[Comparison of two quantitative methods of endobronchial ultrasound real-time elastography for evaluating intrathoracic lymph nodes].

PubMed

Mao, X W; Yang, J Y; Zheng, X X; Wang, L; Zhu, L; Li, Y; Xiong, H K; Sun, J Y

2017-06-12

Objective: To compare the clinical value of two quantitative methods in analyzing endobronchial ultrasound real-time elastography (EBUS-RTE) images for evaluating intrathoracic lymph nodes. Methods: From January 2014 to April 2014, EBUS-RTE examination was performed in patients who received EBUS-TBNA examination in Shanghai Chest Hospital. Each intrathoracic lymph node had a selected EBUS-RTE image. Stiff area ratio and mean hue value of region of interest (ROI) in each image were calculated respectively. The final diagnosis of lymph node was based on the pathologic/microbiologic results of EBUS-TBNA, pathologic/microbiologic results of other examinations and clinical following-up. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy were evaluated for distinguishing malignant and benign lesions. Results: Fifty-six patients and 68 lymph nodes were enrolled in this study, of which 35 lymph nodes were malignant and 33 lymph nodes were benign. The stiff area ratio and mean hue value of benign and malignant lesions were 0.32±0.29, 0.62±0.20 and 109.99±28.13, 141.62±17.52, respectively, and statistical differences were found in both of those two methods ( t =-5.14, P <0.01; t =-5.53, P <0.01). The area under curves was 0.813, 0.814 in stiff area ratio and mean hue value, respectively. The optimal diagnostic cut-off value of stiff area ratio was 0.48, and the sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 82.86%, 81.82%, 82.86%, 81.82% and 82.35%, respectively. The optimal diagnostic cut-off value of mean hue value was 126.28, and the sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 85.71%, 75.76%, 78.95%, 83.33% and 80.88%, respectively. Conclusion: Both the stiff area ratio and mean hue value methods can be used for analyzing EBUS-RTE images quantitatively, having the value of differentiating benign and malignant intrathoracic lymph nodes, and the stiff area ratio is better than the mean hue value between the two methods.

Polar body based aneuploidy screening is poorly predictive of embryo ploidy and reproductive potential.

PubMed

Salvaggio, C N; Forman, E J; Garnsey, H M; Treff, N R; Scott, R T

2014-09-01

Polar body (polar body) biopsy represents one possible solution to performing comprehensive chromosome screening (CCS). This study adds to what is known about the predictive value of polar body based testing for the genetic status of the resulting embryo, but more importantly, provides the first evaluation of the predictive value for actual clinical outcomes after embryo transfer. SNP array was performed on first polar body, second polar body, and either a blastomere or trophectoderm biopsy, or the entire arrested embryo. Concordance of the polar body-based prediction with the observed diagnoses in the embryos was assessed. In addition, the predictive value of the polar body -based diagnosis for the specific clinical outcome of transferred embryos was evaluated through the use of DNA fingerprinting to track individual embryos. There were 459 embryos analyzed from 96 patients with a mean maternal age of 35.3. The polar body-based predictive value for the embryo based diagnosis was 70.3%. The blastocyst implantation predictive value of a euploid trophectoderm was higher than from euploid polar bodies (51% versus 40%). The cleavage stage embryo implantation predictive value of a euploid blastomere was also higher than from euploid polar bodies (31% versus 22%). Polar body based aneuploidy screening results were less predictive of actual clinical outcomes than direct embryo assessment and may not be adequate to improve sustained implantation rates. In nearly one-third of cases the polar body based analysis failed to predict the ploidy of the embryo. This imprecision may hinder efforts for polar body based CCS to improve IVF clinical outcomes.

[Predictive value of qualitative assessment of general movements for adverse outcomes at 24 months of age in infants with asphyxia].

PubMed

Chen, Nan; Wen, Xiao-Hong; Huang, Jin-Hua; Wang, Shui-Yun; Zhu, Yue-E

2015-12-01

To investigate the predictive value of the qualitative assessment of general movements (GMs) for adverse outcomes at 24 months of age in full-term infants with asphyxia. A total of 114 full-term asphyxiated infants, who were admitted to the neonatal intensive care unit between 2009 and 2012 and took part in follow-ups after discharge were included in the study. All of them received the qualitative assessment of GMs within 3 months after birth. The development quotient was determined with the Bayley Scales of Infant Development at 24 months of age. The results of the qualitative assessment of GMs within 3 months after birth showed that among 114 infants, 20 (17.5%) had poor repertoire movements and 7 (6.1%) had cramped-synchronized movements during the writhing movements period; 8 infants (7.0%) had the absence of fidgety movements during the fidgety movements period. The results of development quotient at 24 months of age showed that 7 infants (6.1%) had adverse developmental outcomes: 6 cases of cerebral palsy and mental retardation and 1 case of mental retardation. There was a poor consistency between poor repertoire movements during the writhing movements period and the developmental outcomes at 24 months of age (Kappa=-0.019; P>0.05). There was a high consistency between cramped-synchronized movements during the writhing movements period and the developmental outcomes at 24 months of age (Kappa=0.848; P<0.05), and the results of predictive values of cramped-synchronized movements were shown as follows: predictive validity 98.2%, sensitivity 85.7%, specificity 99.1%, positive predictive value 85.7%, and negative predictive value 99.1%. There was a high consistency between the absence of fidgety movements during the fidgety movements period and the developmental outcomes at 24 months of age (Kappa=0.786; P<0.05), and its predictive values were expressed as follows: predictive validity 97.4%, sensitivity 85.7%, specificity 98.1%, positive predictive value 75.0%, and negative predictive value 99.1%. Cramped-synchronized movements and absence of fidgety movements can predict adverse developmental outcomes at 24 months of age in full-term infants with asphyxia.

Methods of developing core collections based on the predicted genotypic value of rice ( Oryza sativa L.).

PubMed

Li, C T; Shi, C H; Wu, J G; Xu, H M; Zhang, H Z; Ren, Y L

2004-04-01

The selection of an appropriate sampling strategy and a clustering method is important in the construction of core collections based on predicted genotypic values in order to retain the greatest degree of genetic diversity of the initial collection. In this study, methods of developing rice core collections were evaluated based on the predicted genotypic values for 992 rice varieties with 13 quantitative traits. The genotypic values of the traits were predicted by the adjusted unbiased prediction (AUP) method. Based on the predicted genotypic values, Mahalanobis distances were calculated and employed to measure the genetic similarities among the rice varieties. Six hierarchical clustering methods, including the single linkage, median linkage, centroid, unweighted pair-group average, weighted pair-group average and flexible-beta methods, were combined with random, preferred and deviation sampling to develop 18 core collections of rice germplasm. The results show that the deviation sampling strategy in combination with the unweighted pair-group average method of hierarchical clustering retains the greatest degree of genetic diversities of the initial collection. The core collections sampled using predicted genotypic values had more genetic diversity than those based on phenotypic values.

Correlation of clinical predictions and surgical results in maxillary superior repositioning.

PubMed

Tabrizi, Reza; Zamiri, Barbad; Kazemi, Hamidreza

2014-05-01

This is a prospective study to evaluate the accuracy of clinical predictions related to surgical results in subjects who underwent maxillary superior repositioning without anterior-posterior movement. Surgeons' predictions according to clinical (tooth show at rest and at the maximum smile) and cephalometric evaluation were documented for the amount of maxillary superior repositioning. Overcorrection or undercorrection was documented for every subject 1 year after the operations. Receiver operating characteristic curve test was used to find a cutoff point in prediction errors and to determine positive predictive value (PPV) and negative predictive value. Forty subjects (14 males and 26 females) were studied. Results showed a significant difference between changes in the tooth show at rest and at the maximum smile line before and after surgery. Analysis of the data demonstrated no correlation between the predictive data and the surgical results. The incidence of undercorrection (25%) was more common than overcorrection (7.5%). The cutoff point for errors in predictions was 5 mm for tooth show at rest and 15 mm at the maximum smile. When the amount of the presurgical tooth show at rest was more than 5 mm, 50.5% of clinical predictions did not match the clinical results (PPV), and 75% of clinical predictions showed the same results when the tooth show was less than 5 mm (negative predictive value). When the amount of presurgical tooth shown in the maximum smile line was more than 15 mm, 75% of clinical predictions did not match with clinical results (PPV), and 25% of the predictions had the same results because the tooth show at the maximum smile was lower than 15 mm. Clinical predictions according to the tooth show at rest and at the maximum smile have a poor correlation with clinical results in maxillary superior repositioning for vertical maxillary excess. The risk of errors in predictions increased when the amount of superior repositioning of the maxilla increased. Generally, surgeons have a tendency to undercorrect rather than overcorrect, although clinical prediction is an original guideline for surgeons, and it may be associated with variable clinical results.

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

PubMed Central

Craig, Benjamin M.

2015-01-01

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

Should bedside sonography be used first to diagnose pneumothorax secondary to blunt trauma?

PubMed

Donmez, Halil; Tokmak, Turgut Tursem; Yildirim, Afra; Buyukoglan, Hakan; Ozturk, Mehmet; Yaşar Ayaz, Umit; Mavili, Ertugrul

2012-01-01

BACKGROUND.: Our purpose was to evaluate the effectiveness of bedside sonography (US) in the detection of pneumothorax secondary to blunt thoracic trauma. METHODS.: In this prospective study, 240 hemithoraces of 120 consecutive patients with multiple trauma were evaluated with chest radiographs (CXR) and bedside thoracic US for the diagnosis of pneumothorax. CT examinations were performed in 68 patients. Fifty-two patients who did not undergo CT examinations were excluded from the study. US examinations were performed independently at bedside by two radiologists who were not informed about CXR and CT findings. CXRs were interpreted by two radiologists who were unaware of the US and CT results. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of CXR and US were calculated. RESULTS.: One hundred thirty-six hemithoraces were assessed in 68 patients. A total of 35 pneumothoraces were detected in 33 patients. On US, the diagnosis of pneumothorax was correct in 32 hemithoraces. In 98 hemithoraces without pneumothorax, US was normal. With US examination, there were three false-positive and three false-negative results. The sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy of US were 91.4%, 97%, 91.4%, 97%, and 97%, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of CXR were 82.7%, 89.7%, 68.5%, 95%, and 89.5%, respectively. CONCLUSIONS.: Bedside thoracic US is an accurate method that can be used in trauma patients instead of CXR for the detection of pneumothorax. Copyright © 2012 Wiley Periodicals, Inc.

Prediction of anaerobic power values from an abbreviated WAnT protocol.

PubMed

Stickley, Christopher D; Hetzler, Ronald K; Kimura, Iris F

2008-05-01

The traditional 30-second Wingate anaerobic test (WAnT) is a widely used anaerobic power assessment protocol. An abbreviated protocol has been shown to decrease the mild to severe physical discomfort often associated with the WAnT. Therefore, the purpose of this study was to determine whether a 20-second WAnT protocol could be used to accurately predict power values of a standard 30-second WAnT. In 96 college females, anaerobic power variables were assessed using a standard 30-second WAnT protocol. Maximum power values as well as instantaneous power at 10, 15, and 20 seconds were recorded. Based on these results, stepwise regression analysis was performed to determine the accuracy with which mean power, minimum power, 30-second power, and percentage of fatigue for a standard 30-second WAnT could be predicted from values obtained during the first 20 seconds of testing. Mean power values showed the highest level of predictability (R2 = 0.99) from the 20-second values. Minimum power, 30-second power, and percentage of fatigue also showed high levels of predictability (R2 = 0.91, 0.84, and 0.84, respectively) using only values obtained during the first 20 seconds of the protocol. An abbreviated (20-second) WAnT protocol appears to effectively predict results of a standard 30-second WAnT in college-age females, allowing for comparison of data to published norms. A shortened test may allow for a decrease in unwanted side effects associated with the traditional WAnT protocol.

Naked-eye inspection of the cervix after acetic acid application may improve the predictive value of negative cytologic screening.

PubMed

Frisch, L E; Milner, F H; Ferris, D G

1994-11-01

The purpose of this study was to assess the predictive value of naked-eye inspection of the cervix (NIC) after acetic acid application as an adjunct to Papanicolaou (Pap) testing for cervical cancer screening. Study subjects were women attending a medical college student health clinic either for cervical cytologic screening (67%) or because of a recent atypical cytologic screening result (33%). All study participants received cytologic screening, cervicography, and NIC. Of the 95 patients, 71 (75%) had abnormal findings on NIC. Fifty-one patients underwent colposcopy with biopsy, including 48 of the 71 with an abnormal finding on NIC. The results of 40 of the biopsies were abnormal: 36 showed human papillomavirus or low-grade squamous intraepithelial lesions, 3 showed high-grade squamous intraepithelial lesions, and 1 showed invasive cervical cancer. Sixty-five percent (26) of the abnormal biopsy findings occurred in women with normal cytologic test results. NIC and cervicography both were effective in identifying patients with abnormalities, but the combination of NIC followed by cervicography referred fewer women for colposcopy than did a positive result on NIC alone (52% vs 75%). The combination of a negative Pap smear and a negative NIC result had a 91% predictive value for the absence of cervical intraepithelial neoplasia. This was a significant improvement over cytologic screening alone. In this study, the combination of cytologic screening (Pap smear) and NIC increased the screening yield as compared with a Pap smear alone but with some loss of positive predictive value. NIC significantly improved the predictive value of negative cytologic screening results.

Computational prediction of ionic liquid 1-octanol/water partition coefficients.

PubMed

Kamath, Ganesh; Bhatnagar, Navendu; Baker, Gary A; Baker, Sheila N; Potoff, Jeffrey J

2012-04-07

Wet 1-octanol/water partition coefficients (log K(ow)) predicted for imidazolium-based ionic liquids using adaptive bias force-molecular dynamics (ABF-MD) simulations lie in excellent agreement with experimental values. These encouraging results suggest prospects for this computational tool in the a priori prediction of log K(ow) values of ionic liquids broadly with possible screening implications as well (e.g., prediction of CO(2)-philic ionic liquids).

Hierarchical time series bottom-up approach for forecast the export value in Central Java

NASA Astrophysics Data System (ADS)

Mahkya, D. A.; Ulama, B. S.; Suhartono

2017-10-01

The purpose of this study is Getting the best modeling and predicting the export value of Central Java using a Hierarchical Time Series. The export value is one variable injection in the economy of a country, meaning that if the export value of the country increases, the country’s economy will increase even more. Therefore, it is necessary appropriate modeling to predict the export value especially in Central Java. Export Value in Central Java are grouped into 21 commodities with each commodity has a different pattern. One approach that can be used time series is a hierarchical approach. Hierarchical Time Series is used Buttom-up. To Forecast the individual series at all levels using Autoregressive Integrated Moving Average (ARIMA), Radial Basis Function Neural Network (RBFNN), and Hybrid ARIMA-RBFNN. For the selection of the best models used Symmetric Mean Absolute Percentage Error (sMAPE). Results of the analysis showed that for the Export Value of Central Java, Bottom-up approach with Hybrid ARIMA-RBFNN modeling can be used for long-term predictions. As for the short and medium-term predictions, it can be used a bottom-up approach RBFNN modeling. Overall bottom-up approach with RBFNN modeling give the best result.

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

NASA Technical Reports Server (NTRS)

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

1979-01-01

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

Model for forecasting Olea europaea L. airborne pollen in South-West Andalusia, Spain

NASA Astrophysics Data System (ADS)

Galán, C.; Cariñanos, Paloma; García-Mozo, Herminia; Alcázar, Purificación; Domínguez-Vilches, Eugenio

Data on predicted average and maximum airborne pollen concentrations and the dates on which these maximum values are expected are of undoubted value to allergists and allergy sufferers, as well as to agronomists. This paper reports on the development of predictive models for calculating total annual pollen output, on the basis of pollen and weather data compiled over the last 19 years (1982-2000) for Córdoba (Spain). Models were tested in order to predict the 2000 pollen season; in addition, and in view of the heavy rainfall recorded in spring 2000, the 1982-1998 data set was used to test the model for 1999. The results of the multiple regression analysis show that the variables exerting the greatest influence on the pollen index were rainfall in March and temperatures over the months prior to the flowering period. For prediction of maximum values and dates on which these values might be expected, the start of the pollen season was used as an additional independent variable. Temperature proved the best variable for this prediction. Results improved when the 5-day moving average was taken into account. Testing of the predictive model for 1999 and 2000 yielded fairly similar results. In both cases, the difference between expected and observed pollen data was no greater than 10%. However, significant differences were recorded between forecast and expected maximum and minimum values, owing to the influence of rainfall during the flowering period.

Comparison of predictability for human pharmacokinetics parameters among monkeys, rats, and chimeric mice with humanised liver.

PubMed

Miyamoto, Maki; Iwasaki, Shinji; Chisaki, Ikumi; Nakagawa, Sayaka; Amano, Nobuyuki; Hirabayashi, Hideki

2017-12-01

1. The aim of the present study was to evaluate the usefulness of chimeric mice with humanised liver (PXB mice) for the prediction of clearance (CL t ) and volume of distribution at steady state (Vd ss ), in comparison with monkeys, which have been reported as a reliable model for human pharmacokinetics (PK) prediction, and with rats, as a conventional PK model. 2. CL t and Vd ss values in PXB mice, monkeys and rats were determined following intravenous administration of 30 compounds known to be mainly eliminated in humans via the hepatic metabolism by various drug-metabolising enzymes. Using single-species allometric scaling, human CL t and Vd ss values were predicted from the three animal models. 3. Predicted CL t values from PXB mice exhibited the highest predictability: 25 for PXB mice, 21 for monkeys and 14 for rats were predicted within a three-fold range of actual values among 30 compounds. For predicted human Vd ss values, the number of compounds falling within a three-fold range was 23 for PXB mice, 24 for monkeys, and 16 for rats among 29 compounds. PXB mice indicated a higher predictability for CL t and Vd ss values than the other animal models. 4. These results demonstrate the utility of PXB mice in predicting human PK parameters.

Three-dimensional computed tomographic volumetry precisely predicts the postoperative pulmonary function.

PubMed

Kobayashi, Keisuke; Saeki, Yusuke; Kitazawa, Shinsuke; Kobayashi, Naohiro; Kikuchi, Shinji; Goto, Yukinobu; Sakai, Mitsuaki; Sato, Yukio

2017-11-01

It is important to accurately predict the patient's postoperative pulmonary function. The aim of this study was to compare the accuracy of predictions of the postoperative residual pulmonary function obtained with three-dimensional computed tomographic (3D-CT) volumetry with that of predictions obtained with the conventional segment-counting method. Fifty-three patients scheduled to undergo lung cancer resection, pulmonary function tests, and computed tomography were enrolled in this study. The postoperative residual pulmonary function was predicted based on the segment-counting and 3D-CT volumetry methods. The predicted postoperative values were compared with the results of postoperative pulmonary function tests. Regarding the linear correlation coefficients between the predicted postoperative values and the measured values, those obtained using the 3D-CT volumetry method tended to be higher than those acquired using the segment-counting method. In addition, the variations between the predicted and measured values were smaller with the 3D-CT volumetry method than with the segment-counting method. These results were more obvious in COPD patients than in non-COPD patients. Our findings suggested that the 3D-CT volumetry was able to predict the residual pulmonary function more accurately than the segment-counting method, especially in patients with COPD. This method might lead to the selection of appropriate candidates for surgery among patients with a marginal pulmonary function.

Validation of diabetes mellitus and hypertension diagnosis in computerized medical records in primary health care

PubMed Central

2011-01-01

Background Computerized Clinical Records, which are incorporated in primary health care practice, have great potential for research. In order to use this information, data quality and reliability must be assessed to prevent compromising the validity of the results. The aim of this study is to validate the diagnosis of hypertension and diabetes mellitus in the computerized clinical records of primary health care, taking the diagnosis criteria established in the most prominently used clinical guidelines as the gold standard against which what measure the sensitivity, specificity, and determine the predictive values. The gold standard for diabetes mellitus was the diagnostic criteria established in 2003 American Diabetes Association Consensus Statement for diabetic subjects. The gold standard for hypertension was the diagnostic criteria established in the Joint National Committee published in 2003. Methods A cross-sectional multicentre validation study of diabetes mellitus and hypertension diagnoses in computerized clinical records of primary health care was carried out. Diagnostic criteria from the most prominently clinical practice guidelines were considered for standard reference. Sensitivity, specificity, positive and negative predictive values, and global agreement (with kappa index), were calculated. Results were shown overall and stratified by sex and age groups. Results The agreement for diabetes mellitus with the reference standard as determined by the guideline was almost perfect (κ = 0.990), with a sensitivity of 99.53%, a specificity of 99.49%, a positive predictive value of 91.23% and a negative predictive value of 99.98%. Hypertension diagnosis showed substantial agreement with the reference standard as determined by the guideline (κ = 0.778), the sensitivity was 85.22%, the specificity 96.95%, the positive predictive value 85.24%, and the negative predictive value was 96.95%. Sensitivity results were worse in patients who also had diabetes and in those aged 70 years or over. Conclusions Our results substantiate the validity of using diagnoses of diabetes and hypertension found within the computerized clinical records for epidemiologic studies. PMID:22035202

Interleukin (IL)-1A and IL-6: Applications to the predictive diagnostic testing of radiation pneumonitis

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

Chen Yuhchyau; Hyrien, Ollivier; Williams, Jacqueline

2005-05-01

Purpose: To explore the application of interleukin (IL)-1{alpha} and IL-6 measurements in the predictive diagnostic testing for symptomatic radiation pneumonitis (RP). Methods and materials: In a prospective protocol investigating RP and cytokines, IL-1{alpha} and IL-6 values were analyzed by enzyme-linked immunosorbent assay from serial weekly blood samples of patients receiving chest radiation. We analyzed sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) over selected threshold values for both cytokines in the application to diagnostic testing. Results: The average coefficient of variation was 51% of the weekly mean IL-1{alpha} level and 39% of the weekly mean IL-6 value.more » Interleukin 1{alpha} and IL-6 became positively correlated with time. Specificity for both cytokines was better than sensitivity. IL-6 globally outperformed IL-1{alpha} in predicting RP, with higher PPV and NPV. Conclusions: Our data demonstrate the feasibility of applying IL-1{alpha} and IL-6 measurements of blood specimens to predict RP. Interleukin-6 measurements offer stronger positive predictive value than IL-1{alpha}. This application might be further explored in a larger sample of patients.« less

A performance test of the log and tree grades for eastern white pine

Treesearch

Robert L. Brisbin

1972-01-01

The results of testing the Forest Service standard tree grades and sawlog grades for eastern white pine on an independent sample of 75 trees and 299 logs in southwestern Maine. The total predicted value of the 75 trees was 3 percent higher than the actual value. The total predicted value of the 299 logs was 2 percent higher than the actual value. The differences...

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

PubMed

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

2015-10-01

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

Results of the two incidence screenings in the National Lung Screening Trial.

PubMed

Aberle, Denise R; DeMello, Sarah; Berg, Christine D; Black, William C; Brewer, Brenda; Church, Timothy R; Clingan, Kathy L; Duan, Fenghai; Fagerstrom, Richard M; Gareen, Ilana F; Gatsonis, Constantine A; Gierada, David S; Jain, Amanda; Jones, Gordon C; Mahon, Irene; Marcus, Pamela M; Rathmell, Joshua M; Sicks, JoRean

2013-09-05

The National Lung Screening Trial was conducted to determine whether three annual screenings (rounds T0, T1, and T2) with low-dose helical computed tomography (CT), as compared with chest radiography, could reduce mortality from lung cancer. We present detailed findings from the first two incidence screenings (rounds T1 and T2). We evaluated the rate of adherence of the participants to the screening protocol, the results of screening and downstream diagnostic tests, features of the lung-cancer cases, and first-line treatments, and we estimated the performance characteristics of both screening methods. At the T1 and T2 rounds, positive screening results were observed in 27.9% and 16.8% of participants in the low-dose CT group and in 6.2% and 5.0% of participants in the radiography group, respectively. In the low-dose CT group, the sensitivity was 94.4%, the specificity was 72.6%, the positive predictive value was 2.4%, and the negative predictive value was 99.9% at T1; at T2, the positive predictive value increased to 5.2%. In the radiography group, the sensitivity was 59.6%, the specificity was 94.1%, the positive predictive value was 4.4%, and the negative predictive value was 99.8% at T1; both the sensitivity and the positive predictive value increased at T2. Among lung cancers of known stage, 87 (47.5%) were stage IA and 57 (31.1%) were stage III or IV in the low-dose CT group at T1; in the radiography group, 31 (23.5%) were stage IA and 78 (59.1%) were stage III or IV at T1. These differences in stage distribution between groups persisted at T2. Low-dose CT was more sensitive in detecting early-stage lung cancers, but its measured positive predictive value was lower than that of radiography. As compared with radiography, the two annual incidence screenings with low-dose CT resulted in a decrease in the number of advanced-stage cancers diagnosed and an increase in the number of early-stage lung cancers diagnosed. (Funded by the National Cancer Institute; NLST ClinicalTrials.gov number, NCT00047385.).

Predicting Air Quality at First Ingress into Vehicles Visiting the International Space Station.

PubMed

Romoser, Amelia A; Scully, Robert R; Limero, Thomas F; De Vera, Vanessa; Cheng, Patti F; Hand, Jennifer J; James, John T; Ryder, Valerie E

2017-02-01

NASA regularly performs ground-based offgas tests (OGTs), which allow prediction of accumulated volatile pollutant concentrations at first entry on orbit, on whole modules and vehicles scheduled to connect to the International Space Station (ISS). These data guide crew safety operations and allow for estimation of ISS air revitalization systems impact from additional pollutant load. Since volatiles released from vehicle, module, and payload materials can affect crew health and performance, prediction of first ingress air quality is important. To assess whether toxicological risk is typically over or underpredicted, OGT and first ingress samples from 10 vehicles and modules were compared. Samples were analyzed by gas chromatography and gas chromatography-mass spectrometry. The rate of pollutant accumulation was extrapolated over time. Ratios of analytical values and Spacecraft Maximum Allowable Concentrations were used to predict total toxicity values (T-values) at first entry. Results were also compared by compound. Frequently overpredicted was 2-butanone (9/10), whereas propanal (6/10) and ethanol (8/10) were typically underpredicted, but T-values were not substantially affected. Ingress sample collection delay (estimated by octafluoropropane introduced from ISS atmosphere) and T-value prediction accuracy correlated well (R2 = 0.9008), highlighting the importance of immediate air sample collection and accounting for ISS air dilution. Importantly, T-value predictions were conservative 70% of the time. Results also suggest that T-values can be normalized to octafluoropropane levels to adjust for ISS air dilution at first ingress. Finally, OGT and ingress sampling has allowed small leaks in vehicle fluid systems to be recognized and addressed.Romoser AA, Scully RR, Limero TF, De Vera V, Cheng PF, Hand JJ, James JT, Ryder VE. Predicting air quality at first ingress into vehicles visiting the International Space Station. Aerosp Med Hum Perform. 2017; 88(2):104-113.

Prediction of beta-turns from amino acid sequences using the residue-coupled model.

PubMed

Guruprasad, K; Shukla, S

2003-04-01

We evaluated the prediction of beta-turns from amino acid sequences using the residue-coupled model with an enlarged representative protein data set selected from the Protein Data Bank. Our results show that the probability values derived from a data set comprising 425 protein chains yielded an overall beta-turn prediction accuracy 68.74%, compared with 94.7% reported earlier on a data set of 30 proteins using the same method. However, we noted that the overall beta-turn prediction accuracy using probability values derived from the 30-protein data set reduces to 40.74% when tested on the data set comprising 425 protein chains. In contrast, using probability values derived from the 425 data set used in this analysis, the overall beta-turn prediction accuracy yielded consistent results when tested on either the 30-protein data set (64.62%) used earlier or a more recent representative data set comprising 619 protein chains (64.66%) or on a jackknife data set comprising 476 representative protein chains (63.38%). We therefore recommend the use of probability values derived from the 425 representative protein chains data set reported here, which gives more realistic and consistent predictions of beta-turns from amino acid sequences.

In monkeys making value-based decisions, amygdala neurons are sensitive to cue value as distinct from cue salience.

PubMed

Leathers, Marvin L; Olson, Carl R

2017-04-01

Neurons in the lateral intraparietal (LIP) area of macaque monkey parietal cortex respond to cues predicting rewards and penalties of variable size in a manner that depends on the motivational salience of the predicted outcome (strong for both large reward and large penalty) rather than on its value (positive for large reward and negative for large penalty). This finding suggests that LIP mediates the capture of attention by salient events and does not encode value in the service of value-based decision making. It leaves open the question whether neurons elsewhere in the brain encode value in the identical task. To resolve this issue, we recorded neuronal activity in the amygdala in the context of the task employed in the LIP study. We found that responses to reward-predicting cues were similar between areas, with the majority of reward-sensitive neurons responding more strongly to cues that predicted large reward than to those that predicted small reward. Responses to penalty-predicting cues were, however, markedly different. In the amygdala, unlike LIP, few neurons were sensitive to penalty size, few penalty-sensitive neurons favored large over small penalty, and the dependence of firing rate on penalty size was negatively correlated with its dependence on reward size. These results indicate that amygdala neurons encoded cue value under circumstances in which LIP neurons exhibited sensitivity to motivational salience. However, the representation of negative value, as reflected in sensitivity to penalty size, was weaker than the representation of positive value, as reflected in sensitivity to reward size. NEW & NOTEWORTHY This is the first study to characterize amygdala neuronal responses to cues predicting rewards and penalties of variable size in monkeys making value-based choices. Manipulating reward and penalty size allowed distinguishing activity dependent on motivational salience from activity dependent on value. This approach revealed in a previous study that neurons of the lateral intraparietal (LIP) area encode motivational salience. Here, it reveals that amygdala neurons encode value. The results establish a sharp functional distinction between the two areas. Copyright © 2017 the American Physiological Society.

Can blood and semen presepsin levels in males predict pregnancy in couples undergoing intra-cytoplasmic sperm injection?

PubMed Central

Ovayolu, Ali; Arslanbuğa, Cansev Yilmaz; Gun, Ismet; Devranoglu, Belgin; Ozdemir, Arman; Cakar, Sule Eren

2016-01-01

Objective: To determine whether semen and plasma presepsin values measured in men with normozoospermia and oligoasthenospermia undergoing invitro-fertilization would be helpful in predicting ongoing pregnancy and live birth. Methods: Group-I was defined as patients who had pregnancy after treatment and Group-II comprised those with no pregnancy. Semen and blood presepsin values were subsequently compared between the groups. Parametric comparisons were performed using Student’s t-test, and non-parametric comparisons were conducted using the Mann-Whitney U test. Results: There were 42 patients in Group-I and 72 in Group-II. In the context of successful pregnancy and live birth, semen presepsin values were statistically significantly higher in Group-I than in Group-II (p= 0.004 and p= 0.037, respectively). The most appropriate semen presepsin cut-off value for predicting both ongoing pregnancy and live birth was calculated as 199 pg/mL. Accordingly, their sensitivity was 64.5% to 59.3%, their specificity was 57.0% to 54.2%, and their positive predictive value was 37.0% to 29.6%, respectively; their negative predictive value was 80.4% in both instances. Conclusion: Semen presepsin values could be a new marker that may enable the prediction of successful pregnancy and/or live birth. Its negative predictive values are especially high. PMID:27882005

The utility of kindergarten teacher ratings for predicting low academic achievement in first grade.

PubMed

Teisl, J T; Mazzocco, M M; Myers, G F

2001-01-01

The purpose of this study was to assess the predictive value of kindergarten teachers' ratings of pupils for later first-grade academic achievement. Kindergarten students were rated by their teachers on a variety of variables, including math and reading performance, teacher concerns, and amount of learning relative to peers. These variables were then analyzed with respect to outcome measures for math and reading ability administered in the first grade. The teachers' ratings of academic performance were significantly correlated with scores on the outcome measures. Analyses were also carried out to determine sensitivity, specificity, and predictive values of the different teacher ratings. The results indicated high overall accuracy, sensitivity, specificity, and negative predictive value for the ratings. Positive predictive value tended to be lower. A recommendation to follow from these results is that teacher ratings of this sort be used to determine which children should receive cognitive screening measures to further enhance identification of children at risk for learning disability. However, this recommendation is limited by the lack of empirically supported screening measures for math disability versus well-supported screening tools for reading disability.

Theoretical versus experimental results for the rotordynamic coefficients of eccentric, smooth, gas annular seal annular gas seals

NASA Technical Reports Server (NTRS)

Childs, Dara W.; Alexander, Chis

1994-01-01

This viewgraph presentation presents the following results: (1) The analytical results overpredict the experimental results for the direct stiffness values and incorrectly predict increasing stiffness with decreasing pressure ratios. (2) Theory correctly predicts increasing cross-coupled stiffness, K(sub YX), with increasing eccentricity and inlet preswirl. (3) Direct damping, C(sub XX), underpredicts the experimental results, but the analytical results do correctly show that damping increases with increasing eccentricity. (4) The whirl frequency values predicted by theory are insensitive to changes in the static eccentricity ratio. Although these values match perfectly with the experimental results at 16,000 rpm, the results at the lower speed do not correspond. (5) Theoretical and experimental mass flow rates match at 5000 rpm, but at 16,000 rpm the theoretical results overpredict the experimental mass flow rates. (6) Theory correctly shows the linear pressure profiles and the associated entrance losses with the specified rotor positions.

A prospective analysis of physical examination findings in the diagnosis of facial fractures: Determining predictive value.

PubMed

Timashpolsky, Alisa; Dagum, Alexander B; Sayeed, Syed M; Romeiser, Jamie L; Rosenfeld, Elisheva A; Conkling, Nicole

2016-01-01

There are >150,000 patient visits per year to emergency rooms for facial trauma. The reliability of a computed tomography (CT) scan has made it the primary modality for diagnosing facial skeletal injury, with the physical examination playing more a cursory role. Knowing the predictive value of physical findings in facial skeletal injuries may enable more appropriate use of imaging and health care resources. A blinded prospective study was undertaken to assess the predictive value of physical examination findings in detecting maxillofacial fracture in trauma patients, and in determining whether a patient will require surgical intervention. Over a four-month period, the authors' team examined patients admitted with facial trauma to the emergency department of their hospital. The evaluating physician completed a standardized physical examination evaluation form indicating the physical findings. Corresponding CT scans and surgical records were then reviewed, and the results recorded by a plastic surgeon who was blinded to the results of the physical examination. A total of 57 patients met the inclusion criteria; there were 44 male and 13 female patients. The sensitivity, specificity, positive predictive value and negative predictive value of grouped physical examination findings were determined in major areas. In further analysis, specific examination findings with n≥9 (15%) were also reported. The data demonstrated a high negative predictive value of at least 90% for orbital floor, zygomatic, mandibular and nasal bone fractures compared with CT scan. Furthermore, none of the patients who did not have a physical examination finding for a particular facial fracture required surgery for that fracture. Thus, the instrument performed well at ruling out fractures in these areas when there were none. Ultimately, these results may help reduce unnecessary radiation and costly imaging in patients with facial trauma without facial fractures.

Optical coherence tomography in the diagnosis of dysplasia and adenocarcinoma in Barret's esophagus

NASA Astrophysics Data System (ADS)

Gladkova, N. D.; Zagaynova, E. V.; Zuccaro, G.; Kareta, M. V.; Feldchtein, F. I.; Balalaeva, I. V.; Balandina, E. B.

2007-02-01

Statistical analysis of endoscopic optical coherence tomography (EOCT) surveillance of 78 patients with Barrett's esophagus (BE) is presented in this study. The sensitivity of OCT device in retrospective open detection of early malignancy (including high grade dysplasia and intramucosal adenocarcinoma (IMAC)) was 75%, specificity 82%, diagnostic accuracy - 80%, positive predictive value- 60%, negative predictive value- 87%. In the open recognition of IMAC sensitivity was 81% and specificity were 85% each. Results of a blind recognition with the same material were similar: sensitivity - 77%, specificity 85%, diagnostic accuracy - 82%, positive predictive value- 70%, negative predictive value- 87%. As the endoscopic detection of early malignancy is problematic, OCT holds great promise in enhancing the diagnostic capability of clinical GI endoscopy.

NUCLEAR AND HEAVY ION PHYSICS: α-decay half-lives of superheavy nuclei and general predictions

NASA Astrophysics Data System (ADS)

Dong, Jian-Min; Zhang, Hong-Fei; Wang, Yan-Zhao; Zuo, Wei; Su, Xin-Ning; Li, Jun-Qing

2009-08-01

The generalized liquid drop model (GLDM) and the cluster model have been employed to calculate the α-decay half-lives of superheavy nuclei (SHN) using the experimental α-decay Q values. The results of the cluster model are slightly poorer than those from the GLDM if experimental Q values are used. The prediction powers of these two models with theoretical Q values from Audi et al. (QAudi) and Muntian et al. (QM) have been tested to find that the cluster model with QAudi and QM could provide reliable results for Z > 112 but the GLDM with QAudi for Z <= 112. The half-lives of some still unknown nuclei are predicted by these two models and these results may be useful for future experimental assignment and identification.

Ultimate pier and contraction scour prediction in cohesive soils at selected bridges in Illinois

USGS Publications Warehouse

Straub, Timothy D.; Over, Thomas M.; Domanski, Marian M.

2013-01-01

The Scour Rate In COhesive Soils-Erosion Function Apparatus (SRICOS-EFA) method includes an ultimate scour prediction that is the equilibrium maximum pier and contraction scour of cohesive soils over time. The purpose of this report is to present the results of testing the ultimate pier and contraction scour methods for cohesive soils on 30 bridge sites in Illinois. Comparison of the ultimate cohesive and noncohesive methods, along with the Illinois Department of Transportation (IDOT) cohesive soil reduction-factor method and measured scour are presented. Also, results of the comparison of historic IDOT laboratory and field values of unconfined compressive strength of soils (Qu) are presented. The unconfined compressive strength is used in both ultimate cohesive and reduction-factor methods, and knowing how the values from field methods compare to the laboratory methods is critical to the informed application of the methods. On average, the non-cohesive method results predict the highest amount of scour, followed by the reduction-factor method results; and the ultimate cohesive method results predict the lowest amount of scour. The 100-year scour predicted for the ultimate cohesive, noncohesive, and reduction-factor methods for each bridge site and soil are always larger than observed scour in this study, except 12% of predicted values that are all within 0.4 ft of the observed scour. The ultimate cohesive scour prediction is smaller than the non-cohesive scour prediction method for 78% of bridge sites and soils. Seventy-six percent of the ultimate cohesive predictions show a 45% or greater reduction from the non-cohesive predictions that are over 10 ft. Comparing the ultimate cohesive and reduction-factor 100-year scour predictions methods for each bridge site and soil, the scour predicted by the ultimate cohesive scour prediction method is less than the reduction-factor 100-year scour prediction method for 51% of bridge sites and soils. Critical shear stress remains a needed parameter in the ultimate scour prediction for cohesive soils. The unconfined soil compressive strength measured by IDOT in the laboratory was found to provide a good prediction of critical shear stress, as measured by using the erosion function apparatus in a previous study. Because laboratory Qu analyses are time-consuming and expensive, the ability of field-measured Rimac data to estimate unconfined soil strength in the critical shear–soil strength relation was tested. A regression analysis was completed using a historic IDOT dataset containing 366 data pairs of laboratory Qu and field Rimac measurements from common sites with cohesive soils. The resulting equations provide a point prediction of Qu, given any Rimac value with the 90% confidence interval. The prediction equations are not significantly different from the identity Qu = Rimac. The alternative predictions of ultimate cohesive scour presented in this study assume Qu will be estimated using Rimac measurements that include computed uncertainty. In particular, the ultimate cohesive predicted scour is greater than observed scour for the entire 90% confidence interval range for predicting Qu at the bridges and soils used in this study, with the exception of the six predicted values that are all within 0.6 ft of the observed scour.

The efficacy of the reverse contrast mode in digital radiography for the detection of proximal dentinal caries

PubMed Central

Miri, Shimasadat; Mehralizadeh, Sandra; Sadri, Donya; Motamedi, Mahmood Reza Kalantar

2015-01-01

Purpose This study evaluated the diagnostic accuracy of the reverse contrast mode in intraoral digital radiography for the detection of proximal dentinal caries, in comparison with the original digital radiographs. Materials and Methods Eighty extracted premolars with no clinically apparent caries were selected, and digital radiographs of them were taken separately in standard conditions. Four observers examined the original radiographs and the same radiographs in the reverse contrast mode with the goal of identifying proximal dentinal caries. Microscopic sections 5 µm in thickness were prepared from the teeth in the mesiodistal direction. Four slides prepared from each sample used as the diagnostic gold standard. The data were analyzed using SPSS (α=0.05). Results Our results showed that the original radiographs in order to identify proximal dentinal caries had the following values for sensitivity, specificity, positive predictive value, negative predictive value, and accuracy, respectively: 72.5%, 90%, 87.2%, 76.5%, and 80.9%. For the reverse contrast mode, however, the corresponding values were 63.1%, 89.4%, 87.1%, 73.5%, and 78.8%, respectively. The sensitivity of original digital radiograph for detecting proximal dentinal caries was significantly higher than that of reverse contrast mode (p<0.05). However, no statistically significant differences were found regarding specificity, positive predictive value, negative predictive value, or accuracy (p>0.05). Conclusion The sensitivity of the original digital radiograph for detecting proximal dentinal caries was significantly higher than that of the reversed contrast images. However, no statistically significant differences were found between these techniques regarding specificity, positive predictive value, negative predictive value, or accuracy. PMID:26389055

The evolution of trade-offs under directional and correlational selection.

PubMed

Roff, Derek A; Fairbairn, Daphne J

2012-08-01

Using quantitative genetic theory, we develop predictions for the evolution of trade-offs in response to directional and correlational selection. We predict that directional selection favoring an increase in one trait in a trade-off will result in change in the intercept but not the slope of the trade-off function, with the mean value of the selected trait increasing and that of the correlated trait decreasing. Natural selection will generally favor an increase in some combination of trait values, which can be represented as directional selection on an index value. Such selection induces both directional and correlational selection on the component traits. Theory predicts that selection on an index value will also change the intercept but not the slope of the trade-off function but because of correlational selection, the direction of change in component traits may be in the same or opposite directions. We test these predictions using artificial selection on the well-established trade-off between fecundity and flight capability in the cricket, Gryllus firmus and compare the empirical results with a priori predictions made using genetic parameters from a separate half-sibling experiment. Our results support the predictions and illustrate the complexity of trade-off evolution when component traits are subject to both directional and correlational selection. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.

Can administrative health utilisation data provide an accurate diabetes prevalence estimate for a geographical region?

PubMed

Chan, Wing Cheuk; Papaconstantinou, Dean; Lee, Mildred; Telfer, Kendra; Jo, Emmanuel; Drury, Paul L; Tobias, Martin

2018-05-01

To validate the New Zealand Ministry of Health (MoH) Virtual Diabetes Register (VDR) using longitudinal laboratory results and to develop an improved algorithm for estimating diabetes prevalence at a population level. The assigned diabetes status of individuals based on the 2014 version of the MoH VDR is compared to the diabetes status based on the laboratory results stored in the Auckland regional laboratory result repository (TestSafe) using the New Zealand diabetes diagnostic criteria. The existing VDR algorithm is refined by reviewing the sensitivity and positive predictive value of the each of the VDR algorithm rules individually and as a combination. The diabetes prevalence estimate based on the original 2014 MoH VDR was 17% higher (n = 108,505) than the corresponding TestSafe prevalence estimate (n = 92,707). Compared to the diabetes prevalence based on TestSafe, the original VDR has a sensitivity of 89%, specificity of 96%, positive predictive value of 76% and negative predictive value of 98%. The modified VDR algorithm has improved the positive predictive value by 6.1% and the specificity by 1.4% with modest reductions in sensitivity of 2.2% and negative predictive value of 0.3%. At an aggregated level the overall diabetes prevalence estimated by the modified VDR is 5.7% higher than the corresponding estimate based on TestSafe. The Ministry of Health Virtual Diabetes Register algorithm has been refined to provide a more accurate diabetes prevalence estimate at a population level. The comparison highlights the potential value of a national population long term condition register constructed from both laboratory results and administrative data. Copyright © 2018 Elsevier B.V. All rights reserved.

Does Spontaneous Favorability to Power (vs. Universalism) Values Predict Spontaneous Prejudice and Discrimination?

PubMed

Souchon, Nicolas; Maio, Gregory R; Hanel, Paul H P; Bardin, Brigitte

2017-10-01

We conducted five studies testing whether an implicit measure of favorability toward power over universalism values predicts spontaneous prejudice and discrimination. Studies 1 (N = 192) and 2 (N = 86) examined correlations between spontaneous favorability toward power (vs. universalism) values, achievement (vs. benevolence) values, and a spontaneous measure of prejudice toward ethnic minorities. Study 3 (N = 159) tested whether conditioning participants to associate power values with positive adjectives and universalism values with negative adjectives (or inversely) affects spontaneous prejudice. Study 4 (N = 95) tested whether decision bias toward female handball players could be predicted by spontaneous attitude toward power (vs. universalism) values. Study 5 (N = 123) examined correlations between spontaneous attitude toward power (vs. universalism) values, spontaneous importance toward power (vs. universalism) values, and spontaneous prejudice toward Black African people. Spontaneous positivity toward power (vs. universalism) values was associated with spontaneous negativity toward minorities and predicted gender bias in a decision task, whereas the explicit measures did not. These results indicate that the implicit assessment of evaluative responses attached to human values helps to model value-attitude-behavior relations. © 2016 The Authors. Journal of Personality Published by Wiley Periodicals, Inc.

Double dissociation of value computations in orbitofrontal and anterior cingulate neurons

PubMed Central

Kennerley, Steven W.; Behrens, Timothy E. J.; Wallis, Jonathan D.

2011-01-01

Damage to prefrontal cortex (PFC) impairs decision-making, but the underlying value computations that might cause such impairments remain unclear. Here we report that value computations are doubly dissociable within PFC neurons. While many PFC neurons encoded chosen value, they used opponent encoding schemes such that averaging the neuronal population eliminated value coding. However, a special population of neurons in anterior cingulate cortex (ACC) - but not orbitofrontal cortex (OFC) - multiplex chosen value across decision parameters using a unified encoding scheme, and encoded reward prediction errors. In contrast, neurons in OFC - but not ACC - encoded chosen value relative to the recent history of choice values. Together, these results suggest complementary valuation processes across PFC areas: OFC neurons dynamically evaluate current choices relative to recent choice values, while ACC neurons encode choice predictions and prediction errors using a common valuation currency reflecting the integration of multiple decision parameters. PMID:22037498

Predicting long-term absenteeism from work in construction industry: a longitudinal study.

PubMed

Hoonakker, Peter; van Duivenbooden, Cor

2012-01-01

In this study we examine whether the Work Ability Index (WAI) has additional value in predicting long-term absenteeism in construction industry. Results of the study show that the WAI has additional value in predicting absenteeism, but that the amount of explained variance is low. This is partly due to the definition of absenteeism in The Netherlands, where this study took place.

A prospective analysis of physical examination findings in the diagnosis of facial fractures: Determining predictive value

PubMed Central

Timashpolsky, Alisa; Dagum, Alexander B; Sayeed, Syed M; Romeiser, Jamie L; Rosenfeld, Elisheva A; Conkling, Nicole

2016-01-01

BACKGROUND There are >150,000 patient visits per year to emergency rooms for facial trauma. The reliability of a computed tomography (CT) scan has made it the primary modality for diagnosing facial skeletal injury, with the physical examination playing more a cursory role. Knowing the predictive value of physical findings in facial skeletal injuries may enable more appropriate use of imaging and health care resources. OBJECTIVE A blinded prospective study was undertaken to assess the predictive value of physical examination findings in detecting maxillofacial fracture in trauma patients, and in determining whether a patient will require surgical intervention. METHODS Over a four-month period, the authors’ team examined patients admitted with facial trauma to the emergency department of their hospital. The evaluating physician completed a standardized physical examination evaluation form indicating the physical findings. Corresponding CT scans and surgical records were then reviewed, and the results recorded by a plastic surgeon who was blinded to the results of the physical examination. RESULTS A total of 57 patients met the inclusion criteria; there were 44 male and 13 female patients. The sensitivity, specificity, positive predictive value and negative predictive value of grouped physical examination findings were determined in major areas. In further analysis, specific examination findings with n≥9 (15%) were also reported. CONCLUSIONS The data demonstrated a high negative predictive value of at least 90% for orbital floor, zygomatic, mandibular and nasal bone fractures compared with CT scan. Furthermore, none of the patients who did not have a physical examination finding for a particular facial fracture required surgery for that fracture. Thus, the instrument performed well at ruling out fractures in these areas when there were none. Ultimately, these results may help reduce unnecessary radiation and costly imaging in patients with facial trauma without facial fractures. PMID:27441188

Getting off on the right foot: subjective value versus economic value in predicting longitudinal job outcomes from job offer negotiations.

PubMed

Curhan, Jared R; Elfenbein, Hillary Anger; Kilduff, Gavin J

2009-03-01

Although negotiation experiences can affect a negotiator's ensuing attitudes and behavior, little is known about their long-term consequences. Using a longitudinal survey design, the authors tested the degree to which economic and subjective value achieved in job offer negotiations predicts employees' subsequent job attitudes and intentions concerning turnover. Results indicate that subjective value predicts greater compensation satisfaction and job satisfaction and lower turnover intention measured 1 year later. Surprisingly, the economic outcomes that negotiators achieved had no apparent effects on these factors. Implications, limitations, and future directions are discussed. (c) 2009 APA, all rights reserved.

Intra-Operative Frozen Sections for Ovarian Tumors – A Tertiary Center Experience

PubMed Central

Arshad, Nur Zaiti Md; Ng, Beng Kwang; Paiman, Noor Asmaliza Md; Mahdy, Zaleha Abdullah; Noor, Rushdan Mohd

2018-01-01

Background: Accuracy of diagnosis with intra-operative frozen sections is extremely important in the evaluation of ovarian tumors so that appropriate surgical procedures can be selected. Study design: All patients who with intra-operative frozen sections for ovarian masses in a tertiary center over nine years from June 2008 until April 2017 were reviewed. Frozen section diagnosis and final histopathological reports were compared. Main outcome measures: Sensitivity, specificity, positive and negative predictive values of intra-operative frozen section as compared to final histopathological results for ovarian tumors. Results: A total of 92 cases were recruited for final evaluation. The frozen section diagnoses were comparable with the final histopathological reports in 83.7% of cases. The sensitivity, specificity, positive predictive value and negative predictive value for benign and malignant ovarian tumors were 95.6%, 85.1%, 86.0% and 95.2% and 69.2%, 100%, 100% and 89.2% respectively. For borderline ovarian tumors, the sensitivity and specificity were 76.2% and 88.7%, respectively; the positive predictive value was 66.7% and the negative predictive value was 92.7%. Conclusion: The accuracy of intra-operative frozen section diagnoses for ovarian tumors is high and this approach remains a reliable option in assessing ovarian masses intra-operatively. PMID:29373916

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.

The value of temporary external lumbar CSF drainage in predicting the outcome of shunting on normal pressure hydrocephalus

PubMed Central

Walchenbach, R; Geiger, E; Thomeer, R; Vanneste, J

2002-01-01

Objective: It has been reported that temporary external lumbar CSF drainage (ELD) is a very accurate test for predicting the outcome after ventricular shunting in patients with normal pressure hydrocephalus (NPH). However, only a limited number of patients have been studied for assessing the predictive accuracy of ELD. Therefore, the value of ELD in predicting the outcome after a ventriculoperitoneal shunt in patients with presumed NPH was assessed. Methods: All patients with presumed NPH were invited to participate in this study. Clinical assessment, MRI, and neuropsychological evaluation were followed by a lumbar CSF tap test consisting of removing 40 ml CSF. When this test resulted in marked clinical improvement of gait impairment, mental disturbances, or both, the patient was shunted without further tests. In patients with either questionable or no improvement after the CSF tap test, ELD was carried out. The value of ELD for predicting the outcome after shunting was calculated by correlating the results of ELD with that of ventriculoperitoneal shunting. Results: Between January 1994 and December 2000, 49 presumed NPH patients from three institutes were included. Forty three had idiopathic, and the remaining six had secondary NPH. Forty eight patients were shunted; 39 had an ELD of whom 38 completed the test. After 2 months 35 of the 48 (73%) shunted patients had improved. The predictive value of a positive ELD was 87% (95% confidence interval (95% CI) 62–98) and that of a negative ELD 36% (95% CI 17–59). In two patients serious test related complications (meningitis) occurred without residual deficit. Conclusion: The study suggests that although the predictive value of a positive ELD is high, that of a negative ELD is deceptively low because of the high rate of false negative results. The costs and invasiveness of the test and the possibility of serious test related complications further limits its usefulness in managing patients with presumed NPH. PMID:11909911

Retrospective Review of Treponema pallidum PCR and Serology Results: Are Both Tests Necessary?

PubMed

Brischetto, Anna; Gassiep, Ian; Whiley, David; Norton, Robert

2018-05-01

There has been a resurgence of syphilis diagnoses in Australia. We investigated whether our Treponema pallidum PCR test provides any additional diagnostic information over syphilis serology (chemiluminescence immunoassay [CMIA], Treponema pallidum particle agglutination [TPPA] assay, and the rapid plasma reagin [RPR] flocculation test). A retrospective audit of all T. pallidum PCR requests that came through our laboratory from January 2010 to June 2017 was conducted; data collected included age, gender, site of swab, and results from T. pallidum PCR, syphilis serology, and herpes simplex virus 1 (HSV-1) and HSV-2 PCRs. A total of 441 T. pallidum PCR tests were performed; on average, 3 T. pallidum PCRs per month were requested in 2011, and this rate increased to 17.2 requests per month in 2017. A total of 323 patients had both T. pallidum PCR and syphilis serology performed, with 67% of swabs taken from the genitals. T. pallidum PCR gave positive results for 61/323 (19%) patients; of these 61 patients, 59 (97%) also had positive syphilis serology results ( T. pallidum PCR sensitivity, 68%; specificity, 99%; positive predictive value, 97%; negative predictive value, 89%). Syphilis serology was positive for 91/323 patients (28%); of these 91 patients, 61 (66%) were also T. pallidum PCR positive (syphilis serology sensitivity, 97%; specificity, 88%; positive predictive value, 60%; negative predictive value, 99%). The Cohen's kappa value was 0.74, indicating substantial agreement between the two tests. Our results show that most patients with positive T. pallidum PCR results also had positive syphilis serology. Therefore, T. pallidum PCR adds little clinical value over serology for the diagnosis of syphilis in certain clinical settings. Copyright © 2018 American Society for Microbiology.

Predictive Value of Parkinsonian Primates in Pharmacologic Studies: A Comparison between the Macaque, Marmoset, and Squirrel Monkey.

PubMed

Veyres, Nicolas; Hamadjida, Adjia; Huot, Philippe

2018-05-01

The 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-lesioned primate is the gold-standard animal model of Parkinson disease (PD) and has been used to assess the effectiveness of experimental drugs on dyskinesia, parkinsonism, and psychosis. Three species have been used in most studies-the macaque, marmoset, and squirrel monkey-the last much less so than the first two species; however, the predictive value of each species at forecasting clinical efficacy, or lack thereof, is poorly documented. Here, we have reviewed all the published literature detailing pharmacologic studies that assessed the effects of experimental drugs on dyskinesia, parkinsonism, and psychosis in each of these species and have calculated their predictive value of success and failure at the clinical level. We found that, for dyskinesia, the macaque has a positive predictive value of 87.5% and a false-positive rate of 38.1%, whereas the marmoset has a positive predictive value of 76.9% and a false-positive rate of 15.6%. For parkinsonism, the macaque has a positive predictive value of 68.2% and a false-positive rate of 44.4%, whereas the marmoset has a positive predictive value of 86.9% and a false-positive rate of 41.7%. No drug that alleviates psychosis in the clinic has shown efficacy at doing so in the macaque, whereas the marmoset has 100% positive predictive value. The small number of studies conducted in the squirrel monkey precluded us from calculating its predictive efficacy. We hope our results will help in the design of pharmacologic experiments and will facilitate the drug discovery and development process in PD. Copyright © 2018 by The American Society for Pharmacology and Experimental Therapeutics.

Use of visible and near-infrared spectroscopy to predict pork longissimus lean color stability.

PubMed

King, D A; Shackelford, S D; Wheeler, T L

2011-12-01

This study evaluated the use of visible and near-infrared (VISNIR) spectroscopy to predict lean color stability in pork loin chops. Spectra were collected immediately after and approximately 1 h after rib removal on 1,208 loins. Loins were aged for 14 d before a 2.54-cm chop was placed in simulated retail display. Spectra were collected on aged loins immediately after removal from the vacuum package and on chops 10 min after cutting. Instrumental color measurements [L*, a*, b*, hue angle, chroma, and E (overall color change)] were determined on d 0, 1, 7, 11, and 14 of display. Principal components analysis of display d 0 and 14 values of these traits identified a factor (first principal component; PC1) explaining 67% of the variance that was related to color change. Partial least squares regression was used to develop 3 models to predict PC1 values by using VISNIR spectra collected in the plant, on aged loins, and on chops. Loins with predicted PC1 values less than 0 were classified as having a stable color, whereas values greater than 0 were classified as having a labile lean color. Loins classified as stable by the in-plant model had smaller (P < 0.05) L* values than those classified as labile. Hue angle and ΔE values were less (P < 0.05) and a* and chroma values were greater (P < 0.05) after d 7 of display in loins predicted to have a stable color than in loins predicted to have a labile lean color. Similarly, chops from loins classified as stable using the aged loin model had smaller (P < 0.05) L* values than those from loins classified as labile. Furthermore, loins predicted to be stable had smaller (P < 0.05) hue angle and ΔE values and greater (P < 0.05) a* and chroma values after d 7 of display than did loins predicted to be labile. Results for the chop model were similar to those from the 2 loin models. Chops predicted to have a stable lean color had smaller (P < 0.05) L* values than did those predicted to have a labile lean color. Chops classified as stable had smaller (P < 0.05) hue angle and ΔE values and greater (P < 0.05) a* and chroma values after d 7 of display compared with chops classified as labile. All 3 models effectively segregated chops based on color stability, particularly with regard to redness. Regardless of the model being used, d 14 display values for a*, hue angle, and ΔE in loins classified as stable were similar to the d 7 values of loins classified as labile. Thus, these results suggest that VISNIR spectroscopy would be an effective technology for sorting pork loins with regard to lean color stability.

Numerical weather prediction model tuning via ensemble prediction system

NASA Astrophysics Data System (ADS)

Jarvinen, H.; Laine, M.; Ollinaho, P.; Solonen, A.; Haario, H.

2011-12-01

This paper discusses a novel approach to tune predictive skill of numerical weather prediction (NWP) models. NWP models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. Currently, numerical values of these parameters are specified manually. In a recent dual manuscript (QJRMS, revised) we developed a new concept and method for on-line estimation of the NWP model parameters. The EPPES ("Ensemble prediction and parameter estimation system") method requires only minimal changes to the existing operational ensemble prediction infra-structure and it seems very cost-effective because practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating each member of the ensemble of predictions using different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In the presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an atmospheric general circulation model based ensemble prediction system show that the NWP model tuning capacity of EPPES scales up to realistic models and ensemble prediction systems. Finally, a global top-end NWP model tuning exercise with preliminary results is published.

Quantitative structure-toxicity relationship of the aquatic toxicity for various narcotic pollutants using the norm indexes.

PubMed

Wang, Qiang; Jia, Qingzhu; Yan, Lihong; Xia, Shuqian; Ma, Peisheng

2014-08-01

The aquatic toxicity value of hazardous contaminants plays an important role in the risk assessments of aquatic ecosystems. The following study presents a stable and accurate structure-toxicity relationship model based on the norm indexes for the prediction of toxicity value (log(LC50)) for 190 diverse narcotic pollutants (96 h LC50 data for Poecilia reticulata). Research indicates that this new model is very efficient and provides satisfactory results. The suggested prediction model is evidenced by R(2) (square correlation coefficient) and ARD (average relative difference) values of 0.9376 and 10.45%, respectively, for the training set, and 0.9264 and 13.90% for the testing set. Comparison results with reference models demonstrate that this new method, based on the norm indexes proposed in this work, results in significant improvements, both in accuracy and stability for predicting aquatic toxicity values of narcotic pollutants. Copyright © 2014 Elsevier Ltd. All rights reserved.

Periprosthetic infection: where do we stand with regard to Gram stain?

PubMed Central

Ghanem, Elie; Ketonis, Constantinos; Restrepo, Camilo; Joshi, Ashish; Barrack, Robert

2009-01-01

Background and purpose One of the routinely used intraoperative tests for diagnosis of periprosthetic infection (PPI) is the Gram stain. It is not known if the result of this test can vary according to the type of joint affected or the number of specimen samples collected. We examined the role of this diagnostic test in a large cohort of patients from a single institution. Materials and methods A positive gram stain was defined as the visualization of bacterial cells or “many neutrophils” (> 5 per high-power field) in the smear. The sensitivity, specificity, and predictive values of each individual diagnostic arm of Gram stain were determined. Combinations were performed in series, which required both tests to be positive to confirm infection, and also in parallel, which necessitated both tests to be negative to rule out infection. Results The presence of organisms and “many” neutrophils on a Gram smear had high specificity (98–100%) and positive predictive value (89–100%) in both THA and TKA. The sensitivities (30–50%) and negative predictive values (70–79%) of the 2 tests were low for both joint types. When the 2 tests were combined in series, the specificity and positive predictive value were absolute (100%). The sensitivity and the negative predictive value improved for both THA and TKA (43–64% and 82%, respectively). Interpretation Although the 2 diagnostic arms of Gram staining can be combined to achieve improved negative predictive value (82%), Gram stain continues to have little value in ruling out PPI. With the advances in the field of molecular biology, novel diagnostic modalities need to be designed that can replace these traditional and poor tests. PMID:19297787

Comparison of manual scaled and predicted foE and foF1 critical frequencies. Technical report

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

Gamache, R.R.; Kersey, W.T.

1990-07-01

The CCIR and Titheridge foE critical frequency prediction routines were tested by comparison with 1875 manually scaled values. The foF1 critical frequency prediction routine of Millman et al was tested by comparison with 1005 manually scaled values. Plots and statistics of the comparisons are presented and discussed. From the results recommendations are made to help improve autoscaling.

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.

Reassessment of the positive predictive value and specificity of Xpert MTB/RIF: a diagnostic accuracy study in the context of community-wide screening for tuberculosis.

PubMed

Ho, Jennifer; Nguyen, Phuong Thi Bich; Nguyen, Thu Anh; Tran, Khoa Hien; Van Nguyen, Son; Nguyen, Nhung Viet; Nguyen, Hoa Binh; Luu, Khanh Boi; Fox, Greg J; Marks, Guy B

2016-09-01

Community-wide screening for tuberculosis with Xpert MTB/RIF as a primary screening tool overcomes some of the limitations of conventional screening. However, concerns exist about the low positive predictive value of this test in screening settings. We did a cross-sectional assessment of this diagnostic test to directly estimate the actual positive predictive value of Xpert MTB/RIF when used in the setting of community-wide screening for tuberculosis, and to draw an inference about the specificity of the test for tuberculosis detection. Field staff visited households in 60 randomly selected villages in Ca Mau province, Vietnam. We included people aged 15 years or older who provided written informed consent and were able to produce 0·5 mL or more of sputum, irrespective of reported symptoms. Participants were tested with Xpert MTB/RIF, then those with positive results had two further sputum samples tested for smear microscopy and culture, and underwent chest radiography at the provincial TB Health Center. The positive predictive value of Xpert MTB/RIF was compared against two reference standards for tuberculosis diagnosis-a positive sputum culture for Mycobacterium tuberculosis, and a positive sputum culture or a chest radiograph consistent with active pulmonary tuberculosis. We then calculated the specificity of Xpert MTB/RIF for tuberculosis detection on the basis of these positive predictive values and disease prevalence in this setting. 43 435 adults consented to screening with Xpert MTB/RIF. Sputum samples of 0·5 mL or greater were collected from 23 202 participants, producing 22 673 valid results. 169 participants had positive Xpert MTB/RIF results (0·39% of those screened and 0·75% of those with valid sputum results). The positive predictive value of Xpert MTB/RIF was 61·0% (95% CI 52·8-68·7) when compared against a positive sputum culture and 83·9% (76·8-89·2) when compared against a positive sputum culture or chest radiograph consistent with active tuberculosis. On the basis of these positive predictive values, the specificity of Xpert MTB/RIF was determined to be between 99·78% (95% CI 99·71-99·84) and 99·93% (99·88-99·96). The positive predictive value and specificity of Xpert MTB/RIF in the context of community-wide screening for tuberculosis is substantially higher than that predicted in previous studies. Our findings support the potential role of Xpert MTB/RIF as a primary screening tool to detect prevalent cases of tuberculosis in the community. Australian National Health and Medical Research Council. Copyright © 2016 Elsevier Ltd. All rights reserved.

Sensitivity and specificity of subacute computerized neurocognitive testing and symptom evaluation in predicting outcomes after sports-related concussion.

PubMed

Lau, Brian C; Collins, Michael W; Lovell, Mark R

2011-06-01

Concussions affect an estimated 136 000 high school athletes yearly. Computerized neurocognitive testing has been shown to be appropriately sensitive and specific in diagnosing concussions, but no studies have assessed its utility to predict length of recovery. Determining prognosis during subacute recovery after sports concussion will help clinicians more confidently address return-to-play and academic decisions. To quantify the prognostic ability of computerized neurocognitive testing in combination with symptoms during the subacute recovery phase from sports-related concussion. Cohort study (prognosis); Level of evidence, 2. In sum, 108 male high school football athletes completed a computer-based neurocognitive test battery within 2.23 days of injury and were followed until returned to play as set by international guidelines. Athletes were grouped into protracted recovery (>14 days; n = 50) or short-recovery (≤14 days; n = 58). Separate discriminant function analyses were performed using total symptom score on Post-Concussion Symptom Scale, symptom clusters (migraine, cognitive, sleep, neuropsychiatric), and Immediate Postconcussion Assessment and Cognitive Testing neurocognitive scores (verbal memory, visual memory, reaction time, processing speed). Multiple discriminant function analyses revealed that the combination of 4 symptom clusters and 4 neurocognitive composite scores had the highest sensitivity (65.22%), specificity (80.36%), positive predictive value (73.17%), and negative predictive value (73.80%) in predicting protracted recovery. Discriminant function analyses of total symptoms on the Post-Concussion Symptom Scale alone had a sensitivity of 40.81%; specificity, 79.31%; positive predictive value, 62.50%; and negative predictive value, 61.33%. The 4 symptom clusters alone discriminant function analyses had a sensitivity of 46.94%; specificity, 77.20%; positive predictive value, 63.90%; and negative predictive value, 62.86%. Discriminant function analyses of the 4 computerized neurocognitive scores alone had a sensitivity of 53.20%; specificity, 75.44%; positive predictive value, 64.10%; and negative predictive value, 66.15%. The use of computerized neurocognitive testing in conjunction with symptom clusters results improves sensitivity, specificity, positive predictive value, and negative predictive value of predicting protracted recovery compared with each used alone. There is also a net increase in sensitivity of 24.41% when using neurocognitive testing and symptom clusters together compared with using total symptoms on Post-Concussion Symptom Scale alone.

NWP model forecast skill optimization via closure parameter variations

NASA Astrophysics Data System (ADS)

Järvinen, H.; Ollinaho, P.; Laine, M.; Solonen, A.; Haario, H.

2012-04-01

We present results of a novel approach to tune predictive skill of numerical weather prediction (NWP) models. These models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. The current practice is to specify manually the numerical parameter values, based on expert knowledge. We developed recently a concept and method (QJRMS 2011) for on-line estimation of the NWP model parameters via closure parameter variations. The method called EPPES ("Ensemble prediction and parameter estimation system") utilizes ensemble prediction infra-structure for parameter estimation in a very cost-effective way: practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating an ensemble of predictions so that each member uses different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In this presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an ensemble prediction system emulator, based on the ECHAM5 atmospheric GCM show that the model tuning capability of EPPES scales up to realistic models and ensemble prediction systems. Finally, preliminary results of EPPES in the context of ECMWF forecasting system are presented.

Demands, values, and burnout

PubMed Central

Leiter, Michael P.; Frank, Erica; Matheson, Timothy J.

2009-01-01

OBJECTIVE T o explore the interaction between workload and values congruence (personal values with health care system values) in the context of burnout and physician engagement and to explore the relative importance of these factors by sex, given the distinct work patterns of male and female physicians. DESIGN National mailed survey. SETTING Canada. PARTICIPANTS A random sample of 8100 Canadian physicians (response rate 40%, N = 3213); 2536 responses (from physicians working more than 35 hours per week) were analyzed. MAIN OUTCOME MEASURES Levels of burnout, values congruence, and workload, by sex, measured by the Maslach Burnout Inventory—General Scale and the Areas of Worklife Scale. RESULTS Results showed a moderate level of burnout among Canadian physicians, with relatively positive scores on exhaustion, average scores on cynicism, and mildly negative scores on professional efficacy. A series of multiple regression analyses confirmed parallel main effect contributions from manageable workload and values congruence. Both workload and values congruence predicted exhaustion and cynicism for men and women (P = .001). Only values congruence provided a significant prediction of professional efficacy for both men and women (P = .001) These predictors interacted for women on all 3 aspects of burnout (exhaustion, cynicism, and diminished efficacy). Howevever, overall levels of the burnout indicators departed only modestly from normative levels. CONCLUSION W orkload and values congruence make distinct contributions to physician burnout. Work overload contributes to predicting exhaustion and cynicism; professional values crises contribute to predicting exhaustion, cynicism, and low professional efficacy. The interaction of values and workload for women in particular has implications for the distinct work-life patterns of male and female physicians. Specifically, the congruence of individual values with values inherent in the health care system appeared to be of greater consequence for women than for men. PMID:20008605

Predictive Validity of a Cigarette Purchase Task in a Randomized Controlled Trial of Contingent Vouchers for Smoking in Individuals With Substance Use Disorders

PubMed Central

Mackillop, James; Murphy, Cara M.; Martin, Rosemarie A.; Stojek, Monika; Tidey, Jennifer W.; Colby, Suzanne M.

2016-01-01

Abstract Introduction: A cigarette purchase task (CPT) is a behavioral economic measure of the reinforcing value of smoking in monetary terms (ie, cigarette demand). This study investigated whether cigarette demand predicted response to contingent monetary rewards for abstinence among individuals with substance use disorders. It also sought to replicate evidence for greater price sensitivity at whole-dollar pack price transitions (ie, left-digit effects). Methods: Participants ( N = 338) were individuals in residential substance use disorder treatment who participated in a randomized controlled trial that compared contingent vouchers to noncontingent vouchers for smoking abstinence. Baseline demand indices were used to predict number of abstinent days during the 14-day voucher period (after the reduction lead-in) and at 1 and 3 months afterward. Results: Demand indices correlated with measures of smoking and nicotine dependence. As measured by elasticity, intensity and Omax , higher demand significantly predicted fewer abstinent exhaled carbon monoxide readings during voucher period for individuals in the noncontingent vouchers condition. Breakpoint exhibited a trend-level association with abstinent exhaled carbon monoxide readings. Demand indices did not predict abstinence in the contingent vouchers group, and did not predict abstinence at 1- and 3-month follow-ups. Left-digit price transitions were associated with significantly greater reductions in consumption. Conclusions: The association of cigarette demand with smoking behavior only in the group for whom abstinence was not incentivized indicates that CPT assesses the value of smoking more than the value of money per se and that vouchers counteract the effects of the intrinsic reinforcing value of cigarettes. Results provide initial short-term evidence of predictive validity for the CPT indices. Implications: This study provides the first evidence of the validity of the CPT for predicting early response to brief advice for smoking cessation plus nicotine replacement in smokers with substance dependence. However, demand for cigarettes did not predict voucher-based treatment response, indicating that incentives serve as a powerful motivator not to smoke that acts in opposition to the intrinsic reinforcing value of cigarettes and that the indices reflect the value of smoking more than the value of money per se. PMID:26498173

To Communicate or Not to Communicate: Factors Predicting Passengers' Intentions to Ask a Driver to Stop Text Messaging While Driving.

PubMed

Wang, Xiao

2016-01-01

Interpersonal communication is important in health campaigns. This research examined factors that are associated with passengers' intentions to communicate no texting with a texting driver in a scenario where the driver is their friend. Based on survey data collected from 546 college students, results showed that students' attitudes toward communication about no texting while driving were predicted by their utilitarian (i.e., safety), value-expressive, and ego-defensive motivations, in addition to being predicted by self-efficacy and norms. Additional results revealed that empathic concern was correlated with the value-expressive motivation and anticipated guilt. Anticipated guilt, together with attitudes, norms, and efficacy, predicted communication intentions. Results revealed that including attitude functions (motivations) in the reasoned action model could help propose and test theory-based predictions in interpersonal communication and health behaviors.

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.

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

PubMed

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

2016-11-20

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

Experimentally determined stiffness and damping of an inherently compensated air squeeze-film damper

NASA Technical Reports Server (NTRS)

Cunningham, R. E.

1975-01-01

Values of damping and stiffness were determined experimentally for an externally pressurized, inherently compensated, compressible squeeze-film damper up to excitation frequencies of 36,000 cycles per minute. Experimental damping values were higher than theory predicted at low squeeze numbers and less than predicted at high squeeze numbers. Experimental values of air film stiffness were less than theory predicted at low squeeze numbers and much greater at higher squeeze numbers. Results also indicate sufficient damping to attenuate amplitudes and forces at the critical speed when using three dampers in the flexible support system of a small, lightweight turborotor.

SWMF Global Magnetosphere Simulations of January 2005: Geomagnetic Indices and Cross-Polar Cap Potential

DOE PAGES

Haiducek, John D.; Welling, Daniel T.; Ganushkina, Natalia Y.; ...

2017-10-30

We simulated the entire month of January, 2005 using the Space Weather Modeling Framework (SWMF) with observed solar wind data as input. We conducted this simulation with and without an inner magnetosphere model, and tested two different grid resolutions. We evaluated the model's accuracy in predicting Kp, Sym-H, AL, and cross polar cap potential (CPCP). We find that the model does an excellent job of predicting the Sym-H index, with an RMSE of 17-18 nT. Kp is predicted well during storm-time conditions, but over-predicted during quiet times by a margin of 1 to 1.7 Kp units. AL is predicted reasonablymore » well on average, with an RMSE of 230-270 nT. However, the model reaches the largest negative AL values significantly less often than the observations. The model tended to over-predict CPCP, with RMSE values on the order of 46-48 kV. We found the results to be insensitive to grid resoution, with the exception of the rate of occurrence for strongly negative AL values. As a result, the use of the inner magnetosphere component, however, affected results significantly, with all quantities except CPCP improved notably when the inner magnetosphere model was on.« less

SWMF Global Magnetosphere Simulations of January 2005: Geomagnetic Indices and Cross-Polar Cap Potential

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

Haiducek, John D.; Welling, Daniel T.; Ganushkina, Natalia Y.

We simulated the entire month of January, 2005 using the Space Weather Modeling Framework (SWMF) with observed solar wind data as input. We conducted this simulation with and without an inner magnetosphere model, and tested two different grid resolutions. We evaluated the model's accuracy in predicting Kp, Sym-H, AL, and cross polar cap potential (CPCP). We find that the model does an excellent job of predicting the Sym-H index, with an RMSE of 17-18 nT. Kp is predicted well during storm-time conditions, but over-predicted during quiet times by a margin of 1 to 1.7 Kp units. AL is predicted reasonablymore » well on average, with an RMSE of 230-270 nT. However, the model reaches the largest negative AL values significantly less often than the observations. The model tended to over-predict CPCP, with RMSE values on the order of 46-48 kV. We found the results to be insensitive to grid resoution, with the exception of the rate of occurrence for strongly negative AL values. As a result, the use of the inner magnetosphere component, however, affected results significantly, with all quantities except CPCP improved notably when the inner magnetosphere model was on.« less

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).

Reported maternal tendencies predict the reward value of infant facial cuteness, but not cuteness detection

PubMed Central

Hahn, Amanda C.; DeBruine, Lisa M.; Jones, Benedict C.

2015-01-01

The factors that contribute to individual differences in the reward value of cute infant facial characteristics are poorly understood. Here we show that the effect of cuteness on a behavioural measure of the reward value of infant faces is greater among women reporting strong maternal tendencies. By contrast, maternal tendencies did not predict women's subjective ratings of the cuteness of these infant faces. These results show, for the first time, that the reward value of infant facial cuteness is greater among women who report being more interested in interacting with infants, implicating maternal tendencies in individual differences in the reward value of infant cuteness. Moreover, our results indicate that the relationship between maternal tendencies and the reward value of infant facial cuteness is not due to individual differences in women's ability to detect infant cuteness. This latter result suggests that individual differences in the reward value of infant cuteness are not simply a by-product of low-cost, functionless biases in the visual system. PMID:25740842

Sensitivity, Specificity, and Predictive Values of Pediatric Metabolic Syndrome Components in Relation to Adult Metabolic Syndrome: The Princeton LRC Follow-up Study

PubMed Central

Huang, Terry T-K; Nansel, Tonja R.; Belsheim, Allen R.; Morrison, John A.

2008-01-01

Objective To estimate the sensitivity, specificity, and predictive values of pediatric metabolic syndrome (MetS) components (obesity, fasting glucose, triglycerides, high-density lipoprotein, and blood pressure) at various cutoffs in relation to adult MetS. Study design Data from the NHLBI Lipid Research Clinics (LRC) Princeton Prevalence Study (1973–76) and the Princeton Follow-up Study (PFS, 2000-4) were used to calculate sensitivity, specificity, and positive and negative predictive values for each component at a given cutoff, as well as for aggregates of components. Results Individual pediatric components alone showed low to moderate sensitivity, high specificity, and moderate predictive values in relation to adult MetS. When all five pediatric MetS components were considered, the presence of at least one abnormality had higher sensitivity for adult MetS than individual components alone. When multiple abnormalities were mandatory for MetS, positive predictive value was high and sensitivity was low. Childhood body mass alone showed neither high sensitivity nor high positive predictive value for adult MetS. Conclusions Considering multiple metabolic variables in childhood can improve the predictive utility for adult MetS, compared to each component or body mass alone. MetS variables may be useful for identifying some at risk children for prevention interventions. PMID:18206687

Exposure-based screening for Nipah virus encephalitis, Bangladesh.

PubMed

Sazzad, Hossain M S; Luby, Stephen P; Ströher, Ute; Daszak, Peter; Sultana, Sharmin; Afroj, Sayma; Rahman, Mahmudur; Gurley, Emily S

2015-02-01

We measured the performance of exposure screening questions to identify Nipah virus encephalitis in hospitalized encephalitis patients during the 2012-13 Nipah virus season in Bangladesh. The sensitivity (93%), specificity (82%), positive predictive value (37%), and negative predictive value (99%) results suggested that screening questions could more quickly identify persons with Nipah virus encephalitis.

The Predictive Validity of the ABFM's In-Training Examination.

PubMed

O'Neill, Thomas R; Li, Zijia; Peabody, Michael R; Lybarger, Melanie; Royal, Kenneth; Puffer, James C

2015-05-01

Our objective was to examine the predictive validity of the American Board of Family Medicine's (ABFM) In-Training Examination (ITE) with regard to predicting outcomes on the ABFM certification examination. This study used a repeated measures design across three levels of medical training (PGY1--PGY2, PGY2--PGY3, and PGY3--initial certification) with three different cohorts (2010--2011, 2011--2012, and 2012--2013) to examine: (1) how well the residents' ITE scores correlated with their test scores in the following year, (2) what the typical score increase was across training years, and (3) what was the sensitivity, specificity, positive predictive value, and negative predictive value of the PGY3 scores with regard to predicting future results on the MC-FP Examination. ITE scores generally correlate at about .7 with the following year's ITE or with the following year's certification examination. The mean growth from PGY1 to PGY2 was 52 points, from PGY2 to PGY3 was 34 points, and from PGY3 to initial certification was 27 points. The sensitivity, specificity, positive predictive value, and negative predictive value were .91, .47, .96, and .27, respectively. The ITE is a useful predictor of future ITE and initial certification examination performance.

Predicting the Types of Ion Channel-Targeted Conotoxins Based on AVC-SVM Model.

PubMed

Xianfang, Wang; Junmei, Wang; Xiaolei, Wang; Yue, Zhang

2017-01-01

The conotoxin proteins are disulfide-rich small peptides. Predicting the types of ion channel-targeted conotoxins has great value in the treatment of chronic diseases, epilepsy, and cardiovascular diseases. To solve the problem of information redundancy existing when using current methods, a new model is presented to predict the types of ion channel-targeted conotoxins based on AVC (Analysis of Variance and Correlation) and SVM (Support Vector Machine). First, the F value is used to measure the significance level of the feature for the result, and the attribute with smaller F value is filtered by rough selection. Secondly, redundancy degree is calculated by Pearson Correlation Coefficient. And the threshold is set to filter attributes with weak independence to get the result of the refinement. Finally, SVM is used to predict the types of ion channel-targeted conotoxins. The experimental results show the proposed AVC-SVM model reaches an overall accuracy of 91.98%, an average accuracy of 92.17%, and the total number of parameters of 68. The proposed model provides highly useful information for further experimental research. The prediction model will be accessed free of charge at our web server.

Predicting the Types of Ion Channel-Targeted Conotoxins Based on AVC-SVM Model

PubMed Central

Xiaolei, Wang

2017-01-01

The conotoxin proteins are disulfide-rich small peptides. Predicting the types of ion channel-targeted conotoxins has great value in the treatment of chronic diseases, epilepsy, and cardiovascular diseases. To solve the problem of information redundancy existing when using current methods, a new model is presented to predict the types of ion channel-targeted conotoxins based on AVC (Analysis of Variance and Correlation) and SVM (Support Vector Machine). First, the F value is used to measure the significance level of the feature for the result, and the attribute with smaller F value is filtered by rough selection. Secondly, redundancy degree is calculated by Pearson Correlation Coefficient. And the threshold is set to filter attributes with weak independence to get the result of the refinement. Finally, SVM is used to predict the types of ion channel-targeted conotoxins. The experimental results show the proposed AVC-SVM model reaches an overall accuracy of 91.98%, an average accuracy of 92.17%, and the total number of parameters of 68. The proposed model provides highly useful information for further experimental research. The prediction model will be accessed free of charge at our web server. PMID:28497044

Determining Cutoff Point of Ensemble Trees Based on Sample Size in Predicting Clinical Dose with DNA Microarray Data.

PubMed

Yılmaz Isıkhan, Selen; Karabulut, Erdem; Alpar, Celal Reha

2016-01-01

Background/Aim . Evaluating the success of dose prediction based on genetic or clinical data has substantially advanced recently. The aim of this study is to predict various clinical dose values from DNA gene expression datasets using data mining techniques. Materials and Methods . Eleven real gene expression datasets containing dose values were included. First, important genes for dose prediction were selected using iterative sure independence screening. Then, the performances of regression trees (RTs), support vector regression (SVR), RT bagging, SVR bagging, and RT boosting were examined. Results . The results demonstrated that a regression-based feature selection method substantially reduced the number of irrelevant genes from raw datasets. Overall, the best prediction performance in nine of 11 datasets was achieved using SVR; the second most accurate performance was provided using a gradient-boosting machine (GBM). Conclusion . Analysis of various dose values based on microarray gene expression data identified common genes found in our study and the referenced studies. According to our findings, SVR and GBM can be good predictors of dose-gene datasets. Another result of the study was to identify the sample size of n = 25 as a cutoff point for RT bagging to outperform a single RT.

Personal spiritual values and quality of life: evidence from Chinese college students.

PubMed

Zhang, Kaili Chen; Hui, C Harry; Lam, Jasmine; Lau, Esther Yuet Ying; Cheung, Shu-Fai; Mok, Doris Shui Ying

2014-08-01

Values are guiding principles in our life. While some studies found spiritual values to be "healthier," Sagiv and Schwartz (Eur J Soc Psychol 30:177-198, 2000) showed that people holding non-spiritual values were higher on affective well-being. We examined the predictive power of these two types of values with a longitudinal data set collected from Chinese students mainly in Hong Kong. Structural equation modeling revealed that spiritual values (as well as family income) positively predicted quality of life a year later. Non-spiritual, self-enhancement values, did not show any association. Results suggest that developing spiritual values may promote well-being through enabling individuals to find meaning and purpose in life.

Prediction of wastewater treatment plants performance based on artificial fish school neural network

NASA Astrophysics Data System (ADS)

Zhang, Ruicheng; Li, Chong

2011-10-01

A reliable model for wastewater treatment plant is essential in providing a tool for predicting its performance and to form a basis for controlling the operation of the process. This would minimize the operation costs and assess the stability of environmental balance. For the multi-variable, uncertainty, non-linear characteristics of the wastewater treatment system, an artificial fish school neural network prediction model is established standing on actual operation data in the wastewater treatment system. The model overcomes several disadvantages of the conventional BP neural network. The results of model calculation show that the predicted value can better match measured value, played an effect on simulating and predicting and be able to optimize the operation status. The establishment of the predicting model provides a simple and practical way for the operation and management in wastewater treatment plant, and has good research and engineering practical value.

Prediction of venous wound healing with laser speckle imaging.

PubMed

van Vuuren, Timme Maj; Van Zandvoort, Carina; Doganci, Suat; Zwiers, Ineke; tenCate-Hoek, Arina J; Kurstjens, Ralph Lm; Wittens, Cees Ha

2017-12-01

Introduction Laser speckle imaging is used for noninvasive assessment of blood flow of cutaneous wounds. The aim of this study was to assess if laser speckle imaging can be used as a predictor of venous ulcer healing. Methods After generating the flux speckle images, three regions of interest (ROI) were identified to measure the flow. Sensitivity, specificity, negative predictive value, and positive predictive value for ulcer healing were calculated. Results In total, 17 limbs were included. A sensitivity of 92.3%, specificity of 75.0%, PPV of 80.0%, and NPV 75.0% were found in predicting wound healing based on laser speckle images. Mean flux values were lowest in the center (ROI I) and showed an increase at the wound edge (ROI II, p = 0.03). Conclusion Laser speckle imaging shows acceptable sensitivity and specificity rates in predicting venous ulcer healing. The wound edge proved to be the best probability for the prediction of wound healing.

Predictive performance of the human Cell Line Activation Test (h-CLAT) for lipophilic chemicals with high octanol-water partition coefficients.

PubMed

Takenouchi, Osamu; Miyazawa, Masaaki; Saito, Kazutoshi; Ashikaga, Takao; Sakaguchi, Hitoshi

2013-01-01

To meet the urgent need for a reliable alternative test for predicting skin sensitizing potential of many chemicals, we have developed a cell-based in vitro test, human Cell Line Activation Test (h-CLAT). However, the predictive performance for lipophilic chemicals in the h-CLAT still remains relatively unknown. Moreover, it's suggested that low water solubility of chemicals might induce false negative outcomes. Thus, in this study, we tested relatively low water soluble 37 chemicals with log Kow values above and below 3.5 in the h-CLAT. The small-scale assessment resulted in nine false negative outcomes for chemicals with log Kow values greater than 3.5. We then created a dataset of 143 chemicals by combining the existing dataset of 106 chemicals and examined the predictive performance of the h-CLAT for chemicals with a log Kow of less than 3.5; a total of 112 chemicals from the 143 chemicals in the dataset. The sensitivity and overall accuracy for the 143 chemicals were 83% and 80%, respectively. In contrast, sensitivity and overall accuracy for the 112 chemicals with log Kow values below 3.5 improved to 94% and 88%, respectively. These data suggested that the h-CLAT could successfully detect sensitizers with log Kow values up to 3.5. When chemicals with log Kow values greater than 3.5 that were deemed positive by h-CLAT were included with the 112 chemicals, the sensitivity and accuracy in terms of the resulting applicable 128 chemicals out of the 143 chemicals became 95% and 88%, respectively. The use of log Kow values gave the h-CLAT a higher predictive performance. Our results demonstrated that the h-CLAT could predict sensitizing potential of various chemicals, which contain lipophilic chemicals using a large-scale chemical dataset.

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

Use of the Abbott Architect HIV antigen/antibody assay in a low incidence population.

PubMed

Dubravac, Terry; Gahan, Thomas F; Pentella, Michael A

2013-12-01

With the availability of 4th generation HIV diagnostic tests which are capable of detecting acute infection, Iowa evaluated the 3rd and 4th generation HIV test and compared the performance of these products in a low incidence population. This study was conducted to evaluate the performance of an HIV antigen/antibody combination (4th generation) assay compared to an EIA 3rd generation assay. Over a 4 month period, 2037 specimens submitted for HIV screening were tested by Bio-Rad GS HIV-1/HIV-2 Plus O EIA and the Abbott Architect i1000SR HIV Ag/Ab Combo. The performance characteristics of sensitivity, specificity, positive predictive value and negative predictive value were determined. Of the 2037 specimens tested, there were 13 (0.64%) true positives detected. None of the positive specimens were from patients in the acute phase of infection. The Abbott antigen/antibody combo assay had a sensitivity, specificity, positive-predictive value and negative predictive value of 100%, 99.85%, 81.25%, and 100% respectively. The Bio-Rad EIA assay had a sensitivity, specificity, positive-predictive value and negative predictive value of 100%, 99.80%, 76.47% and 100%, respectively. The EIA had four false positive results which tested negative by the antigen/antibody assay and western blot. In a low-incidence state where early infections are less commonly encountered, the EIA assay and the antigen/antibody assay performed with near equivalency. The antigen/antibody assay had one less false positive result. While no patients were detected in the acute stage of infection, the use of the antigen/antibody assay presents the opportunity to detect an infected patient sooner and prevent transmission to others. Copyright © 2013 Elsevier B.V. All rights reserved.

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

PubMed

Shephard, R W; Morton, J M

2018-01-01

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

Evaluation of multivariate linear regression and artificial neural networks in prediction of water quality parameters

PubMed Central

2014-01-01

This paper examined the efficiency of multivariate linear regression (MLR) and artificial neural network (ANN) models in prediction of two major water quality parameters in a wastewater treatment plant. Biochemical oxygen demand (BOD) and chemical oxygen demand (COD) as well as indirect indicators of organic matters are representative parameters for sewer water quality. Performance of the ANN models was evaluated using coefficient of correlation (r), root mean square error (RMSE) and bias values. The computed values of BOD and COD by model, ANN method and regression analysis were in close agreement with their respective measured values. Results showed that the ANN performance model was better than the MLR model. Comparative indices of the optimized ANN with input values of temperature (T), pH, total suspended solid (TSS) and total suspended (TS) for prediction of BOD was RMSE = 25.1 mg/L, r = 0.83 and for prediction of COD was RMSE = 49.4 mg/L, r = 0.81. It was found that the ANN model could be employed successfully in estimating the BOD and COD in the inlet of wastewater biochemical treatment plants. Moreover, sensitive examination results showed that pH parameter have more effect on BOD and COD predicting to another parameters. Also, both implemented models have predicted BOD better than COD. PMID:24456676

Epidemiologic research using probabilistic outcome definitions.

PubMed

Cai, Bing; Hennessy, Sean; Lo Re, Vincent; Small, Dylan S

2015-01-01

Epidemiologic studies using electronic healthcare data often define the presence or absence of binary clinical outcomes by using algorithms with imperfect specificity, sensitivity, and positive predictive value. This results in misclassification and bias in study results. We describe and evaluate a new method called probabilistic outcome definition (POD) that uses logistic regression to estimate the probability of a clinical outcome using multiple potential algorithms and then uses multiple imputation to make valid inferences about the risk ratio or other epidemiologic parameters of interest. We conducted a simulation to evaluate the performance of the POD method with two variables that can predict the true outcome and compared the POD method with the conventional method. The simulation results showed that when the true risk ratio is equal to 1.0 (null), the conventional method based on a binary outcome provides unbiased estimates. However, when the risk ratio is not equal to 1.0, the traditional method, either using one predictive variable or both predictive variables to define the outcome, is biased when the positive predictive value is <100%, and the bias is very severe when the sensitivity or positive predictive value is poor (less than 0.75 in our simulation). In contrast, the POD method provides unbiased estimates of the risk ratio both when this measure of effect is equal to 1.0 and not equal to 1.0. Even when the sensitivity and positive predictive value are low, the POD method continues to provide unbiased estimates of the risk ratio. The POD method provides an improved way to define outcomes in database research. This method has a major advantage over the conventional method in that it provided unbiased estimates of risk ratios and it is easy to use. Copyright © 2014 John Wiley & Sons, Ltd.

Artificial neural network analysis based on genetic algorithm to predict the performance characteristics of a cross flow cooling tower

NASA Astrophysics Data System (ADS)

Wu, Jiasheng; Cao, Lin; Zhang, Guoqiang

2018-02-01

Cooling tower of air conditioning has been widely used as cooling equipment, and there will be broad application prospect if it can be reversibly used as heat source under heat pump heating operation condition. In view of the complex non-linear relationship of each parameter in the process of heat and mass transfer inside tower, In this paper, the BP neural network model based on genetic algorithm optimization (GABP neural network model) is established for the reverse use of cross flow cooling tower. The model adopts the structure of 6 inputs, 13 hidden nodes and 8 outputs. With this model, the outlet air dry bulb temperature, wet bulb temperature, water temperature, heat, sensible heat ratio and heat absorbing efficiency, Lewis number, a total of 8 the proportion of main performance parameters were predicted. Furthermore, the established network model is used to predict the water temperature and heat absorption of the tower at different inlet temperatures. The mean relative error MRE between BP predicted value and experimental value are 4.47%, 3.63%, 2.38%, 3.71%, 6.35%,3.14%, 13.95% and 6.80% respectively; the mean relative error MRE between GABP predicted value and experimental value are 2.66%, 3.04%, 2.27%, 3.02%, 6.89%, 3.17%, 11.50% and 6.57% respectively. The results show that the prediction results of GABP network model are better than that of BP network model; the simulation results are basically consistent with the actual situation. The GABP network model can well predict the heat and mass transfer performance of the cross flow cooling tower.

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.

Will personal values predict the development of smoking and drinking behaviors? A prospective cohort study of children and adolescents in Taiwan.

PubMed

Nieh, Hsi-Ping; Wu, Wen-Chi; Luh, Dih-Ling; Yen, Lee-Lan; Hurng, Baai-Shyun; Chang, Hsing-Yi

2018-06-01

This study examined how personal values predict the development of smoking and drinking behaviors in adolescence. The longitudinal data of 1545 adolescents over a 6-year period were analyzed. The results showed that adolescents who valued health and academics had similarly lower odds of reporting cigarette and alcohol use and those who valued friends had significantly higher odds. While the odds increased over time, the trend on alcohol use lessened for adolescents who valued academics, while the trend accelerated for those who valued friends. The finding suggests the important role that personal values play in adolescent risk behavioral development.

Elongated Tetrakaidecahedron Micromechanics Model for Space Shuttle External Tank Foams

NASA Technical Reports Server (NTRS)

Sullivan, Roy M.; Ghosn, Louis J.; Lerch, Bradley A.; Baker, Eric H.

2009-01-01

The results of microstructural characterization studies and physical and mechanical testing of BX-265 and NCFI24-124 foams are reported. A micromechanics model developed previously by the authors is reviewed, and the resulting equations for the elastic constants, the relative density, and the strength of the foam in the principal material directions are presented. The micromechanics model is also used to derive equations to predict the effect of vacuum on the tensile strength and the strains induced by exposure to vacuum. Using a combination of microstructural dimensions and physical and mechanical measurements as input, the equations for the elastic constants and the relative density are applied and the remaining microstructural dimensions are predicted. The predicted microstructural dimensions are in close agreement with the average measured values for both BX-265 and NCFI24-124. With the microstructural dimensions, the model predicts the ratio of the strengths in the principal material directions for both foams. The model is also used to predict the Poisson s ratios, the vacuum-induced strains, and the effect of vacuum on the tensile strengths. However, the comparison of these predicted values with the measured values is not as favorable.

A model for prediction of color change after tooth bleaching based on CIELAB color space

NASA Astrophysics Data System (ADS)

Herrera, Luis J.; Santana, Janiley; Yebra, Ana; Rivas, María. José; Pulgar, Rosa; Pérez, María. M.

2017-08-01

An experimental study aiming to develop a model based on CIELAB color space for prediction of color change after a tooth bleaching procedure is presented. Multivariate linear regression models were obtained to predict the L*, a*, b* and W* post-bleaching values using the pre-bleaching L*, a*and b*values. Moreover, univariate linear regression models were obtained to predict the variation in chroma (C*), hue angle (h°) and W*. The results demonstrated that is possible to estimate color change when using a carbamide peroxide tooth-bleaching system. The models obtained can be applied in clinic to predict the colour change after bleaching.

The importance of molecular structures, endpoints' values, and predictivity parameters in QSAR research: QSAR analysis of a series of estrogen receptor binders.

PubMed

Li, Jiazhong; Gramatica, Paola

2010-11-01

Quantitative structure-activity relationship (QSAR) methodology aims to explore the relationship between molecular structures and experimental endpoints, producing a model for the prediction of new data; the predictive performance of the model must be checked by external validation. Clearly, the qualities of chemical structure information and experimental endpoints, as well as the statistical parameters used to verify the external predictivity have a strong influence on QSAR model reliability. Here, we emphasize the importance of these three aspects by analyzing our models on estrogen receptor binders (Endocrine disruptor knowledge base (EDKB) database). Endocrine disrupting chemicals, which mimic or antagonize the endogenous hormones such as estrogens, are a hot topic in environmental and toxicological sciences. QSAR shows great values in predicting the estrogenic activity and exploring the interactions between the estrogen receptor and ligands. We have verified our previously published model for additional external validation on new EDKB chemicals. Having found some errors in the used 3D molecular conformations, we redevelop a new model using the same data set with corrected structures, the same method (ordinary least-square regression, OLS) and DRAGON descriptors. The new model, based on some different descriptors, is more predictive on external prediction sets. Three different formulas to calculate correlation coefficient for the external prediction set (Q2 EXT) were compared, and the results indicated that the new proposal of Consonni et al. had more reasonable results, consistent with the conclusions from regression line, Williams plot and root mean square error (RMSE) values. Finally, the importance of reliable endpoints values has been highlighted by comparing the classification assignments of EDKB with those of another estrogen receptor binders database (METI): we found that 16.1% assignments of the common compounds were opposite (20 among 124 common compounds). In order to verify the real assignments for these inconsistent compounds, we predicted these samples, as a blind external set, by our regression models and compared the results with the two databases. The results indicated that most of the predictions were consistent with METI. Furthermore, we built a kNN classification model using the 104 consistent compounds to predict those inconsistent ones, and most of the predictions were also in agreement with METI database.

Learning-Induced Plasticity in Medial Prefrontal Cortex Predicts Preference Malleability

PubMed Central

Garvert, Mona M.; Moutoussis, Michael; Kurth-Nelson, Zeb; Behrens, Timothy E.J.; Dolan, Raymond J.

2015-01-01

Summary Learning induces plasticity in neuronal networks. As neuronal populations contribute to multiple representations, we reasoned plasticity in one representation might influence others. We used human fMRI repetition suppression to show that plasticity induced by learning another individual’s values impacts upon a value representation for oneself in medial prefrontal cortex (mPFC), a plasticity also evident behaviorally in a preference shift. We show this plasticity is driven by a striatal “prediction error,” signaling the discrepancy between the other’s choice and a subject’s own preferences. Thus, our data highlight that mPFC encodes agent-independent representations of subjective value, such that prediction errors simultaneously update multiple agents’ value representations. As the resulting change in representational similarity predicts interindividual differences in the malleability of subjective preferences, our findings shed mechanistic light on complex human processes such as the powerful influence of social interaction on beliefs and preferences. PMID:25611512

Predictive value of general movements' quality in low-risk infants for minor neurological dysfunction and behavioural problems at preschool age.

PubMed

Bennema, Anne N; Schendelaar, Pamela; Seggers, Jorien; Haadsma, Maaike L; Heineman, Maas Jan; Hadders-Algra, Mijna

2016-03-01

General movement (GM) assessment is a well-established tool to predict cerebral palsy in high-risk infants. Little is known on the predictive value of GM assessment in low-risk populations. To assess the predictive value of GM quality in early infancy for the development of the clinically relevant form of minor neurological dysfunction (complex MND) and behavioral problems at preschool age. Prospective cohort study. A total of 216 members of the prospective Groningen Assisted Reproductive Techniques (ART) cohort study were included in this study. ART did not affect neurodevelopmental outcome of these relatively low-risk infants born to subfertile parents. GM quality was determined at 2 weeks and 3 months. At 18 months and 4 years, the Hempel neurological examination was used to assess MND. At 4 years, parents completed the Child Behavior Checklist; this resulted in the total problem score (TPS), internalizing problem score (IPS), and externalizing problem score (EPS). Predictive values of definitely (DA) and mildly (MA) abnormal GMs were calculated. DA GMs at 2 weeks were associated with complex MND at 18 months and atypical TPS and IPS at 4 years (all p<0.05). Sensitivity and positive predictive value of DA GMs at 2 weeks were rather low (13%-60%); specificity and negative predictive value were excellent (92%-99%). DA GMs at 3 months occurred too infrequently to calculate prediction. MA GMs were not associated with outcome. GM quality as a single predictor for complex MND and behavioral problems at preschool age has limited clinical value in children at low risk for developmental disorders. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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.

Neural evidence of motivational conflict between social values.

PubMed

Leszkowicz, Emilia; Linden, David E J; Maio, Gregory R; Ihssen, Niklas

2017-10-01

Motivational interdependence is an organizing principle in Schwartz's circumplex model of social values, which has received abundant cross-cultural support. We used fMRI to test whether motivational relations between social values predict different brain responses in a situation of choice between values. We hypothesized that differences in brain responses would become evident when the more important value had to be selected in pairs of congruent (e.g., wealth and success) as opposed to incongruent (e.g., curiosity and stability) values as they are described in Schwartz's model, because the former serve mutually facilitating motives, whereas the latter serve mutually inhibiting motives. Consistent with the model, choosing between congruent values led to longer response times and more activation in conflict-related brain regions (e.g., the supplementary motor area, dorsolateral prefrontal cortex) than selecting between incongruent values. These results provide novel neural evidence supporting the circumplex model's predictions about motivational interdependence between social values. In particular, our results show that the neural networks underlying social values are organized in a way that allows activation patterns related to motivational similarity between congruent values to be dissociated from those related to incongruent values.

Echocardiography and risk prediction in advanced heart failure: incremental value over clinical markers.

PubMed

Agha, Syed A; Kalogeropoulos, Andreas P; Shih, Jeffrey; Georgiopoulou, Vasiliki V; Giamouzis, Grigorios; Anarado, Perry; Mangalat, Deepa; Hussain, Imad; Book, Wendy; Laskar, Sonjoy; Smith, Andrew L; Martin, Randolph; Butler, Javed

2009-09-01

Incremental value of echocardiography over clinical parameters for outcome prediction in advanced heart failure (HF) is not well established. We evaluated 223 patients with advanced HF receiving optimal therapy (91.9% angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, 92.8% beta-blockers, 71.8% biventricular pacemaker, and/or defibrillator use). The Seattle Heart Failure Model (SHFM) was used as the reference clinical risk prediction scheme. The incremental value of echocardiographic parameters for event prediction (death or urgent heart transplantation) was measured by the improvement in fit and discrimination achieved by addition of standard echocardiographic parameters to the SHFM. After a median follow-up of 2.4 years, there were 38 (17.0%) events (35 deaths; 3 urgent transplants). The SHFM had likelihood ratio (LR) chi(2) 32.0 and C statistic 0.756 for event prediction. Left ventricular end-systolic volume, stroke volume, and severe tricuspid regurgitation were independent echocardiographic predictors of events. The addition of these parameters to SHFM improved LR chi(2) to 72.0 and C statistic to 0.866 (P < .001 and P=.019, respectively). Reclassifying the SHFM-predicted risk with use of the echocardiography-added model resulted in improved prognostic separation. Addition of standard echocardiographic variables to the SHFM results in significant improvement in risk prediction for patients with advanced HF.

Prediction of Mechanical Properties of Polymers With Various Force Fields

NASA Technical Reports Server (NTRS)

Odegard, Gregory M.; Clancy, Thomas C.; Gates, Thomas S.

2005-01-01

The effect of force field type on the predicted elastic properties of a polyimide is examined using a multiscale modeling technique. Molecular Dynamics simulations are used to predict the atomic structure and elastic properties of the polymer by subjecting a representative volume element of the material to bulk and shear finite deformations. The elastic properties of the polyimide are determined using three force fields: AMBER, OPLS-AA, and MM3. The predicted values of Young s modulus and shear modulus of the polyimide are compared with experimental values. The results indicate that the mechanical properties of the polyimide predicted with the OPLS-AA force field most closely matched those from experiment. The results also indicate that while the complexity of the force field does not have a significant effect on the accuracy of predicted properties, small differences in the force constants and the functional form of individual terms in the force fields determine the accuracy of the force field in predicting the elastic properties of the polyimide.

Estimating cross-validatory predictive p-values with integrated importance sampling for disease mapping models.

PubMed

Li, Longhai; Feng, Cindy X; Qiu, Shi

2017-06-30

An important statistical task in disease mapping problems is to identify divergent regions with unusually high or low risk of disease. Leave-one-out cross-validatory (LOOCV) model assessment is the gold standard for estimating predictive p-values that can flag such divergent regions. However, actual LOOCV is time-consuming because one needs to rerun a Markov chain Monte Carlo analysis for each posterior distribution in which an observation is held out as a test case. This paper introduces a new method, called integrated importance sampling (iIS), for estimating LOOCV predictive p-values with only Markov chain samples drawn from the posterior based on a full data set. The key step in iIS is that we integrate away the latent variables associated the test observation with respect to their conditional distribution without reference to the actual observation. By following the general theory for importance sampling, the formula used by iIS can be proved to be equivalent to the LOOCV predictive p-value. We compare iIS and other three existing methods in the literature with two disease mapping datasets. Our empirical results show that the predictive p-values estimated with iIS are almost identical to the predictive p-values estimated with actual LOOCV and outperform those given by the existing three methods, namely, the posterior predictive checking, the ordinary importance sampling, and the ghosting method by Marshall and Spiegelhalter (2003). Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

[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.

Gram staining of protected pulmonary specimens in the early diagnosis of ventilator-associated pneumonia.

PubMed

Mimoz, O; Karim, A; Mazoit, J X; Edouard, A; Leprince, S; Nordmann, P

2000-11-01

We evaluated prospectively the use of Gram staining of protected pulmonary specimens to allow the early diagnosis of ventilator-associated pneumonia (VAP), compared with the use of 60 bronchoscopic protected specimen brushes (PSB) and 126 blinded plugged telescopic catheters (PTC) obtained from 134 patients. Gram stains were from Cytospin slides; they were studied for the presence of microorganisms in 10 and 50 fields by two independent observers and classified according to their Gram stain morphology. Quantitative cultures were performed after serial dilution and plating on appropriate culture medium. A final diagnosis of VAP, based on a culture of > or = 10(3) c.f.u. ml-1, was established after 81 (44%) samplings. When 10 fields were analysed, a strong relationship was found between the presence of bacteria on Gram staining and the final diagnosis of VAP (for PSB and PTC respectively: sensitivity 74 and 81%, specificity 94 and 100%, positive predictive value 91 and 100%, negative predictive value 82 and 88%). The correlation was less when we compared the morphology of microorganisms observed on Gram staining with those of bacteria obtained from quantitative cultures (for PSB and PTC respectively: sensitivity 54 and 69%, specificity 86 and 89%, positive predictive value 72 and 78%, negative predictive value 74 and 84%). Increasing the number of fields read to 50 was associated with a slight decrease in specificity and positive predictive value of Gram staining, but with a small increase in its sensitivity and negative predictive value. The results obtained by the two observers were similar to each other for both numbers of fields analysed. Gram staining of protected pulmonary specimens performed on 10 fields predicted the presence of VAP and partially identified (using Gram stain morphology) the microorganisms growing at significant concentrations, and could help in the early choice of the treatment of VAP. Increasing the number of fields read or having the Gram stain analysed by two independent individuals did not improve the results.

An accurate and efficient method to predict the electronic excitation energies of BODIPY fluorescent dyes.

PubMed

Wang, Jia-Nan; Jin, Jun-Ling; Geng, Yun; Sun, Shi-Ling; Xu, Hong-Liang; Lu, Ying-Hua; Su, Zhong-Min

2013-03-15

Recently, the extreme learning machine neural network (ELMNN) as a valid computing method has been proposed to predict the nonlinear optical property successfully (Wang et al., J. Comput. Chem. 2012, 33, 231). In this work, first, we follow this line of work to predict the electronic excitation energies using the ELMNN method. Significantly, the root mean square deviation of the predicted electronic excitation energies of 90 4,4-difluoro-4-bora-3a,4a-diaza-s-indacene (BODIPY) derivatives between the predicted and experimental values has been reduced to 0.13 eV. Second, four groups of molecule descriptors are considered when building the computing models. The results show that the quantum chemical descriptions have the closest intrinsic relation with the electronic excitation energy values. Finally, a user-friendly web server (EEEBPre: Prediction of electronic excitation energies for BODIPY dyes), which is freely accessible to public at the web site: http://202.198.129.218, has been built for prediction. This web server can return the predicted electronic excitation energy values of BODIPY dyes that are high consistent with the experimental values. We hope that this web server would be helpful to theoretical and experimental chemists in related research. Copyright © 2012 Wiley Periodicals, Inc.

Morality, values, traditional bullying, and cyberbullying in adolescence.

PubMed

Menesini, Ersilia; Nocentini, Annalaura; Camodeca, Marina

2013-03-01

The aim of the present study was to investigate moral aspects and human values in traditional bullying and cyberbullying, in order to detect differences between the two types of bullying and to test the role of immoral and disengaged behaviours in mediating the relationships between personal values and involvement in bullying. Sample comprised 390 adolescents aged 14-18, balanced for gender, attending different high schools. Traditional and cyberbullying were detected by means of two self-report measures, while the Portrait Values Questionnaire was used to assess 10 values in four dimensions according to the value system model by Schwartz (1992): self-trascendence, self-enhancement, openness to change, and conservation. Finally, immoral and disengaged behaviours were assessed by means of five items about behavioural and personal aspects salient for morality. Results showed that, irrespective of gender, self-enhancement and self-trascendence moderately predicted cyber and traditional bullying, respectively, while immoral and disengaged behaviours predicted both. Indirect effects showed that self-enhancement and openness to change predicted both forms of bullying through immoral behaviour. Results are discussed in terms of similarities and differences between cyber and traditional bullying and with attention to the central role of morality in explaining bullying nature. © 2011 The British Psychological Society.

[Rapid determination of fatty acids in soybean oils by transmission reflection-near infrared spectroscopy].

PubMed

Song, Tao; Zhang, Feng-ping; Liu, Yao-min; Wu, Zong-wen; Suo, You-rui

2012-08-01

In the present research, a novel method was established for determination of five fatty acids in soybean oil by transmission reflection-near infrared spectroscopy. The optimum conditions of mathematics model of five components (C16:0, C18:0, C18:1, C18:2 and C18:3) were studied, including the sample set selection, chemical value analysis, the detection methods and condition. Chemical value was analyzed by gas chromatography. One hundred fifty eight samples were selected, 138 for modeling set, 10 for testing set and 10 for unknown sample set. All samples were placed in sample pools and scanned by transmission reflection-near infrared spectrum after sonicleaning for 10 minute. The 1100-2500 nm spectral region was analyzed. The acquisition interval was 2 nm. Modified partial least square method was chosen for calibration mode creating. Result demonstrated that the 1-VR of five fatty acids between the reference value of the modeling sample set and the near infrared spectrum predictive value were 0.8839, 0.5830, 0.9001, 0.9776 and 0.9596, respectively. And the SECV of five fatty acids between the reference value of the modeling sample set and the near infrared spectrum predictive value were 0.42, 0.29, 0.83, 0.46 and 0.21, respectively. The standard error of the calibration (SECV) of five fatty acids between the reference value of testing sample set and the near infrared spectrum predictive value were 0.891, 0.790, 0.900, 0.976 and 0.942, respectively. It was proved that the near infrared spectrum predictive value was linear with chemical value and the mathematical model established for fatty acids of soybean oil was feasible. For validation, 10 unknown samples were selected for analysis by near infrared spectrum. The result demonstrated that the relative standard deviation between predict value and chemical value was less than 5.50%. That was to say that transmission reflection-near infrared spectroscopy had a good veracity in analysis of fatty acids of soybean oil.

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.

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.

Breast cancer mammographic diagnosis performance in a public health institution: a retrospective cohort study.

PubMed

Mello, Juliana M R B; Bittelbrunn, Fernando P; Rockenbach, Marcio A B C; May, Guilherme G; Vedolin, Leonardo M; Kruger, Marilia S; Soldatelli, Matheus D; Zwetsch, Guilherme; de Miranda, Gabriel T F; Teixeira, Saone I P; Arruda, Bruna S

2017-12-01

To evaluate the quality assurance of mammography results at a reference institution for the diagnosis and treatment of breast cancer in southern Brazil, based on the BIRADS (Breast Imaging Reporting and Data System) 5th edition recommendations for auditing purposes. Retrospective cohort and cross-sectional study with 4502 patients (9668 mammographies)) who underwent at least one or both breast mammographies throughout 2013 at a regional public hospital, linked to a federal public university. The results were followed until 31 December 2014, including true positives (TPs), true negatives (TNs), false positives (FPs), false negatives (FNs), positive predictive values (PPVs), negative predictive value (NPV), sensitivity and specificity, with a confidence interval of 95%. The study showed high quality assurance, particularly regarding sensitivity (90.22%) and specificity (92.31%). The overall positive predictive value (PPV) was 65.35%, and the negative predictive value (NPV) was 98.32%. The abnormal interpretation rate (recall rate) was 12.26%. The results are appropriate when compared to the values proposed by the BIRADS 5th edition. Additionally, the study provided self-reflection considering our radiological practice, which is essential for improvements and collaboration regarding breast cancer detection. It may stimulate better radiological practice performance and continuing education, despite possible infrastructure and facility limitations. • Accurate quality performance rates are possible despite financial and governmental limitations. • Low-income institutions should develop standardised teamwork to improve radiological practice. • Regular mammography audits may help to increase the quality of public health systems.

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.

Increasing discomfort tolerance predicts incentive senitization of exercise reinforcement: Preliminary results from a randomized controlled intervention to increase the reinforcing value of exercise in overweight to obese adu

USDA-ARS?s Scientific Manuscript database

Objective: The reinforcing (motivating) value of exercise/physical activity (RRVex) predicts usual exercise behavior and meeting of physical activity guidelines. Recent cross-sectional evidence suggests, for the first time, that greater tolerance for the discomfort experienced during exercise is ass...

Potential uncertainty reduction in model-averaged benchmark dose estimates informed by an additional dose study.

PubMed

Shao, Kan; Small, Mitchell J

2011-10-01

A methodology is presented for assessing the information value of an additional dosage experiment in existing bioassay studies. The analysis demonstrates the potential reduction in the uncertainty of toxicity metrics derived from expanded studies, providing insights for future studies. Bayesian methods are used to fit alternative dose-response models using Markov chain Monte Carlo (MCMC) simulation for parameter estimation and Bayesian model averaging (BMA) is used to compare and combine the alternative models. BMA predictions for benchmark dose (BMD) are developed, with uncertainty in these predictions used to derive the lower bound BMDL. The MCMC and BMA results provide a basis for a subsequent Monte Carlo analysis that backcasts the dosage where an additional test group would have been most beneficial in reducing the uncertainty in the BMD prediction, along with the magnitude of the expected uncertainty reduction. Uncertainty reductions are measured in terms of reduced interval widths of predicted BMD values and increases in BMDL values that occur as a result of this reduced uncertainty. The methodology is illustrated using two existing data sets for TCDD carcinogenicity, fitted with two alternative dose-response models (logistic and quantal-linear). The example shows that an additional dose at a relatively high value would have been most effective for reducing the uncertainty in BMA BMD estimates, with predicted reductions in the widths of uncertainty intervals of approximately 30%, and expected increases in BMDL values of 5-10%. The results demonstrate that dose selection for studies that subsequently inform dose-response models can benefit from consideration of how these models will be fit, combined, and interpreted. © 2011 Society for Risk Analysis.

Rapid detection and ruling out of neonatal sepsis by PCR coupled with Electrospray Ionization Mass Spectrometry (PCR/ESI-MS).

PubMed

Delcò, Cristina; Karam, Oliver; Pfister, Riccardo; Gervaix, Alain; Renzi, Gesuele; Emonet, Stéphane; Schrenzel, Jacques; Posfay-Barbe, Klara M

2017-05-01

Sepsis is an important cause of morbidity and mortality in neonates and clinicians are typically required to administer empiric antibiotics while waiting for blood culture results. However, prolonged and inappropriate use of antibiotics is associated with various complications and adverse events. Better tools to rapidly rule out bacterial infections are therefore needed. We aimed to assess the negative predictive value of PCR coupled with Electrospray Ionization Mass Spectrometry (PCR/ESI-MS) compared to conventional blood cultures in neonatal sepsis. Prospective observational study. All consecutive neonates (<28days old) with clinical suspicion of sepsis. Samples for PCR/ESI-MS analysis were collected at the same time as samples for the blood culture, before the initiation of antibiotics. Our primary objective was to evaluate the negative predictive value of PCR/ESI-MS for the detection of bacteria in the bloodstream of newborns with suspected sepsis. Our secondary objective was the evaluation of the sensitivity, specificity and positive predictive value of the PCR/ESI-MS in such a neonatal population. We analysed 114 samples over 14months. The median age and weight were 32weeks+3days and 1840g, respectively. Two patients had negative PCR/ESI-MS results, but positive blood cultures. Overall, the negative predictive value was 98% (95%CI: 92% to 100%). Based on these results, PCR/ESI-MS analysis of blood samples of neonates with suspected sepsis appears to have a very good negative predictive value when compared to blood cultures as gold standard. This novel test might allow for early reassessment of the need for antibiotics. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluation of a method of estimating low-flow frequencies from base-flow measurements at Indiana streams

USGS Publications Warehouse

Wilson, John Thomas

2000-01-01

A mathematical technique of estimating low-flow frequencies from base-flow measurements was evaluated by using data for streams in Indiana. Low-flow frequencies at low- flow partial-record stations were estimated by relating base-flow measurements to concurrent daily flows at nearby streamflow-gaging stations (index stations) for which low-flowfrequency curves had been developed. A network of long-term streamflow-gaging stations in Indiana provided a sample of sites with observed low-flow frequencies. Observed values of 7-day, 10-year low flow and 7-day, 2-year low flow were compared to predicted values to evaluate the accuracy of the method. Five test cases were used to evaluate the method under a variety of conditions in which the location of the index station and its drainage area varied relative to the partial-record station. A total of 141 pairs of streamflow-gaging stations were used in the five test cases. Four of the test cases used one index station, the fifth test case used two index stations. The number of base-flow measurements was varied for each test case to see if the accuracy of the method was affected by the number of measurements used. The most accurate and least variable results were produced when two index stations on the same stream or tributaries of the partial-record station were used. All but one value of the predicted 7-day, 10-year low flow were within 15 percent of the values observed for the long-term continuous record, and all of the predicted values of the 7-day, 2-year lowflow were within 15 percent of the observed values. This apparent accuracy, to some extent, may be a result of the small sample set of 15. Of the four test cases that used one index station, the most accurate and least variable results were produced in the test case where the index station and partial-record station were on the same stream or on streams tributary to each other and where the index station had a larger drainage area than the partial-record station. In that test case, the method tended to over predict, based on the median relative error. In 23 of 28 test pairs, the predicted 7-day, 10-year low flow was within 15 percent of the observed value; in 26 of 28 test pairs, the predicted 7-day, 2-year low flow was within 15 percent of the observed value. When the index station and partial-record station were on the same stream or streams tributary to each other and the index station had a smaller drainage area than the partial-record station, the method tended to under predict the low-flow frequencies. Nineteen of 28 predicted values of the 7-day, 10-year low flow were within 15 percent of the observed values. Twenty-five of 28 predicted values of the 7-day, 2-year low flow were within 15 percent of the observed values. When the index station and the partial-record station were on different streams, the method tended to under predict regardless of whether the index station had a larger or smaller drainage area than that of the partial-record station. Also, the variability of the relative error of estimate was greatest for the test cases that used index stations and partial-record stations from different streams. This variability, in part, may be caused by using more streamflow-gaging stations with small low-flow frequencies in these test cases. A small difference in the predicted and observed values can equate to a large relative error when dealing with stations that have small low-flow frequencies. In the test cases that used one index station, the method tended to predict smaller low-flow frequencies as the number of base-flow measurements was reduced from 20 to 5. Overall, the average relative error of estimate and the variability of the predicted values increased as the number of base-flow measurements was reduced.

A new model of cavern diameter based on a validated CFD study on stirring of a highly shear-thinning fluid.

PubMed

Story, Anna; Jaworski, Zdzisław

2017-01-01

Results of numerical simulations of momentum transfer for a highly shear-thinning fluid (0.2% Carbopol) in a stirred tank equipped with a Prochem Maxflo T type impeller are presented. The simulation results were validated using LDA data and both tangential and axial force measurements in the laminar and early transitional flow range. A good agreement between the predicted and experimental results of the local fluid velocity components was found. From the predicted and experimental values of both tangential and axial forces, the power number, Po , and thrust number, Th , were also calculated. Values of the absolute relative deviations were below 4.0 and 10.5%, respectively, for Po and Th , which confirms a satisfactory agreement with experiments. An intensive mixing zone, known as cavern, was observed near the impeller. In this zone, the local values of fluid velocity, strain rate, Metzner-Otto coefficient, shear stress and intensity of energy dissipation were all characterized by strong variability. Based on the results of experimental study a new model using non-dimensional impeller force number was proposed to predict the cavern diameter. Comparative numerical simulations were also carried out for a Newtonian fluid (water) and their results were similarly well verified using LDA measurements, as well as experimental power number values.

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

USGS Publications Warehouse

Schilling, Steve P.

2014-01-01

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

Statistical Approaches for Spatiotemporal Prediction of Low Flows

NASA Astrophysics Data System (ADS)

Fangmann, A.; Haberlandt, U.

2017-12-01

An adequate assessment of regional climate change impacts on streamflow requires the integration of various sources of information and modeling approaches. This study proposes simple statistical tools for inclusion into model ensembles, which are fast and straightforward in their application, yet able to yield accurate streamflow predictions in time and space. Target variables for all approaches are annual low flow indices derived from a data set of 51 records of average daily discharge for northwestern Germany. The models require input of climatic data in the form of meteorological drought indices, derived from observed daily climatic variables, averaged over the streamflow gauges' catchments areas. Four different modeling approaches are analyzed. Basis for all pose multiple linear regression models that estimate low flows as a function of a set of meteorological indices and/or physiographic and climatic catchment descriptors. For the first method, individual regression models are fitted at each station, predicting annual low flow values from a set of annual meteorological indices, which are subsequently regionalized using a set of catchment characteristics. The second method combines temporal and spatial prediction within a single panel data regression model, allowing estimation of annual low flow values from input of both annual meteorological indices and catchment descriptors. The third and fourth methods represent non-stationary low flow frequency analyses and require fitting of regional distribution functions. Method three is subject to a spatiotemporal prediction of an index value, method four to estimation of L-moments that adapt the regional frequency distribution to the at-site conditions. The results show that method two outperforms successive prediction in time and space. Method three also shows a high performance in the near future period, but since it relies on a stationary distribution, its application for prediction of far future changes may be problematic. Spatiotemporal prediction of L-moments appeared highly uncertain for higher-order moments resulting in unrealistic future low flow values. All in all, the results promote an inclusion of simple statistical methods in climate change impact assessment.

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.

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

PubMed

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

2015-09-01

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

Investigating the intrinsic and extrinsic work values of 10th grade students in science-oriented charter schools

NASA Astrophysics Data System (ADS)

Ozer, Ozgur

The purpose of this study was to investigate to what extent gender, achievement level, and income level predict the intrinsic and extrinsic work values of 10th grade students. The study explored whether group differences were good predictors of scores in work values. The research was a descriptive, cross-sectional study conducted on 131 10th graders who attended science-oriented charter schools. Students took Super's Work Values Instrument, a Likert-type test that links to 15 work values, which can be categorized as intrinsic and extrinsic values (Super, 1970). Multiple regression analysis was employed as the main analysis followed by ANCOVA. Multiple regression analysis results indicated that there is evidence that 8.9% of the variance in intrinsic work values and 10.2% of the variance in extrinsic work values can be explained by the independent variables ( p < .05). Achievement Level and Income Level may help predict intrinsic work value scores; Achievement Level may also help predict extrinsic work values. Achievement Level was the covariate in ANCOVA. Results indicated that males (M = .174) in this sample have a higher mean of extrinsic work values than that of females (M = -.279). However, there was no statistically significant difference between the intrinsic work values by gender. One possible interpretation of this might be school choice; students in these science-oriented charter schools may have higher intrinsic work values regardless of gender. Results indicated that there was no statistically significant difference among the means of extrinsic work values by income level (p < .05). However, free lunch students (M = .268) have a higher mean of intrinsic work values than that of paid lunch students ( M = -.279). A possible interpretation of this might be that lower income students benefit greatly from the intrinsic work values in overcoming obstacles. Further research is needed in each of these areas. The study produced statistically significant results with little practical significance. Students, parents, teachers, and counselors may still be advised to consider the work value orientations of students during the career choice process.

Comparison of Taxi Time Prediction Performance Using Different Taxi Speed Decision Trees

NASA Technical Reports Server (NTRS)

Lee, Hanbong

2017-01-01

In the STBO modeler and tactical surface scheduler for ATD-2 project, taxi speed decision trees are used to calculate the unimpeded taxi times of flights taxiing on the airport surface. The initial taxi speed values in these decision trees did not show good prediction accuracy of taxi times. Using the more recent, reliable surveillance data, new taxi speed values in ramp area and movement area were computed. Before integrating these values into the STBO system, we performed test runs using live data from Charlotte airport, with different taxi speed settings: 1) initial taxi speed values and 2) new ones. Taxi time prediction performance was evaluated by comparing various metrics. The results show that the new taxi speed decision trees can calculate the unimpeded taxi-out times more accurately.

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.

Statistical procedures for evaluating daily and monthly hydrologic model predictions

USGS Publications Warehouse

Coffey, M.E.; Workman, S.R.; Taraba, J.L.; Fogle, A.W.

2004-01-01

The overall study objective was to evaluate the applicability of different qualitative and quantitative methods for comparing daily and monthly SWAT computer model hydrologic streamflow predictions to observed data, and to recommend statistical methods for use in future model evaluations. Statistical methods were tested using daily streamflows and monthly equivalent runoff depths. The statistical techniques included linear regression, Nash-Sutcliffe efficiency, nonparametric tests, t-test, objective functions, autocorrelation, and cross-correlation. None of the methods specifically applied to the non-normal distribution and dependence between data points for the daily predicted and observed data. Of the tested methods, median objective functions, sign test, autocorrelation, and cross-correlation were most applicable for the daily data. The robust coefficient of determination (CD*) and robust modeling efficiency (EF*) objective functions were the preferred methods for daily model results due to the ease of comparing these values with a fixed ideal reference value of one. Predicted and observed monthly totals were more normally distributed, and there was less dependence between individual monthly totals than was observed for the corresponding predicted and observed daily values. More statistical methods were available for comparing SWAT model-predicted and observed monthly totals. The 1995 monthly SWAT model predictions and observed data had a regression Rr2 of 0.70, a Nash-Sutcliffe efficiency of 0.41, and the t-test failed to reject the equal data means hypothesis. The Nash-Sutcliffe coefficient and the R r2 coefficient were the preferred methods for monthly results due to the ability to compare these coefficients to a set ideal value of one.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Multi-allelic haplotype model based on genetic partition for genomic prediction and variance component estimation using SNP markers.

PubMed

Da, Yang

2015-12-18

The amount of functional genomic information has been growing rapidly but remains largely unused in genomic selection. Genomic prediction and estimation using haplotypes in genome regions with functional elements such as all genes of the genome can be an approach to integrate functional and structural genomic information for genomic selection. Towards this goal, this article develops a new haplotype approach for genomic prediction and estimation. A multi-allelic haplotype model treating each haplotype as an 'allele' was developed for genomic prediction and estimation based on the partition of a multi-allelic genotypic value into additive and dominance values. Each additive value is expressed as a function of h - 1 additive effects, where h = number of alleles or haplotypes, and each dominance value is expressed as a function of h(h - 1)/2 dominance effects. For a sample of q individuals, the limit number of effects is 2q - 1 for additive effects and is the number of heterozygous genotypes for dominance effects. Additive values are factorized as a product between the additive model matrix and the h - 1 additive effects, and dominance values are factorized as a product between the dominance model matrix and the h(h - 1)/2 dominance effects. Genomic additive relationship matrix is defined as a function of the haplotype model matrix for additive effects, and genomic dominance relationship matrix is defined as a function of the haplotype model matrix for dominance effects. Based on these results, a mixed model implementation for genomic prediction and variance component estimation that jointly use haplotypes and single markers is established, including two computing strategies for genomic prediction and variance component estimation with identical results. The multi-allelic genetic partition fills a theoretical gap in genetic partition by providing general formulations for partitioning multi-allelic genotypic values and provides a haplotype method based on the quantitative genetics model towards the utilization of functional and structural genomic information for genomic prediction and estimation.

Prediction of daily sea surface temperature using efficient neural networks

NASA Astrophysics Data System (ADS)

Patil, Kalpesh; Deo, Makaranad Chintamani

2017-04-01

Short-term prediction of sea surface temperature (SST) is commonly achieved through numerical models. Numerical approaches are more suitable for use over a large spatial domain than in a specific site because of the difficulties involved in resolving various physical sub-processes at local levels. Therefore, for a given location, a data-driven approach such as neural networks may provide a better alternative. The application of neural networks, however, needs a large experimentation in their architecture, training methods, and formation of appropriate input-output pairs. A network trained in this manner can provide more attractive results if the advances in network architecture are additionally considered. With this in mind, we propose the use of wavelet neural networks (WNNs) for prediction of daily SST values. The prediction of daily SST values was carried out using WNN over 5 days into the future at six different locations in the Indian Ocean. First, the accuracy of site-specific SST values predicted by a numerical model, ROMS, was assessed against the in situ records. The result pointed out the necessity for alternative approaches. First, traditional networks were tried and after noticing their poor performance, WNN was used. This approach produced attractive forecasts when judged through various error statistics. When all locations were viewed together, the mean absolute error was within 0.18 to 0.32 °C for a 5-day-ahead forecast. The WNN approach was thus found to add value to the numerical method of SST prediction when location-specific information is desired.

The Conforming Brain and Deontological Resolve

PubMed Central

Pincus, Melanie; LaViers, Lisa; Prietula, Michael J.; Berns, Gregory

2014-01-01

Our personal values are subject to forces of social influence. Deontological resolve captures how strongly one relies on absolute rules of right and wrong in the representation of one's personal values and may predict willingness to modify one's values in the presence of social influence. Using fMRI, we found that a neurobiological metric for deontological resolve based on relative activity in the ventrolateral prefrontal cortex (VLPFC) during the passive processing of sacred values predicted individual differences in conformity. Individuals with stronger deontological resolve, as measured by greater VLPFC activity, displayed lower levels of conformity. We also tested whether responsiveness to social reward, as measured by ventral striatal activity during social feedback, predicted variability in conformist behavior across individuals but found no significant relationship. From these results we conclude that unwillingness to conform to others' values is associated with a strong neurobiological representation of social rules. PMID:25170989

Goal-directed EEG activity evoked by discriminative stimuli in reinforcement learning.

PubMed

Luque, David; Morís, Joaquín; Rushby, Jacqueline A; Le Pelley, Mike E

2015-02-01

In reinforcement learning (RL), discriminative stimuli (S) allow agents to anticipate the value of a future outcome, and the response that will produce that outcome. We examined this processing by recording EEG locked to S during RL. Incentive value of outcomes and predictive value of S were manipulated, allowing us to discriminate between outcome-related and response-related activity. S predicting the correct response differed from nonpredictive S in the P2. S paired with high-value outcomes differed from those paired with low-value outcomes in a frontocentral positivity and in the P3b. A slow negativity then distinguished between predictive and nonpredictive S. These results suggest that, first, attention prioritizes detection of informative S. Activation of mental representations of these informative S then retrieves representations of outcomes, which in turn retrieve representations of responses that previously produced those outcomes. © 2014 Society for Psychophysiological Research.

In silico Study of the Pharmacologic Properties and Cytotoxicity Pathways in Cancer Cells of Various Indolylquinone Analogues of Perezone.

PubMed

Escobedo-González, René; Vargas-Requena, Claudia Lucia; Moyers-Montoya, Edgar; Aceves-Hernández, Juan Manuel; Nicolás-Vázquez, María Inés; Miranda-Ruvalcaba, René

2017-06-25

Several indolylquinone analogues of perezone, a natural sesquiterpene quinone, were characterized in this work by theoretical methods. In addition, some physicochemical, toxicological and metabolic properties were predicted using bioinformatics software. The predicted physicochemical properties are in agreement with the solubility and cLogP values, the penetration across the cell membrane, and absorption values, as well as with a possible apoptosis-activated mechanism of cytotoxic action. The toxicological predictions suggest no mutagenic, tumorigenic or reproductive effects of the four target molecules. Complementarily, the results of a performed docking study show high scoring values and hydrogen bonding values in agreement with the cytotoxicity IC 50 value ranking, i.e: indolylmenadione > indolylperezone > indolylplumbagine > indolylisoperezone. Consequently, it is possible to suggest an appropriate apoptotic pathway for each compound. Finally, potential metabolic pathways of the molecules were proposed.

Can non‐clinical repolarization assays predict the results of clinical thorough QT studies? Results from a research consortium

PubMed Central

Park, Eunjung; Gintant, Gary A; Bi, Daoqin; Kozeli, Devi; Pettit, Syril D; Skinner, Matthew; Willard, James; Wisialowski, Todd; Koerner, John; Valentin, Jean‐Pierre

2018-01-01

Background and Purpose Translation of non‐clinical markers of delayed ventricular repolarization to clinical prolongation of the QT interval corrected for heart rate (QTc) (a biomarker for torsades de pointes proarrhythmia) remains an issue in drug discovery and regulatory evaluations. We retrospectively analysed 150 drug applications in a US Food and Drug Administration database to determine the utility of established non‐clinical in vitro IKr current human ether‐à‐go‐go‐related gene (hERG), action potential duration (APD) and in vivo (QTc) repolarization assays to detect and predict clinical QTc prolongation. Experimental Approach The predictive performance of three non‐clinical assays was compared with clinical thorough QT study outcomes based on free clinical plasma drug concentrations using sensitivity and specificity, receiver operating characteristic (ROC) curves, positive (PPVs) and negative predictive values (NPVs) and likelihood ratios (LRs). Key Results Non‐clinical assays demonstrated robust specificity (high true negative rate) but poor sensitivity (low true positive rate) for clinical QTc prolongation at low‐intermediate (1×–30×) clinical exposure multiples. The QTc assay provided the most robust PPVs and NPVs (ability to predict clinical QTc prolongation). ROC curves (overall test accuracy) and LRs (ability to influence post‐test probabilities) demonstrated overall marginal performance for hERG and QTc assays (best at 30× exposures), while the APD assay demonstrated minimal value. Conclusions and Implications The predictive value of hERG, APD and QTc assays varies, with drug concentrations strongly affecting translational performance. While useful in guiding preclinical candidates without clinical QT prolongation, hERG and QTc repolarization assays provide greater value compared with the APD assay. PMID:29181850

Health fair screening: the clinical utility of the comprehensive metabolic profile.

PubMed

Alpert, Jeffrey P; Greiner, Allen; Hall, Sandra

2004-01-01

Health fairs are a common method used by providers and health care organizations to provide screening tests, including comprehensive metabolic profiles (CMPs), to asymptomatic individuals. No national organizations currently recommend the complete CMP as a screening test for asymptomatic individuals in primary care settings. This study evaluated the value of CMPs in a health fair setting by measuring the ability of a health fair CMP to predict new medical diagnoses among residents of a sparsely populated rural county. Volunteer participants submitted fasting blood samples at a health fair conducted by a county health center in a county with 2,531 total residents. CMP values were determined to be "normal" or "abnormal" based on laboratory reference ranges and clinical judgment of the health center physicians. Medical records were reviewed 4 months later to determine if participants with abnormal CMP values had been diagnosed with new medical conditions as a result of the screening tests. Analysis was conducted to evaluate CMP test characteristics and determine whether demographic factors or specific CMP values predicted new medical diagnoses in the participants. Out of 478 health fair participants, 73 individuals had at least one abnormal CMP value. The most frequently occurring abnormal value was an elevated glucose level, with Hispanic participants significantly more likely to have this abnormality than whites. After all evaluation was completed, only about 1% of tested subjects had a new diagnosis as a result of the screening CMP test; most abnormal CMP tests did not result in a new diagnosis. The positive predictive value for an abnormal test resulting in a new medical diagnosis was 0.356. Comprehensive metabolic profiles have limited value as a screening tool in asymptomatic populations at health fairs.

Predictive modelling of flow in a two-dimensional intermediate-scale, heterogeneous porous media

USGS Publications Warehouse

Barth, Gilbert R.; Hill, M.C.; Illangasekare, T.H.; Rajaram, H.

2000-01-01

To better understand the role of sedimentary structures in flow through porous media, and to determine how small-scale laboratory-measured values of hydraulic conductivity relate to in situ values this work deterministically examines flow through simple, artificial structures constructed for a series of intermediate-scale (10 m long), two-dimensional, heterogeneous, laboratory experiments. Nonlinear regression was used to determine optimal values of in situ hydraulic conductivity, which were compared to laboratory-measured values. Despite explicit numerical representation of the heterogeneity, the optimized values were generally greater than the laboratory-measured values. Discrepancies between measured and optimal values varied depending on the sand sieve size, but their contribution to error in the predicted flow was fairly consistent for all sands. Results indicate that, even under these controlled circumstances, laboratory-measured values of hydraulic conductivity need to be applied to models cautiously.To better understand the role of sedimentary structures in flow through porous media, and to determine how small-scale laboratory-measured values of hydraulic conductivity relate to in situ values this work deterministically examines flow through simple, artificial structures constructed for a series of intermediate-scale (10 m long), two-dimensional, heterogeneous, laboratory experiments. Nonlinear regression was used to determine optimal values of in situ hydraulic conductivity, which were compared to laboratory-measured values. Despite explicit numerical representation of the heterogeneity, the optimized values were generally greater than the laboratory-measured values. Discrepancies between measured and optimal values varied depending on the sand sieve size, but their contribution to error in the predicted flow was fairly consistent for all sands. Results indicate that, even under these controlled circumstances, laboratory-measured values of hydraulic conductivity need to be applied to models cautiously.

Predicting mixture toxicity of seven phenolic compounds with similar and dissimilar action mechanisms to Vibrio qinghaiensis sp.nov.Q67.

PubMed

Huang, Wei Ying; Liu, Fei; Liu, Shu Shen; Ge, Hui Lin; Chen, Hong Han

2011-09-01

The predictions of mixture toxicity for chemicals are commonly based on two models: concentration addition (CA) and independent action (IA). Whether the CA and IA can predict mixture toxicity of phenolic compounds with similar and dissimilar action mechanisms was studied. The mixture toxicity was predicted on the basis of the concentration-response data of individual compounds. Test mixtures at different concentration ratios and concentration levels were designed using two methods. The results showed that the Weibull function fit well with the concentration-response data of all the components and their mixtures, with all relative coefficients (Rs) greater than 0.99 and root mean squared errors (RMSEs) less than 0.04. The predicted values from CA and IA models conformed to observed values of the mixtures. Therefore, it can be concluded that both CA and IA can predict reliable results for the mixture toxicity of the phenolic compounds with similar and dissimilar action mechanisms. Copyright © 2011 Elsevier Inc. All rights reserved.

Quantum-gravity predictions for the fine-structure constant

NASA Astrophysics Data System (ADS)

Eichhorn, Astrid; Held, Aaron; Wetterich, Christof

2018-07-01

Asymptotically safe quantum fluctuations of gravity can uniquely determine the value of the gauge coupling for a large class of grand unified models. In turn, this makes the electromagnetic fine-structure constant calculable. The balance of gravity and matter fluctuations results in a fixed point for the running of the gauge coupling. It is approached as the momentum scale is lowered in the transplanckian regime, leading to a uniquely predicted value of the gauge coupling at the Planck scale. The precise value of the predicted fine-structure constant depends on the matter content of the grand unified model. It is proportional to the gravitational fluctuation effects for which computational uncertainties remain to be settled.

Prediction of heart transplant rejection with a breath test for markers of oxidative stress.

PubMed

Phillips, Michael; Boehmer, John P; Cataneo, Renee N; Cheema, Taseer; Eisen, Howard J; Fallon, John T; Fisher, Peter E; Gass, Alan; Greenberg, Joel; Kobashigawa, Jon; Mancini, Donna; Rayburn, Barry; Zucker, Mark J

2004-12-15

The Heart Allograft Rejection: Detection with Breath Alkanes in Low Levels study evaluated a breath test for oxidative stress in heart transplant recipients, and we report here a mathematical model predicting the probability of grade 3 rejection. The breath test divided the heart transplant recipients into 3 groups: positive for grade 3 rejection, negative for grade 3 rejection, and intermediate. The test was 100% sensitive for grade 3 heart transplant rejection when the p value was >/=0.98, and 100% specific when the p value was

Sensitivity, specificity, positive and negative predictive values: diagnosing purple mange.

PubMed

Collier, Jill; Huebscher, Roxana

2010-04-01

To shed light on several epidemiological terms for better understanding of diagnostic testing measures by using a mythical condition, "purple mange." Scientific literature related to epidemiology and statistical tests. Nurse practitioners (NPs) use the concepts of sensitivity (SEN), specificity (SPEC), positive predictive value (PPV), and negative predictive value (NPV) daily in primary care and specialty areas. In addition, PPV and NPV vary with the prevalence of a condition. At times, NPs misunderstand the meaning of these terms. In order to develop appropriate treatment plans, an understanding of the concepts of SEN, SPEC, PPV, and NPV is important for interpreting test results. The authors have used this mythical condition purple mange as a teaching tool for NP students.

Risk factors influencing the early outcome results after laparoscopic repair of perforated duodenal ulcer and their predictive value.

PubMed

Lunevicius, Raimundas; Morkevicius, Matas

2005-09-01

Clear patient selection criteria and indications for laparoscopic repair of perforated duodenal ulcers are necessary. The aims of our study are to report the early outcome results after operation and to define the predictive values of risk factors influencing conversion rate and genesis of suture leakage. Sixty nonrandomly selected patients operated on laparoscopically in a tertiary care academic center between October 1996 and May 2004 for perforated duodenal ulcers were retrospectively analyzed. The primary outcome measures included the duration of symptoms, shock, underlying medical illness, ulcer size, age, Boey score, and the collective predictive value of these variables for conversion and suture leakage rates. Laparoscopic repair was completed in 46 patients (76.7%). Fourteen patients (23.3%) underwent conversion to open repair. Eight patients (13.3%) had postoperative complications. Suture leakage was confirmed in four patients (6.7%). Hospital stay was 7.8+/-5.3 days. There was no mortality. Patients with an ulcer perforation size of >8 mm had a significantly increased risk for conversion to open repair (p<0.05): positive predictive value (PPV) 75%, sensitivity 27%, specificity 98%, and negative predictive value (NPV) 85%. The significance of ulcer perforation size was confirmed by a stepwise logistic regression test (p=0.0201). All patients who developed suture leakage had acute symptoms for >9 h preoperatively (p<0.001): PPV 31%, specificity 84%, sensitivity 100%, and NPV 100%. Conversions happened with surgeons whose previous experience involved 1.8+/-2.3 cases compared to 3.9+/-2.9 cases in successful laparoscopic repair (p=0.039, t test). Ulcer perforation size of >8 mm is a significant risk factor influencing the conversion rate. An increase in the suture leakage rate is predicted by delayed presentation of >9 h.

Coupled rotor/airframe vibration analysis

NASA Technical Reports Server (NTRS)

Sopher, R.; Studwell, R. E.; Cassarino, S.; Kottapalli, S. B. R.

1982-01-01

A coupled rotor/airframe vibration analysis developed as a design tool for predicting helicopter vibrations and a research tool to quantify the effects of structural properties, aerodynamic interactions, and vibration reduction devices on vehicle vibration levels is described. The analysis consists of a base program utilizing an impedance matching technique to represent the coupled rotor/airframe dynamics of the system supported by inputs from several external programs supplying sophisticated rotor and airframe aerodynamic and structural dynamic representation. The theoretical background, computer program capabilities and limited correlation results are presented in this report. Correlation results using scale model wind tunnel results show that the analysis can adequately predict trends of vibration variations with airspeed and higher harmonic control effects. Predictions of absolute values of vibration levels were found to be very sensitive to modal characteristics and results were not representative of measured values.

Ottawa Ankle Rules and Subjective Surgeon Perception to Evaluate Radiograph Necessity Following Foot and Ankle Sprain

PubMed Central

Pires, RES; Pereira, AA; Abreu-e-Silva, GM; Labronici, PJ; Figueiredo, LB; Godoy-Santos, AL; Kfuri, M

2014-01-01

Background: Foot and ankle injuries are frequent in emergency departments. Although only a few patients with foot and ankle sprain present fractures and the fracture patterns are almost always simple, lack of fracture diagnosis can lead to poor functional outcomes. Aim: The present study aims to evaluate the reliability of the Ottawa ankle rules and the orthopedic surgeon subjective perception to assess foot and ankle fractures after sprains. Subjects and Methods: A cross-sectional study was conducted from July 2012 to December 2012. Ethical approval was granted. Two hundred seventy-four adult patients admitted to the emergency department with foot and/or ankle sprain were evaluated by an orthopedic surgeon who completed a questionnaire prior to radiographic assessment. The Ottawa ankle rules and subjective perception of foot and/or ankle fractures were evaluated on the questionnaire. Results: Thirteen percent (36/274) patients presented fracture. Orthopedic surgeon subjective analysis showed 55.6% sensitivity, 90.1% specificity, 46.5% positive predictive value and 92.9% negative predictive value. The general orthopedic surgeon opinion accuracy was 85.4%. The Ottawa ankle rules presented 97.2% sensitivity, 7.8% specificity, 13.9% positive predictive value, 95% negative predictive value and 19.9% accuracy respectively. Weight-bearing inability was the Ottawa ankle rule item that presented the highest reliability, 69.4% sensitivity, 61.6% specificity, 63.1% accuracy, 21.9% positive predictive value and 93% negative predictive value respectively. Conclusion: The Ottawa ankle rules showed high reliability for deciding when to take radiographs in foot and/or ankle sprains. Weight-bearing inability was the most important isolated item to predict fracture presence. Orthopedic surgeon subjective analysis to predict fracture possibility showed a high specificity rate, representing a confident method to exclude unnecessary radiographic exams. PMID:24971221

Incomplete Data in Smart Grid: Treatment of Values in Electric Vehicle Charging Data

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

Majipour, Mostafa; Chu, Peter; Gadh, Rajit

2014-11-03

In this paper, five imputation methods namely Constant (zero), Mean, Median, Maximum Likelihood, and Multiple Imputation methods have been applied to compensate for missing values in Electric Vehicle (EV) charging data. The outcome of each of these methods have been used as the input to a prediction algorithm to forecast the EV load in the next 24 hours at each individual outlet. The data is real world data at the outlet level from the UCLA campus parking lots. Given the sparsity of the data, both Median and Constant (=zero) imputations improved the prediction results. Since in most missing value casesmore » in our database, all values of that instance are missing, the multivariate imputation methods did not improve the results significantly compared to univariate approaches.« less

Evaluation of relative response factor methodology for demonstrating attainment of ozone in Houston, Texas.

PubMed

Vizuete, William; Biton, Leiran; Jeffries, Harvey E; Couzo, Evan

2010-07-01

In 2007, the U.S. Environmental Protection Agency (EPA) released guidance on demonstrating attainment of the federal ozone (O3) standard. This guidance recommended a change in the use of air quality model (AQM) predictions from an absolute to a relative way. This was accomplished by using a ratio, and not the absolute difference of AQM O3 predictions from a historical year to an attainment year. This ratio of O3 concentrations, labeled the relative response factor (RRF), is multiplied by an average of observed concentrations at every monitor. In this analysis, whether the methodology used to calculate RRFs is severing the source-receptor relationship for a given monitor was investigated. Model predictions were generated with a regulatory AQM system used to support the 2004 Houston-Galveston-Brazoria State Implementation Plan. Following the procedures in the EPA guidance, an attainment demonstration was completed using regulatory AQM predictions and measurements from the Houston ground-monitoring network. Results show that the model predictions used for the RRF calculation were often based on model conditions that were geographically remote from observations and counter to wind flow. Many of the monitors used the same model predictions for an RRF, even if that O3 plume did not impact it. The RRF methodology resulted in severing the true source-receptor relationship for a monitor. This analysis also showed that model performance could influence RRF values, and values at monitoring sites appear to be sensitive to model bias. Results indicate an inverse linear correlation of RRFs with model bias at each monitor (R2 = 0.47), resulting in a change in future O3 design values up to 5 parts per billion (ppb). These results suggest that the application of RRF methodology in Houston, TX, should be changed from using all model predictions above 85 ppb to a method that removes any predictions that are not relevant to the observed source-receptor relationship.

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

Development of an evidence-based approach to external quality assurance for breast cancer hormone receptor immunohistochemistry: comparison of reference values.

PubMed

Makretsov, Nikita; Gilks, C Blake; Alaghehbandan, Reza; Garratt, John; Quenneville, Louise; Mercer, Joel; Palavdzic, Dragana; Torlakovic, Emina E

2011-07-01

External quality assurance and proficiency testing programs for breast cancer predictive biomarkers are based largely on traditional ad hoc design; at present there is no universal consensus on definition of a standard reference value for samples used in external quality assurance programs. To explore reference values for estrogen receptor and progesterone receptor immunohistochemistry in order to develop an evidence-based analytic platform for external quality assurance. There were 31 participating laboratories, 4 of which were previously designated as "expert" laboratories. Each participant tested a tissue microarray slide with 44 breast carcinomas for estrogen receptor and progesterone receptor and submitted it to the Canadian Immunohistochemistry Quality Control Program for analysis. Nuclear staining in 1% or more of the tumor cells was a positive score. Five methods for determining reference values were compared. All reference values showed 100% agreement for estrogen receptor and progesterone receptor scores, when indeterminate results were excluded. Individual laboratory performance (agreement rates, test sensitivity, test specificity, positive predictive value, negative predictive value, and κ value) was very similar for all reference values. Identification of suboptimal performance by all methods was identical for 30 of 31 laboratories. Estrogen receptor assessment of 1 laboratory was discordant: agreement was less than 90% for 3 of 5 reference values and greater than 90% with the use of 2 other reference values. Various reference values provide equivalent laboratory rating. In addition to descriptive feedback, our approach allows calculation of technical test sensitivity and specificity, positive and negative predictive values, agreement rates, and κ values to guide corrective actions.

An empirical model for prediction of household solid waste generation rate - A case study of Dhanbad, India.

PubMed

Kumar, Atul; Samadder, S R

2017-10-01

Accurate prediction of the quantity of household solid waste generation is very much essential for effective management of municipal solid waste (MSW). In actual practice, modelling methods are often found useful for precise prediction of MSW generation rate. In this study, two models have been proposed that established the relationships between the household solid waste generation rate and the socioeconomic parameters, such as household size, total family income, education, occupation and fuel used in the kitchen. Multiple linear regression technique was applied to develop the two models, one for the prediction of biodegradable MSW generation rate and the other for non-biodegradable MSW generation rate for individual households of the city Dhanbad, India. The results of the two models showed that the coefficient of determinations (R 2 ) were 0.782 for biodegradable waste generation rate and 0.676 for non-biodegradable waste generation rate using the selected independent variables. The accuracy tests of the developed models showed convincing results, as the predicted values were very close to the observed values. Validation of the developed models with a new set of data indicated a good fit for actual prediction purpose with predicted R 2 values of 0.76 and 0.64 for biodegradable and non-biodegradable MSW generation rate respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Artificial neural networks as alternative tool for minimizing error predictions in manufacturing ultradeformable nanoliposome formulations.

PubMed

León Blanco, José M; González-R, Pedro L; Arroyo García, Carmen Martina; Cózar-Bernal, María José; Calle Suárez, Marcos; Canca Ortiz, David; Rabasco Álvarez, Antonio María; González Rodríguez, María Luisa

2018-01-01

This work was aimed at determining the feasibility of artificial neural networks (ANN) by implementing backpropagation algorithms with default settings to generate better predictive models than multiple linear regression (MLR) analysis. The study was hypothesized on timolol-loaded liposomes. As tutorial data for ANN, causal factors were used, which were fed into the computer program. The number of training cycles has been identified in order to optimize the performance of the ANN. The optimization was performed by minimizing the error between the predicted and real response values in the training step. The results showed that training was stopped at 10 000 training cycles with 80% of the pattern values, because at this point the ANN generalizes better. Minimum validation error was achieved at 12 hidden neurons in a single layer. MLR has great prediction ability, with errors between predicted and real values lower than 1% in some of the parameters evaluated. Thus, the performance of this model was compared to that of the MLR using a factorial design. Optimal formulations were identified by minimizing the distance among measured and theoretical parameters, by estimating the prediction errors. Results indicate that the ANN shows much better predictive ability than the MLR model. These findings demonstrate the increased efficiency of the combination of ANN and design of experiments, compared to the conventional MLR modeling techniques.

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.

Periprosthetic infection: where do we stand with regard to Gram stain?

PubMed

Ghanem, Elie; Ketonis, Constantinos; Restrepo, Camilo; Joshi, Ashish; Barrack, Robert; Parvizi, Javad

2009-02-01

One of the routinely used intraoperative tests for diagnosis of periprosthetic infection (PPI) is the Gram stain. It is not known if the result of this test can vary according to the type of joint affected or the number of specimen samples collected. We examined the role of this diagnostic test in a large cohort of patients from a single institution. A positive gram stain was defined as the visualization of bacterial cells or "many neutrophils" (> 5 per high-power field) in the smear. The sensitivity, specificity, and predictive values of each individual diagnostic arm of Gram stain were determined. Combinations were performed in series, which required both tests to be positive to confirm infection, and also in parallel, which necessitated both tests to be negative to rule out infection. The presence of organisms and "many" neutrophils on a Gram smear had high specificity (98-100%) and positive predictive value (89-100%) in both THA and TKA. The sensitivities (30-50%) and negative predictive values (70-79%) of the 2 tests were low for both joint types. When the 2 tests were combined in series, the specificity and positive predictive value were absolute (100%). The sensitivity and the negative predictive value improved for both THA and TKA (43-64% and 82%, respectively). Although the 2 diagnostic arms of Gram staining can be combined to achieve improved negative predictive value (82%), Gram stain continues to have little value in ruling out PPI. With the advances in the field of molecular biology, novel diagnostic modalities need to be designed that can replace these traditional and poor tests.

Is the Factor-of-2 Rule Broadly Applicable for Evaluating the Prediction Accuracy of Metal-Toxicity Models?

PubMed

Meyer, Joseph S; Traudt, Elizabeth M; Ranville, James F

2018-01-01

In aquatic toxicology, a toxicity-prediction model is generally deemed acceptable if its predicted median lethal concentrations (LC50 values) or median effect concentrations (EC50 values) are within a factor of 2 of their paired, observed LC50 or EC50 values. However, that rule of thumb is based on results from only two studies: multiple LC50 values for the fathead minnow (Pimephales promelas) exposed to Cu in one type of exposure water, and multiple EC50 values for Daphnia magna exposed to Zn in another type of exposure water. We tested whether the factor-of-2 rule of thumb also is supported in a different dataset in which D. magna were exposed separately to Cd, Cu, Ni, or Zn. Overall, the factor-of-2 rule of thumb appeared to be a good guide to evaluating the acceptability of a toxicity model's underprediction or overprediction of observed LC50 or EC50 values in these acute toxicity tests.

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.

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.

Predicting toxic effects of copper on aquatic biota in mineralized areas by using the Biotic Ligand Model

USGS Publications Warehouse

Smith, Kathleen S.; Ranville, James F.; Adams, M.; Choate, LaDonna M.; Church, Stan E.; Fey, David L.; Wanty, Richard B.; Crock, James G.

2006-01-01

The chemical speciation of metals influences their biological effects. The Biotic Ligand Model (BLM) is a computational approach to predict chemical speciation and acute toxicological effects of metals on aquatic biota. Recently, the U.S. Environmental Protection Agency incorporated the BLM into their regulatory water-quality criteria for copper. Results from three different laboratory copper toxicity tests were compared with BLM predictions for simulated test-waters. This was done to evaluate the ability of the BLM to accurately predict the effects of hardness and concentrations of dissolved organic carbon (DOC) and iron on aquatic toxicity. In addition, we evaluated whether the BLM and the three toxicity tests provide consistent results. Comparison of BLM predictions with two types of Ceriodaphnia dubia toxicity tests shows that there is fairly good agreement between predicted LC50 values computed by the BLM and LC50 values determined from the two toxicity tests. Specifically, the effect of increasing calcium concentration (and hardness) on copper toxicity appears to be minimal. Also, there is fairly good agreement between the BLM and the two toxicity tests for test solutions containing elevated DOC, for which the LC50 is 3-to-5 times greater (less toxic) than the LC50 for the lower-DOC test water. This illustrates the protective effects of DOC on copper toxicity and demonstrates the ability of the BLM to predict these protective effects. In contrast, for test solutions with added iron there is a decrease in LC50 values (increase in toxicity) in results from the two C. dubia toxicity tests, and the agreement between BLM LC50 predictions and results from these toxicity tests is poor. The inability of the BLM to account for competitive iron binding to DOC or DOC fractionation may be a significant shortcoming of the BLM for predicting site- specific water-quality criteria in streams affected by iron-rich acidic drainage in mined and mineralized areas.

A clinical study of ischaemic strokes with micro-albuminuria for risk stratification, short-term predictive value and outcome.

PubMed

Das, Sukdeb; Yadav, Ujjal; Ghosh, Kartik Chandra; Panchadhyayee, Sujoy; Kundu, Shib Shankar; Ganguly, Prasanta Kumar

2012-12-01

Stroke results more than 4.3 million deaths worldwide per annum and 85% of all strokes are ischaemic in nature. Besides numerous modifiable and non-modifiable known risk factors, microalbuminuria is thought to be an important marker of global endothelial dysfunction and associated with cardiovascular disease including stroke. Fifty ischaemic stroke cases and 50 (age, sex matched) control subjects were subjected to study to compare and evaluate risk stratification of micro-albuminuria, its predictive value and outcome on day 1 and day 7 among admitted ischaemic stroke cases.The result was found that micro-albuminuria was present in 66% of ischaemic stroke cases compared to only 8% of control group (p < 0.001). Most validated National Institute of Health Stroke Scale (NIHSS) score was used for evaluation and calculation of predictive value and outcome of micro-albuminuria positive patient where higher value indicates poor prognosis, and the result was mean NIHSS score 29.12 versus 18.88 between two groups of strokes ie, with and without micro-albuminuria. Out of 50 ischaemic stroke patients 33 (66%) had micro-albuminuria. Among 11 patients who died, 10 (90.9%) had micro-albuminuria and NIHSS score was 33.64 and 25.0 on day 1 and day 7. Among 39 patients who were discharged, 23 patients (58.97%) were MA positive and NIHSS score was much less than death group ie, 23.38 and 16.38 on day 1 and day 7 respectively. So this study reveals micro-albuminuria itself results higher risk for ischaemic stroke compared to control group and it shows good predictive value for early assessment of clinical severity and subsequent fatal outcome. This is also simple, cost effective and affordable.

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 lung cancer patient survival via supervised machine learning classification techniques.

PubMed

Lynch, Chip M; Abdollahi, Behnaz; Fuqua, Joshua D; de Carlo, Alexandra R; Bartholomai, James A; Balgemann, Rayeanne N; van Berkel, Victor H; Frieboes, Hermann B

2017-12-01

Outcomes for cancer patients have been previously estimated by applying various machine learning techniques to large datasets such as the Surveillance, Epidemiology, and End Results (SEER) program database. In particular for lung cancer, it is not well understood which types of techniques would yield more predictive information, and which data attributes should be used in order to determine this information. In this study, a number of supervised learning techniques is applied to the SEER database to classify lung cancer patients in terms of survival, including linear regression, Decision Trees, Gradient Boosting Machines (GBM), Support Vector Machines (SVM), and a custom ensemble. Key data attributes in applying these methods include tumor grade, tumor size, gender, age, stage, and number of primaries, with the goal to enable comparison of predictive power between the various methods The prediction is treated like a continuous target, rather than a classification into categories, as a first step towards improving survival prediction. The results show that the predicted values agree with actual values for low to moderate survival times, which constitute the majority of the data. The best performing technique was the custom ensemble with a Root Mean Square Error (RMSE) value of 15.05. The most influential model within the custom ensemble was GBM, while Decision Trees may be inapplicable as it had too few discrete outputs. The results further show that among the five individual models generated, the most accurate was GBM with an RMSE value of 15.32. Although SVM underperformed with an RMSE value of 15.82, statistical analysis singles the SVM as the only model that generated a distinctive output. The results of the models are consistent with a classical Cox proportional hazards model used as a reference technique. We conclude that application of these supervised learning techniques to lung cancer data in the SEER database may be of use to estimate patient survival time with the ultimate goal to inform patient care decisions, and that the performance of these techniques with this particular dataset may be on par with that of classical methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Sensitivity and positive predictive values of presurgical clinical diagnosis of excised benign and malignant skin tumors: a prospective study of 835 lesions in 778 patients.

PubMed

Har-Shai, Y; Hai, N; Taran, A; Mayblum, S; Barak, A; Tzur, E; Schafer, I; David, R; David, E; Linn, S

2001-12-01

This article reports on the sensitivity and positive predictive value of clinical diagnosis of benign and malignant skin tumors by expert plastic surgeons in an Israeli clinic. Most published reports have focused on the sensitivity of clinicians' diagnoses, a general measure of the physician's skill that does not predict the rate of accuracy of a physician's diagnoses. Our study of 835 lesions in 778 patients, one of the largest Israeli series, assesses the clinical diagnosis of malignant and benign skin tumors and is one of the few that provide information on the positive predictive value, the measure that is of interest to both physicians and patients. The majority of tumors were benign (56.8 percent), 31.6 percent were malignant, and 11.6 percent were premalignant. Among the 474 benign lesions, 46 percent were nevi. The most common nevi subclass was compound nevi (53 percent), 9 percent of the nevi were dysplastic, and 5 percent were blue nevi. The most common malignant tumor was basal cell carcinoma, accounting for 78 percent of malignant tumors. Although sensitivity for clinical diagnosis of malignancy was 91.3 percent, the positive predictive value for clinical diagnosis of malignancy was 71.3 percent. The sensitivity rate for clinically diagnosing premalignant tumors was 42.3 percent, whereas the positive predictive value for these diagnoses was higher (64.1 percent). The sensitivity rate for diagnosis of all benign lesions was 85.9 percent, and the positive predictive value was 94.2 percent. The sensitivity rate for diagnosis of all nevi was 87.6 percent, and the positive predictive value was 85.7 percent: i.e., only seven of the 218 pathologically proven diagnoses of nevi (3.2 percent) were falsely diagnosed as malignant lesions. Even more interestingly, five of the 223 clinical diagnoses of nevi (2.2 percent) were pathologically proven to be malignant melanomas, and seven were found to be premalignant lesions (3.1 percent). It was concluded that publications which report only on the sensitivity neglect to provide information of interest regarding the positive predictive value. Often, positive predictive value is qualitatively different from the sensitivity, and thus relying only on the sensitivity may lead to incorrect evaluation of a clinical judgment, which may result in erroneous surgical decisions.

Familism Values as a Protective Factor for Mexican-origin Adolescents Exposed to Deviant Peers

PubMed Central

Germán, Miguelina; Gonzales, Nancy A.; Dumka, Larry

2009-01-01

This study examined interactive relations between adolescent, maternal and paternal familism values and deviant peer affiliations in predicting adolescent externalizing problems within low-income, Mexican-origin families (N = 598). Adolescent, maternal and paternal familism values interacted protectively with deviant peer affiliations to predict lower levels of externalizing problems according to two independent teacher reports. These relations were not found with parent reports of adolescent externalizing problems although these models showed a direct, protective effect of maternal familism values. Consistent with the view that traditional cultural values are protective for Latino adolescents, these results suggest that supporting familism values among Mexican-origin groups is a useful avenue for improving adolescent conduct problems, particularly in a school context. PMID:21776180

Development of model for prediction of Leachate Pollution Index (LPI) in absence of leachate parameters.

PubMed

Lothe, Anjali G; Sinha, Alok

2017-05-01

Leachate pollution index (LPI) is an environmental index which quantifies the pollution potential of leachate generated in landfill site. Calculation of Leachate pollution index (LPI) is based on concentration of 18 parameters present in leachate. However, in case of non-availability of all 18 parameters evaluation of actual values of LPI becomes difficult. In this study, a model has been developed to predict the actual values of LPI in case of partial availability of parameters. This model generates eleven equations that helps in determination of upper and lower limit of LPI. The geometric mean of these two values results in LPI value. Application of this model to three landfill site results in LPI value with an error of ±20% for ∑ i n w i ⩾0.6. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Predicted Cross Value for Genetic Introgression of Multiple Alleles

PubMed Central

Han, Ye; Cameron, John N.; Wang, Lizhi; Beavis, William D.

2017-01-01

We consider the plant genetic improvement challenge of introgressing multiple alleles from a homozygous donor to a recipient. First, we frame the project as an algorithmic process that can be mathematically formulated. We then introduce a novel metric for selecting breeding parents that we refer to as the predicted cross value (PCV). Unlike estimated breeding values, which represent predictions of general combining ability, the PCV predicts specific combining ability. The PCV takes estimates of recombination frequencies as an input vector and calculates the probability that a pair of parents will produce a gamete with desirable alleles at all specified loci. We compared the PCV approach with existing estimated-breeding-value approaches in two simulation experiments, in which 7 and 20 desirable alleles were to be introgressed from a donor line into a recipient line. Results suggest that the PCV is more efficient and effective for multi-allelic trait introgression. We also discuss how operations research can be used for other crop genetic improvement projects and suggest several future research directions. PMID:28122824

Evaluating the High Risk Groups for Suicide: A Comparison of Logistic Regression, Support Vector Machine, Decision Tree and Artificial Neural Network

PubMed Central

AMINI, Payam; AHMADINIA, Hasan; POOROLAJAL, Jalal; MOQADDASI AMIRI, Mohammad

2016-01-01

Background: We aimed to assess the high-risk group for suicide using different classification methods includinglogistic regression (LR), decision tree (DT), artificial neural network (ANN), and support vector machine (SVM). Methods: We used the dataset of a study conducted to predict risk factors of completed suicide in Hamadan Province, the west of Iran, in 2010. To evaluate the high-risk groups for suicide, LR, SVM, DT and ANN were performed. The applied methods were compared using sensitivity, specificity, positive predicted value, negative predicted value, accuracy and the area under curve. Cochran-Q test was implied to check differences in proportion among methods. To assess the association between the observed and predicted values, Ø coefficient, contingency coefficient, and Kendall tau-b were calculated. Results: Gender, age, and job were the most important risk factors for fatal suicide attempts in common for four methods. SVM method showed the highest accuracy 0.68 and 0.67 for training and testing sample, respectively. However, this method resulted in the highest specificity (0.67 for training and 0.68 for testing sample) and the highest sensitivity for training sample (0.85), but the lowest sensitivity for the testing sample (0.53). Cochran-Q test resulted in differences between proportions in different methods (P<0.001). The association of SVM predictions and observed values, Ø coefficient, contingency coefficient, and Kendall tau-b were 0.239, 0.232 and 0.239, respectively. Conclusion: SVM had the best performance to classify fatal suicide attempts comparing to DT, LR and ANN. PMID:27957463

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.

Integrating Milk Metabolite Profile Information for the Prediction of Traditional Milk Traits Based on SNP Information for Holstein Cows

PubMed Central

Melzer, Nina; Wittenburg, Dörte; Repsilber, Dirk

2013-01-01

In this study the benefit of metabolome level analysis for the prediction of genetic value of three traditional milk traits was investigated. Our proposed approach consists of three steps: First, milk metabolite profiles are used to predict three traditional milk traits of 1,305 Holstein cows. Two regression methods, both enabling variable selection, are applied to identify important milk metabolites in this step. Second, the prediction of these important milk metabolite from single nucleotide polymorphisms (SNPs) enables the detection of SNPs with significant genetic effects. Finally, these SNPs are used to predict milk traits. The observed precision of predicted genetic values was compared to the results observed for the classical genotype-phenotype prediction using all SNPs or a reduced SNP subset (reduced classical approach). To enable a comparison between SNP subsets, a special invariable evaluation design was implemented. SNPs close to or within known quantitative trait loci (QTL) were determined. This enabled us to determine if detected important SNP subsets were enriched in these regions. The results show that our approach can lead to genetic value prediction, but requires less than 1% of the total amount of (40,317) SNPs., significantly more important SNPs in known QTL regions were detected using our approach compared to the reduced classical approach. Concluding, our approach allows a deeper insight into the associations between the different levels of the genotype-phenotype map (genotype-metabolome, metabolome-phenotype, genotype-phenotype). PMID:23990900

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.

Effect of obesity on preterm delivery prediction by transabdominal recording of uterine electromyography.

PubMed

Lucovnik, Miha; Chambliss, Linda R; Blumrick, Richard; Balducci, James; Gersak, Ksenija; Garfield, Robert E

2016-10-01

It has been shown that noninvasive uterine electromyography (EMG) can identify true preterm labor more accurately than methods available to clinicians today. The objective of this study was to evaluate the effect of body mass index (BMI) on the accuracy of uterine EMG in predicting preterm delivery. Predictive values of uterine EMG for preterm delivery were compared in obese versus overweight/normal BMI patients. Hanley-McNeil test was used to compare receiver operator characteristics curves in these groups. Previously reported EMG cutoffs were used to determine groups with false positive/false negative and true positive/true negative EMG results. BMI in these groups was compared with Student t test (p < 0.05 significant). A total of 88 patients were included: 20 obese, 64 overweight, and four with normal BMI. EMG predicted preterm delivery within 7 days with area under the curve = 0.95 in the normal/overweight group, and with area under the curve = 1.00 in the obese group (p = 0.08). Six patients in true preterm labor (delivering within 7 days from EMG measurement) had low EMG values (false negative group). There were no false positive results. No significant differences in patient's BMI were noted between false negative group patients and preterm labor patients with high EMG values (true positive group) and nonlabor patients with low EMG values (true negative group; p = 0.32). Accuracy of noninvasive uterine EMG monitoring and its predictive value for preterm delivery are not affected by obesity. Copyright © 2016. Published by Elsevier B.V.

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

PubMed

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

2002-09-01

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

[Diagnostic value of a predictive model for complete ruptures of the rotator cuff associated to subacromial impingement].

PubMed

Águila-Ledesma, I R; Córdova-Fonseca, J L; Medina-Pontaza, O; Núñez-Gómez, D A; Calvache-García, C; Pérez-Atanasio, J M; Torres-González, R

2017-01-01

Pathology related to the rotator cuff remains among the most prevalent musculoskeletal diseases. There is an increasing need for imaging studies (MRI, US, arthroscopy) to test the diagnostic performance of the medical history and physical examination. To prove the diagnostic value of a clinical-radiographic predictive model to find complete ruptures of the rotator cuff. Descriptive, observational, prospective, transversal and analytical study. Fifty-five patients with preoperative shoulder pain were evaluated with 13 predictive variables: age > 50 years, nocturnal pain, muscle weakness, clinical signs of Neer, Hawkins, Jobe, external rotation lag (ERLS), belly-press, bear hug, and lift-off, radiographic measurement of subacromial space, acromial index and critical shoulder angle. Sensitivity, specificity, and positive and negative predictive values were measured in each variable, comparing the results of each one against the postoperative findings. Of the 55 patients evaluated, 42 had a complete rupture of the rotator cuff in the postoperative period. The eight variables with a higher diagnostic value were selected and a ROC curve was performed, providing an area under the curve of 0.88. This predictive model uses eight variables (age > 50 years, nocturnal pain, muscle weakness, Jobe, Hawkins, ERLS, subacromial space ≤ 6 mm, and critical shoulder angle > 35°), which together add the predictive value of 0.88 (AUC) to diagnose complete ruptures of the supraspinatus tendon.

A QSAR study of integrase strand transfer inhibitors based on a large set of pyrimidine, pyrimidone, and pyridopyrazine carboxamide derivatives

NASA Astrophysics Data System (ADS)

de Campos, Luana Janaína; de Melo, Eduardo Borges

2017-08-01

In the present study, 199 compounds derived from pyrimidine, pyrimidone and pyridopyrazine carboxamides with inhibitory activity against HIV-1 integrase were modeled. Subsequently, a multivariate QSAR study was conducted with 54 molecules employed by Ordered Predictors Selection (OPS) and Partial Least Squares (PLS) for the selection of variables and model construction, respectively. Topological, electrotopological, geometric, and molecular descriptors were used. The selected real model was robust and free from chance correlation; in addition, it demonstrated favorable internal and external statistical quality. Once statistically validated, the training model was used to predict the activity of a second data set (n = 145). The root mean square deviation (RMSD) between observed and predicted values was 0.698. Although it is a value outside of the standards, only 15 (10.34%) of the samples exhibited higher residual values than 1 log unit, a result considered acceptable. Results of Williams and Euclidean applicability domains relative to the prediction showed that the predictions did not occur by extrapolation and that the model is representative of the chemical space of test compounds.

Prediction of genetic values of quantitative traits with epistatic effects in plant breeding populations.

PubMed

Wang, D; Salah El-Basyoni, I; Stephen Baenziger, P; Crossa, J; Eskridge, K M; Dweikat, I

2012-11-01

Though epistasis has long been postulated to have a critical role in genetic regulation of important pathways as well as provide a major source of variation in the process of speciation, the importance of epistasis for genomic selection in the context of plant breeding is still being debated. In this paper, we report the results on the prediction of genetic values with epistatic effects for 280 accessions in the Nebraska Wheat Breeding Program using adaptive mixed least absolute shrinkage and selection operator (LASSO). The development of adaptive mixed LASSO, originally designed for association mapping, for the context of genomic selection is reported. The results show that adaptive mixed LASSO can be successfully applied to the prediction of genetic values while incorporating both marker main effects and epistatic effects. Especially, the prediction accuracy is substantially improved by the inclusion of two-locus epistatic effects (more than onefold in some cases as measured by cross-validation correlation coefficient), which is observed for multiple traits and planting locations. This points to significant potential in using non-additive genetic effects for genomic selection in crop breeding practices.

Assessing Breast Cancer Risk with an Artificial Neural Network

PubMed

Sepandi, Mojtaba; Taghdir, Maryam; Rezaianzadeh, Abbas; Rahimikazerooni, Salar

2018-04-25

Objectives: Radiologists face uncertainty in making decisions based on their judgment of breast cancer risk. Artificial intelligence and machine learning techniques have been widely applied in detection/recognition of cancer. This study aimed to establish a model to aid radiologists in breast cancer risk estimation. This incorporated imaging methods and fine needle aspiration biopsy (FNAB) for cyto-pathological diagnosis. Methods: An artificial neural network (ANN) technique was used on a retrospectively collected dataset including mammographic results, risk factors, and clinical findings to accurately predict the probability of breast cancer in individual patients. Area under the receiver-operating characteristic curve (AUC), accuracy, sensitivity, specificity, and positive and negative predictive values were used to evaluate discriminative performance. Result: The network incorporating the selected features performed best (AUC = 0.955). Sensitivity and specificity of the ANN were respectively calculated as 0.82 and 0.90. In addition, negative and positive predictive values were respectively computed as 0.90 and 0.80. Conclusion: ANN has potential applications as a decision-support tool to help underperforming practitioners to improve the positive predictive value of biopsy recommendations. Creative Commons Attribution License

Automatic burst detection for the EEG of the preterm infant.

PubMed

Jennekens, Ward; Ruijs, Loes S; Lommen, Charlotte M L; Niemarkt, Hendrik J; Pasman, Jaco W; van Kranen-Mastenbroek, Vivianne H J M; Wijn, Pieter F F; van Pul, Carola; Andriessen, Peter

2011-10-01

To aid with prognosis and stratification of clinical treatment for preterm infants, a method for automated detection of bursts, interburst-intervals (IBIs) and continuous patterns in the electroencephalogram (EEG) is developed. Results are evaluated for preterm infants with normal neurological follow-up at 2 years. The detection algorithm (MATLAB®) for burst, IBI and continuous pattern is based on selection by amplitude, time span, number of channels and numbers of active electrodes. Annotations of two neurophysiologists were used to determine threshold values. The training set consisted of EEG recordings of four preterm infants with postmenstrual age (PMA, gestational age + postnatal age) of 29-34 weeks. Optimal threshold values were based on overall highest sensitivity. For evaluation, both observers verified detections in an independent dataset of four EEG recordings with comparable PMA. Algorithm performance was assessed by calculation of sensitivity and positive predictive value. The results of algorithm evaluation are as follows: sensitivity values of 90% ± 6%, 80% ± 9% and 97% ± 5% for burst, IBI and continuous patterns, respectively. Corresponding positive predictive values were 88% ± 8%, 96% ± 3% and 85% ± 15%, respectively. In conclusion, the algorithm showed high sensitivity and positive predictive values for bursts, IBIs and continuous patterns in preterm EEG. Computer-assisted analysis of EEG may allow objective and reproducible analysis for clinical treatment.

Predictive contribution of neutrophil/lymphocyte ratio in diagnosis of brucellosis.

PubMed

Olt, Serdar; Ergenç, Hasan; Açıkgöz, Seyyid Bilal

2015-01-01

Here we wanted to investigate predictive value of neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR) in the diagnosis of brucellosis. Thirty-two brucellosis patients diagnosed with positive serum agglutination test and thirty-two randomized healthy subjects were enrolled in this study retrospectively. Result with ROC analyzes the baseline NLR and hemoglobin values were found to be significantly associated with brucellosis (P = 0.01, P = 0.01, resp.). Herein we demonstrated for the first time that NLR values were significantly associated with brucellosis. This situation can help clinicians during diagnosis of brucellosis.

Sensitivity, specificity and predictive probability values of serum agglutination test titres for the diagnosis of Salmonella Dublin culture-positive bovine abortion and stillbirth.

PubMed

Sánchez-Miguel, C; Crilly, J; Grant, J; Mee, J F

2018-06-01

The objective of this study was to determine the diagnostic value of maternal serology for the diagnosis of Salmonella Dublin bovine abortion and stillbirth. A retrospective, unmatched, case-control study was carried out using twenty year's data (1989-2009) from bovine foetal submissions to an Irish government veterinary laboratory. Cases (n = 214) were defined as submissions with a S. Dublin culture-positive foetus from a S. Dublin unvaccinated dam where results of maternal S. Dublin serology were available. Controls (n = 415) were defined as submissions where an alternative diagnosis other than S. Dublin was made in a foetus from an S. Dublin unvaccinated dam where the results of maternal S. Dublin serology were available. A logistic regression model was fitted to the data: the dichotomous dependent variable was the S. Dublin foetal culture result, and the independent variables were the maternal serum agglutination test (SAT) titre results. Salmonella serology correctly classified 87% of S. Dublin culture-positive foetuses at a predicted probability threshold of 0.44 (cut-off at which sensitivity and specificity are at a maximum, J = 0.67). The sensitivity of the SAT at the same threshold was 73.8% (95% CI: 67.4%-79.5%), and the specificity was 93.2% (95% CI: 90.3%-95.4%). The positive and negative predictive values were 84.9% (95% CI: 79.3%-88.6%) and 87.3% (95% CI: 83.5%-91.3%), respectively. This study illustrates that the use of predicted probability values, rather than the traditional arbitrary breakpoints of negative, inconclusive and positive, increases the diagnostic value of the maternal SAT. Veterinary laboratory diagnosticians and veterinary practitioners can recover from the test results, information previously categorized, particularly from those results declared to be inconclusive. © 2017 Blackwell Verlag GmbH.

Predictive Genetic Testing and Alternatives to Face to Face Results Disclosure: A Retrospective Review of Patients Preference for Alternative Modes of BRCA 1 and 2 Results Disclosure in the Republic of Ireland.

PubMed

O'Shea, Rosie; Meany, Marie; Carroll, Cliona; Cody, Nuala; Healy, David; Green, Andrew; Lynch, Sally Ann

2016-06-01

The traditional model of providing cancer predictive testing services is changing. Many genetic centres are now offering a choice to patients in how they receive their results instead of the typical face-to-face disclosure. In view of this shift in practice and the increasing demand on the ROI cancer predictive testing service, a 2 year retrospective study on patient preference in how to receive a Breast Cancer (BRCA) predictive result was carried out. Results showed that 71.7 % of respondents would have liked to have the option of obtaining their results by telephone or by letter. However, when asked about their actual experience of BRCA predictive results disclosure 40.6 % did still value the face-to-face contact, while 44.9 % would still have preferred to receive results by either post or telephone. No significant difference was found between males and females (p > 0.05) and those who tested negative or positive for the BRCA mutation (p > 0.05) in wanting a choice in how their results were disclosed. While the majority expressed a wish to have a choice in how to receive their results, it is important not to underestimate the value of a face-to-face encounter in these circumstances.

[Evaluation of performance of five bioinformatics software for the prediction of missense mutations].

PubMed

Chen, Qianting; Dai, Congling; Zhang, Qianjun; Du, Juan; Li, Wen

2016-10-01

To study the prediction performance evaluation with five kinds of bioinformatics software (SIFT, PolyPhen2, MutationTaster, Provean, MutationAssessor). From own database for genetic mutations collected over the past five years, Chinese literature database, Human Gene Mutation Database, and dbSNP, 121 missense mutations confirmed by functional studies, and 121 missense mutations suspected to be pathogenic by pedigree analysis were used as positive gold standard, while 242 missense mutations with minor allele frequency (MAF)>5% in dominant hereditary diseases were used as negative gold standard. The selected mutations were predicted with the five software. Based on the results, the performance of the five software was evaluated for their sensitivity, specificity, positive predict value, false positive rate, negative predict value, false negative rate, false discovery rate, accuracy, and receiver operating characteristic curve (ROC). In terms of sensitivity, negative predictive value and false negative rate, the rank was MutationTaster, PolyPhen2, Provean, SIFT, and MutationAssessor. For specificity and false positive rate, the rank was MutationTaster, Provean, MutationAssessor, SIFT, and PolyPhen2. For positive predict value and false discovery rate, the rank was MutationTaster, Provean, MutationAssessor, PolyPhen2, and SIFT. For area under the ROC curve (AUC) and accuracy, the rank was MutationTaster, Provean, PolyPhen2, MutationAssessor, and SIFT. The prediction performance of software may be different when using different parameters. Among the five software, MutationTaster has the best prediction performance.

Predictive genetic testing for the identification of high-risk groups: a simulation study on the impact of predictive ability

PubMed Central

2011-01-01

Background Genetic risk models could potentially be useful in identifying high-risk groups for the prevention of complex diseases. We investigated the performance of this risk stratification strategy by examining epidemiological parameters that impact the predictive ability of risk models. Methods We assessed sensitivity, specificity, and positive and negative predictive value for all possible risk thresholds that can define high-risk groups and investigated how these measures depend on the frequency of disease in the population, the frequency of the high-risk group, and the discriminative accuracy of the risk model, as assessed by the area under the receiver-operating characteristic curve (AUC). In a simulation study, we modeled genetic risk scores of 50 genes with equal odds ratios and genotype frequencies, and varied the odds ratios and the disease frequency across scenarios. We also performed a simulation of age-related macular degeneration risk prediction based on published odds ratios and frequencies for six genetic risk variants. Results We show that when the frequency of the high-risk group was lower than the disease frequency, positive predictive value increased with the AUC but sensitivity remained low. When the frequency of the high-risk group was higher than the disease frequency, sensitivity was high but positive predictive value remained low. When both frequencies were equal, both positive predictive value and sensitivity increased with increasing AUC, but higher AUC was needed to maximize both measures. Conclusions The performance of risk stratification is strongly determined by the frequency of the high-risk group relative to the frequency of disease in the population. The identification of high-risk groups with appreciable combinations of sensitivity and positive predictive value requires higher AUC. PMID:21797996

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

NASA Astrophysics Data System (ADS)

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

2015-09-01

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

The Accuracy of the Spot Sign and the Blend Sign for Predicting Hematoma Expansion in Patients with Spontaneous Intracerebral Hemorrhage.

PubMed

Zheng, Jun; Yu, Zhiyuan; Xu, Zhao; Li, Mou; Wang, Xiaoze; Lin, Sen; Li, Hao; You, Chao

2017-05-12

BACKGROUND Hematoma expansion is associated with poor outcome in intracerebral hemorrhage (ICH) patients. The spot sign and the blend sign are reliable tools for predicting hematoma expansion in ICH patients. The aim of this study was to compare the accuracy of the two signs in the prediction of hematoma expansion. MATERIAL AND METHODS Patients with spontaneous ICH were screened for the presence of the computed tomography angiography (CTA) spot sign and the non-contrast CT (NCCT) blend sign within 6 hours after onset of symptoms. The sensitivity, specificity, and positive and negative predictive values of the spot sign and the blend sign in predicting hematoma expansion were calculated. The accuracy of the spot sign and the blend sign in predicting hematoma expansion was analyzed by receiver-operator analysis. RESULTS A total of 115 patients were enrolled in this study. The spot sign was observed in 25 (21.74%) patients, whereas the blend sign was observed in 22 (19.13%) patients. Of the 28 patients with hematoma expansion, the CTA spot sign was found on admission CT scans in 16 (57.14%) and the NCCT blend sign in 12 (42.86%), respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of the spot sign for predicting hematoma expansion were 57.14%, 89.66%, 64.00%, and 86.67%, respectively. In contrast, the sensitivity, specificity, positive predictive value, and negative predictive value of the blend sign were 42.86%, 88.51%, 54.55%, and 82.80%, respectively. The area under the curve (AUC) of the spot sign was 0.734, which was higher than that of the blend sign (0.657). CONCLUSIONS Both the spot sign and the blend sign seemed to be good predictors for hematoma expansion, and the spot sign appeared to have better predictive accuracy.

The Accuracy of the Spot Sign and the Blend Sign for Predicting Hematoma Expansion in Patients with Spontaneous Intracerebral Hemorrhage

PubMed Central

Zheng, Jun; Yu, Zhiyuan; Xu, Zhao; Li, Mou; Wang, Xiaoze; Lin, Sen; Li, Hao; You, Chao

2017-01-01

Background Hematoma expansion is associated with poor outcome in intracerebral hemorrhage (ICH) patients. The spot sign and the blend sign are reliable tools for predicting hematoma expansion in ICH patients. The aim of this study was to compare the accuracy of the two signs in the prediction of hematoma expansion. Material/Methods Patients with spontaneous ICH were screened for the presence of the computed tomography angiography (CTA) spot sign and the non-contrast CT (NCCT) blend sign within 6 hours after onset of symptoms. The sensitivity, specificity, and positive and negative predictive values of the spot sign and the blend sign in predicting hematoma expansion were calculated. The accuracy of the spot sign and the blend sign in predicting hematoma expansion was analyzed by receiver-operator analysis. Results A total of 115 patients were enrolled in this study. The spot sign was observed in 25 (21.74%) patients, whereas the blend sign was observed in 22 (19.13%) patients. Of the 28 patients with hematoma expansion, the CTA spot sign was found on admission CT scans in 16 (57.14%) and the NCCT blend sign in 12 (42.86%), respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of the spot sign for predicting hematoma expansion were 57.14%, 89.66%, 64.00%, and 86.67%, respectively. In contrast, the sensitivity, specificity, positive predictive value, and negative predictive value of the blend sign were 42.86%, 88.51%, 54.55%, and 82.80%, respectively. The area under the curve (AUC) of the spot sign was 0.734, which was higher than that of the blend sign (0.657). Conclusions Both the spot sign and the blend sign seemed to be good predictors for hematoma expansion, and the spot sign appeared to have better predictive accuracy. PMID:28498827

Reward inference by primate prefrontal and striatal neurons.

PubMed

Pan, Xiaochuan; Fan, Hongwei; Sawa, Kosuke; Tsuda, Ichiro; Tsukada, Minoru; Sakagami, Masamichi

2014-01-22

The brain contains multiple yet distinct systems involved in reward prediction. To understand the nature of these processes, we recorded single-unit activity from the lateral prefrontal cortex (LPFC) and the striatum in monkeys performing a reward inference task using an asymmetric reward schedule. We found that neurons both in the LPFC and in the striatum predicted reward values for stimuli that had been previously well experienced with set reward quantities in the asymmetric reward task. Importantly, these LPFC neurons could predict the reward value of a stimulus using transitive inference even when the monkeys had not yet learned the stimulus-reward association directly; whereas these striatal neurons did not show such an ability. Nevertheless, because there were two set amounts of reward (large and small), the selected striatal neurons were able to exclusively infer the reward value (e.g., large) of one novel stimulus from a pair after directly experiencing the alternative stimulus with the other reward value (e.g., small). Our results suggest that although neurons that predict reward value for old stimuli in the LPFC could also do so for new stimuli via transitive inference, those in the striatum could only predict reward for new stimuli via exclusive inference. Moreover, the striatum showed more complex functions than was surmised previously for model-free learning.

Reward Inference by Primate Prefrontal and Striatal Neurons

PubMed Central

Pan, Xiaochuan; Fan, Hongwei; Sawa, Kosuke; Tsuda, Ichiro; Tsukada, Minoru

2014-01-01

The brain contains multiple yet distinct systems involved in reward prediction. To understand the nature of these processes, we recorded single-unit activity from the lateral prefrontal cortex (LPFC) and the striatum in monkeys performing a reward inference task using an asymmetric reward schedule. We found that neurons both in the LPFC and in the striatum predicted reward values for stimuli that had been previously well experienced with set reward quantities in the asymmetric reward task. Importantly, these LPFC neurons could predict the reward value of a stimulus using transitive inference even when the monkeys had not yet learned the stimulus–reward association directly; whereas these striatal neurons did not show such an ability. Nevertheless, because there were two set amounts of reward (large and small), the selected striatal neurons were able to exclusively infer the reward value (e.g., large) of one novel stimulus from a pair after directly experiencing the alternative stimulus with the other reward value (e.g., small). Our results suggest that although neurons that predict reward value for old stimuli in the LPFC could also do so for new stimuli via transitive inference, those in the striatum could only predict reward for new stimuli via exclusive inference. Moreover, the striatum showed more complex functions than was surmised previously for model-free learning. PMID:24453328

RaptorX-Angle: real-value prediction of protein backbone dihedral angles through a hybrid method of clustering and deep learning.

PubMed

Gao, Yujuan; Wang, Sheng; Deng, Minghua; Xu, Jinbo

2018-05-08

Protein dihedral angles provide a detailed description of protein local conformation. Predicted dihedral angles can be used to narrow down the conformational space of the whole polypeptide chain significantly, thus aiding protein tertiary structure prediction. However, direct angle prediction from sequence alone is challenging. In this article, we present a novel method (named RaptorX-Angle) to predict real-valued angles by combining clustering and deep learning. Tested on a subset of PDB25 and the targets in the latest two Critical Assessment of protein Structure Prediction (CASP), our method outperforms the existing state-of-art method SPIDER2 in terms of Pearson Correlation Coefficient (PCC) and Mean Absolute Error (MAE). Our result also shows approximately linear relationship between the real prediction errors and our estimated bounds. That is, the real prediction error can be well approximated by our estimated bounds. Our study provides an alternative and more accurate prediction of dihedral angles, which may facilitate protein structure prediction and functional study.

A novel method for structure-based prediction of ion channel conductance properties.

PubMed Central

Smart, O S; Breed, J; Smith, G R; Sansom, M S

1997-01-01

A rapid and easy-to-use method of predicting the conductance of an ion channel from its three-dimensional structure is presented. The method combines the pore dimensions of the channel as measured in the HOLE program with an Ohmic model of conductance. An empirically based correction factor is then applied. The method yielded good results for six experimental channel structures (none of which were included in the training set) with predictions accurate to within an average factor of 1.62 to the true values. The predictive r2 was equal to 0.90, which is indicative of a good predictive ability. The procedure is used to validate model structures of alamethicin and phospholamban. Two genuine predictions for the conductance of channels with known structure but without reported conductances are given. A modification of the procedure that calculates the expected results for the effect of the addition of nonelectrolyte polymers on conductance is set out. Results for a cholera toxin B-subunit crystal structure agree well with the measured values. The difficulty in interpreting such studies is discussed, with the conclusion that measurements on channels of known structure are required. Images FIGURE 1 FIGURE 3 FIGURE 4 FIGURE 6 FIGURE 10 PMID:9138559

[Forest lighting fire forecasting for Daxing'anling Mountains based on MAXENT model].

PubMed

Sun, Yu; Shi, Ming-Chang; Peng, Huan; Zhu, Pei-Lin; Liu, Si-Lin; Wu, Shi-Lei; He, Cheng; Chen, Feng

2014-04-01

Daxing'anling Mountains is one of the areas with the highest occurrence of forest lighting fire in Heilongjiang Province, and developing a lightning fire forecast model to accurately predict the forest fires in this area is of importance. Based on the data of forest lightning fires and environment variables, the MAXENT model was used to predict the lightning fire in Daxing' anling region. Firstly, we studied the collinear diagnostic of each environment variable, evaluated the importance of the environmental variables using training gain and the Jackknife method, and then evaluated the prediction accuracy of the MAXENT model using the max Kappa value and the AUC value. The results showed that the variance inflation factor (VIF) values of lightning energy and neutralized charge were 5.012 and 6.230, respectively. They were collinear with the other variables, so the model could not be used for training. Daily rainfall, the number of cloud-to-ground lightning, and current intensity of cloud-to-ground lightning were the three most important factors affecting the lightning fires in the forest, while the daily average wind speed and the slope was of less importance. With the increase of the proportion of test data, the max Kappa and AUC values were increased. The max Kappa values were above 0.75 and the average value was 0.772, while all of the AUC values were above 0.5 and the average value was 0. 859. With a moderate level of prediction accuracy being achieved, the MAXENT model could be used to predict forest lightning fire in Daxing'anling Mountains.

Algorithm for Lossless Compression of Calibrated Hyperspectral Imagery

NASA Technical Reports Server (NTRS)

Kiely, Aaron B.; Klimesh, Matthew A.

2010-01-01

A two-stage predictive method was developed for lossless compression of calibrated hyperspectral imagery. The first prediction stage uses a conventional linear predictor intended to exploit spatial and/or spectral dependencies in the data. The compressor tabulates counts of the past values of the difference between this initial prediction and the actual sample value. To form the ultimate predicted value, in the second stage, these counts are combined with an adaptively updated weight function intended to capture information about data regularities introduced by the calibration process. Finally, prediction residuals are losslessly encoded using adaptive arithmetic coding. Algorithms of this type are commonly tested on a readily available collection of images from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral imager. On the standard calibrated AVIRIS hyperspectral images that are most widely used for compression benchmarking, the new compressor provides more than 0.5 bits/sample improvement over the previous best compression results. The algorithm has been implemented in Mathematica. The compression algorithm was demonstrated as beneficial on 12-bit calibrated AVIRIS images.

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

NASA Technical Reports Server (NTRS)

Douglass, Anne R.; Stolarski, Richard S.

1987-01-01

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

Evaluation of dental pulp sensibility tests in a clinical setting.

PubMed

Jespersen, James J; Hellstein, John; Williamson, Anne; Johnson, William T; Qian, Fang

2014-03-01

The goal of this project was to evaluate the performance of dental pulp sensibility testing with Endo Ice (1,1,1,2-tetrafluoroethane) and an electric pulp tester (EPT) and to determine the effect of several variables on the reliability of these tests. Data were collected from 656 patients seen in the University of Iowa College of Dentistry Endodontic graduate clinic. The results of pulpal sensibility tests, along with the tooth number, age, sex, number of restored surfaces, presence or absence of clinical or radiographic caries, and reported recent use of analgesic medications, were recorded. The presence of vital tissue within the pulp chamber was used to verify the diagnosis. The Endo Ice results showed accuracy, 0.904; sensitivity, 0.916; specificity, 0.896; positive predictive value, 0.862; and negative predictive value, 0.937. The EPT results showed accuracy, 0.75; sensitivity, 0.84; specificity, 0.74; positive predictive value, 0.58; and negative predictive value, 0.90. Patients aged 21-50 years exhibited a more accurate response to cold testing (P = .0043). Vital teeth with caries responded more accurately to cold testing (P = .0077). There was no statistically significant difference noted with any other variable examined. Pulpal sensibility testing with Endo Ice and EPT are accurate and reliable methods of determining pulpal vitality. Patients aged 21-50 exhibited a more accurate response to cold. Sex, tooth type, number of restored surfaces, presence of caries, and recent analgesic use did not significantly alter the results of pulpal sensibility testing in this study. Copyright © 2014 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Predictive value of the complex magnetocardiographic index in patients with intermediate pretest probability of chronic coronary artery disease: results of a two-center study.

PubMed

Chaikovsky, Illya; Hailer, Birgit; Sosnytskyy, Volodymyr; Lutay, Mykhaylo; Mjasnikov, Georgiy; Kazmirchuk, Anatoly; Bydnyk, Mykola; Lomakovskyy, Alexander; Sosnytskaja, Taisia

2014-09-01

The aim of this paper is to investigate the predictive value of the new integrated magnetocardiographic (MCG) index (CI) in the diagnosis of coronary artery disease (CAD) in patients with suspected CAD with intermediate pretest probability of the disease and uninformative results of routine tests. The study was carried out in the Clinic of Cardiology of the Main Military Clinical Hospital of Ukraine, Kiev (clinic 1), and in the Second Medical Clinic of the 'Katholisches Klinikum Essen', Germany (clinic 2).The main group (group 1) included 89 patients without a history of myocardial infarction. Coronary angiography was performed because of chest pain. Depending on the results of coronary angiography, this group was divided into two subgroups: (i) those with at least 70% stenosis in at least one of the main coronary arteries (subgroup 1a) and (ii) those without hemodynamically significant stenosis (subgroup 1b). The control group included 43 healthy volunteers.In all participants, the MCG examination was performed using a seven-channel MCG system located in an unshielded room. An integrated MCG index (CI), consisting of six parameters, was calculated. It can be shown that CI was significantly higher in patients with stenosis 70% or more compared with the patients without stenosis and healthy volunteers. Sensitivity was 93%, specificity was 84%, positive predictive value was 85%, and negative predictive value was 93%. The MCG test at rest has the potential to be useful in the noninvasive diagnosis of CAD in patients with intermediate pretest probability of disease and uninformative results of routine tests.

Flowfield Comparisons from Three Navier-Stokes Solvers for an Axisymmetric Separate Flow Jet

NASA Technical Reports Server (NTRS)

Koch, L. Danielle; Bridges, James; Khavaran, Abbas

2002-01-01

To meet new noise reduction goals, many concepts to enhance mixing in the exhaust jets of turbofan engines are being studied. Accurate steady state flowfield predictions from state-of-the-art computational fluid dynamics (CFD) solvers are needed as input to the latest noise prediction codes. The main intent of this paper was to ascertain that similar Navier-Stokes solvers run at different sites would yield comparable results for an axisymmetric two-stream nozzle case. Predictions from the WIND and the NPARC codes are compared to previously reported experimental data and results from the CRAFT Navier-Stokes solver. Similar k-epsilon turbulence models were employed in each solver, and identical computational grids were used. Agreement between experimental data and predictions from each code was generally good for mean values. All three codes underpredict the maximum value of turbulent kinetic energy. The predicted locations of the maximum turbulent kinetic energy were farther downstream than seen in the data. A grid study was conducted using the WIND code, and comments about convergence criteria and grid requirements for CFD solutions to be used as input for noise prediction computations are given. Additionally, noise predictions from the MGBK code, using the CFD results from the CRAFT code, NPARC, and WIND as input are compared to data.

Diagnostic value and cost utility analysis for urine Gram stain and urine microscopic examination as screening tests for urinary tract infection.

PubMed

Wiwanitkit, Viroj; Udomsantisuk, Nibhond; Boonchalermvichian, Chaiyaporn

2005-06-01

The aim of this study was to evaluate the diagnostic properties of urine Gram stain and urine microscopic examination for screening for urinary tract infection (UTI), and to perform an additional cost utility analysis. This descriptive study was performed on 95 urine samples sent for urine culture to the Department of Microbiology, Faculty of Medicine, Chulalongkorn University. The first part of the study was to determine the diagnostic properties of two screening tests (urine Gram stain and urine microscopic examination). Urine culture was set as the gold standard and the results from both methods were compared to this. The second part of this study was to perform a cost utility analysis. The sensitivity of urine Gram stain was 96.2%, the specificity 93.0%, the positive predictive value 94.3% and the negative predictive value 95.2%. False positives occurred with a frequency of 7.0% and false negatives 3.8%. For the microscopic examination, the sensitivity was 65.4%, specificity 74.4%, positive predictive value 75.6% and negative predictive value 64.0%. False positives occurred with a frequency of 25.6% and false negatives 34.6%. Combining urine Gram stain and urine microscopic examination, the sensitivity was 98.1%, specificity 74.4%, positive predictive value 82.3% and negative predictive value 97.0%. False positives occurred with a frequency of 25.6% and false negatives 1.9%. However, the cost per utility of the combined method was higher than either urine microscopic examination or urine Gram stain alone. Urine Gram stain provided the lowest cost per utility. Economically, urine Gram stain is the proper screening tool for presumptive diagnosis of UTI.

Prognosis of Pregnant Women with One Abnormal Value on 75g OGTT.

PubMed

Kozuma, Yutaka; Inoue, Shigeru; Horinouchi, Takashi; Shinagawa, Takaaki; Nakayama, Hitomi; Kawaguchi, Atsushi; Hori, Daizo; Kamura, Toshiharu; Yamada, Kentaro; Ushijima, Kimio

2015-01-01

The aim of this study was to identify risk factors to allow us to detect patients at high risk of requiring insulin therapy, among Japanese pregnant women with one abnormal value (OAV) on a 75-g oral glucose tolerance test (75-g OGTT). A total of 118 pregnant women with OAV on a previous 75-g OGTT between 1997 and 2010 were studied. We identified the factors which can predict patients at high risk of requiring insulin therapy among Japanese pregnant women with OAV, by comparing severe abnormal glucose tolerance (insulin treatment; n=17) with mild glucose tolerance patients (diet only; n=101). The following factors were examined; plasma level of glucose (PG) and immunoreactive insulin (IRI) at fasting, 0.5, 1 and 2 hours after loading glucose, insulinogenic index, homeostasis model assessment insulin resistance (HOMA-IR), insulin sensitivity index-composite (ISI composite), and HbA1c at the time of the 75-g OGTT. Univariate analysis showed a positive correlation between insulin therapy and 2-h PG value, 0.5-h and 1-h IRI values, AUC-IRI and insulinogenic index (p<0.05). Multivariate analysis showed that the PG 2-h value and insulinogenic index were independent predictive factors of insulin therapy. A 2-h PG ≥153 mg / dl and an insulinogenic index of <0.42 had a sensitivity of 81.8%, a specificity of 83.8%, a positive predictive value of 60.0% and a negative predictive value of 93.9% for the prediction of patients who required insulin therapy among pregnant women with OAV. These results suggest that a level of 2-h PG ≥153 mg/dl and an insulinogenic index of <0.42 on 75-g OGTT are predictive factors for insulin therapy in Japanese pregnant women with OAV.

Short Term Rain Prediction For Sustainability of Tanks in the Tropic Influenced by Shadow Rains

NASA Astrophysics Data System (ADS)

Suresh, S.

2007-07-01

Rainfall and flow prediction, adapting the Venkataraman single time series approach and Wiener multiple time series approach were conducted for Aralikottai tank system, and Kothamangalam tank system, Tamilnadu, India. The results indicated that the raw prediction of daily values is closer to actual values than trend identified predictions. The sister seasonal time series were more amenable for prediction than whole parent time series. Venkataraman single time approach was more suited for rainfall prediction. Wiener approach proved better for daily prediction of flow based on rainfall. The major conclusion is that the sister seasonal time series of rain and flow have their own identities even though they form part of the whole parent time series. Further studies with other tropical small watersheds are necessary to establish this unique characteristic of independent but not exclusive behavior of seasonal stationary stochastic processes as compared to parent non stationary stochastic processes.

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.

Initial comparison of single cylinder Stirling engine computer model predictions with test results

NASA Technical Reports Server (NTRS)

Tew, R. C., Jr.; Thieme, L. G.; Miao, D.

1979-01-01

A NASA developed digital computer code for a Stirling engine, modelling the performance of a single cylinder rhombic drive ground performance unit (GPU), is presented and its predictions are compared to test results. The GPU engine incorporates eight regenerator/cooler units and the engine working space is modelled by thirteen control volumes. The model calculates indicated power and efficiency for a given engine speed, mean pressure, heater and expansion space metal temperatures and cooler water inlet temperature and flow rate. Comparison of predicted and observed powers implies that the reference pressure drop calculations underestimate actual pressure drop, possibly due to oil contamination in the regenerator/cooler units, methane contamination in the working gas or the underestimation of mechanical loss. For a working gas of hydrogen, the predicted values of brake power are from 0 to 6% higher than experimental values, and brake efficiency is 6 to 16% higher, while for helium the predicted brake power and efficiency are 2 to 15% higher than the experimental.

Predictive value of CHADS2 and CHA2DS2-VASc scores for acute myocardial infarction in patients with atrial fibrillation.

PubMed

Pang, Hui; Han, Bing; Fu, Qiang; Zong, Zhenkun

2017-07-05

The presence of acute myocardial infarction (AMI) confers a poor prognosis in atrial fibrillation (AF), associated with increased mortality dramatically. This study aimed to evaluate the predictive value of CHADS 2 and CHA 2 DS 2 -VASc scores for AMI in patients with AF. This retrospective study enrolled 5140 consecutive nonvalvular AF patients, 300 patients with AMI and 4840 patients without AMI. We identified the optimal cut-off values of the CHADS 2 and CHA 2 DS 2 -VASc scores each based on receiver operating characteristic curves to predict the risk of AMI. Both CHADS 2 score and CHA 2 DS 2 -VASc score were associated with an increased odds ratio of the prevalence of AMI in patients with AF, after adjustment for hyperlipidaemia, hyperuricemia, hyperthyroidism, hypothyroidism and obstructive sleep apnea. The present results showed that the area under the curve (AUC) for CHADS 2 score was 0.787 with a similar accuracy of the CHA 2 DS 2 -VASc score (AUC 0.750) in predicting "high-risk" AF patients who developed AMI. However, the predictive accuracy of the two clinical-based risk scores was fair. The CHA 2 DS 2 -VASc score has fair predictive value for identifying high-risk patients with AF and is not significantly superior to CHADS 2 in predicting patients who develop AMI.

Quantifying model-structure- and parameter-driven uncertainties in spring wheat phenology prediction with Bayesian analysis

DOE PAGES

Alderman, Phillip D.; Stanfill, Bryan

2016-10-06

Recent international efforts have brought renewed emphasis on the comparison of different agricultural systems models. Thus far, analysis of model-ensemble simulated results has not clearly differentiated between ensemble prediction uncertainties due to model structural differences per se and those due to parameter value uncertainties. Additionally, despite increasing use of Bayesian parameter estimation approaches with field-scale crop models, inadequate attention has been given to the full posterior distributions for estimated parameters. The objectives of this study were to quantify the impact of parameter value uncertainty on prediction uncertainty for modeling spring wheat phenology using Bayesian analysis and to assess the relativemore » contributions of model-structure-driven and parameter-value-driven uncertainty to overall prediction uncertainty. This study used a random walk Metropolis algorithm to estimate parameters for 30 spring wheat genotypes using nine phenology models based on multi-location trial data for days to heading and days to maturity. Across all cases, parameter-driven uncertainty accounted for between 19 and 52% of predictive uncertainty, while model-structure-driven uncertainty accounted for between 12 and 64%. Here, this study demonstrated the importance of quantifying both model-structure- and parameter-value-driven uncertainty when assessing overall prediction uncertainty in modeling spring wheat phenology. More generally, Bayesian parameter estimation provided a useful framework for quantifying and analyzing sources of prediction uncertainty.« less

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.

Kubelka-Munk reflectance theory applied to porcelain veneer systems using a colorimeter.

PubMed

Davis, B K; Johnston, W M; Saba, R F

1994-01-01

The purpose of this study was to demonstrate the ability of Kubelka-Munk reflectance theory to predict color parameters of veneer porcelain on various backings using colorimetric measurements. Tristimulus absorption and scattering coefficients were used to predict the respective tristimulus reflectance values of A1, D3, and translucent porcelain samples after they had been bonded to light and dark substrates using universal, opaque, and untinted shades of bonding resin. Observed and predicted reflectance values exhibited high correlation (r2 > or = 0.93 for each porcelain shade). Kubelka-Munk theory offers an accurate prediction for the resultant colorimetric reflectance parameters of veneer porcelain bonded to variously colored backings.

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.

Choosing the appropriate forecasting model for predictive parameter control.

PubMed

Aleti, Aldeida; Moser, Irene; Meedeniya, Indika; Grunske, Lars

2014-01-01

All commonly used stochastic optimisation algorithms have to be parameterised to perform effectively. Adaptive parameter control (APC) is an effective method used for this purpose. APC repeatedly adjusts parameter values during the optimisation process for optimal algorithm performance. The assignment of parameter values for a given iteration is based on previously measured performance. In recent research, time series prediction has been proposed as a method of projecting the probabilities to use for parameter value selection. In this work, we examine the suitability of a variety of prediction methods for the projection of future parameter performance based on previous data. All considered prediction methods have assumptions the time series data has to conform to for the prediction method to provide accurate projections. Looking specifically at parameters of evolutionary algorithms (EAs), we find that all standard EA parameters with the exception of population size conform largely to the assumptions made by the considered prediction methods. Evaluating the performance of these prediction methods, we find that linear regression provides the best results by a very small and statistically insignificant margin. Regardless of the prediction method, predictive parameter control outperforms state of the art parameter control methods when the performance data adheres to the assumptions made by the prediction method. When a parameter's performance data does not adhere to the assumptions made by the forecasting method, the use of prediction does not have a notable adverse impact on the algorithm's performance.

Analysis of the Sensitivity and Specificity of Noninvasive Imaging Tests for the Diagnosis of Renal Artery Stenosis

PubMed Central

Borelli, Flavio Antonio de Oliveira; Pinto, Ibraim M. F.; Amodeo, Celso; Smanio, Paola E. P.; Kambara, Antonio M.; Petisco, Ana Claudia G.; Moreira, Samuel M.; Paiva, Ricardo Calil; Lopes, Hugo Belotti; Sousa, Amanda G. M. R.

2013-01-01

Background Aging and atherosclerosis are related to renovascular hypertension in elderly individuals. Regardless of comorbidities, renal artery stenosis is itself an important cause of cardiovascular morbidity and mortality. Objective To define the sensitivity, specificity, positive predictive value, and negative predictive value of noninvasive imaging tests used in the diagnosis of renal artery stenosis. Methods In a group of 61 patients recruited, 122 arteries were analized, thus permitting the definition of sensitivity, specificity, and the relative contribution of each imaging study performed (Doppler, scintigraphy and computed tomographic angiography in comparison to renal arteriography). Results The mean age was 65.43 years (standard deviation: 8.7). Of the variables related to the study population that were compared to arteriography, two correlated with renal artery stenosis, renal dysfunction and triglycerides. The median glomerular filtration rate was 52.8 mL/min/m2. Doppler showed sensitivity of 82.90%, specificity of 70%, a positive predictive value of 85% and negative predictive value of 66.70%. For tomography, sensitivity was 66.70%, specificity 80%, positive predictive value 87.50% and negative predictive value 55.20%. With these findings, we could identify the imaging tests that best detected stenosis. Conclusion Tomography and Doppler showed good quality and efficacy in the diagnosis of renal artery stenosis, with Doppler having the advantage of not requiring the use of contrast medium for the assessment of a disease that is common in diabetics and is associated with renal dysfunction and severe left ventricular dysfunction. PMID:24061685

Use of the International Classification of Diseases, 9th revision, coding in identifying chronic hepatitis B virus infection in health system data: implications for national surveillance.

PubMed

Mahajan, Reena; Moorman, Anne C; Liu, Stephen J; Rupp, Loralee; Klevens, R Monina

2013-05-01

With increasing use electronic health records (EHR) in the USA, we looked at the predictive values of the International Classification of Diseases, 9th revision (ICD-9) coding system for surveillance of chronic hepatitis B virus (HBV) infection. The chronic HBV cohort from the Chronic Hepatitis Cohort Study was created based on electronic health records (EHR) of adult patients who accessed services from 2006 to 2008 from four healthcare systems in the USA. Using the gold standard of abstractor review to confirm HBV cases, we calculated the sensitivity, specificity, positive and negative predictive values using one qualifying ICD-9 code versus using two qualifying ICD-9 codes separated by 6 months or greater. Of 1 652 055 adult patients, 2202 (0.1%) were confirmed as having chronic HBV. Use of one ICD-9 code had a sensitivity of 83.9%, positive predictive value of 61.0%, and specificity and negative predictive values greater than 99%. Use of two hepatitis B-specific ICD-9 codes resulted in a sensitivity of 58.4% and a positive predictive value of 89.9%. Use of one or two hepatitis B ICD-9 codes can identify cases with chronic HBV infection with varying sensitivity and positive predictive values. As the USA increases the use of EHR, surveillance using ICD-9 codes may be reliable to determine the burden of chronic HBV infection and would be useful to improve reporting by state and local health departments.

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

The validation of a human force model to predict dynamic forces resulting from multi-joint motions

NASA Technical Reports Server (NTRS)

Pandya, Abhilash K.; Maida, James C.; Aldridge, Ann M.; Hasson, Scott M.; Woolford, Barbara J.

1992-01-01

The development and validation is examined of a dynamic strength model for humans. This model is based on empirical data. The shoulder, elbow, and wrist joints were characterized in terms of maximum isolated torque, or position and velocity, in all rotational planes. This data was reduced by a least squares regression technique into a table of single variable second degree polynomial equations determining torque as a function of position and velocity. The isolated joint torque equations were then used to compute forces resulting from a composite motion, in this case, a ratchet wrench push and pull operation. A comparison of the predicted results of the model with the actual measured values for the composite motion indicates that forces derived from a composite motion of joints (ratcheting) can be predicted from isolated joint measures. Calculated T values comparing model versus measured values for 14 subjects were well within the statistically acceptable limits and regression analysis revealed coefficient of variation between actual and measured to be within 0.72 and 0.80.

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.

Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach-A Case Study for the City of Wuhan in China.

PubMed

Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

2017-06-15

Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study-simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan.

Models of Affective Decision Making: How Do Feelings Predict Choice?

PubMed

Charpentier, Caroline J; De Neve, Jan-Emmanuel; Li, Xinyi; Roiser, Jonathan P; Sharot, Tali

2016-06-01

Intuitively, how you feel about potential outcomes will determine your decisions. Indeed, an implicit assumption in one of the most influential theories in psychology, prospect theory, is that feelings govern choice. Surprisingly, however, very little is known about the rules by which feelings are transformed into decisions. Here, we specified a computational model that used feelings to predict choices. We found that this model predicted choice better than existing value-based models, showing a unique contribution of feelings to decisions, over and above value. Similar to the value function in prospect theory, our feeling function showed diminished sensitivity to outcomes as value increased. However, loss aversion in choice was explained by an asymmetry in how feelings about losses and gains were weighted when making a decision, not by an asymmetry in the feelings themselves. The results provide new insights into how feelings are utilized to reach a decision. © The Author(s) 2016.

Non-invasive assessment of liver fibrosis by transient elastography in post transfusional iron overload.

PubMed

Mirault, Tristan; Lucidarme, Damien; Turlin, Bruno; Vandevenne, Philippe; Gosset, Pierre; Ernst, Olivier; Rose, Christian

2008-04-01

Liver fibrosis, assessed by biopsy, is the main complication of post transfusional liver iron overload. Transient elastography (TE) is a new, non invasive method able to measure liver stiffness (LS) caused by fibrosis. We prospectively evaluated the predictive value of LS measurement for liver fibrosis evaluation in 15 chronically transfused patients and compared these results with the METAVIR histological fibrosis stage from liver biopsies. Mean TE values significantly differed in patients with severe fibrosis (METAVIR F3, F4): 9.1 (+/-3.7 SD) kPa from those with mild or no fibrosis (METAVIR F0, F1, F2): 5.9 (+/-1.8 SD) kPa (P = 0.046). TE value above 6.25 kPa (Se = 80%; Sp = 70%; AUROC = 0.820) identified patients at risk for severe fibrosis (Negative Predictive Value 88%; Positive Predictive Value 57%). Transient elastography appears to be a reliable tool to evaluate liver fibrosis in post-transfusional iron overload.

Dynamic Divisive Normalization Predicts Time-Varying Value Coding in Decision-Related Circuits

PubMed Central

LoFaro, Thomas; Webb, Ryan; Glimcher, Paul W.

2014-01-01

Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. PMID:25429145

The influence of intrinsic and extrinsic job values on turnover intention among continuing care assistants in Nova Scotia.

PubMed

Dill, Donna M; Keefe, Janice M; McGrath, Daniel S

2012-01-01

This article examines the influence that intrinsic and extrinsic job values have on the turnover intention of continuing care assistants (CCAs) who work either in home care or facility-based care in Nova Scotia (n = 188). Factor analysis of job values identified three latent job values structures: "compensation and commitment," "flexibility and opportunity," and "positive work relationships." Using binary logistic regression, we examined the predictive utility of these factors on two indices of turnover intention. Regression results indicate that, in general, job values constructs did not significantly predict turnover intention when controlling for demographics and job characteristics. However, a trend was found for the "positive work relationships" factor in predicting consideration of changing employers. In addition, CCAs who work in facility-based care were significantly more likely to have considered leaving their current employer. With projected increases in the demand for these workers in both home and continuing care, more attention is needed to identify and address factors to reduce turnover intention.

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

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

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.

Adaptation of clinical prediction models for application in local settings.

PubMed

Kappen, Teus H; Vergouwe, Yvonne; van Klei, Wilton A; van Wolfswinkel, Leo; Kalkman, Cor J; Moons, Karel G M

2012-01-01

When planning to use a validated prediction model in new patients, adequate performance is not guaranteed. For example, changes in clinical practice over time or a different case mix than the original validation population may result in inaccurate risk predictions. To demonstrate how clinical information can direct updating a prediction model and development of a strategy for handling missing predictor values in clinical practice. A previously derived and validated prediction model for postoperative nausea and vomiting was updated using a data set of 1847 patients. The update consisted of 1) changing the definition of an existing predictor, 2) reestimating the regression coefficient of a predictor, and 3) adding a new predictor to the model. The updated model was then validated in a new series of 3822 patients. Furthermore, several imputation models were considered to handle real-time missing values, so that possible missing predictor values could be anticipated during actual model use. Differences in clinical practice between our local population and the original derivation population guided the update strategy of the prediction model. The predictive accuracy of the updated model was better (c statistic, 0.68; calibration slope, 1.0) than the original model (c statistic, 0.62; calibration slope, 0.57). Inclusion of logistical variables in the imputation models, besides observed patient characteristics, contributed to a strategy to deal with missing predictor values at the time of risk calculation. Extensive knowledge of local, clinical processes provides crucial information to guide the process of adapting a prediction model to new clinical practices.

[Predictive value of preoperative tests in estimating difficult intubation in patients who underwent direct laryngoscopy in ear, nose, and throat surgery].

PubMed

Karakus, Osman; Kaya, Cengiz; Ustun, Faik Emre; Koksal, Ersin; Ustun, Yasemin Burcu

2015-01-01

Predictive value of preoperative tests in estimating difficult intubation may differ in the laryngeal pathologies. Patients who had undergone direct laryngoscopy (DL) were reviewed, and predictive value of preoperative tests in estimating difficult intubation was investigated. Preoperative, and intraoperative anesthesia record forms, and computerized system of the hospital were screened. A total of 2611 patients were assessed. In 7.4% of the patients, difficult intubations were detected. Difficult intubations were encountered in some of the patients with Mallampati scoring (MS) system Class 4 (50%), Cormack-Lehane classification (CLS) Grade 4 (95.7%), previous knowledge of difficult airway (86.2%), restricted neck movements (cervical ROM) (75.8%), short thyromental distance (TMD) (81.6%), vocal cord mass (49.5%) as indicated in parentheses (p<0.0001). MS had a low sensitivity, while restricted cervical ROM, presence of a vocal cord mass, short thyromental distance, and MS each had a relatively higher positive predictive value. Incidence of difficult intubations increased 6.159 and 1.736-fold with each level of increase in CLS grade and MS class, respectively. When all tests were considered in combination difficult intubation could be classified accurately in 96.3% of the cases. Test results predicting difficult intubations in cases with DL had observedly overlapped with the results provided in the literature for the patient populations in general. Differences in some test results when compared with those of the general population might stem from the concomitant underlying laryngeal pathological conditions in patient populations with difficult intubation. Copyright © 2014 Sociedade Brasileira de Anestesiologia. Publicado por Elsevier Editora Ltda. All rights reserved.

Acid deposition in east Asia

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

Phadnis, M.J.; Carmichael, G.R.; Ichikawa, Y.

1996-12-31

A comparison between transport models was done to study the acid deposition in east Asia. The two models in question were different in the way the treated the pollutant species and the way simulation was carried out. A single-layer, trajectory model with simple (developed by the Central Research Institute of Electric Power Industry (CRIEPI), Japan) was compared with a multi-layered, eulerian type model (Sulfur Transport Eulerian Model - II [STEM-II]) treating the chemical processes in detail. The acidic species used in the simulation were sulfur dioxide and sulfate. The comparison was done for two episodes: each a month long inmore » winter (February) and summer (August) of 1989. The predicted results from STEM-II were compared with the predicted results from the CRIEPI model as well as the observed data at twenty-one stations in Japan. The predicted values from STEM-II were similar to the ones from the CRIEPI results and the observed values in regards to the transport features. The average monthly values of SO{sub 2} in air, sulfate in air and sulfate in precipitation were in good agreement. Sensitivity studies were carried out under different scenarios of emissions, dry depositions velocities and mixing heights. The predicted values in these sensitivity studies showed a strong dependence on the mixing heights. The predicted wet deposition of sulfur for the two months is 0.7 gS/m2.mon, while the observed deposition is around 1.1 gS/m2.mon. It was also observed that the wet deposition on the Japan sea side of the islands is more than those on the Pacific side and the Okhotsk sea, mainly because of the continental outflow of pollutant air masses from mainland China and Korea. The effects of emissions from Russia and volcanoes were also evaluated.« less

Grandmothers’ Familism Values, Adolescent Mothers’ Parenting Efficacy, and Children’s Well-Being

PubMed Central

Zeiders, Katharine H.; Umaña-Taylor, Adriana J.; Jahromi, Laudan B.; Updegraff, Kimberly A.

2016-01-01

The current study examined intergenerational processes related to familism values among grandmothers, adolescent mothers, and their children. Mexican-origin families (N = 180) participated in in-home interviews during adolescent mothers’ third trimester of pregnancy and 10-, 24-, 48-, and 60-months postpartum. Using longitudinal path analyses, we linked grandmothers’ familism values and behaviors to adolescent mothers’ parenting processes and, in turn, their child’s well-being, taking into account developmentally relevant needs of adolescent mothers. Results revealed that grandmothers’ familism values before the birth of the baby predicted child-rearing support and communication within the grandmother-adolescent mother dyad after the birth of the baby. Support, but not communication, was in turn predictive of adolescent mothers’ parenting self-efficacy, but only at high levels of autonomy granting within the grandmother-adolescent mother dyad. Finally, adolescent mothers’ parenting self-efficacy predicted children’s greater social competence (48 months old), which in turn, predicted greater academic functioning (60 months old). Our findings shed light on the behavioral correlates of familism values within Mexican-origin families with adolescent mothers and highlight the need to consider factors that are developmentally salient (e.g., autonomy) when understanding how familism behaviors benefit adolescent mothers and their children. PMID:26075734

[Rapid determination of componential contents and calorific value of selected agricultural biomass feedstocks using spectroscopic technology].

PubMed

Sheng, Kui-Chuan; Shen, Ying-Ying; Yang, Hai-Qing; Wang, Wen-Jin; Luo, Wei-Qiang

2012-10-01

Rapid determination of biomass feedstock properties is of value for the production of biomass densification briquetting fuel with high quality. In the present study, visible and near-infrared (Vis-NIR) spectroscopy was employed to build prediction models of componential contents, i. e. moisture, ash, volatile matter and fixed-carbon, and calorific value of three selected species of agricultural biomass feedstock, i. e. pine wood, cedar wood, and cotton stalk. The partial least squares (PLS) cross validation results showed that compared with original reflection spectra, PLS regression models developed for first derivative spectra produced higher prediction accuracy with coefficients of determination (R2) of 0.97, 0.94 and 0.90, and residual prediction deviation (RPD) of 6.57, 4.00 and 3.01 for ash, volatile matter and moisture, respectively. Good prediction accuracy was achieved with R2 of 0.85 and RPD of 2.55 for fixed carbon, and R2 of 0.87 and RPD of 2.73 for calorific value. It is concluded that the Vis-NIR spectroscopy is promising as an alternative of traditional proximate analysis for rapid determination of componential contents and calorific value of agricultural biomass feedstock

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.

Prognostic and predictive value of TP53 mutations in node-positive breast cancer patients treated with anthracycline- or anthracycline/taxane-based adjuvant therapy: results from the BIG 02-98 phase III trial

PubMed Central

2012-01-01

Abstract Introduction Pre-clinical data suggest p53-dependent anthracycline-induced apoptosis and p53-independent taxane activity. However, dedicated clinical research has not defined a predictive role for TP53 gene mutations. The aim of the current study was to retrospectively explore the prognosis and predictive values of TP53 somatic mutations in the BIG 02-98 randomized phase III trial in which women with node-positive breast cancer were treated with adjuvant doxorubicin-based chemotherapy with or without docetaxel. Methods The prognostic and predictive values of TP53 were analyzed in tumor samples by gene sequencing within exons 5 to 8. Patients were classified according to p53 protein status predicted from TP53 gene sequence, as wild-type (no TP53 variation or TP53 variations which are predicted not to modify p53 protein sequence) or mutant (p53 nonsynonymous mutations). Mutations were subcategorized according to missense or truncating mutations. Survival analyses were performed using the Kaplan-Meier method and log-rank test. Cox-regression analysis was used to identify independent predictors of outcome. Results TP53 gene status was determined for 18% (520 of 2887) of the women enrolled in BIG 02-98. TP53 gene variations were found in 17% (90 of 520). Nonsynonymous p53 mutations, found in 16.3% (85 of 520), were associated with older age, ductal morphology, higher grade and hormone-receptor negativity. Of the nonsynonymous mutations, 12.3% (64 of 520) were missense and 3.6% were truncating (19 of 520). Only truncating mutations showed significant independent prognostic value, with an increased recurrence risk compared to patients with non-modified p53 protein (hazard ratio = 3.21, 95% confidence interval = 1.740 to 5.935, P = 0.0002). p53 status had no significant predictive value for response to docetaxel. Conclusions p53 truncating mutations were uncommon but associated with poor prognosis. No significant predictive role for p53 status was detected. Trial registration ClinicalTrials.gov NCT00174655 PMID:22551440

Carotid bruit for detection of hemodynamically significant carotid stenosis: the Northern Manhattan Study

PubMed Central

Ratchford, Elizabeth V.; Jin, Zhezhen; Di Tullio, Marco R.; Salameh, Maya J.; Homma, Shunichi; Gan, Robert; Boden-Albala, Bernadette; Sacco, Ralph L.; Rundek, Tatjana

2009-01-01

Objective The prevalence of carotid bruits and the utility of auscultation for predicting carotid stenosis are not well known. We aimed to establish the prevalence of carotid bruits and the diagnostic accuracy of auscultation for detection of hemodynamically significant carotid stenosis, using carotid duplex as the gold standard. Methods The Northern Manhattan Study (NOMAS) is a prospective multiethnic community-based cohort designed to examine the incidence of stroke and other vascular events and the association between various vascular risk factors and subclinical atherosclerosis. Of the stroke-free cohort (n=3298), 686 were examined for carotid bruits and underwent carotid duplex. Main outcome measures included prevalence of carotid bruits and sensitivity, specificity, positive predictive value, negative predictive value and accuracy of auscultation for prediction of ipsilateral carotid stenosis. Results Among 686 subjects with a mean age of 68.2 ± 9.4 years, the prevalence of ≥60% carotid stenosis as detected by ultrasound was 2.2% and the prevalence of carotid bruits was 4.1%. For detection of carotid stenosis, sensitivity of auscultation was 56%, specificity was 98%, positive predictive value was 25%, negative predictive value was 99% and overall accuracy was 97.5%. Discussion In this ethnically diverse cohort, the prevalence of carotid bruits and hemodynamically significant carotid stenosis was low. Sensitivity and positive predictive value were also low, and the 44% false-negative rate suggests that auscultation is not sufficient to exclude carotid stenosis. While the presence of a bruit may still warrant further evaluation with carotid duplex, ultrasonography may be considered in high-risk asymptomatic patients, irrespective of findings on auscultation. PMID:19133168

Incorporating Psychological Predictors of Treatment Response into Health Economic Simulation Models: A Case Study in Type 1 Diabetes.

PubMed

Kruger, Jen; Pollard, Daniel; Basarir, Hasan; Thokala, Praveen; Cooke, Debbie; Clark, Marie; Bond, Rod; Heller, Simon; Brennan, Alan

2015-10-01

. Health economic modeling has paid limited attention to the effects that patients' psychological characteristics have on the effectiveness of treatments. This case study tests 1) the feasibility of incorporating psychological prediction models of treatment response within an economic model of type 1 diabetes, 2) the potential value of providing treatment to a subgroup of patients, and 3) the cost-effectiveness of providing treatment to a subgroup of responders defined using 5 different algorithms. . Multiple linear regressions were used to investigate relationships between patients' psychological characteristics and treatment effectiveness. Two psychological prediction models were integrated with a patient-level simulation model of type 1 diabetes. Expected value of individualized care analysis was undertaken. Five different algorithms were used to provide treatment to a subgroup of predicted responders. A cost-effectiveness analysis compared using the algorithms to providing treatment to all patients. . The psychological prediction models had low predictive power for treatment effectiveness. Expected value of individualized care results suggested that targeting education at responders could be of value. The cost-effectiveness analysis suggested, for all 5 algorithms, that providing structured education to a subgroup of predicted responders would not be cost-effective. . The psychological prediction models tested did not have sufficient predictive power to make targeting treatment cost-effective. The psychological prediction models are simple linear models of psychological behavior. Collection of data on additional covariates could potentially increase statistical power. . By collecting data on psychological variables before an intervention, we can construct predictive models of treatment response to interventions. These predictive models can be incorporated into health economic models to investigate more complex service delivery and reimbursement strategies. © The Author(s) 2015.

Vasospasm on transcranial Doppler is predictive of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage: a systematic review and meta-analysis.

PubMed

Kumar, Gyanendra; Shahripour, Reza Bavarsad; Harrigan, Mark R

2016-05-01

OBJECT The impact of transcranial Doppler (TCD) ultrasonography evidence of vasospasm on patient-centered clinical outcomes following aneurysmal subarachnoid hemorrhage (aSAH) is unknown. Vasospasm is known to lead to delayed cerebral ischemia (DCI) and poor outcomes. This systematic review and meta-analysis evaluates the predictive value of vasospasm on DCI, as diagnosed on TCD. METHODS MEDLINE, Scopus, the Cochrane trial register, and clinicaltrials.gov were searched through September 2014 using key words and the terms "subarachnoid hemorrhage," "aneurysm," "aneurysmal," "cerebral vasospasm," "vasospasm," "transcranial Doppler," and "TCD." Sensitivities, specificities, and positive and negative predictive values were pooled by a DerSimonian and Laird random-effects model. RESULTS Seventeen studies (n = 2870 patients) met inclusion criteria. The amount of variance attributable to heterogeneity was significant (I(2) > 50%) for all syntheses. No studies reported the impact of TCD evidence of vasospasm on functional outcome or mortality. TCD evidence of vasospasm was found to be highly predictive of DCI. Pooled estimates for TCD diagnosis of vasospasm (for DCI) were sensitivity 90% (95% confidence interval [CI] 77%-96%), specificity 71% (95% CI 51%-84%), positive predictive value 57% (95% CI 38%-71%), and negative predictive value 92% (95% CI 83%-96%). CONCLUSIONS TCD evidence of vasospasm is predictive of DCI with high accuracy. Although high sensitivity and negative predictive value make TCD an ideal monitoring device, it is not a mandated standard of care in aSAH due to the paucity of evidence on clinically relevant outcomes, despite recommendation by national guidelines. High-quality randomized trials evaluating the impact of TCD monitoring on patient-centered and physician-relevant outcomes are needed.

[Analysis of energy expenditure in adults with cystic fibrosis: comparison of indirect calorimetry and prediction equations].

PubMed

Fuster, Casilda Olveira; Fuster, Gabriel Olveira; Galindo, Antonio Dorado; Galo, Alicia Padilla; Verdugo, Julio Merino; Lozano, Francisco Miralles

2007-07-01

Undernutrition, which implies an imbalance between energy intake and energy requirements, is common in patients with cystic fibrosis. The aim of this study was to compare resting energy expenditure determined by indirect calorimetry with that obtained with commonly used predictive equations in adults with cystic fibrosis and to assess the influence of clinical variables on the values obtained. We studied 21 patients with clinically stable cystic fibrosis, obtaining data on anthropometric variables, hand grip dynamometry, electrical bioimpedance, and resting energy expenditure by indirect calorimetry. We used the intraclass correlation coefficient (ICC) and the Bland-Altman method to assess agreement between the values obtained for resting energy expenditure measured by indirect calorimetry and those obtained with the World Health Organization (WHO) and Harris-Benedict prediction equations. The prediction equations underestimated resting energy expenditure in more than 90% of cases. The agreement between the value obtained by indirect calorimetry and that calculated with the prediction equations was poor (ICC for comparisons with the WHO and Harris-Benedict equations, 0.47 and 0.41, respectively). Bland-Altman analysis revealed a variable bias between the results of indirect calorimetry and those obtained with prediction equations, irrespective of the resting energy expenditure. The difference between the values measured by indirect calorimetry and those obtained with the WHO equation was significantly larger in patients homozygous for the DeltaF508 mutation and in those with exocrine pancreatic insufficiency. The WHO and Harris-Benedict prediction equations underestimate resting energy expenditure in adults with cystic fibrosis. There is poor agreement between the values for resting energy expenditure determined by indirect calorimetry and those estimated with prediction equations. Underestimation was greater in patients with exocrine pancreatic insufficiency and patients who were homozygous for DeltaF508.

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.

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

PubMed

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

2008-10-01

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

Fractional flow reserve by computerized tomography and subsequent coronary revascularization

PubMed Central

Packard, René R. Sevag; Li, Dong; Budoff, Matthew J.; Karlsberg, Ronald P.

2017-01-01

Aims Fractional flow reserve by computerized tomography (FFR-CT) provides non-invasive functional assessment of the hemodynamic significance of coronary artery stenosis. We determined the FFR-CT values, receiver operator characteristic (ROC) curves, and predictive ability of FFR-CT for actual standard of care guided coronary revascularization. Methods and results Consecutive outpatients who underwent coronary CT angiography (coronary CTA) followed by invasive angiography over a 24-month period from 2012 to 2014 were identified. Studies that fit inclusion criteria (n = 75 patients, mean age 66, 75% males) were sent for FFR-CT analysis, and results stratified by coronary artery calcium (CAC) scores. Coronary CTA studies were re-interpreted in a blinded manner, and baseline FFR-CT values were obtained retrospectively. Therefore, results did not interfere with clinical decision-making. Median FFR-CT values were 0.70 in revascularized (n = 69) and 0.86 in not revascularized (n = 138) coronary arteries (P < 0.001). Using clinically established significance cut-offs of FFR-CT ≤0.80 and coronary CTA ≥70% stenosis for the prediction of clinical decision-making and subsequent coronary revascularization, the positive predictive values were 74 and 88% and negative predictive values were 96 and 84%, respectively. The area under the curve (AUC) for all studied territories was 0.904 for coronary CTA, 0.920 for FFR-CT, and 0.941 for coronary CTA combined with FFR-CT (P = 0.001). With increasing CAC scores, the AUC decreased for coronary CTA but remained higher for FFR-CT (P < 0.05). Conclusion The addition of FFR-CT provides a complementary role to coronary CTA and increases the ability of a CT-based approach to identify subsequent standard of care guided coronary revascularization. PMID:27469588

1.5-Tesla Multiparametric-Magnetic Resonance Imaging for the detection of clinically significant prostate cancer

PubMed Central

POPITA, CRISTIAN; POPITA, ANCA RALUCA; SITAR-TAUT, ADELA; PETRUT, BOGDAN; FETICA, BOGDAN; COMAN, IOAN

2017-01-01

Background and aim Multiparametric-magnetic resonance imaging (mp-MRI) is the main imaging modality used for prostate cancer detection. The aim of this study is to evaluate the diagnostic performance of mp-MRI at 1.5-Tesla (1.5-T) for the detection of clinically significant prostate cancer. Methods In this ethical board approved prospective study, 39 patients with suspected prostate cancer were included. Patients with a history of positive prostate biopsy and patients treated for prostate cancer were excluded. All patients were examined at 1.5-T MRI, before standard transrectal ultrasonography–guided biopsy. Results The overall sensitivity, specificity, positive predictive value and negative predictive value for mp-MRI were 100%, 73.68%, 80% and 100%, respectively. Conclusion Our results showed that 1.5 T mp-MRI has a high sensitivity for detection of clinically significant prostate cancer and high negative predictive value in order to rule out significant disease. PMID:28246496

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

Subsonic Longitudinal Performance Coefficient Extraction from Shuttle Flight Data: an Accuracy Assessment for Determination of Data Base Updates

NASA Technical Reports Server (NTRS)

Findlay, J. T.; Kelly, G. M.; Mcconnell, J. G.; Compton, H. R.

1983-01-01

Longitudinal performance comparisons between flight derived and predicted values are presented for the first five NASA Space Shuttle Columbia flights. Though subsonic comparisons are emphasized, comparisons during the transonic and low supersonic regions of flight are included. Computed air data information based on the remotely sensed atmospheric measurements as well as in situ Orbiter Air Data System (ADS) measurements were incorporated. Each air data source provides for comparisons versus the predicted values from the LaRC data base. Principally, L/D, C sub L, and C sub D, comparisons are presented, though some pitching moment results are included. Similarities in flight conditions and spacecraft configuration during the first five flights are discussed. Contributions from the various elements of the data base are presented and the overall differences observed between the flight and predicted values are discussed in terms of expected variations. A discussion on potential data base updates is presented based on the results from the five flights to date.

Usefulness of a 50-meter round walking test for fall prediction in the elderly requiring long-term care

PubMed Central

Hachiya, Mizuki; Murata, Shin; Otao, Hiroshi; Ihara, Takehiko; Mizota, Katsuhiko; Asami, Toyoko

2015-01-01

[Purpose] This study aimed to verify the usefulness of a 50-m round walking test developed as an assessment method for walking ability in the elderly. [Subjects] The subjects were 166 elderly requiring long-term care individuals (mean age, 80.5 years). [Methods] In order to evaluate the factors that had affected falls in the subjects in the previous year, we performed the 50-m round walking test, functional reach test, one-leg standing test, and 5-m walking test and measured grip strength and quadriceps strength. [Results] The 50-m round walking test was selected as a variable indicating fall risk based on the results of multiple logistic regression analysis. The cutoff value of the 50-m round walking test for determining fall risk was 0.66 m/sec. The area under the receiver operating characteristic curve was 0.64. The sensitivity of the cutoff value was 65.7%, the specificity was 63.6%, the positive predictive value was 55.0%, the negative predictive value was 73.3%, and the accuracy was 64.5%. [Conclusion] These results suggest that the 50-m round walking test is a potentially useful parameter for the determination of fall risk in the elderly requiring long-term care. PMID:26834327

Exercise testing after beta-blockade: improved specificity and predictive value in detecting coronary heart disease.

PubMed Central

Marcomichelakis, J; Donaldson, R; Green, J; Joseph, S; Kelly, H B; Taggart, P; Somerville, W

1980-01-01

The value of exercise testing in detecting myocardial ischaemia resulting from coronary atheroma remains controversial. In order to increase the reliability of exercise testing, all its components (asymptomatic, haemodynamic, and electrocardiographic) have been scrutinised. In this study, concerned only with the electrocardiographic response to exercise, the incorporation of beta-blockade into the standard exercise procedure has improved specificity and predictive value without affecting sensitivity. Fifty patients with anginal pain and 50 asymptomatic subjects with an abnormal electrocardiogram were investigated by exercise testing before and after beta-blockade (oxprenolol). All subjects had coronary arteriograms and left ventriculograms, and the results of exercise testing were related to the presence or absence of obstructive coronary artery disease. Possible causes of false positive exercise tests were eliminated by echocardiography. Though beta-blockade was unreliable in distinguishing ischaemic from non-ischaemic resting electrocardiograms, it eliminated all the false positive electrocardiographic responses to exercise in both groups and did not abolish any of the true positive electrocardiographic responses. Thus, specificity and predictive value were improved without reduction in sensitivity. This technique may not necessarily be applicable to other groups of patients or to a random population, but the results of this study suggest it will be a useful additional routine procedure in the investigation of coronary heart disease. PMID:7437172

Usefulness of a 50-meter round walking test for fall prediction in the elderly requiring long-term care.

PubMed

Hachiya, Mizuki; Murata, Shin; Otao, Hiroshi; Ihara, Takehiko; Mizota, Katsuhiko; Asami, Toyoko

2015-12-01

[Purpose] This study aimed to verify the usefulness of a 50-m round walking test developed as an assessment method for walking ability in the elderly. [Subjects] The subjects were 166 elderly requiring long-term care individuals (mean age, 80.5 years). [Methods] In order to evaluate the factors that had affected falls in the subjects in the previous year, we performed the 50-m round walking test, functional reach test, one-leg standing test, and 5-m walking test and measured grip strength and quadriceps strength. [Results] The 50-m round walking test was selected as a variable indicating fall risk based on the results of multiple logistic regression analysis. The cutoff value of the 50-m round walking test for determining fall risk was 0.66 m/sec. The area under the receiver operating characteristic curve was 0.64. The sensitivity of the cutoff value was 65.7%, the specificity was 63.6%, the positive predictive value was 55.0%, the negative predictive value was 73.3%, and the accuracy was 64.5%. [Conclusion] These results suggest that the 50-m round walking test is a potentially useful parameter for the determination of fall risk in the elderly requiring long-term care.

Predicting lake trophic state by relating Secchi-disk transparency measurements to Landsat-satellite imagery for Michigan inland lakes, 2003-05 and 2007-08

USGS Publications Warehouse

Fuller, L.M.; Jodoin, R.S.; Minnerick, R.J.

2011-01-01

Inland lakes are an important economic and environmental resource for Michigan. The U.S. Geological Survey and the Michigan Department of Natural Resources and Environment have been cooperatively monitoring the quality of selected lakes in Michigan through the Lake Water Quality Assessment program. Sampling for this program began in 2001; by 2010, 730 of Michigan’s 11,000 inland lakes are expected to have been sampled once. Volunteers coordinated by the Michigan Department of Natural Resources and Environment began sampling lakes in 1974 and continue to sample (in 2010) approximately 250 inland lakes each year through the Michigan Cooperative Lakes Monitoring Program. Despite these sampling efforts, it still is impossible to physically collect measurements for all Michigan inland lakes; however, Landsat-satellite imagery has been used successfully in Minnesota, Wisconsin, Michigan, and elsewhere to predict the trophic state of unsampled inland lakes greater than 20 acres by producing regression equations relating in-place Secchi-disk measurements to Landsat bands. This study tested three alternatives to methods previously used in Michigan to improve results for predicted statewide Trophic State Index (TSI) computed from Secchi-disk transparency (TSI (SDT)). The alternative methods were used on 14 Landsat-satellite scenes with statewide TSI (SDT) for two time periods (2003– 05 and 2007–08). Specifically, the methods were (1) satellitedata processing techniques to remove areas affected by clouds, cloud shadows, haze, shoreline, and dense vegetation for inland lakes greater than 20 acres in Michigan; (2) comparison of the previous method for producing a single open-water predicted TSI (SDT) value (which was based on an area of interest (AOI) and lake-average approach) to an alternative Gethist method for identifying open-water areas in inland lakes (which follows the initial satellite-data processing and targets the darkest pixels, representing the deepest water, before regression equations are created); and (3) checking to see whether the predicted TSI (SDT) values compared well between two regression equations, one previously used in Michigan and an alternative equation from the hydrologic literature. The combination of improved satellite-data processing techniques and the Gethist method to identify open-water areas in inland lakes during 2003–05 and 2007–08 provided a stronger relation and statistical significance between predicted TSI (SDT) and measured TSI than did the AOI lake-average method; differences in results for the two methods were significant at the 99-percent confidence level. With regard to the comparison of the regression equations, there were no statistically significant differences at the 95-percent confidence level between results from the two equations. The previously used equation, in combination with the Gethist method, yielded coefficient of determination (R2) values of 0.71 and 0.77 for the periods 2003–05 and 2007–08, respectively. The alternative equation, in combination with the Gethist method, yielded R2 values of 0.74 and 0.75 for 2003–05 and 2007–08, respectively. Predicted TSI (SDT) and measured TSI (SDT) values for lakes used in the regression equations compared well, with R2 values of 0.95 and 0.96 for predicted TSI (SDT) for 2003–05 and 2007–08, respectively. The R2 values for statewide predicted TSI (SDT) for all inland lakes with available open-water areas for 2003–05 and 2007–08 were 0.91 and 0.93, respectively. Although the two equations predicted similar trophic-state classes, the alternative equation is planned to be used for future prediction of TSI (SDT) values for Michigan inland lakes, to promote consistency in comparing predicted values between States and for potential use in trend analysis.

Incremental Value of Repeated Risk Factor Measurements for Cardiovascular Disease Prediction in Middle-Aged Korean Adults: Results From the NHIS-HEALS (National Health Insurance System-National Health Screening Cohort).

PubMed

Cho, In-Jeong; Sung, Ji Min; Chang, Hyuk-Jae; Chung, Namsik; Kim, Hyeon Chang

2017-11-01

Increasing evidence suggests that repeatedly measured cardiovascular disease (CVD) risk factors may have an additive predictive value compared with single measured levels. Thus, we evaluated the incremental predictive value of incorporating periodic health screening data for CVD prediction in a large nationwide cohort with periodic health screening tests. A total of 467 708 persons aged 40 to 79 years and free from CVD were randomly divided into development (70%) and validation subcohorts (30%). We developed 3 different CVD prediction models: a single measure model using single time point screening data; a longitudinal average model using average risk factor values from periodic screening data; and a longitudinal summary model using average values and the variability of risk factors. The development subcohort included 327 396 persons who had 3.2 health screenings on average and 25 765 cases of CVD over 12 years. The C statistics (95% confidence interval [CI]) for the single measure, longitudinal average, and longitudinal summary models were 0.690 (95% CI, 0.682-0.698), 0.695 (95% CI, 0.687-0.703), and 0.752 (95% CI, 0.744-0.760) in men and 0.732 (95% CI, 0.722-0.742), 0.735 (95% CI, 0.725-0.745), and 0.790 (95% CI, 0.780-0.800) in women, respectively. The net reclassification index from the single measure model to the longitudinal average model was 1.78% in men and 1.33% in women, and the index from the longitudinal average model to the longitudinal summary model was 32.71% in men and 34.98% in women. Using averages of repeatedly measured risk factor values modestly improves CVD predictability compared with single measurement values. Incorporating the average and variability information of repeated measurements can lead to great improvements in disease prediction. URL: https://www.clinicaltrials.gov. Unique identifier: NCT02931500. © 2017 American Heart Association, Inc.

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

Predictive equations for total lung capacity and residual volume calculated from radiographs in a random sample of the Michigan population.

PubMed Central

Kilburn, K H; Warshaw, R H; Thornton, J C; Thornton, K; Miller, A

1992-01-01

BACKGROUND: Published predicted values for total lung capacity and residual volume are often based on a small number of subjects and derive from different populations from predicted spirometric values. Equations from the only two large studies gave smaller predicted values for total lung capacity than the smaller studies. A large number of subjects have been studied from a population which has already provided predicted values for spirometry and transfer factor for carbon monoxide. METHODS: Total lung capacity was measured from standard posteroanterior and lateral chest radiographs and forced vital capacity by spirometry in a population sample of 771 subjects. Prediction equations were developed for total lung capacity (TLC), residual volume (RV) and RV/TLC in two groups--normal and total. Subjects with signs or symptoms of cardiopulmonary disease were combined with the normal subjects and equations for all subjects were also modelled. RESULTS: Prediction equations for TLC and RV in non-smoking normal men and women were square root transformations which included height and weight but not age. They included a coefficient for duration of smoking in current smokers. The predictive equation for RV/TLC included weight, age, age and duration of smoking for current smokers and ex-smokers of both sexes. For the total population the equations took the same form but the height coefficients and constants were slightly different. CONCLUSION: These population based prediction equations for TLC, RV and RV/TLC provide reference standards in a population that has provided reference standards for spirometry and single breath transfer factor for carbon monoxide. PMID:1412094

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 Contribution of Neutrophil/Lymphocyte Ratio in Diagnosis of Brucellosis

PubMed Central

Olt, Serdar; Ergenç, Hasan; Açıkgöz, Seyyid Bilal

2015-01-01

Here we wanted to investigate predictive value of neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR) in the diagnosis of brucellosis. Thirty-two brucellosis patients diagnosed with positive serum agglutination test and thirty-two randomized healthy subjects were enrolled in this study retrospectively. Result with ROC analyzes the baseline NLR and hemoglobin values were found to be significantly associated with brucellosis (P = 0.01, P = 0.01, resp.). Herein we demonstrated for the first time that NLR values were significantly associated with brucellosis. This situation can help clinicians during diagnosis of brucellosis. PMID:25722970

Revisiting Grodzins systematics of B(E2) values

DOE PAGES

Pritychenko, B.; Birch, M.; Singh, B.

2017-04-03

Using Grodzins formalism, we analyze systematics of our latest evaluated B(E2) data for all the even–even nuclei in Z=2–104. The analysis indicates a low predictive power of systematics for a large number of cases, and a strong correlation between B(E2) fit values and nuclear structure effects. These findings provide a strong rationale for introduction of individual or elemental (grouped by Z) fit parameters. The current estimates of quadrupole collectivities for systematics of even–even nuclei yield complementary values for comparison with experimental results and theoretical calculations. Furthermore, the lists of fit parameters and predicted B(E2) values are given and possible implicationsmore » are discussed.« less

An improved method for predicting the evolution of the characteristic parameters of an information system

NASA Astrophysics Data System (ADS)

Dushkin, A. V.; Kasatkina, T. I.; Novoseltsev, V. I.; Ivanov, S. V.

2018-03-01

The article proposes a forecasting method that allows, based on the given values of entropy and error level of the first and second kind, to determine the allowable time for forecasting the development of the characteristic parameters of a complex information system. The main feature of the method under consideration is the determination of changes in the characteristic parameters of the development of the information system in the form of the magnitude of the increment in the ratios of its entropy. When a predetermined value of the prediction error ratio is reached, that is, the entropy of the system, the characteristic parameters of the system and the depth of the prediction in time are estimated. The resulting values of the characteristics and will be optimal, since at that moment the system possessed the best ratio of entropy as a measure of the degree of organization and orderliness of the structure of the system. To construct a method for estimating the depth of prediction, it is expedient to use the maximum principle of the value of entropy.

B-mode Ultrasound Versus Color Doppler Twinkling Artifact in Detecting Kidney Stones

PubMed Central

Harper, Jonathan D.; Hsi, Ryan S.; Shah, Anup R.; Dighe, Manjiri K.; Carter, Stephen J.; Moshiri, Mariam; Paun, Marla; Lu, Wei; Bailey, Michael R.

2013-01-01

Abstract Purpose To compare color Doppler twinkling artifact and B-mode ultrasonography in detecting kidney stones. Patients and Methods Nine patients with recent CT scans prospectively underwent B-mode and twinkling artifact color Doppler ultrasonography on a commercial ultrasound machine. Video segments of the upper pole, interpolar area, and lower pole were created, randomized, and independently reviewed by three radiologists. Receiver operator characteristics were determined. Results There were 32 stones in 18 kidneys with a mean stone size of 8.9±7.5 mm. B-mode ultrasonography had 71% sensitivity, 48% specificity, 52% positive predictive value, and 68% negative predictive value, while twinkling artifact Doppler ultrasonography had 56% sensitivity, 74% specificity, 62% positive predictive value, and 68% negative predictive value. Conclusions When used alone, B-mode is more sensitive, but twinkling artifact is more specific in detecting kidney stones. This information may help users employ twinkling and B-mode to identify stones and developers to improve signal processing to harness the fundamental acoustic differences to ultimately improve stone detection. PMID:23067207

The predictive value of selected serum microRNAs for acute GVHD by TaqMan MicroRNA arrays.

PubMed

Zhang, Chunyan; Bai, Nan; Huang, Wenrong; Zhang, Pengjun; Luo, Yuan; Men, Shasha; Wen, Ting; Tong, Hongli; Wang, Shuhong; Tian, Ya-Ping

2016-10-01

Currently, the diagnosis of acute graft-versus-host disease (aGVHD) is mainly based on clinical symptoms and biopsy results. This study was designed to further explore new no noninvasive biomarkers for aGVHD prediction/diagnosis. We profiled miRNAs in serum pools from patients with aGVHD (grades II-IV) (n = 9) and non-aGVHD controls (n = 9) by real-time qPCR-based TaqMan MicroRNA arrays. Then, predictive models were established using related miRNAs (n = 38) and verified by a double-blind trial (n = 54). We found that miR-411 was significantly down regulated when aGVHD developed and recovered when aGVHD was controlled, which demonstrated that miR-411 has potential as an indicator for aGVHD monitoring. We developed and validated a predictive model and a diagnostic model for aGVHD. The predictive model included two miRNAs (miR-26b and miR-374a), which could predict an increased risk for aGVHD 1 or 2 weeks in advance, with an AUC, Positive Predictive Value (PPV), and Negative Predictive Value (NPV) of 0.722, 76.19 %, and 69.70 %, respectively. The diagnostic model included three miRNAs (miR-28-5p, miR-489, and miR-671-3p) with an AUC, PPV, and NPV of 0.841, 85.71 % and 83.33 %, respectively. Our results show that circulating miRNAs (miR-26b and miR-374a, miR-28-5p, miR-489 and miR-671-3p) may serve as biomarkers for the prediction and diagnosis of grades II-IV aGVHD.

Prediction of early and late preeclampsia by flow-mediated dilation of the brachial artery*

PubMed Central

Brandão, Augusto Henriques Fulgêncio; Evangelista, Aline Aarão; Martins, Raphaela Menin Franco; Leite, Henrique Vítor; Cabral, Antônio Carlos Vieira

2014-01-01

Objective To assess the accuracy in the prediction of both early and late preeclampsia by flow-mediated dilation of the brachial artery (FMD), a biophysical marker for endothelial dysfunction. Materials and Methods A total of 91 patients, considered at high risk for development of preeclampsia were submitted to brachial artery FMD between 24 and 28 weeks of gestation. Results Nineteen out of the selected patients developed preeclampsia, 8 in its early form and 11 in the late form. With a cut-off value of 6.5%, the FMD sensitivity for early preeclampsia prediction was 75.0%, with specificity of 73.3%, positive predictive value (PPV) of 32.4% and negative predictive value (NPV) of 91.9%. For the prediction of late preeclampsia, sensitivity = 83.3%, specificity = 73.2%, PPV = 34.4% and NPV = 96.2% were observed. And for the prediction of all associated forms of preeclampsia, sensitivity = 84.2%, specificity = 73.6%, PPV = 45.7% and NPV = 94.6% were observed. Conclusion FMD of the brachial artery is a test with good accuracy in the prediction of both early and late preeclampsia, which may represent a positive impact on the follow-up of pregnant women at high risk for developing this syndrome. PMID:25741086

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.

Reference Values for Spirometry Derived Using Lambda, Mu, Sigma (LMS) Method in Korean Adults: in Comparison with Previous References.

PubMed

Jo, Bum Seak; Myong, Jun Pyo; Rhee, Chin Kook; Yoon, Hyoung Kyu; Koo, Jung Wan; Kim, Hyoung Ryoul

2018-01-15

The present study aimed to update the prediction equations for spirometry and their lower limits of normal (LLN) by using the lambda, mu, sigma (LMS) method and to compare the outcomes with the values of previous spirometric reference equations. Spirometric data of 10,249 healthy non-smokers (8,776 females) were extracted from the fourth and fifth versions of the Korea National Health and Nutrition Examination Survey (KNHANES IV, 2007-2009; V, 2010-2012). Reference equations were derived using the LMS method which allows modeling skewness (lambda [L]), mean (mu [M]), and coefficient of variation (sigma [S]). The outcome equations were compared with previous reference values. Prediction equations were presented in the following form: predicted value = e{a + b × ln(height) + c × ln(age) + M - spline}. The new predicted values for spirometry and their LLN derived using the LMS method were shown to more accurately reflect transitions in pulmonary function in young adults than previous prediction equations derived using conventional regression analysis in 2013. There were partial discrepancies between the new reference values and the reference values from the Global Lung Function Initiative in 2012. The results should be interpreted with caution for young adults and elderly males, particularly in terms of the LLN for forced expiratory volume in one second/forced vital capacity in elderly males. Serial spirometry follow-up, together with correlations with other clinical findings, should be emphasized in evaluating the pulmonary function of individuals. Future studies are needed to improve the accuracy of reference data and to develop continuous reference values for spirometry across all ages. © 2018 The Korean Academy of Medical Sciences.

18F-FDG PET/CT in Detecting Metastatic Infection in Children.

PubMed

Kouijzer, Ilse J E; Blokhuis, Gijsbert J; Draaisma, Jos M T; Oyen, Wim J G; de Geus-Oei, Lioe-Fee; Bleeker-Rovers, Chantal P

2016-04-01

Metastatic infection is a severe complication of bacteremia with high morbidity and mortality. The aim of this study was to investigate the diagnostic value of 18F-FDG PET combined with CT (FDG PET/CT) in children suspected of having metastatic infection. The results of FDG PET/CT scans performed in children because of suspected metastatic infection from September 2003 to June 2013 were analyzed retrospectively. The results were compared with the final clinical diagnosis. FDG PET/CT was performed in 13 children with suspected metastatic infection. Of the total number of FDG PET/CT scans, 38% were clinically helpful. Positive predictive value of FDG PET/CT was 71%, and negative predictive value was 100%. FDG PET/CT appears to be a valuable diagnostic technique in children with suspected metastatic infection. Prospective studies of FDG PET/CT as part of a structured diagnostic protocol are needed to assess the exact additional diagnostic value.

Intrinsic Work Value-Reward Dissonance and Work Satisfaction during Young Adulthood

PubMed Central

Porfeli, Erik J.; Mortimer, Jeylan T.

2010-01-01

Previous research suggests that discrepancies between work values and rewards are indicators of dissonance that induce change in both to reduce such dissonance over time. The present study elaborates this model to suggest parallels with the first phase of the extension- and-strain curve. Small discrepancies or small increases in extension are presumed to be almost unnoticeable, while increasingly large discrepancies are thought to yield exponentially increasing strain. Work satisfaction is a principal outcome of dissonance; hence, work value-reward discrepancies are predicted to diminish work satisfaction in an exponential fashion. Findings from the work and family literature, however, lead to the prediction that this curvilinear association will be moderated by gender and family roles. Using longitudinal data spanning the third decade of life, the results suggest that intrinsic work value-reward discrepancies, as predicted, are increasingly associated, in a negative curvilinear fashion, with work satisfaction. This pattern, however, differs as a function of gender and family roles. Females who established family roles exhibited the expected pattern while other gender by family status groups did not. The results suggest that gender and family roles moderate the association between intrinsic work value-reward dissonance and satisfaction. In addition, women who remained unmarried and childless exhibited the strongest associations between occupational rewards and satisfaction. PMID:20526434

Intrinsic Work Value-Reward Dissonance and Work Satisfaction during Young Adulthood.

PubMed

Porfeli, Erik J; Mortimer, Jeylan T

2010-06-01

Previous research suggests that discrepancies between work values and rewards are indicators of dissonance that induce change in both to reduce such dissonance over time. The present study elaborates this model to suggest parallels with the first phase of the extension- and-strain curve. Small discrepancies or small increases in extension are presumed to be almost unnoticeable, while increasingly large discrepancies are thought to yield exponentially increasing strain. Work satisfaction is a principal outcome of dissonance; hence, work value-reward discrepancies are predicted to diminish work satisfaction in an exponential fashion. Findings from the work and family literature, however, lead to the prediction that this curvilinear association will be moderated by gender and family roles. Using longitudinal data spanning the third decade of life, the results suggest that intrinsic work value-reward discrepancies, as predicted, are increasingly associated, in a negative curvilinear fashion, with work satisfaction. This pattern, however, differs as a function of gender and family roles. Females who established family roles exhibited the expected pattern while other gender by family status groups did not. The results suggest that gender and family roles moderate the association between intrinsic work value-reward dissonance and satisfaction. In addition, women who remained unmarried and childless exhibited the strongest associations between occupational rewards and satisfaction.

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.

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

PubMed Central

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

2017-01-01

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

Identification of cognitive and non-cognitive predictive variables related to attrition in baccalaureate nursing education programs in Mississippi

NASA Astrophysics Data System (ADS)

Hayes, Catherine

2005-07-01

This study sought to identify a variable or variables predictive of attrition among baccalaureate nursing students. The study was quantitative in design and multivariate correlational statistics and discriminant statistical analysis were used to identify a model for prediction of attrition. The analysis then weighted variables according to their predictive value to determine the most parsimonious model with the greatest predictive value. Three public university nursing education programs in Mississippi offering a Bachelors Degree in Nursing were selected for the study. The population consisted of students accepted and enrolled in these three programs for the years 2001 and 2002 and graduating in the years 2003 and 2004 (N = 195). The categorical dependent variable was attrition (includes academic failure or withdrawal) from the program of nursing education. The ten independent variables selected for the study and considered to have possible predictive value were: Grade Point Average for Pre-requisite Course Work; ACT Composite Score, ACT Reading Subscore, and ACT Mathematics Subscore; Letter Grades in the Courses: Anatomy & Physiology and Lab I, Algebra I, English I (101), Chemistry & Lab I, and Microbiology & Lab I; and Number of Institutions Attended (Universities, Colleges, Junior Colleges or Community Colleges). Descriptive analysis was performed and the means of each of the ten independent variables was compared for students who attrited and those who were retained in the population. The discriminant statistical analysis performed created a matrix using the ten variable model that was able to correctly predicted attrition in the study's population in 77.6% of the cases. Variables were then combined and recombined to produce the most efficient and parsimonious model for prediction. A six variable model resulted which weighted each variable according to predictive value: GPA for Prerequisite Coursework, ACT Composite, English I, Chemistry & Lab I, Microbiology & Lab I, and Number of Institutions Attended. Results of the study indicate that it is possible to predict attrition among students enrolled in baccalaureate nursing education programs and that additional investigation on the subject is warranted.

SWMF Global Magnetosphere Simulations of January 2005: Geomagnetic Indices and Cross-Polar Cap Potential

NASA Astrophysics Data System (ADS)

Haiducek, John D.; Welling, Daniel T.; Ganushkina, Natalia Y.; Morley, Steven K.; Ozturk, Dogacan Su

2017-12-01

We simulated the entire month of January 2005 using the Space Weather Modeling Framework (SWMF) with observed solar wind data as input. We conducted this simulation with and without an inner magnetosphere model and tested two different grid resolutions. We evaluated the model's accuracy in predicting Kp, SYM-H, AL, and cross-polar cap potential (CPCP). We find that the model does an excellent job of predicting the SYM-H index, with a root-mean-square error (RMSE) of 17-18 nT. Kp is predicted well during storm time conditions but overpredicted during quiet times by a margin of 1 to 1.7 Kp units. AL is predicted reasonably well on average, with an RMSE of 230-270 nT. However, the model reaches the largest negative AL values significantly less often than the observations. The model tended to overpredict CPCP, with RMSE values on the order of 46-48 kV. We found the results to be insensitive to grid resolution, with the exception of the rate of occurrence for strongly negative AL values. The use of the inner magnetosphere component, however, affected results significantly, with all quantities except CPCP improved notably when the inner magnetosphere model was on.

Tablet Velocity Measurement and Prediction in the Pharmaceutical Film Coating Process.

PubMed

Suzuki, Yasuhiro; Yokohama, Chihiro; Minami, Hidemi; Terada, Katsuhide

2016-01-01

The purpose of this study was to measure the tablet velocity in pan coating machines during the film coating process in order to understand the impact of the batch size (laboratory to commercial scale), coating machine type (DRIACOATER, HICOATER® and AQUA COATER®) and manufacturing conditions on tablet velocity. We used a high speed camera and particle image velocimetry to measure the tablet velocity in the coating pans. It was observed that increasing batch sizes resulted in increased tablet velocities under the same rotation number because of the differences in circumferential rotation speeds. We also observed the tendency that increase in the filling ratio of tablets resulted in an increased tablet velocity for all coating machines. Statistical analysis was used to make a tablet velocity predictive equation by employing the filling ratio and rotation speed as the parameters from these measured values. The correlation coefficients of predicted value and experimental value were more than 0.959 in each machine. Using the predictive equation to determine tablet velocities, the manufacturing conditions of previous products were reviewed, and it was found that the tablet velocities of commercial scales, in which tablet chipping and breakage problems had occurred, were higher than those of pilot scales or laboratory scales.

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.

The value of nodal information in predicting lung cancer relapse using 4DPET/4DCT

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

Li, Heyse, E-mail: heyse.li@mail.utoronto.ca; Becker, Nathan; Raman, Srinivas

2015-08-15

Purpose: There is evidence that computed tomography (CT) and positron emission tomography (PET) imaging metrics are prognostic and predictive in nonsmall cell lung cancer (NSCLC) treatment outcomes. However, few studies have explored the use of standardized uptake value (SUV)-based image features of nodal regions as predictive features. The authors investigated and compared the use of tumor and node image features extracted from the radiotherapy target volumes to predict relapse in a cohort of NSCLC patients undergoing chemoradiation treatment. Methods: A prospective cohort of 25 patients with locally advanced NSCLC underwent 4DPET/4DCT imaging for radiation planning. Thirty-seven image features were derivedmore » from the CT-defined volumes and SUVs of the PET image from both the tumor and nodal target regions. The machine learning methods of logistic regression and repeated stratified five-fold cross-validation (CV) were used to predict local and overall relapses in 2 yr. The authors used well-known feature selection methods (Spearman’s rank correlation, recursive feature elimination) within each fold of CV. Classifiers were ranked on their Matthew’s correlation coefficient (MCC) after CV. Area under the curve, sensitivity, and specificity values are also presented. Results: For predicting local relapse, the best classifier found had a mean MCC of 0.07 and was composed of eight tumor features. For predicting overall relapse, the best classifier found had a mean MCC of 0.29 and was composed of a single feature: the volume greater than 0.5 times the maximum SUV (N). Conclusions: The best classifier for predicting local relapse had only tumor features. In contrast, the best classifier for predicting overall relapse included a node feature. Overall, the methods showed that nodes add value in predicting overall relapse but not local relapse.« less

Adjusting Quality index Log Values to Represent Local and Regional Commercial Sawlog Product Values

Treesearch

Orris D. McCauley; Joseph J. Mendel; Joseph J. Mendel

1969-01-01

The primary purpose of this paper is not only to report the results of a comparative analysis as to how well the Q.I. method predicts log product values when compared to commercial sawmill log output values, but also to develop a methodology which will facilitate the comparison and provide the adjustments needed by the sawmill operator.

Protecting the Innocence of Youth: Moral Sanctity Values Underlie Censorship From Young Children.

PubMed

Anderson, Rajen A; Masicampo, E J

2017-11-01

Three studies examined the relationship between people's moral values (drawing on moral foundations theory) and their willingness to censor immoral acts from children. Results revealed that diverse moral values did not predict censorship judgments. It was not the case that participants who valued loyalty and authority, respectively, sought to censor depictions of disloyal and disobedient acts. Rather, censorship intentions were predicted by a single moral value-sanctity. The more people valued sanctity, the more willing they were to censor from children, regardless of the types of violations depicted (impurity, disloyalty, disobedience, etc.). Furthermore, people who valued sanctity objected to indecent exposure only to apparently innocent and pure children-those who were relatively young and who had not been previously exposed to immoral acts. These data suggest that sanctity, purity, and the preservation of innocence underlie intentions to censor from young children.

Theoretical predictions of the changes in the irradiance and color of light beams traveling in sugared water caused by optical rotation phenomena, and their possible applications for educational purposes

NASA Astrophysics Data System (ADS)

Tokumitsu, S.; Hasegawa, M.

2018-05-01

The coloring phenomena caused by optical rotation of polarized light beams in sugared water can be an appropriate subject for use as an educational tool. In this paper, such coloring phenomena are studied in terms of theory, and the results are compared with experimental results. First, polarized laser beams in red, blue, or green were allowed to travel in sugared water of certain concentrations, and changes in the irradiance of the beams were measured while changing the distance between a pair of polarizing plates arranged in the sugared water. The angle of rotation was then determined for each color. An equation was established for predicting a theoretical value of the angle of rotation for laser beams of specific colors (wavelengths) traveling in sugared water of specific concentrations. The predicted results from the equation exhibited satisfactory agreement with the experimental values obtained from the measurements. In addition, changes in the irradiance of traveling laser beams, as well as the changes in colors observable for white light beams, were also predicted, resulting in good agreement with the observed results.

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.

Reality Check Algorithm for Complex Sources in Early Warning

NASA Astrophysics Data System (ADS)

Karakus, G.; Heaton, T. H.

2013-12-01

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

CPO Prediction: Accuracy Assessment and Impact on UT1 Intensive Results

NASA Technical Reports Server (NTRS)

Malkin, Zinovy

2010-01-01

The UT1 Intensive results heavily depend on the celestial pole offset (CPO) model used during data processing. Since accurate CPO values are available with a delay of two to four weeks, CPO predictions are necessarily applied to the UT1 Intensive data analysis, and errors in the predictions can influence the operational UT1 accuracy. In this paper we assess the real accuracy of CPO prediction using the actual IERS and PUL predictions made in 2007-2009. Also, results of operational processing were analyzed to investigate the actual impact of EOP prediction errors on the rapid UT1 results. It was found that the impact of CPO prediction errors is at a level of several microseconds, whereas the impact of the inaccuracy in the polar motion prediction may be about one order of magnitude larger for ultra-rapid UT1 results. The situation can be amended if the IERS Rapid solution will be updated more frequently.

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%.

Temporal Stability of ADHD in the High-IQ Population: Results from the MGH Longitudinal Family Studies of ADHD

ERIC Educational Resources Information Center

Antshel, Kevin M.; Faraone, Stephen V.; Maglione, Katherine; Doyle, Alysa; Fried, Ronna; Seidman, Larry; Biederman, Joseph

2008-01-01

A study was conducted to establish the relationship between Attention-Deficit/Hyperactivity (ADHD) disorder and high-IQ children and whether ADHD has a high predictive value among youths with high-IQ. Results further supported the hypothesis for the predictive validity of ADHD in high-IQ youths.

South Asian women: identities and conflicts.

PubMed

Inman, Arpana G

2006-04-01

This study investigated the effects of education, level of religiosity, ethnic identity (internal and external), and racial identity statuses (conformity, dissonance, resistance, and awareness) on cultural value conflict for first and second generation South Asian women (N = 193). Cultural value conflict was examined in two areas, intimate relations and sex-role expectations. Results revealed that level of religiosity was more predictive of intimate relations conflict for second generation than first generation women. Furthermore, higher ratings in internal ethnic identity predicted greater intimate relations conflict in first generation women, while both internal and external ethnic identity predicted intimate relations conflict in second generation women. Finally, higher dissonance scores in racial identity predicted greater conflicts in sex-role expectations for second generation women alone.

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.

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)

A Review On Missing Value Estimation Using Imputation Algorithm

NASA Astrophysics Data System (ADS)

Armina, Roslan; Zain, Azlan Mohd; Azizah Ali, Nor; Sallehuddin, Roselina

2017-09-01

The presence of the missing value in the data set has always been a major problem for precise prediction. The method for imputing missing value needs to minimize the effect of incomplete data sets for the prediction model. Many algorithms have been proposed for countermeasure of missing value problem. In this review, we provide a comprehensive analysis of existing imputation algorithm, focusing on the technique used and the implementation of global or local information of data sets for missing value estimation. In addition validation method for imputation result and way to measure the performance of imputation algorithm also described. The objective of this review is to highlight possible improvement on existing method and it is hoped that this review gives reader better understanding of imputation method trend.

Our transthoracic biopsy practices accompanied by the imaging process: The contribution of positron emission tomography usage to accurate diagnosis.

PubMed

İntepe, Yavuz Selim; Metin, Bayram; Şahin, Sevinç; Kaya, Buğra; Okur, Aylin

2016-08-01

The objective of this study was to compare the results of transthoracic biopsies performed through the use of FDG PET/CT imaging with the results of transthoracic needle biopsy performed without using the FDG PET/CT imaging. The medical files of a total of 58 patients with pulmonary and mediastinal masses. A total of 20 patients, who were suspected of malignancy with the SUVmax value of over 2.5 in FDG PET/CT, underwent a biopsy process. Twelve patients with no suspicion of malignancy in accordance with CT images and with the SUVmax value below 2.5 underwent no biopsy procedure, and hence, they were excluded from the study. On the other hand, 26 patients directly went through a biopsy process with the suspicion of malignancy according to CT imaging, regardless of performing any FDG PET/CT imaging. According to the biopsy results, the number of the patients diagnosed with cancer was 20 (43.5%), while the number of non-cancerous patients was 26 (56.5%). When these findings were considered, it was determined that the sensitivity of the whole TTNB (transthoracic needle biopsy) was 80.8%, and the specificity was found as 100%. The positive predictive value of the whole TTNB was 100%, while its negative predictive value was found to be 80%. The sensitivity in TTNB performed together with FDG PET/CT was 90.9%, whereas the specificity was 100%. The positive predictive value of TTNB with FDG PET/CT was 100%, while its negative predictive value was found to be 81.8%. The sensitivity in TTNB performed without the use of FDG PET/CT was 73.3%, whereas the specificity was determined as 100%. Performing FDG PET/CT imaging process prior to a transthoracic biopsy as well as preferring FDG PET/CT for the spot on which the biopsy will be performed during the transthoracic biopsy procedure increases the rate of receiving accurate diagnosis.

Acute toxicity value extrapolation with fish and aquatic invertebrates

USGS Publications Warehouse

Buckler, Denny R.; Mayer, Foster L.; Ellersieck, Mark R.; Asfaw, Amha

2005-01-01

Assessment of risk posed by an environmental contaminant to an aquatic community requires estimation of both its magnitude of occurrence (exposure) and its ability to cause harm (effects). Our ability to estimate effects is often hindered by limited toxicological information. As a result, resource managers and environmental regulators are often faced with the need to extrapolate across taxonomic groups in order to protect the more sensitive members of the aquatic community. The goals of this effort were to 1) compile and organize an extensive body of acute toxicity data, 2) characterize the distribution of toxicant sensitivity across taxa and species, and 3) evaluate the utility of toxicity extrapolation methods based upon sensitivity relations among species and chemicals. Although the analysis encompassed a wide range of toxicants and species, pesticides and freshwater fish and invertebrates were emphasized as a reflection of available data. Although it is obviously desirable to have high-quality acute toxicity values for as many species as possible, the results of this effort allow for better use of available information for predicting the sensitivity of untested species to environmental contaminants. A software program entitled “Ecological Risk Analysis” (ERA) was developed that predicts toxicity values for sensitive members of the aquatic community using species sensitivity distributions. Of several methods evaluated, the ERA program used with minimum data sets comprising acute toxicity values for rainbow trout, bluegill, daphnia, and mysids provided the most satisfactory predictions with the least amount of data. However, if predictions must be made using data for a single species, the most satisfactory results were obtained with extrapolation factors developed for rainbow trout (0.412), bluegill (0.331), or scud (0.041). Although many specific exceptions occur, our results also support the conventional wisdom that invertebrates are generally more sensitive to contaminants than fish are.

Comparative study between cytotoxicity and flowcytometry crossmatches before and after renal transplantation.

PubMed

Abdel Rahman, Afaf S; Fahim, Nehal M A; El Sayed, Abeer A; El Hady, Soha A R; Ahmad, Yasser S

2005-01-01

Renal transplantation, in most countries, is based on human leukocyte antigen (HLA) matching of the donor kidney with the recipient. Traditional human leukocyte antigen matching is based on defining human leukocyte antigen specificities by antibodies utilizing cytotoxicity crossmatch techniques. Newer techniques have emerged, which challenge the accuracy of serological typing and crossmatching. We compared the results of the standard complement-dependent cytotoxicity crossmatch (CDCXM) with the anti-human globulin augmented cytotoxicity (AHG-CDC), and Flowcytometry crossmatch (FCXM) for the detection of anti-HLA antibodies in 150 pre-transplant patients. The development of post-transplantation sensitization was screened utilizing these three techniques within two weeks post-operative and correlated with rejection episodes. Comparison between the results of CDCXM and AHG-CDC in 150 recipients, revealed no significant correlation (P>0.05). When comparing these results with that of FCXM in 50 recipients a significant correlation was shown (P<0.05). Relative to CDCXM, the sensitivity of AHG-CDC was 100%, specificity 97.4%, positive predictive value 92.3%, and negative predictive value 100%. On the other hand, the sensitivity of FCXM was 100%, specificity 76.3%, positive predictive value 57.1%, and negative predictive value 100%. According to the results of CDCXM, AHG-CDC, and FCXM, no difference was detected between pre- and posttransplant anti-HLA sensitization within two weeks after the operation. Patients with negative cytotoxicity crossmatch (CDCXM and AHG-CDC) and positive FCXM may have an increased risk of early graft loss and may represent a relative contraindication to transplantation. Given the important theoretical advantages of FCXM over the CDC XM, further testing of the clinical relevance is warranted.

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.

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

Tree value system: description and assumptions.

Treesearch

D.G. Briggs

1989-01-01

TREEVAL is a microcomputer model that calculates tree or stand values and volumes based on product prices, manufacturing costs, and predicted product recovery. It was designed as an aid in evaluating management regimes. TREEVAL calculates values in either of two ways, one based on optimized tree bucking using dynamic programming and one simulating the results of user-...

Tree value system: users guide.

Treesearch

J.K. Ayer Sachet; D.G. Briggs; R.D. Fight

1989-01-01

This paper instructs resource analysts on use of the Tree Value System (TREEVAL). TREEVAL is a microcomputer system of programs for calculating tree or stand values and volumes based on predicted product recovery. Designed for analyzing silvicultural decisions, the system can also be used for appraisals and for evaluating log bucking. The system calculates results...

Performance characteristics of broth-only cultures after revision total joint arthroplasty.

PubMed

Smith, Eric B; Cai, Jenny; Wynne, Rachael; Maltenfort, Mitchell; Good, Robert P

2014-11-01

Surgeons frequently obtain intraoperative cultures at the time of revision total joint arthroplasty. The use of broth or liquid medium before applying the sample to the agar medium may be associated with contamination and false-positive cultures; however, the degree to which this is the case is not known. We (1) calculated the performance characteristics of broth-only cultures (sensitivity, specificity, positive predictive value, and negative predictive value) and (2) characterized the organisms identified in broth to determine whether a specific organism showed increased proclivity for true-positive periprosthetic joint infection (PJI). A single-institution retrospective chart review was performed on 257 revision total joint arthroplasties from 2009 through 2010. One hundred ninety (74%) had cultures for review. All culture results, as well as treatment, if any, were documented and patients were followed for a minimum of 1 year for evidence of PJI. Cultures were measured as either positive from the broth only or broth negative. The true diagnosis of infection was determined by the Musculoskeletal Infection Society criteria during the preoperative workup or postoperatively at 1 year for purposes of calculating the performance characteristics of the broth-only culture. The sensitivity, specificity, positive predictive value, and negative predictive value were 19%, 88%, 13%, and 92%, respectively. The most common organism identified was coagulase-negative Staphylococcus (16 of 24 cases, 67%). Coagulase-negative Staphylococcus was present in all three true-positive cases; however, it was also found in 13 of the false-positive cases. The broth-only positive cultures showed poor sensitivity and positive predictive value but good specificity and negative predictive value. The good specificity indicates that it can help to rule in the presence of PJI; however, the poor sensitivity makes broth-only culture an unreliable screening test. We recommend that broth-only culture results be carefully scrutinized and decisions on the diagnosis and treatment of infection should be based specifically on the Musculoskeletal Infection Society criteria. Level IV, diagnostic study. See Instructions for Authors for a complete description of levels of evidence.

Prediction of response factors for gas chromatography with flame ionization detection: Algorithm improvement, extension to silylated compounds, and application to the quantification of metabolites

PubMed Central

de Saint Laumer, Jean‐Yves; Leocata, Sabine; Tissot, Emeline; Baroux, Lucie; Kampf, David M.; Merle, Philippe; Boschung, Alain; Seyfried, Markus

2015-01-01

We previously showed that the relative response factors of volatile compounds were predictable from either combustion enthalpies or their molecular formulae only 1. We now extend this prediction to silylated derivatives by adding an increment in the ab initio calculation of combustion enthalpies. The accuracy of the experimental relative response factors database was also improved and its population increased to 490 values. In particular, more brominated compounds were measured, and their prediction accuracy was improved by adding a correction factor in the algorithm. The correlation coefficient between predicted and measured values increased from 0.936 to 0.972, leading to a mean prediction accuracy of ± 6%. Thus, 93% of the relative response factors values were predicted with an accuracy of better than ± 10%. The capabilities of the extended algorithm are exemplified by (i) the quick and accurate quantification of hydroxylated metabolites resulting from a biodegradation test after silylation and prediction of their relative response factors, without having the reference substances available; and (ii) the rapid purity determinations of volatile compounds. This study confirms that Gas chromatography with a flame ionization detector and using predicted relative response factors is one of the few techniques that enables quantification of volatile compounds without calibrating the instrument with the pure reference substance. PMID:26179324

Gene expression programming approach for the estimation of moisture ratio in herbal plants drying with vacuum heat pump dryer

NASA Astrophysics Data System (ADS)

Dikmen, Erkan; Ayaz, Mahir; Gül, Doğan; Şahin, Arzu Şencan

2017-07-01

The determination of drying behavior of herbal plants is a complex process. In this study, gene expression programming (GEP) model was used to determine drying behavior of herbal plants as fresh sweet basil, parsley and dill leaves. Time and drying temperatures are input parameters for the estimation of moisture ratio of herbal plants. The results of the GEP model are compared with experimental drying data. The statistical values as mean absolute percentage error, root-mean-squared error and R-square are used to calculate the difference between values predicted by the GEP model and the values actually observed from the experimental study. It was found that the results of the GEP model and experimental study are in moderately well agreement. The results have shown that the GEP model can be considered as an efficient modelling technique for the prediction of moisture ratio of herbal plants.

Type I and II β-turns prediction using NMR chemical shifts.

PubMed

Wang, Ching-Cheng; Lai, Wen-Chung; Chuang, Woei-Jer

2014-07-01

A method for predicting type I and II β-turns using nuclear magnetic resonance (NMR) chemical shifts is proposed. Isolated β-turn chemical-shift data were collected from 1,798 protein chains. One-dimensional statistical analyses on chemical-shift data of three classes β-turn (type I, II, and VIII) showed different distributions at four positions, (i) to (i + 3). Considering the central two residues of type I β-turns, the mean values of Cο, Cα, H(N), and N(H) chemical shifts were generally (i + 1) > (i + 2). The mean values of Cβ and Hα chemical shifts were (i + 1) < (i + 2). The distributions of the central two residues in type II and VIII β-turns were also distinguishable by trends of chemical shift values. Two-dimensional cluster analyses on chemical-shift data show positional distributions more clearly. Based on these propensities of chemical shift classified as a function of position, rules were derived using scoring matrices for four consecutive residues to predict type I and II β-turns. The proposed method achieves an overall prediction accuracy of 83.2 and 84.2% with the Matthews correlation coefficient values of 0.317 and 0.632 for type I and II β-turns, indicating that its higher accuracy for type II turn prediction. The results show that it is feasible to use NMR chemical shifts to predict the β-turn types in proteins. The proposed method can be incorporated into other chemical-shift based protein secondary structure prediction methods.

A novel model to predict gas-phase hydroxyl radical oxidation kinetics of polychlorinated compounds.

PubMed

Luo, Shuang; Wei, Zongsu; Spinney, Richard; Yang, Zhihui; Chai, Liyuan; Xiao, Ruiyang

2017-04-01

In this study, a novel model based on aromatic meta-substituent grouping was presented to predict the second-order rate constants (k) for OH oxidation of PCBs in gas-phase. Since the oxidation kinetics are dependent on the chlorination degree and position, we hypothesized that it may be more accurate for k value prediction if we group PCB congeners based on substitution positions (i.e., ortho (o), meta (m), and para (p)). To test this hypothesis, we examined the correlation of polarizability (α), a quantum chemical based descriptor for k values, with an empirical Hammett constant (σ + ) on each substitution position. Our result shows that α is highly linearly correlated to ∑σ o,m,p + based on aromatic meta-substituents leading to the grouping based predictive model. With the new model, the calculated k values exhibited an excellent agreement with experimental measurements, and greater predictive power than the quantum chemical based quantitative structure activity relationship (QSAR) model. Further, the relationship of α and ∑σ o,m,p + for PCDDs congeners, together with highest occupied molecular orbital (HOMO) distribution, were used to validate the aromatic meta-substituent grouping method. This newly developed model features a combination of good predictability of quantum chemical based QSAR model and simplicity of Hammett relationship, showing a great potential for fast and computational tractable prediction of k values for gas-phase OH oxidation of polychlorinated compounds. Copyright © 2017 Elsevier Ltd. All rights reserved.

Technical note: A linear model for predicting δ13 Cprotein.

PubMed

Pestle, William J; Hubbe, Mark; Smith, Erin K; Stevenson, Joseph M

2015-08-01

Development of a model for the prediction of δ(13) Cprotein from δ(13) Ccollagen and Δ(13) Cap-co . Model-generated values could, in turn, serve as "consumer" inputs for multisource mixture modeling of paleodiet. Linear regression analysis of previously published controlled diet data facilitated the development of a mathematical model for predicting δ(13) Cprotein (and an experimentally generated error term) from isotopic data routinely generated during the analysis of osseous remains (δ(13) Cco and Δ(13) Cap-co ). Regression analysis resulted in a two-term linear model (δ(13) Cprotein (%) = (0.78 × δ(13) Cco ) - (0.58× Δ(13) Cap-co ) - 4.7), possessing a high R-value of 0.93 (r(2)  = 0.86, P < 0.01), and experimentally generated error terms of ±1.9% for any predicted individual value of δ(13) Cprotein . This model was tested using isotopic data from Formative Period individuals from northern Chile's Atacama Desert. The model presented here appears to hold significant potential for the prediction of the carbon isotope signature of dietary protein using only such data as is routinely generated in the course of stable isotope analysis of human osseous remains. These predicted values are ideal for use in multisource mixture modeling of dietary protein source contribution. © 2015 Wiley Periodicals, Inc.

The Value of Geriatric Assessments in Predicting Treatment Tolerance and All-Cause Mortality in Older Patients With Cancer

PubMed Central

Vos, Alinda G.; Smorenburg, Carolien H.; de Rooij, Sophia E.; van Munster, Barbara C.

2012-01-01

Background. Awareness of the use of geriatric assessments for older patients with cancer is increasing. The aim of this review is to summarize all available evidence on the association between geriatric assessments and relevant oncologic outcomes. Method. A systematic search was conducted in Medline and Embase of studies on geriatric assessment in oncology, focusing on the association between baseline assessment and outcome. Results. The literature search identified 2008 reports; 51 publications from 37 studies were selected for inclusion in the review. The quality of studies was heterogeneous and generally poor. A median of five geriatric conditions were assessed per study (interquartile range: 4–8). Little consistency was found in the results of the studies. Furthermore, different tools appear to be predictive depending on the outcome measure: frailty, nutritional status, and comorbidity assessed by the Cumulative Illness Rating Scale for Geriatrics were predictive for all-cause mortality; frailty was predictive for toxicity of chemotherapy; cognitive impairment and activities of daily living impairment were predictive for chemotherapy completion; and instrumental activities of daily living impairment was predictive for perioperative complications. Conclusion. Although various geriatric conditions appear to be of some value in predicting outcome in elderly patients with cancer, the results are too inconsistent to guide treatment decisions. Further research is needed to elucidate the role of geriatric assessments in the oncologic decision-making process for these patients. PMID:22941970

Prediction of intramuscular fat content and major fatty acid groups of lamb M. longissimus lumborum using Raman spectroscopy.

PubMed

Fowler, Stephanie M; Ponnampalam, Eric N; Schmidt, Heinar; Wynn, Peter; Hopkins, David L

2015-12-01

A hand held Raman spectroscopic device was used to predict intramuscular fat (IMF) levels and the major fatty acid (FA) groups of fresh intact ovine M. longissimus lumborum (LL). IMF levels were determined using the Soxhlet method, while FA analysis was conducted using a rapid (KOH in water, methanol and sulphuric acid in water) extraction procedure. IMF levels and FA values were regressed against Raman spectra using partial least squares regression and against each other using linear regression. The results indicate that there is potential to predict PUFA (R(2)=0.93) and MUFA (R(2)=0.54) as well as SFA values that had been adjusted for IMF content (R(2)=0.54). However, this potential was significantly reduced when correlations between predicted and observed values were determined by cross validation (R(2)cv=0.21-0.00). Overall, the prediction of major FA groups using Raman spectra was more precise (relative reductions in error of 0.3-40.8%) compared to the null models. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

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.

Falls Risk Prediction for Older Inpatients in Acute Care Medical Wards: Is There an Interest to Combine an Early Nurse Assessment and the Artificial Neural Network Analysis?

PubMed

Beauchet, O; Noublanche, F; Simon, R; Sekhon, H; Chabot, J; Levinoff, E J; Kabeshova, A; Launay, C P

2018-01-01

Identification of the risk of falls is important among older inpatients. This study aims to examine performance criteria (i.e.; sensitivity, specificity, positive predictive value, negative predictive value and accuracy) for fall prediction resulting from a nurse assessment and an artificial neural networks (ANNs) analysis in older inpatients hospitalized in acute care medical wards. A total of 848 older inpatients (mean age, 83.0±7.2 years; 41.8% female) admitted to acute care medical wards in Angers University hospital (France) were included in this study using an observational prospective cohort design. Within 24 hours after admission of older inpatients, nurses performed a bedside clinical assessment. Participants were separated into non-fallers and fallers (i.e.; ≥1 fall during hospitalization stay). The analysis was conducted using three feed forward ANNs (multilayer perceptron [MLP], averaged neural network, and neuroevolution of augmenting topologies [NEAT]). Seventy-three (8.6%) participants fell at least once during their hospital stay. ANNs showed a high specificity, regardless of which ANN was used, and the highest value reported was with MLP (99.8%). In contrast, sensitivity was lower, with values ranging between 98.4 to 14.8%. MLP had the highest accuracy (99.7). Performance criteria for fall prediction resulting from a bedside nursing assessment and an ANNs analysis was associated with a high specificity but a low sensitivity, suggesting that this combined approach should be used more as a diagnostic test than a screening test when considering older inpatients in acute care medical ward.

Classification of drug molecules considering their IC50 values using mixed-integer linear programming based hyper-boxes method.

PubMed

Armutlu, Pelin; Ozdemir, Muhittin E; Uney-Yuksektepe, Fadime; Kavakli, I Halil; Turkay, Metin

2008-10-03

A priori analysis of the activity of drugs on the target protein by computational approaches can be useful in narrowing down drug candidates for further experimental tests. Currently, there are a large number of computational methods that predict the activity of drugs on proteins. In this study, we approach the activity prediction problem as a classification problem and, we aim to improve the classification accuracy by introducing an algorithm that combines partial least squares regression with mixed-integer programming based hyper-boxes classification method, where drug molecules are classified as low active or high active regarding their binding activity (IC50 values) on target proteins. We also aim to determine the most significant molecular descriptors for the drug molecules. We first apply our approach by analyzing the activities of widely known inhibitor datasets including Acetylcholinesterase (ACHE), Benzodiazepine Receptor (BZR), Dihydrofolate Reductase (DHFR), Cyclooxygenase-2 (COX-2) with known IC50 values. The results at this stage proved that our approach consistently gives better classification accuracies compared to 63 other reported classification methods such as SVM, Naïve Bayes, where we were able to predict the experimentally determined IC50 values with a worst case accuracy of 96%. To further test applicability of this approach we first created dataset for Cytochrome P450 C17 inhibitors and then predicted their activities with 100% accuracy. Our results indicate that this approach can be utilized to predict the inhibitory effects of inhibitors based on their molecular descriptors. This approach will not only enhance drug discovery process, but also save time and resources committed.

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

Diagnostic accuracy of quantitative real-time PCR assay versus clinical and Gram stain identification of bacterial vaginosis.

PubMed

Menard, J-P; Mazouni, C; Fenollar, F; Raoult, D; Boubli, L; Bretelle, F

2010-12-01

The purpose of this investigation was to determine the diagnostic accuracy of quantitative real-time polymerase chain reaction (PCR) assay in diagnosing bacterial vaginosis versus the standard methods, the Amsel criteria and the Nugent score. The Amsel criteria, the Nugent score, and results from the molecular tool were obtained independently from vaginal samples of 163 pregnant women who reported abnormal vaginal symptoms before 20 weeks gestation. To determine the performance of the molecular tool, we calculated the kappa value, sensitivity, specificity, and positive and negative predictive values. Either or both of the Amsel criteria (≥3 criteria) and the Nugent score (score ≥7) indicated that 25 women (15%) had bacterial vaginosis, and the remaining 138 women did not. DNA levels of Gardnerella vaginalis or Atopobium vaginae exceeded 10(9) copies/mL or 10(8) copies/mL, respectively, in 34 (21%) of the 163 samples. Complete agreement between both reference methods and high concentrations of G. vaginalis and A. vaginae was found in 94.5% of women (154/163 samples, kappa value = 0.81, 95% confidence interval 0.70-0.81). The nine samples with discordant results were categorized as intermediate flora by the Nugent score. The molecular tool predicted bacterial vaginosis with a sensitivity of 100%, a specificity of 93%, a positive predictive value of 73%, and a negative predictive value of 100%. The quantitative real-time PCR assay shows excellent agreement with the results of both reference methods for the diagnosis of bacterial vaginosis.

Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach—A Case Study for the City of Wuhan in China

PubMed Central

Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

2017-01-01

Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study—simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan. PMID:28617348

Structural features that predict real-value fluctuations of globular proteins.

PubMed

Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

2012-05-01

It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics (MD) trajectories of nonhomologous proteins as references and examined static structural features of proteins that are most relevant to fluctuations. We examined correlation of individual structural features with fluctuations and further investigated effective combinations of features for predicting the real value of residue fluctuations using the support vector regression (SVR). It was found that some structural features have higher correlation than crystallographic B-factors with fluctuations observed in MD trajectories. Moreover, SVR that uses combinations of static structural features showed accurate prediction of fluctuations with an average Pearson's correlation coefficient of 0.669 and a root mean square error of 1.04 Å. This correlation coefficient is higher than the one observed in predictions by the Gaussian network model (GNM). An advantage of the developed method over the GNMs is that the former predicts the real value of fluctuation. The results help improve our understanding of relationships between protein structure and fluctuation. Furthermore, the developed method provides a convienient practial way to predict fluctuations of proteins using easily computed static structural features of proteins. Copyright © 2012 Wiley Periodicals, Inc.

Structural features that predict real-value fluctuations of globular proteins

PubMed Central

Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

2012-01-01

It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics trajectories of non-homologous proteins as references and examined static structural features of proteins that are most relevant to fluctuations. We examined correlation of individual structural features with fluctuations and further investigated effective combinations of features for predicting the real-value of residue fluctuations using the support vector regression. It was found that some structural features have higher correlation than crystallographic B-factors with fluctuations observed in molecular dynamics trajectories. Moreover, support vector regression that uses combinations of static structural features showed accurate prediction of fluctuations with an average Pearson’s correlation coefficient of 0.669 and a root mean square error of 1.04 Å. This correlation coefficient is higher than the one observed for the prediction by the Gaussian network model. An advantage of the developed method over the Gaussian network models is that the former predicts the real-value of fluctuation. The results help improve our understanding of relationships between protein structure and fluctuation. Furthermore, the developed method provides a convienient practial way to predict fluctuations of proteins using easily computed static structural features of proteins. PMID:22328193

Moral Attitudes Predict Cheating and Gamesmanship Behaviors Among Competitive Tennis Players

PubMed Central

Lucidi, Fabio; Zelli, Arnaldo; Mallia, Luca; Nicolais, Giampaolo; Lazuras, Lambros; Hagger, Martin S.

2017-01-01

Background: The present study tested Lee et al.’s (2008) model of moral attitudes and cheating behavior in sports in an Italian sample of young tennis players and extended it to predict behavior in actual match play. In the first phase of the study we proposed that moral, competence and status values would predict prosocial and antisocial moral attitudes directly, and indirectly through athletes’ goal orientations. In the second phase, we hypothesized that moral attitudes would directly predict actual cheating behavior observed during match play. Method: Adolescent competitive tennis players (N = 314, 76.75% males, M age = 14.36 years, SD = 1.50) completed measures of values, goal orientations, and moral attitudes. A sub-sample (n = 90) was observed in 45 competitive tennis matches by trained observers who recorded their cheating and gamesmanship behaviors on a validated checklist. Results: Consistent with hypotheses, athletes’ values predicted their moral attitudes through the effects of goal orientations. Anti-social attitudes directly predicted cheating behavior in actual match play providing support for a direct link between moral attitude and actual behavior. Conclusion: The present study findings support key propositions of Lee and colleagues’ model, and extended its application to competitive athletes in actual match play. PMID:28446891

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

USGS Publications Warehouse

Hoos, Anne B.; Patel, Anant R.

1996-01-01

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

OPR-PPR, a Computer Program for Assessing Data Importance to Model Predictions Using Linear Statistics

USGS Publications Warehouse

Tonkin, Matthew J.; Tiedeman, Claire; Ely, D. Matthew; Hill, Mary C.

2007-01-01

The OPR-PPR program calculates the Observation-Prediction (OPR) and Parameter-Prediction (PPR) statistics that can be used to evaluate the relative importance of various kinds of data to simulated predictions. The data considered fall into three categories: (1) existing observations, (2) potential observations, and (3) potential information about parameters. The first two are addressed by the OPR statistic; the third is addressed by the PPR statistic. The statistics are based on linear theory and measure the leverage of the data, which depends on the location, the type, and possibly the time of the data being considered. For example, in a ground-water system the type of data might be a head measurement at a particular location and time. As a measure of leverage, the statistics do not take into account the value of the measurement. As linear measures, the OPR and PPR statistics require minimal computational effort once sensitivities have been calculated. Sensitivities need to be calculated for only one set of parameter values; commonly these are the values estimated through model calibration. OPR-PPR can calculate the OPR and PPR statistics for any mathematical model that produces the necessary OPR-PPR input files. In this report, OPR-PPR capabilities are presented in the context of using the ground-water model MODFLOW-2000 and the universal inverse program UCODE_2005. The method used to calculate the OPR and PPR statistics is based on the linear equation for prediction standard deviation. Using sensitivities and other information, OPR-PPR calculates (a) the percent increase in the prediction standard deviation that results when one or more existing observations are omitted from the calibration data set; (b) the percent decrease in the prediction standard deviation that results when one or more potential observations are added to the calibration data set; or (c) the percent decrease in the prediction standard deviation that results when potential information on one or more parameters is added.

Predictive value of stroke discharge diagnoses in the Danish National Patient Register.

PubMed

Lühdorf, Pernille; Overvad, Kim; Schmidt, Erik B; Johnsen, Søren P; Bach, Flemming W

2017-08-01

To determine the positive predictive values for stroke discharge diagnoses, including subarachnoidal haemorrhage, intracerebral haemorrhage and cerebral infarction in the Danish National Patient Register. Participants in the Danish cohort study Diet, Cancer and Health with a stroke discharge diagnosis in the National Patient Register between 1993 and 2009 were identified and their medical records were retrieved for validation of the diagnoses. A total of 3326 records of possible cases of stroke were reviewed. The overall positive predictive value for stroke was 69.3% (95% confidence interval (CI) 67.8-70.9%). The predictive values differed according to hospital characteristics, with the highest predictive value of 87.8% (95% CI 85.5-90.1%) found in departments of neurology and the lowest predictive value of 43.0% (95% CI 37.6-48.5%) found in outpatient clinics. The overall stroke diagnosis in the Danish National Patient Register had a limited predictive value. We therefore recommend the critical use of non-validated register data for research on stroke. The possibility of optimising the predictive values based on more advanced algorithms should be considered.

Early prediction of blonanserin response in Japanese patients with schizophrenia

PubMed Central

Kishi, Taro; Matsuda, Yuki; Fujita, Kiyoshi; Iwata, Nakao

2014-01-01

Background Blonanserin is a second-generation antipsychotic used for the treatment of schizophrenia in Japan and Korea. The present study aimed to examine early prediction of blonanserin in patients with schizophrenia. Methods An 8-week, prospective, single-arm, flexible-dose clinical trial of blonanserin in patients with schizophrenia was conducted under real-world conditions. The inclusion criteria were antipsychotic naïve, and first-episode schizophrenia patients or schizophrenia patients with no consumption of any antipsychotic medication for more than 4 weeks before enrollment in this study. The positive predictive value, negative predictive value, sensitivity, specificity, and predictive power were calculated for the response status at week 4 to predict the subsequent response at week 8. Results Thirty-seven patients were recruited (56.8% of them had first-episode schizophrenia), and 28 (75.7%) completed the trial. At week 8, blonanserin was associated with a significant improvement in the Positive and Negative Syndrome Scale (PANSS) total score (P<0.0001) and in positive (P<0.0001), negative (P<0.0001), and general subscale scores (P<0.0001). In terms of percentage improvement of PANSS total scores from baseline to week 8, 64.9% of patients showed a ≥20% reduction in the PANSS total score and 48.6% showed a ≥30% reduction. However, 8.1% of patients experienced at least one adverse event. Using the 20% reduction in the PANSS total score at week 4 as a definition of an early response, the negative predictive values for later responses (ie, reductions of ≥30 and ≥40 in the PANSS total scores) were 88.9% and 94.1%, respectively. The specificities were 80.0% and 51.6%, respectively. Conclusion Our results suggest that the blonanserin response at week 4 could predict the later response at week 8. PMID:25285009

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

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.

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.

Clinical Decision Support Model to Predict Occlusal Force in Bruxism Patients

PubMed Central

Thanathornwong, Bhornsawan

2017-01-01

Objectives The aim of this study was to develop a decision support model for the prediction of occlusal force from the size and color of articulating paper markings in bruxism patients. Methods We used the information from the datasets of 30 bruxism patients in which digital measurements of the size and color of articulating paper markings (12-µm Hanel; Coltene/Whaledent GmbH, Langenau, Germany) on canine protected hard stabilization splints were measured in pixels (P) and in red (R), green (G), and blue (B) values using Adobe Photoshop software (Adobe Systems, San Jose, CA, USA). The occlusal force (F) was measured using T-Scan III (Tekscan Inc., South Boston, MA, USA). The multiple regression equation was applied to predict F from the P and RGB. Model evaluation was performed using the datasets from 10 new patients. The patient's occlusal force measured by T-Scan III was used as a ‘gold standard’ to compare with the occlusal force predicted by the multiple regression model. Results The results demonstrate that the correlation between the occlusal force and the pixels and RGB of the articulating paper markings was positive (F = 1.62×P + 0.07×R –0.08×G + 0.08×B + 4.74; R2 = 0.34). There was a high degree of agreement between the occlusal force of the patient measured using T-Scan III and the occlusal force predicted by the model (kappa value = 0.82). Conclusions The results obtained demonstrate that the multiple regression model can predict the occlusal force using the digital values for the size and color of the articulating paper markings in bruxism patients. PMID:29181234

Application of the migration models implemented in the decision system MOIRA-PLUS to assess the long term behaviour of (137)Cs in water and fish of the Baltic Sea.

PubMed

Monte, Luigi

2014-08-01

This work presents and discusses the results of an application of the contaminant migration models implemented in the decision support system MOIRA-PLUS to simulate the time behaviour of the concentrations of (137)Cs of Chernobyl origin in water and fish of the Baltic Sea. The results of the models were compared with the extensive sets of highly reliable empirical data of radionuclide contamination available from international databases and covering a period of, approximately, twenty years. The model application involved three main phases: a) the customisation performed by using hydrological, morphometric and water circulation data obtained from the literature; b) a blind test of the model results, in the sense that the models made use of default values of the migration parameters to predict the dynamics of the contaminant in the environmental components; and c) the adjustment of the model parameter values to improve the agreement of the predictions with the empirical data. The results of the blind test showed that the models successfully predicted the empirical contamination values within the expected range of uncertainty of the predictions (confidence level at 68% of approximately a factor 2). The parameter adjustment can be helpful for the assessment of the fluxes of water circulating among the main sub-basins of the Baltic Sea, substantiating the usefulness of radionuclides to trace the movement of masses of water in seas. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

PubMed

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

2016-04-01

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

Evaluation of Sanofi Diagnostics Pasteur Chlamydia Microplate EIA shortened assay and comparison with cell culture and Syva Chlamydia MicroTrak II EIA in high- and low-risk populations.

PubMed

Chan, E L; Brandt, K; Horsman, G

1995-11-01

Seven hundred thirty-two female urogenital samples were collected for Chlamydia trachomatis testing by both the Sanofi Diagnostics Pasteur (Chaska, Minn.) Chlamydia Microplate EIA by the shortened protocol and the Syva (San Jose, Calif.) MicroTrak II EIA, and the results were compared with those obtained by cell culture. For the analysis of samples from female patients, the patients were divided into high- and low-risk categories. An additional 121 male urethral samples were collected and tested by the Sanofi Microplate EIA and cell culture; for the analysis of samples from male patients, the patients were divided into asymptomatic and symptomatic categories. All specimens positive by enzyme immunoassay (EIA) were confirmed by a blocking assay following the respective manufacturer's instructions. Specimens negative by EIA that fell within a gray zone 30% below the cutoff and negative cultures with one or more corresponding positive EIA results were tested further by cytocentrifugation and direct immunofluorescent assay. The overall sensitivity, specificity, positive predictive value, and negative predictive value for Syva versus culture were 94, 98.8, 85.5 and 99.6%, respectively. After resolution, the results were 94.5, 99.6, 94.5, and 99.6%, respectively. The parallel results for the Sanofi Microplate EIA versus culture were 94.0, 98.7, and 83.9, and 99.6%, respectively, and after being resolved, the results were 94.9, 100, 100, and 99.6%, respectively. In the small male population tested, the resolved results of the Sanofi Microplate EIA versus culture demonstrated sensitivity, specificity, positive predictive value, and negative predictive value of 100, 100, 100, and 100%, respectively. The present study demonstrated that the Sanofi Microplate EIA shortened protocol is highly sensitive and specific in comparison with cell culture and the Syva MicroTrak II EIA.

Added value of delayed computed tomography angiography in primary intracranial hemorrhage and hematoma size for predicting spot sign.

PubMed

Wu, Te Chang; Chen, Tai Yuan; Shiue, Yow Ling; Chen, Jeon Hor; Hsieh, Tsyh-Jyi; Ko, Ching Chung; Lin, Ching Po

2018-04-01

Background The computed tomography angiography (CTA) spot sign represents active contrast extravasation within acute primary intracerebral hemorrhage (ICH) and is an independent predictor of hematoma expansion (HE) and poor clinical outcomes. The spot sign could be detected on first-pass CTA (fpCTA) or delayed CTA (dCTA). Purpose To investigate the additional benefits of dCTA spot sign in primary ICH and hematoma size for predicting spot sign. Material and Methods This is a retrospective study of 100 patients who underwent non-contrast CT (NCCT) and CTA within 24 h of onset of primary ICH. The presence of spot sign on fpCTA or dCTA, and hematoma size on NCCT were recorded. The spot sign on fpCTA or dCTA for predicting significant HE, in-hospital mortality, and poor clinical outcomes (mRS ≥ 4) are calculated. The hematoma size for prediction of CTA spot sign was also analyzed. Results Only the spot sign on dCTA could predict high risk of significant HE and poor clinical outcomes as on fpCTA ( P < 0.05). With dCTA, there is increased sensitivity and negative predictive value (NPV) for predicting significant HE, in-hospital mortality, and poor clinical outcomes. The XY value (product of the two maximum perpendicular axial dimensions) is the best predictor (area under the curve [AUC] = 0.82) for predicting spot sign on fpCTA or dCTA in the absence of intraventricular and subarachnoid hemorrhage. Conclusion This study clarifies that dCTA imaging could improve predictive performance of CTA in primary ICH. Furthermore, the XY value is the best predictor for CTA spot sign.

Finite-Temperature Behavior of PdH x Elastic Constants Computed by Direct Molecular Dynamics

DOE PAGES

Zhou, X. W.; Heo, T. W.; Wood, B. C.; ...

2017-05-30

In this paper, robust time-averaged molecular dynamics has been developed to calculate finite-temperature elastic constants of a single crystal. We find that when the averaging time exceeds a certain threshold, the statistical errors in the calculated elastic constants become very small. We applied this method to compare the elastic constants of Pd and PdH 0.6 at representative low (10 K) and high (500 K) temperatures. The values predicted for Pd match reasonably well with ultrasonic experimental data at both temperatures. In contrast, the predicted elastic constants for PdH 0.6 only match well with ultrasonic data at 10 K; whereas, atmore » 500 K, the predicted values are significantly lower. We hypothesize that at 500 K, the facile hydrogen diffusion in PdH 0.6 alters the speed of sound, resulting in significantly reduced values of predicted elastic constants as compared to the ultrasonic experimental data. Finally, literature mechanical testing experiments seem to support this hypothesis.« less

Progress in the prediction of pKa values in proteins

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

Alexov, Emil; Mehler, Ernest L.; Baker, Nathan A.

2011-12-15

The pKa-cooperative aims to provide a forum for experimental and theoretical researchers interested in protein pKa values and protein electrostatics in general. The first round of the pKa -cooperative, which challenged computational labs to carry out blind predictions against pKas experimentally determined in the laboratory of Bertrand Garcia-Moreno, was completed and results discussed at the Telluride meeting (July 6-10, 2009). This paper serves as an introduction to the reports submitted by the blind prediction participants that will be published in a special issue of PROTEINS: Structure, Function and Bioinformatics. Here we briefly outline existing approaches for pKa calculations, emphasizing methodsmore » that were used by the participants in calculating the blind pKa values in the first round of the cooperative. We then point out some of the difficulties encountered by the participating groups in making their blind predictions, and finally try to provide some insights for future developments aimed at improving the accuracy of pKa calculations.« less

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.

Quality Evaluation of Shelled and Unshelled Macadamia Nuts by Means of Near-Infrared Spectroscopy (NIR).

PubMed

Canneddu, Giovanna; Júnior, Luis Carlos Cunha; de Almeida Teixeira, Gustavo Henrique

2016-07-01

The quality of shelled and unshelled macadamia nuts was assessed by means of Fourier transformed near-infrared (FT-NIR) spectroscopy. Shelled macadamia nuts were sorted as sound nuts; nuts infected by Ecdytolopha aurantiana and Leucopteara coffeella; and cracked nuts caused by germination. Unshelled nuts were sorted as intact nuts (<10% half nuts, 2014); half nuts (March, 2013; November, 2013); and crushed nuts (2014). Peroxide value (PV) and acidity index (AI) were determined according to AOAC. PCA-LDA shelled macadamia nuts classification resulted in 93.2% accurate classification. PLS PV prediction model resulted in a square error of prediction (SEP) of 3.45 meq/kg, and a prediction coefficient determination value (Rp (2) ) of 0.72. The AI PLS prediction model was better (SEP = 0.14%, Rp (2) = 0.80). Although adequate classification was possible (93.2%), shelled nuts must not contain live insects, therefore the classification accuracy was not satisfactory. FT-NIR spectroscopy can be successfully used to predict PV and AI in unshelled macadamia nuts, though. © 2016 Institute of Food Technologists®

Improvement of Quench Factor Analysis in Phase and Hardness Prediction of a Quenched Steel

NASA Astrophysics Data System (ADS)

Kianezhad, M.; Sajjadi, S. A.

2013-05-01

The accurate prediction of alloys' properties introduced by heat treatment has been considered by many researchers. The advantages of such predictions are reduction of test trails and materials' consumption as well as time and energy saving. One of the most important methods to predict hardness in quenched steel parts is Quench Factor Analysis (QFA). Classical QFA is based on the Johnson-Mehl-Avrami-Kolmogorov (JMAK) equation. In this study, a modified form of the QFA based on the work by Rometsch et al. is compared with the classical QFA, and they are applied to prediction of hardness of steels. For this purpose, samples of CK60 steel were utilized as raw material. They were austenitized at 1103 K (830 °C). After quenching in different environments, they were cut and their hardness was determined. In addition, the hardness values of the samples were fitted using the classical and modified equations for the quench factor analysis and the results were compared. Results showed a significant improvement in fitted values of the hardness and proved the higher efficiency of the new method.

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.

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.

Study of Vis/NIR spectroscopy measurement on acidity of yogurt

NASA Astrophysics Data System (ADS)

He, Yong; Feng, Shuijuan; Wu, Di; Li, Xiaoli

2006-09-01

A fast measurement of pH of yogurt using Vis/NIR-spectroscopy techniques was established in order to measuring the acidity of yogurt rapidly. 27 samples selected separately from five different brands of yogurt were measured by Vis/NIR-spectroscopy. The pH of yogurt on positions scanned by spectrum was measured by a pH meter. The mathematical model between pH and Vis/NIR spectral measurements was established and developed based on partial least squares (PLS) by using Unscramble V9.2. Then 25 unknown samples from 5 different brands were predicted based on the mathematical model. The result shows that The correlation coefficient of pH based on PLS model is more than 0.890, and standard error of calibration (SEC) is 0.037, standard error of prediction (SEP) is 0.043. Through predicting the pH of 25 samples of yogurt from 5 different brands, the correlation coefficient between predictive value and measured value of those samples is more than 0918. The results show the good to excellent prediction performances. The Vis/NIR spectroscopy technique had a significant greater accuracy for determining the value of pH. It was concluded that the VisINIRS measurement technique can be used to measure pH of yogurt fast and accurately, and a new method for the measurement of pH of yogurt was established.

Improved in silico prediction of carcinogenic potency (TD50) and the risk specific dose (RSD) adjusted Threshold of Toxicological Concern (TTC) for genotoxic chemicals and pharmaceutical impurities.

PubMed

Contrera, Joseph F

2011-02-01

The Threshold of Toxicological Concern (TTC) is a level of exposure to a genotoxic impurity that is considered to represent a negligible risk to humans. The TTC was derived from the results of rodent carcinogenicity TD50 values that are a measure of carcinogenic potency. The TTC currently sets a default limit of 1.5 μg/day in food contact substances and pharmaceuticals for all genotoxic impurities without carcinogenicity data. Bercu et al. (2010) used the QSAR predicted TD50 to calculate a risk specific dose (RSD) which is a carcinogenic potency adjusted TTC for genotoxic impurities. This promising approach is currently limited by the software used, a combination of MC4PC (www.multicase.com) and a Lilly Inc. in-house software (VISDOM) that is not available to the public. In this report the TD50 and RSD were predicted using a commercially available software, SciQSAR (formally MDL-QSAR, www.scimatics.com) employing the same TD50 training data set and external validation test set that was used by Bercu et al. (2010). The results demonstrate the general applicability of QSAR predicted TD50 values to determine the RSDs for genotoxic impurities and the improved performance of SciQSAR for predicting TD50 values. Copyright © 2010 Elsevier Inc. All rights reserved.

Artificial neural network models for prediction of cardiovascular autonomic dysfunction in general Chinese population

PubMed Central

2013-01-01

Background The present study aimed to develop an artificial neural network (ANN) based prediction model for cardiovascular autonomic (CA) dysfunction in the general population. Methods We analyzed a previous dataset based on a population sample consisted of 2,092 individuals aged 30–80 years. The prediction models were derived from an exploratory set using ANN analysis. Performances of these prediction models were evaluated in the validation set. Results Univariate analysis indicated that 14 risk factors showed statistically significant association with CA dysfunction (P < 0.05). The mean area under the receiver-operating curve was 0.762 (95% CI 0.732–0.793) for prediction model developed using ANN analysis. The mean sensitivity, specificity, positive and negative predictive values were similar in the prediction models was 0.751, 0.665, 0.330 and 0.924, respectively. All HL statistics were less than 15.0. Conclusion ANN is an effective tool for developing prediction models with high value for predicting CA dysfunction among the general population. PMID:23902963

Early pregnancy factor as a marker for assessing embryonic viability in threatened and missed abortions.

PubMed

Shahani, S K; Moniz, C L; Bordekar, A D; Gupta, S M; Naik, K

1994-01-01

It is now well recognized that the presence of early pregnancy factor (EPF) can signify the occurrence of fertilization, continuation of pregnancy and the existence of a viable embryo. With this in view, a study was undertaken to observe the potential of EPF as a marker in assessing embryo viability in cases complicated with vaginal bleeding during early pregnancy. The results indicated that the sensitivity of EPF as a marker in predicting threatened or missed abortion was 78.9% and the specificity 95.6%. The positive predictive value was observed to be 93.8% and the negative predictive value 84.6%. Our studies have shown that since EPF is present in viable but absent in non-viable pregnancies, it could be a useful marker of prognostic value in threatened abortions.

Foundations for computer simulation of a low pressure oil flooded single screw air compressor

NASA Astrophysics Data System (ADS)

Bein, T. W.

1981-12-01

The necessary logic to construct a computer model to predict the performance of an oil flooded, single screw air compressor is developed. The geometric variables and relationships used to describe the general single screw mechanism are developed. The governing equations to describe the processes are developed from their primary relationships. The assumptions used in the development are also defined and justified. The computer model predicts the internal pressure, temperature, and flowrates through the leakage paths throughout the compression cycle of the single screw compressor. The model uses empirical external values as the basis for the internal predictions. The computer values are compared to the empirical values, and conclusions are drawn based on the results. Recommendations are made for future efforts to improve the computer model and to verify some of the conclusions that are drawn.

Prognostic value of blood interleukin-6 in the prediction of functional outcome after stroke: a systematic review and meta-analysis.

PubMed

Bustamante, Alejandro; Sobrino, Tomás; Giralt, Dolors; García-Berrocoso, Teresa; Llombart, Victor; Ugarriza, Iratxe; Espadaler, Marc; Rodríguez, Noelia; Sudlow, Cathie; Castellanos, Mar; Smith, Craig J; Rodríguez-Yánez, Manuel; Waje-Andreassen, Ulrike; Tanne, David; Oto, Jun; Barber, Mark; Worthmann, Hans; Wartenberg, Katja E; Becker, Kyra J; Chakraborty, Baidarbhi; Oh, Seung-Hun; Whiteley, William N; Castillo, José; Montaner, Joan

2014-09-15

We aimed to quantify the association of blood interleukin-6 (IL-6) concentrations with poor outcome after stroke and its added predictive value over clinical information. Meta-analysis of 24 studies confirmed this association with a weighted mean difference of 3.443 (1.592-5.294) pg/mL, despite high heterogeneity and publication bias. Individual participant data including 4112 stroke patients showed standardized IL-6 levels in the 4th quartile were independently associated with poor outcome (OR=2.346 (1.814-3.033), p<0.0001). However, the additional predictive value of IL-6 was moderate (IDI=1.5%, NRI=5.35%). Overall these results indicate an unlikely translation of IL-6 into clinical practice for this purpose. Copyright © 2014 Elsevier B.V. All rights reserved.

Using Artificial Neural Networks to Predict the Presence of Overpressured Zones in the Anadarko Basin, Oklahoma

NASA Astrophysics Data System (ADS)

Cranganu, Constantin

2007-10-01

Many sedimentary basins throughout the world exhibit areas with abnormal pore-fluid pressures (higher or lower than normal or hydrostatic pressure). Predicting pore pressure and other parameters (depth, extension, magnitude, etc.) in such areas are challenging tasks. The compressional acoustic (sonic) log (DT) is often used as a predictor because it responds to changes in porosity or compaction produced by abnormal pore-fluid pressures. Unfortunately, the sonic log is not commonly recorded in most oil and/or gas wells. We propose using an artificial neural network to synthesize sonic logs by identifying the mathematical dependency between DT and the commonly available logs, such as normalized gamma ray (GR) and deep resistivity logs (REID). The artificial neural network process can be divided into three steps: (1) Supervised training of the neural network; (2) confirmation and validation of the model by blind-testing the results in wells that contain both the predictor (GR, REID) and the target values (DT) used in the supervised training; and 3) applying the predictive model to all wells containing the required predictor data and verifying the accuracy of the synthetic DT data by comparing the back-predicted synthetic predictor curves (GRNN, REIDNN) to the recorded predictor curves used in training (GR, REID). Artificial neural networks offer significant advantages over traditional deterministic methods. They do not require a precise mathematical model equation that describes the dependency between the predictor values and the target values and, unlike linear regression techniques, neural network methods do not overpredict mean values and thereby preserve original data variability. One of their most important advantages is that their predictions can be validated and confirmed through back-prediction of the input data. This procedure was applied to predict the presence of overpressured zones in the Anadarko Basin, Oklahoma. The results are promising and encouraging.

The predictive value of haemodynamic parameters for outcome of deep venous reconstructions in patients with chronic deep vein obstruction - A systematic review.

PubMed

Kurstjens, Rlm; de Wolf, Maf; Kleijnen, J; de Graaf, R; Wittens, Cha

2017-09-01

Objective The aim of this study was to investigate the predictive value of haemodynamic parameters on success of stenting or bypass surgery in patients with non-thrombotic or post-thrombotic deep venous obstruction. Methods EMBASE, MEDLINE and trial registries were searched up to 5 February 2016. Studies needed to investigate stenting or bypass surgery in patients with post-thrombotic obstruction or stenting for non-thrombotic iliac vein compression. Haemodynamic data needed to be available with prognostic analysis for success of treatment. Two authors, independently, selected studies and extracted data with risk bias assessment using the Quality in Prognosis Studies tool. Results Two studies using stenting and two using bypass surgery were included. Three investigated plethysmography, though results varied and confounding was not properly taken into account. Dorsal foot vein pressure and venous refill times appeared to be of influence in one study, though confounding by deep vein incompetence was likely. Another investigated femoral-central pressure gradients without finding statistical significance, though sample size was small without details on statistical methodology. Reduced femoral inflow was found to be a predictor for stent stenosis or occlusion in one study, though patients also received additional surgery to improve stent inflow. Data on prediction of haemodynamic parameters for stenting of non-thrombotic iliac vein compression were not available. Conclusions Data on the predictive value of haemodynamic parameters for success of treatment in deep venous obstructive disease are scant and of poor quality. Plethysmography does not seem to be of value in predicting outcome of stenting or bypass surgery in post-thrombotic disease. The relevance of pressure-related parameters is unclear. Reduced flow into the common femoral vein seems to be predictive for in-stent stenosis or occlusion. Further research into the predictive effect of haemodynamic parameters is warranted and the possibility of developing new techniques that evaluate various haemodynamic aspects should be explored.

Dynamic divisive normalization predicts time-varying value coding in decision-related circuits.

PubMed

Louie, Kenway; LoFaro, Thomas; Webb, Ryan; Glimcher, Paul W

2014-11-26

Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. Copyright © 2014 the authors 0270-6474/14/3416046-12$15.00/0.

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.

A comparison of the performance of threshold criteria for binary classification in terms of predicted prevalence and Kappa

Treesearch

Elizabeth A. Freeman; Gretchen G. Moisen

2008-01-01

Modelling techniques used in binary classification problems often result in a predicted probability surface, which is then translated into a presence - absence classification map. However, this translation requires a (possibly subjective) choice of threshold above which the variable of interest is predicted to be present. The selection of this threshold value can have...

Prediction of atmospheric degradation data for POPs by gene expression programming.

PubMed

Luan, F; Si, H Z; Liu, H T; Wen, Y Y; Zhang, X Y

2008-01-01

Quantitative structure-activity relationship models for the prediction of the mean and the maximum atmospheric degradation half-life values of persistent organic pollutants were developed based on the linear heuristic method (HM) and non-linear gene expression programming (GEP). Molecular descriptors, calculated from the structures alone, were used to represent the characteristics of the compounds. HM was used both to pre-select the whole descriptor sets and to build the linear model. GEP yielded satisfactory prediction results: the square of the correlation coefficient r(2) was 0.80 and 0.81 for the mean and maximum half-life values of the test set, and the root mean square errors were 0.448 and 0.426, respectively. The results of this work indicate that the GEP is a very promising tool for non-linear approximations.

Method and system for early detection of incipient faults in electric motors

DOEpatents

Parlos, Alexander G; Kim, Kyusung

2003-07-08

A method and system for early detection of incipient faults in an electric motor are disclosed. First, current and voltage values for one or more phases of the electric motor are measured during motor operations. A set of current predictions is then determined via a neural network-based current predictor based on the measured voltage values and an estimate of motor speed values of the electric motor. Next, a set of residuals is generated by combining the set of current predictions with the measured current values. A set of fault indicators is subsequently computed from the set of residuals and the measured current values. Finally, a determination is made as to whether or not there is an incipient electrical, mechanical, and/or electromechanical fault occurring based on the comparison result of the set of fault indicators and a set of predetermined baseline values.

Physical discipline in Chinese American immigrant families: An adaptive culture perspective.

PubMed

Lau, Anna S

2010-07-01

Research on ethnic minority parenting has examined heritage cultural influences and contextual stressors on parenting processes. However, rarely are adaptive cultural processes considered, whereby ethnic minority parents bring their cultural values to bear in adapting to contextual demands in the host society. A survey of 107 Chinese American immigrant parents examined whether use of physical discipline can be predicted by cultural values, contextual stressors, and their interactions. Results indicated that distinct domains of cultural values were related to physical discipline in disparate ways, with some values decreasing risk and others indirectly increasing risk. There was some evidence that cultural values interacted with contextual stress to predict physical discipline. Parent-child acculturation conflicts were only related to physical discipline when parents held strong values about the importance of firm parental control. The findings illustrate how heritage cultural influences and current ecological demands may converge to shape parenting in immigrant families.

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

PubMed

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

2014-04-01

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

Diagnostic accuracy of uriSed automated urine microscopic sediment analyzer and dipstick parameters in predicting urine culture test results.

PubMed

Huysal, Kağan; Budak, Yasemin U; Karaca, Ayse Ulusoy; Aydos, Murat; Kahvecioğlu, Serdar; Bulut, Mehtap; Polat, Murat

2013-01-01

Urinary tract infection (UTI) is one of the most common types of infection. Currently, diagnosis is primarily based on microbiologic culture, which is time- and labor-consuming. The aim of this study was to assess the diagnostic accuracy of urinalysis results from UriSed (77 Electronica, Budapest, Hungary), an automated microscopic image-based sediment analyzer, in predicting positive urine cultures. We examined a total of 384 urine specimens from hospitalized patients and outpatients attending our hospital on the same day for urinalysis, dipstick tests and semi-quantitative urine culture. The urinalysis results were compared with those of conventional semiquantitative urine culture. Of 384 urinary specimens, 68 were positive for bacteriuria by culture, and were thus considered true positives. Comparison of these results with those obtained from the UriSed analyzer indicated that the analyzer had a specificity of 91.1%, a sensitivity of 47.0%, a positive predictive value (PPV) of 53.3% (95% confidence interval (CI) = 40.8-65.3), and a negative predictive value (NPV) of 88.8% (95% CI = 85.0-91.8%). The accuracy was 83.3% when the urine leukocyte parameter was used, 76.8% when bacteriuria analysis of urinary sediment was used, and 85.1% when the bacteriuria and leukocyturia parameters were combined. The presence of nitrite was the best indicator of culture positivity (99.3% specificity) but had a negative likelihood ratio of 0.7, indicating that it was not a reliable clinical test. Although the specificity of the UriSed analyzer was within acceptable limits, the sensitivity value was low. Thus, UriSed urinalysis resuIts do not accurately predict the outcome of culture.

Long-enduring primary hepatocyte-based co-cultures improve prediction of hepatotoxicity.

PubMed

Novik, Eric I; Dwyer, Jacquelyn; Morelli, James K; Parekh, Amit; Cho, Cheul; Pludwinski, Eitan; Shrirao, Anil; Freedman, Robert M; MacDonald, James S; Jayyosi, Zaid

2017-12-01

The failure of drug candidates during clinical trials and post-marketing withdrawal due to Drug Induced Liver Injury (DILI), results in significant late-stage attrition in the pharmaceutical industry. Animal studies have proven insufficient to definitively predict DILI in the clinic, therefore a variety of in vitro models are being tested in an effort to improve prediction of human hepatotoxicity. The model system described here consists of cryopreserved primary rat, dog or human hepatocytes co-cultured together with a fibroblast cell line, which aids in the hepatocytes' maintenance of more in vivo-like characteristics compared to traditional hepatic mono-cultures, including long term viability and retention of activity of cytochrome P450 isozymes. Cell viability was assessed by measurement of ATP following treatment with 29 compounds having known hepatotoxic liabilities. Hμrelrat™, Hμreldog™, and Hμrelhuman™ hepatic co-cultures were treated for 24h, or under repeat-dosing for 7 or 13days, and compared to rat and human hepatic mono-cultures following single-dose exposure for 24h. The results allowed for a comparison of cytotoxicity, species-specific responses and the effect of repeat compound exposure on the prediction of hepatotoxic potential in each model. Results show that the co-culture model had greater sensitivity compared to that of the hepatic mono-cultures. In addition, "time-based ratios" were determined by dividing the compounds' 24-hour TC 50 /C max values by TC 50 /C max values measured after dosing for either 7 or 13days. The results suggest that this approach may serve as a useful adjunct to traditional measurements of hepatotoxicity, improving the predictive value of early screening studies. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Predicting gaseous emissions from small-scale combustion of agricultural biomass fuels.

PubMed

Fournel, S; Marcos, B; Godbout, S; Heitz, M

2015-03-01

A prediction model of gaseous emissions (CO, CO2, NOx, SO2 and HCl) from small-scale combustion of agricultural biomass fuels was developed in order to rapidly assess their potential to be burned in accordance to current environmental threshold values. The model was established based on calculation of thermodynamic equilibrium of reactive multicomponent systems using Gibbs free energy minimization. Since this method has been widely used to estimate the composition of the syngas from wood gasification, the model was first validated by comparing its prediction results with those of similar models from the literature. The model was then used to evaluate the main gas emissions from the combustion of four dedicated energy crops (short-rotation willow, reed canary grass, switchgrass and miscanthus) previously burned in a 29-kW boiler. The prediction values revealed good agreement with the experimental results. The model was particularly effective in estimating the influence of harvest season on SO2 emissions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Development of wavelet-ANN models to predict water quality parameters in Hilo Bay, Pacific Ocean.

PubMed

Alizadeh, Mohamad Javad; Kavianpour, Mohamad Reza

2015-09-15

The main objective of this study is to apply artificial neural network (ANN) and wavelet-neural network (WNN) models for predicting a variety of ocean water quality parameters. In this regard, several water quality parameters in Hilo Bay, Pacific Ocean, are taken under consideration. Different combinations of water quality parameters are applied as input variables to predict daily values of salinity, temperature and DO as well as hourly values of DO. The results demonstrate that the WNN models are superior to the ANN models. Also, the hourly models developed for DO prediction outperform the daily models of DO. For the daily models, the most accurate model has R equal to 0.96, while for the hourly model it reaches up to 0.98. Overall, the results show the ability of the model to monitor the ocean parameters, in condition with missing data, or when regular measurement and monitoring are impossible. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dopamine neurons learn relative chosen value from probabilistic rewards

PubMed Central

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

2016-01-01

Economic theories posit reward probability as one of the factors defining reward value. Individuals learn the value of cues that predict probabilistic rewards from experienced reward frequencies. Building on the notion that responses of dopamine neurons increase with reward probability and expected value, we asked how dopamine neurons in monkeys acquire this value signal that may represent an economic decision variable. We found in a Pavlovian learning task that reward probability-dependent value signals arose from experienced reward frequencies. We then assessed neuronal response acquisition during choices among probabilistic rewards. Here, dopamine responses became sensitive to the value of both chosen and unchosen options. Both experiments showed also the novelty responses of dopamine neurones that decreased as learning advanced. These results show that dopamine neurons acquire predictive value signals from the frequency of experienced rewards. This flexible and fast signal reflects a specific decision variable and could update neuronal decision mechanisms. DOI: http://dx.doi.org/10.7554/eLife.18044.001 PMID:27787196

Evaluation of approaches for estimating the accuracy of genomic prediction in plant breeding

PubMed Central

2013-01-01

Background In genomic prediction, an important measure of accuracy is the correlation between the predicted and the true breeding values. Direct computation of this quantity for real datasets is not possible, because the true breeding value is unknown. Instead, the correlation between the predicted breeding values and the observed phenotypic values, called predictive ability, is often computed. In order to indirectly estimate predictive accuracy, this latter correlation is usually divided by an estimate of the square root of heritability. In this study we use simulation to evaluate estimates of predictive accuracy for seven methods, four (1 to 4) of which use an estimate of heritability to divide predictive ability computed by cross-validation. Between them the seven methods cover balanced and unbalanced datasets as well as correlated and uncorrelated genotypes. We propose one new indirect method (4) and two direct methods (5 and 6) for estimating predictive accuracy and compare their performances and those of four other existing approaches (three indirect (1 to 3) and one direct (7)) with simulated true predictive accuracy as the benchmark and with each other. Results The size of the estimated genetic variance and hence heritability exerted the strongest influence on the variation in the estimated predictive accuracy. Increasing the number of genotypes considerably increases the time required to compute predictive accuracy by all the seven methods, most notably for the five methods that require cross-validation (Methods 1, 2, 3, 4 and 6). A new method that we propose (Method 5) and an existing method (Method 7) used in animal breeding programs were the fastest and gave the least biased, most precise and stable estimates of predictive accuracy. Of the methods that use cross-validation Methods 4 and 6 were often the best. Conclusions The estimated genetic variance and the number of genotypes had the greatest influence on predictive accuracy. Methods 5 and 7 were the fastest and produced the least biased, the most precise, robust and stable estimates of predictive accuracy. These properties argue for routinely using Methods 5 and 7 to assess predictive accuracy in genomic selection studies. PMID:24314298

Quantification, Prediction, and the Online Impact of Sentence Truth-Value: Evidence From Event-Related Potentials

PubMed Central

2015-01-01

Do negative quantifiers like “few” reduce people’s ability to rapidly evaluate incoming language with respect to world knowledge? Previous research has addressed this question by examining whether online measures of quantifier comprehension match the “final” interpretation reflected in verification judgments. However, these studies confounded quantifier valence with its impact on the unfolding expectations for upcoming words, yielding mixed results. In the current event-related potentials study, participants read negative and positive quantifier sentences matched on cloze probability and on truth-value (e.g., “Most/Few gardeners plant their flowers during the spring/winter for best results”). Regardless of whether participants explicitly verified the sentences or not, true-positive quantifier sentences elicited reduced N400s compared with false-positive quantifier sentences, reflecting the facilitated semantic retrieval of words that render a sentence true. No such facilitation was seen in negative quantifier sentences. However, mixed-effects model analyses (with cloze value and truth-value as continuous predictors) revealed that decreasing cloze values were associated with an interaction pattern between truth-value and quantifier, whereas increasing cloze values were associated with more similar truth-value effects regardless of quantifier. Quantifier sentences are thus understood neither always in 2 sequential stages, nor always in a partial-incremental fashion, nor always in a maximally incremental fashion. Instead, and in accordance with prediction-based views of sentence comprehension, quantifier sentence comprehension depends on incorporation of quantifier meaning into an online, knowledge-based prediction for upcoming words. Fully incremental quantifier interpretation occurs when quantifiers are incorporated into sufficiently strong online predictions for upcoming words. PMID:26375784

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...

Evaluation of the WinROP system for identifying retinopathy of prematurity in Czech preterm infants.

PubMed

Timkovic, Juraj; Pokryvkova, Martina; Janurova, Katerina; Barinova, Denisa; Polackova, Renata; Masek, Petr

2017-03-01

Retinopathy of Prematurity (ROP) is a potentially serious condition that can afflict preterm infants. Timely and correct identification of individuals at risk of developing a serious form of ROP is therefore of paramount importance. WinROP is an online system for predicting ROP based on birth weight and weight increments. However, the results vary significantly for various populations. It has not been evaluated in the Czech population. This study evaluates the test characteristics (specificity, sensitivity, positive and negative predictive values) of the WinROP system in Czech preterm infants. Data on 445 prematurely born infants included in the ROP screening program at the University Hospital Ostrava, Czech Republic, were retrospectively entered into the WinROP system and the outcomes of the WinROP and regular screening were compared. All 24 infants who developed high-risk (Type 1 or Type 2) ROP were correctly identified by the system. The sensitivity and negative predictive values for this group were 100%. However, the specificity and positive predictive values were substantially lower, resulting in a large number of false positives. Extending the analysis to low risk ROP, the system did not provide such reliable results. The system is a valuable tool for identifying infants who are not likely to develop high-risk ROP and this could help to substantially reduce the number of preterm infants in need of regular ROP screening. It is not suitable for predicting the development of less serious forms of ROP which is however in accordance with the declared aims of the WinROP system.

The Accuracy of Urinalysis in Predicting Intra-Abdominal Injury Following Blunt Traumas.

PubMed

Sabzghabaei, Anita; Shojaee, Majid; Safari, Saeed; Hatamabadi, Hamid Reza; Shirvani, Reza

2016-01-01

In cases of blunt abdominal traumas, predicting the possible intra-abdominal injuries is still a challenge for the physicians involved with these patients. Therefore, this study was designed, to evaluate the accuracy of urinalysis in predicting intra-abdominal injuries. Patients aged 15 to 65 years with blunt abdominal trauma who were admitted to emergency departments were enrolled. Abdominopelvic computed tomography (CT) scan with intravenous contrast and urinalysis were requested for all the included patients. Demographic data, trauma mechanism, the results of urinalysis, and the results of abdominopelvic CT scan were gathered. Finally, the correlation between the results of abdominopelvic CT scan, and urinalysis was determined. Urinalysis was considered positive in case of at least one positive value in gross appearance, blood in dipstick, or red blood cell count. 325 patients with blunt abdominal trauma were admitted to the emergency departments (83% male with the mean age of 32.63±17.48 years). Sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios of urinalysis, were 77.9% (95% CI: 69.6-84.4), 58.5% (95% CI: 51.2-65.5), 56% (95% CI: 48.5-63.3), 79.6% (95% CI: 71.8-85.7), 1.27% (95% CI: 1.30-1.57), and 0.25% (95% CI: 0.18-0.36), respectively. The diagnostic value of urinalysis in prediction of blunt traumatic intra-abdominal injuries is low and it seems that it should be considered as an adjuvant diagnostic tool, in conjunction with other sources such as clinical findings and imaging.

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

Comparison of bronchoalveolar lavage cytology and transbronchial biopsy in the diagnosis of carcinoma of lung.

PubMed

Ahmed, Ayesha; Ahmed, Sajjad

2004-01-01

The objectives of this study were to compare bronchoalveolar lavage (BAL) cytology and transbronchial biopsy in the diagnosis of carcinoma lung and to determine accuracy of BAL cytology using histopathlologic examination of transbronchial biopsy as gold standard at our center. This study was carried out at Department of Histopathology, Ayub Medical College, Abbottabad, from 1.09.2000 to 28.02.2003. BAL fluid and bronchial biopsy were received and processed simultaneously. Four cytology and a set of histopathology slides were prepared. These were screened and diagnosis recorded. Sensitivity, Specificity, False Positive, False Negative, Positive predictive value and Negative predictive value of BAL cytology were determined using histopathology of transbronchial biopsy as gold standard. We found the sensitivity of BAL cytology to be 93.44% as compared with transbronchial biopsy. The specificity was 100%. There was no false positive while false negative results were 6.55 %. The positive predictive value was 100 %, while the negative predictive value was 75 %. The overall diagnostic efficacy of BAL cytology was 94.52 %. BAL cytology is a highly sensitive and specific test for diagnosis of carcinoma lung. It can be used as a quick and reliable diagnostic method for diagnosis of lung malignancy.

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.

Evaluation of a Mysis bioenergetics model

USGS Publications Warehouse

Chipps, S.R.; Bennett, D.H.

2002-01-01

Direct approaches for estimating the feeding rate of the opossum shrimp Mysis relicta can be hampered by variable gut residence time (evacuation rate models) and non-linear functional responses (clearance rate models). Bioenergetics modeling provides an alternative method, but the reliability of this approach needs to be evaluated using independent measures of growth and food consumption. In this study, we measured growth and food consumption for M. relicta and compared experimental results with those predicted from a Mysis bioenergetics model. For Mysis reared at 10??C, model predictions were not significantly different from observed values. Moreover, decomposition of mean square error indicated that 70% of the variation between model predictions and observed values was attributable to random error. On average, model predictions were within 12% of observed values. A sensitivity analysis revealed that Mysis respiration and prey energy density were the most sensitive parameters affecting model output. By accounting for uncertainty (95% CLs) in Mysis respiration, we observed a significant improvement in the accuracy of model output (within 5% of observed values), illustrating the importance of sensitive input parameters for model performance. These findings help corroborate the Mysis bioenergetics model and demonstrate the usefulness of this approach for estimating Mysis feeding rate.

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.

FPGA implementation of predictive degradation model for engine oil lifetime

NASA Astrophysics Data System (ADS)

Idros, M. F. M.; Razak, A. H. A.; Junid, S. A. M. Al; Suliman, S. I.; Halim, A. K.

2018-03-01

This paper presents the implementation of linear regression model for degradation prediction on Register Transfer Logic (RTL) using QuartusII. A stationary model had been identified in the degradation trend for the engine oil in a vehicle in time series method. As for RTL implementation, the degradation model is written in Verilog HDL and the data input are taken at a certain time. Clock divider had been designed to support the timing sequence of input data. At every five data, a regression analysis is adapted for slope variation determination and prediction calculation. Here, only the negative value are taken as the consideration for the prediction purposes for less number of logic gate. Least Square Method is adapted to get the best linear model based on the mean values of time series data. The coded algorithm has been implemented on FPGA for validation purposes. The result shows the prediction time to change the engine oil.

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.

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.

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

PubMed Central

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

2012-01-01

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

Relationships among values, achievement orientations, and attitudes in youth sport.

PubMed

Lee, Martin J; Whitehead, Jean; Ntoumanis, Nikos; Hatzigeorgiadis, Antonis

2008-10-01

This research examines the value-expressive function of attitudes and achievement goal theory in predicting moral attitudes. In Study 1, the Youth Sport Values Questionnaire (YSVQ; Lee, Whitehead, & Balchin, 2000) was modified to measure moral, competence, and status values. In Study 2, structural equation modeling on data from 549 competitors (317 males, 232 females) aged 12-15 years showed that moral and competence values predicted prosocial attitudes, whereas moral (negatively) and status values (positively) predicted antisocial attitudes. Competence and status values predicted task and ego orientation, respectively, and task and ego orientation partially mediated the effect of competence values on prosocial attitudes and of status values on antisocial attitudes, respectively. The role of sport values is discussed, and new research directions are proposed.

Linear array ultrasonography to stage rectal neoplasias suitable for local treatment.

PubMed

Ravizza, Davide; Tamayo, Darina; Fiori, Giancarla; Trovato, Cristina; De Roberto, Giuseppe; de Leone, Annalisa; Crosta, Cristiano

2011-08-01

Because of the many therapeutic options available, a reliable staging is crucial for rectal neoplasia management. Adenomas and cancers limited to the submucosa without lymph node involvement may be treated locally. The aim of this study is to evaluate the diagnostic accuracy of endorectal ultrasonography in the staging of neoplasias suitable for local treatment. We considered all patients who underwent endorectal ultrasonography between 2001 and 2010. The study population consisted of 92 patients with 92 neoplasias (68 adenocarcinomas and 24 adenomas). A 5 and 7.5MHz linear array echoendoscope was used. The postoperative histopathologic result was compared with the preoperative staging defined by endorectal ultrasonography. Adenomas and cancers limited to the submucosa were considered together (pT0-1). The sensitivity, specificity, overall accuracy rate, positive predictive value, and negative predictive value of endorectal ultrasonography for pT0-1 were 86%, 95.6%, 91.3%, 94.9% and 88.7%. Those for nodal involvement were 45.4%, 95.5%, 83%, 76.9% and 84%, with 3 false positive results and 12 false negative. For combined pT0-1 and pN0, endorectal ultrasonography showed an 87.5% sensitivity, 95.9% specificity, 92% overall accuracy rate, 94.9% positive predictive value and 90.2% negative predictive value. Endorectal linear array ultrasonography is a reliable tool to detect rectal neoplasias suitable for local treatment. Copyright © 2011 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

Value of a negative aeroallergen skin-prick test result in the diagnosis of asthma in young adults: correlative study with methacholine challenge testing.

PubMed

Graif, Yael; Yigla, Mordechai; Tov, Naveh; Kramer, Mordechai R

2002-09-01

None of the existing tests for the diagnosis of asthma are considered to be definitive. Certain circumstances require prompt diagnosis, and a test able to predict the absence of asthma would be very useful. To evaluate the contribution of a skin-prick test (SPT) to the diagnostic workup of subjects with suspected asthma. The study included three groups of subjects aged 18 to 24 years: group A, asthmatic patients (n = 175); group B, control subjects (n = 100); and group C, subjects with suspected asthma (n = 150) with normal spirometry findings and a negative exercise challenge test result. All underwent an SPT to a battery of common aeroallergens, and group C underwent a methacholine challenge test (MCT) in addition. The sensitivity, specificity, positive predictive value, and negative predictive values (NPV) of the SPT were calculated using provocative concentrations of methacholine causing a 20% fall in FEV(1) (PC(20)) of < 4 mg/mL and < 8 mg/mL as diagnostic cutoff values for asthma in the MCT. Bayes' formula was used to determine posttest probabilities of having asthma, both for positive and negative SPT results. A positive SPT result to at least one allergen was found in 95.5%, 54%, and 69% of patients in the three groups, respectively. The sensitivity, specificity, and NPV of the SPT were 90.7%, 52.0%, and 84.8%, respectively, with a cutoff value of PC(20) < 8 mg/mL. The lower cutoff, PC(20) < 4 mg/mL, increased the sensitivity and NPV to 98.2% and 97.8%, respectively. A negative SPT result decreased the probability of having asthma by 10-fold to 20-fold in subjects whose pretest probability was low to moderate. Incorporating an SPT into the workup of subjects with suspected asthma can reduce the cost of this process significantly. The SPT may be used as a simple, fast, safe, inexpensive, and reliable method to predict the absence of asthma in young adults.

Establishing a sample-to cut-off ratio for lab-diagnosis of hepatitis C virus in Indian context.

PubMed

Tiwari, Aseem K; Pandey, Prashant K; Negi, Avinash; Bagga, Ruchika; Shanker, Ajay; Baveja, Usha; Vimarsh, Raina; Bhargava, Richa; Dara, Ravi C; Rawat, Ganesh

2015-01-01

Lab-diagnosis of hepatitis C virus (HCV) is based on detecting specific antibodies by enzyme immuno-assay (EIA) or chemiluminescence immuno-assay (CIA). Center for Disease Control reported that signal-to-cut-off (s/co) ratios in anti-HCV antibody tests like EIA/CIA can be used to predict the probable result of supplemental test; above a certain s/co value it is most likely to be true-HCV positive result and below that certain s/co it is most likely to be false-positive result. A prospective study was undertaken in patients in tertiary care setting for establishing this "certain" s/co value. The study was carried out in consecutive patients requiring HCV testing for screening/diagnosis and medical management. These samples were tested for anti-HCV on CIA (VITROS(®) Anti-HCV assay, Ortho-Clinical Diagnostics, New Jersey) for calculating s/co value. The supplemental nucleic acid test used was polymerase chain reaction (PCR) (Abbott). PCR test results were used to define true negatives, false negatives, true positives, and false positives. Performance of different putative s/co ratios versus PCR was measured using sensitivity, specificity, positive predictive value and negative predictive value and most appropriate s/co was considered on basis of highest specificity at sensitivity of at least 95%. An s/co ratio of ≥6 worked out to be over 95% sensitive and almost 92% specific in 438 consecutive patient samples tested. The s/co ratio of six can be used for lab-diagnosis of HCV infection; those with s/co higher than six can be diagnosed to have HCV infection without any need for supplemental assays.

Cardiothoracic ratio for prediction of left ventricular dilation: a systematic review and pooled analysis.

PubMed

Loomba, Rohit S; Shah, Parinda H; Nijhawan, Karan; Aggarwal, Saurabh; Arora, Rohit

2015-03-01

Increased cardiothoracic ratio noted on chest radiographs often prompts concern and further evaluation with additional imaging. This study pools available data assessing the utility of cardiothoracic ratio in predicting left ventricular dilation. A systematic review of the literature was conducted to identify studies comparing cardiothoracic ratio by chest x-ray to left ventricular dilation by echocardiography. Electronic databases were used to identify studies which were then assessed for quality and bias, with those with adequate quality and minimal bias ultimately being included in the pooled analysis. The pooled data were used to determine the sensitivity, specificity, positive predictive value and negative predictive value of cardiomegaly in predicting left ventricular dilation. A total of six studies consisting of 466 patients were included in this analysis. Cardiothoracic ratio had 83.3% sensitivity, 45.4% specificity, 43.5% positive predictive value and 82.7% negative predictive value. When a secondary analysis was conducted with a pediatric study excluded, a total of five studies consisting of 371 patients were included. Cardiothoracic ratio had 86.2% sensitivity, 25.2% specificity, 42.5% positive predictive value and 74.0% negative predictive value. Cardiothoracic ratio as determined by chest radiograph is sensitive but not specific for identifying left ventricular dilation. Cardiothoracic ratio also has a strong negative predictive value for identifying left ventricular dilation.

GEMAS: prediction of solid-solution phase partitioning coefficients (Kd) for oxoanions and boric acid in soils using mid-infrared diffuse reflectance spectroscopy.

PubMed

Janik, Leslie J; Forrester, Sean T; Soriano-Disla, José M; Kirby, Jason K; McLaughlin, Michael J; Reimann, Clemens

2015-02-01

The authors' aim was to develop rapid and inexpensive regression models for the prediction of partitioning coefficients (Kd), defined as the ratio of the total or surface-bound metal/metalloid concentration of the solid phase to the total concentration in the solution phase. Values of Kd were measured for boric acid (B[OH]3(0)) and selected added soluble oxoanions: molybdate (MoO4(2-)), antimonate (Sb[OH](6-)), selenate (SeO4(2-)), tellurate (TeO4(2-)) and vanadate (VO4(3-)). Models were developed using approximately 500 spectrally representative soils of the Geochemical Mapping of Agricultural Soils of Europe (GEMAS) program. These calibration soils represented the major properties of the entire 4813 soils of the GEMAS project. Multiple linear regression (MLR) from soil properties, partial least-squares regression (PLSR) using mid-infrared diffuse reflectance Fourier-transformed (DRIFT) spectra, and models using DRIFT spectra plus analytical pH values (DRIFT + pH), were compared with predicted log K(d + 1) values. Apart from selenate (R(2)  = 0.43), the DRIFT + pH calibrations resulted in marginally better models to predict log K(d + 1) values (R(2)  = 0.62-0.79), compared with those from PSLR-DRIFT (R(2)  = 0.61-0.72) and MLR (R(2)  = 0.54-0.79). The DRIFT + pH calibrations were applied to the prediction of log K(d + 1) values in the remaining 4313 soils. An example map of predicted log K(d + 1) values for added soluble MoO4(2-) in soils across Europe is presented. The DRIFT + pH PLSR models provided a rapid and inexpensive tool to assess the risk of mobility and potential availability of boric acid and selected oxoanions in European soils. For these models to be used in the prediction of log K(d + 1) values in soils globally, additional research will be needed to determine if soil variability is accounted on the calibration. © 2014 SETAC.

Usefulness of the 6-minute walk test as a screening test for pulmonary arterial enlargement in COPD

PubMed Central

Oki, Yutaro; Kaneko, Masahiro; Fujimoto, Yukari; Sakai, Hideki; Misu, Shogo; Mitani, Yuji; Yamaguchi, Takumi; Yasuda, Hisafumi; Ishikawa, Akira

2016-01-01

Purpose Pulmonary hypertension and exercise-induced oxygen desaturation (EID) influence acute exacerbation of COPD. Computed tomography (CT)-detected pulmonary artery (PA) enlargement is independently associated with acute COPD exacerbations. Associations between PA to aorta (PA:A) ratio and EID in patients with COPD have not been reported. We hypothesized that the PA:A ratio correlated with EID and that results of the 6-minute walk test (6MWT) would be useful for predicting the risk associated with PA:A >1. Patients and methods We retrospectively measured lung function, 6MWT, emphysema area, and PA enlargement on CT in 64 patients with COPD. The patients were classified into groups with PA:A ≤1 and >1. Receiver-operating characteristic curves were used to determine the threshold values with the best cutoff points to predict patients with PA:A >1. Results The PA:A >1 group had lower forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FEV1:FVC ratio, diffusion capacity of lung carbon monoxide, 6MW distance, and baseline peripheral oxygen saturation (SpO2), lowest SpO2, highest modified Borg scale results, percentage low-attenuation area, and history of acute COPD exacerbations ≤1 year, and worse BODE (Body mass index, airflow Obstruction, Dyspnea, and Exercise) index results (P<0.05). Predicted PA:A >1 was determined for SpO2 during 6MWT (best cutoff point 89%, area under the curve 0.94, 95% confidence interval 0.88–1). SpO2 <90% during 6MWT showed a sensitivity of 93.1, specificity of 94.3, positive predictive value of 93.1, negative predictive value of 94.3, positive likelihood ratio of 16.2, and negative likelihood ratio of 0.07. Conclusion Lowest SpO2 during 6MWT may predict CT-measured PA:A, and lowest SpO2 <89% during 6MWT is excellent for detecting pulmonary hypertension in COPD. PMID:27920514

A neighborhood statistics model for predicting stream pathogen indicator levels.

PubMed

Pandey, Pramod K; Pasternack, Gregory B; Majumder, Mahbubul; Soupir, Michelle L; Kaiser, Mark S

2015-03-01

Because elevated levels of water-borne Escherichia coli in streams are a leading cause of water quality impairments in the U.S., water-quality managers need tools for predicting aqueous E. coli levels. Presently, E. coli levels may be predicted using complex mechanistic models that have a high degree of unchecked uncertainty or simpler statistical models. To assess spatio-temporal patterns of instream E. coli levels, herein we measured E. coli, a pathogen indicator, at 16 sites (at four different times) within the Squaw Creek watershed, Iowa, and subsequently, the Markov Random Field model was exploited to develop a neighborhood statistics model for predicting instream E. coli levels. Two observed covariates, local water temperature (degrees Celsius) and mean cross-sectional depth (meters), were used as inputs to the model. Predictions of E. coli levels in the water column were compared with independent observational data collected from 16 in-stream locations. The results revealed that spatio-temporal averages of predicted and observed E. coli levels were extremely close. Approximately 66 % of individual predicted E. coli concentrations were within a factor of 2 of the observed values. In only one event, the difference between prediction and observation was beyond one order of magnitude. The mean of all predicted values at 16 locations was approximately 1 % higher than the mean of the observed values. The approach presented here will be useful while assessing instream contaminations such as pathogen/pathogen indicator levels at the watershed scale.

A new approach to measure visual field progression in glaucoma patients using variational bayes linear regression.

PubMed

Murata, Hiroshi; Araie, Makoto; Asaoka, Ryo

2014-11-20

We generated a variational Bayes model to predict visual field (VF) progression in glaucoma patients. This retrospective study included VF series from 911 eyes of 547 glaucoma patients as test data, and VF series from 5049 eyes of 2858 glaucoma patients as training data. Using training data, variational Bayes linear regression (VBLR) was created to predict VF progression. The performance of VBLR was compared against ordinary least-squares linear regression (OLSLR) by predicting VFs in the test dataset. The total deviation (TD) values of test patients' 11th VFs were predicted using TD values from their second to 10th VFs (VF2-10), the root mean squared error (RMSE) associated with each approach then was calculated. Similarly, mean TD (mTD) of test patients' 11th VFs was predicted using VBLR and OLSLR, and the absolute prediction errors compared. The RMSE resulting from VBLR averaged 3.9 ± 2.1 (SD) and 4.9 ± 2.6 dB for prediction based on the second to 10th VFs (VF2-10) and the second to fourth VFs (VF2-4), respectively. The RMSE resulting from OLSLR was 4.1 ± 2.0 (VF2-10) and 19.9 ± 12.0 (VF2-4) dB. The absolute prediction error (SD) for mTD using VBLR was 1.2 ± 1.3 (VF2-10) and 1.9 ± 2.0 (VF2-4) dB, while the prediction error resulting from OLSLR was 1.2 ± 1.3 (VF2-10) and 6.2 ± 6.6 (VF2-4) dB. The VBLR more accurately predicts future VF progression in glaucoma patients compared to conventional OLSLR, especially in short VF series. © ARVO.

Which risk factors are associated with neurosensory deficits of inferior alveolar nerve after mandibular third molar extraction?

PubMed

Kim, Jin-Woo; Cha, In-Ho; Kim, Sun-Jong; Kim, Myung-Rae

2012-11-01

Mandibular third molar extraction is a commonly performed procedure and is recognized as a relatively frequent cause of inferior alveolar nerve (IAN) injury. The aim of the present study was to investigate the specific risk factors for neurosensory deficits, including age, gender, impaction depth, angulation of the third molar, and various radiographic superimposition signs. In a case-control study of patients who had undergone mandibular third molar extraction, a case group was developed of patients showing neurosensory deficits of the IAN, and a control group was formed of randomly selected patients without any neurosensory symptoms. Bivariate analyses were performed to assess the relationship between each variable and IAN injury. A multivariate logistic regression model was used to compute the odds ratios, P values, and predictive values of the radiographic superimposition signs. Of 12,842 total patients, the study group included 104 cases and 135 controls. The results indicated that older age and deeper impaction status were significant risk factors (P < .05). Darkening of the roots, deflection of the roots, narrowing of the roots, dark and bifid apexes of the roots, and narrowing of the canal were also significant risk factors. The positive predictive values ranged from 0.7% to 6.9% and the negative predictive values from 99% to 100%, with adjustment for the definitive prevalence of IAN injury (0.81%, 104/12,842 patients). However, the relatively low positive predictive value renders questionable the predictability of superimposition signs on orthopantomography. In the absence of specific radiographic signs, the risk of neurosensory deficit of the IAN could be negligible. The sensory symptoms disappeared after 6 months in 92.3% of the patients and 98.1% showed recovery after 1 year. The results of the present study have demonstrated a significant association between several risk factors and neurosensory deficits of the IAN after third molar extraction. With a case group of 104 patients, the number of subjects was significantly greater than that in previous studies, increasing the reliability of these results. Copyright © 2012 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

Does exposure to simulated patient cases improve accuracy of clinicians' predictive value estimates of diagnostic test results? A within-subjects experiment at St Michael's Hospital, Toronto, Canada.

PubMed

Armstrong, Bonnie; Spaniol, Julia; Persaud, Nav

2018-02-13

Clinicians often overestimate the probability of a disease given a positive test result (positive predictive value; PPV) and the probability of no disease given a negative test result (negative predictive value; NPV). The purpose of this study was to investigate whether experiencing simulated patient cases (ie, an 'experience format') would promote more accurate PPV and NPV estimates compared with a numerical format. Participants were presented with information about three diagnostic tests for the same fictitious disease and were asked to estimate the PPV and NPV of each test. Tests varied with respect to sensitivity and specificity. Information about each test was presented once in the numerical format and once in the experience format. The study used a 2 (format: numerical vs experience) × 3 (diagnostic test: gold standard vs low sensitivity vs low specificity) within-subjects design. The study was completed online, via Qualtrics (Provo, Utah, USA). 50 physicians (12 clinicians and 38 residents) from the Department of Family and Community Medicine at St Michael's Hospital in Toronto, Canada, completed the study. All participants had completed at least 1 year of residency. Estimation accuracy was quantified by the mean absolute error (MAE; absolute difference between estimate and true predictive value). PPV estimation errors were larger in the numerical format (MAE=32.6%, 95% CI 26.8% to 38.4%) compared with the experience format (MAE=15.9%, 95% CI 11.8% to 20.0%, d =0.697, P<0.001). Likewise, NPV estimation errors were larger in the numerical format (MAE=24.4%, 95% CI 14.5% to 34.3%) than in the experience format (MAE=11.0%, 95% CI 6.5% to 15.5%, d =0.303, P=0.015). Exposure to simulated patient cases promotes accurate estimation of predictive values in clinicians. This finding carries implications for diagnostic training and practice. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

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.

Adolescent-perceived parent and teacher overestimation of mathematics ability: Developmental implications for students' mathematics task values.

PubMed

Gniewosz, Burkhard; Watt, Helen M G

2017-07-01

This study examines whether and how student-perceived parents' and teachers' overestimation of students' own perceived mathematical ability can explain trajectories for adolescents' mathematical task values (intrinsic and utility) controlling for measured achievement, following expectancy-value and self-determination theories. Longitudinal data come from a 3-cohort (mean ages 13.25, 12.36, and 14.41 years; Grades 7-10), 4-wave data set of 1,271 Australian secondary school students. Longitudinal structural equation models revealed positive effects of student-perceived overestimation of math ability by parents and teachers on students' intrinsic and utility math task values development. Perceived parental overestimations predicted intrinsic task value changes between all measurement occasions, whereas utility task value changes only were predicted between Grades 9 and 10. Parental influences were stronger for intrinsic than utility task values. Teacher influences were similar for both forms of task values and commenced after the curricular school transition in Grade 8. Results support the assumptions that the perceived encouragement conveyed by student-perceived mathematical ability beliefs of parents and teachers, promote positive mathematics task values development. Moreover, results point to different mechanisms underlying parents' and teachers' support. Finally, the longitudinal changes indicate transition-related increases in the effects of student-perceived overestimations and stronger effects for intrinsic than utility values. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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.

The metabolic equivalents of one-mile walking by older adults; implications for health promotion

PubMed Central

Gault, Mandy Lucinda; Willems, Mark Elisabeth Theodorus

2017-01-01

Background: Instructions for older adults regarding the intensity of walking may not elicit an intensity to infer health gains. We recorded the metabolic equivalents (METs) during a 1-mile walk using constant and predicted values of resting MET in older adults to establish walking guidelines for health promotion and participation. Methods: In a cross-sectional design study, participants (15 men, 10 women) walked 1-mile overground, in a wooden floored gymnasium, wearing the Cosmed K4b2 for measurement of energy expenditure. Constant or predicted values for resting MET were used to calculate the number of 1-mile walks to meet 450-750 MET∙min∙wk-1. Results: Participants had MET values higher than 3 for both methods, with 29% and 64% of the participants higher than 6 for a constant and predicted MET value, respectively. The METs of the1-mile walk were (mean ± SD) 6 ± 1 and 7 ± 1 METs using constant and predicted resting MET,and similar for men (constant: 6 ± 1 METs; predicted: 7 ± 1 METs) and women (constant: 5±1METs; predicted: 6 ± 1 METs) (P > 0.05). Conclusion: Older adults that are instructed to walk 1-mile at a fast and constant pace meet the minimum required intensity for physical activity, and public health guidelines. Health professionals, that administer exercise, could encourage older adults to accumulate between six and nine 1-mile walks per week for health gains. PMID:29085799

The metabolic equivalents of one-mile walking by older adults; implications for health promotion.

PubMed

Gault, Mandy Lucinda; Willems, Mark Elisabeth Theodorus

2017-01-01

Background: Instructions for older adults regarding the intensity of walking may not elicit an intensity to infer health gains. We recorded the metabolic equivalents (METs) during a 1-mile walk using constant and predicted values of resting MET in older adults to establish walking guidelines for health promotion and participation. Methods: In a cross-sectional design study, participants (15 men, 10 women) walked 1-mile overground, in a wooden floored gymnasium, wearing the Cosmed K4b 2 for measurement of energy expenditure. Constant or predicted values for resting MET were used to calculate the number of 1-mile walks to meet 450-750 MET∙min∙wk -1 . Results: Participants had MET values higher than 3 for both methods, with 29% and 64% of the participants higher than 6 for a constant and predicted MET value, respectively. The METs of the1-mile walk were (mean ± SD) 6 ± 1 and 7 ± 1 METs using constant and predicted resting MET,and similar for men (constant: 6 ± 1 METs; predicted: 7 ± 1 METs) and women (constant: 5±1METs; predicted: 6 ± 1 METs) (P > 0.05). Conclusion: Older adults that are instructed to walk 1-mile at a fast and constant pace meet the minimum required intensity for physical activity, and public health guidelines. Health professionals, that administer exercise, could encourage older adults to accumulate between six and nine 1-mile walks per week for health gains.

Predicting coronary artery disease using different artificial neural network models.

PubMed

Colak, M Cengiz; Colak, Cemil; Kocatürk, Hasan; Sağiroğlu, Seref; Barutçu, Irfan

2008-08-01

Eight different learning algorithms used for creating artificial neural network (ANN) models and the different ANN models in the prediction of coronary artery disease (CAD) are introduced. This work was carried out as a retrospective case-control study. Overall, 124 consecutive patients who had been diagnosed with CAD by coronary angiography (at least 1 coronary stenosis > 50% in major epicardial arteries) were enrolled in the work. Angiographically, the 113 people (group 2) with normal coronary arteries were taken as control subjects. Multi-layered perceptrons ANN architecture were applied. The ANN models trained with different learning algorithms were performed in 237 records, divided into training (n=171) and testing (n=66) data sets. The performance of prediction was evaluated by sensitivity, specificity and accuracy values based on standard definitions. The results have demonstrated that ANN models trained with eight different learning algorithms are promising because of high (greater than 71%) sensitivity, specificity and accuracy values in the prediction of CAD. Accuracy, sensitivity and specificity values varied between 83.63%-100%, 86.46%-100% and 74.67%-100% for training, respectively. For testing, the values were more than 71% for sensitivity, 76% for specificity and 81% for accuracy. It may be proposed that the use of different learning algorithms other than backpropagation and larger sample sizes can improve the performance of prediction. The proposed ANN models trained with these learning algorithms could be used a promising approach for predicting CAD without the need for invasive diagnostic methods and could help in the prognostic clinical decision.

Investigation of Periodic Pitching through the Static Stall Angle of Attack.

DTIC Science & Technology

1987-03-01

been completed to characterize and predict the dynamic stall process. In 1968 Ham (Ref 11) completed a study to explain the torsional oscillation of...peak values of l.:t and moment could be predicted accurately, but the model did not predict when the peaks would occur. Another problem with the...model was that it required input from experimental results to tell when leading edge vortex separation occurred. The prediction of when vortex shedding

Uniting Cheminformatics and Chemical Theory To Predict the Intrinsic Aqueous Solubility of Crystalline Druglike Molecules

PubMed Central

2014-01-01

We present four models of solution free-energy prediction for druglike molecules utilizing cheminformatics descriptors and theoretically calculated thermodynamic values. We make predictions of solution free energy using physics-based theory alone and using machine learning/quantitative structure–property relationship (QSPR) models. We also develop machine learning models where the theoretical energies and cheminformatics descriptors are used as combined input. These models are used to predict solvation free energy. While direct theoretical calculation does not give accurate results in this approach, machine learning is able to give predictions with a root mean squared error (RMSE) of ∼1.1 log S units in a 10-fold cross-validation for our Drug-Like-Solubility-100 (DLS-100) dataset of 100 druglike molecules. We find that a model built using energy terms from our theoretical methodology as descriptors is marginally less predictive than one built on Chemistry Development Kit (CDK) descriptors. Combining both sets of descriptors allows a further but very modest improvement in the predictions. However, in some cases, this is a statistically significant enhancement. These results suggest that there is little complementarity between the chemical information provided by these two sets of descriptors, despite their different sources and methods of calculation. Our machine learning models are also able to predict the well-known Solubility Challenge dataset with an RMSE value of 0.9–1.0 log S units. PMID:24564264

[Predictive factors of contamination in a blood culture with bacterial growth in an Emergency Department].

PubMed

Hernández-Bou, S; Trenchs Sainz de la Maza, V; Esquivel Ojeda, J N; Gené Giralt, A; Luaces Cubells, C

2015-06-01

The aim of this study is to identify predictive factors of bacterial contamination in positive blood cultures (BC) collected in an emergency department. A prospective, observational and analytical study was conducted on febrile children aged on to 36 months, who had no risk factors of bacterial infection, and had a BC collected in the Emergency Department between November 2011 and October 2013 in which bacterial growth was detected. The potential BC contamination predicting factors analysed were: maximum temperature, time to positivity, initial Gram stain result, white blood cell count, absolute neutrophil count, band count, and C-reactive protein (CRP). Bacteria grew in 169 BC. Thirty (17.8%) were finally considered true positives and 139 (82.2%) false positives. All potential BC contamination predicting factors analysed, except maximum temperature, showed significant differences between true positives and false positives. CRP value, time to positivity, and initial Gram stain result are the best predictors of false positives in BC. The positive predictive values of a CRP value≤30mg/L, BC time to positivity≥16h, and initial Gram stain suggestive of a contaminant in predicting a FP, are 95.1, 96.9 and 97.5%, respectively. When all 3 conditions are applied, their positive predictive value is 100%. Four (8.3%) patients with a false positive BC and discharged to home were revaluated in the Emergency Department. The majority of BC obtained in the Emergency Department that showed positive were finally considered false positives. Initial Gram stain, time to positivity, and CRP results are valuable diagnostic tests in distinguishing between true positives and false positives in BC. The early detection of false positives will allow minimising their negative consequences. Copyright © 2014 Asociación Española de Pediatría. Published by Elsevier España, S.L.U. All rights reserved.

Combining 'Bottom-Up' and 'Top-Down' Methods to Assess Ethnic Difference in Clearance: Bitopertin as an Example.

PubMed

Feng, Sheng; Shi, Jun; Parrott, Neil; Hu, Pei; Weber, Cornelia; Martin-Facklam, Meret; Saito, Tomohisa; Peck, Richard

2016-07-01

We propose a strategy for studying ethnopharmacology by conducting sequential physiologically based pharmacokinetic (PBPK) prediction (a 'bottom-up' approach) and population pharmacokinetic (popPK) confirmation (a 'top-down' approach), or in reverse order, depending on whether the purpose is ethnic effect assessment for a new molecular entity under development or a tool for ethnic sensitivity prediction for a given pathway. The strategy is exemplified with bitopertin. A PBPK model was built using Simcyp(®) to simulate the pharmacokinetics of bitopertin and to predict the ethnic sensitivity in clearance, given pharmacokinetic data in just one ethnicity. Subsequently, a popPK model was built using NONMEM(®) to assess the effect of ethnicity on clearance, using human data from multiple ethnic groups. A comparison was made to confirm the PBPK-based ethnic sensitivity prediction, using the results of the popPK analysis. PBPK modelling predicted that the bitopertin geometric mean clearance values after 20 mg oral administration in Caucasians would be 1.32-fold and 1.27-fold higher than the values in Chinese and Japanese, respectively. The ratios of typical clearance in Caucasians to the values in Chinese and Japanese estimated by popPK analysis were 1.20 and 1.17, respectively. The popPK analysis results were similar to the PBPK modelling results. As a general framework, we propose that PBPK modelling should be considered to predict ethnic sensitivity of pharmacokinetics prior to any human data and/or with data in only one ethnicity. In some cases, this will be sufficient to guide initial dose selection in different ethnicities. After clinical trials in different ethnicities, popPK analysis can be used to confirm ethnic differences and to support dose justification and labelling. PBPK modelling prediction and popPK analysis confirmation can complement each other to assess ethnic differences in pharmacokinetics at different drug development stages.

Model Update of a Micro Air Vehicle (MAV) Flexible Wing Frame with Uncertainty Quantification

NASA Technical Reports Server (NTRS)

Reaves, Mercedes C.; Horta, Lucas G.; Waszak, Martin R.; Morgan, Benjamin G.

2004-01-01

This paper describes a procedure to update parameters in the finite element model of a Micro Air Vehicle (MAV) to improve displacement predictions under aerodynamics loads. Because of fabrication, materials, and geometric uncertainties, a statistical approach combined with Multidisciplinary Design Optimization (MDO) is used to modify key model parameters. Static test data collected using photogrammetry are used to correlate with model predictions. Results show significant improvements in model predictions after parameters are updated; however, computed probabilities values indicate low confidence in updated values and/or model structure errors. Lessons learned in the areas of wing design, test procedures, modeling approaches with geometric nonlinearities, and uncertainties quantification are all documented.

Neurobiological factors as predictors of cognitive-behavioral therapy outcome in individuals with antisocial behavior: a review of the literature.

PubMed

Cornet, Liza J M; de Kogel, Catharina H; Nijman, Henk L I; Raine, Adrian; van der Laan, Peter H

2014-11-01

This review focuses on the predictive value of neurobiological factors in relation to cognitive-behavioral therapy outcome among individuals with antisocial behavior. Ten relevant studies were found. Although the literature on this topic is scarce and diverse, it appears that specific neurobiological characteristics, such as physiological arousal levels, can predict treatment outcome. The predictive value of neurobiological factors is important as it could give more insight into the causes of variability in treatment outcome among individuals with antisocial behavior. Furthermore, results can contribute to improvement in current treatment selection procedures and to the development of alternative treatment options. © The Author(s) 2013.

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.

Novel, customizable scoring functions, parameterized using N-PLS, for structure-based drug discovery.

PubMed

Catana, Cornel; Stouten, Pieter F W

2007-01-01

The ability to accurately predict biological affinity on the basis of in silico docking to a protein target remains a challenging goal in the CADD arena. Typically, "standard" scoring functions have been employed that use the calculated docking result and a set of empirical parameters to calculate a predicted binding affinity. To improve on this, we are exploring novel strategies for rapidly developing and tuning "customized" scoring functions tailored to a specific need. In the present work, three such customized scoring functions were developed using a set of 129 high-resolution protein-ligand crystal structures with measured Ki values. The functions were parametrized using N-PLS (N-way partial least squares), a multivariate technique well-known in the 3D quantitative structure-activity relationship field. A modest correlation between observed and calculated pKi values using a standard scoring function (r2 = 0.5) could be improved to 0.8 when a customized scoring function was applied. To mimic a more realistic scenario, a second scoring function was developed, not based on crystal structures but exclusively on several binding poses generated with the Flo+ docking program. Finally, a validation study was conducted by generating a third scoring function with 99 randomly selected complexes from the 129 as a training set and predicting pKi values for a test set that comprised the remaining 30 complexes. Training and test set r2 values were 0.77 and 0.78, respectively. These results indicate that, even without direct structural information, predictive customized scoring functions can be developed using N-PLS, and this approach holds significant potential as a general procedure for predicting binding affinity on the basis of in silico docking.

Evaluation of dual flow thrust vectored nozzles with exhaust stream impingement. MS Thesis Final Technical Report, Oct. 1990 - Jul. 1991

NASA Technical Reports Server (NTRS)

Carpenter, Thomas W.

1991-01-01

The main objective of this project was to predict the expansion wave/oblique shock wave structure in an under-expanded jet expanding from a convergent nozzle. The shock structure was predicted by combining the calculated curvature of the free pressure boundary with principles and governing equations relating to oblique shock wave and expansion wave interaction. The procedure was then continued until the shock pattern repeated itself. A mathematical model was then formulated and written in FORTRAN to calculate the oblique shock/expansion wave structure within the jet. In order to study shock waves in expanding jets, Schlieren photography, a form of flow visualization, was employed. Thirty-six Schlieren photographs of jets from both a straight and 15 degree nozzle were taken. An iterative procedure was developed to calculate the shock structure within the jet and predict the non-dimensional values of Prandtl primary wavelength (w/rn), distance to Mach Disc (Ld) and Mach Disc radius (rd). These values were then compared to measurements taken from Schlieren photographs and experimental results. The results agreed closely to measurements from Schlieren photographs and previously obtained data. This method provides excellent results for pressure ratios below that at which a Mach Disc first forms. Calculated values of non-dimensional distance to the Mach Disc (Ld) agreed closely to values measured from Schlieren photographs and published data. The calculated values of non-dimensional Mach Disc radius (rd), however, deviated from published data by as much as 25 percent at certain pressure ratios.

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.

Automated Pressure Injury Risk Assessment System Incorporated Into an Electronic Health Record System.

PubMed

Jin, Yinji; Jin, Taixian; Lee, Sun-Mi

Pressure injury risk assessment is the first step toward preventing pressure injuries, but traditional assessment tools are time-consuming, resulting in work overload and fatigue for nurses. The objectives of the study were to build an automated pressure injury risk assessment system (Auto-PIRAS) that can assess pressure injury risk using data, without requiring nurses to collect or input additional data, and to evaluate the validity of this assessment tool. A retrospective case-control study and a system development study were conducted in a 1,355-bed university hospital in Seoul, South Korea. A total of 1,305 pressure injury patients and 5,220 nonpressure injury patients participated for the development of a risk scoring algorithm: 687 and 2,748 for the validation of the algorithm and 237 and 994 for validation after clinical implementation, respectively. A total of 4,211 pressure injury-related clinical variables were extracted from the electronic health record (EHR) systems to develop a risk scoring algorithm, which was validated and incorporated into the EHR. That program was further evaluated for predictive and concurrent validity. Auto-PIRAS, incorporated into the EHR system, assigned a risk assessment score of high, moderate, or low and displayed this on the Kardex nursing record screen. Risk scores were updated nightly according to 10 predetermined risk factors. The predictive validity measures of the algorithm validation stage were as follows: sensitivity = .87, specificity = .90, positive predictive value = .68, negative predictive value = .97, Youden index = .77, and the area under the receiver operating characteristic curve = .95. The predictive validity measures of the Braden Scale were as follows: sensitivity = .77, specificity = .93, positive predictive value = .72, negative predictive value = .95, Youden index = .70, and the area under the receiver operating characteristic curve = .85. The kappa of the Auto-PIRAS and Braden Scale risk classification result was .73. The predictive performance of the Auto-PIRAS was similar to Braden Scale assessments conducted by nurses. Auto-PIRAS is expected to be used as a system that assesses pressure injury risk automatically without additional data collection by nurses.

Evaluating a slope-stability model for shallow rain-induced landslides using gage and satellite data

USGS Publications Warehouse

Yatheendradas, S.; Kirschbaum, D.; Baum, Rex L.; Godt, Jonathan W.

2014-01-01

Improving prediction of landslide early warning systems requires accurate estimation of the conditions that trigger slope failures. This study tested a slope-stability model for shallow rainfall-induced landslides by utilizing rainfall information from gauge and satellite records. We used the TRIGRS model (Transient Rainfall Infiltration and Grid-based Regional Slope-stability analysis) for simulating the evolution of the factor of safety due to rainfall infiltration. Using a spatial subset of a well-characterized digital landscape from an earlier study, we considered shallow failure on a slope adjoining an urban transportation roadway near the Seattle area in Washington, USA.We ran the TRIGRS model using high-quality rain gage and satellite-based rainfall data from the Tropical Rainfall Measuring Mission (TRMM). Preliminary results with parameterized soil depth values suggest that the steeper slope values in this spatial domain have factor of safety values that are extremely close to the failure limit within an extremely narrow range of values, providing multiple false alarms. When the soil depths were constrained using a back analysis procedure to ensure that slopes were stable under initial condtions, the model accurately predicted the timing and location of the landslide observation without false alarms over time for gage rain data. The TRMM satellite rainfall data did not show adequately retreived rainfall peak magnitudes and accumulation over the study period, and as a result failed to predict the landslide event. These preliminary results indicate that more accurate and higher-resolution rain data (e.g., the upcoming Global Precipitation Measurement (GPM) mission) are required to provide accurate and reliable landslide predictions in ungaged basins.

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.

Ontario multidetector computed tomographic coronary angiography study: field evaluation of diagnostic accuracy.

PubMed

Chow, Benjamin J W; Freeman, Michael R; Bowen, James M; Levin, Leslie; Hopkins, Robert B; Provost, Yves; Tarride, Jean-Eric; Dennie, Carole; Cohen, Eric A; Marcuzzi, Dan; Iwanochko, Robert; Moody, Alan R; Paul, Narinder; Parker, John D; O'Reilly, Daria J; Xie, Feng; Goeree, Ron

2011-06-13

Computed tomographic coronary angiography (CTCA) has gained clinical acceptance for the detection of obstructive coronary artery disease. Although single-center studies have demonstrated excellent accuracy, multicenter studies have yielded variable results. The true diagnostic accuracy of CTCA in the "real world" remains uncertain. We conducted a field evaluation comparing multidetector CTCA with invasive CA (ICA) to understand CTCA's diagnostic accuracy in a real-world setting. A multicenter cohort study of patients awaiting ICA was conducted between September 2006 and June 2009. All patients had either a low or an intermediate pretest probability for coronary artery disease and underwent CTCA and ICA within 10 days. The results of CTCA and ICA were interpreted visually by local expert observers who were blinded to all clinical data and imaging results. Using a patient-based analysis (diameter stenosis ≥50%) of 169 patients, the sensitivity, specificity, positive predictive value, and negative predictive value were 81.3% (95% confidence interval [CI], 71.0%-89.1%), 93.3% (95% CI, 85.9%-97.5%), 91.6% (95% CI, 82.5%-96.8%), and 84.7% (95% CI, 76.0%-91.2%), respectively; the area under receiver operating characteristic curve was 0.873. The diagnostic accuracy varied across centers (P < .001), with a sensitivity, specificity, positive predictive value, and negative predictive value ranging from 50.0% to 93.2%, 92.0% to 100%, 84.6% to 100%, and 42.9% to 94.7%, respectively. Compared with ICA, CTCA appears to have good accuracy; however, there was variability in diagnostic accuracy across centers. Factors affecting institutional variability need to be better understood before CTCA is universally adopted. Additional real-world evaluations are needed to fully understand the impact of CTCA on clinical care. clinicaltrials.gov Identifier: NCT00371891.

Comparison of wheat and rye flour solutions for skin prick testing: a multi-centre study (Stad 1).

PubMed

van Kampen, V; Merget, R; Rabstein, S; Sander, I; Bruening, T; Broding, H C; Keller, C; Muesken, H; Overlack, A; Schultze-Werninghaus, G; Walusiak, J; Raulf-Heimsoth, M

2009-12-01

Skin prick testing (SPT) is the basic method for diagnosing IgE-mediated allergies. However, skin reactivity is related to the quality of allergen extracts, which are often poorly defined for occupational allergens. To compare wheat and rye flour SPT solutions from different producers. Standardized SPTs were performed in seven allergy centres with wheat and rye flour solutions from four producers in 125 symptomatic bakers. Optimal cut-off levels for weal sizes were assessed with the Youden Index. Comparisons between SPT results of different solutions were made with flour-specific IgE (sIgE) as the gold standard. Sensitivities, specificities, positive and negative predictive values, and test efficiencies were calculated and compared with McNemar and chi(2)-tests. The influence of the choice of the gold standard (sIgE or challenge) test was examined for 95 subjects. Additionally, SPT solutions were analysed for protein and antigen content. The optimal cut-off level for all SPT solutions was a weal size of >or=1.5 mm. While differences between wheat and rye flours were small, differences between producers were important. Variability of sensitivities (0.31-0.96), negative predictive values (0.42-0.91), and test efficiencies (0.54-0.90) were higher than variations of specificities (0.74-1.00) and positive predictive values (0.88-1.00). Similar results were obtained when using challenge test results as the gold standard. Variability could be explained by the different antigen contents of the SPT solutions. There is a wide variability of SPT solutions for wheat and rye flour from different producers, mainly with respect to sensitivities, negative predictive values, and test efficiencies. Improvement and standardization of SPT solutions used for the diagnosis of baker's asthma are highly recommended.

Multiple testing of food contact materials: a predictive algorithm for assessing the global migration from silicone moulds.

PubMed

Elskens, Marc; Vloeberghs, Daniel; Van Elsen, Liesbeth; Baeyens, Willy; Goeyens, Leo

2012-09-15

For reasons of food safety, packaging and food contact materials must be submitted to migration tests. Testing of silicone moulds is often very laborious, since three replicate tests are required to decide about their compliancy. This paper presents a general modelling framework to predict the sample's compliance or non-compliance using results of the first two migration tests. It compares the outcomes of models with multiple continuous predictors with a class of models involving latent and dummy variables. The model's prediction ability was tested using cross and external validations, i.e. model revalidation each time a new measurement set became available. At the overall migration limit of 10 mg dm(-2), the relative uncertainty on a prediction was estimated to be ~10%. Taking the default values for α and β equal to 0.05, the maximum value that can be predicted for sample compliance was therefore 7 mg dm(-2). Beyond this limit the risk for false compliant results increases significantly, and a third migration test should be performed. The result of this latter test defines the sample's compliance or non-compliance. Propositions for compliancy control inspired by the current dioxin control strategy are discussed. Copyright © 2012 Elsevier B.V. All rights reserved.

Influence of Fuel Moisture Content and Reactor Temperature on the Calorific Value of Syngas Resulted from Gasification of Oil Palm Fronds

PubMed Central

Atnaw, Samson Mekbib; Sulaiman, Shaharin Anwar; Yusup, Suzana

2014-01-01

Biomass wastes produced from oil palm mills and plantations include empty fruit bunches (EFBs), shells, fibers, trunks, and oil palm fronds (OPF). EFBs and shells are partially utilized as boiler fuel while the rest of the biomass materials like OPF have not been utilized for energy generation. No previous study has been reported on gasification of oil palm fronds (OPF) biomass for the production of fuel gas. In this paper, the effect of moisture content of fuel and reactor temperature on downdraft gasification of OPF was experimentally investigated using a lab scale gasifier of capacity 50 kW. In addition, results obtained from equilibrium model of gasification that was developed for facilitating the prediction of syngas composition are compared with experimental data. Comparison of simulation results for predicting calorific value of syngas with the experimental results showed a satisfactory agreement with a mean error of 0.1 MJ/Nm3. For a biomass moisture content of 29%, the resulting calorific value for the syngas was found to be only 2.63 MJ/Nm3, as compared to nearly double (4.95 MJ/Nm3) for biomass moisture content of 22%. A calorific value as high as 5.57 MJ/Nm3 was recorded for higher oxidation zone temperature values. PMID:24578617

Influence of fuel moisture content and reactor temperature on the calorific value of syngas resulted from gasification of oil palm fronds.

PubMed

Atnaw, Samson Mekbib; Sulaiman, Shaharin Anwar; Yusup, Suzana

2014-01-01

Biomass wastes produced from oil palm mills and plantations include empty fruit bunches (EFBs), shells, fibers, trunks, and oil palm fronds (OPF). EFBs and shells are partially utilized as boiler fuel while the rest of the biomass materials like OPF have not been utilized for energy generation. No previous study has been reported on gasification of oil palm fronds (OPF) biomass for the production of fuel gas. In this paper, the effect of moisture content of fuel and reactor temperature on downdraft gasification of OPF was experimentally investigated using a lab scale gasifier of capacity 50 kW. In addition, results obtained from equilibrium model of gasification that was developed for facilitating the prediction of syngas composition are compared with experimental data. Comparison of simulation results for predicting calorific value of syngas with the experimental results showed a satisfactory agreement with a mean error of 0.1 MJ/Nm³. For a biomass moisture content of 29%, the resulting calorific value for the syngas was found to be only 2.63 MJ/Nm³, as compared to nearly double (4.95 MJ/Nm³) for biomass moisture content of 22%. A calorific value as high as 5.57 MJ/Nm³ was recorded for higher oxidation zone temperature values.

1.5-Tesla Multiparametric-Magnetic Resonance Imaging for the detection of clinically significant prostate cancer.

PubMed

Popita, Cristian; Popita, Anca Raluca; Sitar-Taut, Adela; Petrut, Bogdan; Fetica, Bogdan; Coman, Ioan

2017-01-01

Multiparametric-magnetic resonance imaging (mp-MRI) is the main imaging modality used for prostate cancer detection. The aim of this study is to evaluate the diagnostic performance of mp-MRI at 1.5-Tesla (1.5-T) for the detection of clinically significant prostate cancer. In this ethical board approved prospective study, 39 patients with suspected prostate cancer were included. Patients with a history of positive prostate biopsy and patients treated for prostate cancer were excluded. All patients were examined at 1.5-T MRI, before standard transrectal ultrasonography-guided biopsy. The overall sensitivity, specificity, positive predictive value and negative predictive value for mp-MRI were 100%, 73.68%, 80% and 100%, respectively. Our results showed that 1.5 T mp-MRI has a high sensitivity for detection of clinically significant prostate cancer and high negative predictive value in order to rule out significant disease.

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

PubMed

Johnstone, C; Markandya, A

2006-08-01

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

[Evaluation of eco-environmental quality based on artificial neural network and remote sensing techniques].

PubMed

Li, Hongyi; Shi, Zhou; Sha, Jinming; Cheng, Jieliang

2006-08-01

In the present study, vegetation, soil brightness, and moisture indices were extracted from Landsat ETM remote sensing image, heat indices were extracted from MODIS land surface temperature product, and climate index and other auxiliary geographical information were selected as the input of neural network. The remote sensing eco-environmental background value of standard interest region evaluated in situ was selected as the output of neural network, and the back propagation (BP) neural network prediction model containing three layers was designed. The network was trained, and the remote sensing eco-environmental background value of Fuzhou in China was predicted by using software MATLAB. The class mapping of remote sensing eco-environmental background values based on evaluation standard showed that the total classification accuracy was 87. 8%. The method with a scheme of prediction first and classification then could provide acceptable results in accord with the regional eco-environment types.

NP-59 test for preoperative localization of primary hyperaldosteronism.

PubMed

Di Martino, Marcello; García Sanz, Iñigo; Muñoz de Nova, Jose Luis; Marín Campos, Cristina; Martínez Martín, Miguel; Domínguez Gadea, Luis

2017-03-01

Adrenal venous sampling is generally considered the gold standard to identify unilateral hormone production in cases of primary hyperaldosteronism. The aim of this study is to evaluate whether the iodine-131-6-β-iodomethyl-19-norcholesterol (NP-59) test may represent an alternative in selected cases. Patients submitted to laparoscopic adrenalectomy for suspected primary hyperaldosteronism (n = 27) were retrospectively reviewed. When nuclear medicine tests were preoperatively performed, their results were compared with the histopathologic findings and clinical improvement. Nuclear medicine tests were realized in 13 patients. In 11 (84.6%), a planar anterior and posterior NP-59 scintigraphy was performed and a SPECT/TC in two (15.4%). Scintigraphy indicated a preoperative lateralization in 12 out of 13 patients (92.3%). When the value of NP-59 tests was based on pathologic results, it showed a sensitivity of 90.9% and a positive predictive value of 83.3%. When the nuclear medicine test's performance was based on postoperative blood pressure control, both sensitivity and positive predictive value were 91.6%. Nuclear medicine tests represent a useful tool in the preoperative localisation of primary hyperaldosteronism with a high sensitivity and positive predictive value. In patients with contraindications to adrenal venous sampling like contrast allergies, or when it is inconclusive, scintigraphy can represent a useful and non-invasive alternative.

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.

Theoretical Study of pKa Values for Trivalent Rare-Earth Metal Cations in Aqueous Solution.

PubMed

Yu, Donghai; Du, Ruobing; Xiao, Ji-Chang; Xu, Shengming; Rong, Chunying; Liu, Shubin

2018-01-18

Molecular acidity of trivalent rare-earth metal cations in aqueous solution is an important factor dedicated to the efficiency of their extraction and separation processes. In this work, the aqueous acidity of these metal ions has been quantitatively investigated using a few theoretical approaches. Our computational results expressed in terms of pK a values agree well with the tetrad effect of trivalent rare-earth ions extensively reported in the extraction and separation of these elements. Strong linear relationships have been observed between the acidity and quantum electronic descriptors such as the molecular electrostatic potential on the acidic nucleus and the sum of the valence natural atomic orbitals energies of the dissociating proton. Making use of the predicted pK a values, we have also predicted the major ionic forms of these species in the aqueous environment with different pH values, which can be employed to rationalize the behavior difference of different rare-earth metal cations during the extraction process. Our present results should provide needed insights not only for the qualitatively understanding about the extraction and separation between yttrium and lanthanide elements but also for the prediction of novel and more efficient rare-earth metal extractants in the future.

Observations and theoretical evaluations of color changes of traveling light beams caused by optical rotation phenomena in sugared water and their applications for educational purposes

NASA Astrophysics Data System (ADS)

Tokumitsu, Seika; Hasegawa, Makoto

2017-08-01

Investigations were conducted for the purposes of understanding coloring phenomena to be caused by optical rotation of polarized light beams in sugared water and realizing their applications as educational tools. By allowing polarized laser beams in red, blue or green to travel in sugared water of certain concentrations, changes in their intensities were measured while changing a distance between a pair of polarizing plates in the sugared water. An equation was established for a theoretical value for the angle of rotation for light of any colors (wavelengths) travelling in sugared water of any concentrations. The predicted results exhibited satisfactory matching with the measured values. In addition, the intensities of transmitted laser beams, as well as colors to be observable when a white-color LED torch was employed as a light source, were also become predictable, and the predicted results were well-matched with the observation results.

Performance of highly sensitive cardiac troponin T assay to detect ischaemia at PET-CT in low-risk patients with acute coronary syndrome: a prospective observational study.

PubMed

Morawiec, Beata; Fournier, Stephane; Tapponnier, Maxime; Prior, John O; Monney, Pierre; Dunet, Vincent; Lauriers, Nathalie; Recordon, Frederique; Trana, Catalina; Iglesias, Juan-Fernando; Kawecki, Damian; Boulat, Olivier; Bardy, Daniel; Lamsidri, Sabine; Eeckhout, Eric; Hugli, Olivier; Muller, Olivier

2017-07-10

Highly sensitive troponin T (hs-TnT) assay has improved clinical decision-making for patients admitted with chest pain. However, this assay's performance in detecting myocardial ischaemia in a lowrisk population has been poorly documented. To assess hs-TnT assay's performance to detect myocardial ischaemia at positron emission tomography/CT (PET-CT) in low-risk patients admitted with chest pain. Patients admitted for chest pain with a nonconclusive ECG and negative standard cardiac troponin T results at admission and after 6 hours were prospectively enrolled. Their hs-TnT samples were at T0, T2 and T6. Physicians were blinded to hs-TnT results. All patients underwent a PET-CT at rest and during adenosine-induced stress. All patients with a positive PET-CT result underwent a coronary angiography. Forty-eight patients were included. Six had ischaemia at PET-CT. All of them had ≥1 significant stenosis at coronary angiography. Areas under the curve (95% CI) for predicting significant ischaemia at PET-CT using hs-TnT were 0.764 (0.515 to 1.000) at T0, 0.812(0.616 to 1.000) at T2 and 0.813(0.638 to 0.989) at T6. The receiver operating characteristicbased optimal cut-off value for hs-TnT at T0, T2 and T6 needed to exclude significant ischaemia at PET-CT was <4 ng/L. Using this value, sensitivity, specificity, positive and negative predictive values of hs-TnT to predict significant ischaemia were 83%/38%/16%/94% at T0, 100%/40%/19%/100% at T2 and 100%/43%/20%/100% at T6, respectively. Our findings suggest that in low-risk patients, using the hs-TnT assay with a cut-off value of 4 ng/L demonstrates excellent negative predictive value to exclude myocardial ischaemia detection at PET-CT, at the expense of weak specificity and positive predictive value. ClinicalTrials.gov Identifier: NCT01374607. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

[Quality assurance of fine-needle aspiration cytology of the organized mammography screening].

PubMed

Bak, Mihály; Konyár, Eva; Schneider, Ferenc; Bidlek, Mária; Szabó, Eva; Nyári, Tibor; Godény, Mária; Kásler, Miklós

2010-08-08

The National Public Health Program has established the organized mammography screening in Hungary. The aim of our study was to determine the quality assurance of breast aspiration cytology. Cytology results were rated to 5 categories (C1, C2, C3, C4 and C5). All cytology reports were compared with the final histology diagnosis. 1361 women had aspiration cytology diagnosis performed from a total of 47718 mammography non-negative lesions. There were 805 (59.1%) benign and 187 (13.7%) malignant alterations. Sensitivity was 91%, specificity 88%, positive predictive value 96.6% and negative predictive value turned to be 71% (p<0.001). The auditing values of fine needle aspiration cytology in our laboratory meet, or in certain aspects exceed the proposed minimum threshold values.

The Optimal Cut-Off Value of Neutrophil-to-Lymphocyte Ratio for Predicting Prognosis in Adult Patients with Henoch–Schönlein Purpura

PubMed Central

Park, Chan Hyuk; Han, Dong Soo; Jeong, Jae Yoon; Eun, Chang Soo; Yoo, Kyo-Sang; Jeon, Yong Cheol; Sohn, Joo Hyun

2016-01-01

Background The development of gastrointestinal (GI) bleeding and end-stage renal disease (ESRD) can be a concern in the management of Henoch–Schönlein purpura (HSP). We aimed to evaluate whether the neutrophil-to-lymphocyte ratio (NLR) is associated with the prognosis of adult patients with HSP. Methods Clinical data including the NLR of adult patients with HSP were retrospectively analyzed. Patients were classified into three groups as follows: (a) simple recovery, (b) wax & wane without GI bleeding, and (c) development of GI bleeding. The optimal cut-off value was determined using a receiver operating characteristics curve and the Youden index. Results A total of 66 adult patients were enrolled. The NLR was higher in the GI bleeding group than in the simple recovery or wax & wane group (simple recovery vs. wax & wane vs. GI bleeding; median [IQR], 2.32 [1.61–3.11] vs. 3.18 [2.16–3.71] vs. 7.52 [4.91–10.23], P<0.001). For the purpose of predicting simple recovery, the optimal cut-off value of NLR was 3.18, and the sensitivity and specificity were 74.1% and 75.0%, respectively. For predicting development of GI bleeding, the optimal cut-off value was 3.90 and the sensitivity and specificity were 87.5% and 88.6%, respectively. Conclusions The NLR is useful for predicting development of GI bleeding as well as simple recovery without symptom relapse. Two different cut-off values of NLR, 3.18 for predicting an easy recovery without symptom relapse and 3.90 for predicting GI bleeding can be used in adult patients with HSP. PMID:27073884

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

Comparison of conventional and automated breast volume ultrasound in the description and characterization of solid breast masses based on BI-RADS features.

PubMed

Kim, Hyunji; Cha, Joo Hee; Oh, Ha-Yeun; Kim, Hak Hee; Shin, Hee Jung; Chae, Eun Young

2014-07-01

To compare the performance of radiologists in the use of conventional ultrasound (US) and automated breast volume ultrasound (ABVU) for the characterization of benign and malignant solid breast masses based on breast imaging and reporting data system (BI-RADS) criteria. Conventional US and ABVU images were obtained in 87 patients with 106 solid breast masses (52 cancers, 54 benign lesions). Three experienced radiologists who were blinded to all examination results independently characterized the lesions and reported a BI-RADS assessment category and a level of suspicion of malignancy. The results were analyzed by calculation of Cohen's κ coefficient and by receiver operating characteristic (ROC) analysis. Assessment of the agreement of conventional US and ABVU indicated that the posterior echo feature was the most discordant feature of seven features (κ = 0.371 ± 0.225) and that orientation had the greatest agreement (κ = 0.608 ± 0.210). The final assessment showed substantial agreement (κ = 0.773 ± 0.104). The areas under the ROC curves (Az) for conventional US and ABVU were not statistically significant for each reader, but the mean Az values of conventional US and ABVU by multi-reader multi-case analysis were significantly different (conventional US 0.991, ABVU 0.963; 95 % CI -0.0471 to -0.0097). The means for sensitivity, specificity, positive predictive value, and negative predictive value of conventional US and ABVU did not differ significantly. There was substantial inter-observer agreement in the final assessment of solid breast masses by conventional US and ABVU. ROC analysis comparing the performance of conventional US and ABVU indicated a marginally significant difference in mean Az, but not in mean sensitivity, specificity, positive predictive value, or negative predictive value.

Gravity-darkening exponents in semi-detached binary systems from their photometric observations. II.

NASA Astrophysics Data System (ADS)

Djurašević, G.; Rovithis-Livaniou, H.; Rovithis, P.; Georgiades, N.; Erkapić, S.; Pavlović, R.

2006-01-01

This second part of our study concerning gravity-darkening presents the results for 8 semi-detached close binary systems. From the light-curve analysis of these systems the exponent of the gravity-darkening (GDE) for the Roche lobe filling components has been empirically derived. The method used for the light-curve analysis is based on Roche geometry, and enables simultaneous estimation of the systems' parameters and the gravity-darkening exponents. Our analysis is restricted to the black-body approximation which can influence in some degree the parameter estimation. The results of our analysis are: 1) For four of the systems, namely: TX UMa, β Per, AW Cam and TW Cas, there is a very good agreement between empirically estimated and theoretically predicted values for purely convective envelopes. 2) For the AI Dra system, the estimated value of gravity-darkening exponent is greater, and for UX Her, TW And and XZ Pup lesser than corresponding theoretical predictions, but for all mentioned systems the obtained values of the gravity-darkening exponent are quite close to the theoretically expected values. 3) Our analysis has proved generally that with the correction of the previously estimated mass ratios of the components within some of the analysed systems, the theoretical predictions of the gravity-darkening exponents for stars with convective envelopes are highly reliable. The anomalous values of the GDE found in some earlier studies of these systems can be considered as the consequence of the inappropriate method used to estimate the GDE. 4) The empirical estimations of GDE given in Paper I and in the present study indicate that in the light-curve analysis one can apply the recent theoretical predictions of GDE with high confidence for stars with both convective and radiative envelopes.

Airborne fungal spores of Alternaria, meteorological parameters and predicting variables

NASA Astrophysics Data System (ADS)

Filali Ben Sidel, Farah; Bouziane, Hassan; del Mar Trigo, Maria; El Haskouri, Fatima; Bardei, Fadoua; Redouane, Abdelbari; Kadiri, Mohamed; Riadi, Hassane; Kazzaz, Mohamed

2015-03-01

Alternaria is frequently found as airborne fungal spores and is recognized as an important cause of respiratory allergies. The aerobiological monitoring of fungal spores was performed using a Burkard volumetric spore traps. To establish predicting variables for daily and weakly spore counts, a stepwise multiple regression between spore concentrations and independent variables (meteorological parameters and lagged values from the series of spore concentrations: previous day or week concentration (Alt t - 1) and mean concentration of the same day or week in other years ( C mean)) was made with data obtained during 2009-2011. Alternaria conidia are present throughout the year in the atmosphere of Tetouan, although they show important seasonal fluctuations. The highest levels of Alternaria spores were recorded during the spring and summer or autumn. Alternaria showed maximum daily values in April, May or October depending on year. When the spore variables of Alternaria, namely C mean and Alt t - 1, and meteorological parameters were included in the equation, the resulting R 2 satisfactorily predict future concentrations for 55.5 to 81.6 % during the main spore season and the pre-peak 2. In the predictive model using weekly values, the adjusted R 2 varied from 0.655 to 0.676. The Wilcoxon test was used to compare the results from the expected values and the pre-peak spore data or weekly values for 2012, indicating that there were no significant differences between series compared. This test showed the C mean, Alt t - 1, frequency of the wind third quadrant, maximum wind speed and minimum relative humidity as the most efficient independent variables to forecast the overall trend of this spore in the air.

Predictors of Handwriting in Children with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Hellinckx, Tinneke; Roeyers, Herbert; Van Waelvelde, Hilde

2013-01-01

During writing, perceptual, motor, and cognitive processes interact. This study explored the predictive value of several factors on handwriting quality as well as on speed in children with Autism Spectrum Disorder (ASD). Our results showed that, in this population, age, gender, and visual-motor integration significantly predicted handwriting…

Suitability of hyperspectral imaging for rapid evaluation of thiobarbituric acid (TBA) value in grass carp (Ctenopharyngodon idella) fillet.

PubMed

Cheng, Jun-Hu; Sun, Da-Wen; Pu, Hong-Bin; Wang, Qi-Jun; Chen, Yu-Nan

2015-03-15

The suitability of hyperspectral imaging technique (400-1000 nm) was investigated to determine the thiobarbituric acid (TBA) value for monitoring lipid oxidation in fish fillets during cold storage at 4°C for 0, 2, 5, and 8 days. The PLSR calibration model was established with full spectral region between the spectral data extracted from the hyperspectral images and the reference TBA values and showed good performance for predicting TBA value with determination coefficients (R(2)P) of 0.8325 and root-mean-square errors of prediction (RMSEP) of 0.1172 mg MDA/kg flesh. Two simplified PLSR and MLR models were built and compared using the selected ten most important wavelengths. The optimised MLR model yielded satisfactory results with R(2)P of 0.8395 and RMSEP of 0.1147 mg MDA/kg flesh, which was used to visualise the TBA values distribution in fish fillets. The whole results confirmed that using hyperspectral imaging technique as a rapid and non-destructive tool is suitable for the determination of TBA values for monitoring lipid oxidation and evaluation of fish freshness. Copyright © 2014 Elsevier Ltd. All rights reserved.

Using liver enzymes as screening tests to predict mortality risk.

PubMed

Fulks, Michael; Stout, Robert L; Dolan, Vera F

2008-01-01

Determine the relationship between liver function test results (GGT, alkaline phosphatase, AST, and ALT) and all-cause mortality in life insurance applicants. By use of the Social Security Master Death File, mortality was examined in 1,905,664 insurance applicants for whom blood samples were submitted to the Clinical Reference Laboratory. There were 50,174 deaths observed in this study population. Results were stratified by 3 age/sex groups: females, age <60; males, age <60; and all, age 60+. Liver function test values were grouped using percentiles of their distribution in these 3 age/sex groups, as well as ranges of actual values. Using the risk of the middle 50% of the population by distribution as a reference, relative mortality observed for GGT and alkaline phosphatase was linear with a steep slope from very low to relatively high values. Relative mortality was increased at lower values for both AST and ALT. ALT did not predict mortality for values above the middle 50% of its distribution. GGT and alkaline phosphatase are significant predictors of mortality risk for all values. ALT is still useful for triggering further testing for hepatitis, but AST should be used instead to assess mortality risk linked with transaminases.

Time trade-off and attitudes toward euthanasia: implications of using 'death' as an anchor in health state valuation.

PubMed

Augestad, Liv A; Rand-Hendriksen, Kim; Stavem, Knut; Kristiansen, Ivar Sønbø

2013-05-01

Health state values are by convention anchored to 'perfect health' and 'death.' Attitudes toward death may consequently influence the valuations. We used attitudes toward euthanasia (ATE) as a sub-construct for attitudes toward death. We compared the influence on values elicited with time trade-off (TTO), lead-time TTO (LT-TTO) and visual analogue scale (VAS).Since the 'death' anchor is most explicit in TTO, we hypothesized that TTO values would be most influenced by ATE. Respondents valued eight EQ-5D health states with VAS, then TTO (n = 328) or LT-TTO (n = 484). We measured ATE on a scale from -2 (fully disagree) to 2 (fully agree) and used multiple linear regressions to predict VAS, TTO, and LT-TTO values by ATE, sex, age, and education. A one-point increase on the ATE scale predicted a mean TTO value change of -.113 and LT-TTO change of -.072. Demographic variables, but not ATE, predicted VAS values. TTO appears to measure ATE in addition to preferences for health states. Different ways of incorporating death in the valuation may impact substantially on the resulting values. 'Death' is a metaphysically unknown concept, and implications of attitudes toward death should be investigated further to evaluate the appropriateness of using 'death' as an anchor.

Pulmonary Masses: Initial Results of Cone-beam CT Guidance with Needle Planning Software for Percutaneous Lung Biopsy

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

Braak, Sicco J., E-mail: sjbraak@gmail.com; Herder, Gerarda J. M., E-mail: j.herder@antoniusziekenhuis.nl; Heesewijk, Johannes P. M. van, E-mail: j.heesewijk@antoniusziekenhuis.nl

2012-12-15

Purpose: To evaluate the outcome of percutaneous lung biopsy (PLB) findings using cone-beam computed tomographic (CT) guidance (CBCT guidance) and compared to conventional biopsy guidance techniques. Methods: CBCT guidance is a stereotactic technique for needle interventions, combining 3D soft-tissue cone-beam CT, needle planning software, and real-time fluoroscopy. Between March 2007 and August 2010, we performed 84 Tru-Cut PLBs, where bronchoscopy did not provide histopathologic diagnosis. Mean patient age was 64.6 (range 24-85) years; 57 patients were men, and 25 were women. Records were prospectively collected for calculating sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. We also registeredmore » fluoroscopy time, room time, interventional time, dose-area product (DAP), and complications. Procedures were divided into subgroups (e.g., location, size, operator). Results: Mean lesion diameter was 32.5 (range 3.0-93.0) mm, and the mean number of samples per biopsy procedure was 3.2 (range 1-7). Mean fluoroscopy time was 161 (range 104-551) s, room time was 34 (range 15-79) min, mean DAP value was 25.9 (range 3.9-80.5) Gy{center_dot}cm{sup -2}, and interventional time was 18 (range 5-65) min. Of 84 lesions, 70 were malignant (83.3%) and 14 were benign (16.7%). Seven (8.3%) of the biopsy samples were nondiagnostic. All nondiagnostic biopsied lesions proved to be malignant during surgical resection. The outcome for sensitivity, specificity, positive predictive value, negative predictive value, and accuracy was 90% (95% confidence interval [CI] 86-96), 100% (95% CI 82-100), 100% (95% CI 96-100), 66.7% (95% CI 55-83), and 91.7% (95% CI 86-96), respectively. Sixteen patients (19%) had minor and 2 (2.4%) had major complications. Conclusion: CBCT guidance is an effective method for PLB, with results comparable to CT/CT fluoroscopy guidance.« less

Diagnostic accuracy of liver fibrosis based on red cell distribution width (RDW) to platelet ratio with fibroscan in chronic hepatitis B

NASA Astrophysics Data System (ADS)

Sembiring, J.; Jones, F.

2018-03-01

Red cell Distribution Width (RDW) and platelet ratio (RPR) can predict liver fibrosis and cirrhosis in chronic hepatitis B with relatively high accuracy. RPR was superior to other non-invasive methods to predict liver fibrosis, such as AST and ALT ratio, AST and platelet ratio Index and FIB-4. The aim of this study was to assess diagnostic accuracy liver fibrosis by using RDW and platelets ratio in chronic hepatitis B patients based on compared with Fibroscan. This cross-sectional study was conducted at Adam Malik Hospital from January-June 2015. We examine 34 patients hepatitis B chronic, screen RDW, platelet, and fibroscan. Data were statistically analyzed. The result RPR with ROC procedure has an accuracy of 72.3% (95% CI: 84.1% - 97%). In this study, the RPR had a moderate ability to predict fibrosis degree (p = 0.029 with AUC> 70%). The cutoff value RPR was 0.0591, sensitivity and spesificity were 71.4% and 60%, Positive Prediction Value (PPV) was 55.6% and Negative Predictions Value (NPV) was 75%, positive likelihood ratio was 1.79 and negative likelihood ratio was 0.48. RPR have the ability to predict the degree of liver fibrosis in chronic hepatitis B patients with moderate accuracy.

Finite element elastic-plastic-creep and cyclic life analysis of a cowl lip

NASA Technical Reports Server (NTRS)

Arya, Vinod K.; Melis, Matthew E.; Halford, Gary R.

1990-01-01

Results are presented of elastic, elastic-plastic, and elastic-plastic-creep analyses of a test-rig component of an actively cooled cowl lip. A cowl lip is part of the leading edge of an engine inlet of proposed hypersonic aircraft and is subject to severe thermal loadings and gradients during flight. Values of stresses calculated by elastic analysis are well above the yield strength of the cowl lip material. Such values are highly unrealistic, and thus elastic stress analyses are inappropriate. The inelastic (elastic-plastic and elastic-plastic-creep) analyses produce more reasonable and acceptable stress and strain distributions in the component. Finally, using the results from these analyses, predictions are made for the cyclic crack initiation life of a cowl lip. A comparison of predicted cyclic lives shows the cyclic life prediction from the elastic-plastic-creep analysis to be the lowest and, hence, most realistic.

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.

Predictive value of uterine Doppler waveform during pregnancies complicated by diabetes.

PubMed

Haddad, B; Uzan, M; Tchobroutsky, C; Uzan, S; Papiernik-Berkhauer, E

1993-01-01

Diabetes, whether or not it is insulin deficient, is frequently associated with vascular complications during pregnancies. It is accepted nowadays that the uterine artery velocity waveform is predictive concerning pregnancy-induced hypertension (PIH) and its complications. It thus seemed interesting to analyse the predictivity of vascular complications of diabetes by using uterine artery velocity waveforms. We have thus explored 37 diabetic patients [group 1: insulin-deficient diabetes (IDD), n = 10; group 2: gestational IDD, n = 6; and gestational non-IDD, n = 21). We have found vascular complications for 10 patients, divided between all 2 groups: 2 pre-eclampsia, 2 fetal suffering before any labour, 2 cases of intra-uterine growth retardation (including a trisomy 18) and 5 PIH. The uterine artery velocimetry measurement has been found to be pathological 5 times, and always in patients who later developed vascular complications. Among this selected population and excluding the trisomy 18, the sensitivity is of 44.5%, the specificity of 100%, the positive predictive value of 100%, and the negative predictive value of 84.3%. If these results are confirmed, this examination could be an excellent marker of the vascular risk and thus would have its place during systematic survey of pregnancies complicated by diabetes.

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.

Customized versus population-based birth weight charts for the detection of neonatal growth and perinatal morbidity in a cross-sectional study of term neonates.

PubMed

Carberry, Angela E; Raynes-Greenow, Camille H; Turner, Robin M; Jeffery, Heather E

2013-10-15

Customized birth weight charts that incorporate maternal characteristics are now being adopted into clinical practice. However, there is controversy surrounding the value of these charts in the prediction of growth and perinatal outcomes. The objective of this study was to assess the use of customized charts in predicting growth, defined by body fat percentage, and perinatal morbidity. A total of 581 term (≥37 weeks' gestation) neonates born in Sydney, Australia, in 2010 were included. Body fat percentage measurements were taken by using air displacement plethysmography. Objective composite measurements of perinatal morbidity were used to identify neonates who had poor outcomes; these data were extracted from medical records. The value of customized charts was assessed by calculating positive predictive values, negative predictive values, and odds ratios with 95% confidence intervals. Customized versus population-based charts did not improve the prediction of either low body fat percentage (59% vs. 66% positive predictive value and 87% vs. 89% negative predictive value, respectively) or high body fat percentage (48% vs. 53% positive predictive value and 90% vs. 89% negative predictive value, respectively). Customized charts were not better than population-based charts at predicting perinatal morbidity (for customized charts, odds ratio = 1.02, 95% confidence interval: 1.01, 1.04; for population-based charts, odds ratio = 1.03, 95% confidence interval: 1.01, 1.05) per percentile decrease in birth weight. Customized birth weight charts do not provide significant improvements over population-based charts in predicting neonatal growth and morbidity.

Mathematical Description of the Uptake of Hydrocarbons in Jet Fuel into the Stratum Corneum of Human Volunteers

PubMed Central

Kim, David; Farthing, Matthew W.; Miller, Cass T.; Nylander-French, Leena A.

2008-01-01

The objective of this research was to develop a mathematical description of uptake of aromatic and aliphatic hydrocarbons into the stratum corneum of human skin in vivo. A simple description based on Fick’s Laws of diffusion was used to predict the spatiotemporal variation of naphthalene, 1- and 2-methylnaphthalene, undecane, and dodecane in the stratum corneum of human volunteers. The estimated values of the diffusion coefficients for each chemical were comparable to values predicted using in vitro skin systems and biomonitoring studies. These results demonstrate the value of measuring dermal exposure using the tape-strip technique and the importance of quantifying of dermal uptake. PMID:18423910

Performance of the OraQuick HCV rapid antibody test for screening exposed patients in a hepatitis C outbreak investigation.

PubMed

Gao, Fengxiang; Talbot, Elizabeth A; Loring, Carol H; Power, Jill J; Dionne-Odom, Jodie; Alroy-Preis, Sharon; Jackson, Patricia; Bean, Christine L

2014-07-01

During a nosocomial hepatitis C outbreak, emergency public clinics employed the OraQuick HCV rapid antibody test on site, and all results were verified by a standard enzyme immunoassay (EIA). Of 1,157 persons, 1,149 (99.3%) exhibited concordant results between the two tests (16 positive, 1,133 negative). The sensitivity, specificity, positive predictive value, and negative predictive value were 94.1%, 99.5%, 72.7%, and 99.9%, respectively. OraQuick performed well as a screening test during an outbreak investigation and could be integrated into future hepatitis C virus (HCV) outbreak testing algorithms. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Appropriate clinical use of human leukocyte antigen typing for coeliac disease: an Australasian perspective

PubMed Central

Tye-Din, J A; Cameron, D J S; Daveson, A J; Day, A S; Dellsperger, P; Hogan, C; Newnham, E D; Shepherd, S J; Steele, R H; Wienholt, L; Varney, M D

2015-01-01

The past decade has seen human leukocyte antigen (HLA) typing emerge as a remarkably popular test for the diagnostic work-up of coeliac disease with high patient acceptance. Although limited in its positive predictive value for coeliac disease, the strong disease association with specific HLA genes imparts exceptional negative predictive value to HLA typing, enabling a negative result to exclude coeliac disease confidently. In response to mounting evidence that the clinical use and interpretation of HLA typing often deviates from best practice, this article outlines an evidence-based approach to guide clinically appropriate use of HLA typing, and establishes a reporting template for pathology providers to improve communication of results. PMID:25827511

21 CFR 868.1890 - Predictive pulmonary-function value calculator.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 8 2011-04-01 2011-04-01 false Predictive pulmonary-function value calculator. 868.1890 Section 868.1890 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN... pulmonary-function value calculator. (a) Identification. A predictive pulmonary-function value calculator is...

21 CFR 868.1890 - Predictive pulmonary-function value calculator.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Predictive pulmonary-function value calculator. 868.1890 Section 868.1890 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN... pulmonary-function value calculator. (a) Identification. A predictive pulmonary-function value calculator is...

Evaluation of Diagnostic Values of Clinical Assessment in Determining the Maturation of Arteriovenous Fistulas for Satisfactory Hemodialysis.

PubMed

Salimi, Fereshteh; Shahabi, Shahab; Talebzadeh, Hamid; Keshavarzian, Amir; Pourfakharan, Mohammad; Safaei, Mansour

2017-01-01

Fistulas are the preferred permanent hemodialysis vascular access, but a significant obstacle to increasing their prevalence is the fistula's high "failure to mature" (FTM) rate. This study aimed to identify postoperative clinical characteristics that are predictive of fistula FTM. This descriptive cross-sectional study was performed on 80 end-stage renal disease patients who referred to Al Zahra Hospital, Isfahan, for brachiocephalic fistula placement. After 4 weeks, the clinical criteria (trill, firmness, vein length, and venous engorgement) examined and the fistulas situation divided to favorable or unfavorable by each criterion, and the results comprised with dialysis possibility. Data were analyzed with SPSS version 21. Diagnostic index for CLINICAL examination was calculated. Among the 80 cases, 25 (31.2%) female and 55 (68.8%) male were studied with the mean age of 51.9 (standard deviation = 17) year ranged between 18 and 86 years old. Sixty-two (77.5%) cases had successful hemodialysis. All four clinical assessments were significantly more acceptable in patients with successful dialysis ( P < 0.001). According to the results of our study, the accuracy of all physical assessments was above 70% and except vein length other criteria had a sensitivity and negative predictive value of 100%. In this study, firmness of vein has highest specificity and positive predictive value (83.9% and 64.3%, respectively). Results of our study showed that high sensitivity and relatively low specificity of the clinical criterion. It means that unfavorable results of each clinical criterion predict unfavorable dialysis. Clinical evaluation of a newly created fistula 4-6 weeks after surgery should be considered mandatory.

Reference values of inspiratory spirometry for Finnish adults.

PubMed

Kainu, Annette; Timonen, Kirsi L; Vanninen, Esko; Sovijärvi, Anssi R

2018-03-07

Inspiratory spirometry is used in evaluation of upper airway disorders e.g. fixed or variable obstruction. There are, however, very few published data on normal values for inspiratory spirometry. The main aim of this study was to produce reference values for inspiratory spirometry for healthy Finnish adults. Inspiratory spirometry was preplanned to a sample of the Finnish spirometry reference values sample. Data was successfully retrieved from 368 healthy nonsmoking adults (132 males) between 19 and 83 years of age. Reference equations were produced for forced inspiratory vital capacity (FIVC), forced inspiratory volume in one second (FIV1), FIV1/FIVC, peak inspiratory flow (PIF) and the ratios of FIV1/forced expiratory volume in one second and PIF/peak expiratory flow. The present values were compared to PIF values from previously used Finnish study of Viljanen et al. (1982) reference values and Norwegian values for FIV1, FIVC and FIV1/FIVC presented by Gulsvik et al. (2001). The predicted values from the Gulsvik et al. (2001), provided a good fit for FIVC, but smaller values for FIV1 with mean 108.3 and 109.1% of predicted values for males and females, respectively. PIF values were 87.4 and 91.2% of Viljanen et al. (1982) predicted values in males and females, respectively. Differences in measurement methods and selection of results may contribute to the observed differences. Inspiratory spirometry is technically more demanding and needs repeatability criteria to improve validity. New reference values are suggested to clinical use in Finland when assessing inspiratory spirometry. Utility of inspiratory to expiratory values indices in assessment of airway collapse need further study.

Improved Model for Predicting the Free Energy Contribution of Dinucleotide Bulges to RNA Duplex Stability.

PubMed

Tomcho, Jeremy C; Tillman, Magdalena R; Znosko, Brent M

2015-09-01

Predicting the secondary structure of RNA is an intermediate in predicting RNA three-dimensional structure. Commonly, determining RNA secondary structure from sequence uses free energy minimization and nearest neighbor parameters. Current algorithms utilize a sequence-independent model to predict free energy contributions of dinucleotide bulges. To determine if a sequence-dependent model would be more accurate, short RNA duplexes containing dinucleotide bulges with different sequences and nearest neighbor combinations were optically melted to derive thermodynamic parameters. These data suggested energy contributions of dinucleotide bulges were sequence-dependent, and a sequence-dependent model was derived. This model assigns free energy penalties based on the identity of nucleotides in the bulge (3.06 kcal/mol for two purines, 2.93 kcal/mol for two pyrimidines, 2.71 kcal/mol for 5'-purine-pyrimidine-3', and 2.41 kcal/mol for 5'-pyrimidine-purine-3'). The predictive model also includes a 0.45 kcal/mol penalty for an A-U pair adjacent to the bulge and a -0.28 kcal/mol bonus for a G-U pair adjacent to the bulge. The new sequence-dependent model results in predicted values within, on average, 0.17 kcal/mol of experimental values, a significant improvement over the sequence-independent model. This model and new experimental values can be incorporated into algorithms that predict RNA stability and secondary structure from sequence.

The habenula governs the attribution of incentive salience to reward predictive cues

PubMed Central

Danna, Carey L.; Shepard, Paul D.; Elmer, Greg I.

2013-01-01

The attribution of incentive salience to reward associated cues is critical for motivation and the pursuit of rewards. Disruptions in the integrity of the neural systems controlling these processes can lead to avolition and anhedonia, symptoms that cross the diagnostic boundaries of many neuropsychiatric illnesses. Here, we consider whether the habenula (Hb), a region recently demonstrated to encode negatively valenced events, also modulates the attribution of incentive salience to a neutral cue predicting a food reward. The Pavlovian autoshaping paradigm was used in the rat as an investigative tool to dissociate Pavlovian learning processes imparting strictly predictive value from learning that attributes incentive motivational value. Electrolytic lesions of the fasciculus retroflexus (fr), the sole pathway through which descending Hb efferents are conveyed, significantly increased incentive salience as measured by conditioned approaches to a cue light predictive of reward. Conversely, generation of a fictive Hb signal via fr stimulation during CS+ presentation significantly decreased the incentive salience of the predictive cue. Neither manipulation altered the reward predictive value of the cue as measured by conditioned approach to the food. Our results provide new evidence supporting a significant role for the Hb in governing the attribution of incentive motivational salience to reward predictive cues and further imply that pathological changes in Hb activity could contribute to the aberrant pursuit of debilitating goals or avolition and depression-like symptoms. PMID:24368898

A 3-Year Study of Predictive Factors for Positive and Negative Appendicectomies.

PubMed

Chang, Dwayne T S; Maluda, Melissa; Lee, Lisa; Premaratne, Chandrasiri; Khamhing, Srisongham

2018-03-06

Early and accurate identification or exclusion of acute appendicitis is the key to avoid the morbidity of delayed treatment for true appendicitis or unnecessary appendicectomy, respectively. We aim (i) to identify potential predictive factors for positive and negative appendicectomies; and (ii) to analyse the use of ultrasound scans (US) and computed tomography (CT) scans for acute appendicitis. All appendicectomies that took place at our hospital from the 1st of January 2013 to the 31st of December 2015 were retrospectively recorded. Test results of potential predictive factors of acute appendicitis were recorded. Statistical analysis was performed using Fisher exact test, logistic regression analysis, sensitivity, specificity, and positive and negative predictive values calculation. 208 patients were included in this study. 184 patients had histologically proven acute appendicitis. The other 24 patients had either nonappendicitis pathology or normal appendix. Logistic regression analysis showed statistically significant associations between appendicitis and white cell count, neutrophil count, C-reactive protein, and bilirubin. Neutrophil count was the test with the highest sensitivity and negative predictive values, whereas bilirubin was the test with the highest specificity and positive predictive values (PPV). US and CT scans had high sensitivity and PPV for diagnosing appendicitis. No single test was sufficient to diagnose or exclude acute appendicitis by itself. Combining tests with high sensitivity (abnormal neutrophil count, and US and CT scans) and high specificity (raised bilirubin) may predict acute appendicitis more accurately.

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

PubMed

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

2016-09-01

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

The prediction of three-dimensional liquid-propellant rocket nozzle admittances

NASA Technical Reports Server (NTRS)

Bell, W. A.; Zinn, B. T.

1973-01-01

Crocco's three-dimensional nozzle admittance theory is extended to be applicable when the amplitudes of the combustor and nozzle oscillations increase or decrease with time. An analytical procedure and a computer program for determining nozzle admittance values from the extended theory are presented and used to compute the admittances of a family of liquid-propellant rocket nozzles. The calculated results indicate that the nozzle geometry entrance Mach number and temporal decay coefficient significantly affect the nozzle admittance values. The theoretical predictions are shown to be in good agreement with available experimental data.

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.

Prediction of regulatory gene pairs using dynamic time warping and gene ontology.

PubMed

Yang, Andy C; Hsu, Hui-Huang; Lu, Ming-Da; Tseng, Vincent S; Shih, Timothy K

2014-01-01

Selecting informative genes is the most important task for data analysis on microarray gene expression data. In this work, we aim at identifying regulatory gene pairs from microarray gene expression data. However, microarray data often contain multiple missing expression values. Missing value imputation is thus needed before further processing for regulatory gene pairs becomes possible. We develop a novel approach to first impute missing values in microarray time series data by combining k-Nearest Neighbour (KNN), Dynamic Time Warping (DTW) and Gene Ontology (GO). After missing values are imputed, we then perform gene regulation prediction based on our proposed DTW-GO distance measurement of gene pairs. Experimental results show that our approach is more accurate when compared with existing missing value imputation methods on real microarray data sets. Furthermore, our approach can also discover more regulatory gene pairs that are known in the literature than other methods.

Predicting fetal lung maturity by visual assessment of amniotic fluid turbidity: comparison with fluorescence polarization assay.

PubMed

Adair, C D; Sanchez-Ramos, L; McDyer, D L; Gaudier, F L; Del Valle, G O; Delke, I

1995-10-01

We prospectively studied 159 patients having clinically indicated amniocentesis. Amniotic fluid (3 to 5 mL) was placed in a nonheparinized glass tube. This sample was then classified as turbid (indicating maturity) or clear (indicating immaturity) on the basis of a single examiner's ability to read newspaper print through the glass tube. These results were then compared with fluorescence polarization values for the same sample. A value of 70 mg/g was considered positive evidence of fetal lung maturity. By study criteria, 62 samples (39%) indicated immaturity and 97 (61%) indicated maturity. Turbidity correctly identified 89 samples that produced fluorescence polarization values of at least 70 mg/g. Turbidity as a predictor of fetal lung maturity when compared with fluorescence polarization assay has a 91% positive and 87% negative predictive value. Visual inspection of amniotic fluid may be of value in areas where sophisticated methods are unavailable.

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

Risk Assessment Using Cytochrome P450 Time-Dependent Inhibition Assays at Single Time and Concentration in the Early Stage of Drug Discovery.

PubMed

Kosaka, Mai; Kosugi, Yohei; Hirabayashi, Hideki

2017-09-01

In this article, we proposed a risk assessment strategy for CYP3A time-dependent inhibition (TDI) during drug discovery based on a thorough retrospective study of 13 reference drugs, some of which are known to have in vitro TDI potential but have unknown clinical relevance. First, the traditional parameter k inact /K I , recommended by regulatory authorities for necessity decision making in clinical drug-drug interaction (DDI) studies, was investigated as a predictive index for clinical TDI liability. The cutoff value of 1.1 for k inact /K I , established by the Food and Drug Administration, tended to produce false-positive prediction results for clinical DDI occurrence. The value of 1.25 recommended in the European Medicines Evaluation Agency draft guideline yielded better predictions with only 1 false negative for diltiazem. Second, to enable earlier risk assessment, remaining activity, defined as the residual CYP3A activity in vitro obtained in the screening conditions, was investigated as an alternative index. As a result, the ratios of unbound C max or area under the curve to remaining activity precisely predicted clinical DDI occurrence. In conclusion, we demonstrated the predictive power of k inact /K I and remaining activity values for clinical DDIs. These findings provide insights that enable TDI risk assessment, even during drug discovery. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

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

Exponential analysis of the lung pressure-volume curve in patients with chronic pigeon-breeder's lung.

PubMed

Sansores, R; Perez-Padilla, R; Paré, P D; Selman, M

1992-05-01

Pigeon-breeder's lung (PBL) is extremely common in Mexico City and often progresses to irreversible pulmonary fibrosis. The exponential analysis of the lung pressure-volume (PV) curve (V = A - Be-kp) has been suggested as a method to separate the lung restriction caused by inflammation from that caused by pulmonary fibrosis; a significantly decreased value for the exponential constant, k, suggests a change in the mechanical properties of the functioning lung parenchyma, while a normal value accompanied by restriction suggests subtraction of lung units without a change in the mechanical properties of the functioning units. We measured lung volumes and static PV curves in 29 patients who had persistent lung restriction following a biopsy-proven diagnosis of PBL. Mean values in the 29 subjects were as follows: age, 43 +/- 13 years; TLC, 61 +/- 15 percent of predicted; VC, 46 +/- 19 percent of predicted; and k, 55 +/- 17 percent of predicted. Twenty-four of the 29 patients had values for k that were below the 95 percent confidence level, and five had "normal" values. There was no difference in TLC and VC (percent of predicted) between those with or without a decreased value for k. Four of five patients with a normal value for k improved subsequent to diagnosis, while only one of 21 patients with a decreased k improved. We conclude that increased lung elasticity manifested by a low value for k is common in patients with chronic PBL. These results support the observation of frequent irreversible lung fibrosis in these patients. Measurements of k could prove a good prognostic indicator at the time of initial diagnosis.

[Phenotypic trends and breeding values for canine congenital sensorineural deafness in Dalmatian dogs].

PubMed

Blum, Meike; Distl, Ottmar

2014-01-01

In the present study, breeding values for canine congenital sensorineural deafness, the presence of blue eyes and patches have been predicted using multivariate animal models to test the reliability of the breeding values for planned matings. The dataset consisted of 6669 German Dalmatian dogs born between 1988 and 2009. Data were provided by the Dalmatian kennel clubs which are members of the German Association for Dog Breeding and Husbandry (VDH). The hearing status for all dogs was evaluated using brainstem auditory evoked potentials. The reliability using the prediction error variance of breeding values and the realized reliability of the prediction of the phenotype of future progeny born in each one year between 2006 and 2009 were used as parameters to evaluate the goodness of prediction through breeding values. All animals from the previous birth years were used for prediction of the breeding values of the progeny in each of the up-coming birth years. The breeding values based on pedigree records achieved an average reliability of 0.19 for the future 1951 progeny. The predictive accuracy (R2) for the hearing status of single future progeny was at 1.3%. Combining breeding values for littermates increased the predictive accuracy to 3.5%. Corresponding values for maternal and paternal half-sib groups were at 3.2 and 7.3%. The use of breeding values for planned matings increases the phenotypic selection response over mass selection. The breeding values of sires may be used for planned matings because reliabilities and predictive accuracies for future paternal progeny groups were highest.

Impact damage of composite plates

NASA Technical Reports Server (NTRS)

Lal, K. M.; Goglia, G. L.

1983-01-01

A simple model to study low velocity transverse impact of thin plates made of fiber-reinforced composite material, in particular T300/5208 graphite-epoxy was discussed. This model predicts the coefficient of restitution, which is a measure of the energy absorbed by the target during an impact event. The model is constructed on the assumption that the plate is inextensible in the fiber direction and that the material is incompressible in the z-direction. Such a plate essentially deforms by shear, hence this model neglects bending deformations of the plate. The coefficient of restitution is predicted to increase with large interlaminar shear strength and low transverse shear modulus of the laminate. Predictions are compared with the test results of impacted circular and rectangular clamped plates. Experimentally measured values of the coefficient of restitution are found to agree with the predicted values within a reasonable error.

Pre-service teachers' perceived value of general pedagogical knowledge for practice: Relations with epistemic beliefs and source beliefs.

PubMed

Merk, Samuel; Rosman, Tom; Rueß, Julia; Syring, Marcus; Schneider, Jürgen

2017-01-01

Pre-service teachers tend to devalue general pedagogical knowledge (GPK) as a valid source for deriving successful teaching practices. The present study investigated beliefs about knowledge sources and epistemic beliefs as predictors for students' perceived value of GPK. Three pre-registered hypotheses were tested. We expected beliefs that GPK originates from scientific sources to entail a devaluation of GPK (Hypothesis 1). Concerning epistemic beliefs, we expected absolute beliefs to positively, and multiplistic beliefs to negatively predict pre-service teachers' perceived practical value of GPK (Hypothesis 2). Finally, we expected relationships between epistemic beliefs and pre-service teachers' perceived practical value of GPK to be confounded by epistemic trustworthiness, perceived topic-specific consistency and topic-specific familiarity (Hypothesis 3). In a study using a split plot design, 365 pre-service teachers were presented with four texts on different educational research topics. For each topic, three text versions were constructed. Even though they were invariant in content, these versions varied in a way that the results were allegedly generated by a practitioner, an expert or by means of a scientific study. Unexpectedly, results showed that research findings allegedly generated by means of a scientific study were associated with a higher perceived value of (topic-specific) GPK for practice (Hypothesis 1). As expected, the perceived value of GPK for practice was predicted by topic-specific multiplism and domain-specific absolutism (Hypothesis 2). These predictive effects were confounded by expertise evaluations of the source and the consistency of prior beliefs with the presented research results (Hypothesis 3). In summary, our results suggest that source beliefs might not be responsible for the devaluation of GPK, but that beliefs on the nature and structure of GPK (i.e., epistemic beliefs) might play an even more important role in this respect. Implications for research and practice are discussed.

Pre-service teachers’ perceived value of general pedagogical knowledge for practice: Relations with epistemic beliefs and source beliefs

PubMed Central

Rosman, Tom; Rueß, Julia; Syring, Marcus; Schneider, Jürgen

2017-01-01

Pre-service teachers tend to devalue general pedagogical knowledge (GPK) as a valid source for deriving successful teaching practices. The present study investigated beliefs about knowledge sources and epistemic beliefs as predictors for students’ perceived value of GPK. Three pre-registered hypotheses were tested. We expected beliefs that GPK originates from scientific sources to entail a devaluation of GPK (Hypothesis 1). Concerning epistemic beliefs, we expected absolute beliefs to positively, and multiplistic beliefs to negatively predict pre-service teachers’ perceived practical value of GPK (Hypothesis 2). Finally, we expected relationships between epistemic beliefs and pre-service teachers’ perceived practical value of GPK to be confounded by epistemic trustworthiness, perceived topic-specific consistency and topic-specific familiarity (Hypothesis 3). In a study using a split plot design, 365 pre-service teachers were presented with four texts on different educational research topics. For each topic, three text versions were constructed. Even though they were invariant in content, these versions varied in a way that the results were allegedly generated by a practitioner, an expert or by means of a scientific study. Unexpectedly, results showed that research findings allegedly generated by means of a scientific study were associated with a higher perceived value of (topic-specific) GPK for practice (Hypothesis 1). As expected, the perceived value of GPK for practice was predicted by topic-specific multiplism and domain-specific absolutism (Hypothesis 2). These predictive effects were confounded by expertise evaluations of the source and the consistency of prior beliefs with the presented research results (Hypothesis 3). In summary, our results suggest that source beliefs might not be responsible for the devaluation of GPK, but that beliefs on the nature and structure of GPK (i.e., epistemic beliefs) might play an even more important role in this respect. Implications for research and practice are discussed. PMID:28934358

Longitudinal association of short-term, metronome-paced heart rate variability and echocardiographically assessed cardiac structure at a 4-year follow-up: results from the prospective, population-based CARLA cohort.

PubMed

Medenwald, Daniel; Swenne, Cees A; Frantz, Stefan; Nuding, Sebastian; Kors, Jan A; Pietzner, Diana; Tiller, Daniel; Greiser, Karin H; Kluttig, Alexander; Haerting, Johannes

2017-12-01

To assess the value of cardiac structure/function in predicting heart rate variability (HRV) and the possibly predictive value of HRV on cardiac parameters. Baseline and 4-year follow-up data from the population-based CARLA cohort were used (790 men, 646 women, aged 45-83 years at baseline and 50-87 years at follow-up). Echocardiographic and HRV recordings were performed at baseline and at follow-up. Linear regression models with a quadratic term were used. Crude and covariate adjusted estimates were calculated. Missing values were imputed by means of multiple imputation. Heart rate variability measures taken into account consisted of linear time and frequency domain [standard deviation of normal-to-normal intervals (SDNN), high-frequency power (HF), low-frequency power (LF), LF/HF ratio] and non-linear measures [detrended fluctuation analysis (DFA1), SD1, SD2, SD1/SD2 ratio]. Echocardiographic parameters considered were ventricular mass index, diastolic interventricular septum thickness, left ventricular diastolic dimension, left atrial dimension systolic (LADS), and ejection fraction (Teichholz). A negative quadratic relation between baseline LADS and change in SDNN and HF was observed. The maximum HF and SDNN change (an increase of roughly 0.02%) was predicted at LADS of 3.72 and 3.57 cm, respectively, while the majority of subjects experienced a decrease in HRV. There was no association between further echocardiographic parameters and change in HRV, and there was no evidence of a predictive value of HRV in the prediction of changes in cardiac structure. In the general population, LADS predicts 4-year alteration in SDNN and HF non-linearly. Because of the novelty of the result, analyses should be replicated in other populations. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions please email: journals.permissions@oup.com.

Prediction of explosive yield and other characteristics of liquid rocket propellant explosions

NASA Technical Reports Server (NTRS)

Farber, E. A.; Smith, J. H.; Watts, E. H.

1973-01-01

Work which has been done at the University of Florida in arriving at credible explosive yield values for liquid rocket propellants is presented. The results are based upon logical methods which have been well worked out theoretically and verified through experimental procedures. Three independent methods to predict explosive yield values for liquid rocket propellants are described. All three give the same end result even though they utilize different parameters and procedures. They are: (1) mathematical model; (2) seven chart approach; and (3) critical mass method. A brief description of the methods, how they were derived, how they were applied, and the results which they produced are given. The experimental work used to support and verify the above methods both in the laboratory and in the field with actually explosive mixtures are presented. The methods developed are used and their value demonstrated in analyzing real problems, among them the destruct system of the Saturn 5, and the early configurations of the space shuttle.

Hints for new sources of flavour violation in meson mixing

NASA Astrophysics Data System (ADS)

Blanke, M.

2017-07-01

The recent results by the Fermilab-Lattice and MILC collaborations on the hadronic matrix elements entering B_{d,s} - bar{B}_{d,s} mixing show a significant tension of the measured values of the mass differences Δ M_{d,s} with their SM predictions. We review the implications of these results in the context of Constrained Minimal Flavour Violation models. In these models, the CKM elements γ and \\vert V_{ub}\\vert/\\vert V_{cb}\\vert can be determined from B_{d,s} - bar{B}_{d,s} mixing observables, yielding a prediction for γ below its tree-level value. Determining subsequently \\vert V_{cb}\\vert from the measured value of either Δ M_s or ɛ_K gives inconsistent results, with the tension being smallest in the Standard Model limit. This tension can be resolved if the flavour universality of new contributions to Δ F = 2 observables is broken. We briefly discuss the case of U(2)^3 flavour models as an illustrative example.

Triple Test in Carcinoma Breast

PubMed Central

Sameer; Mukherjee, Arindam

2014-01-01

Introduction: The commonest clinical presentation in majority of breast pathology is a lump. A definite diagnosis of breast lump is very important for the surgeon to decide on the final course of treatment and also saves the patient from unnecessary physical, emotional and psychological trauma if there is a definite preoperative diagnosis of benign lesion. The present study was done to evaluate the effectiveness and relevance of “TRIPLE TEST”in diagnosis of carcinoma breast in rural labour class population. Materials and Methods: The present study was a prospective study conducted on patients over 35 years of age having palpable breast lumps presenting in the out patient department of general surgery, ESI Hospital Basaidarapur New Delhi, India. The duration of study was from May 2007 to June 2009 and a total of 100 cases were studied. Each patient was subjected to a detailed history, clinical breast examination ,diagnostic mammography and FNAC. In this study, the results of each modality was divided in three groups: benign, suspicious and malignant. The sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of each test was calculated individually and as combined. Result: Out of 100 patients enrolled in this study, 60 cases were benign and 40 cases were of malignant breast disease. The age of patients with carcinoma breast in the series varied from 35 years to 70 years. The highest incidence of malignancy noted was 30% in 41-50 years age group (4th decade) followed by 27.5% in 51-60 years age group (5th decade). The sensitivity of clinical examination was found to be 75%, specificity was 83.3%, positive predictive value (PPV) of 75% and diagnostic accuracy of 80%. The sensitivity, specificity, positive predictive value and diagnostic accuracy of mammography was calculated and was found to be 94.9% , 90% , 86% and 92% respectively. The sensitivity, specificity, positive predictive value and diagnostic accuracy of FNAC was 94.7%, 98.3%, 97.3% and 96.6% respectively. Out of 100 cases triple test was concordant (all three test either benign or malignant) in 80 cases, all the benign cases detected by triple test were benign on final biopsy i.e. 100% specificity and 100% negative predictive value. Conclusion: TTS is an accurate and least invasive diagnostic test based on which definitive treatment can be initiated. PMID:25478391

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

USGS Publications Warehouse

Barks, C.S.

1996-01-01

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

Model-based predictions for dopamine.

PubMed

Langdon, Angela J; Sharpe, Melissa J; Schoenbaum, Geoffrey; Niv, Yael

2018-04-01

Phasic dopamine responses are thought to encode a prediction-error signal consistent with model-free reinforcement learning theories. However, a number of recent findings highlight the influence of model-based computations on dopamine responses, and suggest that dopamine prediction errors reflect more dimensions of an expected outcome than scalar reward value. Here, we review a selection of these recent results and discuss the implications and complications of model-based predictions for computational theories of dopamine and learning. Copyright © 2017. Published by Elsevier Ltd.

Turboexpander calculations using a generalized equation of state correlation

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

Han, M.S.; Starling, K.E.

1975-01-01

A generalized method for predicting the thermodynamic properties of natural gas fluids has been developed and tested. The results of several comparisons between thermodynamic property values predicted by the method and experimental data are presented. Comparisons of predicted and experimental vapor-liquid equilibrium are presented. These comparisons indicate that the generalized correlation can be used to predict many thermodynamic properties of natural gas and LNG. Turboexpander calculations are presented to show the utility of the generalized correlation for process design calculations.

Docking Based 3D-QSAR Study of Tricyclic Guanidine Analogues of Batzelladine K as anti-malarial agents

NASA Astrophysics Data System (ADS)

Ahmed, Nafees; Anwar, Sirajudheen; Thet Htar, Thet

2017-06-01

The Plasmodium falciparum Lactate Dehydrogenase enzyme (PfLDH) catalyzes inter-conversion of pyruvate to lactate during glycolysis producing the energy required for parasitic growth. The PfLDH has been studied as a potential molecular target for development of anti-malarial agents. In an attempt to find the potent inhibitor of PfLDH, we have used Discovery studio to perform molecular docking in the active binding pocket of PfLDH by CDOCKER, followed by three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of tricyclic guanidine batzelladine compounds, which were previously synthesized in our laboratory. Docking studies showed that there is a very strong correlation between in silico and in vitro results. Based on docking results, a highly predictive 3D-QSAR model was developed with q2 of 0.516. The model has predicted r2 of 0.91 showing that predicted IC50 values are in good agreement with experimental IC50 values. The results obtained from this study revealed the developed model can be used to design new anti-malarial compounds based on tricyclic guanidine derivatives and to predict activities of new inhibitors.

Docking Based 3D-QSAR Study of Tricyclic Guanidine Analogues of Batzelladine K As Anti-Malarial Agents.

PubMed

Ahmed, Nafees; Anwar, Sirajudheen; Thet Htar, Thet

2017-01-01

The Plasmodium falciparum Lactate Dehydrogenase enzyme ( Pf LDH) catalyzes inter-conversion of pyruvate to lactate during glycolysis producing the energy required for parasitic growth. The Pf LDH has been studied as a potential molecular target for development of anti-malarial agents. In an attempt to find the potent inhibitor of Pf LDH, we have used Discovery studio to perform molecular docking in the active binding pocket of Pf LDH by CDOCKER, followed by three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of tricyclic guanidine batzelladine compounds, which were previously synthesized in our laboratory. Docking studies showed that there is a very strong correlation between in silico and in vitro results. Based on docking results, a highly predictive 3D-QSAR model was developed with q 2 of 0.516. The model has predicted r 2 of 0.91 showing that predicted IC 50 values are in good agreement with experimental IC 50 values. The results obtained from this study revealed the developed model can be used to design new anti-malarial compounds based on tricyclic guanidine derivatives and to predict activities of new inhibitors.

Docking Based 3D-QSAR Study of Tricyclic Guanidine Analogues of Batzelladine K As Anti-Malarial Agents

PubMed Central

Ahmed, Nafees; Anwar, Sirajudheen; Thet Htar, Thet

2017-01-01

The Plasmodium falciparum Lactate Dehydrogenase enzyme (PfLDH) catalyzes inter-conversion of pyruvate to lactate during glycolysis producing the energy required for parasitic growth. The PfLDH has been studied as a potential molecular target for development of anti-malarial agents. In an attempt to find the potent inhibitor of PfLDH, we have used Discovery studio to perform molecular docking in the active binding pocket of PfLDH by CDOCKER, followed by three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of tricyclic guanidine batzelladine compounds, which were previously synthesized in our laboratory. Docking studies showed that there is a very strong correlation between in silico and in vitro results. Based on docking results, a highly predictive 3D-QSAR model was developed with q2 of 0.516. The model has predicted r2 of 0.91 showing that predicted IC50 values are in good agreement with experimental IC50 values. The results obtained from this study revealed the developed model can be used to design new anti-malarial compounds based on tricyclic guanidine derivatives and to predict activities of new inhibitors. PMID:28664157

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.

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.

Forecasting impact injuries of unrestrained occupants in railway vehicle passenger compartments.

PubMed

Xie, Suchao; Zhou, Hui

2014-01-01

In order to predict the injury parameters of the occupants corresponding to different experimental parameters and to determine impact injury indices conveniently and efficiently, a model forecasting occupant impact injury was established in this work. The work was based on finite experimental observation values obtained by numerical simulation. First, the various factors influencing the impact injuries caused by the interaction between unrestrained occupants and the compartment's internal structures were collated and the most vulnerable regions of the occupant's body were analyzed. Then, the forecast model was set up based on a genetic algorithm-back propagation (GA-BP) hybrid algorithm, which unified the individual characteristics of the back propagation-artificial neural network (BP-ANN) model and the genetic algorithm (GA). The model was well suited to studies of occupant impact injuries and allowed multiple-parameter forecasts of the occupant impact injuries to be realized assuming values for various influencing factors. Finally, the forecast results for three types of secondary collision were analyzed using forecasting accuracy evaluation methods. All of the results showed the ideal accuracy of the forecast model. When an occupant faced a table, the relative errors between the predicted and experimental values of the respective injury parameters were kept within ± 6.0 percent and the average relative error (ARE) values did not exceed 3.0 percent. When an occupant faced a seat, the relative errors between the predicted and experimental values of the respective injury parameters were kept within ± 5.2 percent and the ARE values did not exceed 3.1 percent. When the occupant faced another occupant, the relative errors between the predicted and experimental values of the respective injury parameters were kept within ± 6.3 percent and the ARE values did not exceed 3.8 percent. The injury forecast model established in this article reduced repeat experiment times and improved the design efficiency of the internal compartment's structure parameters, and it provided a new way for assessing the safety performance of the interior structural parameters in existing, and newly designed, railway vehicle compartments.

Predictive values of egg-specific IgE by two commonly used assay systems for the diagnosis of egg allergy in young children: a prospective multicenter study.

PubMed

Furuya, K; Nagao, M; Sato, Y; Ito, S; Fujisawa, T

2016-10-01

Specific IgE (sIgE) is often used to predict oral food challenge (OFC) outcomes in food allergy, but interpretation of the results may vary depending on the assay method employed and the patient population tested. The aim of this study was to use two commercial assay systems to determine egg-sIgE values predictive of allergy within the most common populations treated at pediatric clinics. In a multicenter prospective study, 433 children with suspected or confirmed egg allergy underwent oral challenge (OFC) using cooked egg (CE) and raw egg (RE) powders to diagnose either true allergy in 1-year-old (group A, n = 220) or tolerance in 2- to 6-year-old (group B, n = 213). Egg white (EW)- and ovomucoid (OM)-sIgE values were measured using the ImmunoCAP(®) sIgE (ImmunoCAP) and the IMMULITE(®) 2000 3 gAllergy(™) (3gAllergy) systems. Children were recruited from six primary care clinics and 18 hospitals in Japan. Receiver-operating characteristic (ROC) curve analysis yielded similar areas under the curve (AUC) for the two assays (0.7-0.8). The optimal cutoff values and the probability curves (PCs) of the sIgE by the two assays to predict CE and RE OFC outcomes were determined for both groups. Values for 3gAllergy were higher than for ImmunoCAP; however, correlation of sIgE and predicted probability calculated by PCs were strong between the two methods. Cutoff values and PCs for egg-sIgE established using both ImmunoCAP and 3gAllergy may be useful for predicting egg allergy in early childhood patient populations. © 2016 The Authors. Allergy Published by John Wiley & Sons Ltd.

Comparative Study of foF2 Measurements with IRI-2007 Model Predictions During Extended Solar Minimum

NASA Technical Reports Server (NTRS)

Zakharenkova, I. E.; Krankowski, A.; Bilitza, D.; Cherniak, Iu.V.; Shagimuratov, I.I.; Sieradzki, R.

2013-01-01

The unusually deep and extended solar minimum of cycle 2324 made it very difficult to predict the solar indices 1 or 2 years into the future. Most of the predictions were proven wrong by the actual observed indices. IRI gets its solar, magnetic, and ionospheric indices from an indices file that is updated twice a year. In recent years, due to the unusual solar minimum, predictions had to be corrected downward with every new indices update. In this paper we analyse how much the uncertainties in the predictability of solar activity indices affect the IRI outcome and how the IRI values calculated with predicted and observed indices compared to the actual measurements.Monthly median values of F2 layer critical frequency (foF2) derived from the ionosonde measurements at the mid-latitude ionospheric station Juliusruh were compared with the International Reference Ionosphere (IRI-2007) model predictions. The analysis found that IRIprovides reliable results that compare well with actual measurements, when the definite (observed and adjusted) indices of solar activityare used, while IRI values based on earlier predictions of these indices noticeably overestimated the measurements during the solar minimum.One of the principal objectives of this paper is to direct attention of IRI users to update their solar activity indices files regularly.Use of an older index file can lead to serious IRI overestimations of F-region electron density during the recent extended solar minimum.

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

PubMed

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

2018-04-01

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

Discussion about different cut-off values of conventional hamstring-to-quadriceps ratio used in hamstring injury prediction among professional male football players

PubMed Central

Michałowska, Martyna; Walczak, Tomasz; Owen, Adam; Grabski, Jakub Krzysztof; Pyda, Andrzej; Piontek, Tomasz; Kotwicki, Tomasz

2017-01-01

Objective To measure the sensitivity and specificity of differences cut-off values for isokinetic Hcon/Qcon ratio in order to improve the capacity to evaluate (retrospectively) the injury of hamstring muscles in professional soccer screened with knee isokinetic tests. Design Retrospective study. Methods Medical and biomechanical data of professional football players playing for the same team for at least one season between 2010 and 2016 were analysed. Hamstring strain injury cases and the reports generated via isokinetic testing were investigated. Isokinetic concentric(con) hamstring(H) and quadriceps(Q) absolute strength in addition with Hcon/Qcon ratio were examined for the injured versus uninjured limbs among injured players, and for the injured and non-injured players. 2 x 2 contingency table was used for comparing variables: predicted injured or predicted uninjured with actual injured or actual uninjured. Sensitivity, specificity, accuracy, positive and negative predictive values, and positive and negative likelihood ratio were calculated for three different cut-off values (0.47 vs. 0.6 vs. 0.658) to compare the discriminative power of an isokinetic test, whilst examining the key value of Hcon/Qcon ratio which may indicate the highest level of ability to predispose a player to injury. McNemar’s chi2 test with Yates’s correction was used to determine agreement between the tests. PQStat software was used for all statistical analysis, and an alpha level of p <0.05 was used for all statistical comparisons. Results 340 isokinetic test reports on both limbs of 66 professional soccer players were analysed. Eleven players suffered hamstring injuries during the analysed period. None of these players sustained recurrence of hamstring injury. One player sustained hamstring strain injury on both legs, thus the total number of injuries was 12. Application of different cut-off values for Hcon/Qcon significantly affected the sensitivity and specificity of isokinetic test used as a tool for muscle injury detection. The use of 0.47 of Hcon/Qcon as a discriminate value resulted in significantly lower sensitivity when compared to 0.658 threshold (sensitivity of 16.7% vs. 91.7%, respectively; t = 6.125,p = 0.0133). Calculated values of specificity (when three different cut-off were applied) were also significantly different. Threshold of 0.6 of Hcon/Qcon resulted with significantly lower specificity compared to 0.47 value (specificity of 46.9% vs. 94.5%, respectively; t = 153.0,p<0.0001), and significantly higher specificity when compared to 0.658 (specificity of 46.9% vs. 24.1%, respectively; t = 229.0, p<0.0001). Conclusion The use of different cut-off values for Hcon/Qcon significantly affected the sensitivity and specificity of isokinetic testing. The interpretation of usefulness of isokinetic test as a screening tool in a group of male professional football players to predict hamstring injury occurrence within the next 12 months might be therefore significantly biased due to the different threshold values of Hcon/Qcon. Using one “normative” value as a cut-off (e.g. 0.47 or 0.60, or 0.658) to quantify soccer players (or not) to the group with a higher risk of knee injury might result in biased outcomes due to the natural strength asymmetry that is observed within the group of soccer players. PMID:29216241

Fragment based group QSAR and molecular dynamics mechanistic studies on arylthioindole derivatives targeting the α-β interfacial site of human tubulin

PubMed Central

2014-01-01

Background A number of microtubule disassembly blocking agents and inhibitors of tubulin polymerization have been elements of great interest in anti-cancer therapy, some of them even entering into the clinical trials. One such class of tubulin assembly inhibitors is of arylthioindole derivatives which results in effective microtubule disorganization responsible for cell apoptosis by interacting with the colchicine binding site of the β-unit of tubulin close to the interface with the α unit. We modelled the human tubulin β unit (chain D) protein and performed docking studies to elucidate the detailed binding mode of actions associated with their inhibition. The activity enhancing structural aspects were evaluated using a fragment-based Group QSAR (G-QSAR) model and was validated statistically to determine its robustness. A combinatorial library was generated keeping the arylthioindole moiety as the template and their activities were predicted. Results The G-QSAR model obtained was statistically significant with r2 value of 0.85, cross validated correlation coefficient q2 value of 0.71 and pred_r2 (r2 value for test set) value of 0.89. A high F test value of 65.76 suggests robustness of the model. Screening of the combinatorial library on the basis of predicted activity values yielded two compounds HPI (predicted pIC50 = 6.042) and MSI (predicted pIC50 = 6.001) whose interactions with the D chain of modelled human tubulin protein were evaluated in detail. A toxicity evaluation resulted in MSI being less toxic in comparison to HPI. Conclusions The study provides an insight into the crucial structural requirements and the necessary chemical substitutions required for the arylthioindole moiety to exhibit enhanced inhibitory activity against human tubulin. The two reported compounds HPI and MSI showed promising anti cancer activities and thus can be considered as potent leads against cancer. The toxicity evaluation of these compounds suggests that MSI is a promising therapeutic candidate. This study provided another stepping stone in the direction of evaluating tubulin inhibition and microtubule disassembly degeneration as viable targets for development of novel therapeutics against cancer. PMID:25521775

[Detection of the main quality indicators in red wine with infrared spectroscopy based on FastICA and neural network].

PubMed

Fang, Li-Min; Lin, Min

2009-08-01

For the rapid detection of the ethanol, pH and rest sugar in red wine, infrared (IR) spectra of 44 wine samples were analyzed. The algorithm of fast independent component analysis (FastICA) was used to decompose the data of IR spectra, and their independent components and the mixing matrix were obtained. Then, the ICA-NNR calibration model with three-level artificial neural network (ANN) structure was built by using back-propagation (BP) algorithm. The models were used to estimate the contents of ethanol, pH and rest sugar in red wine samples for both in calibration set and predicted set. Correlation coefficient (r) of prediction and root mean square error of prediction (RMSEP) were used as the evaluation indexes. The results indicate that the r and RMSEP for the prediction of ethanol content, pH and rest sugar content are 0.953, 0.983 and 0.994, and 0.161, 0.017 and 0.181, respectively. The maximum relative deviations between the ICA-NNR method predicted value and referenced value of the 22 samples in predicted set are less than 4%. The results of this paper provide a foundation for the application and further development of IR on-line red wine analyzer.

Comparison of Measured and Predicted Bioconcentration Estimates of Pharmaceuticals in Fish Plasma and Prediction of Chronic Risk.

PubMed

Nallani, Gopinath; Venables, Barney; Constantine, Lisa; Huggett, Duane

2016-05-01

Evaluation of the environmental risk of human pharmaceuticals is now a mandatory component in all new drug applications submitted for approval in EU. With >3000 drugs currently in use, it is not feasible to test each active ingredient, so prioritization is key. A recent review has listed nine prioritization approaches including the fish plasma model (FPM). The present paper focuses on comparison of measured and predicted fish plasma bioconcentration factors (BCFs) of four common over-the-counter/prescribed pharmaceuticals: norethindrone (NET), ibuprofen (IBU), verapamil (VER) and clozapine (CLZ). The measured data were obtained from the earlier published fish BCF studies. The measured BCF estimates of NET, IBU, VER and CLZ were 13.4, 1.4, 0.7 and 31.2, while the corresponding predicted BCFs (based log Kow at pH 7) were 19, 1.0, 7.6 and 30, respectively. These results indicate that the predicted BCFs matched well the measured values. The BCF estimates were used to calculate the human: fish plasma concentration ratios of each drug to predict potential risk to fish. The plasma ratio results show the following order of risk potential for fish: NET > CLZ > VER > IBU. The FPM has value in prioritizing pharmaceutical products for ecotoxicological assessments.

Integrating qPLM and biomechanical test data with an anisotropic fiber distribution model and predictions of TGF-β1 and IGF-1 regulation of articular cartilage fiber modulus

PubMed Central

Stender, Michael E.; Raub, Christopher B.; Yamauchi, Kevin A.; Shirazi, Reza; Vena, Pasquale; Sah, Robert L.; Hazelwood, Scott J.; Klisch, Stephen M.

2013-01-01

A continuum mixture model with distinct collagen (COL) and glycosaminoglycan (GAG) elastic constituents was developed for the solid matrix of immature bovine articular cartilage. A continuous COL fiber volume fraction distribution function and a true COL fiber elastic modulus (Ef) were used. Quantitative polarized light microscopy (qPLM) methods were developed to account for the relatively high cell density of immature articular cartilage and used with a novel algorithm that constructs a 3D distribution function from 2D qPLM data. For specimens untreated and cultured in vitro, most model parameters were specified from qPLM analysis and biochemical assay results; consequently, Ef was predicted using an optimization to measured mechanical properties in uniaxial tension and unconfined compression. Analysis of qPLM data revealed a highly anisotropic fiber distribution, with principal fiber orientation parallel to the surface layer. For untreated samples, predicted Ef values were 175 and 422 MPa for superficial (S) and middle (M) zone layers, respectively. TGF-β1 treatment was predicted to increase and decrease Ef values for the S and M layers to 281 and 309 MPa, respectively. IGF-1 treatment was predicted to decrease Ef values for the S and M layers to 22 and 26 MPa, respectively. A novel finding was that distinct native depth-dependent fiber modulus properties were modulated to nearly homogeneous values by TGF-β1 and IGF-1 treatments, with modulated values strongly dependent on treatment. PMID:23266906

Prediction of strain values in reinforcements and concrete of a RC frame using neural networks

NASA Astrophysics Data System (ADS)

Vafaei, Mohammadreza; Alih, Sophia C.; Shad, Hossein; Falah, Ali; Halim, Nur Hajarul Falahi Abdul

2018-03-01

The level of strain in structural elements is an important indicator for the presence of damage and its intensity. Considering this fact, often structural health monitoring systems employ strain gauges to measure strains in critical elements. However, because of their sensitivity to the magnetic fields, inadequate long-term durability especially in harsh environments, difficulties in installation on existing structures, and maintenance cost, installation of strain gauges is not always possible for all structural components. Therefore, a reliable method that can accurately estimate strain values in critical structural elements is necessary for damage identification. In this study, a full-scale test was conducted on a planar RC frame to investigate the capability of neural networks for predicting the strain values. Two neural networks each of which having a single hidden layer was trained to relate the measured rotations and vertical displacements of the frame to the strain values measured at different locations of the frame. Results of trained neural networks indicated that they accurately estimated the strain values both in reinforcements and concrete. In addition, the trained neural networks were capable of predicting strains for the unseen input data set.

The effect of geographical indices on left ventricular structure in healthy Han Chinese population

NASA Astrophysics Data System (ADS)

Cen, Minyi; Ge, Miao; Liu, Yonglin; Wang, Congxia; Yang, Shaofang

2017-02-01

The left ventricular posterior wall thickness (LVPWT) and interventricular septum thickness (IVST) are generally regarded as the functional parts of the left ventricular (LV) structure. This paper aims to examine the effects of geographical indices on healthy Han adults' LV structural indices and to offer a scientific basis for developing a unified standard for the reference values of adults' LV structural indices in China. Fifteen terrain, climate, and soil indices were examined as geographical explanatory variables. Statistical analysis was performed using correlation analysis. Moreover, a back propagation neural network (BPNN) and a support vector regression (SVR) were applied to developing models to predict the values of two indices. After the prediction models were built, distribution maps were produced. The results show that LV structural indices are characteristically associated with latitude, longitude, altitude, average temperature, average wind velocity, topsoil sand fraction, topsoil silt fraction, topsoil organic carbon, and topsoil sodicity. The model test analyses show the BPNN model possesses better simulative and predictive ability in comparison with the SVR model. The distribution maps of the LV structural indices show that, in China, the values are higher in the west and lower in the east. These results demonstrate that the reference values of the adults' LV structural indices will be different affected by different geographical environment. The reference values of LV structural indices in one region can be calculated by setting up a BPNN, which showed better applicability in this study. The distribution of the reference values of the LV structural indices can be seen clearly on the geographical distribution map.

The effect of geographical indices on left ventricular structure in healthy Han Chinese population.

PubMed

Cen, Minyi; Ge, Miao; Liu, Yonglin; Wang, Congxia; Yang, Shaofang

2017-02-01

The left ventricular posterior wall thickness (LVPWT) and interventricular septum thickness (IVST) are generally regarded as the functional parts of the left ventricular (LV) structure. This paper aims to examine the effects of geographical indices on healthy Han adults' LV structural indices and to offer a scientific basis for developing a unified standard for the reference values of adults' LV structural indices in China. Fifteen terrain, climate, and soil indices were examined as geographical explanatory variables. Statistical analysis was performed using correlation analysis. Moreover, a back propagation neural network (BPNN) and a support vector regression (SVR) were applied to developing models to predict the values of two indices. After the prediction models were built, distribution maps were produced. The results show that LV structural indices are characteristically associated with latitude, longitude, altitude, average temperature, average wind velocity, topsoil sand fraction, topsoil silt fraction, topsoil organic carbon, and topsoil sodicity. The model test analyses show the BPNN model possesses better simulative and predictive ability in comparison with the SVR model. The distribution maps of the LV structural indices show that, in China, the values are higher in the west and lower in the east. These results demonstrate that the reference values of the adults' LV structural indices will be different affected by different geographical environment. The reference values of LV structural indices in one region can be calculated by setting up a BPNN, which showed better applicability in this study. The distribution of the reference values of the LV structural indices can be seen clearly on the geographical distribution map.

A transient dopamine signal encodes subjective value and causally influences demand in an economic context

PubMed Central

Schelp, Scott A.; Pultorak, Katherine J.; Rakowski, Dylan R.; Gomez, Devan M.; Krzystyniak, Gregory; Das, Raibatak; Oleson, Erik B.

2017-01-01

The mesolimbic dopamine system is strongly implicated in motivational processes. Currently accepted theories suggest that transient mesolimbic dopamine release events energize reward seeking and encode reward value. During the pursuit of reward, critical associations are formed between the reward and cues that predict its availability. Conditioned by these experiences, dopamine neurons begin to fire upon the earliest presentation of a cue, and again at the receipt of reward. The resulting dopamine concentration scales proportionally to the value of the reward. In this study, we used a behavioral economics approach to quantify how transient dopamine release events scale with price and causally alter price sensitivity. We presented sucrose to rats across a range of prices and modeled the resulting demand curves to estimate price sensitivity. Using fast-scan cyclic voltammetry, we determined that the concentration of accumbal dopamine time-locked to cue presentation decreased with price. These data confirm and extend the notion that dopamine release events originating in the ventral tegmental area encode subjective value. Using optogenetics to augment dopamine concentration, we found that enhancing dopamine release at cue made demand more sensitive to price and decreased dopamine concentration at reward delivery. From these observations, we infer that value is decreased because of a negative reward prediction error (i.e., the animal receives less than expected). Conversely, enhancing dopamine at reward made demand less sensitive to price. We attribute this finding to a positive reward prediction error, whereby the animal perceives they received a better value than anticipated. PMID:29109253

The Tridimensional Personality Questionnaire as a predictor of relapse in detoxified alcohol dependents. The European Fluvoxamine in Alcoholism Study Group.

PubMed

Meszaros, K; Lenzinger, E; Hornik, K; Füreder, T; Willinger, U; Fischer, G; Schönbeck, G; Aschauer, H N

1999-03-01

Personality traits have been found as strong predictors for treatment response in different psychiatric disorders. We administered the Tridimensional Personality Questionnaire, which measures the three personality dimensions: novelty seeking, harm avoidance (HA), and reward dependence, as introduced by Cloninger in a multicenter study (11 centers in the United Kingdom, Eire, Switzerland, and Austria) with detoxified alcohol-dependent patients (n = 521). The objective of this study was to evaluate a possible predictive value of these three dimensions on relapse over 1 -year follow up. A logistic regression analysis showed that novelty seeking is a strong predictor for relapse in detoxified male alcoholics (p = 0.0007; p values adjusted for treatment), but not in females. In both sexes, HA and reward dependence were of no predictive value. However, we found a trend for significance of HA for predicting "early" relapse (4 weeks) in females (p = 0.074). Our results show that Tridimensional Personality Questionnaire personality traits have direct clinical applications for prediction of relapse in detoxified alcohol dependents and indicate the necessity of additional therapeutic treatment in risk groups.

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

PubMed

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

2010-10-01

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

2D dynamic studies combined with the surface curvature analysis to predict Arias Intensity amplification

NASA Astrophysics Data System (ADS)

Torgoev, Almaz; Havenith, Hans-Balder

2016-07-01

A 2D elasto-dynamic modelling of the pure topographic seismic response is performed for six models with a total length of around 23.0 km. These models are reconstructed from the real topographic settings of the landslide-prone slopes situated in the Mailuu-Suu River Valley, Southern Kyrgyzstan. The main studied parameter is the Arias Intensity (Ia, m/sec), which is applied in the GIS-based Newmark method to regionally map the seismically-induced landslide susceptibility. This method maps the Ia values via empirical attenuation laws and our studies investigate a potential to include topographic input into them. Numerical studies analyse several signals with varying shape and changing central frequency values. All tests demonstrate that the spectral amplification patterns directly affect the amplification of the Ia values. These results let to link the 2D distribution of the topographically amplified Ia values with the parameter called as smoothed curvature. The amplification values for the low-frequency signals are better correlated with the curvature smoothed over larger spatial extent, while those values for the high-frequency signals are more linked to the curvature with smaller smoothing extent. The best predictions are provided by the curvature smoothed over the extent calculated according to Geli's law. The sample equations predicting the Ia amplification based on the smoothed curvature are presented for the sinusoid-shape input signals. These laws cannot be directly implemented in the regional Newmark method, as 3D amplification of the Ia values addresses more problem complexities which are not studied here. Nevertheless, our 2D results prepare the theoretical framework which can potentially be applied to the 3D domain and, therefore, represent a robust basis for these future research targets.

Performance characteristics of prostate-specific antigen density and biopsy core details to predict oncological outcome in patients with intermediate to high-risk prostate cancer underwent robot-assisted radical prostatectomy.

PubMed

Yashi, Masahiro; Nukui, Akinori; Tokura, Yuumi; Takei, Kohei; Suzuki, Issei; Sakamoto, Kazumasa; Yuki, Hideo; Kambara, Tsunehito; Betsunoh, Hironori; Abe, Hideyuki; Fukabori, Yoshitatsu; Nakazato, Yoshimasa; Kaji, Yasushi; Kamai, Takao

2017-06-23

Many urologic surgeons refer to biopsy core details for decision making in cases of localized prostate cancer (PCa) to determine whether an extended resection and/or lymph node dissection should be performed. Furthermore, recent reports emphasize the predictive value of prostate-specific antigen density (PSAD) for further risk stratification, not only for low-risk PCa, but also for intermediate- and high-risk PCa. This study focused on these parameters and compared respective predictive impact on oncologic outcomes in Japanese PCa patients. Two-hundred and fifty patients with intermediate- and high-risk PCa according to the National Comprehensive Cancer Network (NCCN) classification, that underwent robot-assisted radical prostatectomy at a single institution, and with observation periods of longer than 6 months were enrolled. None of the patients received hormonal treatments including antiandrogens, luteinizing hormone-releasing hormone analogues, or 5-alpha reductase inhibitors preoperatively. PSAD and biopsy core details, including the percentage of positive cores and the maximum percentage of cancer extent in each positive core, were analyzed in association with unfavorable pathologic results of prostatectomy specimens, and further with biochemical recurrence. The cut-off values of potential predictive factors were set through receiver-operating characteristic curve analyses. In the entire cohort, a higher PSAD, the percentage of positive cores, and maximum percentage of cancer extent in each positive core were independently associated with advanced tumor stage ≥ pT3 and an increased index tumor volume > 0.718 ml. NCCN classification showed an association with a tumor stage ≥ pT3 and a Gleason score ≥8, and the attribution of biochemical recurrence was also sustained. In each NCCN risk group, these preoperative factors showed various associations with unfavorable pathological results. In the intermediate-risk group, the percentage of positive cores showed an independent predictive value for biochemical recurrence. In the high-risk group, PSAD showed an independent predictive value. PSAD and biopsy core details have different performance characteristics for the prediction of oncologic outcomes in each NCCN risk group. Despite the need for further confirmation of the results with a larger cohort and longer observation, these factors are important as preoperative predictors in addition to the NCCN classification for a urologic surgeon to choose a surgical strategy.

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.

Total motile sperm count has a superior predictive value over the WHO 2010 cut-off values for the outcomes of intracytoplasmic sperm injection cycles.

PubMed

Borges, E; Setti, A S; Braga, D P A F; Figueira, R C S; Iaconelli, A

2016-09-01

The objective of this study was to compare (i) the intracytoplasmic sperm injection outcomes among groups with different total motile sperm count ranges, (ii) the intracytoplasmic sperm injection outcomes between groups with normal and abnormal total motile sperm count, and (iii) the predictive values of WHO 2010 cut-off values and pre-wash total motile sperm count for the intracytoplasmic sperm injection outcomes, in couples with male infertility. This study included data from 518 patients undergoing their first intracytoplasmic sperm injection cycle as a result of male infertility. Couples were divided into five groups according to their total motile sperm count: Group I, total motile sperm count <1 × 10(6) ; group II, total motile sperm count 1-5 × 10(6) ; group III, total motile sperm count 5-10 × 10(6) ; group IV, total motile sperm count 10-20 × 10(6) ; and group V, total motile sperm count >20 × 10(6) (which was considered a normal total motile sperm count value). Then, couples were grouped into an abnormal and normal total motile sperm count group. The groups were compared regarding intracytoplasmic sperm injection outcomes. The predictive values of WHO 2010 cut-off values and total motile sperm count for the intracytoplasmic sperm injection outcomes were also investigated. The fertilization rate was lower in total motile sperm count group I compared to total motile sperm count group V (72.5 ± 17.6 vs. 84.9 ± 14.4, p = 0.011). The normal total motile sperm count group had a higher fertilization rate (84.9 ± 14.4 vs. 81.1 ± 15.8, p = 0.016) and lower miscarriage rate (17.9% vs. 29.5%, p = 0.041) compared to the abnormal total motile sperm count group. The total motile sperm count was the only parameter that demonstrated a predictive value for the formation of high-quality embryos on D2 (OR: 1.18, p = 0.013), formation of high-quality embryos on D3 (OR: 1.12, p = 0.037), formation of blastocysts on D5 (OR: 1.16, p = 0.011), blastocyst expansion grade on D5 (OR: 1.27, p = 0.042), and the odds of miscarriage (OR: 0.52, p < 0.045). The total motile sperm count has a greater predictive value than the WHO 2010 cut-off values for laboratory results and pregnancy outcomes in couples undergoing intracytoplasmic sperm injection as a result of male infertility. © 2016 American Society of Andrology and European Academy of Andrology.

The predictive value of 2-year posttreatment biopsy after prostate cancer radiotherapy for eventual biochemical outcome

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

Vance, Waseet; Tucker, Susan L.; Crevoisier, Renaud de

2007-03-01

Purpose: To determine the value of a 2-year post-radiotherapy (RT) prostate biopsy for predicting eventual biochemical failure in patients who were treated for localized prostate cancer. Methods and Materials: This study comprised 164 patients who underwent a planned 2-year post-RT prostate biopsy. The independent prognostic value of the biopsy results for forecasting eventual biochemical outcome and overall survival was tested with other factors (the Gleason score, 1992 American Joint Committee on Cancer tumor stage, pretreatment prostate-specific antigen level, risk group, and RT dose) in a multivariate analysis. The current nadir + 2 (CN + 2) definition of biochemical failure wasmore » used. Patients with rising prostate-specific antigen (PSA) or suspicious digital rectal examination before the biopsy were excluded. Results: The biopsy results were normal in 78 patients, scant atypical and malignant cells in 30, carcinoma with treatment effect in 43, and carcinoma without treatment effect in 13. Using the CN + 2 definition, we found a significant association between biopsy results and eventual biochemical failure. We also found that the biopsy status provides predictive information independent of the PSA status at the time of biopsy. Conclusion: A 2-year post-RT prostate biopsy may be useful for forecasting CN + 2 biochemical failure. Posttreatment prostate biopsy may be useful for identifying patients for aggressive salvage therapy.« less

Predictors of Cultural Values Conflict for Asian Indian Women

ERIC Educational Resources Information Center

Kaduvettoor-Davidson, Anju; Inman, Arpana G.

2012-01-01

This study explored the relationship between the family environments and coping styles and the cultural values conflicts of 110 Asian Indian women. Results indicated that women perceiving supportive family environments had less sex role conflict. Additionally, avoidant and emotion-focused coping predicted high conflict regarding intimate relations…

Virtual World Currency Value Fluctuation Prediction System Based on User Sentiment Analysis.

PubMed

Kim, Young Bin; Lee, Sang Hyeok; Kang, Shin Jin; Choi, Myung Jin; Lee, Jung; Kim, Chang Hun

2015-01-01

In this paper, we present a method for predicting the value of virtual currencies used in virtual gaming environments that support multiple users, such as massively multiplayer online role-playing games (MMORPGs). Predicting virtual currency values in a virtual gaming environment has rarely been explored; it is difficult to apply real-world methods for predicting fluctuating currency values or shares to the virtual gaming world on account of differences in domains between the two worlds. To address this issue, we herein predict virtual currency value fluctuations by collecting user opinion data from a virtual community and analyzing user sentiments or emotions from the opinion data. The proposed method is straightforward and applicable to predicting virtual currencies as well as to gaming environments, including MMORPGs. We test the proposed method using large-scale MMORPGs and demonstrate that virtual currencies can be effectively and efficiently predicted with it.

Virtual World Currency Value Fluctuation Prediction System Based on User Sentiment Analysis

PubMed Central

Kim, Young Bin; Lee, Sang Hyeok; Kang, Shin Jin; Choi, Myung Jin; Lee, Jung; Kim, Chang Hun

2015-01-01

In this paper, we present a method for predicting the value of virtual currencies used in virtual gaming environments that support multiple users, such as massively multiplayer online role-playing games (MMORPGs). Predicting virtual currency values in a virtual gaming environment has rarely been explored; it is difficult to apply real-world methods for predicting fluctuating currency values or shares to the virtual gaming world on account of differences in domains between the two worlds. To address this issue, we herein predict virtual currency value fluctuations by collecting user opinion data from a virtual community and analyzing user sentiments or emotions from the opinion data. The proposed method is straightforward and applicable to predicting virtual currencies as well as to gaming environments, including MMORPGs. We test the proposed method using large-scale MMORPGs and demonstrate that virtual currencies can be effectively and efficiently predicted with it. PMID:26241496

Application of Artificial Neural Network and Support Vector Machines in Predicting Metabolizable Energy in Compound Feeds for Pigs.

PubMed

Ahmadi, Hamed; Rodehutscord, Markus

2017-01-01

In the nutrition literature, there are several reports on the use of artificial neural network (ANN) and multiple linear regression (MLR) approaches for predicting feed composition and nutritive value, while the use of support vector machines (SVM) method as a new alternative approach to MLR and ANN models is still not fully investigated. The MLR, ANN, and SVM models were developed to predict metabolizable energy (ME) content of compound feeds for pigs based on the German energy evaluation system from analyzed contents of crude protein (CP), ether extract (EE), crude fiber (CF), and starch. A total of 290 datasets from standardized digestibility studies with compound feeds was provided from several institutions and published papers, and ME was calculated thereon. Accuracy and precision of developed models were evaluated, given their produced prediction values. The results revealed that the developed ANN [ R 2  = 0.95; root mean square error (RMSE) = 0.19 MJ/kg of dry matter] and SVM ( R 2  = 0.95; RMSE = 0.21 MJ/kg of dry matter) models produced better prediction values in estimating ME in compound feed than those produced by conventional MLR ( R 2  = 0.89; RMSE = 0.27 MJ/kg of dry matter). The developed ANN and SVM models produced better prediction values in estimating ME in compound feed than those produced by conventional MLR; however, there were not obvious differences between performance of ANN and SVM models. Thus, SVM model may also be considered as a promising tool for modeling the relationship between chemical composition and ME of compound feeds for pigs. To provide the readers and nutritionist with the easy and rapid tool, an Excel ® calculator, namely, SVM_ME_pig, was created to predict the metabolizable energy values in compound feeds for pigs using developed support vector machine model.

A study on the predictability of acute lymphoblastic leukaemia response to treatment using a hybrid oncosimulator.

PubMed

Ouzounoglou, Eleftherios; Kolokotroni, Eleni; Stanulla, Martin; Stamatakos, Georgios S

2018-02-06

Efficient use of Virtual Physiological Human (VPH)-type models for personalized treatment response prediction purposes requires a precise model parameterization. In the case where the available personalized data are not sufficient to fully determine the parameter values, an appropriate prediction task may be followed. This study, a hybrid combination of computational optimization and machine learning methods with an already developed mechanistic model called the acute lymphoblastic leukaemia (ALL) Oncosimulator which simulates ALL progression and treatment response is presented. These methods are used in order for the parameters of the model to be estimated for retrospective cases and to be predicted for prospective ones. The parameter value prediction is based on a regression model trained on retrospective cases. The proposed Hybrid ALL Oncosimulator system has been evaluated when predicting the pre-phase treatment outcome in ALL. This has been correctly achieved for a significant percentage of patient cases tested (approx. 70% of patients). Moreover, the system is capable of denying the classification of cases for which the results are not trustworthy enough. In that case, potentially misleading predictions for a number of patients are avoided, while the classification accuracy for the remaining patient cases further increases. The results obtained are particularly encouraging regarding the soundness of the proposed methodologies and their relevance to the process of achieving clinical applicability of the proposed Hybrid ALL Oncosimulator system and VPH models in general.

Investigating the Energetic Ordering of Stable and Metastable TiO 2 Polymorphs Using DFT+ U and Hybrid Functionals

DOE PAGES

Curnan, Matthew T.; Kitchin, John R.

2015-08-12

Prediction of transition metal oxide BO 2 (B = Ti, V, etc.) polymorph energetic properties is critical to tunable material design and identifying thermodynamically accessible structures. Determining procedures capable of synthesizing particular polymorphs minimally requires prior knowledge of their relative energetic favorability. Information concerning TiO 2 polymorph relative energetic favorability has been ascertained from experimental research. In this study, the consistency of first-principles predictions and experimental results involving the relative energetic ordering of stable (rutile), metastable (anatase and brookite), and unstable (columbite) TiO 2 polymorphs is assessed via density functional theory (DFT). Considering the issues involving electron–electron interaction and chargemore » delocalization in TiO 2 calculations, relative energetic ordering predictions are evaluated over trends varying Ti Hubbard U 3d or exact exchange fraction parameter values. Energetic trends formed from varying U 3d predict experimentally consistent energetic ordering over U 3d intervals when using GGA-based functionals, regardless of pseudopotential selection. Given pertinent linear response calculated Hubbard U values, these results enable TiO 2 polymorph energetic ordering prediction. Here, the hybrid functional calculations involving rutile–anatase relative energetics, though demonstrating experimentally consistent energetic ordering over exact exchange fraction ranges, are not accompanied by predicted fractions, for a first-principles methodology capable of calculating exact exchange fractions precisely predicting TiO 2 polymorph energetic ordering is not available.« less

The value of geriatric assessments in predicting treatment tolerance and all-cause mortality in older patients with cancer.

PubMed

Hamaker, Marije E; Vos, Alinda G; Smorenburg, Carolien H; de Rooij, Sophia E; van Munster, Barbara C

2012-01-01

Awareness of the use of geriatric assessments for older patients with cancer is increasing. The aim of this review is to summarize all available evidence on the association between geriatric assessments and relevant oncologic outcomes. A systematic search was conducted in Medline and Embase of studies on geriatric assessment in oncology, focusing on the association between baseline assessment and outcome. The literature search identified 2008 reports; 51 publications from 37 studies were selected for inclusion in the review. The quality of studies was heterogeneous and generally poor. A median of five geriatric conditions were assessed per study (interquartile range: 4-8). Little consistency was found in the results of the studies. Furthermore, different tools appear to be predictive depending on the outcome measure: frailty, nutritional status, and comorbidity assessed by the Cumulative Illness Rating Scale for Geriatrics were predictive for all-cause mortality; frailty was predictive for toxicity of chemotherapy; cognitive impairment and activities of daily living impairment were predictive for chemotherapy completion; and instrumental activities of daily living impairment was predictive for perioperative complications. Although various geriatric conditions appear to be of some value in predicting outcome in elderly patients with cancer, the results are too inconsistent to guide treatment decisions. Further research is needed to elucidate the role of geriatric assessments in the oncologic decision-making process for these patients.

Predicting liver metastasis of gastrointestinal tract cancer by diffusion-weighted imaging of apparent diffusion coefficient values

PubMed Central

Zheng, De-Xian; Meng, Shu-Chun; Liu, Qing-Jun; Li, Chuan-Ting; Shang, Xi-Dan; Zhu, Yu-Seng; Bai, Tian-Jun; Xu, Shi-Ming

2016-01-01

AIM: To determine if efficacy of chemotherapy on liver metastasis of gastrointestinal tract cancer can be predicted by apparent diffusion coefficient (ADC) values of diffusion-weighted imaging (DWI). METHODS: In total, 86 patients with liver metastasis of gastrointestinal tract cancer (156 metastatic lesions) diagnosed in our hospital were included in this study. The maximum diameters of these tumors were compared with each other before treatment, 2 wk after treatment, and 12 wk after treatment. Selected patients were classified as the effective group and the ineffective group, depending on the maximum diameter of the tumor after 12 wk of treatment; and the ADC values at different treatment times between the two groups were compared. Spearman rank correlation was used to analyze the relationship between ADC value and tumor diameter. Receiver operating characteristic curve (ROC curve) was used to analyze the ADC values before treatment to predict the patient’s sensitivity and specificity degree of efficacy to the chemotherapy. RESULTS: There was no difference in age between the two groups and in maximum tumor diameter before treatment and 2 wk after treatment. However, after 12 wk of treatment, maximum tumor diameter in the effective group was significantly lower than that in the ineffective group (P < 0.05). Before treatment, ADC values in the ineffective group were significantly higher than those in the effective group (P < 0.05). There was no difference in ADC values between the effective and ineffective groups after 2 and 12 wk of treatment. However, ADC values were significantly higher after 2 and 12 wk of treatment compared to before treatment in the effective group (P < 0.05). Spearman rank correlation analysis showed that ADC value before treatment and the reduced percentage of the maximum tumor diameter after 12 wk of treatment were negatively correlated, while the increase in the percentage of the ADC value 12 wk after treatment and the decrease in the percentage of the maximum tumor diameter were significantly positively correlated. The results of the ROC curve showed that ADC value with a chemotherapy ineffective threshold value of 1.14 × 10-3 mm2/s before treatment had a sensitivity and specificity of 94.3% and 76.7%, respectively. CONCLUSION: DWI ADC values can be used to predict the response of patients with liver metastasis of gastrointestinal tract cancer to chemotherapy with high sensitivity and relatively high specificity. PMID:26973399

Predicting Intracerebral Hemorrhage Growth With the Spot Sign: The Effect of Onset-to-Scan Time.

PubMed

Dowlatshahi, Dar; Brouwers, H Bart; Demchuk, Andrew M; Hill, Michael D; Aviv, Richard I; Ufholz, Lee-Anne; Reaume, Michael; Wintermark, Max; Hemphill, J Claude; Murai, Yasuo; Wang, Yongjun; Zhao, Xingquan; Wang, Yilong; Li, Na; Sorimachi, Takatoshi; Matsumae, Mitsunori; Steiner, Thorsten; Rizos, Timolaos; Greenberg, Steven M; Romero, Javier M; Rosand, Jonathan; Goldstein, Joshua N; Sharma, Mukul

2016-03-01

Hematoma expansion after acute intracerebral hemorrhage is common and is associated with early deterioration and poor clinical outcome. The computed tomographic angiography (CTA) spot sign is a promising predictor of expansion; however, frequency and predictive values are variable across studies, possibly because of differences in onset-to-CTA time. We performed a patient-level meta-analysis to define the relationship between onset-to-CTA time and frequency and predictive ability of the spot sign. We completed a systematic review for studies of CTA spot sign and hematoma expansion. We subsequently pooled patient-level data on the frequency and predictive values for significant hematoma expansion according to 5 predefined categorized onset-to-CTA times. We calculated spot-sign frequency both as raw and frequency-adjusted rates. Among 2051 studies identified, 12 met our inclusion criteria. Baseline hematoma volume, spot-sign status, and time-to-CTA were available for 1176 patients, and 1039 patients had follow-up computed tomographies for hematoma expansion analysis. The overall spot sign frequency was 26%, decreasing from 39% within 2 hours of onset to 13% beyond 8 hours (P<0.001). There was a significant decrease in hematoma expansion in spot-positive patients as onset-to-CTA time increased (P=0.004), with positive predictive values decreasing from 53% to 33%. The frequency of the CTA spot sign is inversely related to intracerebral hemorrhage onset-to-CTA time. Furthermore, the positive predictive value of the spot sign for significant hematoma expansion decreases as time-to-CTA increases. Our results offer more precise risk stratification for patients with acute intracerebral hemorrhage and will help refine clinical prediction rules for intracerebral hemorrhage expansion. © 2016 American Heart Association, Inc.

Predicting depressive symptoms from acculturative family distancing: A study of Taiwanese parachute kids in adulthood.

PubMed

Lee, Hsin-Hua; Friedlander, Myrna L

2014-07-01

We applied Hwang's (2006a) acculturative family distancing (AFD) theory to Taiwanese "parachute kids," who had immigrated to the United States or Canada as unaccompanied minors and remained in North American as adults. It was hypothesized that each dimension of AFD-communication breakdown and cultural value incongruence-would uniquely predict conflict with participants' family members in Taiwan, which would, in turn, predict their depressive symptoms. In a sample of 68 former parachute kids aged 18 to 36 years, the relation between communication breakdown and depressive symptoms was fully mediated by family conflict. On the other hand, the mediation effect was not found for cultural value incongruence. Moreover, a suppression effect occurred, suggesting the likelihood that an additional, unknown variable accounts for the relation between cultural value incongruence and depressive symptoms. We concluded, from these results, that the 2 AFD dimensions operate differently in this population than in previous AFD research. This conclusion was further supported by the finding that participants reported significantly more communication breakdown than cultural value incongruence with family members residing in Taiwan.

Methods for using groundwater model predictions to guide hydrogeologic data collection, with application to the Death Valley regional groundwater flow system

USGS Publications Warehouse

Tiedeman, C.R.; Hill, M.C.; D'Agnese, F. A.; Faunt, C.C.

2003-01-01

Calibrated models of groundwater systems can provide substantial information for guiding data collection. This work considers using such models to guide hydrogeologic data collection for improving model predictions by identifying model parameters that are most important to the predictions. Identification of these important parameters can help guide collection of field data about parameter values and associated flow system features and can lead to improved predictions. Methods for identifying parameters important to predictions include prediction scaled sensitivities (PSS), which account for uncertainty on individual parameters as well as prediction sensitivity to parameters, and a new "value of improved information" (VOII) method presented here, which includes the effects of parameter correlation in addition to individual parameter uncertainty and prediction sensitivity. In this work, the PSS and VOII methods are demonstrated and evaluated using a model of the Death Valley regional groundwater flow system. The predictions of interest are advective transport paths originating at sites of past underground nuclear testing. Results show that for two paths evaluated the most important parameters include a subset of five or six of the 23 defined model parameters. Some of the parameters identified as most important are associated with flow system attributes that do not lie in the immediate vicinity of the paths. Results also indicate that the PSS and VOII methods can identify different important parameters. Because the methods emphasize somewhat different criteria for parameter importance, it is suggested that parameters identified by both methods be carefully considered in subsequent data collection efforts aimed at improving model predictions.

Context-sensitivity of the feedback-related negativity for zero-value feedback outcomes.

PubMed

Pfabigan, Daniela M; Seidel, Eva-Maria; Paul, Katharina; Grahl, Arvina; Sailer, Uta; Lanzenberger, Rupert; Windischberger, Christian; Lamm, Claus

2015-01-01

The present study investigated whether the same visual stimulus indicating zero-value feedback (€0) elicits feedback-related negativity (FRN) variation, depending on whether the outcomes correspond with expectations or not. Thirty-one volunteers performed a monetary incentive delay (MID) task while EEG was recorded. FRN amplitudes were comparable and more negative when zero-value outcome deviated from expectations than with expected gain or loss, supporting theories emphasising the impact of unexpectedness and salience on FRN amplitudes. Surprisingly, expected zero-value outcomes elicited the most negative FRNs. However, source localisation showed that such outcomes evoked less activation in cingulate areas than unexpected zero-value outcomes. Our study illustrates the context dependency of identical zero-value feedback stimuli. Moreover, the results indicate that the incentive cues in the MID task evoke different reward prediction error signals. These prediction signals differ in FRN amplitude and neuronal sources, and have to be considered in the design and interpretation of future studies. Copyright © 2014 Elsevier B.V. All rights reserved.

[Effects of finitude salience and social value intention on emotional responses of "kandoh" (the state of being emotionally moved) associated with sadness].

PubMed

Kato, Juri; Murata, Koji

2013-06-01

Two experiments investigated whether emotional responses of "kandoh" (the state of being emotionally moved) associated with sadness were facilitated by the factors of "finitude salience" and "social value intention". We predicted that participants who strongly intended social value would be more strongly moved by movies that portrayed social values than participants who weakly intended social value. Furthermore we predicted that this difference would increase in the finitude salience condition. In both experiments, participants assigned to the finitude salience condition subtracted the years of the person's birth from death. In the control condition, participants performed the same task in the form of simple numerical calculations. Then all participants watched a movie that portrayed family love and death in Experiment 1 (N = 88). We used another movie that described friendship and separation in Experiment 2 (N = 82). The results supported the two hypotheses that social value intention facilitated emotional responses of "kandoh" and this effect increased under finitude salience.

Heroin and saccharin demand and preference in rats.

PubMed

Schwartz, Lindsay P; Kim, Jung S; Silberberg, Alan; Kearns, David N

2017-09-01

Several recent studies have investigated the choice between heroin and a non-drug alternative reinforcer in rats. A common finding in these studies is that there are large individual differences in preference, with some rats preferring heroin and some preferring the non-drug alternative. The primary goal of the present study was to determine whether individual differences in how heroin or saccharin is valued, based on demand analysis, predicts choice. Rats lever-pressed for heroin infusions and saccharin reinforcers on fixed-ratio schedules. The essential value of each reinforcer was obtained from resulting demand curves. Rats were then trained on a mutually exclusive choice procedure where pressing one lever resulted in heroin and pressing another resulted in saccharin. After seven sessions of increased access to heroin or saccharin, rats were reexposed to the demand and choice procedures. Demand for heroin was more elastic than demand for saccharin (i.e., heroin had lower essential value than saccharin). When allowed to choose, most rats preferred saccharin. The essential value of heroin, but not saccharin, predicted preference. The essential value of both heroin and saccharin increased following a week of increased access to heroin, but similar saccharin exposure had no effect on essential value. Preference was unchanged after increased access to either reinforcer. Heroin-preferring rats differed from saccharin-preferring rats in how they valued heroin, but not saccharin. To the extent that choice models addiction-related behavior, these results suggest that overvaluation of opioids specifically, rather than undervaluation of non-drug alternatives, could identify susceptible individuals. Copyright © 2017 Elsevier B.V. All rights reserved.

Positive predictive value of infective endocarditis in the Danish National Patient Registry: a validation study.

PubMed

Østergaard, Lauge; Adelborg, Kasper; Sundbøll, Jens; Pedersen, Lars; Loldrup Fosbøl, Emil; Schmidt, Morten

2018-05-30

The positive predictive value of an infective endocarditis diagnosis is approximately 80% in the Danish National Patient Registry. However, since infective endocarditis is a heterogeneous disease implying long-term intravenous treatment, we hypothesiszed that the positive predictive value varies by length of hospital stay. A total of 100 patients with first-time infective endocarditis in the Danish National Patient Registry were identified from January 2010 - December 2012 at the University hospital of Aarhus and regional hospitals of Herning and Randers. Medical records were reviewed. We calculated the positive predictive value according to admission length, and separately for patients with a cardiac implantable electronic device and a prosthetic heart valve using the Wilson score method. Among the 92 medical records available for review, the majority of the patients had admission length ⩾2 weeks. The positive predictive value increased with length of admission. In patients with admission length <2 weeks the positive predictive value was 65% while it was 90% for admission length ⩾2 weeks. The positive predictive value was 81% for patients with a cardiac implantable electronic device and 87% for patients with a prosthetic valve. The positive predictive value of the infective endocarditis diagnosis in the Danish National Patient Registry is high for patients with admission length ⩾2 weeks. Using this algorithm, the Danish National Patient Registry provides a valid source for identifying infective endocarditis for research.

Defining probabilities of bowel resection in deep endometriosis of the rectum: Prediction with preoperative magnetic resonance imaging.

PubMed

Perandini, Alessio; Perandini, Simone; Montemezzi, Stefania; Bonin, Cecilia; Bellini, Gaia; Bergamini, Valentino

2018-02-01

Deep endometriosis of the rectum is a highly challenging disease, and a surgical approach is often needed to restore anatomy and function. Two kinds of surgeries may be performed: radical with segmental bowel resection or conservative without resection. Most patients undergo magnetic resonance imaging (MRI) before surgery, but there is currently no method to predict if conservative surgery is feasible or whether bowel resection is required. The aim of this study was to create an algorithm that could predict bowel resection using MRI images, that was easy to apply and could be useful in a clinical setting, in order to adequately discuss informed consent with the patient and plan the an appropriate and efficient surgical session. We collected medical records from 2010 to 2016 and reviewed the MRI results of 52 patients to detect any parameters that could predict bowel resection. Parameters that were reproducible and with a significant correlation to radical surgery were investigated by statistical regression and combined in an algorithm to give the best prediction of resection. The calculation of two parameters in MRI, impact angle and lesion size, and their use in a mathematical algorithm permit us to predict bowel resection with a positive predictive value of 87% and a negative predictive value of 83%. MRI could be of value in predicting the need for bowel resection in deep endometriosis of the rectum. Further research is required to assess the possibility of a wider application of this algorithm outside our single-center study. © 2017 Japan Society of Obstetrics and Gynecology.

Disparities between Ophthalmologists and Patients in Estimating Quality of Life Associated with Diabetic Retinopathy

PubMed Central

Zou, Haidong; Xu, Xun; Zhang, Xi

2015-01-01

Background This study aimed to evaluate and compare the utility values associated with diabetic retinopathy (DR) in a sample of Chinese patients and ophthalmologists. Methods Utility values were evaluated by both the time trade-off (TTO) and rating scale (RS) methods for 109 eligible patients with DR and 2 experienced ophthalmologists. Patients were stratified by Snellen best-corrected visual acuity (BCVA) in the better-seeing eye. The correlations between the utility values and general vision-related health status measures were analyzed. These utility values were compared with data from two other studies. Results The mean utility values elicited from the patients themselves with the TTO (0.81; SD 0.10) and RS (0.81; SD 0.11) methods were both statistically lower than the mean utility values assessed by ophthalmologists. Significant predictors of patients’ TTO and RS utility values were both LogMAR BCVA in the affected eye and average weighted LogMAR BCVA. DR grade and duration of visual dysfunction were also variables that significantly predicted patients’ TTO utility values. For ophthalmologists, patients’ LogMAR BCVA in the affected eye and in the better eye were the variables that significantly predicted both the TTO and RS utility values. Patients’ education level was also a variable that significantly predicted RS utility values. Moreover, both diabetic macular edema and employment status were significant predictors of TTO and RS utility values, whether from patients or ophthalmologists. There was no difference in mean TTO utility values compared to our American and Canadian patients. Conclusions DR caused a substantial decrease in Chinese patients’ utility values, and ophthalmologists substantially underestimated its effect on patient quality of life. PMID:26630653

Predicting drug hydrolysis based on moisture uptake in various packaging designs.

PubMed

Naversnik, Klemen; Bohanec, Simona

2008-12-18

An attempt was made to predict the stability of a moisture sensitive drug product based on the knowledge of the dependence of the degradation rate on tablet moisture. The moisture increase inside a HDPE bottle with the drug formulation was simulated with the sorption-desorption moisture transfer model, which, in turn, allowed an accurate prediction of the drug degradation kinetics. The stability prediction, obtained by computer simulation, was made in a considerably shorter time frame and required little resources compared to a conventional stability study. The prediction was finally upgraded to a stochastic Monte Carlo simulation, which allowed quantitative incorporation of uncertainty, stemming from various sources. The resulting distribution of the outcome of interest (amount of degradation product at expiry) is a comprehensive way of communicating the result along with its uncertainty, superior to single-value results or confidence intervals.

Attitudes toward older adults: A matter of cultural values or personal values?

PubMed

Zhang, Xin; Xing, Cai; Guan, Yanjun; Song, Xuan; Melloy, Robert; Wang, Fei; Jin, Xiaoyu

2016-02-01

The current research aimed to address the inconsistent findings regarding cultural differences in attitudes toward older adults by differentiating the effects of personal and cultural values. In Study 1, we used data from the sixth wave of the World Values Survey to examine attitudes toward older adults across cultures, and how different personal values (i.e., communal vs. agentic) and cultural values (i.e., individualism) predicted these attitudes. The results of hierarchical linear modeling analyses showed that after controlling for potential covariates, personal communal values positively correlated with positive attitudes toward older adults; however, cultural individualistic values did not. To further examine the causal effects of personal values (vs. cultural values), we conducted an experimental study and confirmed that priming personal values rather than cultural values had significant effects on ageism attitudes. The present studies help to reconcile conflicting results on cultural differences in attitudes toward older adults. (c) 2016 APA, all rights reserved).

Laryngeal Electromyography for Prognosis of Vocal Fold Paralysis.

PubMed

Pardo-Maza, Adriana; García-Lopez, Isabel; Santiago-Pérez, Susana; Gavilán, Javier

2017-01-01

This study aimed to determine the value of laryngeal electromyography in the prognosis of vocal fold paralysis. This is a retrospective descriptive study. This study included 80 patients diagnosed with unilateral or bilateral vocal fold paralysis on flexible laryngoscopy between 2002 and 2014 in a tertiary medical center. Laryngeal electromyography using a standardized protocol was performed; the outcome measures were classified and analyzed into two groups according to the degree of injury. Group 1 included patients with mild to moderate injury, and group 2 included patients with severe to complete injury. Prognosis was correlated with vocal fold motion recovery status with a minimum of 6 months of follow-up since the symptoms onset using positive and negative predictive values. Sixty patients showed acute or chronic recurrent laryngeal neuropathy in laryngeal electromyography. Twelve of 41 patients included in group 1 recovered motion, and 30 of 35 patients included in group 2 did not recover, resulting in 88.2% of positive predictive value and 35.7% of negative predictive value. Our data confirm that laryngeal electromyography is a useful clinical tool in predicting poor recovery in patients with vocal fold paralysis. It allows identification of candidates for early intervention. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Predicting critical micelle concentration and micelle molecular weight of polysorbate 80 using compendial methods.

PubMed

Braun, Alexandra C; Ilko, David; Merget, Benjamin; Gieseler, Henning; Germershaus, Oliver; Holzgrabe, Ulrike; Meinel, Lorenz

2015-08-01

This manuscript addresses the capability of compendial methods in controlling polysorbate 80 (PS80) functionality. Based on the analysis of sixteen batches, functionality related characteristics (FRC) including critical micelle concentration (CMC), cloud point, hydrophilic-lipophilic balance (HLB) value and micelle molecular weight were correlated to chemical composition including fatty acids before and after hydrolysis, content of non-esterified polyethylene glycols and sorbitan polyethoxylates, sorbitan- and isosorbide polyethoxylate fatty acid mono- and diesters, polyoxyethylene diesters, and peroxide values. Batches from some suppliers had a high variability in functionality related characteristic (FRC), questioning the ability of the current monograph in controlling these. Interestingly, the combined use of the input parameters oleic acid content and peroxide value - both of which being monographed methods - resulted in a model adequately predicting CMC. Confining the batches to those complying with specifications for peroxide value proved oleic acid content alone as being predictive for CMC. Similarly, a four parameter model based on chemical analyses alone was instrumental in predicting the molecular weight of PS80 micelles. Improved models based on analytical outcome from fingerprint analyses are also presented. A road map controlling PS80 batches with respect to FRC and based on chemical analyses alone is provided for the formulator. Copyright © 2014 Elsevier B.V. All rights reserved.

A simple brain atrophy measure improves the prediction of malignant middle cerebral artery infarction by acute DWI lesion volume.

PubMed

Beck, Christoph; Kruetzelmann, Anna; Forkert, Nils D; Juettler, Eric; Singer, Oliver C; Köhrmann, Martin; Kersten, Jan F; Sobesky, Jan; Gerloff, Christian; Fiehler, Jens; Schellinger, Peter D; Röther, Joachim; Thomalla, Götz

2014-06-01

In patients with malignant middle cerebral artery infarction (MMI) decompressive surgery within 48 h improves functional outcome. In this respect, early identification of patients at risk of developing MMI is crucial. While the acute diffusion weighted imaging (DWI) lesion volume was found to predict MMI with high predictive values, the potential impact of preexisting brain atrophy on the course of space-occupying middle cerebral artery (MCA) infarction and the development of MMI remains unclear. We tested the hypothesis that the combination of the acute DWI lesion volume with simple measures of brain atrophy improves the early prediction of MMI. Data from a prospective, multicenter, observational study, which included patients with acute middle cerebral artery main stem occlusion studied by MRI within 6 h of symptom onset, was analyzed retrospectively. The development of MMI was defined according to the European randomized controlled trials of decompressive surgery. Acute DWI lesion volume, as well as brain and cerebrospinal fluid volume (CSF) were delineated. The intercaudate distance (ICD) was assessed as a linear brain atrophy marker by measuring the hemi-ICD of the intact hemisphere to account for local brain swelling. Binary logistic regression analysis was used to identify significant predictors of MMI. Cut-off values were determined by Classification and Regression Trees analysis. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the resulting models were calculated. Twenty-one (18 %) of 116 patients developed a MMI. Malignant middle cerebral artery infarctions patients had higher National Institutes of Health Stroke Scale scores on admission and presented more often with combined occlusion of the internal carotid artery and MCA. There were no differences in brain and CSF volume between the two groups. Diffusion weighted imaging lesion volume was larger (p < 0.001), while hemi-ICD was smaller (p = 0.029) in MMI patients. Inclusion of hemi-ICD improved the prediction of MMI. Best cut-off values to predict the development of MMI were DWI lesion volume > 87 ml and hemi-ICD ≤ 9.4 mm. The addition of hemi-ICD to the decision tree strongly increased PPV (0.93 vs. 0.70) resulting in a reduction of false positive findings from 7/23 (30 %) to 1/15 (7 %), while there were only slight changes in specificity, sensitivity and NPV. The absolute number of correct classifications increased by 4 (3.4 %). The integration of hemi-ICD as a linear marker of brain atrophy, that can easily be assessed in an emergency setting, may improve the prediction of MMI by lesion volume based predictive models.

Nonlinear Dynamics: Theoretical Perspectives and Application to Suicidology

ERIC Educational Resources Information Center

Schiepek, Gunter; Fartacek, Clemens; Sturm, Josef; Kralovec, Karl; Fartacek, Reinhold; Ploderl, Martin

2011-01-01

Despite decades of research, the prediction of suicidal behavior remains limited. As a result, searching for more specific risk factors and testing their predictive power are central in suicidology. This strategy may be of limited value because it assumes linearity to the suicidal process that is most likely nonlinear by nature and which can be…

The Role of Fine Needle Aspiration in the Diagnosis of Parotid Gland Tumors: Correlation With Preoperative Computerized Tomography Tumor Size.

PubMed

Ghantous, Yasmine; Naddaf, Raja; Barak, Michal; Abd-Elraziq, Murad; Abu Eln-Naaj, Imad

2016-03-01

The role of fine needle aspiration cytology (FNAC) in the diagnosis of parotid gland masses is still controversial, regarding its sensitivity and specificity that vary between 41% and 100% and between 86% and 100% respectively.The aim of this study was to identify the specificity and sensitivity of FNAC of parotid gland tumors in relation to the tumor size as characterized preoperatively by computer tomography. The medical files of 79 patients whom were referred to the MaxilloFacila Surgery Department, Rambam medical center, over a 10.5-year period (2000-2010) were analyzed retrospectively.The extensity of the operation was determined by the location of the tumor as presented in computed tomography (CT) radiography, and preoperative FNAC examination.The majority of the masses were located in the superficial lobe (88.52%), and only 11.48% of the patients were located in the deep lobe (8:1 ratio). FNAC results were nondiagnostic in 7 patients (8.86%), 62 patients were diagnosed as inflammatory and benign lesion in (78.48%), malignant tumors were diagnosed in 10 patients (12.65%).The sensitivity in our study was 90%, the specificity was 98%, positive predictive value was 90%, negative predictive value was 98%, and diagnostic accuracy was 88%. The positive predictive value was 90%, the negative predictive value was 98%.Analyzing the effect of the preoperative CT size upon the accuracy of the FNAC diagnosis, we found that lesion with preoperative CT size greater than 24 mm has a more accurate FNAC result (P = 0.034).

Right hemisphere structures predict poststroke speech fluency

PubMed Central

Pani, Ethan; Zheng, Xin; Wang, Jasmine; Norton, Andrea

2016-01-01

Objective: We sought to determine via a cross-sectional study the contribution of (1) the right hemisphere's speech-relevant white matter regions and (2) interhemispheric connectivity to speech fluency in the chronic phase of left hemisphere stroke with aphasia. Methods: Fractional anisotropy (FA) of white matter regions underlying the right middle temporal gyrus (MTG), precentral gyrus (PreCG), pars opercularis (IFGop) and triangularis (IFGtri) of the inferior frontal gyrus, and the corpus callosum (CC) was correlated with speech fluency measures. A region within the superior parietal lobule (SPL) was examined as a control. FA values of regions that significantly predicted speech measures were compared with FA values from healthy age- and sex-matched controls. Results: FA values for the right MTG, PreCG, and IFGop significantly predicted speech fluency, but FA values of the IFGtri and SPL did not. A multiple regression showed that combining FA of the significant right hemisphere regions with the lesion load of the left arcuate fasciculus—a previously identified biomarker of poststroke speech fluency—provided the best model for predicting speech fluency. FA of CC fibers connecting left and right supplementary motor areas (SMA) was also correlated with speech fluency. FA of the right IFGop and PreCG was significantly higher in patients than controls, while FA of a whole CC region of interest (ROI) and the CC-SMA ROI was significantly lower in patients. Conclusions: Right hemisphere white matter integrity is related to speech fluency measures in patients with chronic aphasia. This may indicate premorbid anatomical variability beneficial for recovery or be the result of poststroke remodeling. PMID:27029627