear region and thus also the maximal predicted tablet tensile strength. Furthermore, the correspondence between experimental and predicted SPR was influenced by the α value and satisfactory predictions were in general obtained for α = 4.1 indicating the predictive potential of the hybrid approach. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Kinetic measurement of 2-aminopurine X cytosine and 2-aminopurine X thymine base pairs as a test of DNA polymerase fidelity mechanisms.

PubMed Central

Watanabe, S M; Goodman, M F

1982-01-01

Enzyme kinetic measurements are presented showing that Km rather than maximum velocity (Vmax) discrimination governs the frequency of forming 2-aminopurine X cytosine base mispairs by DNA polymerase alpha. An in vitro system is used in which incorporation of dTMP or dCMP occurs opposite a template 2-aminopurine, and values for Km and Vmax are obtained. Results from a previous study in which dTTP and dCTP were competing simultaneously for insertion opposite 2-aminopurine indicated that dTMP is inserted 22 times more frequently than dCMP. We now report that the ratio of Km values KCm/KTm = 25 +/- 6, which agrees quantitatively with the dTMP/dCMP incorporation ratio obtained previously. We also report that VCmax is indistinguishable from VTmax. These Km and Vmax data are consistent with predictions from a model, the Km discrimination model, in which replication fidelity is determined by free energy differences between matched and mismatched base pairs. Central to this model is the prediction that the ratio of Km values for insertion of correct and incorrect nucleotides specifies the insertion fidelity, and the maximum velocities of insertion are the same for both nucleotides. PMID:6959128

Supercritical fluid extraction of phenolic compounds and antioxidants from grape (Vitis labrusca B.) seeds.

PubMed

Ghafoor, Kashif; Al-Juhaimi, Fahad Y; Choi, Yong Hee

2012-12-01

Supercritical fluid extraction (SFE) technique was applied and optimized for temperature, CO₂ pressure and ethanol (modifier) concentration using orthogonal array design and response surface methodology for the extract yield, total phenols and antioxidants from grape (Vitis labrusca B.) seeds. Effects of extraction temperature and pressure were found to be significant for all these response variables in SFE process. Optimum SFE conditions (44 ~ 46 °C temperature and 153 ~ 161 bar CO₂ pressure) along with ethanol (<7 %) as modifier, for the maximum predicted values of extract yield (12.09 %), total phenols (2.41 mg GAE/ml) and antioxidants (7.08 mg AAE/ml), were used to obtain extracts from grape seeds. The predicted values matched well with the experimental values (12.32 % extract yield, 2.45 mg GAE/ml total phenols and 7.08 mg AAE/ml antioxidants) obtained at optimum SFE conditions. The antiradical assay showed that SFE extracts of grape seeds can scavenge more than 85 % of 1, 1-diphenyl-2-picrylhydrazyl (DPPH) radicals. The grape seeds extracts were also analyzed for hydroxybenzoic acids which included gallic acid (1.21 ~ 3.84 μg/ml), protocatechuic acid (3.57 ~ 11.78 μg/ml) and p-hydroxybenzoic acid (206.72 ~ 688.18 μg/ml).

Spectral multivariate calibration without laboratory prepared or determined reference analyte values.

PubMed

Ottaway, Josh; Farrell, Jeremy A; Kalivas, John H

2013-02-05

An essential part to calibration is establishing the analyte calibration reference samples. These samples must characterize the sample matrix and measurement conditions (chemical, physical, instrumental, and environmental) of any sample to be predicted. Calibration usually requires measuring spectra for numerous reference samples in addition to determining the corresponding analyte reference values. Both tasks are typically time-consuming and costly. This paper reports on a method named pure component Tikhonov regularization (PCTR) that does not require laboratory prepared or determined reference values. Instead, an analyte pure component spectrum is used in conjunction with nonanalyte spectra for calibration. Nonanalyte spectra can be from different sources including pure component interference samples, blanks, and constant analyte samples. The approach is also applicable to calibration maintenance when the analyte pure component spectrum is measured in one set of conditions and nonanalyte spectra are measured in new conditions. The PCTR method balances the trade-offs between calibration model shrinkage and the degree of orthogonality to the nonanalyte content (model direction) in order to obtain accurate predictions. Using visible and near-infrared (NIR) spectral data sets, the PCTR results are comparable to those obtained using ridge regression (RR) with reference calibration sets. The flexibility of PCTR also allows including reference samples if such samples are available.

Ambulatory versus home versus clinic blood pressure: the association with subclinical cerebrovascular diseases: the Ohasama Study.

PubMed

Hara, Azusa; Tanaka, Kazushi; Ohkubo, Takayoshi; Kondo, Takeo; Kikuya, Masahiro; Metoki, Hirohito; Hashimoto, Takanao; Satoh, Michihiro; Inoue, Ryusuke; Asayama, Kei; Obara, Taku; Hirose, Takuo; Izumi, Shin-Ichi; Satoh, Hiroshi; Imai, Yutaka

2012-01-01

The usefulness of ambulatory, home, and casual/clinic blood pressure measurements to predict subclinical cerebrovascular diseases (silent cerebrovascular lesions and carotid atherosclerosis) was compared in a general population. Data on ambulatory, home, and casual/clinic blood pressures and brain MRI to detect silent cerebrovascular lesions were obtained in 1007 subjects aged ≥55 years in a general population of Ohasama, Japan. Of the 1007 subjects, 583 underwent evaluation of the extent of carotid atherosclerosis. Twenty-four-hour, daytime, and nighttime ambulatory and home blood pressure levels were closely associated with the risk of silent cerebrovascular lesions and carotid atherosclerosis (all P<0.05). When home and one of the ambulatory blood pressure values were simultaneously included in the same regression model, each of the ambulatory blood pressure values remained a significant predictor of silent cerebrovascular lesions, whereas home blood pressure lost its predictive value. Of the ambulatory blood pressure values, nighttime blood pressure was the strongest predictor of silent cerebrovascular lesions. The home blood pressure value was more closely associated with the risk of carotid atherosclerosis than any of the ambulatory blood pressure values when home and one of the ambulatory blood pressure values were simultaneously included in the same regression model. The casual/clinic blood pressure value had no significant association with the risk of subclinical cerebrovascular diseases. Although the clinical indications for ambulatory blood pressure monitoring and home blood pressure measurements may overlap, the clinical significance of each method for predicting target organ damage may differ for different target organs.

Gastric Cancer-Specific Protein Profile Identified Using Endoscopic Biopsy Samples via MALDI Mass Spectrometry

PubMed Central

Kim, Hark Kyun; Reyzer, Michelle L.; Choi, Il Ju; Kim, Chan Gyoo; Kim, Hee Sung; Oshima, Akira; Chertov, Oleg; Colantonio, Simona; Fisher, Robert J.; Allen, Jamie L.; Caprioli, Richard M.; Green, Jeffrey E.

2012-01-01

To date, proteomic analyses on gastrointestinal cancer tissue samples have been performed using surgical specimens only, which are obtained after a diagnosis is made. To determine if a proteomic signature obtained from endoscopic biopsy samples could be found to assist with diagnosis, frozen endoscopic biopsy samples collected from 63 gastric cancer patients and 43 healthy volunteers were analyzed using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry. A statistical classification model was developed to distinguish tumor from normal tissues using half the samples and validated with the other half. A protein profile was discovered consisting of 73 signals that could classify 32 cancer and 22 normal samples in the validation set with high predictive values (positive and negative predictive values for cancer, 96.8% and 91.3%; sensitivity, 93.8%; specificity, 95.5%). Signals overexpressed in tumors were identified as α-defensin-1, α-defensin-2, calgranulin A, and calgranulin B. A protein profile was also found to distinguish pathologic stage Ia (pT1N0M0) samples (n = 10) from more advanced stage (Ib or higher) tumors (n = 48). Thus, protein profiles obtained from endoscopic biopsy samples may be useful in assisting with the diagnosis of gastric cancer and, possibly, in identifying early stage disease. PMID:20557134

Density-dependent host choice by disease vectors: epidemiological implications of the ideal free distribution.

PubMed

Basáñez, María-Gloria; Razali, Karina; Renz, Alfons; Kelly, David

2007-03-01

The proportion of vector blood meals taken on humans (the human blood index, h) appears as a squared term in classical expressions of the basic reproduction ratio (R(0)) for vector-borne infections. Consequently, R(0) varies non-linearly with h. Estimates of h, however, constitute mere snapshots of a parameter that is predicted, from evolutionary theory, to vary with vector and host abundance. We test this prediction using a population dynamics model of river blindness assuming that, before initiation of vector control or chemotherapy, recorded measures of vector density and human infection accurately represent endemic equilibrium. We obtain values of h that satisfy the condition that the effective reproduction ratio (R(e)) must equal 1 at equilibrium. Values of h thus obtained decrease with vector density, decrease with the vector:human ratio and make R(0) respond non-linearly rather than increase linearly with vector density. We conclude that if vectors are less able to obtain human blood meals as their density increases, antivectorial measures may not lead to proportional reductions in R(0) until very low vector levels are achieved. Density dependence in the contact rate of infectious diseases transmitted by insects may be an important non-linear process with implications for their epidemiology and control.

REVIEWS OF TOPICAL PROBLEMS: Cosmology, primordial black holes, and supermassive particles

NASA Astrophysics Data System (ADS)

Polnarev, A. G.; Khlopov, M. Yu

1985-03-01

Analysis of astrophysical restrictions on the spectrum of primordial black holes (PBH) makes it possible to obtain indirect information about the physical conditions in the very early universe. These restrictions are compared with the probability of PBH production in early dust stages as predicted on the basis of modern models of quantum field theory. As a result of such comparison, restrictions are obtained on the parameters of various models corresponding to different values of the parameters of the spectrum of initial small-scale inhomogeneities.

Evaluation of axial pile bearing capacity based on pile driving analyzer (PDA) test using Neural Network

NASA Astrophysics Data System (ADS)

Maizir, H.; Suryanita, R.

2018-01-01

A few decades, many methods have been developed to predict and evaluate the bearing capacity of driven piles. The problem of the predicting and assessing the bearing capacity of the pile is very complicated and not yet established, different soil testing and evaluation produce a widely different solution. However, the most important thing is to determine methods used to predict and evaluate the bearing capacity of the pile to the required degree of accuracy and consistency value. Accurate prediction and evaluation of axial bearing capacity depend on some variables, such as the type of soil, diameter, and length of pile, etc. The aims of the study of Artificial Neural Networks (ANNs) are utilized to obtain more accurate and consistent axial bearing capacity of a driven pile. ANNs can be described as mapping an input to the target output data. The method using the ANN model developed to predict and evaluate the axial bearing capacity of the pile based on the pile driving analyzer (PDA) test data for more than 200 selected data. The results of the predictions obtained by the ANN model and the PDA test were then compared. This research as the neural network models give a right prediction and evaluation of the axial bearing capacity of piles using neural networks.

Status of linear boundary-layer stability and the e to the nth method, with emphasis on swept-wing applications

NASA Technical Reports Server (NTRS)

Hefner, J. N.; Bushnell, D. M.

1980-01-01

The-state-of-the-art for the application of linear stability theory and the e to the nth power method for transition prediction and laminar flow control design are summarized, with analyses of previously published low disturbance, swept wing data presented. For any set of transition data with similar stream distrubance levels and spectra, the e to the nth power method for estimating the beginning of transition works reasonably well; however, the value of n can vary significantly, depending upon variations in disturbance field or receptivity. Where disturbance levels are high, the values of n are appreciably below the usual average value of 9 to 10 obtained for relatively low disturbance levels. It is recommended that the design of laminar flow control systems be based on conservative estimates of n and that, in considering the values of n obtained from different analytical approaches or investigations, the designer explore the various assumptions which entered into the analyses.

Paleomagnetic secular variation at the Azores during the last 3 ka

NASA Astrophysics Data System (ADS)

di Chiara, Anita; Speranza, Fabio; Porreca, Massimiliano

2012-07-01

We report on 33 new paleomagnetic directions obtained from 16 lava flows emplaced in the last 3 ka on São Miguel, the largest island of the Azores. The data provide 27 well-dated directions from historical or 14C dated flows which, together with 6 directions previously gathered from the same flows by Johnson et al. (1998), yield the first paleomagnetic directional record of the last 3 ka from the Atlantic Ocean. Within-flow directions are consistent, suggesting that inclination swings from 60° to 25° and declination changes between -10° to 20° reflect variations in the geomagnetic field over the last 3 ka. To a first approximation, the declination record is consistent with predictions from CALS3k.4 and gufm1 global field models. Conversely, inclination values are lower than model predictions at two different ages: 1) four sites from the 1652 AD flow yield I = 48° instead of I = 63° predicted by gufm1; 2) data from several flows nicely mimic the inclination minimum of 800-1400 AD, but inclination values are lower by ˜10° than CALS3k.4 model predictions. By interpolating a cubic spline fit on declination / inclination versus age data, we tentatively infer the directional evolution of the geomagnetic field at the Azores from 1000 BC to 1600 AD. The obtained curve shows three tracks in virtual overlap during the 1000-800 BC, 800-500 BC, and 400-700 AD time spans.

[Design and validation of an instrument to assess families at risk for health problems].

PubMed

Puschel, Klaus; Repetto, Paula; Solar, María Olga; Soto, Gabriela; González, Karla

2012-04-01

There is a paucity of screening instruments with a high clinical predictive value to identify families at risk and therefore, develop focused interventions in primary care. To develop an easy to apply screening instrument with a high clinical predictive value to identify families with a higher health vulnerability. In the first stage of the study an instrument with a high content validity was designed through a review of existent instruments, qualitative interviews with families and expert opinions following a Delphi approach of three rounds. In the second stage, concurrent validity was tested through a comparative analysis between the pilot instrument and a family clinical interview conducted to 300 families randomly selected from a population registered at a primary care clinic in Santiago. The sampling was blocked based on the presence of diabetes, depression, child asthma, behavioral disorders, presence of an older person or the lack of previous conditions among family members. The third stage, was directed to test the clinical predictive validity of the instrument by comparing the baseline vulnerability obtained by the instrument and the change in clinical status and health related quality of life perceptions of the family members after nine months of follow-up. The final SALUFAM instrument included 13 items and had a high internal consistency (Cronbach's alpha: 0.821), high test re-test reproducibility (Pearson correlation: 0.84) and a high clinical predictive value for clinical deterioration (Odds ratio: 1.826; 95% confidence intervals: 1.101-3.029). SALUFAM instrument is applicable, replicable, has a high content validity, concurrent validity and clinical predictive value.

Dopamine reward prediction error responses reflect marginal utility.

PubMed

Stauffer, William R; Lak, Armin; Schultz, Wolfram

2014-11-03

Optimal choices require an accurate neuronal representation of economic value. In economics, utility functions are mathematical representations of subjective value that can be constructed from choices under risk. Utility usually exhibits a nonlinear relationship to physical reward value that corresponds to risk attitudes and reflects the increasing or decreasing marginal utility obtained with each additional unit of reward. Accordingly, neuronal reward responses coding utility should robustly reflect this nonlinearity. In two monkeys, we measured utility as a function of physical reward value from meaningful choices under risk (that adhered to first- and second-order stochastic dominance). The resulting nonlinear utility functions predicted the certainty equivalents for new gambles, indicating that the functions' shapes were meaningful. The monkeys were risk seeking (convex utility function) for low reward and risk avoiding (concave utility function) with higher amounts. Critically, the dopamine prediction error responses at the time of reward itself reflected the nonlinear utility functions measured at the time of choices. In particular, the reward response magnitude depended on the first derivative of the utility function and thus reflected the marginal utility. Furthermore, dopamine responses recorded outside of the task reflected the marginal utility of unpredicted reward. Accordingly, these responses were sufficient to train reinforcement learning models to predict the behaviorally defined expected utility of gambles. These data suggest a neuronal manifestation of marginal utility in dopamine neurons and indicate a common neuronal basis for fundamental explanatory constructs in animal learning theory (prediction error) and economic decision theory (marginal utility). Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

WASP (Write a Scientific Paper) using Excel - 11: Test characteristics.

PubMed

Grech, Victor

2018-07-01

The calculation of various test characteristics may be required as part of a data analysis exercise. This paper explains how to set up these calculations in Microsoft Excel in order to obtain sensitivity, specificity, positive and negative predictive values, diagnostic accuracy and prevalence. Copyright © 2018 Elsevier B.V. All rights reserved.

Forecasting Enrollments with Fuzzy Time Series.

ERIC Educational Resources Information Center

Song, Qiang; Chissom, Brad S.

The concept of fuzzy time series is introduced and used to forecast the enrollment of a university. Fuzzy time series, an aspect of fuzzy set theory, forecasts enrollment using a first-order time-invariant model. To evaluate the model, the conventional linear regression technique is applied and the predicted values obtained are compared to the…

Age-Dependent and Age-Independent Measures of Locus of Control.

ERIC Educational Resources Information Center

Sherman, Lawrence W.; Hofmann, Richard

Using a longitudinal data set obtained from 169 pre-adolescent children between the ages of 8 and 13 years, this study statistically divided locus of control into two independent components. The first component was noted as "age-dependent" (AD) and was determined by predicted values generated by regressing children's ages onto their…

Event generator tunes obtained from underlying event and multiparton scattering measurements

DOE PAGES

Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; ...

2016-03-17

Here, new sets of parameters (“tunes”) for the underlying-event (UE) modelling of the pythia8, pythia6 and herwig++ Monte Carlo event generators are constructed using different parton distribution functions. Combined fits to CMS UE proton–proton (more » $$\\mathrm {p}\\mathrm {p}$$ ) data at $$\\sqrt{s} = 7\\,\\text {TeV} $$ and to UE proton–antiproton ( $$\\mathrm {p}\\overline{\\mathrm{p}} $$ ) data from the CDF experiment at lower $$\\sqrt{s}$$ , are used to study the UE models and constrain their parameters, providing thereby improved predictions for proton–proton collisions at 13 $$\\,\\text {TeV}$$ . In addition, it is investigated whether the values of the parameters obtained from fits to UE observables are consistent with the values determined from fitting observables sensitive to double-parton scattering processes. Finally, comparisons are presented of the UE tunes to “minimum bias” (MB) events, multijet, and Drell–Yan ( $$ \\mathrm{q} \\overline{\\mathrm{q}} \\rightarrow \\mathrm{Z}/ \\gamma ^* \\rightarrow $$ lepton-antilepton+jets) observables at 7 and 8 $$\\,\\text {TeV}$$ , as well as predictions for MB and UE observables at 13 $$\\,\\text {TeV}$$ .« less

First-and Second-Order Displacement Transfer Functions for Structural Shape Calculations Using Analytically Predicted Surface Strains

NASA Technical Reports Server (NTRS)

Ko, William L.; Fleischer, Van Tran

2012-01-01

New first- and second-order displacement transfer functions have been developed for deformed shape calculations of nonuniform cross-sectional beam structures such as aircraft wings. The displacement transfer functions are expressed explicitly in terms of beam geometrical parameters and surface strains (uniaxial bending strains) obtained at equally spaced strain stations along the surface of the beam structure. By inputting the measured or analytically calculated surface strains into the displacement transfer functions, one could calculate local slopes, deflections, and cross-sectional twist angles of the nonuniform beam structure for mapping the overall structural deformed shapes for visual display. The accuracy of deformed shape calculations by the first- and second-order displacement transfer functions are determined by comparing these values to the analytically predicted values obtained from finite element analyses. This comparison shows that the new displacement transfer functions could quite accurately calculate the deformed shapes of tapered cantilever tubular beams with different tapered angles. The accuracy of the present displacement transfer functions also are compared to those of the previously developed displacement transfer functions.

Estimation and optimization of thermal performance of evacuated tube solar collector system

NASA Astrophysics Data System (ADS)

Dikmen, Erkan; Ayaz, Mahir; Ezen, H. Hüseyin; Küçüksille, Ecir U.; Şahin, Arzu Şencan

2014-05-01

In this study, artificial neural networks (ANNs) and adaptive neuro-fuzzy (ANFIS) in order to predict the thermal performance of evacuated tube solar collector system have been used. The experimental data for the training and testing of the networks were used. The results of ANN are compared with ANFIS in which the same data sets are used. The R2-value for the thermal performance values of collector is 0.811914 which can be considered as satisfactory. The results obtained when unknown data were presented to the networks are satisfactory and indicate that the proposed method can successfully be used for the prediction of the thermal performance of evacuated tube solar collectors. In addition, new formulations obtained from ANN are presented for the calculation of the thermal performance. The advantages of this approaches compared to the conventional methods are speed, simplicity, and the capacity of the network to learn from examples. In addition, genetic algorithm (GA) was used to maximize the thermal performance of the system. The optimum working conditions of the system were determined by the GA.

Mortality of atomic bomb survivors predicted from laboratory animals

NASA Technical Reports Server (NTRS)

Carnes, Bruce A.; Grahn, Douglas; Hoel, David

2003-01-01

Exposure, pathology and mortality data for mice, dogs and humans were examined to determine whether accurate interspecies predictions of radiation-induced mortality could be achieved. The analyses revealed that (1) days of life lost per unit dose can be estimated for a species even without information on radiation effects in that species, and (2) accurate predictions of age-specific radiation-induced mortality in beagles and the atomic bomb survivors can be obtained from a dose-response model for comparably exposed mice. These findings illustrate the value of comparative mortality analyses and the relevance of animal data to the study of human health effects.

Using the Real-Ear-to-Coupler Difference within the American Academy of Audiology Pediatric Amplification Guideline: Protocols for Applying and Predicting Earmold RECDs.

PubMed

Moodie, Sheila; Pietrobon, Jonathan; Rall, Eileen; Lindley, George; Eiten, Leisha; Gordey, Dave; Davidson, Lisa; Moodie, K Shane; Bagatto, Marlene; Haluschak, Meredith Magathan; Folkeard, Paula; Scollie, Susan

2016-03-01

Real-ear-to-coupler difference (RECD) measurements are used for the purposes of estimating degree and configuration of hearing loss (in dB SPL ear canal) and predicting hearing aid output from coupler-based measures. Accurate measurements of hearing threshold, derivation of hearing aid fitting targets, and predictions of hearing aid output in the ear canal assume consistent matching of RECD coupling procedure (i.e., foam tip or earmold) with that used during assessment and in verification of the hearing aid fitting. When there is a mismatch between these coupling procedures, errors are introduced. The goal of this study was to quantify the systematic difference in measured RECD values obtained when using a foam tip versus an earmold with various tube lengths. Assuming that systematic errors exist, the second goal was to investigate the use of a foam tip to earmold correction for the purposes of improving fitting accuracy when mismatched RECD coupling conditions occur (e.g., foam tip at assessment, earmold at verification). Eighteen adults and 17 children (age range: 3-127 mo) participated in this study. Data were obtained using simulated ears of various volumes and earmold tubing lengths and from patients using their own earmolds. Derived RECD values based on simulated ear measurements were compared with RECD values obtained for adult and pediatric ears for foam tip and earmold coupling. Results indicate that differences between foam tip and earmold RECDs are consistent across test ears for adults and children which support the development of a correction between foam tip and earmold couplings for RECDs that can be applied across individuals. The foam tip to earmold correction values developed in this study can be used to provide improved estimations of earmold RECDs. This may support better accuracy in acoustic transforms related to transforming thresholds and/or hearing aid coupler responses to ear canal sound pressure level for the purposes of fitting behind-the-ear hearing aids. American Academy of Audiology.

Predictive value of high sensitivity CRP in patients with diastolic heart failure.

PubMed

Michowitz, Yoav; Arbel, Yaron; Wexler, Dov; Sheps, David; Rogowski, Ori; Shapira, Itzhak; Berliner, Shlomo; Keren, Gad; George, Jacob; Roth, Arie

2008-04-25

C-reactive protein (CRP) has been tested in patients with systolic heart failure (HF) and mixed results have been obtained with regards to its potential predictive value. However, the role of C-reactive protein (CRP) in patients with diastolic HF is not established. We studied the predictive role of high sensitivity CRP (hsCRP) in patients with diastolic HF. HsCRP levels were measured in a cohort of CHF outpatients, 77 patients with diastolic HF and 217 patients with systolic HF. Concentrations were compared to a large cohort of healthy population (n=7701) and associated with the HF admissions and mortality of the patients. Levels of hsCRP did not differ between patients with systolic and diastolic HF and were significantly elevated compared to the cohort of healthy subjects even after adjustment to various clinical parameters (p<0.0001). In patients with diastolic HF, hsCRP levels associated with New York Heart Association functional class (NYHA-FC) (r=0.31 p=0.01). On univariate Cox regression model hsCRP levels independently predicted hospitalizations in patients with systolic but not diastolic HF (p=0.047). HsCRP concentrations are elevated in patients with diastolic HF and correlate with disease severity; their prognostic value in this patient population should be further investigated.

Modeling and predicting the biofilm formation of Salmonella Virchow with respect to temperature and pH.

PubMed

Ariafar, M Nima; Buzrul, Sencer; Akçelik, Nefise

2016-03-01

Biofilm formation of Salmonella Virchow was monitored with respect to time at three different temperature (20, 25 and 27.5 °C) and pH (5.2, 5.9 and 6.6) values. As the temperature increased at a constant pH level, biofilm formation decreased while as the pH level increased at a constant temperature, biofilm formation increased. Modified Gompertz equation with high adjusted determination coefficient (Radj(2)) and low mean square error (MSE) values produced reasonable fits for the biofilm formation under all conditions. Parameters of the modified Gompertz equation could be described in terms of temperature and pH by use of a second order polynomial function. In general, as temperature increased maximum biofilm quantity, maximum biofilm formation rate and time of acceleration of biofilm formation decreased; whereas, as pH increased; maximum biofilm quantity, maximum biofilm formation rate and time of acceleration of biofilm formation increased. Two temperature (23 and 26 °C) and pH (5.3 and 6.3) values were used up to 24 h to predict the biofilm formation of S. Virchow. Although the predictions did not perfectly match with the data, reasonable estimates were obtained. In principle, modeling and predicting the biofilm formation of different microorganisms on different surfaces under various conditions could be possible.

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

Prediction of Response to Sorafenib in Hepatocellular Carcinoma: A Putative Marker Panel by Multiple Reaction Monitoring-Mass Spectrometry (MRM-MS).

PubMed

Kim, Hyunsoo; Yu, Su Jong; Yeo, Injun; Cho, Young Youn; Lee, Dong Hyeon; Cho, Yuri; Cho, Eun Ju; Lee, Jeong-Hoon; Kim, Yoon Jun; Lee, Sungyoung; Jun, Jongsoo; Park, Taesung; Yoon, Jung-Hwan; Kim, Youngsoo

2017-07-01

Sorafenib is the only standard treatment for unresectable hepatocellular carcinoma (HCC), but it provides modest survival benefits over placebo, necessitating predictive biomarkers of the response to sorafenib. Serum samples were obtained from 115 consecutive patients with HCC before sorafenib treatment and analyzed by multiple reaction monitoring-mass spectrometry (MRM-MS) and ELISA to quantify candidate biomarkers. We verified a triple-marker panel to be predictive of the response to sorafenib by MRM-MS, comprising CD5 antigen-like (CD5L), immunoglobulin J (IGJ), and galectin-3-binding protein (LGALS3BP), in HCC patients. This panel was a significant predictor (AUROC > 0.950) of the response to sorafenib treatment, having the best cut-off value (0.4) by multivariate analysis. In the training set, patients who exceeded this cut-off value had significantly better overall survival (median, 21.4 months) than those with lower values (median, 8.6 months; p = 0.001). Further, a value that was lower than this cutoff was an independent predictor of poor overall survival [hazard ratio (HR), 2.728; 95% confidence interval (CI), 1.312-5.672; p = 0.007] and remained an independent predictive factor of rapid progression (HR, 2.631; 95% CI, 1.448-4.780; p = 0.002). When applied to the independent validation set, levels of the cut-off value for triple-marker panel maintained their prognostic value for poor clinical outcomes. On the contrast, the triple-marker panel was not a prognostic factor for patients who were treated with transarterial chemoembolization (TACE). The discriminatory signature of a triple-marker panel provides new insights into targeted proteomic biomarkers for individualized sorafenib therapy. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Serum Protein Electrophoresis in the Evaluation of Lytic Bone Lesions

PubMed Central

Nystrom, Lukas M.; Buckwalter, Joseph A.; Syrbu, Sergei; Miller, Benjamin J.

2013-01-01

Serum protein electrophoresis (SPEP) is often obtained at the initial evaluation of a radiolucent bone lesion of unknown etiology. The results are considered convincing evidence of the presence or absence of a plasma cell neoplasm. The sensitivity and specificity of the SPEP have not been reported in this clinical scenario. Our purpose is to assess the diagnostic value of the SPEP in the initial work-up of the radiolucent bone lesion. We identified 182 patients undergoing evaluation of a radiolucent bone lesion that included tissue biopsy and an SPEP value. We then calculated the sen-sitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of SPEP as a diagnostic test for a plasma cell neo-plasm in this clinical scenario. Forty-six of 182 (25.3%) patients in our series were diagnosed with a plasma cell neo-plasm by histopathologic analysis. The sensitivity of SPEP was 71% and the specificity was 83%. PPV was 47% and NPV was 94%. When analyzing only those presenting with multiple lesions, the percentage of patients diag-nosed with multiple myeloma increased to 44.7% (34 of 76 patients). The SPEP, however, did not have a substantially increased diagnostic accuracy with sensitivity of 71%, specificity 79%, PPV 40% and NPV 93%. SPEP lacks sensitivity and positive predictive value to provide a definitive diagnosis of myeloma in radiolucent bone lesions, but has a high negative predictive value which may make it useful in ruling out the disease. We recommend that this test either be performed in conjunction with urine electrophoresis, immunofixation electro-phoresis and free light chain assay, or after biopsy confirming the diagnosis of myeloma. PMID:24027470

Hydrodynamic chromatography of polystyrene microparticles in micropillar array columns.

PubMed

Op de Beeck, Jeff; De Malsche, Wim; Vangelooven, Joris; Gardeniers, Han; Desmet, Gert

2010-09-24

We report on the possibility to perform HDC in micropillar array columns and the potential advantages of such a system. The HDC performance of a pillar array column with pillar diameter = 5 microm and an interpillar distance of 2.5 microm has been characterized using both a low MW tracer (FITC) and differently sized polystyrene bead samples (100, 200 and 500 nm). The reduced plate height curves that were obtained for the different investigated markers all overlapped very well, and attained a minimum value of about h(min)=0.3 (reduction based on the pillar diameter), corresponding to 1.6 microm in absolute value and giving good prospects for high efficiency separations. The obtained reduced retention time values were in fair agreement with that predicted by the Di Marzio and Guttman model for a flow between flat plates, using the minimal interpillar distance as characteristic interplate distance. Copyright 2010 Elsevier B.V. All rights reserved.

Sum-over-states density functional perturbation theory: Prediction of reliable 13C, 15N, and 17O nuclear magnetic resonance chemical shifts

NASA Astrophysics Data System (ADS)

Olsson, Lars; Cremer, Dieter

1996-11-01

Sum-over-states density functional perturbation theory (SOS-DFPT) has been used to calculate 13C, 15N, and 17O NMR chemical shifts of 20 molecules, for which accurate experimental gas-phase values are available. Compared to Hartree-Fock (HF), SOS-DFPT leads to improved chemical shift values and approaches the degree of accuracy obtained with second order Møller-Plesset perturbation theory (MP2). This is particularly true in the case of 15N chemical shifts where SOS-DFPT performs even better than MP2. Additional improvements of SOS-DFPT chemical shifts can be obtained by empirically correcting diamagnetic and paramagnetic contributions to compensate for deficiencies which are typical of DFT.

Restoration of acidic mine spoils with sewage sludge: II measurement of solids applied

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

Stucky, D.J.; Zoeller, A.L.

1980-01-01

Sewage sludge was incorporated in acidic strip mine spoils at rates equivalent to 0, 224, 336, and 448 dry metric tons (dmt)/ha and placed in pots in a greenhouse. Spoil parameters were determined 48 hours after sludge incorporation, Time Planting (P), and five months after orchardgrass (Dactylis glomerata L.) was planted, Time Harvest (H), in the pots. Parameters measured were: pH, organic matter content (OM), cation exchange capacity (CEC), electrical conductivity (EC) and yield. Values for each parameter were significantly different at the two sampling times. Correlation coefficient values were calculated for all parameters versus rates of applied sewage sludgemore » and all parameters versus each other. Multiple regressions were performed, stepwise, for all parameters versus rates of applied sewage sludge. Equations to predict amounts of sewage sludge incorporated in spoils were derived for individual and multiple parameters. Generally, measurements made at Time P achieved the highest correlation coefficient and multiple correlation coefficient values; therefore, the authors concluded data from Time P had the greatest predictability value. The most important value measured to predict rate of applied sewage sludge was pH and some additional accuracy was obtained by including CEC in equation. This experiment indicated that soil properties can be used to estimate amounts of sewage sludge solids required to reclaim acidic mine spoils and to estimate quantities incorporated.« less

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

Experimental evaluation of a recursive model identification technique for type 1 diabetes.

PubMed

Finan, Daniel A; Doyle, Francis J; Palerm, Cesar C; Bevier, Wendy C; Zisser, Howard C; Jovanovic, Lois; Seborg, Dale E

2009-09-01

A model-based controller for an artificial beta cell requires an accurate model of the glucose-insulin dynamics in type 1 diabetes subjects. To ensure the robustness of the controller for changing conditions (e.g., changes in insulin sensitivity due to illnesses, changes in exercise habits, or changes in stress levels), the model should be able to adapt to the new conditions by means of a recursive parameter estimation technique. Such an adaptive strategy will ensure that the most accurate model is used for the current conditions, and thus the most accurate model predictions are used in model-based control calculations. In a retrospective analysis, empirical dynamic autoregressive exogenous input (ARX) models were identified from glucose-insulin data for nine type 1 diabetes subjects in ambulatory conditions. Data sets consisted of continuous (5-minute) glucose concentration measurements obtained from a continuous glucose monitor, basal insulin infusion rates and times and amounts of insulin boluses obtained from the subjects' insulin pumps, and subject-reported estimates of the times and carbohydrate content of meals. Two identification techniques were investigated: nonrecursive, or batch methods, and recursive methods. Batch models were identified from a set of training data, whereas recursively identified models were updated at each sampling instant. Both types of models were used to make predictions of new test data. For the purpose of comparison, model predictions were compared to zero-order hold (ZOH) predictions, which were made by simply holding the current glucose value constant for p steps into the future, where p is the prediction horizon. Thus, the ZOH predictions are model free and provide a base case for the prediction metrics used to quantify the accuracy of the model predictions. In theory, recursive identification techniques are needed only when there are changing conditions in the subject that require model adaptation. Thus, the identification and validation techniques were performed with both "normal" data and data collected during conditions of reduced insulin sensitivity. The latter were achieved by having the subjects self-administer a medication, prednisone, for 3 consecutive days. The recursive models were allowed to adapt to this condition of reduced insulin sensitivity, while the batch models were only identified from normal data. Data from nine type 1 diabetes subjects in ambulatory conditions were analyzed; six of these subjects also participated in the prednisone portion of the study. For normal test data, the batch ARX models produced 30-, 45-, and 60-minute-ahead predictions that had average root mean square error (RMSE) values of 26, 34, and 40 mg/dl, respectively. For test data characterized by reduced insulin sensitivity, the batch ARX models produced 30-, 60-, and 90-minute-ahead predictions with average RMSE values of 27, 46, and 59 mg/dl, respectively; the recursive ARX models demonstrated similar performance with corresponding values of 27, 45, and 61 mg/dl, respectively. The identified ARX models (batch and recursive) produced more accurate predictions than the model-free ZOH predictions, but only marginally. For test data characterized by reduced insulin sensitivity, RMSE values for the predictions of the batch ARX models were 9, 5, and 5% more accurate than the ZOH predictions for prediction horizons of 30, 60, and 90 minutes, respectively. In terms of RMSE values, the 30-, 60-, and 90-minute predictions of the recursive models were more accurate than the ZOH predictions, by 10, 5, and 2%, respectively. In this experimental study, the recursively identified ARX models resulted in predictions of test data that were similar, but not superior, to the batch models. Even for the test data characteristic of reduced insulin sensitivity, the batch and recursive models demonstrated similar prediction accuracy. The predictions of the identified ARX models were only marginally more accurate than the model-free ZOH predictions. Given the simplicity of the ARX models and the computational ease with which they are identified, however, even modest improvements may justify the use of these models in a model-based controller for an artificial beta cell. 2009 Diabetes Technology Society.

INDIVIDUALIZED FETAL GROWTH ASSESSMENT: CRITICAL EVALUATION OF KEY CONCEPTS IN THE SPECIFICATION OF THIRD TRIMESTER GROWTH TRAJECTORIES

PubMed Central

Deter, Russell L.; Lee, Wesley; Yeo, Lami; Romero, Roberto

2012-01-01

Objectives To characterize 2nd and 3rd trimester fetal growth using Individualized Growth Assessment in a large cohort of fetuses with normal growth outcomes. Methods A prospective longitudinal study of 119 pregnancies was carried out from 18 weeks, MA, to delivery. Measurements of eleven fetal growth parameters were obtained from 3D scans at 3–4 week intervals. Regression analyses were used to determine Start Points [SP] and Rossavik model [P = c (t) k + st] coefficients c, k and s for each parameter in each fetus. Second trimester growth model specification functions were re-established. These functions were used to generate individual growth models and determine predicted s and s-residual [s = pred s + s-resid] values. Actual measurements were compared to predicted growth trajectories obtained from the growth models and Percent Deviations [% Dev = {{actual − predicted}/predicted} × 100] calculated. Age-specific reference standards for this statistic were defined using 2-level statistical modeling for the nine directly measured parameters and estimated weight. Results Rossavik models fit the data for all parameters very well [R2: 99%], with SP’s and k values similar to those found in a much smaller cohort. The c values were strongly related to the 2nd trimester slope [R2: 97%] as was predicted s to estimated c [R2: 95%]. The latter was negative for skeletal parameters and positive for soft tissue parameters. The s-residuals were unrelated to estimated c’s [R2: 0%], and had mean values of zero. Rossavik models predicted 3rd trimester growth with systematic errors close to 0% and random errors [95% range] of 5.7 – 10.9% and 20.0 – 24.3% for one and three dimensional parameters, respectively. Moderate changes in age-specific variability were seen in the 3rd trimester.. Conclusions IGA procedures for evaluating 2nd and 3rd trimester growth are now established based on a large cohort [4–6 fold larger than those used previously], thus permitting more reliable growth assessment with each fetus acting as its own control. New, more rigorously defined, age-specific standards for the evaluation of 3rd trimester growth deviations are now available for 10 anatomical parameters. Our results are also consistent with the predicted s and s-residual being representatives of growth controllers operating through the insulin-like growth factor [IGF] axis. PMID:23962305

3D QSAR studies on protein tyrosine phosphatase 1B inhibitors: comparison of the quality and predictivity among 3D QSAR models obtained from different conformer-based alignments.

PubMed

Pandey, Gyanendra; Saxena, Anil K

2006-01-01

A set of 65 flexible peptidomimetic competitive inhibitors (52 in the training set and 13 in the test set) of protein tyrosine phosphatase 1B (PTP1B) has been used to compare the quality and predictive power of 3D quantitative structure-activity relationship (QSAR) comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models for the three most commonly used conformer-based alignments, namely, cocrystallized conformer-based alignment (CCBA), docked conformer-based alignment (DCBA), and global minima energy conformer-based alignment (GMCBA). These three conformers of 5-[(2S)-2-({(2S)-2-[(tert-butoxycarbonyl)amino]-3-phenylpropanoyl}amino)3-oxo-3-pentylamino)propyl]-2-(carboxymethoxy)benzoic acid (compound number 66) were obtained from the X-ray structure of its cocrystallized complex with PTP1B (PDB ID: 1JF7), its docking studies, and its global minima by simulated annealing. Among the 3D QSAR models developed using the above three alignments, the CCBA provided the optimal predictive CoMFA model for the training set with cross-validated r2 (q2)=0.708, non-cross-validated r2=0.902, standard error of estimate (s)=0.165, and F=202.553 and the optimal CoMSIA model with q2=0.440, r2=0.799, s=0.192, and F=117.782. These models also showed the best test set prediction for the 13 compounds with predictive r2 values of 0.706 and 0.683, respectively. Though the QSAR models derived using the other two alignments also produced statistically acceptable models in the order DCBA>GMCBA in terms of the values of q2, r2, and predictive r2, they were inferior to the corresponding models derived using CCBA. Thus, the order of preference for the alignment selection for 3D QSAR model development may be CCBA>DCBA>GMCBA, and the information obtained from the CoMFA and CoMSIA contour maps may be useful in designing specific PTP1B inhibitors.

Validity of electromyographic fatigue threshold as a noninvasive method for tracking changes in ventilatory threshold in college-aged men.

PubMed

Kendall, Kristina L; Smith, Abbie E; Graef, Jennifer L; Walter, Ashley A; Moon, Jordan R; Lockwood, Christopher M; Beck, Travis W; Cramer, Joel T; Stout, Jeffrey R

2010-01-01

The submaximal electromyographic fatigue threshold test (EMG(FT)) has been shown to be highly correlated to ventilatory threshold (VT) as determined from maximal graded exercise tests (GXTs). Recently, a prediction equation was developed using the EMG(FT) value to predict VT. The aim of this study, therefore, was to determine if this new equation could accurately track changes in VT after high-intensity interval training (HIIT). Eighteen recreationally trained men (mean +/- SD; age 22.4 +/- 3.2 years) performed a GXT to determine maximal oxygen consumption rate (V(O2)peak) and VT using breath-by-breath spirometry. Participants also completed a discontinuous incremental cycle ergometer test to determine their EMGFT value. A total of four 2-minute work bouts were completed to obtain 15-second averages of the electromyographic amplitude. The resulting slopes from each successive work bout were used to calculate EMG(FT). The EMG(FT) value from each participant was used to estimate VT from the recently developed equation. All participants trained 3 days a week for 6 weeks. Training consisted of 5 sets of 2-minute work bouts with 1 minute of rest in between. Repeated-measures analysis of variance indicated no significant difference between actual and predicted VT values after 3 weeks of training. However, there was a significant difference between the actual and predicted VT values after 6 weeks of training. These findings suggest that the EMG(FT) may be useful when tracking changes in VT after 3 weeks of HIIT in recreationally trained individuals. However, the use of EMG(FT) to predict VT does not seem to be valid for tracking changes after 6 weeks of HIIT. At this time, it is not recommended that EMG(FT) be used to predict and track changes in VT.

Optimal interpolation analysis of leaf area index using MODIS data

USGS Publications Warehouse

Gu, Yingxin; Belair, Stephane; Mahfouf, Jean-Francois; Deblonde, Godelieve

2006-01-01

A simple data analysis technique for vegetation leaf area index (LAI) using Moderate Resolution Imaging Spectroradiometer (MODIS) data is presented. The objective is to generate LAI data that is appropriate for numerical weather prediction. A series of techniques and procedures which includes data quality control, time-series data smoothing, and simple data analysis is applied. The LAI analysis is an optimal combination of the MODIS observations and derived climatology, depending on their associated errors σo and σc. The “best estimate” LAI is derived from a simple three-point smoothing technique combined with a selection of maximum LAI (after data quality control) values to ensure a higher quality. The LAI climatology is a time smoothed mean value of the “best estimate” LAI during the years of 2002–2004. The observation error is obtained by comparing the MODIS observed LAI with the “best estimate” of the LAI, and the climatological error is obtained by comparing the “best estimate” of LAI with the climatological LAI value. The LAI analysis is the result of a weighting between these two errors. Demonstration of the method described in this paper is presented for the 15-km grid of Meteorological Service of Canada (MSC)'s regional version of the numerical weather prediction model. The final LAI analyses have a relatively smooth temporal evolution, which makes them more appropriate for environmental prediction than the original MODIS LAI observation data. They are also more realistic than the LAI data currently used operationally at the MSC which is based on land-cover databases.

Factors affecting the transformation of a pyritic tailing: scaled-up column tests.

PubMed

García, C; Ballester, A; González, F; Blázquez, M L

2005-02-14

Two different methods for predicting the quality of the water draining from a pyritic tailing are compared; for this, a static test (ABA test) and a kinetic test in large columns were chosen. The different results obtained in the two experimental set-ups show the necessity of being careful in selecting both the adequate predictive method and the conclusions and extrapolations derived from them. The tailing chosen for the weathering tests (previously tested in shake flasks and in small weathering columns) was a pyritic residue produced in a flotation plant of complex polymetallic sulphides (Huelva, Spain). The ABA test was a modification of the conventional ABA test reported in bibliography. The modification consisted in the soft conditions employed in the digestion phase. For column tests, two identical methacrylate columns (150 cm high and 15 cm diameter) were used to study the chemical and microbiological processes controlling the leaching of pyrite. The results obtained in the two tests were very different. The static test predicted a strong potential acidity for the tailing. On the contrary, pH value in the effluents draining from the columns reached values of only 5 units, being the concentration of metals (<600 mg/L) and sulphate ions (<17,000 mg/L) very small and far from the values of a typical acid mine drainage. In consequence, the static test may oversize the potential acidity of the tailing; whereas large columns may be saturated in water, displacing the oxygen and inhibiting the microbial activity necessary to catalyse mineral oxidation.

Optimization of chitin yield from shrimp shell waste by Bacillus subtilis and impact of gamma irradiation on production of low molecular weight chitosan.

PubMed

Gamal, Rawia F; El-Tayeb, Tarek S; Raffat, Enas I; Ibrahim, Haytham M M; Bashandy, A S

2016-10-01

Chitin and chitosan have been produced from the exoskeletons of crustacean shells such as shrimps. In this study, seventy bacterial isolates, isolated from soil, were tested for proteolytic enzymes production. The most efficient one, identified as Bacillus subtilis, was employed to extract chitin from shrimp shell waste (SSW). Following one-variable-at-a-time approach, the relevant factors affecting deproteinization (DP) and demineralization (DM) were sucrose concentration (10%, w/v), SSW concentration (5%, w/v), inoculum size (15%, v/v), and fermentation time (6days). These factors were optimized subsequently using Box-Behnken design and response surface methodology. Maximum DP (97.65%) and DM (82.94%) were predicted at sucrose concentration (5%), SSW concentration (12.5%), inoculum size (10%, containing 35×10(8) CFU/mL), and fermentation time (7days). The predicted optimum values were verified by additional experiment. The values of DP (96.0%) and DM (82.1%) obtained experimentally correlated to the predicted values which justify the authenticity of optimum points. Overall 1.3-fold increase in DP% and DM% was obtained compared with 75.27% and 63.50%, respectively, before optimization. Gamma-irradiation (35kGy) reduced deacetylation time of irradiated chitin by 4.5-fold compared with non-irradiated chitin. The molecular weight of chitosan was decreased from 1.9×10(6) (non-irradiated) to 3.7×10(4)g/mol (at 35kGy). Copyright © 2016 Elsevier B.V. All rights reserved.

Studies on the interactions between drugs and estrogen: analytical method for prediction system of gynecomastia induced by drugs on the inhibitory metabolism of estradiol using Escherichia coli coexpressing human CYP3A4 with human NADPH-cytochrome P450 reductase.

PubMed

Satoh, T; Fujita, K I; Munakata, H; Itoh, S; Nakamura, K; Kamataki, T; Itoh, S; Yoshizawa, I

2000-11-15

To establish a prediction system for drug-induced gynecomastia in clinical fields, a model reaction system was developed to explain numerically this side effect. The principle is based on the assumption that 50% inhibition concentration (IC(50)) of drugs on the in vitro metabolism of estradiol (E2) to its major product 2-hydroxyestradiol (2-OH-E2) can be regarded as the index for achieving this purpose. By using human cytochrome P450s coexpressed with human NADPH-cytochrome P450 reductase in Escherichia coli as the enzyme, the reaction was examined. Among the nine enzymes (CYP1A1, 1A2, 2A6, 2C8, 2C9, 2C19, 2D6, 2E1, and 3A4) tested, CYP3A4 having a V(max)/K(m) (ml/min/nmol P450) value of 0.32 for production of 2-OH-E2 was shown to be the most suitable enzyme as the reagent. The inhibitory effects of ketoconazole, cyclosporin A, and cimetidine toward the 2-hydroxylation of E2 catalyzed by CYP3A4 were obtained, and their IC(50) values were 7 nM, 64 nM, and 290 microM, respectively. The present results suggest that IC(50) values thus obtained can be substituted as the prediction index for gynecomastia induced by drugs, considering the patients' individual information. Copyright 2000 Academic Press.

HBeAg and hepatitis B virus DNA as outcome predictors during therapy with peginterferon alfa-2a for HBeAg-positive chronic hepatitis B.

PubMed

Fried, Michael W; Piratvisuth, Teerha; Lau, George K K; Marcellin, Patrick; Chow, Wan-Cheng; Cooksley, Graham; Luo, Kang-Xian; Paik, Seung Woon; Liaw, Yun-Fan; Button, Peter; Popescu, Matei

2008-02-01

The aims of this study were to evaluate the usefulness of quantitative hepatitis B e antigen (HBeAg) values for predicting HBeAg seroconversion in patients treated with peginterferon alfa-2a and to assess the dynamic changes in quantitative HBeAg during therapy, compared with conventional measures of serum hepatitis B virus DNA. Data were analyzed from a large, randomized, multinational phase III registration trial involving 271 HBV-infected HBeAg-positive patients who received peginterferon alfa-2a plus oral placebo for 48 weeks. HBeAg levels were measured serially during therapy using a microparticle enzyme immunoassay validated with in-house reference standards obtained from the Paul Ehrlich Institute (PEIU/mL). In patients who achieved HBeAg seroconversion, levels of HBeAg consistently decreased during treatment and remained at their lowest level during the 24 weeks of posttreatment follow-up. After 24 weeks of treatment, 4% of patients with the highest levels of HBeAg (>or=100 PEIU/mL) achieved HBeAg seroconversion, yielding a negative predictive value of 96%, which was greater than that obtained for levels of HBV DNA (86%). Late responders to peginterferon alfa-2a could also be differentiated from nonresponders by continued decrease in HBeAg values, which were not evident by changes in HBV DNA. These analyses suggest quantitative HBeAg is a useful adjunctive measurement for predicting HBeAg seroconversion in patients treated with peginterferon when considering both sensitivity and specificity compared with serum HBV DNA.

Predicting heavy metals' adsorption edges and adsorption isotherms on MnO2 with the parameters determined from Langmuir kinetics.

PubMed

Hu, Qinghai; Xiao, Zhongjin; Xiong, Xinmei; Zhou, Gongming; Guan, Xiaohong

2015-01-01

Although surface complexation models have been widely used to describe the adsorption of heavy metals, few studies have verified the feasibility of modeling the adsorption kinetics, edge, and isotherm data with one pH-independent parameter. A close inspection of the derivation process of Langmuir isotherm revealed that the equilibrium constant derived from the Langmuir kinetic model, KS-kinetic, is theoretically equivalent to the adsorption constant in Langmuir isotherm, KS-Langmuir. The modified Langmuir kinetic model (MLK model) and modified Langmuir isotherm model (MLI model) incorporating pH factor were developed. The MLK model was employed to simulate the adsorption kinetics of Cu(II), Co(II), Cd(II), Zn(II) and Ni(II) on MnO2 at pH3.2 or 3.3 to get the values of KS-kinetic. The adsorption edges of heavy metals could be modeled with the modified metal partitioning model (MMP model), and the values of KS-Langmuir were obtained. The values of KS-kinetic and KS-Langmuir are very close to each other, validating that the constants obtained by these two methods are basically the same. The MMP model with KS-kinetic constants could predict the adsorption edges of heavy metals on MnO2 very well at different adsorbent/adsorbate concentrations. Moreover, the adsorption isotherms of heavy metals on MnO2 at various pH levels could be predicted reasonably well by the MLI model with the KS-kinetic constants. Copyright © 2014. Published by Elsevier B.V.

A Maximum Muscle Strength Prediction Formula Using Theoretical Grade 3 Muscle Strength Value in Daniels et al.'s Manual Muscle Test, in Consideration of Age: An Investigation of Hip and Knee Joint Flexion and Extension.

PubMed

Usa, Hideyuki; Matsumura, Masashi; Ichikawa, Kazuna; Takei, Hitoshi

2017-01-01

This study attempted to develop a formula for predicting maximum muscle strength value for young, middle-aged, and elderly adults using theoretical Grade 3 muscle strength value (moment fair: M f )-the static muscular moment to support a limb segment against gravity-from the manual muscle test by Daniels et al. A total of 130 healthy Japanese individuals divided by age group performed isometric muscle contractions at maximum effort for various movements of hip joint flexion and extension and knee joint flexion and extension, and the accompanying resisting force was measured and maximum muscle strength value (moment max, M m ) was calculated. Body weight and limb segment length (thigh and lower leg length) were measured, and M f was calculated using anthropometric measures and theoretical calculation. There was a linear correlation between M f and M m in each of the four movement types in all groups, excepting knee flexion in elderly. However, the formula for predicting maximum muscle strength was not sufficiently compatible in middle-aged and elderly adults, suggesting that the formula obtained in this study is applicable in young adults only.

Diagnostic accuracy of ultrasonography in detection of blunt abdominal trauma and comparison of early and late ultrasonography 24 hours after trauma.

PubMed

Feyzi, Ali; Rad, Masoud Pezeshki; Ahanchi, Navid; Firoozabadi, Jalil

2015-01-01

Despite the advantages of ultrasound scan, its use as a screening tool in blunt abdominal trauma is controversial. The aim of this study was to evaluate the diagnostic value of early and late ultrasound in patients with blunt abdominal trauma (BAT). In this study which was performed in a level I trauma center, firstly, 2418 patients with BAT had ultrasound (US) examination by two trauma expert radiologists. Results were compared with the best available gold standards such as laparotomy, CT, repeated ultrasound or clinical course follow-up. Then, 400 patients with BAT were examined by a trained residency student. In the first phase, sensitivity, specificity, negative predictive value, positive predictive value and accuracy of ultrasound were 97%, 98.1%, 99.7%, 83% and 98% respectively. In the second phase, they were 97.3%, 97.2%, 97.7%, 96.8% and 97.3% for the early and 98.5%, 97.6%, 98.5%, 97.5% and 98% for the late ultrasound respectively. Results obtained from this study indicate that negative ultrasound findings associated with negative clinical observation virtually exclude abdominal injury, and confirmation by performing other tests is unnecessary. High sensitivity and negative predictive value is achieved if ultrasound is performed by expert trauma radiologist.

A Maximum Muscle Strength Prediction Formula Using Theoretical Grade 3 Muscle Strength Value in Daniels et al.'s Manual Muscle Test, in Consideration of Age: An Investigation of Hip and Knee Joint Flexion and Extension

PubMed Central

Matsumura, Masashi; Ichikawa, Kazuna; Takei, Hitoshi

2017-01-01

This study attempted to develop a formula for predicting maximum muscle strength value for young, middle-aged, and elderly adults using theoretical Grade 3 muscle strength value (moment fair: Mf)—the static muscular moment to support a limb segment against gravity—from the manual muscle test by Daniels et al. A total of 130 healthy Japanese individuals divided by age group performed isometric muscle contractions at maximum effort for various movements of hip joint flexion and extension and knee joint flexion and extension, and the accompanying resisting force was measured and maximum muscle strength value (moment max, Mm) was calculated. Body weight and limb segment length (thigh and lower leg length) were measured, and Mf was calculated using anthropometric measures and theoretical calculation. There was a linear correlation between Mf and Mm in each of the four movement types in all groups, excepting knee flexion in elderly. However, the formula for predicting maximum muscle strength was not sufficiently compatible in middle-aged and elderly adults, suggesting that the formula obtained in this study is applicable in young adults only. PMID:28133549

Unenhanced breast MRI (STIR, T2-weighted TSE, DWIBS): An accurate and alternative strategy for detecting and differentiating breast lesions.

PubMed

Telegrafo, Michele; Rella, Leonarda; Stabile Ianora, Amato Antonio; Angelelli, Giuseppe; Moschetta, Marco

2015-10-01

To assess the role of STIR, T2-weighted TSE and DWIBS sequences for detecting and characterizing breast lesions and to compare unenhanced (UE)-MRI results with contrast-enhanced (CE)-MRI and histological findings, having the latter as the reference standard. Two hundred eighty consecutive patients (age range, 27-73 years; mean age±standard deviation (SD), 48.8±9.8years) underwent MR examination with a diagnostic protocol including STIR, T2-weighted TSE, THRIVE and DWIBS sequences. Two radiologists blinded to both dynamic sequences and histological findings evaluated in consensus STIR, T2-weighted TSE and DWIBS sequences and after two weeks CE-MRI images searching for breast lesions. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy for UE-MRI and CE-MRI were calculated. UE-MRI results were also compared with CE- MRI. UE-MRI sequences obtained sensitivity, specificity, diagnostic accuracy, PPV and NPV values of 94%, 79%, 86%, 79% and 94%, respectively. CE-MRI sequences obtained sensitivity, specificity, diagnostic accuracy, PPV and NPV values of 98%, 83%, 90%, 84% and 98%, respectively. No statistically significant difference between UE-MRI and CE-MRI was found. Breast UE-MRI could represent an accurate diagnostic tool and a valid alternative to CE-MRI for evaluating breast lesions. STIR and DWIBS sequences allow to detect breast lesions while T2-weighted TSE sequences and ADC values could be useful for lesion characterization. Copyright © 2015 Elsevier Inc. All rights reserved.

Reconsidering the use of rankings in the valuation of health states: a model for estimating cardinal values from ordinal data

PubMed Central

Salomon, Joshua A

2003-01-01

Background In survey studies on health-state valuations, ordinal ranking exercises often are used as precursors to other elicitation methods such as the time trade-off (TTO) or standard gamble, but the ranking data have not been used in deriving cardinal valuations. This study reconsiders the role of ordinal ranks in valuing health and introduces a new approach to estimate interval-scaled valuations based on aggregate ranking data. Methods Analyses were undertaken on data from a previously published general population survey study in the United Kingdom that included rankings and TTO values for hypothetical states described using the EQ-5D classification system. The EQ-5D includes five domains (mobility, self-care, usual activities, pain/discomfort and anxiety/depression) with three possible levels on each. Rank data were analysed using a random utility model, operationalized through conditional logit regression. In the statistical model, probabilities of observed rankings were related to the latent utilities of different health states, modeled as a linear function of EQ-5D domain scores, as in previously reported EQ-5D valuation functions. Predicted valuations based on the conditional logit model were compared to observed TTO values for the 42 states in the study and to predictions based on a model estimated directly from the TTO values. Models were evaluated using the intraclass correlation coefficient (ICC) between predictions and mean observations, and the root mean squared error of predictions at the individual level. Results Agreement between predicted valuations from the rank model and observed TTO values was very high, with an ICC of 0.97, only marginally lower than for predictions based on the model estimated directly from TTO values (ICC = 0.99). Individual-level errors were also comparable in the two models, with root mean squared errors of 0.503 and 0.496 for the rank-based and TTO-based predictions, respectively. Conclusions Modeling health-state valuations based on ordinal ranks can provide results that are similar to those obtained from more widely analyzed valuation techniques such as the TTO. The information content in aggregate ranking data is not currently exploited to full advantage. The possibility of estimating cardinal valuations from ordinal ranks could also simplify future data collection dramatically and facilitate wider empirical study of health-state valuations in diverse settings and population groups. PMID:14687419

Uncertainty analysis of neural network based flood forecasting models: An ensemble based approach for constructing prediction interval

NASA Astrophysics Data System (ADS)

Kasiviswanathan, K.; Sudheer, K.

2013-05-01

Artificial neural network (ANN) based hydrologic models have gained lot of attention among water resources engineers and scientists, owing to their potential for accurate prediction of flood flows as compared to conceptual or physics based hydrologic models. The ANN approximates the non-linear functional relationship between the complex hydrologic variables in arriving at the river flow forecast values. Despite a large number of applications, there is still some criticism that ANN's point prediction lacks in reliability since the uncertainty of predictions are not quantified, and it limits its use in practical applications. A major concern in application of traditional uncertainty analysis techniques on neural network framework is its parallel computing architecture with large degrees of freedom, which makes the uncertainty assessment a challenging task. Very limited studies have considered assessment of predictive uncertainty of ANN based hydrologic models. In this study, a novel method is proposed that help construct the prediction interval of ANN flood forecasting model during calibration itself. The method is designed to have two stages of optimization during calibration: at stage 1, the ANN model is trained with genetic algorithm (GA) to obtain optimal set of weights and biases vector, and during stage 2, the optimal variability of ANN parameters (obtained in stage 1) is identified so as to create an ensemble of predictions. During the 2nd stage, the optimization is performed with multiple objectives, (i) minimum residual variance for the ensemble mean, (ii) maximum measured data points to fall within the estimated prediction interval and (iii) minimum width of prediction interval. The method is illustrated using a real world case study of an Indian basin. The method was able to produce an ensemble that has an average prediction interval width of 23.03 m3/s, with 97.17% of the total validation data points (measured) lying within the interval. The derived prediction interval for a selected hydrograph in the validation data set is presented in Fig 1. It is noted that most of the observed flows lie within the constructed prediction interval, and therefore provides information about the uncertainty of the prediction. One specific advantage of the method is that when ensemble mean value is considered as a forecast, the peak flows are predicted with improved accuracy by this method compared to traditional single point forecasted ANNs. Fig. 1 Prediction Interval for selected hydrograph

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.

A new approach for modeling patient overall radiosensitivity and predicting multiple toxicity endpoints for breast cancer patients.

PubMed

Mbah, Chamberlain; De Ruyck, Kim; De Schrijver, Silke; De Sutter, Charlotte; Schiettecatte, Kimberly; Monten, Chris; Paelinck, Leen; De Neve, Wilfried; Thierens, Hubert; West, Catharine; Amorim, Gustavo; Thas, Olivier; Veldeman, Liv

2018-05-01

Evaluation of patient characteristics inducing toxicity in breast radiotherapy, using simultaneous modeling of multiple endpoints. In 269 early-stage breast cancer patients treated with whole-breast irradiation (WBI) after breast-conserving surgery, toxicity was scored, based on five dichotomized endpoints. Five logistic regression models were fitted, one for each endpoint and the effect sizes of all variables were estimated using maximum likelihood (MLE). The MLEs are improved with James-Stein estimates (JSEs). The method combines all the MLEs, obtained for the same variable but from different endpoints. Misclassification errors were computed using MLE- and JSE-based prediction models. For associations, p-values from the sum of squares of MLEs were compared with p-values from the Standardized Total Average Toxicity (STAT) Score. With JSEs, 19 highest ranked variables were predictive of the five different endpoints. Important variables increasing radiation-induced toxicity were chemotherapy, age, SATB2 rs2881208 SNP and nodal irradiation. Treatment position (prone position) was most protective and ranked eighth. Overall, the misclassification errors were 45% and 34% for the MLE- and JSE-based models, respectively. p-Values from the sum of squares of MLEs and p-values from STAT score led to very similar conclusions, except for the variables nodal irradiation and treatment position, for which STAT p-values suggested an association with radiosensitivity, whereas p-values from the sum of squares indicated no association. Breast volume was ranked as the most significant variable in both strategies. The James-Stein estimator was used for selecting variables that are predictive for multiple toxicity endpoints. With this estimator, 19 variables were predictive for all toxicities of which four were significantly associated with overall radiosensitivity. JSEs led to almost 25% reduction in the misclassification error rate compared to conventional MLEs. Finally, patient characteristics that are associated with radiosensitivity were identified without explicitly quantifying radiosensitivity.

Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments.

PubMed

Zheng, Ce; Kurgan, Lukasz

2008-10-10

beta-turn is a secondary protein structure type that plays significant role in protein folding, stability, and molecular recognition. To date, several methods for prediction of beta-turns from protein sequences were developed, but they are characterized by relatively poor prediction quality. The novelty of the proposed sequence-based beta-turn predictor stems from the usage of a window based information extracted from four predicted three-state secondary structures, which together with a selected set of position specific scoring matrix (PSSM) values serve as an input to the support vector machine (SVM) predictor. We show that (1) all four predicted secondary structures are useful; (2) the most useful information extracted from the predicted secondary structure includes the structure of the predicted residue, secondary structure content in a window around the predicted residue, and features that indicate whether the predicted residue is inside a secondary structure segment; (3) the PSSM values of Asn, Asp, Gly, Ile, Leu, Met, Pro, and Val were among the top ranked features, which corroborates with recent studies. The Asn, Asp, Gly, and Pro indicate potential beta-turns, while the remaining four amino acids are useful to predict non-beta-turns. Empirical evaluation using three nonredundant datasets shows favorable Q total, Q predicted and MCC values when compared with over a dozen of modern competing methods. Our method is the first to break the 80% Q total barrier and achieves Q total = 80.9%, MCC = 0.47, and Q predicted higher by over 6% when compared with the second best method. We use feature selection to reduce the dimensionality of the feature vector used as the input for the proposed prediction method. The applied feature set is smaller by 86, 62 and 37% when compared with the second and two third-best (with respect to MCC) competing methods, respectively. Experiments show that the proposed method constitutes an improvement over the competing prediction methods. The proposed prediction model can better discriminate between beta-turns and non-beta-turns due to obtaining lower numbers of false positive predictions. The prediction model and datasets are freely available at http://biomine.ece.ualberta.ca/BTNpred/BTNpred.html.

Cosmological velocity correlations - Observations and model predictions

NASA Technical Reports Server (NTRS)

Gorski, Krzysztof M.; Davis, Marc; Strauss, Michael A.; White, Simon D. M.; Yahil, Amos

1989-01-01

By applying the present simple statistics for two-point cosmological peculiar velocity-correlation measurements to the actual data sets of the Local Supercluster spiral galaxy of Aaronson et al. (1982) and the elliptical galaxy sample of Burstein et al. (1987), as well as to the velocity field predicted by the distribution of IRAS galaxies, a coherence length of 1100-1600 km/sec is obtained. Coherence length is defined as that separation at which the correlations drop to half their zero-lag value. These results are compared with predictions from two models of large-scale structure formation: that of cold dark matter and that of baryon isocurvature proposed by Peebles (1980). N-body simulations of these models are performed to check the linear theory predictions and measure sampling fluctuations.

Video image analysis as a potential grading system for Uruguayan beef carcasses.

PubMed

Vote, D J; Bowling, M B; Cunha, B C N; Belk, K E; Tatum, J D; Montossi, F; Smith, G C

2009-07-01

A study was conducted in 2 phases to evaluate the effectiveness of 1) the VIAscan Beef Carcass System (BCSys; hot carcass system) and the CVS BeefCam (chilled carcass system), used independently or in combination, to predict Uruguayan beef carcass fabrication yields; and 2) the CVS BeefCam to segregate Uruguayan beef carcasses into groups that differ in the Warner-Bratzler shear force (WBSF) values of their LM steaks. The results from the meat yield phase of the present study indicated that the prediction of saleable meat yield percentages from Uruguayan beef carcasses by use of the BCSys or CVS BeefCam is similar to, or slightly better than, the use of USDA yield grade calculated to the nearest 0.1 and was much more effective than prediction based on Uruguay National Institute of Meat (INAC) grades. A further improvement in fabrication yield prediction could be obtained by use of a dual-component video image analysis (VIA) system. Whichever method of VIA prediction of fabrication yield is used, a single predicted value of fabrication yield for every carcass removes an impediment to the implementation of a value-based pricing system. Additionally, a VIA method of predicting carcass yield has the advantage over the current INAC classification system in that estimates would be produced by an instrument rather than by packing plant personnel, which would appeal to cattle producers. Results from the tenderness phase of the study indicated that the CVS BeefCam output variable for marbling was not (P > 0.05) able to segregate steer and heifer carcasses into groups that differed in WBSF values. In addition, the results of segregating steer and heifer carcasses according to muscle color output variables indicate that muscle maturity and skeletal maturity were useful for segregating carcasses according to differences in WBSF values of their steaks (P > 0.05). Use of VIA to predict beef carcass fabrication yields could improve accuracy and reduce subjectivity in comparison with use of current INAC grades. Use of VIA to sort carcasses according to muscle color would allow for the marketing of more consistent beef products with respect to tenderness. This would help facilitate the initiation of a value-based marketing system for the Uruguayan beef industry.

Validation of soil hydraulic pedotransfer functions at the local and catchment scale for an Indonesian basin

NASA Astrophysics Data System (ADS)

Booij, Martijn J.; Oldhoff, Ruben J. J.; Rustanto, Andry

2016-04-01

In order to accurately model the hydrological processes in a catchment, information on the soil hydraulic properties is of great importance. These data can be obtained by conducting field work, which is costly and time consuming, or by using pedotransfer functions (PTFs). A PTF is an empirical relationship between easily obtainable soil characteristics and a soil hydraulic parameter. In this study, PTFs for the saturated hydraulic conductivity (Ks) and the available water content (AWC) are investigated. PTFs are area-specific, since for instance tropical soils often have a different composition and hydraulic behaviour compared to temperate soils. Application of temperate soil PTFs on tropical soils might result in poor performance, which is a problem as few tropical soil PTFs are available. The objective of this study is to determine whether Ks and AWC can be accurately approximated using PTFs, by analysing their performance at both the local scale and the catchment scale. Four published PTFs for Ks and AWC are validated on a data set of 91 soil samples collected in the Upper Bengawan Solo catchment on Java, Indonesia. The AWC is predicted very poorly, with Nash-Sutcliffe Efficiency (NSE) values below zero for all selected PTFs. For Ks PTFs better results were found. The Wösten and Rosetta-3 PTFs predict the Ks moderately accurate, with NSE values of 0.28 and 0.39, respectively. New PTFs for both AWC and Ks were developed using multiple linear regression and NSE values of 0.37 (AWC) and 0.55 (Ks) were obtained. Although these values are not very high, they are significantly higher than for the published PTFs. The hydrological SWAT model was set up for the Keduang, a sub-catchment of the Upper Bengawan Solo River, to simulate monthly catchment streamflow. Eleven cases were defined to validate the PTFs at the catchment scale. For the Ks-PTF cases NSE values of around 0.84 were obtained for the validation period. The use of AWC PTFs resulted in slightly lower NSE values, although the differences in model accuracy are low. The small differences between the cases are caused by the soil homogeneity in the Keduang catchment. Without model calibration an NSE value of 0.51 was found. At the local scale, the Wösten and Rosetta-3 PTFs can be used to predict Ks. AWC PTFs show insufficient accuracy at the local scale. At the catchment scale, the Wösten and Rosetta-3 Ks PTFs and the developed AWC and Ks PTFs are validated. It is recommended to use the PTFs developed in this study for the Upper Bengawan Solo catchment. More research is needed on the effect of PTF input on simulated hydrological state variables, such as soil moisture content, and the effect of catchment soil heterogeneity on the validation and application of PTFs.

QSRR using evolved artificial neural network for 52 common pharmaceuticals and drugs of abuse in hair from UPLC-TOF-MS.

PubMed

Noorizadeh, Hadi; Farmany, Abbas; Narimani, Hojat; Noorizadeh, Mehrab

2013-05-01

A quantitative structure-retention relationship (QSRR) study based on an artificial neural network (ANN) was carried out for the prediction of the ultra-performance liquid chromatography-Time-of-Flight mass spectrometry (UPLC-TOF-MS) retention time (RT) of a set of 52 pharmaceuticals and drugs of abuse in hair. The genetic algorithm was used as a variable selection tool. A partial least squares (PLS) method was used to select the best descriptors which were used as input neurons in neural network model. For choosing the best predictive model from among comparable models, square correlation coefficient R(2) for the whole set calculated based on leave-group-out predicted values of the training set and model-derived predicted values for the test set compounds is suggested to be a good criterion. Finally, to improve the results, structure-retention relationships were followed by a non-linear approach using artificial neural networks and consequently better results were obtained. This also demonstrates the advantages of ANN. Copyright © 2011 John Wiley & Sons, Ltd.

Prediction of solubility parameters and miscibility of pharmaceutical compounds by molecular dynamics simulations.

PubMed

Gupta, Jasmine; Nunes, Cletus; Vyas, Shyam; Jonnalagadda, Sriramakamal

2011-03-10

The objectives of this study were (i) to develop a computational model based on molecular dynamics technique to predict the miscibility of indomethacin in carriers (polyethylene oxide, glucose, and sucrose) and (ii) to experimentally verify the in silico predictions by characterizing the drug-carrier mixtures using thermoanalytical techniques. Molecular dynamics (MD) simulations were performed using the COMPASS force field, and the cohesive energy density and the solubility parameters were determined for the model compounds. The magnitude of difference in the solubility parameters of drug and carrier is indicative of their miscibility. The MD simulations predicted indomethacin to be miscible with polyethylene oxide and to be borderline miscible with sucrose and immiscible with glucose. The solubility parameter values obtained using the MD simulations values were in reasonable agreement with those calculated using group contribution methods. Differential scanning calorimetry showed melting point depression of polyethylene oxide with increasing levels of indomethacin accompanied by peak broadening, confirming miscibility. In contrast, thermal analysis of blends of indomethacin with sucrose and glucose verified general immiscibility. The findings demonstrate that molecular modeling is a powerful technique for determining the solubility parameters and predicting miscibility of pharmaceutical compounds. © 2011 American Chemical Society

Near infrared spectroscopy as an on-line method to quantitatively determine glycogen and predict ultimate pH in pre rigor bovine M. longissimus dorsi.

PubMed

Lomiwes, D; Reis, M M; Wiklund, E; Young, O A; North, M

2010-12-01

The potential of near infrared (NIR) spectroscopy as an on-line method to quantify glycogen and predict ultimate pH (pH(u)) of pre rigor beef M. longissimus dorsi (LD) was assessed. NIR spectra (538 to 1677 nm) of pre rigor LD from steers, cows and bulls were collected early post mortem and measurements were made for pre rigor glycogen concentration and pH(u). Spectral and measured data were combined to develop models to quantify glycogen and predict the pH(u) of pre rigor LD. NIR spectra and pre rigor predicted values obtained from quantitative models were shown to be poorly correlated against glycogen and pH(u) (r(2)=0.23 and 0.20, respectively). Qualitative models developed to categorize each muscle according to their pH(u) were able to correctly categorize 42% of high pH(u) samples. Optimum qualitative and quantitative models derived from NIR spectra found low correlation between predicted values and reference measurements. Copyright © 2010 The American Meat Science Association. Published by Elsevier Ltd.. All rights reserved.

Determination of Spatially Resolved Tablet Density and Hardness Using Near-Infrared Chemical Imaging (NIR-CI).

PubMed

Talwar, Sameer; Roopwani, Rahul; Anderson, Carl A; Buckner, Ira S; Drennen, James K

2017-08-01

Near-infrared chemical imaging (NIR-CI) combines spectroscopy with digital imaging, enabling spatially resolved analysis and characterization of pharmaceutical samples. Hardness and relative density are critical quality attributes (CQA) that affect tablet performance. Intra-sample density or hardness variability can reveal deficiencies in formulation design or the tableting process. This study was designed to develop NIR-CI methods to predict spatially resolved tablet density and hardness. The method was implemented using a two-step procedure. First, NIR-CI was used to develop a relative density/solid fraction (SF) prediction method for pure microcrystalline cellulose (MCC) compacts only. A partial least squares (PLS) model for predicting SF was generated by regressing the spectra of certain representative pixels selected from each image against the compact SF. Pixel selection was accomplished with a threshold based on the Euclidean distance from the median tablet spectrum. Second, micro-indentation was performed on the calibration compacts to obtain hardness values. A univariate model was developed by relating the empirical hardness values to the NIR-CI predicted SF at the micro-indented pixel locations: this model generated spatially resolved hardness predictions for the entire tablet surface.

Using Long-Short-Term-Memory Recurrent Neural Networks to Predict Aviation Engine Vibrations

NASA Astrophysics Data System (ADS)

ElSaid, AbdElRahman Ahmed

This thesis examines building viable Recurrent Neural Networks (RNN) using Long Short Term Memory (LSTM) neurons to predict aircraft engine vibrations. The different networks are trained on a large database of flight data records obtained from an airline containing flights that suffered from excessive vibration. RNNs can provide a more generalizable and robust method for prediction over analytical calculations of engine vibration, as analytical calculations must be solved iteratively based on specific empirical engine parameters, and this database contains multiple types of engines. Further, LSTM RNNs provide a "memory" of the contribution of previous time series data which can further improve predictions of future vibration values. LSTM RNNs were used over traditional RNNs, as those suffer from vanishing/exploding gradients when trained with back propagation. The study managed to predict vibration values for 1, 5, 10, and 20 seconds in the future, with 2.84% 3.3%, 5.51% and 10.19% mean absolute error, respectively. These neural networks provide a promising means for the future development of warning systems so that suitable actions can be taken before the occurrence of excess vibration to avoid unfavorable situations during flight.

An Experimental Study of Mortars with Recycled Ceramic Aggregates: Deduction and Prediction of the Stress-Strain.

PubMed

Cabrera-Covarrubias, Francisca Guadalupe; Gómez-Soberón, José Manuel; Almaral-Sánchez, Jorge Luis; Arredondo-Rea, Susana Paola; Gómez-Soberón, María Consolación; Corral-Higuera, Ramón

2016-12-21

The difficult current environmental situation, caused by construction industry residues containing ceramic materials, could be improved by using these materials as recycled aggregates in mortars, with their processing causing a reduction in their use in landfill, contributing to recycling and also minimizing the consumption of virgin materials. Although some research is currently being carried out into recycled mortars, little is known about their stress-strain (σ-ε); therefore, this work will provide the experimental results obtained from recycled mortars with recycled ceramic aggregates (with contents of 0%, 10%, 20%, 30%, 50% and 100%), such as the density and compression strength, as well as the σ-ε curves representative of their behavior. The values obtained from the analytical process of the results in order to finally obtain, through numerical analysis, the equations to predict their behavior (related to their recycled content) are those of: σ (elastic ranges and failure maximum), ε (elastic ranges and failure maximum), and Resilience and Toughness. At the end of the investigation, it is established that mortars with recycled ceramic aggregate contents of up to 20% could be assimilated just like mortars with the usual aggregates, and the obtained prediction equations could be used in cases of similar applications.