Using continuous intraoperative optical coherence tomography measurements of the aphakic eye for intraocular lens power calculation.

PubMed

Hirnschall, Nino; Norrby, Sverker; Weber, Maria; Maedel, Sophie; Amir-Asgari, Sahand; Findl, Oliver

2015-01-01

To include intraoperative measurements of the anterior lens capsule of the aphakic eye into the intraocular lens power calculation (IPC) process and to compare the refractive outcome with conventional IPC formulae. In this prospective study, a prototype operating microscope with an integrated continuous optical coherence tomography (OCT) device (Visante attached to OPMI VISU 200, Carl Zeiss Meditec AG, Germany) was used to measure the anterior lens capsule position after implanting a capsular tension ring (CTR). Optical biometry (intraocular lens (IOL) Master 500) and ACMaster measurements (Carl Zeiss Meditec AG, Germany) were performed before surgery. Autorefraction and subjective refraction were performed 3 months after surgery. Conventional IPC formulae were compared with a new intraoperatively measured anterior chamber depth (ACD) (ACDIntraOP) partial least squares regression (PLSR) model for prediction of the postoperative refractive outcome. In total, 70 eyes of 70 patients were included. Mean axial eye length (AL) was 23.3 mm (range: 20.6-29.5 mm). Predictive power of the intraoperative measurements was found to be slightly better compared to conventional IOL power calculations. Refractive error dependency on AL for Holladay I, HofferQ, SRK/T, Haigis and ACDintraOP PLSR was r(2)=-0.42 (p<0.0001), r(2)=-0.5 (p<0.0001), r(2)=-0.34 (p=0.010), r(2)=-0.28 (p=0.049) and r(2)<0.001 (p=0.866), respectively, ACDIntraOP measurements help to better predict the refractive outcome and could be useful, if implemented in fourth-generation IPC formulae. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Psychopathy and Violence: The Importance of Factor Level Interactions

ERIC Educational Resources Information Center

Walsh, Zach; Kosson, David S.

2008-01-01

The power of scales based on the Psychopathy Checklist (PCL; R. D. Hare, 1980) for prediction of violent behavior is well established. Although evidence suggests that this relationship is chiefly due to the impulsive and antisocial lifestyle component (Factor 2), the predictive power of psychopathy for violence may also reflect the multiplicative…

Comparison of anthropometric indices (body mass index, waist circumference, waist to hip ratio and waist to height ratio) in predicting risk of type II diabetes in the population of Yazd, Iran.

PubMed

Mirzaei, Masoud; Khajeh, Mohammad

2018-04-13

The purpose of this study was to determine the best anthropometric index and calculate the cut-off point for each anthropometric index in predicting the risk of type II diabetes in the population of Yazd city in Iran. The present analytical cross-sectional study was performed using the data from Yazd Health Study (YaHS) with a sample size of 9293. All required data including anthropometric indices BMI, WC, WHR, and WHtR were extracted from the YAHS questionnaire. The ROC curve was employed to compare the predictive power of each anthropometric index in the risk of developing the type II diabetes. WHtR in both genders had better predictive power for the risk of type II diabetes (AUC = 0.692 for males and AUC = 0.708 for females), and BMI showed a weaker predictive power (AUC = 0.603 for males and AUC = 0.632 for females), WC and WHR also revealed similar predictive power in the risk of type II diabetes. The cut-off point of BMI for predicting the risk of diabetes was almost identical in both genders (26.2 in males and 25.9 in females), the cut-off point of WC (91 cm), and WHtR (0.56) in males was lower than in the females (96 cm for WC and 0.605 for WHtR). The cut-off point of WHR in males (0.939) was higher than in females (0.892). The WHtR showed the best predictor of diabetes risk compared to other indices, and the BMI was the weakest predictor of the risk for diabetes. Copyright © 2018. Published by Elsevier Ltd.

Biometry and intraocular lens power calculation results with a new optical biometry device: comparison with the gold standard.

PubMed

Kaswin, Godefroy; Rousseau, Antoine; Mgarrech, Mohamed; Barreau, Emmanuel; Labetoulle, Marc

2014-04-01

To evaluate the agreement in axial length (AL), keratometry (K), anterior chamber depth (ACD) measurements; intraocular lens (IOL) power calculations; and predictability using a new partial coherence interferometry (PCI) optical biometer (AL-Scan) and a reference (gold standard) PCI optical biometer (IOLMaster 500). Service d'Ophtalmologie, Hopital Bicêtre, APHP Université, Paris, France. Evaluation of a diagnostic device. One eye of consecutive patients scheduled for cataract surgery was measured. Biometry was performed with the new biometer and the reference biometer. Comparisons were performed for AL, average K at 2.4 mm, ACD, IOL power calculations with the Haigis and SRK/T formulas, and postoperative predictability of the devices. A P value less than 0.05 was statistically significant. The study enrolled 50 patients (mean age 72.6 years±4.2 SEM). There was a good correlation between biometers for AL, K, and ACD measurements (r=0.999, r=0.933, and r=0.701, respectively) and between IOL power calculation with the Haigis formula (r=0.972) and the SRK/T formula (r=0.981). The mean absolute error (MAE) in IOL power prediction was 0.42±0.08 diopter (D) with the new biometer and 0.44±0.08 D with the reference biometer. The MAE was 0.20 D with the Haigis formula and 0.19 with the SRK/T formula (P=.36). The new PCI biometer provided valid measurements compared with the current gold standard, indicating that the new device can be used for IOL power calculations for routine cataract surgery. No author has a financial or proprietary interest in any material or method mentioned. Copyright © 2014 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

Simulation of Radiowave Propagation in a Dense Urban Environment

DTIC Science & Technology

2007-03-01

areas by Equation 2-22. The received signal power in free space can be expressed by the Friis transmission equation as follows: 2 2(4 ) t t r r PG GP...2 2(4 ) r fs t PL P R λ π = = . 2 - 30 In urban propagation applications it is common to use d in place of R for distance from the transmitter...and Bertoni and Ikegami [13]. The basic COST 231 model uses Walfisch-Bertoni results to calculate urban environment propagation prediction along

Predictive ability of a comprehensive incremental test in mountain bike marathon

PubMed Central

Schneeweiss, Patrick; Martus, Peter; Niess, Andreas M; Krauss, Inga

2018-01-01

Objectives Traditional performance tests in mountain bike marathon (XCM) primarily quantify aerobic metabolism and may not describe the relevant capacities in XCM. We aimed to validate a comprehensive test protocol quantifying its intermittent demands. Methods Forty-nine athletes (38.8±9.1 years; 38 male; 11 female) performed a laboratory performance test, including an incremental test, to determine individual anaerobic threshold (IAT), peak power output (PPO) and three maximal efforts (10 s all-out sprint, 1 min maximal effort and 5 min maximal effort). Within 2 weeks, the athletes participated in one of three XCM races (n=15, n=9 and n=25). Correlations between test variables and race times were calculated separately. In addition, multiple regression models of the predictive value of laboratory outcomes were calculated for race 3 and across all races (z-transformed data). Results All variables were correlated with race times 1, 2 and 3: 10 s all-out sprint (r=−0.72; r=−0.59; r=−0.61), 1 min maximal effort (r=−0.85; r=−0.84; r=−0.82), 5 min maximal effort (r=−0.57; r=−0.85; r=−0.76), PPO (r=−0.77; r=−0.73; r=−0.76) and IAT (r=−0.71; r=−0.67; r=−0.68). The best-fitting multiple regression models for race 3 (r2=0.868) and across all races (r2=0.757) comprised 1 min maximal effort, IAT and body weight. Conclusion Aerobic and intermittent variables correlated least strongly with race times. Their use in a multiple regression model confirmed additional explanatory power to predict XCM performance. These findings underline the usefulness of the comprehensive incremental test to predict performance in that sport more precisely. PMID:29387445

Testing the consistency of three-point halo clustering in Fourier and configuration space

NASA Astrophysics Data System (ADS)

Hoffmann, K.; Gaztañaga, E.; Scoccimarro, R.; Crocce, M.

2018-05-01

We compare reduced three-point correlations Q of matter, haloes (as proxies for galaxies) and their cross-correlations, measured in a total simulated volume of ˜100 (h-1 Gpc)3, to predictions from leading order perturbation theory on a large range of scales in configuration space. Predictions for haloes are based on the non-local bias model, employing linear (b1) and non-linear (c2, g2) bias parameters, which have been constrained previously from the bispectrum in Fourier space. We also study predictions from two other bias models, one local (g2 = 0) and one in which c2 and g2 are determined by b1 via approximately universal relations. Overall, measurements and predictions agree when Q is derived for triangles with (r1r2r3)1/3 ≳60 h-1 Mpc, where r1 - 3 are the sizes of the triangle legs. Predictions for Qmatter, based on the linear power spectrum, show significant deviations from the measurements at the BAO scale (given our small measurement errors), which strongly decrease when adding a damping term or using the non-linear power spectrum, as expected. Predictions for Qhalo agree best with measurements at large scales when considering non-local contributions. The universal bias model works well for haloes and might therefore be also useful for tightening constraints on b1 from Q in galaxy surveys. Such constraints are independent of the amplitude of matter density fluctuation (σ8) and hence break the degeneracy between b1 and σ8, present in galaxy two-point correlations.

Fault Diagnosis and Prognosis Based on Lebesgue Sampling

DTIC Science & Technology

2014-10-02

required for many safety critical systems such as unmanned air/ground/sea vehicles, aircraft , power generation, nuclear power plants, and various industrial...prediction horizon in the fault dimen- sion axis and described by the number fo fault states. This provides a straightforward means to conduct prognosis that...shown in Figure 2.(b), only 5 Lebesgue states are visited during the 550 cycles in R1 and 4 states during the 100 cycles in R2, which means that the

Relationships and Predictive Capabilities of Jump Assessments to Soccer-Specific Field Test Performance in Division I Collegiate Players

PubMed Central

Lockie, Robert G.; Stage, Alyssa A.; Stokes, John J.; Orjalo, Ashley J.; Davis, DeShaun L.; Giuliano, Dominic V.; Moreno, Matthew R.; Risso, Fabrice G.; Lazar, Adrina; Birmingham-Babauta, Samantha A.; Tomita, Tricia M.

2016-01-01

Leg power is an important characteristic for soccer, and jump tests can measure this capacity. Limited research has analyzed relationships between jumping and soccer-specific field test performance in collegiate male players. Nineteen Division I players completed tests of: leg power (vertical jump (VJ), standing broad jump (SBJ), left- and right-leg triple hop (TH)); linear (30 m sprint; 0–5 m, 5–10 m, 0–10, 0–30 m intervals) and change-of-direction (505) speed; soccer-specific fitness (Yo-Yo Intermittent Recovery Test Level 2); and 7 × 30-m sprints to measure repeated-sprint ability (RSA; total time (TT), performance decrement (PD)). Pearson’s correlations (r) determined jump and field test relationships; stepwise regression ascertained jump predictors of the tests (p < 0.05). All jumps correlated with the 0–5, 0–10, and 0–30 m sprint intervals (r = −0.65–−0.90). VJ, SBJ, and left- and right-leg TH correlated with RSA TT (r = −0.51–−0.59). Right-leg TH predicted the 0–5 and 0–10 m intervals (R2 = 0.55–0.81); the VJ predicted the 0–30 m interval and RSA TT (R2 = 0.41–0.84). Between-leg TH asymmetry correlated with and predicted left-leg 505 and RSA PD (r = −0.68–0.62; R2 = 0.39–0.46). Improvements in jumping ability could contribute to faster speed and RSA performance in collegiate soccer players. PMID:29910304

The relationship of plasma decoy receptor 3 and coronary collateral circulation in patients with coronary artery disease.

PubMed

Yan, Youyou; Song, Dandan; Liu, Lulu; Meng, Xiuping; Qi, Chao; Wang, Junnan

2017-11-15

Previously, decoy receptor 3 (DcR3) was found to be a potential angiogenetic factor, while the relationship of DcR3 with coronary collateral circulation formation has not been investigated. In this study, we aimed to investigate whether plasma decoy receptor 3 levels was associated with CCC formation and evaluate its predictive power for CCC status in patients with coronary artery disease. Among patients who underwent coronary angiography with coronary artery disease and had a stenosis of ≥90% were included in our study. Collateral degree was graded according to Rentrope Cohen classification. Patients with grade 2 or 3 collateral degree were enrolled in good CCC group and patients with grade 0 or 1 collateral degree were enrolled in poor CCC group. Plasma DcR3 level was significantly higher in good CCC group (328.00±230.82 vs 194.84±130.63ng/l, p<0.01) and positively correlated with Rentrope grade (p<0.01). In addition, plasma DcR3 was also positively correlated with VEGF-A. Both ROC (receiver operating characteristic curve) and multinomial logistical regression analysis showed that plasma DcR3 displayed potent predictive power for CCC status. Higher plasma DcR3 level was related to better CCC formation and displayed potent predictive power for CCC status. Copyright © 2017. Published by Elsevier Inc.

Does power indicate capacity? 30-s Wingate anaerobic test vs. maximal accumulated O2 deficit.

PubMed

Minahan, C; Chia, M; Inbar, O

2007-10-01

The purpose of this study was to evaluate the relationship between anaerobic power and capacity. Seven men and seven women performed a 30-s Wingate Anaerobic Test on a cycle ergometer to determine peak power, mean power, and the fatigue index. Subjects also cycled at a work rate predicted to elicit 120 % of peak oxygen uptake to exhaustion to determine the maximal accumulated O (2) deficit. Peak power and the maximal accumulated O (2) deficit were significantly correlated (r = 0.782, p = 0.001). However, when the absolute difference in exercise values between groups (men and women) was held constant using a partial correlation, the relationship diminished (r = 0.531, p = 0.062). In contrast, we observed a significant correlation between fatigue index and the maximal accumulated O (2) deficit when controlling for gender (r = - 0.597, p = 0.024) and the relationship remained significant when values were expressed relative to active muscle mass. A higher anaerobic power does not indicate a greater anaerobic capacity. Furthermore, we suggest that the ability to maintain power output during a 30-s cycle sprint is related to anaerobic capacity.

Multivariate reference technique for quantitative analysis of fiber-optic tissue Raman spectroscopy.

PubMed

Bergholt, Mads Sylvest; Duraipandian, Shiyamala; Zheng, Wei; Huang, Zhiwei

2013-12-03

We report a novel method making use of multivariate reference signals of fused silica and sapphire Raman signals generated from a ball-lens fiber-optic Raman probe for quantitative analysis of in vivo tissue Raman measurements in real time. Partial least-squares (PLS) regression modeling is applied to extract the characteristic internal reference Raman signals (e.g., shoulder of the prominent fused silica boson peak (~130 cm(-1)); distinct sapphire ball-lens peaks (380, 417, 646, and 751 cm(-1))) from the ball-lens fiber-optic Raman probe for quantitative analysis of fiber-optic Raman spectroscopy. To evaluate the analytical value of this novel multivariate reference technique, a rapid Raman spectroscopy system coupled with a ball-lens fiber-optic Raman probe is used for in vivo oral tissue Raman measurements (n = 25 subjects) under 785 nm laser excitation powers ranging from 5 to 65 mW. An accurate linear relationship (R(2) = 0.981) with a root-mean-square error of cross validation (RMSECV) of 2.5 mW can be obtained for predicting the laser excitation power changes based on a leave-one-subject-out cross-validation, which is superior to the normal univariate reference method (RMSE = 6.2 mW). A root-mean-square error of prediction (RMSEP) of 2.4 mW (R(2) = 0.985) can also be achieved for laser power prediction in real time when we applied the multivariate method independently on the five new subjects (n = 166 spectra). We further apply the multivariate reference technique for quantitative analysis of gelatin tissue phantoms that gives rise to an RMSEP of ~2.0% (R(2) = 0.998) independent of laser excitation power variations. This work demonstrates that multivariate reference technique can be advantageously used to monitor and correct the variations of laser excitation power and fiber coupling efficiency in situ for standardizing the tissue Raman intensity to realize quantitative analysis of tissue Raman measurements in vivo, which is particularly appealing in challenging Raman endoscopic applications.

A Critical Analysis and Assessment of High Power Switches

DTIC Science & Technology

1978-09-01

applications. Because of field-distorting corona discharges in high voltage gas gaps it is difficult to predict the exact break- down strength of a nonuniform ...applied field. The streamer velocity is a/R Vs =E 2 a/R (A-9) i n i - laiR -i e o 411 where S= mobility of electrons E = applied electric field a = length

Predicting Power Output of Upper Body using the OMNI-RES Scale.

PubMed

Bautista, Iker J; Chirosa, Ignacio J; Tamayo, Ignacio Martín; González, Andrés; Robinson, Joseph E; Chirosa, Luis J; Robertson, Robert J

2014-12-09

The main aim of this study was to determine the optimal training zone for maximum power output. This was to be achieved through estimating mean bar velocity of the concentric phase of a bench press using a prediction equation. The values for the prediction equation would be obtained using OMNI-RES scale values of different loads of the bench press exercise. Sixty males (age 23.61 2.81 year; body height 176.29 6.73 cm; body mass 73.28 4.75 kg) voluntarily participated in the study and were tested using an incremental protocol on a Smith machine to determine one repetition maximum (1RM) in the bench press exercise. A linear regression analysis produced a strong correlation (r = -0.94) between rating of perceived exertion (RPE) and mean bar velocity (Velmean). The Pearson correlation analysis between real power output (PotReal) and estimated power (PotEst) showed a strong correlation coefficient of r = 0.77, significant at a level of p = 0.01. Therefore, the OMNI-RES scale can be used to predict Velmean in the bench press exercise to control the intensity of the exercise. The positive relationship between PotReal and PotEst allowed for the identification of a maximum power-training zone.

Predicting Power Output of Upper Body using the OMNI-RES Scale

PubMed Central

Bautista, Iker J.; Chirosa, Ignacio J.; Tamayo, Ignacio Martín; González, Andrés; Robinson, Joseph E.; Chirosa, Luis J.; Robertson, Robert J.

2014-01-01

The main aim of this study was to determine the optimal training zone for maximum power output. This was to be achieved through estimating mean bar velocity of the concentric phase of a bench press using a prediction equation. The values for the prediction equation would be obtained using OMNI–RES scale values of different loads of the bench press exercise. Sixty males (age 23.61 2.81 year; body height 176.29 6.73 cm; body mass 73.28 4.75 kg) voluntarily participated in the study and were tested using an incremental protocol on a Smith machine to determine one repetition maximum (1RM) in the bench press exercise. A linear regression analysis produced a strong correlation (r = −0.94) between rating of perceived exertion (RPE) and mean bar velocity (Velmean). The Pearson correlation analysis between real power output (PotReal) and estimated power (PotEst) showed a strong correlation coefficient of r = 0.77, significant at a level of p = 0.01. Therefore, the OMNI–RES scale can be used to predict Velmean in the bench press exercise to control the intensity of the exercise. The positive relationship between PotReal and PotEst allowed for the identification of a maximum power-training zone. PMID:25713677

Fetal Cerebrovascular Resistance and Neonatal EEG Predict 18-month Neurodevelopmental Outcome in Infants with Congenital Heart Disease

PubMed Central

Williams, Ismee A.; Tarullo, Amanda R.; Grieve, Philip G.; Wilpers, Abigail; Vignola, Emilia F.; Myers, Michael M.; Fifer, William P.

2012-01-01

Objectives The purpose of this study was to investigate early markers of risk for neurobehavioral compromise in congenital heart disease (CHD) survivors. Methods Fetuses < 24 wks gestational age (GA) were enrolled in this prospective pilot study for serial Doppler assessment of the middle cerebral and umbilical artery. The cerebral-to-placental resistance ratio (CPR) and MCA pulsatility index (PI) z-scores for GA were calculated. After birth, subjects underwent high-density (128-lead) electroencephalogram (EEG) and beta frequency (12–24Hz) band EEG power, a measure of local neural synchrony, was analyzed. Neurodevelopment was assessed at 18-months with the Bayley Scales of Infant Development III (BSID). Results 13 subjects were enrolled: 4 with hypoplastic left heart syndrome (HLHS), 4 with transposition of the great arteries (TGA), and 5 with tetralogy of Fallot (TOF). Compared with subjects with normal CPR, those with CPR<1(N=7) had lower mean BSID cognitive scores (91.4±4.8 vs. 99.2±3.8, p=.008). Fetal MCA PI z-score also correlated with BSID cognitive score (r=.589, p=0.044) as did neonatal EEG left frontal polar (r=.58, p=.037) and left frontal (r=.77,p=.002) beta power. Furthermore, fetal Doppler measures were associated with EEG power: fetuses with CPR<1 had lower left frontal polar (t=2.36, p=.038) and left frontal (t=2.85, p=.016) beta power as newborns compared with fetuses with normal CPR, and fetal MCA PI z-score correlated with neonatal EEG left frontal polar (r=.596, p=.04) and left frontal (r=.598, p=.04) beta power. Conclusions In CHD fetuses with HLHS, TGA, and TOF, abnormal cerebrovascular resistance predicted decreased neonatal EEG left frontal beta power and lower 18-mo cognitive development scores. PMID:22351034

References of anthropometric indices of central obesity and metabolic syndrome in Jordanian men and women.

PubMed

Al-Odat, Areej Zaal; Ahmad, Mousa Numan; Haddad, Fares Halim

2012-01-01

To set references and evaluate the associations between the predictive powers of the anthropometric indices of obesity, particularly central obesity, including body mass index (BMI), waist circumference (WC), waist to hip ratio (WHpR) and waist to height ratio (WHtR), and the risk factor accumulations of ≥ 2 of the components of the metabolic syndrome (MS) in a group of Jordanian men and women. Five hundreds subjects were randomly selected from among the visitors attending several family clinics in Amman. Obesity was assessed using BMI, WC, WHpR and WHtR anthropometric indices. MS risk factors as defined by the International Diabetes Federation were determined. Receiver operating characteristic curve (ROC) analysis was used to determine the predictive powers and the cut off points of each index associated with increased MS risk. There were 212 men and 288 women with age ranged 20-85 years. Optimal cut off points of BMI, WC, WHpR for MS diagnosis in men were 28.4 kg/m(2), 97.8 cm and 0.89, respectively. In women, these were 30.3 kg/m(2), 95.6 cm and 0.84, respectively. WHtR was 0.61 in both genders. Area under the curve (AUC) of ROC analysis for identifying of MS (≥ 2 risk factors) was the highest for WHpR (AUC=0.71), followed by WHtR (AUC=0.67), WC (AUC=0.64) and BMI (AUC=0.59) in men; whereas in women WHpR, WHtR and WC were almost equal (AUC=0.76, 0.75 and 0.74, respectively), followed by BMI (AUC=0.67). Correlation coefficients (r) between WHpR and MS risk factors were the strongest among the other obesity indices, followed by WC and WHtR. WHpR correlated significantly with FBG (r=0.27, p<0.01), systolic blood pressure (r=0.20, p<0.01), TGs (r=0.24, p<0.01) and HDL-C (r=-0.39, p<0.01). The respective r-values between WC and WHtR and each MS risk factors were: FBG (r=0.15, p<0.001 or r=0.13, p<0.01), systolic blood pressure (r=0.16, p<0.01 or r=0.11, p<0.05), TGs (r=0.20, p<0.01 or r=0.14, p<0.01) and HDL-C (r=-0.25, p<0.01 or r=-0.11, p<0.01). This study showed that BMI tended to be the weakest index for identifying MS risk factors in both sexes. WHpR exhibited the best predictive index for MS, particularly in men. Almost similar predictive powers of WHtR, WHpR and WC for identifying MS risk factors were seen in women. WHtR had the highest sensitivity for MS diagnosis among obesity indices in men and its boundary value was the same for both men and women. These cut off values of obesity particularly waist circumference should be advocated and used in Arab Jordanians until larger cross sectional studies shows different results. Copyright © 2012 Diabetes India. Published by Elsevier Ltd. All rights reserved.

Modeling sediment concentration of rill flow

NASA Astrophysics Data System (ADS)

Yang, Daming; Gao, Peiling; Zhao, Yadong; Zhang, Yuhang; Liu, Xiaoyuan; Zhang, Qingwen

2018-06-01

Accurate estimation of sediment concentration is essential to establish physically-based erosion models. The objectives of this study were to evaluate the effects of flow discharge (Q), slope gradient (S), flow velocity (V), shear stress (τ), stream power (ω) and unit stream power (U) on sediment concentration. Laboratory experiments were conducted using a 10 × 0.1 m rill flume under four flow discharges (2, 4, 8 and 16 L min-1), and five slope gradients (5°, 10°, 15°, 20° and 25°). The results showed that the measured sediment concentration varied from 87.08 to 620.80 kg m-3 with a mean value of 343.13 kg m-3. Sediment concentration increased as a power function with flow discharge and slope gradient, with R2 = 0.975 and NSE = 0.945. The sediment concentration was more sensitive to slope gradient than to flow discharge. The sediment concentration was well predicted by unit stream power (R2 = 0.937, NSE = 0.865), whereas less satisfactorily by flow velocity (R2 = 0.470, NSE = 0.539) and stream power (R2 = 0.773, NSE = 0.732). In addition, using the equations to simulate the measured sediment concentration of other studies, the result further indicated that slope gradient, flow discharge and unit stream power were good predictors of sediment concentration. In general, slope gradient, flow discharge and unit stream power seem to be the preferred predictors for estimating sediment concentration.

The relationship of plasma miR-503 and coronary collateral circulation in patients with coronary artery disease.

PubMed

Fei, Yu; Hou, Jianhua; Xuan, Wei; Zhang, Chenghua; Meng, Xiuping

2018-06-02

Although angiogenesis plays an important role in coronary collateral circulation (CCC) formation and there are many determinants of coronary angiogenesis, they cannot fully explain the mechanism of CCC formation or as potent biomarker for CCC status. Therefore, there is of great clinical significance to identify the novel molecules associated with CCC. Previously, miR-503 exerts anti-angiogenesis effect via inhibition of VEGF-A and its expression is associated with many angiogenesis-related factors. Thus, we aimed to investigate the relationship of plasma miR-503 with CCC formation as well as its predictive power for CCC status in patients with coronary artery disease. Among patients who underwent coronary angiography with coronary artery disease and a stenosis of ≥90% were included in our study. Collateral degree was graded according to Rentrop Cohen classification. The patients were divided to good CCC group (grade 2 or 3) and poor CCC group (grade 0 or 1) according to Rentrop grade. We investigated the plasma levels of miR-503 and VEGF-A by ELISA or q RT-PCR, respectively. In addition, we assayed the correlations of plasma miR-503 with VEGF-A or Rentrop grade using the spearman correlation test and its predictive power by receiver operating characteristic (ROC) and binary logistical regression analysis. Our data showed that plasma VEGF-A was significantly higher in good CCC group than that in poor group. Plasma miR-503 was lower in CAD patients with good CCC or poor CCC compared with control subjects and lowest in good CCC group. In addition, miR-503 negatively correlated with VEGF-A and Rentrop grade, respectively. Moreover, miR-503 displayed more potent predictive power for CCC status than VEGF-A, but its sensitivity and specificity for CCC status were only 72.4 or 60.9%, respectively. Lower plasma miR-503 level was related to better CCC formation, accompanied by up-regulation of VEGF-A. In addition, miR-503 displayed potent predictive power for CCC status, but its sensitivity and specificity were not high enough, indicating that miR-503 might be as an additional prognosis biomarker for CCC. Copyright © 2017. Published by Elsevier Inc.

QSAR studies in substituted 1,2,3,4,6,7,12,12a-octa-hydropyrazino[2',1':6,1]pyrido[3,4-b]indoles--a potent class of neuroleptics.

PubMed

Saxena, Anil K; Ram, Siya; Saxena, Mridula; Singh, Nidhi; Prathipati, Philip; Jain, Padam C; Singh, H K; Anand, Nitya

2003-05-01

A series of nineteen substituted 1,2,3,4,6,7,12,12a-octahydropyrazino[2',1':6,1]pyrido[3, 4-b]indoles analogues of neuroleptic drug, Centbutindole have been studied using quantitative structure-activity relationship analysis. The derived models display good fits to the experimental data (r>or=0.75) having good predictive power (r(cv)>or=0.688). The best model describes a high correlation between predicted and experimental activity data (r=0.967). Statistical analysis of the equation populations indicates that hydrophobicity (as measured by pi(R), logP(o/w) and SlogP_VSA8), dipole y and structural parameters in terms of indicator variable, (In(1)) and globularity are important variables in describing the variation in the neuroleptic activity in the series.

Predicting cardiometabolic disturbances from waist-to-height ratio: findings from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) baseline.

PubMed

Castanheira, Marcelo; Chor, Dóra; Braga, José Uéleres; Cardoso, Letícia de Oliveira; Griep, Rosane Härter; Molina, Maria Del Carmen Bisi; Fonseca, Maria de Jesus Mendes da

2018-04-01

To evaluate the performance of waist-to-height ratio (WHtR) in predicting cardiometabolic outcomes and compare cut-off points for Brazilian adults. Cross-sectional study. WHtR areas under the curve (AUC) were compared with those for BMI, waist circumference (WC) and waist-to-hip ratio (WHR). The outcomes of interest were hypertension, diabetes, hypertriacylglycerolaemia and presence of at least two components of metabolic syndrome (≥2 MetS). Cut-offs for WHtR were compared and validity measures were estimated for each point. Teaching and research institutions in six Brazilian state capitals, 2008-2010. Women (n 5026) and men (n 4238) aged 35-54 years who participated in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) at baseline. WHtR age-adjusted AUC ranged from 0·68 to 0·72 in men and 0·69 to 0·75 in women, with smaller AUC for hypertriacylglycerolaemia and the largest for ≥2 MetS. WHtR performed better than BMI for practically all outcomes; better than WHR for hypertension in both sexes; and displayed larger AUC than WC in predicting diabetes mellitus. It also offered better discriminatory power for ≥2 MetS in men; and was better than WC, but not WHR, in women. Optimal cut-off points of WHtR were 0·55 (women) and 0·54 (men), but they presented high false-negative rate compared with 0·50. We recommend using WHtR (which performed similarly to, or better than, other available indices of adiposity) as an anthropometric index with good discriminatory power for cardiometabolic outcomes in Brazilian adults, indicating the already referenced limit of WHtR≥0·50.

3D-quantitative structure-activity relationship studies on benzothiadiazepine hydroxamates as inhibitors of tumor necrosis factor-alpha converting enzyme.

PubMed

Murumkar, Prashant R; Giridhar, Rajani; Yadav, Mange Ram

2008-04-01

A set of 29 benzothiadiazepine hydroxamates having selective tumor necrosis factor-alpha converting enzyme inhibitory activity were used to compare the quality and predictive power of 3D-quantitative structure-activity relationship, comparative molecular field analysis, and comparative molecular similarity indices models for the atom-based, centroid/atom-based, data-based, and docked conformer-based alignment. Removal of two outliers from the initial training set of molecules improved the predictivity of models. Among the 3D-quantitative structure-activity relationship models developed using the above four alignments, the database alignment provided the optimal predictive comparative molecular field analysis model for the training set with cross-validated r(2) (q(2)) = 0.510, non-cross-validated r(2) = 0.972, standard error of estimates (s) = 0.098, and F = 215.44 and the optimal comparative molecular similarity indices model with cross-validated r(2) (q(2)) = 0.556, non-cross-validated r(2) = 0.946, standard error of estimates (s) = 0.163, and F = 99.785. These models also showed the best test set prediction for six compounds with predictive r(2) values of 0.460 and 0.535, respectively. The contour maps obtained from 3D-quantitative structure-activity relationship studies were appraised for activity trends for the molecules analyzed. The comparative molecular similarity indices models exhibited good external predictivity as compared with that of comparative molecular field analysis models. The data generated from the present study helped us to further design and report some novel and potent tumor necrosis factor-alpha converting enzyme inhibitors.

A Critical Evaluation of Refractive Outcomes Following LASIK for Moderate to High Astigmatism Using Two Excimer Laser Platforms.

PubMed

Patel, Sudi; Bohac, Maja; Biscevic, Alma; Koncarevic, Mateja; Anticic, Marija; Gabric, Nikica

2017-02-01

To calculate the surgically induced astigmatism (SIA) following LASIK and identify any association between SIA and the target induced astigmatism (TIA) at 1 year postoperatively. The SIA was calculated using the TIA and residual astigmatism values for [A] myopic astigmatism and [B] mixed astigmatism treated with either the [I] WaveLight Allegretto EyeQ 400-Hz (Alcon Laboratories, Inc. Fort Worth, TX) or [II] Schwind Amaris 750S (Schwind eye-tech-solutions, Kleinostheim, Germany) platforms. The TIA and corresponding SIA results were analyzed using various techniques. Key findings were the negative SIA power (y 1 ) was significantly correlated with negative TIA power (x 1 ) and sine of the TIA axis (x 2 ) as follows: [A] I, y 1 = 0.829x 1 -0.403x 2 -0.325 (F = 87.76, r = 0.804, P < .001, n = 127); II, y 1 = 0.891x 1 -0.037x 2 -0.192 (F = 240.06, r = 0.901, P < .001, n = 119) and [B] I, y 1 = 1.063x 1 +0.233x 2 +0.411 (F = 990.99, r = 0.881, P < .001, n = 61); II, y 1 = 1.029x 1 -0.115x 2 +0.322 (F = 270.12, r = 0.908, P < 0.001, n = 111). The sine of negative SIA axis (y 2 ) was significantly correlated with negative TIA power (x 1 ) and TIA axis (x 2 ) as follows: [A] I, y 2 = 0.951x 2 -0.007x 1 +0.008 (F = 446.58, r = 0.950, P < .001, n = 127); II, y 2 = 0.856x 2 +0.007x 1 +0.105 (F = 277.18, r = 0.912, P< .001, n = 119) and [B] I, y 2 = 0.953x 2 +0.009x 1 +0.075 (F = 362.6, r = 0.963, P < .001, n = 61); II, y 2 = 0.977x 2 -0.004x 1 +0.002 (F = 2910.9, r = 0.990, P < .001, n = 111). The predicted SIA power was up to 12% less than expected in cases of -6.00 diopters cylinder treated for myopic astigmatism using the Allegretto platform. The mean predicted angle of error (the angle between the SIA and TIA axes) was less than 4°, increasing to 12° for against-the-rule astigmatism. The Allegretto platform tended toward a clockwise axis rotational error, whereas the Amaris platform tended toward the opposite. [J Refract Surg. 2017;33(2):104-109.]. Copyright 2017, SLACK Incorporated.

A Comprehensive Prediction Model of Hydraulic Extended-Reach Limit Considering the Allowable Range of Drilling Fluid Flow Rate in Horizontal Drilling.

PubMed

Li, Xin; Gao, Deli; Chen, Xuyue

2017-06-08

Hydraulic extended-reach limit (HERL) model of horizontal extended-reach well (ERW) can predict the maximum measured depth (MMD) of the horizontal ERW. The HERL refers to the well's MMD when drilling fluid cannot be normally circulated by drilling pump. Previous model analyzed the following two constraint conditions, drilling pump rated pressure and rated power. However, effects of the allowable range of drilling fluid flow rate (Q min  ≤ Q ≤ Q max ) were not considered. In this study, three cases of HERL model are proposed according to the relationship between allowable range of drilling fluid flow rate and rated flow rate of drilling pump (Q r ). A horizontal ERW is analyzed to predict its HERL, especially its horizontal-section limit (L h ). Results show that when Q min  ≤ Q r  ≤ Q max (Case I), L h depends both on horizontal-section limit based on rated pump pressure (L h1 ) and horizontal-section limit based on rated pump power (L h2 ); when Q min  < Q max  < Q r (Case II), L h is exclusively controlled by L h1 ; while L h is only determined by L h2 when Q r  < Q min  < Q max (Case III). Furthermore, L h1 first increases and then decreases with the increase in drilling fluid flow rate, while L h2 keeps decreasing as the drilling fluid flow rate increases. The comprehensive model provides a more accurate prediction on HERL.

Fractal correlation properties of R-R interval dynamics and mortality in patients with depressed left ventricular function after an acute myocardial infarction

NASA Technical Reports Server (NTRS)

Huikuri, H. V.; Makikallio, T. H.; Peng, C. K.; Goldberger, A. L.; Hintze, U.; Moller, M.

2000-01-01

BACKGROUND: Preliminary data suggest that the analysis of R-R interval variability by fractal analysis methods may provide clinically useful information on patients with heart failure. The purpose of this study was to compare the prognostic power of new fractal and traditional measures of R-R interval variability as predictors of death after acute myocardial infarction. METHODS AND RESULTS: Time and frequency domain heart rate (HR) variability measures, along with short- and long-term correlation (fractal) properties of R-R intervals (exponents alpha(1) and alpha(2)) and power-law scaling of the power spectra (exponent beta), were assessed from 24-hour Holter recordings in 446 survivors of acute myocardial infarction with a depressed left ventricular function (ejection fraction

Relationships between salivary free testosterone and the expression of force and power in elite athletes.

PubMed

Crewther, B T; Kilduff, L P; Cook, C J; Cunningham, D J; Bunce, P; Bracken, R M; Gaviglio, C M

2012-04-01

This study examined the predictive relationships between the salivary free testosterone (T) concentrations of elite athletes and the expression of force and power. A group of elite male rugby players (N.=64) were assessed for peak force (PF), peak rate of force development (PRFD), force at 100 milliseconds (F100 ms) and 250 milliseconds (F250 ms) during an isometric mid-thigh pull (IMTP), and/or peak power (PP) and height during a countermovement jump (CMJ). Saliva samples were collected before testing and assayed for free T. Relationships between individual T concentrations and performance were assessed as a pooled group and 4 sub-groups of equal size. As pooled data sets, none of the IMTP and CMJ performance variables were significantly correlated with free T in either the PF or PP groups (r=0.01-0.23). The PF and PP abilities of the 4 sub-groups were significantly different, so that PF1>PF2>PF3>PF4 (P<0.001) and PP1>PP2>PP3>PP4 (P<0.01). When the 4 sub-groups were analysed, the T concentrations of the PF4 group were significantly (P<0.05-0.01) correlated to PRFD (r=0.69) and F100 ms (r=0.55) during the IMTP, as was F100 ms in the PF1 group (r=0.66). In the PP1 group, free T also correlated to CMJ height (r=0.62). The key conclusion is that the expression of force and power in an elite athletic group may be dependent, to some extent, on individual variation in salivary free T concentrations and existing strength or power levels. The current results also confirm that the grouping of elite athletes of mixed strength or power ability may bias predictive results in a manner not reflective of sub-groups within this population.

Effect of Adding McKenzie Syndrome, Centralization, Directional Preference, and Psychosocial Classification Variables to a Risk-Adjusted Model Predicting Functional Status Outcomes for Patients With Lumbar Impairments.

PubMed

Werneke, Mark W; Edmond, Susan; Deutscher, Daniel; Ward, Jason; Grigsby, David; Young, Michelle; McGill, Troy; McClenahan, Brian; Weinberg, Jon; Davidow, Amy L

2016-09-01

Study Design Retrospective cohort. Background Patient-classification subgroupings may be important prognostic factors explaining outcomes. Objectives To determine effects of adding classification variables (McKenzie syndrome and pain patterns, including centralization and directional preference; Symptom Checklist Back Pain Prediction Model [SCL BPPM]; and the Fear-Avoidance Beliefs Questionnaire subscales of work and physical activity) to a baseline risk-adjusted model predicting functional status (FS) outcomes. Methods Consecutive patients completed a battery of questionnaires that gathered information on 11 risk-adjustment variables. Physical therapists trained in Mechanical Diagnosis and Therapy methods classified each patient by McKenzie syndromes and pain pattern. Functional status was assessed at discharge by patient-reported outcomes. Only patients with complete data were included. Risk of selection bias was assessed. Prediction of discharge FS was assessed using linear stepwise regression models, allowing 13 variables to enter the model. Significant variables were retained in subsequent models. Model power (R(2)) and beta coefficients for model variables were estimated. Results Two thousand sixty-six patients with lumbar impairments were evaluated. Of those, 994 (48%), 10 (<1%), and 601 (29%) were excluded due to incomplete psychosocial data, McKenzie classification data, and missing FS at discharge, respectively. The final sample for analyses was 723 (35%). Overall R(2) for the baseline prediction FS model was 0.40. Adding classification variables to the baseline model did not result in significant increases in R(2). McKenzie syndrome or pain pattern explained 2.8% and 3.0% of the variance, respectively. When pain pattern and SCL BPPM were added simultaneously, overall model R(2) increased to 0.44. Although none of these increases in R(2) were significant, some classification variables were stronger predictors compared with some other variables included in the baseline model. Conclusion The small added prognostic capabilities identified when combining McKenzie or pain-pattern classifications with the SCL BPPM classification did not significantly improve prediction of FS outcomes in this study. Additional research is warranted to investigate the importance of classification variables compared with those used in the baseline model to maximize predictive power. Level of Evidence Prognosis, level 4. J Orthop Sports Phys Ther 2016;46(9):726-741. Epub 31 Jul 2016. doi:10.2519/jospt.2016.6266.

Advanced chronic kidney disease in non-valvular atrial fibrillation: extending the utility of R2CHADS2 to patients with advanced renal failure.

PubMed

Bautista, Josef; Bella, Archie; Chaudhari, Ashok; Pekler, Gerald; Sapra, Katherine J; Carbajal, Roger; Baumstein, Donald

2015-04-01

The R2CHADS2 is a new prediction rule for stroke risk in atrial fibrillation (AF) patients wherein R stands for renal risk. However, it was created from a cohort that excluded patients with advanced renal failure (defined as glomerular filtration rate of <30 mL/min). Our study extends the use of R2CHADS2 to patients with advanced renal failure and aims to compare its predictive power against the currently used CHADS and CHA2DS2VaSc. This retrospective cohort study analyzed the 1-year risk for stroke of the 524 patients with AF at Metropolitan Hospital Center. AUC and C statistics were calculated using three groups: (i) the entire cohort including patients with advanced renal failure, (ii) a cohort excluding patients with advanced renal failure and (iii) all patients with GFR < 30 mL/min only. R2CHADS2, as a predictor for stroke risk, consistently performs better than CHADS2 and CHA2DS2VsC in groups 1 and 2. The C-statistic was highest in R2CHADS compared with CHADS or CHADSVASC in group 1 (0.718 versus 0.605 versus 0.602) and in group 2 (0.724 versus 0.584 versus 0.579). However, there was no statistically significant difference in group 3 (0.631 versus 0.629 versus 0.623). Our study supports the utility of R2CHADS2 as a clinical prediction rule for stroke risk in patients with advanced renal failure.

A kilonova as the electromagnetic counterpart to a gravitational-wave source.

PubMed

Smartt, S J; Chen, T-W; Jerkstrand, A; Coughlin, M; Kankare, E; Sim, S A; Fraser, M; Inserra, C; Maguire, K; Chambers, K C; Huber, M E; Krühler, T; Leloudas, G; Magee, M; Shingles, L J; Smith, K W; Young, D R; Tonry, J; Kotak, R; Gal-Yam, A; Lyman, J D; Homan, D S; Agliozzo, C; Anderson, J P; Angus, C R; Ashall, C; Barbarino, C; Bauer, F E; Berton, M; Botticella, M T; Bulla, M; Bulger, J; Cannizzaro, G; Cano, Z; Cartier, R; Cikota, A; Clark, P; De Cia, A; Della Valle, M; Denneau, L; Dennefeld, M; Dessart, L; Dimitriadis, G; Elias-Rosa, N; Firth, R E; Flewelling, H; Flörs, A; Franckowiak, A; Frohmaier, C; Galbany, L; González-Gaitán, S; Greiner, J; Gromadzki, M; Guelbenzu, A Nicuesa; Gutiérrez, C P; Hamanowicz, A; Hanlon, L; Harmanen, J; Heintz, K E; Heinze, A; Hernandez, M-S; Hodgkin, S T; Hook, I M; Izzo, L; James, P A; Jonker, P G; Kerzendorf, W E; Klose, S; Kostrzewa-Rutkowska, Z; Kowalski, M; Kromer, M; Kuncarayakti, H; Lawrence, A; Lowe, T B; Magnier, E A; Manulis, I; Martin-Carrillo, A; Mattila, S; McBrien, O; Müller, A; Nordin, J; O'Neill, D; Onori, F; Palmerio, J T; Pastorello, A; Patat, F; Pignata, G; Podsiadlowski, Ph; Pumo, M L; Prentice, S J; Rau, A; Razza, A; Rest, A; Reynolds, T; Roy, R; Ruiter, A J; Rybicki, K A; Salmon, L; Schady, P; Schultz, A S B; Schweyer, T; Seitenzahl, I R; Smith, M; Sollerman, J; Stalder, B; Stubbs, C W; Sullivan, M; Szegedi, H; Taddia, F; Taubenberger, S; Terreran, G; van Soelen, B; Vos, J; Wainscoat, R J; Walton, N A; Waters, C; Weiland, H; Willman, M; Wiseman, P; Wright, D E; Wyrzykowski, Ł; Yaron, O

2017-11-02

Gravitational waves were discovered with the detection of binary black-hole mergers and they should also be detectable from lower-mass neutron-star mergers. These are predicted to eject material rich in heavy radioactive isotopes that can power an electromagnetic signal. This signal is luminous at optical and infrared wavelengths and is called a kilonova. The gravitational-wave source GW170817 arose from a binary neutron-star merger in the nearby Universe with a relatively well confined sky position and distance estimate. Here we report observations and physical modelling of a rapidly fading electromagnetic transient in the galaxy NGC 4993, which is spatially coincident with GW170817 and with a weak, short γ-ray burst. The transient has physical parameters that broadly match the theoretical predictions of blue kilonovae from neutron-star mergers. The emitted electromagnetic radiation can be explained with an ejected mass of 0.04 ± 0.01 solar masses, with an opacity of less than 0.5 square centimetres per gram, at a velocity of 0.2 ± 0.1 times light speed. The power source is constrained to have a power-law slope of -1.2 ± 0.3, consistent with radioactive powering from r-process nuclides. (The r-process is a series of neutron capture reactions that synthesise many of the elements heavier than iron.) We identify line features in the spectra that are consistent with light r-process elements (atomic masses of 90-140). As it fades, the transient rapidly becomes red, and a higher-opacity, lanthanide-rich ejecta component may contribute to the emission. This indicates that neutron-star mergers produce gravitational waves and radioactively powered kilonovae, and are a nucleosynthetic source of the r-process elements.

A kilonova as the electromagnetic counterpart to a gravitational-wave source

NASA Astrophysics Data System (ADS)

Smartt, S. J.; Chen, T.-W.; Jerkstrand, A.; Coughlin, M.; Kankare, E.; Sim, S. A.; Fraser, M.; Inserra, C.; Maguire, K.; Chambers, K. C.; Huber, M. E.; Krühler, T.; Leloudas, G.; Magee, M.; Shingles, L. J.; Smith, K. W.; Young, D. R.; Tonry, J.; Kotak, R.; Gal-Yam, A.; Lyman, J. D.; Homan, D. S.; Agliozzo, C.; Anderson, J. P.; Angus, C. R.; Ashall, C.; Barbarino, C.; Bauer, F. E.; Berton, M.; Botticella, M. T.; Bulla, M.; Bulger, J.; Cannizzaro, G.; Cano, Z.; Cartier, R.; Cikota, A.; Clark, P.; De Cia, A.; Della Valle, M.; Denneau, L.; Dennefeld, M.; Dessart, L.; Dimitriadis, G.; Elias-Rosa, N.; Firth, R. E.; Flewelling, H.; Flörs, A.; Franckowiak, A.; Frohmaier, C.; Galbany, L.; González-Gaitán, S.; Greiner, J.; Gromadzki, M.; Guelbenzu, A. Nicuesa; Gutiérrez, C. P.; Hamanowicz, A.; Hanlon, L.; Harmanen, J.; Heintz, K. E.; Heinze, A.; Hernandez, M.-S.; Hodgkin, S. T.; Hook, I. M.; Izzo, L.; James, P. A.; Jonker, P. G.; Kerzendorf, W. E.; Klose, S.; Kostrzewa-Rutkowska, Z.; Kowalski, M.; Kromer, M.; Kuncarayakti, H.; Lawrence, A.; Lowe, T. B.; Magnier, E. A.; Manulis, I.; Martin-Carrillo, A.; Mattila, S.; McBrien, O.; Müller, A.; Nordin, J.; O'Neill, D.; Onori, F.; Palmerio, J. T.; Pastorello, A.; Patat, F.; Pignata, G.; Podsiadlowski, Ph.; Pumo, M. L.; Prentice, S. J.; Rau, A.; Razza, A.; Rest, A.; Reynolds, T.; Roy, R.; Ruiter, A. J.; Rybicki, K. A.; Salmon, L.; Schady, P.; Schultz, A. S. B.; Schweyer, T.; Seitenzahl, I. R.; Smith, M.; Sollerman, J.; Stalder, B.; Stubbs, C. W.; Sullivan, M.; Szegedi, H.; Taddia, F.; Taubenberger, S.; Terreran, G.; van Soelen, B.; Vos, J.; Wainscoat, R. J.; Walton, N. A.; Waters, C.; Weiland, H.; Willman, M.; Wiseman, P.; Wright, D. E.; Wyrzykowski, Ł.; Yaron, O.

2017-11-01

Gravitational waves were discovered with the detection of binary black-hole mergers and they should also be detectable from lower-mass neutron-star mergers. These are predicted to eject material rich in heavy radioactive isotopes that can power an electromagnetic signal. This signal is luminous at optical and infrared wavelengths and is called a kilonova. The gravitational-wave source GW170817 arose from a binary neutron-star merger in the nearby Universe with a relatively well confined sky position and distance estimate. Here we report observations and physical modelling of a rapidly fading electromagnetic transient in the galaxy NGC 4993, which is spatially coincident with GW170817 and with a weak, short γ-ray burst. The transient has physical parameters that broadly match the theoretical predictions of blue kilonovae from neutron-star mergers. The emitted electromagnetic radiation can be explained with an ejected mass of 0.04 ± 0.01 solar masses, with an opacity of less than 0.5 square centimetres per gram, at a velocity of 0.2 ± 0.1 times light speed. The power source is constrained to have a power-law slope of -1.2 ± 0.3, consistent with radioactive powering from r-process nuclides. (The r-process is a series of neutron capture reactions that synthesise many of the elements heavier than iron.) We identify line features in the spectra that are consistent with light r-process elements (atomic masses of 90-140). As it fades, the transient rapidly becomes red, and a higher-opacity, lanthanide-rich ejecta component may contribute to the emission. This indicates that neutron-star mergers produce gravitational waves and radioactively powered kilonovae, and are a nucleosynthetic source of the r-process elements.

Limited Sampling Strategy for Accurate Prediction of Pharmacokinetics of Saroglitazar: A 3-point Linear Regression Model Development and Successful Prediction of Human Exposure.

PubMed

Joshi, Shuchi N; Srinivas, Nuggehally R; Parmar, Deven V

2018-03-01

Our aim was to develop and validate the extrapolative performance of a regression model using a limited sampling strategy for accurate estimation of the area under the plasma concentration versus time curve for saroglitazar. Healthy subject pharmacokinetic data from a well-powered food-effect study (fasted vs fed treatments; n = 50) was used in this work. The first 25 subjects' serial plasma concentration data up to 72 hours and corresponding AUC 0-t (ie, 72 hours) from the fasting group comprised a training dataset to develop the limited sampling model. The internal datasets for prediction included the remaining 25 subjects from the fasting group and all 50 subjects from the fed condition of the same study. The external datasets included pharmacokinetic data for saroglitazar from previous single-dose clinical studies. Limited sampling models were composed of 1-, 2-, and 3-concentration-time points' correlation with AUC 0-t of saroglitazar. Only models with regression coefficients (R 2 ) >0.90 were screened for further evaluation. The best R 2 model was validated for its utility based on mean prediction error, mean absolute prediction error, and root mean square error. Both correlations between predicted and observed AUC 0-t of saroglitazar and verification of precision and bias using Bland-Altman plot were carried out. None of the evaluated 1- and 2-concentration-time points models achieved R 2 > 0.90. Among the various 3-concentration-time points models, only 4 equations passed the predefined criterion of R 2 > 0.90. Limited sampling models with time points 0.5, 2, and 8 hours (R 2 = 0.9323) and 0.75, 2, and 8 hours (R 2 = 0.9375) were validated. Mean prediction error, mean absolute prediction error, and root mean square error were <30% (predefined criterion) and correlation (r) was at least 0.7950 for the consolidated internal and external datasets of 102 healthy subjects for the AUC 0-t prediction of saroglitazar. The same models, when applied to the AUC 0-t prediction of saroglitazar sulfoxide, showed mean prediction error, mean absolute prediction error, and root mean square error <30% and correlation (r) was at least 0.9339 in the same pool of healthy subjects. A 3-concentration-time points limited sampling model predicts the exposure of saroglitazar (ie, AUC 0-t ) within predefined acceptable bias and imprecision limit. Same model was also used to predict AUC 0-∞ . The same limited sampling model was found to predict the exposure of saroglitazar sulfoxide within predefined criteria. This model can find utility during late-phase clinical development of saroglitazar in the patient population. Copyright © 2018 Elsevier HS Journals, Inc. All rights reserved.

Galaxy-galaxy weak gravitational lensing in f(R) gravity

NASA Astrophysics Data System (ADS)

Li, Baojiu; Shirasaki, Masato

2018-03-01

We present an analysis of galaxy-galaxy weak gravitational lensing (GGL) in chameleon f(R) gravity - a leading candidate of non-standard gravity models. For the analysis, we have created mock galaxy catalogues based on dark matter haloes from two sets of numerical simulations, using a halo occupation distribution (HOD) prescription which allows a redshift dependence of galaxy number density. To make a fairer comparison between the f(R) and Λ cold dark matter (ΛCDM) models, their HOD parameters are tuned so that the galaxy two-point correlation functions in real space (and therefore the projected two-point correlation functions) match. While the f(R) model predicts an enhancement of the convergence power spectrum by up to ˜ 30 per cent compared to the standard ΛCDM model with the same parameters, the maximum enhancement of GGL is only half as large and less than 5 per cent on separations above ˜1-2 h-1 Mpc, because the latter is a cross-correlation of shear (or matter, which is more strongly affected by modified gravity) and galaxy (which is weakly affected given the good match between galaxy autocorrelations in the two models) fields. We also study the possibility of reconstructing the matter power spectrum by combination of GGL and galaxy clustering in f(R) gravity. We find that the galaxy-matter cross-correlation coefficient remains at unity down to ˜2-3 h-1 Mpc at relevant redshifts even in f(R) gravity, indicating joint analysis of GGL and galaxy clustering can be a powerful probe of matter density fluctuations in chameleon gravity. The scale dependence of the model differences in their predictions of GGL can potentially allows us to break the degeneracy between f(R) gravity and other cosmological parameters such as Ωm and σ8.

Solar maximum: Solar array degradation

NASA Technical Reports Server (NTRS)

Miller, T.

1985-01-01

The 5-year in-orbit power degradation of the silicon solar array aboard the Solar Maximum Satellite was evaluated. This was the first spacecraft to use Teflon R FEP as a coverglass adhesive, thus avoiding the necessity of an ultraviolet filter. The peak power tracking mode of the power regulator unit was employed to ensure consistent maximum power comparisons. Telemetry was normalized to account for the effects of illumination intensity, charged particle irradiation dosage, and solar array temperature. Reference conditions of 1.0 solar constant at air mass zero and 301 K (28 C) were used as a basis for normalization. Beginning-of-life array power was 2230 watts. Currently, the array output is 1830 watts. This corresponds to a 16 percent loss in array performance over 5 years. Comparison of Solar Maximum Telemetry and predicted power levels indicate that array output is 2 percent less than predictions based on an annual 1.0 MeV equivalent election fluence of 2.34 x ten to the 13th power square centimeters space environment.

Prediction of future asset prices

NASA Astrophysics Data System (ADS)

Seong, Ng Yew; Hin, Pooi Ah; Ching, Soo Huei

2014-12-01

This paper attempts to incorporate trading volumes as an additional predictor for predicting asset prices. Denoting r(t) as the vector consisting of the time-t values of the trading volume and price of a given asset, we model the time-(t+1) asset price to be dependent on the present and l-1 past values r(t), r(t-1), ....., r(t-1+1) via a conditional distribution which is derived from a (2l+1)-dimensional power-normal distribution. A prediction interval based on the 100(α/2)% and 100(1-α/2)% points of the conditional distribution is then obtained. By examining the average lengths of the prediction intervals found by using the composite indices of the Malaysia stock market for the period 2008 to 2013, we found that the value 2 appears to be a good choice for l. With the omission of the trading volume in the vector r(t), the corresponding prediction interval exhibits a slightly longer average length, showing that it might be desirable to keep trading volume as a predictor. From the above conditional distribution, the probability that the time-(t+1) asset price will be larger than the time-t asset price is next computed. When the probability differs from 0 (or 1) by less than 0.03, the observed time-(t+1) increase in price tends to be negative (or positive). Thus the above probability has a good potential of being used as a market indicator in technical analysis.

Modeling the expenditure and reconstitution of work capacity above critical power.

PubMed

Skiba, Philip Friere; Chidnok, Weerapong; Vanhatalo, Anni; Jones, Andrew M

2012-08-01

The critical power (CP) model includes two constants: the CP and the W' [P = (W' / t) + CP]. The W' is the finite work capacity available above CP. Power output above CP results in depletion of the W' complete depletion of the W' results in exhaustion. Monitoring the W' may be valuable to athletes during training and competition. Our purpose was to develop a function describing the dynamic state of the W' during intermittent exercise. After determination of V˙O(2max), CP, and W', seven subjects completed four separate exercise tests on a cycle ergometer on different days. Each protocol comprised a set of intervals: 60 s at a severe power output, followed by 30-s recovery at a lower prescribed power output. The intervals were repeated until exhaustion. These data were entered into a continuous equation predicting balance of W' remaining, assuming exponential reconstitution of the W'. The time constant was varied by an iterative process until the remaining modeled W' = 0 at the point of exhaustion. The time constants of W' recharge were negatively correlated with the difference between sub-CP recovery power and CP. The relationship was best fit by an exponential (r = 0.77). The model-predicted W' balance correlated with the temporal course of the rise in V˙O(2) (r = 0.82-0.96). The model accurately predicted exhaustion of the W' in a competitive cyclist during a road race. We have developed a function to track the dynamic state of the W' during intermittent exercise. This may have important implications for the planning and real-time monitoring of athletic performance.

Performance of comorbidity, risk adjustment, and functional status measures in expenditure prediction for patients with diabetes.

PubMed

Maciejewski, Matthew L; Liu, Chuan-Fen; Fihn, Stephan D

2009-01-01

To compare the ability of generic comorbidity and risk adjustment measures, a diabetes-specific measure, and a self-reported functional status measure to explain variation in health care expenditures for individuals with diabetes. This study included a retrospective cohort of 3,092 diabetic veterans participating in a multisite trial. Two comorbidity measures, four risk adjusters, a functional status measure, a diabetes complication count, and baseline expenditures were constructed from administrative and survey data. Outpatient, inpatient, and total expenditure models were estimated using ordinary least squares regression. Adjusted R(2) statistics and predictive ratios were compared across measures to assess overall explanatory power and explanatory power of low- and high-cost subgroups. Administrative data-based risk adjusters performed better than the comorbidity, functional status, and diabetes-specific measures in all expenditure models. The diagnostic cost groups (DCGs) measure had the greatest predictive power overall and for the low- and high-cost subgroups, while the diabetes-specific measure had the lowest predictive power. A model with DCGs and the diabetes-specific measure modestly improved predictive power. Existing generic measures can be useful for diabetes-specific research and policy applications, but more predictive diabetes-specific measures are needed.

Age, body mass, and gender as predictors of masters olympic weightlifting performance.

PubMed

Thé, Dwight J; Ploutz-Snyder, Lori

2003-07-01

The purpose of this study was to examine previously collected performance scores from the 2000 World Masters Weightlifting Championships to 1). determine the extent to which age and body mass are related to and predictive of indirect estimates of absolute and relative muscular power, and 2). assess possible gender differences in these associations. Dependent variables were absolute load (ABS = heaviest snatch [kg] + heaviest clean and jerk [kg]) and relative load (REL = ABS [kg]/body mass [kg]), representing indirect estimates of absolute and relative muscular power, respectively. Predictor variables were age (yr) and body mass (kg). Linear regression and various diagnostic procedures were used to analyze the data. The linear model provided an adequate fit for the data because no departures from the usual assumptions of normally distributed variables and homoscedastic error variance were observed. All predictor variables were significantly (P < 0.05) predictive of the dependent variables, but the magnitude of associations (e.g., R(ABS|BM) = 0.18 among females vs R(ABS|BM) = 0.57 among males) and extent of predictive ability (e.g., R(adj)2 for regression of ABS on age and body mass was 0.18-0.58 among females vs 0.74-0.83 among males) were significantly (P < 0.05) higher among males versus females. The extent to which age and body mass explain differences in muscular power differs between female and male masters weightlifters, but the rate of decline (%.yr-1) in power with advancing age is similar and is in agreement with previous reports for world record holders, other masters athletes, and healthy, untrained individuals, suggesting the importance of the aging process itself over physical activity history.

Mechanical work for step-to-step transitions is a major determinant of the metabolic cost of human walking.

PubMed

Donelan, J Maxwell; Kram, Rodger; Kuo, Arthur D

2002-12-01

In the single stance phase of walking, center of mass motion resembles that of an inverted pendulum. Theoretically, mechanical work is not necessary for producing the pendular motion, but work is needed to redirect the center of mass velocity from one pendular arc to the next during the transition between steps. A collision model predicts a rate of negative work proportional to the fourth power of step length. Positive work is required to restore the energy lost, potentially exacting a proportional metabolic cost. We tested these predictions with humans (N=9) walking over a range of step lengths (0.4-1.1 m) while keeping step frequency fixed at 1.8 Hz. We measured individual limb external mechanical work using force plates, and metabolic rate using indirect calorimetry. As predicted, average negative and positive external mechanical work rates increased with the fourth power of step length (from 1 W to 38 W; r(2)=0.96). Metabolic rate also increased with the fourth power of step length (from 7 W to 379 W; r(2)=0.95), and linearly with mechanical work rate. Mechanical work for step-to-step transitions, rather than pendular motion itself, appears to be a major determinant of the metabolic cost of walking.

Rational selection of training and test sets for the development of validated QSAR models

NASA Astrophysics Data System (ADS)

Golbraikh, Alexander; Shen, Min; Xiao, Zhiyan; Xiao, Yun-De; Lee, Kuo-Hsiung; Tropsha, Alexander

2003-02-01

Quantitative Structure-Activity Relationship (QSAR) models are used increasingly to screen chemical databases and/or virtual chemical libraries for potentially bioactive molecules. These developments emphasize the importance of rigorous model validation to ensure that the models have acceptable predictive power. Using k nearest neighbors ( kNN) variable selection QSAR method for the analysis of several datasets, we have demonstrated recently that the widely accepted leave-one-out (LOO) cross-validated R2 (q2) is an inadequate characteristic to assess the predictive ability of the models [Golbraikh, A., Tropsha, A. Beware of q2! J. Mol. Graphics Mod. 20, 269-276, (2002)]. Herein, we provide additional evidence that there exists no correlation between the values of q 2 for the training set and accuracy of prediction ( R 2) for the test set and argue that this observation is a general property of any QSAR model developed with LOO cross-validation. We suggest that external validation using rationally selected training and test sets provides a means to establish a reliable QSAR model. We propose several approaches to the division of experimental datasets into training and test sets and apply them in QSAR studies of 48 functionalized amino acid anticonvulsants and a series of 157 epipodophyllotoxin derivatives with antitumor activity. We formulate a set of general criteria for the evaluation of predictive power of QSAR models.

Predicting Rediated Noise With Power Flow Finite Element Analysis

DTIC Science & Technology

2007-02-01

Defence R&D Canada – Atlantic DEFENCE DÉFENSE & Predicting Rediated Noise With Power Flow Finite Element Analysis D. Brennan T.S. Koko L. Jiang J...PREDICTING RADIATED NOISE WITH POWER FLOW FINITE ELEMENT ANALYSIS D.P. Brennan T.S. Koko L. Jiang J.C. Wallace Martec Limited Martec Limited...model- or full-scale data before it is available for general use. Brennan, D.P., Koko , T.S., Jiang, L., Wallace, J.C. 2007. Predicting Radiated

Predictors of high-intensity running capacity in collegiate women during a soccer game.

PubMed

McCormack, William P; Stout, Jeffrey R; Wells, Adam J; Gonzalez, Adam M; Mangine, Gerald T; Fragala, Maren S; Hoffman, Jay R

2014-04-01

The purpose of this investigation was to determine which physiological assessments best predicted high-intensity running (HIR) performance during a women's collegiate soccer game. A secondary purpose was to examine the relationships among physiological performance measures including muscle architecture on soccer performance (distance covered, HIR, and sprints during the game) during a competitive collegiate women's soccer game. Ten National Collegiate Athletic Association (NCAA) Division I women soccer players performed physiological assessments within a 2-week period before a competitive regulation soccer game performed during the spring season. Testing consisted of height, body mass, ultrasound measurement of dominant (DOMleg), and nondominant leg (NDOMleg) vastus lateralis for muscle thickness (MT) and pennation angle (PA), VO2max, running economy, and Wingate anaerobic test (WAnT) for peak power (PP), mean power (MP), and fatigue rate (FR). During the game, distance run, HIR, and sprints were measured using a 10-Hz global positioning system. Stepwise regression revealed that VO2max, dominant leg thickness, and dominant leg PA were the strongest predictors of HIR distance during the game (R = 0.989, SEE = 115.5 m, p = 0.001). V[Combining Dot Above]O2max was significantly correlated with total distance run (r = 0.831; p = 0.003), HIR (r = 0.755; p = 0.012), WAnTPP (r = -0.737; p = 0.015), WAnTPP·kg (r = -0.706; p = 0.022), and WAnTFR (r = -0.713; p = 0.021). DOMlegMT was significantly correlated with WAnTFR (r = 0.893; p = 0.001). DOMlegPA was significantly correlated with WAnTFR (r = 0.740; p = 0.023). The NDOMlegPA was significantly correlated to peak running velocity (r = 0.781; p = 0.013) and WAnT MP·kg (r = 0.801; p = 0.01). Results of this study indicate that V[Combining Dot Above]O2max and muscle architecture are important characteristics of NCAA Division I women soccer players and may predict HIR distance during a competitive contest.

Multi-center prediction of hemorrhagic transformation in acute ischemic stroke using permeability imaging features.

PubMed

Scalzo, Fabien; Alger, Jeffry R; Hu, Xiao; Saver, Jeffrey L; Dani, Krishna A; Muir, Keith W; Demchuk, Andrew M; Coutts, Shelagh B; Luby, Marie; Warach, Steven; Liebeskind, David S

2013-07-01

Permeability images derived from magnetic resonance (MR) perfusion images are sensitive to blood-brain barrier derangement of the brain tissue and have been shown to correlate with subsequent development of hemorrhagic transformation (HT) in acute ischemic stroke. This paper presents a multi-center retrospective study that evaluates the predictive power in terms of HT of six permeability MRI measures including contrast slope (CS), final contrast (FC), maximum peak bolus concentration (MPB), peak bolus area (PB), relative recirculation (rR), and percentage recovery (%R). Dynamic T2*-weighted perfusion MR images were collected from 263 acute ischemic stroke patients from four medical centers. An essential aspect of this study is to exploit a classifier-based framework to automatically identify predictive patterns in the overall intensity distribution of the permeability maps. The model is based on normalized intensity histograms that are used as input features to the predictive model. Linear and nonlinear predictive models are evaluated using a cross-validation to measure generalization power on new patients and a comparative analysis is provided for the different types of parameters. Results demonstrate that perfusion imaging in acute ischemic stroke can predict HT with an average accuracy of more than 85% using a predictive model based on a nonlinear regression model. Results also indicate that the permeability feature based on the percentage of recovery performs significantly better than the other features. This novel model may be used to refine treatment decisions in acute stroke. Copyright © 2013 Elsevier Inc. All rights reserved.

Development and validation of a shared decision-making instrument for health-related quality of life one year after total hip replacement based on quality registries data.

PubMed

Nemes, Szilard; Rolfson, Ola; Garellick, Göran

2018-02-01

Clinicians considering improvements in health-related quality of life (HRQoL) after total hip replacement (THR) must account for multiple pieces of information. Evidence-based decisions are important to best assess the effect of THR on HRQoL. This work aims at constructing a shared decision-making tool that helps clinicians assessing the future benefits of THR by offering predictions of 1-year postoperative HRQoL of THR patients. We used data from the Swedish Hip Arthroplasty Register. Data from 2008 were used as training set and data from 2009 to 2012 as validation set. We adopted two approaches. First, we assumed a continuous distribution for the EQ-5D index and modelled the postoperative EQ-5D index with regression models. Second, we modelled the five dimensions of the EQ-5D and weighted together the predictions using the UK Time Trade-Off value set. As predictors, we used preoperative EQ-5D dimensions and the EQ-5D index, EQ visual analogue scale, visual analogue scale pain, Charnley classification, age, gender, body mass index, American Society of Anesthesiologists, surgical approach and prosthesis type. Additionally, the tested algorithms were combined in a single predictive tool by stacking. Best predictive power was obtained by the multivariate adaptive regression splines (R 2  = 0.158). However, this was not significantly better than the predictive power of linear regressions (R 2  = 0.157). The stacked model had a predictive power of 17%. Successful implementation of a shared decision-making tool that can aid clinicians and patients in understanding expected improvement in HRQoL following THR would require higher predictive power than we achieved. For a shared decision-making tool to succeed, further variables, such as socioeconomics, need to be considered. © 2016 John Wiley & Sons, Ltd.

An index predictive of cognitive outcome in retired professional American Football players with a history of sports concussion.

PubMed

Wright, Mathew J; Woo, Ellen; Birath, J Brandon; Siders, Craig A; Kelly, Daniel F; Wang, Christina; Swerdloff, Ronald; Romero, Elizabeth; Kernan, Claudia; Cantu, Robert C; Guskiewicz, Kevin

2016-01-01

Various concussion characteristics and personal factors are associated with cognitive recovery in athletes. We developed an index based on concussion frequency, severity, and timeframe, as well as cognitive reserve (CR), and we assessed its predictive power regarding cognitive ability in retired professional football players. Data from 40 retired professional American football players were used in the current study. On average, participants had been retired from football for 20 years. Current neuropsychological performances, indicators of CR, concussion history, and play data were used to create an index for predicting cognitive outcome. The sample displayed a range of concussions, concussion severities, seasons played, CR, and cognitive ability. Many of the participants demonstrated cognitive deficits. The index strongly predicted global cognitive ability (R(2) = .31). The index also predicted the number of areas of neuropsychological deficit, which varied as a function of the deficit classification system used (Heaton: R(2) = .15; Wechsler: R(2) = .28). The current study demonstrated that a unique combination of CR, sports concussion, and game-related data can predict cognitive outcomes in participants who had been retired from professional American football for an average of 20 years. Such indices may prove to be useful for clinical decision making and research.

3D QSAR studies on protein tyrosine phosphatase 1B inhibitors: comparison of the quality and predictivity among 3D QSAR models obtained from different conformer-based alignments.

PubMed

Pandey, Gyanendra; Saxena, Anil K

2006-01-01

A set of 65 flexible peptidomimetic competitive inhibitors (52 in the training set and 13 in the test set) of protein tyrosine phosphatase 1B (PTP1B) has been used to compare the quality and predictive power of 3D quantitative structure-activity relationship (QSAR) comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models for the three most commonly used conformer-based alignments, namely, cocrystallized conformer-based alignment (CCBA), docked conformer-based alignment (DCBA), and global minima energy conformer-based alignment (GMCBA). These three conformers of 5-[(2S)-2-({(2S)-2-[(tert-butoxycarbonyl)amino]-3-phenylpropanoyl}amino)3-oxo-3-pentylamino)propyl]-2-(carboxymethoxy)benzoic acid (compound number 66) were obtained from the X-ray structure of its cocrystallized complex with PTP1B (PDB ID: 1JF7), its docking studies, and its global minima by simulated annealing. Among the 3D QSAR models developed using the above three alignments, the CCBA provided the optimal predictive CoMFA model for the training set with cross-validated r2 (q2)=0.708, non-cross-validated r2=0.902, standard error of estimate (s)=0.165, and F=202.553 and the optimal CoMSIA model with q2=0.440, r2=0.799, s=0.192, and F=117.782. These models also showed the best test set prediction for the 13 compounds with predictive r2 values of 0.706 and 0.683, respectively. Though the QSAR models derived using the other two alignments also produced statistically acceptable models in the order DCBA>GMCBA in terms of the values of q2, r2, and predictive r2, they were inferior to the corresponding models derived using CCBA. Thus, the order of preference for the alignment selection for 3D QSAR model development may be CCBA>DCBA>GMCBA, and the information obtained from the CoMFA and CoMSIA contour maps may be useful in designing specific PTP1B inhibitors.

Predictors of outcomes in patients with primary retroperitoneal dedifferentiated liposarcoma undergoing surgery.

PubMed

Keung, Emily Z; Hornick, Jason L; Bertagnolli, Monica M; Baldini, Elizabeth H; Raut, Chandrajit P

2014-02-01

Although sarcoma histology is recognized as a prognostic factor, most studies of retroperitoneal sarcomas report results combining multiple histologies and are inadequately powered to identify prognostic factors specific to a particular histology. We reviewed our experience with retroperitoneal dedifferentiated liposarcoma (RP DDLPS) to identify factors predictive of outcomes. All patients with RP DDLPS treated at our institution between 1998 and 2008 were reviewed. Multivariable Cox regression analyses were performed to identify factors predictive of progression-free survival (PFS), local recurrence-free survival (LRFS), distant recurrence-free survival (DRFS), and overall survival (OS). We identified 119 patients with primary DDLPS. Median tumor size was 20.5 cm; 21% were multifocal. French Federation of Cancer Centers Sarcoma Group tumor grades were intermediate in 53% of patients and high in 28% (unknown 19%). Resections were complete (R0/R1) in 80% of patients and incomplete (R2) in 11% (unknown 9%). Tumors were removed intact in 72% of patients and fragmented in 16% (unknown 12%). Median follow-up was 74.1 months. One hundred patients (84%) experienced recurrence or progression, with 92% occurring in the retroperitoneum. Median PFS, LRFS, DRFS, and OS were 21.1, 21.5, 45.8, and 59.0 months, respectively, and were significantly worse with R2 resection. On multivariate analysis, tumor integrity (intact vs fragmented) was predictive of PFS, multifocality predicted LRFS, and extent of resection (R0/R1 vs R2), grade, and tumor integrity predicted OS. In this cohort of primary RP DDLPS, factors under surgeon control (tumor integrity, extent of resection) and reflective of tumor biology (grade, multifocality) impact patient outcomes. Copyright © 2014 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

A phenomenological model of muscle fatigue and the power-endurance relationship.

PubMed

James, A; Green, S

2012-11-01

The relationship between power output and the time that it can be sustained during exercise (i.e., endurance) at high intensities is curvilinear. Although fatigue is implicit in this relationship, there is little evidence pertaining to it. To address this, we developed a phenomenological model that predicts the temporal response of muscle power during submaximal and maximal exercise and which was based on the type, contractile properties (e.g., fatiguability), and recruitment of motor units (MUs) during exercise. The model was first used to predict power outputs during all-out exercise when fatigue is clearly manifest and for several distributions of MU type. The model was then used to predict times that different submaximal power outputs could be sustained for several MU distributions, from which several power-endurance curves were obtained. The model was simultaneously fitted to two sets of human data pertaining to all-out exercise (power-time profile) and submaximal exercise (power-endurance relationship), yielding a high goodness of fit (R(2) = 0.96-0.97). This suggested that this simple model provides an accurate description of human power output during submaximal and maximal exercise and that fatigue-related processes inherent in it account for the curvilinearity of the power-endurance relationship.

Association between selected physical fitness parameters and esthetic competence in contemporary dancers.

PubMed

Angioi, Manuela; Metsios, George S; Twitchett, Emily; Koutedakis, Yiannis; Wyon, Matthew

2009-01-01

The physical demands imposed on contemporary dancers by choreographers and performance schedules make their physical fitness just as important to them as skill development. Nevertheless, it remains to be confirmed which physical fitness components are associated with aesthetic competence. The aim of this study was to: 1. replicate and test a novel aesthetic competence tool for reliability, and 2. investigate the association between selected physical fitness components and aesthetic competence by using this new tool. Seventeen volunteers underwent a series of physical fitness tests (body composition, flexibility, muscular power and endurance, and aerobic capacity) and aesthetic competence assessments (seven individual criteria commonly used by selected dance companies). Inter-rater reliability of the aesthetic competence tool was very high (r = 0.96). There were significant correlations between the aesthetic competence score and jump ability and push-ups (r = 0.55 and r = 0.55, respectively). Stepwise backward multiple regression analysis revealed that the best predictor of aesthetic competence was push-ups (R(2) = 0.30, p = 0.03). Univariate analyses also revealed that the interaction of push-ups and jump ability improved the prediction power of aesthetic competence (R(2) = 0.44, p = 0.004). It is concluded that upper body muscular endurance and jump ability best predict aesthetic competence of the present sample of contemporary dancers. Further research is required to investigate the contribution of other components of aesthetic competence, including upper body strength, lower body muscular endurance, general coordination, and static and dynamic balance.

From Motion to Emotion: Accelerometer Data Predict Subjective Experience of Music

PubMed Central

Irrgang, Melanie

2016-01-01

Music is often discussed to be emotional because it reflects expressive movements in audible form. Thus, a valid approach to measure musical emotion could be to assess movement stimulated by music. In two experiments we evaluated the discriminative power of mobile-device generated acceleration data produced by free movement during music listening for the prediction of ratings on the Geneva Emotion Music Scales (GEMS-9). The quality of prediction for different dimensions of GEMS varied between experiments for tenderness (R12(first experiment) = 0.50, R22(second experiment) = 0.39), nostalgia (R12 = 0.42, R22 = 0.30), wonder (R12 = 0.25, R22 = 0.34), sadness (R12 = 0.24, R22 = 0.35), peacefulness (R12 = 0.20, R22 = 0.35) and joy (R12 = 0.19, R22 = 0.33) and transcendence (R12 = 0.14, R22 = 0.00). For others like power (R12 = 0.42, R22 = 0.49) and tension (R12 = 0.28, R22 = 0.27) results could be almost reproduced. Furthermore, we extracted two principle components from GEMS ratings, one representing arousal and the other one valence of the experienced feeling. Both qualities, arousal and valence, could be predicted by acceleration data, indicating, that they provide information on the quantity and quality of experience. On the one hand, these findings show how music-evoked movement patterns relate to music-evoked feelings. On the other hand, they contribute to integrate findings from the field of embodied music cognition into music recommender systems. PMID:27415015

From Motion to Emotion: Accelerometer Data Predict Subjective Experience of Music.

PubMed

Irrgang, Melanie; Egermann, Hauke

2016-01-01

Music is often discussed to be emotional because it reflects expressive movements in audible form. Thus, a valid approach to measure musical emotion could be to assess movement stimulated by music. In two experiments we evaluated the discriminative power of mobile-device generated acceleration data produced by free movement during music listening for the prediction of ratings on the Geneva Emotion Music Scales (GEMS-9). The quality of prediction for different dimensions of GEMS varied between experiments for tenderness (R12(first experiment) = 0.50, R22(second experiment) = 0.39), nostalgia (R12 = 0.42, R22 = 0.30), wonder (R12 = 0.25, R22 = 0.34), sadness (R12 = 0.24, R22 = 0.35), peacefulness (R12 = 0.20, R22 = 0.35) and joy (R12 = 0.19, R22 = 0.33) and transcendence (R12 = 0.14, R22 = 0.00). For others like power (R12 = 0.42, R22 = 0.49) and tension (R12 = 0.28, R22 = 0.27) results could be almost reproduced. Furthermore, we extracted two principle components from GEMS ratings, one representing arousal and the other one valence of the experienced feeling. Both qualities, arousal and valence, could be predicted by acceleration data, indicating, that they provide information on the quantity and quality of experience. On the one hand, these findings show how music-evoked movement patterns relate to music-evoked feelings. On the other hand, they contribute to integrate findings from the field of embodied music cognition into music recommender systems.

Relationship between percentages of heart rate reserve and oxygen uptake reserve during cycling and running: a validation study.

PubMed

Guimarães, Giovanna C; Farinatti, Paulo T V; Midgley, Adrian W; Vasconcellos, Fabrício; Vigário, Patrícia; Cunha, Felipe A

2017-06-22

The present study investigated the relationship between percentages of heart rate reserve (%HRR) and oxygen uptake reserve (%VO2R) during a cardiopulmonary exercise test (CPET) and discrete bouts of isocaloric cycling and treadmill running. Thirty men visited the laboratory three times for anthropometrical and resting VO2 assessments, and perform cycling and running CPETs. Ten men visited the laboratory twice more to investigate the validity of the %HRR-%VO2R relationships during isocaloric bouts of cycling and running at 75% VO2R with energy expenditures of 400 kcals. The %HRR was significantly higher than the %VO2R during both CPETs at all exercise intensities (P < 0.001). During isocaloric exercise bouts, mean %HRR-%VO2R differences of 6.5% and 7.0% were observed for cycling and running, respectively (P = 0.007 to P < 0.001). The %HRR and %VO2R increased over time (P < 0.001), the rate of which was influenced by exercise modality (P < 0.001). On average, heart rate was 5 (P = 0.007) and 8 (P < 0.001) beats·min higher than predicted from the second energy expenditure quartile for cycling and running, respectively; however, observed VO2 was lower than predicted during all quartiles for cycling, and the first quartile for running. Consequently, time to achieve the target energy expenditure was greater than predicted (P < 0.01). In conclusion, the %HRR-%VO2R relationship observed during CPET data did not accurately transpose to prolonged isocaloric bouts of cycling and running. Additionally, power outputs and speeds defined by the ACSM equations for cycling and running, respectively, overestimated VO2 and energy expenditure.

Neonatal Sleep-Wake Analyses Predict 18-month Neurodevelopmental Outcomes.

PubMed

Shellhaas, Renée A; Burns, Joseph W; Hassan, Fauziya; Carlson, Martha D; Barks, John D E; Chervin, Ronald D

2017-11-01

The neurological examination of critically ill neonates is largely limited to reflexive behavior. The exam often ignores sleep-wake physiology that may reflect brain integrity and influence long-term outcomes. We assessed whether polysomnography and concurrent cerebral near-infrared spectroscopy (NIRS) might improve prediction of 18-month neurodevelopmental outcomes. Term newborns with suspected seizures underwent standardized neurologic examinations to generate Thompson scores and had 12-hour bedside polysomnography with concurrent cerebral NIRS. For each infant, the distribution of sleep-wake stages and electroencephalogram delta power were computed. NIRS-derived fractional tissue oxygen extraction (FTOE) was calculated across sleep-wake stages. At age 18-22 months, surviving participants were evaluated with Bayley Scales of Infant Development (Bayley-III), 3rd edition. Twenty-nine participants completed Bayley-III. Increased newborn time in quiet sleep predicted worse 18-month cognitive and motor scores (robust regression models, adjusted r2 = 0.22, p = .007, and 0.27, .004, respectively). Decreased 0.5-2 Hz electroencephalograph (EEG) power during quiet sleep predicted worse 18-month language and motor scores (adjusted r2 = 0.25, p = .0005, and 0.33, .001, respectively). Predictive values remained significant after adjustment for neonatal Thompson scores or exposure to phenobarbital. Similarly, an attenuated difference in FTOE, between neonatal wakefulness and quiet sleep, predicted worse 18-month cognitive, language, and motor scores in adjusted analyses (each p < .05). These prospective, longitudinal data suggest that inefficient neonatal sleep-as quantified by increased time in quiet sleep, lower electroencephalogram delta power during that stage, and muted differences in FTOE between quiet sleep and wakefulness-may improve prediction of adverse long-term outcomes for newborns with neurological dysfunction. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

Performance of Comorbidity, Risk Adjustment, and Functional Status Measures in Expenditure Prediction for Patients With Diabetes

PubMed Central

Maciejewski, Matthew L.; Liu, Chuan-Fen; Fihn, Stephan D.

2009-01-01

OBJECTIVE—To compare the ability of generic comorbidity and risk adjustment measures, a diabetes-specific measure, and a self-reported functional status measure to explain variation in health care expenditures for individuals with diabetes. RESEARCH DESIGN AND METHODS—This study included a retrospective cohort of 3,092 diabetic veterans participating in a multisite trial. Two comorbidity measures, four risk adjusters, a functional status measure, a diabetes complication count, and baseline expenditures were constructed from administrative and survey data. Outpatient, inpatient, and total expenditure models were estimated using ordinary least squares regression. Adjusted R2 statistics and predictive ratios were compared across measures to assess overall explanatory power and explanatory power of low- and high-cost subgroups. RESULTS—Administrative data–based risk adjusters performed better than the comorbidity, functional status, and diabetes-specific measures in all expenditure models. The diagnostic cost groups (DCGs) measure had the greatest predictive power overall and for the low- and high-cost subgroups, while the diabetes-specific measure had the lowest predictive power. A model with DCGs and the diabetes-specific measure modestly improved predictive power. CONCLUSIONS—Existing generic measures can be useful for diabetes-specific research and policy applications, but more predictive diabetes-specific measures are needed. PMID:18945927

ACTN3 genotype does not influence muscle power.

PubMed

Hanson, E D; Ludlow, A T; Sheaff, A K; Park, J; Roth, S M

2010-11-01

The R577X polymorphism within the ACTN3 gene has been associated with elite athletic performance, strength, power, fat free mass, and adaptations to strength training, though inconsistencies exist in the literature. The specific muscle power phenotypes most influenced by the polymorphism are uncertain. The purpose of this study was to examine the association between ACTN3 R577X genotype and muscle power phenotypes. Recreationally active young men and women (N=57) were selected to complete 2 muscle performance assessments, an isokinetic fatigue protocol at testing speeds of 180°  s (-1) and 250°  s (-1) and a 30 s Wingate test. Isokinetic torque and Wingate power significantly decreased over the duration of each test, but no differences in the rate of decline were observed among ACTN3 genotype groups. Similarly, no significant genotype differences were observed for isokinetic peak torque, Wingate absolute or relative peak power, or fatigue index. These results indicate that in recreationally active individuals the ACTN3 R577X polymorphism is not associated with muscle performance phenotypes, supporting recent findings that R577X may only be important for predicting performance in elite athletes. Our data also indicate that using this polymorphism for genetic screening in the lay population is scientifically questionable.

An extended fatty liver index to predict non-alcoholic fatty liver disease.

PubMed

Kantartzis, K; Rettig, I; Staiger, H; Machann, J; Schick, F; Scheja, L; Gastaldelli, A; Bugianesi, E; Peter, A; Schulze, M B; Fritsche, A; Häring, H-U; Stefan, N

2017-06-01

In clinical practice, there is a strong interest in non-invasive markers of non-alcoholic fatty liver disease (NAFLD). Our hypothesis was that the fold-change in plasma triglycerides (TG) during a 2-h oral glucose tolerance test (fold-change TG OGTT ) in concert with blood glucose and lipid parameters, and the rs738409 C>G single nucleotide polymorphism (SNP) in PNPLA3 might improve the power of the widely used fatty liver index (FLI) to predict NAFLD. The liver fat content of 330 subjects was quantified by 1 H-magnetic resonance spectroscopy. Blood parameters were measured during fasting and after a 2-h OGTT. A subgroup of 213 subjects underwent these measurements before and after 9 months of a lifestyle intervention. The fold-change TG OGTT was closely associated with liver fat content (r=0.51, P<0.0001), but had less power to predict NAFLD (AUROC=0.75) than the FLI (AUROC=0.79). Not only was the fold-change TG OGTT independently associated with liver fat content and NAFLD, but so also were the 2-h blood glucose level and rs738409 C>G SNP in PNPLA3. In fact, a novel index (extended FLI) generated from these and the usual FLI parameters considerably increased its power to predict NAFLD (AUROC=0.79-0.86). The extended FLI also increased the power to predict changes in liver fat content with a lifestyle intervention (n=213; standardized beta coefficient: 0.23-0.29). This study has provided novel data confirming that the OGTT-derived fold-change TG OGTT and 2-h glucose level, together with the rs738409 C>G SNP in PNPLA3, allow calculation of an extended FLI that considerably improves its power to predict NAFLD. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Can human experts predict solubility better than computers?

PubMed

Boobier, Samuel; Osbourn, Anne; Mitchell, John B O

2017-12-13

In this study, we design and carry out a survey, asking human experts to predict the aqueous solubility of druglike organic compounds. We investigate whether these experts, drawn largely from the pharmaceutical industry and academia, can match or exceed the predictive power of algorithms. Alongside this, we implement 10 typical machine learning algorithms on the same dataset. The best algorithm, a variety of neural network known as a multi-layer perceptron, gave an RMSE of 0.985 log S units and an R 2 of 0.706. We would not have predicted the relative success of this particular algorithm in advance. We found that the best individual human predictor generated an almost identical prediction quality with an RMSE of 0.942 log S units and an R 2 of 0.723. The collection of algorithms contained a higher proportion of reasonably good predictors, nine out of ten compared with around half of the humans. We found that, for either humans or algorithms, combining individual predictions into a consensus predictor by taking their median generated excellent predictivity. While our consensus human predictor achieved very slightly better headline figures on various statistical measures, the difference between it and the consensus machine learning predictor was both small and statistically insignificant. We conclude that human experts can predict the aqueous solubility of druglike molecules essentially equally well as machine learning algorithms. We find that, for either humans or algorithms, combining individual predictions into a consensus predictor by taking their median is a powerful way of benefitting from the wisdom of crowds.

Teacher ratings of DSM-III-R symptoms for the disruptive behavior disorders.

PubMed

Pelham, W E; Gnagy, E M; Greenslade, K E; Milich, R

1992-03-01

Ratings were collected on a rating scale comprised of the DSM-III-R diagnostic criteria for disruptive behavior disorders. Teacher ratings were obtained for 931 boys in regular classrooms in grades K through 8 from around North America. Means and standard deviations for attention-deficit hyperactivity disorder (ADHD), oppositional-defiant disorder (ODD), and conduct disorder (CD) scales are reported by age. Frequencies of DSM-III-R symptoms are reported by age, and suggested diagnostic cutoffs are discussed. A factor analysis revealed three factors: one reflecting ODD and several CD symptoms, one on which ADHD symptoms of inattention loaded, and one comprised of ADHD impulsivity/overactivity symptoms. Conditional probability analyses revealed that several hallmark symptoms of ADHD had very poor predictive power, whereas combinations of symptoms from the two ADHD factors had good predictive power. Combinations of ODD symptoms also had very high predictive power. The limited utility of teacher ratings in assessing symptoms of conduct disorder in this age range is discussed.

Conformations of organophosphine oxides

DOE PAGES

De Silva, Nuwan; Zahariev, Federico; Hay, Benjamin P.; ...

2015-07-17

The conformations of a series of organophosphine oxides, OP(CH 3) 2R, where R = methyl, ethyl, isopropyl, tert-butyl, vinyl, and phenyl, are predicted using the MP2/cc-pVTZ level of theory. Comparison of potential energy surfaces for rotation about P–C bonds with crystal structure data reveals a strong correlation between predicted location and energetics of minima and histograms of dihedral angle distributions observed in the solid state. In addition, the most stable conformers are those that minimize the extent of steric repulsion between adjacent rotor substituents, and the torsional barriers tend to increase with the steric bulk of the rotating alkyl group.more » MM3 force field parameters were adjusted to fit the MP2 results, providing a fast and accurate model for predicting organophosphine oxides shapes—an essential part of understanding the chemistry of these compounds. As a result, the predictive power of the modified MM3 model was tested against MP2/cc-pVTZ conformations for triethylphosphine oxide, OP(CH 2CH 3) 3, and triphenylphosphine oxide, OP(Ph) 3.« less

Predicting Blood Lactate Concentration and Oxygen Uptake from sEMG Data during Fatiguing Cycling Exercise.

PubMed

Ražanskas, Petras; Verikas, Antanas; Olsson, Charlotte; Viberg, Per-Arne

2015-08-19

This article presents a study of the relationship between electromyographic (EMG) signals from vastus lateralis, rectus femoris, biceps femoris and semitendinosus muscles, collected during fatiguing cycling exercises, and other physiological measurements, such as blood lactate concentration and oxygen consumption. In contrast to the usual practice of picking one particular characteristic of the signal, e.g., the median or mean frequency, multiple variables were used to obtain a thorough characterization of EMG signals in the spectral domain. Based on these variables, linear and non-linear (random forest) models were built to predict blood lactate concentration and oxygen consumption. The results showed that mean and median frequencies are sub-optimal choices for predicting these physiological quantities in dynamic exercises, as they did not exhibit significant changes over the course of our protocol and only weakly correlated with blood lactate concentration or oxygen uptake. Instead, the root mean square of the original signal and backward difference, as well as parameters describing the tails of the EMG power distribution were the most important variables for these models. Coefficients of determination ranging from R(2) = 0:77 to R(2) = 0:98 (for blood lactate) and from R(2) = 0:81 to R(2) = 0:97 (for oxygen uptake) were obtained when using random forest regressors.

Prediction of some physical and drying properties of terebinth fruit (Pistacia atlantica L.) using Artificial Neural Networks.

PubMed

Kaveh, Mohammad; Chayjan, Reza Amiri

2014-01-01

Drying of terebinth fruit was conducted to provide microbiological stability, reduce product deterioration due to chemical reactions, facilitate storage and lower transportation costs. Because terebinth fruit is susceptible to heat, the selection of a suitable drying technology is a challenging task. Artificial neural networks (ANNs) are used as a nonlinear mapping structures for modelling and prediction of some physical and drying properties of terebinth fruit. Drying characteristics of terebinth fruit with an initial moisture content of 1.16 (d.b.) was studied in an infrared fluidized bed dryer. Different levels of air temperatures (40, 55 and 70°C), air velocities (0.93, 1.76 and 2.6 m/s) and infrared (IR) radiation powers (500, 1000 and 1500 W) were applied. In the present study, the application of Artificial Neural Network (ANN) for predicting the drying moisture diffusivity, energy consumption, shrinkage, drying rate and moisture ratio (output parameter for ANN modelling) was investigated. Air temperature, air velocity, IR radiation and drying time were considered as input parameters. The results revealed that to predict drying rate and moisture ratio a network with the TANSIG-LOGSIG-TANSIG transfer function and Levenberg-Marquardt (LM) training algorithm made the most accurate predictions for the terebinth fruit drying. The best results for ANN at predications were R2 = 0.9678 for drying rate, R2 = 0.9945 for moisture ratio, R2 = 0.9857 for moisture diffusivity and R2 = 0.9893 for energy consumption. Results indicated that artificial neural network can be used as an alternative approach for modelling and predicting of terebinth fruit drying parameters with high correlation. Also ANN can be used in optimization of the process.

Wind Power predictability a risk factor in the design, construction and operation of Wind Generation Turbines

NASA Astrophysics Data System (ADS)

Thiesen, J.; Gulstad, L.; Ristic, I.; Maric, T.

2010-09-01

Summit: The wind power predictability is often a forgotten decision and planning factor for most major wind parks, both onshore and offshore. The results of the predictability are presented after having examined a number of European offshore and offshore parks power predictability by using three(3) mesoscale model IRIE_GFS and IRIE_EC and WRF. Full description: It is well known that the potential wind production is changing with latitude and complexity in terrain, but how big are the changes in the predictability and the economic impacts on a project? The concept of meteorological predictability has hitherto to some degree been neglected as a risk factor in the design, construction and operation of wind power plants. Wind power plants are generally built in places where the wind resources are high, but these are often also sites where the predictability of the wind and other weather parameters is comparatively low. This presentation addresses the question of whether higher predictability can outweigh lower average wind speeds with regard to the overall economy of a wind power project. Low predictability also tends to reduce the value of the energy produced. If it is difficult to forecast the wind on a site, it will also be difficult to predict the power production. This, in turn, leads to increased balance costs and a less reduced carbon emission from the renewable source. By investigating the output from three(3) mesoscale models IRIE and WRF, using ECMWF and GFS as boundary data over a forecasting period of 3 months for 25 offshore and onshore wind parks in Europe, the predictability are mapped. Three operational mesoscale models with two different boundary data have been chosen in order to eliminate the uncertainty with one mesoscale model. All mesoscale models are running in a 10 km horizontal resolution. The model output are converted into "day a head" wind turbine generation forecasts by using a well proven advanced physical wind power model. The power models are using a number of weather parameters like wind speed in different heights, friction velocity and DTHV. The 25 wind sites are scattered around in Europe and contains 4 offshore parks and 21 onshore parks in various terrain complexity. The "day a head" forecasts are compared with production data and predictability for the period February 2010-April 2010 are given in Mean Absolute Errors (MAE) and Root Mean Squared Errors (RMSE). The power predictability results are mapped for each turbine giving a clear picture of the predictability in Europe. . Finally a economic analysis are shown for each wind parks in different regimes of predictability will be compared with regard to the balance costs that result from errors in the wind power prediction. Analysis shows that it may very well be profitable to place wind parks in regions of lower, but more predictable wind ressource. Authors: Ivan Ristic, CTO Weather2Umberlla D.O.O Tomislav Maric, Meteorologist at Global Flow Solutions Vestas Wind Technology R&D Line Gulstad, Manager Global Flow Solutions Vestas Wind Technology R&D Jesper Thiesen, CEO ConWx ApS

The extension of total gain (TG) statistic in survival models: properties and applications.

PubMed

Choodari-Oskooei, Babak; Royston, Patrick; Parmar, Mahesh K B

2015-07-01

The results of multivariable regression models are usually summarized in the form of parameter estimates for the covariates, goodness-of-fit statistics, and the relevant p-values. These statistics do not inform us about whether covariate information will lead to any substantial improvement in prediction. Predictive ability measures can be used for this purpose since they provide important information about the practical significance of prognostic factors. R (2)-type indices are the most familiar forms of such measures in survival models, but they all have limitations and none is widely used. In this paper, we extend the total gain (TG) measure, proposed for a logistic regression model, to survival models and explore its properties using simulations and real data. TG is based on the binary regression quantile plot, otherwise known as the predictiveness curve. Standardised TG ranges from 0 (no explanatory power) to 1 ('perfect' explanatory power). The results of our simulations show that unlike many of the other R (2)-type predictive ability measures, TG is independent of random censoring. It increases as the effect of a covariate increases and can be applied to different types of survival models, including models with time-dependent covariate effects. We also apply TG to quantify the predictive ability of multivariable prognostic models developed in several disease areas. Overall, TG performs well in our simulation studies and can be recommended as a measure to quantify the predictive ability in survival models.

Do physiological measures predict selected CrossFit(®) benchmark performance?

PubMed

Butcher, Scotty J; Neyedly, Tyler J; Horvey, Karla J; Benko, Chad R

2015-01-01

CrossFit(®) is a new but extremely popular method of exercise training and competition that involves constantly varied functional movements performed at high intensity. Despite the popularity of this training method, the physiological determinants of CrossFit performance have not yet been reported. The purpose of this study was to determine whether physiological and/or muscle strength measures could predict performance on three common CrossFit "Workouts of the Day" (WODs). Fourteen CrossFit Open or Regional athletes completed, on separate days, the WODs "Grace" (30 clean and jerks for time), "Fran" (three rounds of thrusters and pull-ups for 21, 15, and nine repetitions), and "Cindy" (20 minutes of rounds of five pull-ups, ten push-ups, and 15 bodyweight squats), as well as the "CrossFit Total" (1 repetition max [1RM] back squat, overhead press, and deadlift), maximal oxygen consumption (VO2max), and Wingate anaerobic power/capacity testing. Performance of Grace and Fran was related to whole-body strength (CrossFit Total) (r=-0.88 and -0.65, respectively) and anaerobic threshold (r=-0.61 and -0.53, respectively); however, whole-body strength was the only variable to survive the prediction regression for both of these WODs (R (2)=0.77 and 0.42, respectively). There were no significant associations or predictors for Cindy. CrossFit benchmark WOD performance cannot be predicted by VO2max, Wingate power/capacity, or either respiratory compensation or anaerobic thresholds. Of the data measured, only whole-body strength can partially explain performance on Grace and Fran, although anaerobic threshold also exhibited association with performance. Along with their typical training, CrossFit athletes should likely ensure an adequate level of strength and aerobic endurance to optimize performance on at least some benchmark WODs.

Association between laboratory capacities and world-cup performance in Nordic combined

PubMed Central

Fudel, Ronny; Kocbach, Jan; Moen, Frode; Ettema, Gertjan; Sandbakk, Øyvind

2017-01-01

Background Nordic combined (NC) is an Olympic winter-sport performed as a ski jumping (SJ) event followed by a cross-country (XC) pursuit race employing the skating style. Purpose To elucidate the associations between sport-specific laboratory capacities and SJ, XC skiing, and overall NC performance in a world-cup NC event. Methods Twelve international world-cup NC athletes from 8 nations performed laboratory testing one day prior to participating in a world-cup NC event. Squat jumps and SJ imitations (IMIT) were performed on a three-dimensional force plate, whereas XC skiing-specific physiological characteristics were obtained from roller ski skating tests on a treadmill and an all-out double poling (DP) test. Finally, body composition was measured. Laboratory capacities were correlated against performance in SJ, 10-km XC skiing, and overall NC in the world-cup event. Multiple regression analysis was used to determine the best suited laboratory variables for predicting performance. Results Vertical IMIT velocity together with body-mass provided the best prediction for SJ performance (r2 = 0.70, p<0.01), while body-mass-normalized V˙O2peak and DP power provided the best prediction for XC performance (r2 = 0.68, p<0.05). Body-mass-normalized V˙O2peak was the only significant correlate with overall NC performance (r2 = 0.43, p<0.05) in this competition. Conclusion Overall, the concurrent development of V˙O2peak, upper-body power, and SJ-specific vertical jump capacity while minimizing body-mass within the BMI limit set by FIS should be considered in the seasonal training of NC athletes. PMID:28662163

Comparison of simulation results with sea-level experimental data on 10(14) - 10(16) air shower cores

NASA Technical Reports Server (NTRS)

Ash, A. G.

1985-01-01

Simulation predictions for the Leeds 35 sq m horizontal discharge chamber array for proton primaries with a approx. E sup 2.7 spectrum extrapolated from balloon data to 10 to the 16th power eV give power law rho (r)-spectra with constant slope approx. -2 consistent with the experimental data up to the point at which they steepen but overshooting them at higher densities, and at high shower sizes predicted cores which are significantly steeper than those observed. Further comparisons with results for heavy nuclei primaries (up to A = 56) point to the inadequacy of changes in primary composition to account for the observed density spectra and core flattening, and the shower size spectrum together, and point, therefore, to the failure of the scaling interaction model at approx. 10 to the 15th power eV primary energy.

Non-Porod scattering and non-integer scaling of resistance in rough films

NASA Astrophysics Data System (ADS)

Bupathy, Arunkumar; Verma, Rupesh; Banerjee, Varsha; Puri, Sanjay

2017-04-01

In many physical systems, films are rough due to the stochastic behavior of depositing particles. They are characterized by non-Porod power law decays in the structure factor S (k) . Theoretical studies predict anomalous diffusion in such morphologies, with important implications for diffusivity, conductivity, etc. We use the non-Porod decay to accurately determine the fractal properties of two prototypical nanoparticle films: (i) Palladium (Pd) and (ii) Cu2O. Using scaling arguments, we find that the resistance of rough films of lateral size L obeys a non-integer power law R ∼L-ζ , in contrast to integer power laws for compact structures. The exponent ζ is anisotropic. We confirm our predictions by re-analyzing experimental data from Cu2O nano-particle films. Our results are valuable for understanding recent experiments that report anisotropic electrical properties in (rough) thin films.

Prediction of Critical Power and W' in Hypoxia: Application to Work-Balance Modelling.

PubMed

Townsend, Nathan E; Nichols, David S; Skiba, Philip F; Racinais, Sebastien; Périard, Julien D

2017-01-01

Purpose: Develop a prediction equation for critical power (CP) and work above CP (W') in hypoxia for use in the work-balance ([Formula: see text]) model. Methods: Nine trained male cyclists completed cycling time trials (TT; 12, 7, and 3 min) to determine CP and W' at five altitudes (250, 1,250, 2,250, 3,250, and 4,250 m). Least squares regression was used to predict CP and W' at altitude. A high-intensity intermittent test (HIIT) was performed at 250 and 2,250 m. Actual and predicted CP and W' were used to compute W' during HIIT using differential ([Formula: see text]) and integral ([Formula: see text]) forms of the [Formula: see text] model. Results: CP decreased at altitude ( P < 0.001) as described by 3rd order polynomial function ( R 2 = 0.99). W' decreased at 4,250 m only ( P < 0.001). A double-linear function characterized the effect of altitude on W' ( R 2 = 0.99). There was no significant effect of parameter input (actual vs. predicted CP and W') on modelled [Formula: see text] at 2,250 m ( P = 0.24). [Formula: see text] returned higher values than [Formula: see text] throughout HIIT ( P < 0.001). During HIIT, [Formula: see text] was not different to 0 kJ at completion, at 250 m (0.7 ± 2.0 kJ; P = 0.33) and 2,250 m (-1.3 ± 3.5 kJ; P = 0.30). However, [Formula: see text] was lower than 0 kJ at 250 m (-0.9 ± 1.3 kJ; P = 0.058) and 2,250 m (-2.8 ± 2.8 kJ; P = 0.02). Conclusion: The altitude prediction equations for CP and W' developed in this study are suitable for use with the [Formula: see text] model in acute hypoxia. This enables the application of [Formula: see text] modelling to training prescription and competition analysis at altitude.

Methods for measuring serum activity levels of the 192 Q and R isoenzymes of paraoxonase 1 in QR heterozygous individuals.

PubMed

Teiber, John F; Kramer, Gerald L; Haley, Robert W

2013-08-01

Paraoxonase 1 (PON1), an esterase that hydrolyzes toxic organophosphates and has antioxidative and antiatherogenic properties, contains a common polymorphism at position 192: glutamine (Q) or arginine (R). The Q and R isoenzymes exhibit different physical and protective properties. We describe 2 methods for quantifying their serum activity levels. We measured serum hydrolytic activity with paraoxon [paraoxonase (PXN) activity], phenylacetate [arylesterase (AE) activity], and diazoxon [diazoxonase (DZN) activity] with standard automated assays. We determined PON1 Q192R genotypes with PCR and Q192R phenotypes using the PXN/AE and PXN/DZN ratios. Interpolation equations were empirically derived to predict the percentage of total PON1 hydrolytic activity due to the Q isoenzyme (%Q) from the PXN/AE and PXN/DZN ratios; %R is 100 - %Q. We estimated Q and R isoenzyme activity levels in sera from 2095 veterans by multiplying AE activity, a measure of total PON1 hydrolytic activity, by %Q and %R. In all 2095 samples, the PXN/AE and PXN/DZN ratios predicted Q192R phenotypes with nearly identical accuracy (κ = 0.997). In the 925 QR heterozygotes, the 2 interpolation methods predicted Q and R isoenzyme activity levels with excellent agreement (intraclass correlation 0.94). After excluding a few genotype/phenotype-discordant samples, the percentage of total PON1 activity due to the Q isoenzyme ranged from 22% to 70%. These new interpolation methods allow accurate estimation of PON1 192 Q and R isoenzyme activity levels, increasing specificity and power for studying susceptibility to disease.

Relationships and Predictive Capabilities of Jump Assessments to Soccer-Specific Field Test Performance in Division I Collegiate Players.

PubMed

Lockie, Robert G; Stage, Alyssa A; Stokes, John J; Orjalo, Ashley J; Davis, DeShaun L; Giuliano, Dominic V; Moreno, Matthew R; Risso, Fabrice G; Lazar, Adrina; Birmingham-Babauta, Samantha A; Tomita, Tricia M

2016-12-03

Leg power is an important characteristic for soccer, and jump tests can measure this capacity. Limited research has analyzed relationships between jumping and soccer-specific field test performance in collegiate male players. Nineteen Division I players completed tests of: leg power (vertical jump (VJ), standing broad jump (SBJ), left- and right-leg triple hop (TH)); linear (30 m sprint; 0⁻5 m, 5⁻10 m, 0⁻10, 0⁻30 m intervals) and change-of-direction (505) speed; soccer-specific fitness (Yo-Yo Intermittent Recovery Test Level 2); and 7 × 30-m sprints to measure repeated-sprint ability (RSA; total time (TT), performance decrement (PD)). Pearson's correlations ( r ) determined jump and field test relationships; stepwise regression ascertained jump predictors of the tests ( p < 0.05). All jumps correlated with the 0⁻5, 0⁻10, and 0⁻30 m sprint intervals ( r = -0.65⁻-0.90). VJ, SBJ, and left- and right-leg TH correlated with RSA TT ( r = -0.51⁻-0.59). Right-leg TH predicted the 0⁻5 and 0⁻10 m intervals (R² = 0.55⁻0.81); the VJ predicted the 0⁻30 m interval and RSA TT (R² = 0.41⁻0.84). Between-leg TH asymmetry correlated with and predicted left-leg 505 and RSA PD ( r = -0.68⁻0.62; R² = 0.39⁻0.46). Improvements in jumping ability could contribute to faster speed and RSA performance in collegiate soccer players.

The longitudinal mental health impact of Fukushima nuclear disaster exposures and public criticism among power plant workers: the Fukushima NEWS Project study.

PubMed

Tanisho, Y; Shigemura, J; Kubota, K; Tanigawa, T; Bromet, E J; Takahashi, S; Matsuoka, Y; Nishi, D; Nagamine, M; Harada, N; Tanichi, M; Takahashi, Y; Shimizu, K; Nomura, S; Yoshino, A

2016-11-01

The Fukushima Daiichi and Daini Nuclear Power Plant workers experienced multiple stressors as both victims and onsite workers after the 2011 Great East Japan Earthquake and subsequent nuclear accidents. Previous studies found that disaster-related exposures, including discrimination/slurs, were associated with their mental health. Their long-term impact has yet to be investigated. A total of 968 plant workers (Daiichi, n = 571; Daini, n = 397) completed self-written questionnaires 2-3 months (time 1) and 14-15 months (time 2) after the disaster (response rate 55.0%). Sociodemographics, disaster-related experiences, and peritraumatic distress were assessed at time 1. At time 1 and time 2, general psychological distress (GPD) and post-traumatic stress response (PTSR) were measured, respectively, using the K6 scale and Impact of Event Scale Revised. We examined multivariate covariates of time 2 GPD and PTSR, adjusting for autocorrelations in the hierarchical multiple regression analyses. Higher GPD at time 2 was predicted by higher GPD at time 1 (β = 0.491, p < 0.001) and discrimination/slurs experiences at time 1 (β = 0.065, p = 0.025, adjusted R 2 = 0.24). Higher PTSR at time 2 was predicted with higher PTSR at time 1 (β = 0.548, p < 0.001), higher age (β = 0.085, p = 0.005), and discrimination/slurs experiences at time 1 (β = 0.079, p = 0.003, adjusted R 2 = 0.36). Higher GPD at time 2 was predicted by higher GPD and discrimination/slurs experience at time 1. Higher PTSR at time 2 was predicted by higher PTSR, higher age, and discrimination/slurs experience at time 1.

Hedonic Hunger Is Related to Increased Neural and Perceptual Responses to Cues of Palatable Food and Motivation to Consume: Evidence from 3 Independent Investigations.

PubMed

Burger, Kyle S; Sanders, Abigail J; Gilbert, Jennifer R

2016-09-01

The Power of Food Scale (PFS) seeks to identify individuals who experience high appetitive drive in response to food cues, which is a construct termed "hedonic hunger." The purpose of this study was to assess cross-sectional correlates and predictive power of PFS scores to probe the construct of hedonic hunger. Separate data from 3 studies (study 1, n = 44; study 2, n = 398; study 3, n = 100) were used to evaluate the construct of hedonic hunger. We examined the correlations between the PFS and neural responsivity during intake and anticipated intake of palatable foods, behavioral food reinforcement, perceptual hedonic ratings of food images, and change in body mass index (BMI) and binge eating over time. Hedonic hunger was strongly related to bilateral brain response in regions implicated in oral somatosensory processing during cue-elicited anticipation of food intake (study 1; right postcentral gyrus: r = 0.67, P < 0.001; left postcentral gyrus: r = 0.64, P < 0.001), and was correlated with behavioral food reinforcement (study 2; r = 0.31, P = 0.03) and perceptual hedonic ratings (study 3; r = 0.24, P = 0.02). Hedonic hunger was not associated with baseline BMI (studies 1-3: P = 0.14, 0.21, and 0.37, respectively) or change in BMI over the 2-y follow-up (studies 1 and 2: P = 0.14 and 0.37, respectively) but was significantly correlated with baseline binge eating in 2 samples (study 1: r = 0.58, P = 0.001; study 2: r = 0.31, P = 0.02; and study 3: P = 0.02). Hedonic hunger was not predictive of weight regulation. However, individuals who report high hedonic hunger are likely to show increased neural and perceptual responses to cues of palatable foods, increased motivation to consume such foods, and a greater likelihood of current binge eating. © 2016 American Society for Nutrition.

Hedonic Hunger Is Related to Increased Neural and Perceptual Responses to Cues of Palatable Food and Motivation to Consume: Evidence from 3 Independent Investigations12

PubMed Central

Burger, Kyle S; Sanders, Abigail J; Gilbert, Jennifer R

2016-01-01

Background: The Power of Food Scale (PFS) seeks to identify individuals who experience high appetitive drive in response to food cues, which is a construct termed “hedonic hunger.” Objective: The purpose of this study was to assess cross-sectional correlates and predictive power of PFS scores to probe the construct of hedonic hunger. Methods: Separate data from 3 studies (study 1, n = 44; study 2, n = 398; study 3, n = 100) were used to evaluate the construct of hedonic hunger. We examined the correlations between the PFS and neural responsivity during intake and anticipated intake of palatable foods, behavioral food reinforcement, perceptual hedonic ratings of food images, and change in body mass index (BMI) and binge eating over time. Results: Hedonic hunger was strongly related to bilateral brain response in regions implicated in oral somatosensory processing during cue-elicited anticipation of food intake (study 1; right postcentral gyrus: r = 0.67, P < 0.001; left postcentral gyrus: r = 0.64, P < 0.001), and was correlated with behavioral food reinforcement (study 2; r = 0.31, P = 0.03) and perceptual hedonic ratings (study 3; r = 0.24, P = 0.02). Hedonic hunger was not associated with baseline BMI (studies 1–3: P = 0.14, 0.21, and 0.37, respectively) or change in BMI over the 2-y follow-up (studies 1 and 2: P = 0.14 and 0.37, respectively) but was significantly correlated with baseline binge eating in 2 samples (study 1: r = 0.58, P = 0.001; study 2: r = 0.31, P = 0.02; and study 3: P = 0.02). Conclusions: Hedonic hunger was not predictive of weight regulation. However, individuals who report high hedonic hunger are likely to show increased neural and perceptual responses to cues of palatable foods, increased motivation to consume such foods, and a greater likelihood of current binge eating. PMID:27489006

3D-QSAR studies and molecular docking on [5-(4-amino-1 H-benzoimidazol-2-yl)-furan-2-yl]-phosphonic acid derivatives as fructose-1,6-biphophatase inhibitors

NASA Astrophysics Data System (ADS)

Lan, Ping; Xie, Mei-Qi; Yao, Yue-Mei; Chen, Wan-Na; Chen, Wei-Min

2010-12-01

Fructose-1,6-biphophatase has been regarded as a novel therapeutic target for the treatment of type 2 diabetes mellitus (T2DM). 3D-QSAR and docking studies were performed on a series of [5-(4-amino-1 H-benzoimidazol-2-yl)-furan-2-yl]-phosphonic acid derivatives as fructose-1,6-biphophatase inhibitors. The CoMFA and CoMSIA models using thirty-seven molecules in the training set gave r cv 2 values of 0.614 and 0.598, r 2 values of 0.950 and 0.928, respectively. The external validation indicated that our CoMFA and CoMSIA models possessed high predictive powers with r 0 2 values of 0.994 and 0.994, r m 2 values of 0.751 and 0.690, respectively. Molecular docking studies revealed that a phosphonic group was essential for binding to the receptor, and some key features were also identified. A set of forty new analogues were designed by utilizing the results revealed in the present study, and were predicted with significantly improved potencies in the developed models. The findings can be quite useful to aid the designing of new fructose-1,6-biphophatase inhibitors with improved biological response.

In silico prediction of toxicity of phenols to Tetrahymena pyriformis by using genetic algorithm and decision tree-based modeling approach.

PubMed

Abbasitabar, Fatemeh; Zare-Shahabadi, Vahid

2017-04-01

Risk assessment of chemicals is an important issue in environmental protection; however, there is a huge lack of experimental data for a large number of end-points. The experimental determination of toxicity of chemicals involves high costs and time-consuming process. In silico tools such as quantitative structure-toxicity relationship (QSTR) models, which are constructed on the basis of computational molecular descriptors, can predict missing data for toxic end-points for existing or even not yet synthesized chemicals. Phenol derivatives are known to be aquatic pollutants. With this background, we aimed to develop an accurate and reliable QSTR model for the prediction of toxicity of 206 phenols to Tetrahymena pyriformis. A multiple linear regression (MLR)-based QSTR was obtained using a powerful descriptor selection tool named Memorized_ACO algorithm. Statistical parameters of the model were 0.72 and 0.68 for R training 2 and R test 2 , respectively. To develop a high-quality QSTR model, classification and regression tree (CART) was employed. Two approaches were considered: (1) phenols were classified into different modes of action using CART and (2) the phenols in the training set were partitioned to several subsets by a tree in such a manner that in each subset, a high-quality MLR could be developed. For the first approach, the statistical parameters of the resultant QSTR model were improved to 0.83 and 0.75 for R training 2 and R test 2 , respectively. Genetic algorithm was employed in the second approach to obtain an optimal tree, and it was shown that the final QSTR model provided excellent prediction accuracy for the training and test sets (R training 2 and R test 2 were 0.91 and 0.93, respectively). The mean absolute error for the test set was computed as 0.1615. Copyright © 2016 Elsevier Ltd. All rights reserved.

Singular ferromagnetic susceptibility of the transverse-field Ising antiferromagnet on the triangular lattice

NASA Astrophysics Data System (ADS)

Biswas, Sounak; Damle, Kedar

2018-02-01

A transverse magnetic field Γ is known to induce antiferromagnetic three-sublattice order of the Ising spins σz in the triangular lattice Ising antiferromagnet at low enough temperature. This low-temperature order is known to melt on heating in a two-step manner, with a power-law ordered intermediate temperature phase characterized by power-law correlations at the three-sublattice wave vector Q : <σz(R ⃗) σz(0 ) > ˜cos(Q .R ⃗) /|R⃗| η (T ) with the temperature-dependent power-law exponent η (T )∈(1 /9 ,1 /4 ) . Here, we use a quantum cluster algorithm to study the ferromagnetic easy-axis susceptibility χu(L ) of an L ×L sample in this power-law ordered phase. Our numerical results are consistent with a recent prediction of a singular L dependence χu(L ) ˜L2 -9 η when η (T ) is in the range (1 /9 ,2 /9 ) . This finite-size result implies, via standard scaling arguments, that the ferromagnetic susceptibility χu(B ) to a uniform field B along the easy axis is singular at intermediate temperatures in the small B limit, χu(B ) ˜|B| -4/-18 η 4 -9 η for η (T )∈(1 /9 ,2 /9 ) , although there is no ferromagnetic long-range order in the low temperature state. Additionally we establish similar two-step melting behavior (via a study of the order parameter susceptibility χQ) in the case of the ferrimagnetic three-sublattice ordered phase which is stabilized by ferromagnetic next-neighbor couplings (J2) and confirm that the ferromagnetic susceptibility obeys the predicted singular form in the associated power-law ordered phase.

Prediction of Backbreak in Open Pit Blasting by Adaptive Neuro-Fuzzy Inference System / Prognozowanie Spękań Skał Przy Pracach Strzałowych W Kopalniach Odkrywkowych Przy Użyciu Metod Neuronowych I Wnioskowania Rozmytego (Anfis) Zastosowanych W Modelu Adaptywnym

NASA Astrophysics Data System (ADS)

Bazzazi, Abbas Aghajani; Esmaeili, Mohammad

2012-12-01

Adaptive neuro-fuzzy inference system (ANFIS) is powerful model in solving complex problems. Since ANFIS has the potential of solving nonlinear problem and can easily achieve the input-output mapping, it is perfect to be used for solving the predicting problem. Backbreak is one of the undesirable effects of blasting operations causing instability in mine walls, falling down the machinery, improper fragmentation and reduction in efficiency of drilling. In this paper, ANFIS was applied to predict backbreak in Sangan iron mine of Iran. The performance of the model was assessed through the root mean squared error (RMSE), the variance account for (VAF) and the correlation coefficient (R2) computed from the measured of backbreak and model-predicted values of the dependent variables. The RMSE, VAF, R2 indices were calculated 0.6, 0.94 and 0.95 for ANFIS model. As results, these indices revealed that the ANFIS model has very good prediction performance.

In-vivo corneal pulsation in relation to in-vivo intraocular pressure and corneal biomechanics assessed in-vitro. An animal pilot study.

PubMed

Rogala, Maja M; Danielewska, Monika E; Antończyk, Agnieszka; Kiełbowicz, Zdzisław; Rogowska, Marta E; Kozuń, Marta; Detyna, Jerzy; Iskander, D Robert

2017-09-01

The aim was to ascertain whether the characteristics of the corneal pulse (CP) measured in-vivo in a rabbit eye change after short-term artificial increase of intraocular pressure (IOP) and whether they correlate with corneal biomechanics assessed in-vitro. Eight New Zealand white rabbits were included in this study and were anesthetized. In-vivo experiments included simultaneous measurements of the CP signal, registered with a non-contact method, IOP, intra-arterial blood pressure, and blood pulse (BPL), at the baseline and short-term elevated IOP. Afterwards, thickness of post-mortem corneas was determined and then uniaxial tensile tests were conducted leading to estimates of their Young's modulus (E). At the baseline IOP, backward stepwise regression analyses were performed in which successively the ocular biomechanical, biometric and cardiovascular predictors were separately taken into account. Results of the analysis revealed that the 3rd CP harmonic can be statistically significantly predicted by E and central corneal thickness (Models: R 2  = 0.662, p < 0.005 and R 2  = 0.832, p < 0.001 for the signal amplitude and power, respectively). The 1st CP harmonic can be statistically significantly predicted by the amplitude and power of the 1st BPL harmonic (Models: R 2  = 0.534, p = 0.015 and R 2  = 0.509, p < 0.018, respectively). For elevated IOP, non-parametric analysis indicated significant differences for the power of the 1st CP harmonic (Kruskal-Wallis test; p = 0.031) and for the mean, systolic and diastolic blood pressures (p = 0.025, p = 0.019, p = 0.033, respectively). In conclusion, for the first time, the association between parameters of the CP signal in-vivo and corneal biomechanics in-vitro was confirmed. In particular, spectral analysis revealed that higher amplitude and power of the 3rd CP harmonic indicates higher corneal stiffness, while the 1st CP harmonic correlates positively with the corresponding harmonic of the BPL signal. Copyright © 2017 Elsevier Ltd. All rights reserved.

Prediction of blood-brain partitioning: a model based on molecular electronegativity distance vector descriptors.

PubMed

Zhang, Yong-Hong; Xia, Zhi-Ning; Qin, Li-Tang; Liu, Shu-Shen

2010-09-01

The objective of this paper is to build a reliable model based on the molecular electronegativity distance vector (MEDV) descriptors for predicting the blood-brain barrier (BBB) permeability and to reveal the effects of the molecular structural segments on the BBB permeability. Using 70 structurally diverse compounds, the partial least squares regression (PLSR) models between the BBB permeability and the MEDV descriptors were developed and validated by the variable selection and modeling based on prediction (VSMP) technique. The estimation ability, stability, and predictive power of a model are evaluated by the estimated correlation coefficient (r), leave-one-out (LOO) cross-validation correlation coefficient (q), and predictive correlation coefficient (R(p)). It has been found that PLSR model has good quality, r=0.9202, q=0.7956, and R(p)=0.6649 for M1 model based on the training set of 57 samples. To search the most important structural factors affecting the BBB permeability of compounds, we performed the values of the variable importance in projection (VIP) analysis for MEDV descriptors. It was found that some structural fragments in compounds, such as -CH(3), -CH(2)-, =CH-, =C, triple bond C-, -CH<, =C<, =N-, -NH-, =O, and -OH, are the most important factors affecting the BBB permeability. (c) 2010. Published by Elsevier Inc.

Temporal stability of the theory of planned behavior: a prospective analysis of sugar consumption among Ugandan adolescents.

PubMed

Astrøm, Anne Nordrehaug; Okullo, I

2004-12-01

This study addressed three questions: What is the power of the Theory of Planned Behavior (TPB) in predicting adolescents' intended and self-perceived consumption of non-milk extrinsic sugars using a non-intervention prospective approach? To what extent do the TPB constructs change across time following adolescents' mere exposure to an oral health survey? Do changes in self-perceived sugar consumption at follow-up associate with changes in behavioral intention as predicted by the TPB? A survey was conducted in Kampala (urban) and Lira (rural) and 1146 secondary school students completed questionnaires assessing the TPB at school (Time 1). A random sub-sample of 415 students was selected from the original survey of which 372 students were examined clinically. After 3 months (Time 2), the questionnaire was administered a second time in the sub-sample. All analyses are based on the number of students who participated on both survey occasions, n = 372. Attitudes and perceived behavioral control predicted intended sugar consumption at Time 1 and Time 2, accounting for 58% (DeltaR(2) = 0.58) and 19% (DeltaR(2) = 0.19) of the variance, respectively. Time 1 intention provided significant prediction of Time 2 self-perceived sugar consumption with DeltaR(2) = 0.5. Adolescents with high-caries experience more than their counterparts with low, changed towards weaker intentions and less frequent sugar consumption across the survey period. Mean sugar consumption scores changed from 2.6 to 2.7 (ns), 3.1 to 2.6 (P < 0.001) and 2.3 to 3.2 (P < 0.001) among adolescents who, respectively, remained stable, increased and decreased their intentions across time. This study supports the validity of the TPB in predicting intended and self-perceived sugar consumption prospectively.

Assessing temporally and spatially resolved PM 2.5 exposures for epidemiological studies using satellite aerosol optical depth measurements

NASA Astrophysics Data System (ADS)

Kloog, Itai; Koutrakis, Petros; Coull, Brent A.; Lee, Hyung Joo; Schwartz, Joel

2011-11-01

Land use regression (LUR) models provide good estimates of spatially resolved long-term exposures, but are poor at capturing short term exposures. Satellite-derived Aerosol Optical Depth (AOD) measurements have the potential to provide spatio-temporally resolved predictions of both long and short term exposures, but previous studies have generally showed relatively low predictive power. Our objective was to extend our previous work on day-specific calibrations of AOD data using ground PM 2.5 measurements by incorporating commonly used LUR variables and meteorological variables, thus benefiting from both the spatial resolution from the LUR models and the spatio-temporal resolution from the satellite models. Later we use spatial smoothing to predict PM 2.5 concentrations for day/locations with missing AOD measures. We used mixed models with random slopes for day to calibrate AOD data for 2000-2008 across New-England with monitored PM 2.5 measurements. We then used a generalized additive mixed model with spatial smoothing to estimate PM 2.5 in location-day pairs with missing AOD, using regional measured PM 2.5, AOD values in neighboring cells, and land use. Finally, local (100 m) land use terms were used to model the difference between grid cell prediction and monitored value to capture very local traffic particles. Out-of-sample ten-fold cross-validation was used to quantify the accuracy of our predictions. For days with available AOD data we found high out-of-sample R2 (mean out-of-sample R2 = 0.830, year to year variation 0.725-0.904). For days without AOD values, our model performance was also excellent (mean out-of-sample R2 = 0.810, year to year variation 0.692-0.887). Importantly, these R2 are for daily, rather than monthly or yearly, values. Our model allows one to assess short term and long-term human exposures in order to investigate both the acute and chronic effects of ambient particles, respectively.

Prediction of brain tissue temperature using near-infrared spectroscopy

PubMed Central

Holper, Lisa; Mitra, Subhabrata; Bale, Gemma; Robertson, Nicola; Tachtsidis, Ilias

2017-01-01

Abstract. Broadband near-infrared spectroscopy (NIRS) can provide an endogenous indicator of tissue temperature based on the temperature dependence of the water absorption spectrum. We describe a first evaluation of the calibration and prediction of brain tissue temperature obtained during hypothermia in newborn piglets (animal dataset) and rewarming in newborn infants (human dataset) based on measured body (rectal) temperature. The calibration using partial least squares regression proved to be a reliable method to predict brain tissue temperature with respect to core body temperature in the wavelength interval of 720 to 880 nm with a strong mean predictive power of R2=0.713±0.157 (animal dataset) and R2=0.798±0.087 (human dataset). In addition, we applied regression receiver operating characteristic curves for the first time to evaluate the temperature prediction, which provided an overall mean error bias between NIRS predicted brain temperature and body temperature of 0.436±0.283°C (animal dataset) and 0.162±0.149°C (human dataset). We discuss main methodological aspects, particularly the well-known aspect of over- versus underestimation between brain and body temperature, which is relevant for potential clinical applications. PMID:28630878

Prediction of retail beef yield and fat content from live animal and carcass measurements in Nellore cattle.

PubMed

Sakamoto, L S; Mercadante, M E Z; Bonilha, S F M; Branco, R H; Bonilha, E F M; Magnani, E

2014-11-01

Data from 156 Nellore males were used to develop equations for the prediction of retail beef yield and carcass fat content, expressed as kilograms and as a percentage, from live animal and carcass measurements. Longissimus muscle area and backfat and rump fat thickness were measured by ultrasound up to 5 d before slaughter and fasted live weight was determined 1 d before slaughter. The same traits were obtained after slaughter. The carcass edible portion (CEP in kg and CEP% in percentage; n = 116) was calculated by the sum of the edible portions of primal cuts: hindquarter, forequarter, and spare ribs. Trimmable fat from the carcass boning process, with the standardization of about 3 mm of fat on retail beef, was considered to be representative of carcass fat content. Most of the variation in CEP was explained by fasted live weight or carcass weight (R(2) of 0.92 and 0.96); the same occurred for CEP% (R(2) of 0.15 and 0.13), and for CEP, the inclusion of LM area and fat thickness reduced the equation bias (lower value of Mallow's Cp statistics). For trimmable fat, most variation could be explained by weight or rump fat thickness. In general, the equations developed from live animal measurements showed a predictive power similar to the equations using carcass measurements. In all cases, the traits expressed as kilograms were better predicted (R(2) of 0.39 to 0.96) than traits expressed as a percentage (R(2) of 0.08 to 0.42).

Predictability of depression severity based on posterior alpha oscillations.

PubMed

Jiang, H; Popov, T; Jylänki, P; Bi, K; Yao, Z; Lu, Q; Jensen, O; van Gerven, M A J

2016-04-01

We aimed to integrate neural data and an advanced machine learning technique to predict individual major depressive disorder (MDD) patient severity. MEG data was acquired from 22 MDD patients and 22 healthy controls (HC) resting awake with eyes closed. Individual power spectra were calculated by a Fourier transform. Sources were reconstructed via beamforming technique. Bayesian linear regression was applied to predict depression severity based on the spatial distribution of oscillatory power. In MDD patients, decreased theta (4-8 Hz) and alpha (8-14 Hz) power was observed in fronto-central and posterior areas respectively, whereas increased beta (14-30 Hz) power was observed in fronto-central regions. In particular, posterior alpha power was negatively related to depression severity. The Bayesian linear regression model showed significant depression severity prediction performance based on the spatial distribution of both alpha (r=0.68, p=0.0005) and beta power (r=0.56, p=0.007) respectively. Our findings point to a specific alteration of oscillatory brain activity in MDD patients during rest as characterized from MEG data in terms of spectral and spatial distribution. The proposed model yielded a quantitative and objective estimation for the depression severity, which in turn has a potential for diagnosis and monitoring of the recovery process. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Circulating microRNAs in follicular fluid, powerful tools to explore in vitro fertilization process.

PubMed

Scalici, E; Traver, S; Mullet, T; Molinari, N; Ferrières, A; Brunet, C; Belloc, S; Hamamah, S

2016-04-22

Circulating or "extracellular" microRNAs (miRNAs) detected in biological fluids, could be used as potential diagnostic and prognostic biomarkers of several disease, such as cancer, gynecological and pregnancy disorders. However, their contributions in female infertility and in vitro fertilization (IVF) remain unknown. This study investigated the expression profiles of five circulating miRNAs (let-7b, miR-29a, miR-30a, miR-140 and miR-320a) in human follicular fluid from 91 women with normal ovarian reserve and 30 with polycystic ovary syndrome (PCOS) and their ability to predict IVF outcomes. The combination of FF miR-30a, miR-140 and let-7b expression levels discriminated between PCOS and normal ovarian reserve with a specificity of 83.8% and a sensitivity of 70% (area under the ROC curve, AUC = 0.83 [0.73-0.92]; p < 0.0001). FF samples related to low number of mature oocytes (≤2) contained significant less miR-320a levels than those related to a number of mature oocytes >2 (p = 0.04). Moreover, FF let-7b predicted the development of expanded blastocysts with 70% sensitivity and 64.3% specificity (AUC = 0.67 [0.54-0.79]; p = 0.02) and FF miR-29a potential to predict clinical pregnancy outcome reached 0.68 [0.55-0.79] with a sensitivity of 83.3% and a specificity of 53.5% (p = 0.01). Therefore, these miRNAs could provide new helpful biomarkers to facilitate personalized medical care during IVF.

Relationships of physical performance tests to military-relevant tasks in women.

PubMed

Szivak, Tunde K; Kraemer, William J; Nindl, Bradley C; Gotshalk, Lincoln A; Volek, Jeff S; Gomez, Ana L; Dunn-Lewis, Courtenay; Looney, David P; Comstock, Brett A; Hooper, David R; Flanagan, Shawn D; Maresh, Carl M

2014-01-01

This investigation sought to determine the most predictive measures of performance on a repetitive box lifting task (RBLT) and load bearing task (LBT) among 123 women (aged ±4 years, height 165±7 cm, body mass 64±10 kg). To determine the relationship of various predictors to performance on the RBLT and LBT, multiple regression analysis was conducted on body mass, height, leg cross-sectional area, upper and lower body muscular strength, lower body explosive power, upper and lower body local muscular endurance, and aerobic capacity. The mean±SD (range) number of repetitions for the RBLT was 86±23 (20-159). The mean±SD (range) time to complete the LBT was 2,054±340 seconds (1,307-3,447). The following equations were generated: RBLT (number of repetitions)=57.4+0.2(peak jump power)+0.4(number of pushups in 2 minutes)+0.15(number of repetitions during the squat endurance test)+1.39(one repetition maximal strength boxlift (kg))-0.04(2-mile run time (2MR) in seconds), R=0.81; standard error of the estimate (SEE)=14; LBT (in seconds)=1,831-4.28(number of repetitions during the squat endurance test)+0.95(2MR in seconds)-13.4(body mass), R=0.73; SEE=232. We found that the 2MR and squat endurance test were significant predictive factors for performance on both load carriage tasks. These data also imply that women's performance in combat-related tasks can be improved with training that targets muscular strength, power, and local muscular endurance in addition to aerobic capacity.

Body fat distribution in the Finnish population: environmental determinants and predictive power for cardiovascular risk factor levels.

PubMed Central

Marti, B; Tuomilehto, J; Salomaa, V; Kartovaara, L; Korhonen, H J; Pietinen, P

1991-01-01

STUDY OBJECTIVE--The aim was to examine (1) whether health habits are associated with body fat distribution, as measured by the waist/hip girth ratio, and (2) to what extent environmental factors, including anthropometric characteristics, explain the variability in levels of cardiovascular risk factors. DESIGN--The study was a population based cross sectional survey, conducted in the spring of 1987 as a part of an international research project on cardiovascular epidemiology. SETTING--The survey was conducted in three geographical areas of eastern and south western Finland. SUBJECTS--2526 men and 2756 women aged 25-64 years took part in the study, corresponding to a survey participation rate of 82%. MEASUREMENTS AND MAIN RESULTS--In men, waist/hip ratio showed stronger associations with exercise (Pearson's r = -0.24), resting heart rate (r = 0.10), alcohol consumption (r = 0.07), smoking (r = 0.05), and education (r = -0.23) than did body mass index. Jointly, exercise, resting heart rate, alcohol consumption, education, and age explained 18% of variance in male waist/hip ratio, but only 9% of variance in male body mass index. In women, environmental factors were more predictive for body mass index than for waist/hip ratio, with age and education being the strongest determinants. Waist/hip ratio and body mass index were approximately equally strong predictors of cardiovascular risk factor levels. The additional predictive power of waist/hip ratio over and above body mass index was tested in a hierarchical, stepwise regression. In this conservative type of analysis the increase in explained variance uniquely attributable to waist/hip ratio was 2-3% for female and 1-2% for male lipoprotein levels, and less than 0.5% for female and 0-2% for male blood pressure values. CONCLUSIONS--The distribution of abdominal obesity in Finland is significantly influenced by health habits and sociodemographic factors in both men and women. This in turn is obviously one reason for the relatively small "independent" effect of body fat distribution on cardiovascular risk factor levels. PMID:2072072

On the efficiency of jet production in FR II radio galaxies and quasars

NASA Astrophysics Data System (ADS)

Rusinek, Katarzyna; Sikora, Marek; Kozieł-Wierzbowska, Dorota; Godfrey, Leith

2017-04-01

Jet powers in many radio galaxies with extended radio structures appear to exceed their associated accretion luminosities. In systems with very low accretion rates, this is likely due to the very low accretion luminosities resulting from radiatively inefficient accretion flows. In systems with high accretion rates, the accretion flows are expected to be radiatively efficient, and the production of such powerful jets may require an accretion scenario, which involves magnetically arrested discs (MADs). However, numerical simulations of the MAD scenario indicate that jet production efficiency is large only for geometrically thick accretion flows and scales roughly with (H/R)2, where H is the disc height and R is the distance from the black hole. Using samples of FR II radio galaxies and quasars accreting at moderate accretion rates, we show that their jets are much more powerful than predicted by the MAD scenario. We discuss possible origins of this discrepancy, suggesting that it can be related to approximations adopted in magnetohydrodynamic simulations to treat optically thick accretion flow within the MAD zone, or may indicate that accretion discs are geometrically thicker than the standard theory predicts.

Predictive power of food web models based on body size decreases with trophic complexity.

PubMed

Jonsson, Tomas; Kaartinen, Riikka; Jonsson, Mattias; Bommarco, Riccardo

2018-05-01

Food web models parameterised using body size show promise to predict trophic interaction strengths (IS) and abundance dynamics. However, this remains to be rigorously tested in food webs beyond simple trophic modules, where indirect and intraguild interactions could be important and driven by traits other than body size. We systematically varied predator body size, guild composition and richness in microcosm insect webs and compared experimental outcomes with predictions of IS from models with allometrically scaled parameters. Body size was a strong predictor of IS in simple modules (r 2  = 0.92), but with increasing complexity the predictive power decreased, with model IS being consistently overestimated. We quantify the strength of observed trophic interaction modifications, partition this into density-mediated vs. behaviour-mediated indirect effects and show that model shortcomings in predicting IS is related to the size of behaviour-mediated effects. Our findings encourage development of dynamical food web models explicitly including and exploring indirect mechanisms. © 2018 John Wiley & Sons Ltd/CNRS.

Weather conditions and visits to the medical wing of emergency rooms in a metropolitan area during the warm season in Israel: a predictive model

NASA Astrophysics Data System (ADS)

Novikov, Ilya; Kalter-Leibovici, Ofra; Chetrit, Angela; Stav, Nir; Epstein, Yoram

2012-01-01

Global climate changes affect health and present new challenges to healthcare systems. The aim of the present study was to analyze the pattern of visits to the medical wing of emergency rooms (ERs) in public hospitals during warm seasons, and to develop a predictive model that will forecast the number of visits to ERs 2 days ahead. Data on daily visits to the ERs of the four largest medical centers in the Tel-Aviv metropolitan area during the warm months of the year (April-October, 2001-2004), the corresponding daily meteorological data, daily electrical power consumption (a surrogate marker for air-conditioning), air-pollution parameters, and calendar information were obtained and used in the analyses. The predictive model employed a time series analysis with transitional Poisson regression. The concise multivariable model was highly accurate ( r 2 = 0.819). The contribution of mean daily temperature was small but significant: an increase of 1°C in ambient temperature was associated with a 1.47% increase in the number of ER visits ( P < 0.001). An increase in electrical power consumption significantly attenuated the effect of weather conditions on ER visits by 4% per 1,000 MWh ( P < 0.001). Higher daily mean SO2 concentrations were associated with a greater number of ER visits (1% per 1 ppb increment; P = 0.017). Calendar data were the main predictors of ER visits ( r 2 = 0.794). The predictive model was highly accurate in forecasting the number of visits to ERs 2 days ahead. The marginal effect of temperature on the number of ER visits can be attributed to behavioral adaptations, including the use of air-conditioning.

Risk Adjustment and Primary Health Care in Chile

PubMed Central

Vargas, Veronica; Wasem, Juergen

2006-01-01

Aim To offer a capitation formula with greater capacity for guiding resource spending on population with poorer health and lower socioeconomic status in the context of financing and equity in primary health care. Methods We collected two years of data on a sample of 10 000 individuals from a region in Chile, Valdivia and Temuco and evaluated three models to estimate utilization and expenditures per capita. The first model included age and sex; the second one included age, sex, and the presence of two key diagnoses; and the third model included age, sex, and the presence of seven key diagnoses. Regression results were evaluated by R2 and predictive ratios to select the best specifications. Results Per-capita expenditures by age and sex confirmed international trends, where children under five, women, and the elderly were the main users of primary health care services. Women sought health advice twice as much as men. Clear differences by socioeconomic status were observed for the indigent population aged ≥65 years who under-utilized primary health care services. From the three models, major improvement in the predictive power occurred from the demographic (adjusted R2, 9%) to the demographic plus two diagnoses model (adjusted R2, 27%). Improvements were modest when five other diagnoses were added (adjusted R2, 28%). Conclusion The current formula that uses municipality’s financial power and geographic location of health centers to adjust capitation payments provides little incentive to appropriate care for the indigent and people with chronic conditions. A capitation payment that adjusts for age, sex, and the presence of diabetes and hypertension will better guide resource allocation to those with poorer health and lower socioeconomic status. PMID:16758525

Application of the hybrid ANFIS models for long term wind power density prediction with extrapolation capability.

PubMed

Hossain, Monowar; Mekhilef, Saad; Afifi, Firdaus; Halabi, Laith M; Olatomiwa, Lanre; Seyedmahmoudian, Mehdi; Horan, Ben; Stojcevski, Alex

2018-01-01

In this paper, the suitability and performance of ANFIS (adaptive neuro-fuzzy inference system), ANFIS-PSO (particle swarm optimization), ANFIS-GA (genetic algorithm) and ANFIS-DE (differential evolution) has been investigated for the prediction of monthly and weekly wind power density (WPD) of four different locations named Mersing, Kuala Terengganu, Pulau Langkawi and Bayan Lepas all in Malaysia. For this aim, standalone ANFIS, ANFIS-PSO, ANFIS-GA and ANFIS-DE prediction algorithm are developed in MATLAB platform. The performance of the proposed hybrid ANFIS models is determined by computing different statistical parameters such as mean absolute bias error (MABE), mean absolute percentage error (MAPE), root mean square error (RMSE) and coefficient of determination (R2). The results obtained from ANFIS-PSO and ANFIS-GA enjoy higher performance and accuracy than other models, and they can be suggested for practical application to predict monthly and weekly mean wind power density. Besides, the capability of the proposed hybrid ANFIS models is examined to predict the wind data for the locations where measured wind data are not available, and the results are compared with the measured wind data from nearby stations.

Application of the hybrid ANFIS models for long term wind power density prediction with extrapolation capability

PubMed Central

Mekhilef, Saad; Afifi, Firdaus; Halabi, Laith M.; Olatomiwa, Lanre; Seyedmahmoudian, Mehdi; Stojcevski, Alex

2018-01-01

In this paper, the suitability and performance of ANFIS (adaptive neuro-fuzzy inference system), ANFIS-PSO (particle swarm optimization), ANFIS-GA (genetic algorithm) and ANFIS-DE (differential evolution) has been investigated for the prediction of monthly and weekly wind power density (WPD) of four different locations named Mersing, Kuala Terengganu, Pulau Langkawi and Bayan Lepas all in Malaysia. For this aim, standalone ANFIS, ANFIS-PSO, ANFIS-GA and ANFIS-DE prediction algorithm are developed in MATLAB platform. The performance of the proposed hybrid ANFIS models is determined by computing different statistical parameters such as mean absolute bias error (MABE), mean absolute percentage error (MAPE), root mean square error (RMSE) and coefficient of determination (R2). The results obtained from ANFIS-PSO and ANFIS-GA enjoy higher performance and accuracy than other models, and they can be suggested for practical application to predict monthly and weekly mean wind power density. Besides, the capability of the proposed hybrid ANFIS models is examined to predict the wind data for the locations where measured wind data are not available, and the results are compared with the measured wind data from nearby stations. PMID:29702645

Blunted cyclic variation of heart rate predicts mortality risk in post-myocardial infarction, end-stage renal disease, and chronic heart failure patients

PubMed Central

Hayano, Junichiro; Yasuma, Fumihiko; Watanabe, Eiichi; Carney, Robert M.; Stein, Phyllis K.; Blumenthal, James A.; Arsenos, Petros; Gatzoulis, Konstantinos A.; Takahashi, Hiroshi; Ishii, Hideki; Kiyono, Ken; Yamamoto, Yoshiharu; Yoshida, Yutaka; Yuda, Emi; Kodama, Itsuo

2017-01-01

Abstract Aims Cyclic variation of heart rate (CVHR) associated with sleep-disordered breathing is thought to reflect cardiac autonomic responses to apnoeic/hypoxic stress. We examined whether blunted CVHR observed in ambulatory ECG could predict the mortality risk. Methods and results CVHR in night-time Holter ECG was detected by an automated algorithm, and the prognostic relationships of the frequency (FCV) and amplitude (ACV) of CVHR were examined in 717 patients after myocardial infarction (post-MI 1, 6% mortality, median follow-up 25 months). The predictive power was prospectively validated in three independent cohorts: a second group of 220 post-MI patients (post-MI 2, 25.5% mortality, follow-up 45 months); 299 patients with end-stage renal disease on chronic haemodialysis (ESRD, 28.1% mortality, follow-up 85 months); and 100 patients with chronic heart failure (CHF, 35% mortality, follow-up 38 months). Although CVHR was observed in ≥96% of the patients in all cohorts, FCV did not predict mortality in any cohort. In contrast, decreased ACV was a powerful predictor of mortality in the post-MI 1 cohort (hazard ratio [95% CI] per 1 ln [ms] decrement, 2.9 [2.2–3.7], P < 0.001). This prognostic relationship was validated in the post-MI 2 (1.8 [1.4–2.2], P < 0.001), ESRD (1.5 [1.3–1.8], P < 0.001), and CHF (1.4 [1.1–1.8], P = 0.02) cohorts. The prognostic value of ACV was independent of age, gender, diabetes, β-blocker therapy, left ventricular ejection fraction, sleep-time mean R-R interval, and FCV. Conclusion Blunted CVHR detected by decreased ACV in a night-time Holter ECG predicts increased mortality risk in post-MI, ESRD, and CHF patients. PMID:27789562

Blunted cyclic variation of heart rate predicts mortality risk in post-myocardial infarction, end-stage renal disease, and chronic heart failure patients.

PubMed

Hayano, Junichiro; Yasuma, Fumihiko; Watanabe, Eiichi; Carney, Robert M; Stein, Phyllis K; Blumenthal, James A; Arsenos, Petros; Gatzoulis, Konstantinos A; Takahashi, Hiroshi; Ishii, Hideki; Kiyono, Ken; Yamamoto, Yoshiharu; Yoshida, Yutaka; Yuda, Emi; Kodama, Itsuo

2017-08-01

Cyclic variation of heart rate (CVHR) associated with sleep-disordered breathing is thought to reflect cardiac autonomic responses to apnoeic/hypoxic stress. We examined whether blunted CVHR observed in ambulatory ECG could predict the mortality risk. CVHR in night-time Holter ECG was detected by an automated algorithm, and the prognostic relationships of the frequency (FCV) and amplitude (ACV) of CVHR were examined in 717 patients after myocardial infarction (post-MI 1, 6% mortality, median follow-up 25 months). The predictive power was prospectively validated in three independent cohorts: a second group of 220 post-MI patients (post-MI 2, 25.5% mortality, follow-up 45 months); 299 patients with end-stage renal disease on chronic haemodialysis (ESRD, 28.1% mortality, follow-up 85 months); and 100 patients with chronic heart failure (CHF, 35% mortality, follow-up 38 months). Although CVHR was observed in ≥96% of the patients in all cohorts, FCV did not predict mortality in any cohort. In contrast, decreased ACV was a powerful predictor of mortality in the post-MI 1 cohort (hazard ratio [95% CI] per 1 ln [ms] decrement, 2.9 [2.2-3.7], P < 0.001). This prognostic relationship was validated in the post-MI 2 (1.8 [1.4-2.2], P < 0.001), ESRD (1.5 [1.3-1.8], P < 0.001), and CHF (1.4 [1.1-1.8], P = 0.02) cohorts. The prognostic value of ACV was independent of age, gender, diabetes, β-blocker therapy, left ventricular ejection fraction, sleep-time mean R-R interval, and FCV. Blunted CVHR detected by decreased ACV in a night-time Holter ECG predicts increased mortality risk in post-MI, ESRD, and CHF patients. © The Author 2016. Published by Oxford University Press on behalf of the European Society of Cardiology.

A comparison of the Full Outline of UnResponsiveness (FOUR) score and Glasgow Coma Score (GCS) in predictive modelling in traumatic brain injury.

PubMed

Kasprowicz, Magdalena; Burzynska, Malgorzata; Melcer, Tomasz; Kübler, Andrzej

2016-01-01

To compare the performance of multivariate predictive models incorporating either the Full Outline of UnResponsiveness (FOUR) score or Glasgow Coma Score (GCS) in order to test whether substituting GCS with the FOUR score in predictive models for outcome in patients after TBI is beneficial. A total of 162 TBI patients were prospectively enrolled in the study. Stepwise logistic regression analysis was conducted to compare the prediction of (1) in-ICU mortality and (2) unfavourable outcome at 3 months post-injury using as predictors either the FOUR score or GCS along with other factors that may affect patient outcome. The areas under the ROC curves (AUCs) were used to compare the discriminant ability and predictive power of the models. The internal validation was performed with bootstrap technique and expressed as accuracy rate (AcR). The FOUR score, age, the CT Rotterdam score, systolic ABP and being placed on ventilator within day one (model 1: AUC: 0.906 ± 0.024; AcR: 80.3 ± 4.8%) performed equally well in predicting in-ICU mortality as the combination of GCS with the same set of predictors plus pupil reactivity (model 2: AUC: 0.913 ± 0.022; AcR: 81.1 ± 4.8%). The CT Rotterdam score, age and either the FOUR score (model 3) or GCS (model 4) equally well predicted unfavourable outcome at 3 months post-injury (AUC: 0.852 ± 0.037 vs. 0.866 ± 0.034; AcR: 72.3 ± 6.6% vs. 71.9%±6.6%, respectively). Adding the FOUR score or GCS at discharge from ICU to predictive models for unfavourable outcome increased significantly their performances (AUC: 0.895 ± 0.029, p = 0.05; AcR: 76.1 ± 6.5%; p < 0.004 when compared with model 3; and AUC: 0.918 ± 0.025, p < 0.05; AcR: 79.6 ± 7.2%, p < 0.009 when compared with model 4), but there was no benefit from substituting GCS with the FOUR score. Results showed that FOUR score and GCS perform equally well in multivariate predictive modelling in TBI.

Theoretical insights on the antioxidant activity of edaravone free radical scavengers derivatives

NASA Astrophysics Data System (ADS)

Cerón-Carrasco, José P.; Roy, Hélène M.; Cerezo, Javier; Jacquemin, Denis; Laurent, Adèle D.

2014-04-01

The prediction of antioxidant properties is not straightforward due to the complexity of the in vivo systems. Here, we use theoretical descriptors, including the potential of ionization, the electrodonating power and the spin density distribution, to characterize the antioxidant capacity of edaravone (EDV) derivatives. Our computations reveal the relationship between these parameters and their potential bioactivity as free radical scavengers. We conclude that more efficient antioxidants could be synthesized by tuning the R1 and R2 positions of the EDV structure, rather than modifying the R3 group. Such modifications might improve the antioxidant activity in neutral and deprotonated forms.

Velocity- and power-load relationships of the bench pull vs. bench press exercises.

PubMed

Sánchez-Medina, L; González-Badillo, J J; Pérez, C E; Pallarés, J G

2014-03-01

This study compared the velocity- and power-load relationships of the antagonistic upper-body exercises of prone bench pull (PBP) and bench press (BP). 75 resistance-trained athletes performed a progressive loading test in each exercise up to the one-repetition maximum (1RM) in random order. Velocity and power output across the 30-100% 1RM were significantly higher for PBP, whereas 1RM strength was greater for BP. A very close relationship was observed between relative load and mean propulsive velocity for both BP (R2=0.97) and PBP (R2=0.94) which enables us to estimate %1RM from velocity using the obtained prediction equations. Important differences in the load that maximizes power output (Pmax) and the power profiles of both exercises were found according to the outcome variable used: mean (MP), peak (PP) or mean propulsive power (MPP). When MP was considered, the Pmax load was higher (56% BP, 70% PBP) than when PP (37% BP, 41% PBP) or MPP (37% BP, 46% PBP) were used. For each variable there was a broad range of loads at which power output was not significantly different. The differing velocity- and power-load relationships between PBP and BP seem attributable to the distinct muscle architecture and moment arm levers involved in these exercises. © Georg Thieme Verlag KG Stuttgart · New York.

Inflation in the mixed Higgs-R2 model

NASA Astrophysics Data System (ADS)

He, Minxi; Starobinsky, Alexei A.; Yokoyama, Jun'ichi

2018-05-01

We analyze a two-field inflationary model consisting of the Ricci scalar squared (R2) term and the standard Higgs field non-minimally coupled to gravity in addition to the Einstein R term. Detailed analysis of the power spectrum of this model with mass hierarchy is presented, and we find that one can describe this model as an effective single-field model in the slow-roll regime with a modified sound speed. The scalar spectral index predicted by this model coincides with those given by the R2 inflation and the Higgs inflation implying that there is a close relation between this model and the R2 inflation already in the original (Jordan) frame. For a typical value of the self-coupling of the standard Higgs field at the high energy scale of inflation, the role of the Higgs field in parameter space involved is to modify the scalaron mass, so that the original mass parameter in the R2 inflation can deviate from its standard value when non-minimal coupling between the Ricci scalar and the Higgs field is large enough.

Diagnostic, pharmacy-based, and self-reported health measures in risk equalization models.

PubMed

Stam, Pieter J A; van Vliet, René C J A; van de Ven, Wynand P M M

2010-05-01

Current research on the added value of self-reported health measures for risk equalization modeling does not include all types of self-reported health measures; and/or is compared with a limited set of medically diagnosed or pharmacy-based diseases; and/or is limited to specific populations of high-risk individuals. The objective of our study is to determine the predictive power of all types of self-reported health measures for prospective modeling of health care expenditures in a general population of adult Dutch sickness fund enrollees, given that pharmacy and diagnostic data from administrative records are already included in the risk equalization formula. We used 4 models of 2002 total, inpatient and outpatient expenditures to evaluate the separate and combined predictive ability of 2 kinds of data: (1) Pharmacy-based (PCGs) and Diagnosis-based (DCGs) Cost Groups and (2) summarized self-reported health information. Model performance is measured at the total population level using R2 and mean absolute prediction error; also, by examining mean discrepancies between model-predicted and actual expenditures (ie, expected over- or undercompensation) for members of potentially "mispriced" subgroups. These subgroups are identified by self-reports from prior-year health surveys and utilization and expenditure data from 5 preceding years. Subjects were 18,617 respondents to a health survey, held among a stratified sample of adult members of the largest Dutch sickness fund in 2002, with an overrepresentation of people in poor health. The data were extracted from a claims database and a health survey. The claims-based data are the outcomes of total, inpatient, and outpatient annualized expenditures in 2002; age, gender, PCGs, DCGs in 2001; and health care expenditures and hospitalizations during the years 1997 to 2001. The SF-36, Organization for Economic Cooperation and Development items, and long-term diseases and conditions were collected by a special purpose health survey conducted in the last quarter of 2001. Out-of-sample R2 equals 17.2%, 2.6%, and 32.4% for the models of total, inpatient and outpatient expenditures including PCGs, DCGs, and self-reported health measures. Self-reported health measures contribute less to predictive power than PCGs and DCGs. PCGs and DCGs also predict better than self-reported health measures for people with top 25% total expenditures or hospitalizations in each year during a 5-year period. On the other hand, self-reported health measures are better predictors than PCGs and DCGs for people without any top 25% expenditures during the 5-year period, for switchers, and for most subgroups of relatively unhealthy people defined by self-reported health measures. Among the set of self-reported health measures, the SF-36 adds most to predictive power in terms of R2, mean absolute prediction error, and for almost all studied subgroups. It is concluded that the self-reported health measures make an independent contribution to forecasting health care expenditures, even if the prediction model already includes diagnostic and pharmacy-based information currently used in Dutch risk equalization models.

Predictions of high QDT in ITER H-mode plasmas

NASA Astrophysics Data System (ADS)

Budny, Robert

2009-05-01

Time-dependent integrated predictions of performance metrics such as the fusion power PDT, QDT≡ PDT/Pext, and alpha profiles are presented. The PTRANSP code (see R.V. Budny, R. Andre, G. Bateman, F. Halpern, C.E. Kessel, A. Kritz, and D. McCune, Nuclear Fusion 48 075005, and F. Halpern, A. Kritz, G. Bateman, R.V. Budny, and D. McCune, Phys. Plasmas 15 062505) is used, along with GLF23 to predict plasma profiles, NUBEAM for NNBI and alpha heating, TORIC for ICRH, and TORAY for ECRH. Effects of sawteeth mixing, beam steering, beam shine-through, radiation loss, ash accumulation, and toroidal rotation are included. A total heating of Pext=73MW is assumed to achieve H-mode during the density and current ramp-up phase. Various mixes of NNBI, ICRH, and ECRH heating schemes are compared. After steady state conditions are achieved, Pext is stepped down to lower values to explore high QDT. Physics and computation uncertainties lead to ranges in predictions for PDT and QDT. Physics uncertainties include the L->H and H->L threshold powers, pedestal height, impurity and ash transport, and recycling. There are considerably more uncertainties predicting the peak value for QDT than for PDT.

Assessing the accuracy of predictive models for numerical data: Not r nor r2, why not? Then what?

PubMed Central

2017-01-01

Assessing the accuracy of predictive models is critical because predictive models have been increasingly used across various disciplines and predictive accuracy determines the quality of resultant predictions. Pearson product-moment correlation coefficient (r) and the coefficient of determination (r2) are among the most widely used measures for assessing predictive models for numerical data, although they are argued to be biased, insufficient and misleading. In this study, geometrical graphs were used to illustrate what were used in the calculation of r and r2 and simulations were used to demonstrate the behaviour of r and r2 and to compare three accuracy measures under various scenarios. Relevant confusions about r and r2, has been clarified. The calculation of r and r2 is not based on the differences between the predicted and observed values. The existing error measures suffer various limitations and are unable to tell the accuracy. Variance explained by predictive models based on cross-validation (VEcv) is free of these limitations and is a reliable accuracy measure. Legates and McCabe’s efficiency (E1) is also an alternative accuracy measure. The r and r2 do not measure the accuracy and are incorrect accuracy measures. The existing error measures suffer limitations. VEcv and E1 are recommended for assessing the accuracy. The applications of these accuracy measures would encourage accuracy-improved predictive models to be developed to generate predictions for evidence-informed decision-making. PMID:28837692

MiRNA Expression Analysis of Pretreatment Biopsies Predicts the Pathological Response of Esophageal Squamous Cell Carcinomas to Neoadjuvant Chemoradiotherapy.

PubMed

Wen, Jing; Luo, Kongjia; Liu, Hui; Liu, Shiliang; Lin, Guangrong; Hu, Yi; Zhang, Xu; Wang, Geng; Chen, Yuping; Chen, Zhijian; Li, Yi; Lin, Ting; Xie, Xiuying; Liu, Mengzhong; Wang, Huiyun; Yang, Hong; Fu, Jianhua

2016-05-01

To identify miRNA markers useful for esophageal squamous cell carcinoma (ESCC) neoadjuvant chemoradiotherapy (neo-CRT) response prediction. Neo-CRT followed by surgery improves ESCC patients' survival compared with surgery alone. However, CRT outcomes are heterogeneous, and no current methods can predict CRT responses. Differentially expressed miRNAs between ESCC pathological responders and nonresponders after neo-CRT were identified by miRNA profiling and verified by real-time quantitative polymerase chain reaction (qPCR) of 27 ESCCs in the training set. Several class prediction algorithms were used to build the response-classifying models with the qPCR data. Predictive powers of the models were further assessed with a second set of 79 ESCCs. Ten miRNAs with greater than a 1.5-fold change between pathological responders and nonresponders were identified and verified, respectively. A support vector machine (SVM) prediction model, composed of 4 miRNAs (miR-145-5p, miR-152, miR-193b-3p, and miR-376a-3p), were developed. It provided overall accuracies of 100% and 87.3% for discriminating pathological responders and nonresponders in the training and external validation sets, respectively. In multivariate analysis, the subgroup determined by the SVM model was the only independent factor significantly associated with neo-CRT response in the external validation sets. Combined qPCR of the 4 miRNAs provides the possibility of ESCC neo-CRT response prediction, which may facilitate individualized ESCC treatment. Further prospective validation in larger independent cohorts is necessary to fully assess its predictive power.

Optimal scaling of weight and waist circumference to height for maximal association with DXA-measured total body fat mass by sex, age and race/ethnicity.

PubMed

Heo, M; Kabat, G C; Gallagher, D; Heymsfield, S B; Rohan, T E

2013-08-01

Body mass index (BMI; weight (Wt)/height (Ht) (in kg m(-2)) and waist circumference (WC) are widely used as proxy anthropometric measures for total adiposity. Little is known about what scaling power of 'x' in both Wt(kg)/Ht(m)(x) and WC(m)/Ht(m)(x) is maximally associated with measured total body fat mass (TBFM). Establishing values for x would provide the information needed to create optimum anthropometric surrogate measures of adiposity. To estimate the value of 'x' that renders Wt/Ht(x) and WC/Ht(x) maximally associated with DXA-measured TBFM. Participants of the NHANES 1999-2004 surveys, stratified by sex (men, women), race/ethnicity (non-Hispanic whites, non-Hispanic blacks, Mexican-Americans), and age(18-29, 30-49, 50-84 years). We apply a grid search by increasing x from 0.0-3.0 by increments of 0.1 to the simple regression models, TBFM=b0+b1*(Wt/Ht(x)) and TBFM=b0+b1*(WC/Ht(x)) to obtain an estimate of x that results in the greatest R(2), taking into account complex survey design features and multiply imputed data. R(2)'s for BMI are 0.86 for men (N=6544) and 0.92 for women (N=6362). The optimal powers x for weight are 1.0 (R(2)=0.90) for men and 0.8 (R(2)=0.96) for women. The optimal power x for WC is 0, that is, no scaling of WC to height, for men (R(2)=0.90) or women (R(2)=0.82). The optimal powers for weight across nine combinations of race/ethnicity and age groups for each sex vary slightly (x=0.8-1.3) whereas the optimal scaling powers for WC are all 0 for both sexes except for non-Hispanic black men aged 18-29y (x=0.1). Although the weight-for-height indices with optimal powers are not independent of height, they yield more accurate TBFM estimates than BMI. In reference to TBFM, Wt/Ht and Wt/Ht(0.8) are the optimal weight-for-height indices for men and women, respectively, whereas WC alone, without Ht adjustment, is the optimal WC-for-height index for both sexes. Thus, BMI, an index independent of height, may be less useful when predicting TBFM.

Effects of Surface and Subsurface Bed Material Composition on Gravel Transport and Flow Competence Relations—Possibilities for Prediction

NASA Astrophysics Data System (ADS)

Bunte, K.; Abt, S. R.; Swingle, K. W.; Cenderelli, D. A.; Gaeuman, D. A.

2014-12-01

Bedload transport and flow competence relations are difficult to predict in coarse-bedded steep streams where widely differing sediment supply, bed stability, and complex flow hydraulics greatly affect amounts and sizes of transported gravel particles. This study explains how properties of bed material surface and subsurface size distributions are directly related to gravel transport and may be used for prediction of gravel transport and flow competence relations. Gravel transport, flow competence, and bed material size were measured in step-pool and plane-bed streams. Power functions were fitted to gravel transport QB=aQb and flow competence Dmax=cQd relations; Q is water discharge. Frequency distributions of surface FDsurf and subsurface FDsub bed material were likewise described by power functions FDsurf=hD j and FDsub=kDm fitted over six 0.5-phi size classes within 4 to 22.4 mm. Those gravel sizes are typically mobile even in moderate floods. Study results show that steeper subsurface bed material size distributions lead to steeper gravel transport and flow competence relations, whereas larger amounts of sediment contained in those 6 size bedmaterial classes (larger h and k) flatten the relations. Similarly, steeper surface size distributions decrease the coefficients of the gravel transport and flow competence relations, whereas larger amounts of sediment within the six bed material classes increase the intercepts of gravel transport and flow competence relations. Those relations are likely causative in streams where bedload stems almost entirely from the channel bed as opposed to direct (unworked) contributions from hillslopes and tributaries. The exponent of the subsurface bed material distribution m predicted the gravel transport exponent b with r2 near 0.7 and flow competence exponent d with r2 near 0.5. The intercept of bed surface distributions h increased the intercept a of gravel transport and c of the flow competence relations with r2 near 0.6.

Do physiological measures predict selected CrossFit® benchmark performance?

PubMed Central

Butcher, Scotty J; Neyedly, Tyler J; Horvey, Karla J; Benko, Chad R

2015-01-01

Purpose CrossFit® is a new but extremely popular method of exercise training and competition that involves constantly varied functional movements performed at high intensity. Despite the popularity of this training method, the physiological determinants of CrossFit performance have not yet been reported. The purpose of this study was to determine whether physiological and/or muscle strength measures could predict performance on three common CrossFit “Workouts of the Day” (WODs). Materials and methods Fourteen CrossFit Open or Regional athletes completed, on separate days, the WODs “Grace” (30 clean and jerks for time), “Fran” (three rounds of thrusters and pull-ups for 21, 15, and nine repetitions), and “Cindy” (20 minutes of rounds of five pull-ups, ten push-ups, and 15 bodyweight squats), as well as the “CrossFit Total” (1 repetition max [1RM] back squat, overhead press, and deadlift), maximal oxygen consumption (VO2max), and Wingate anaerobic power/capacity testing. Results Performance of Grace and Fran was related to whole-body strength (CrossFit Total) (r=−0.88 and −0.65, respectively) and anaerobic threshold (r=−0.61 and −0.53, respectively); however, whole-body strength was the only variable to survive the prediction regression for both of these WODs (R2=0.77 and 0.42, respectively). There were no significant associations or predictors for Cindy. Conclusion CrossFit benchmark WOD performance cannot be predicted by VO2max, Wingate power/capacity, or either respiratory compensation or anaerobic thresholds. Of the data measured, only whole-body strength can partially explain performance on Grace and Fran, although anaerobic threshold also exhibited association with performance. Along with their typical training, CrossFit athletes should likely ensure an adequate level of strength and aerobic endurance to optimize performance on at least some benchmark WODs. PMID:26261428

Correlating Resolving Power, Resolution, and Collision Cross Section: Unifying Cross-Platform Assessment of Separation Efficiency in Ion Mobility Spectrometry.

PubMed

Dodds, James N; May, Jody C; McLean, John A

2017-11-21

Here we examine the relationship among resolving power (R p ), resolution (R pp ), and collision cross section (CCS) for compounds analyzed in previous ion mobility (IM) experiments representing a wide variety of instrument platforms and IM techniques. Our previous work indicated these three variables effectively describe and predict separation efficiency for drift tube ion mobility spectrometry experiments. In this work, we seek to determine if our previous findings are a general reflection of IM behavior that can be applied to various instrument platforms and mobility techniques. Results suggest IM distributions are well characterized by a Gaussian model and separation efficiency can be predicted on the basis of the empirical difference in the gas-phase CCS and a CCS-based resolving power definition (CCS/ΔCCS). Notably traveling wave (TWIMS) was found to operate at resolutions substantially higher than a single-peak resolving power suggested. When a CCS-based R p definition was utilized, TWIMS was found to operate at a resolving power between 40 and 50, confirming the previous observations by Giles and co-workers. After the separation axis (and corresponding resolving power) is converted to cross section space, it is possible to effectively predict separation behavior for all mobility techniques evaluated (i.e., uniform field, trapped ion mobility, traveling wave, cyclic, and overtone instruments) using the equations described in this work. Finally, we are able to establish for the first time that the current state-of-the-art ion mobility separations benchmark at a CCS-based resolving power of >300 that is sufficient to differentiate analyte ions with CCS differences as small as 0.5%.

Analysis of the irradiation data for A302B and A533B correlation monitor materials

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

Wang, J.A.

1996-04-01

The results of Charpy V-notch impact tests for A302B and A533B-1 Correlation Monitor Materials (CMM) listed in the surveillance power reactor data base (PR-EDB) and material test reactor data base (TR-EDB) are analyzed. The shift of the transition temperature at 30 ft-lb (T{sub 30}) is considered as the primary measure of radiation embrittlement in this report. The hyperbolic tangent fitting model and uncertainty of the fitting parameters for Charpy impact tests are presented in this report. For the surveillance CMM data, the transition temperature shifts at 30 ft-lb ({Delta}T{sub 30}) generally follow the predictions provided by Revision 2 of Regulatorymore » Guide 1.99 (R.G. 1.99). Difference in capsule temperatures is a likely explanation for large deviations from R.G. 1.99 predictions. Deviations from the R.G. 1.99 predictions are correlated to similar deviations for the accompanying materials in the same capsules, but large random fluctuations prevent precise quantitative determination. Significant scatter is noted in the surveillance data, some of which may be attributed to variations from one specimen set to another, or inherent in Charpy V-notch testing. The major contributions to the uncertainty of the R.G. 1.99 prediction model, and the overall data scatter are from mechanical test results, chemical analysis, irradiation environments, fluence evaluation, and inhomogeneous material properties. Thus in order to improve the prediction model, control of the above-mentioned error sources needs to be improved. In general the embrittlement behavior of both the A302B and A533B-1 plate materials is similar. There is evidence for a fluence-rate effect in the CMM data irradiated in test reactors; thus its implication on power reactor surveillance programs deserves special attention.« less

Fuzzy logic, artificial neural network and mathematical model for prediction of white mulberry drying kinetics

NASA Astrophysics Data System (ADS)

Jahedi Rad, Shahpour; Kaveh, Mohammad; Sharabiani, Vali Rasooli; Taghinezhad, Ebrahim

2018-05-01

The thin-layer convective- infrared drying behavior of white mulberry was experimentally studied at infrared power levels of 500, 1000 and 1500 W, drying air temperatures of 40, 55 and 70 °C and inlet drying air speeds of 0.4, 1 and 1.6 m/s. Drying rate raised with the rise of infrared power levels at a distinct air temperature and velocity and thus decreased the drying time. Five mathematical models describing thin-layer drying have been fitted to the drying data. Midlli et al. model could satisfactorily describe the convective-infrared drying of white mulberry fruit with the values of the correlation coefficient (R 2=0.9986) and root mean square error of (RMSE= 0.04795). Artificial neural network (ANN) and fuzzy logic methods was desirably utilized for modeling output parameters (moisture ratio (MR)) regarding input parameters. Results showed that output parameters were more accurately predicted by fuzzy model than by the ANN and mathematical models. Correlation coefficient (R 2) and RMSE generated by the fuzzy model (respectively 0.9996 and 0.01095) were higher than referred values for the ANN model (0.9990 and 0.01988 respectively).

Hypoxanthine as a predictor of performance in highly trained athletes.

PubMed

Zieliński, J; Krasińska, B; Kusy, K

2013-12-01

Purine metabolism reflects the exercise-induced muscle adaptations and training status. This study evaluated the utility of plasma hypoxanthine in the prediction of actual sport performance. We studied male athletes: 28 triathletes (21.4±2.9 years), 12 long-distance runners (23.2±1.9 years), 13 middle-distance runners (22.9±1.8 years) and 18 sprinters (22.0±2.7 years). Season-best race times were considered, achieved over standard triathlon, 5 000 m, 1 500 m and 100 m, respectively. Incremental treadmill test was administered to determine maximum and "threshold" oxygen uptake. Resting and post-exercise plasma concentrations of hypoxanthine, xanthine, uric acid and lactate were measured as well as resting erythrocyte hypoxanthine-guanine phosphoribosyltransferase activity. Simple and multiple regression analyses were used to identify significant contributors to the variance in performance. Hypoxanthine considered alone explained more variance in triathletes, long-distance runners, middle-distance runners and sprinters (r 2=0.81, 0.81, 0.88 and 0.78, respectively) than models based on aerobic capacity and lactate (R 2=0.51, 0.37, 0.59 and 0.31, respectively). Combining purine metabolites and cardiorespiratory variables resulted in the best prediction (R 2=0.86, 0.93, 0.93 and 0.91; r=0.93, 0.96, 0.96 and 0.95, respectively). In summary, hypoxanthine is a strong predictor of performance in highly trained athletes and its prediction ability is very high regardless of sport specialization, spanning the continuum from speed-power to endurance disciplines. © Georg Thieme Verlag KG Stuttgart · New York.

Scaling for the SOL/separatrix χ ⊥ following from the heuristic drift model for the power scrape-off layer width

NASA Astrophysics Data System (ADS)

Huber, A.; Chankin, A. V.

2017-06-01

A simple two-point representation of the tokamak scrape-off layer (SOL) in the conduction limited regime, based on the parallel and perpendicular energy balance equations in combination with the heat flux width predicted by a heuristic drift-based model, was used to derive a scaling for the cross-field thermal diffusivity {χ }\\perp . For fixed plasma shape and neglecting weak power dependence indexes 1/8, the scaling {χ }\\perp \\propto {P}{{S}{{O}}{{L}}}/(n{B}θ {R}2) is derived.

Detection of Butter Adulteration with Lard by Employing (1)H-NMR Spectroscopy and Multivariate Data Analysis.

PubMed

Fadzillah, Nurrulhidayah Ahmad; Man, Yaakob bin Che; Rohman, Abdul; Rosman, Arieff Salleh; Ismail, Amin; Mustafa, Shuhaimi; Khatib, Alfi

2015-01-01

The authentication of food products from the presence of non-allowed components for certain religion like lard is very important. In this study, we used proton Nuclear Magnetic Resonance ((1)H-NMR) spectroscopy for the analysis of butter adulterated with lard by simultaneously quantification of all proton bearing compounds, and consequently all relevant sample classes. Since the spectra obtained were too complex to be analyzed visually by the naked eyes, the classification of spectra was carried out.The multivariate calibration of partial least square (PLS) regression was used for modelling the relationship between actual value of lard and predicted value. The model yielded a highest regression coefficient (R(2)) of 0.998 and the lowest root mean square error calibration (RMSEC) of 0.0091% and root mean square error prediction (RMSEP) of 0.0090, respectively. Cross validation testing evaluates the predictive power of the model. PLS model was shown as good models as the intercept of R(2)Y and Q(2)Y were 0.0853 and -0.309, respectively.

Selection of the most influential factors on the water-jet assisted underwater laser process by adaptive neuro-fuzzy technique

NASA Astrophysics Data System (ADS)

Nikolić, Vlastimir; Petković, Dalibor; Lazov, Lyubomir; Milovančević, Miloš

2016-07-01

Water-jet assisted underwater laser cutting has shown some advantages as it produces much less turbulence, gas bubble and aerosols, resulting in a more gentle process. However, this process has relatively low efficiency due to different losses in water. It is important to determine which parameters are the most important for the process. In this investigation was analyzed the water-jet assisted underwater laser cutting parameters forecasting based on the different parameters. The method of ANFIS (adaptive neuro fuzzy inference system) was applied to the data in order to select the most influential factors for water-jet assisted underwater laser cutting parameters forecasting. Three inputs are considered: laser power, cutting speed and water-jet speed. The ANFIS process for variable selection was also implemented in order to detect the predominant factors affecting the forecasting of the water-jet assisted underwater laser cutting parameters. According to the results the combination of laser power cutting speed forms the most influential combination foe the prediction of water-jet assisted underwater laser cutting parameters. The best prediction was observed for the bottom kerf-width (R2 = 0.9653). The worst prediction was observed for dross area per unit length (R2 = 0.6804). According to the results, a greater improvement in estimation accuracy can be achieved by removing the unnecessary parameter.

Using Plasticity Values Determined From Systematic Hardness Indentation Measurements for Predicting Impact Behavior in Structural Ceramics: A New, Simple Screening Technique

DTIC Science & Technology

2009-09-01

kFc ) is shown to fit the Knoop data quite well. A plot of log10 (HK) vs. log10 (F) yielded easily comparable straight lines, whose slope and...AlON), silicon carbide, aluminum oxide and boron carbide. A power-law equation (H = kFc ) is shown to fit the Knoop data quite well. A plot of log10... kFc HK= 24.183 F-0.0699 R2= 0.97 H K (G Pa ) Load (N) HK = a/F + b ErrorValue 0.919483.7367a 0.6903619.361b NA25.591Chisq NA0.67368R2 1 1.1 1.2

Quantitative structure activity relationship studies of sulfamide derivatives as carbonic anhydrase inhibitor: as antiglaucoma agents.

PubMed

Kumar, Surendra; Singh, Vineet; Tiwari, Meena

2007-07-01

Selective inhibition of ciliary process enzyme i.e. Carbonic Anhydrase-II is an excellent approach in reducing elevated intraocular pressure, thus treating glaucoma. Due to characteristic physicochemical properties of sulphonamide (Inhibition of Carbonic Anhydrase), they are clinically effective against glaucoma. But the non-specificity of sulphonamide derivatives to isozyme, leads to a range of side effects. Presently, the absence of comparative studies related to the binding of the sulphonamides as inhibitors to CA isozymes limits their use. In this paper we have represented "Three Dimensional Quantitative Structure Activity Relationship" study to characterize structural features of Sulfamide derivative [RR'NSO(2)NH(2)] as inhibitors, that are required for selective binding of carbonic anhydrase isozymes (CAI and CAII). In the analysis, stepwise multiple linear regression was performed using physiochemical parameters as independent variable and CA-I and CA-II inhibitory activity as dependent variable, respectively. The best multiparametric QSAR model obtained for CA-I inhibitory activity shows good statistical significance (r= 0.9714) and predictability (Q(2)=0.8921), involving the Electronic descriptors viz. Highest Occupied Molecular Orbital, Lowest Unoccupied Molecular Orbital and Steric descriptors viz. Principal moment of Inertia at X axis. Similarly, CA-II inhibitory activity also shows good statistical significance (r=0.9644) and predictability (Q(2)=0.8699) involving aforementioned descriptors. The predictive power of the model was successfully tested externally using a set of six compounds as test set for CA-I inhibitory activity and a set of seven compounds in case of CA-II inhibitory activity with good predictive squared correlation coefficient, r(2)(pred)=0.6016 and 0.7662, respectively. Overview of analysis favours substituents with high electronegativity and less bulk at R and R' positions of the parent nucleus, provides a basis to design new Sulfamide derivatives possessing potent and selective carbonic anhydrase-II inhibitory activity.

Evaluation of leaf litter leaching kinetics through commonly-used mathematical models

NASA Astrophysics Data System (ADS)

Montoya, J. V.; Bastianoni, A.; Mendez, C.; Paolini, J.

2012-04-01

Leaching is defined as the abiotic process by which soluble compounds of the litter are released into the water. Most studies dealing with leaf litter breakdown and leaching kinetics apply the single exponential decay model since it corresponds well with the understanding of the biology of decomposition. However, during leaching important mass losses occur and mathematical models often fail in describing this process adequately. During the initial hours of leaching leaf litter experience high decay rates which are not properly modelled. Adjusting leaching losses to mathematical models has not been investigated thoroughly and the use of models assuming constant decay rates leads to inappropriate assessments of leaching kinetics. We aim to describe, assess, and compare different leaching kinetics models fitted to leaf litter mass losses from six Neotropical riparian forest species. Leaf litter from each species was collected in the lower reaches of San Miguel stream in Northern Venezuela. Air-dried leaves from each species were incubated in 250 ml of water in the dark at room temperature. At 1h, 6h, 1d, 2d, 4d, 8d and 15d, three jars were removed from the assay in a no-replacement experimental design. At each time leaves from each jar were removed and oven-dried. Afterwards, dried up leaves were weighed and remaining dry mass was determined and expressed as ash-free dry mass. Mass losses of leaf litter showed steep declines for the first two days followed by a steady decrease in mass loss. Data was fitted to three different models: single-exponential, power and rational. Our results showed that the mass loss predicted with the single-exponential model did not reflect the real data at any stage of the leaching process. The power model showed a better adjustment, but fails predicting successfully the behavior during leaching's early stages. To evaluate the performance of our models we used three criteria: Adj-R2, Akaike's Information Criteria (AIC), and residual distribution. Higher Adj-R2 were obtained for the power and the rational-type models. However, when AIC and residuals distribution were used, the only model that could satisfactory predict the behavior of our dataset was the rational-type. Even if the Adj-R2 was higher for some species when using the power model compared to the rational-type; our results showed that this criterion alone cannot demonstrate the predicting performance of any model. Usually Adj-R2 is used when assessing the goodness of fit for any mathematical model disregarding the fact that a good Adj-R2 could be obtained even when statistical assumptions required for the validity of the model are not satisfied. Our results showed that sampling at the initial stages of leaching is necessary to adequately describe this process. We also provided evidence that using traditional mathematical models is not the best option to evaluate leaching kinetics because of its mathematical inability to properly describe the abrupt changes that occur during the early stages of leaching. We also found useful applying different criteria to evaluate the goodness-of-fit and performance of any model considered taking into account both statistical and biological meaning of the results.

Improve regional distribution and source apportionment of PM2.5 trace elements in China using inventory-observation constrained emission factors.

PubMed

Ying, Qi; Feng, Miao; Song, Danlin; Wu, Li; Hu, Jianlin; Zhang, Hongliang; Kleeman, Michael J; Li, Xinghua

2018-05-15

Contributions to 15 trace elements in airborne particulate matter with aerodynamic diameters <2.5μm (PM 2.5 ) in China from five major source sectors (industrial sources, residential sources, transportation, power generation and windblown dust) were determined using a source-oriented Community Multiscale Air Quality (CMAQ) model. Using emission factors in the composite speciation profiles from US EPA's SPECIATE database for the five sources leads to relatively poor model performance at an urban site in Beijing. Improved predictions of the trace elements are obtained by using adjusted emission factors derived from a robust multilinear regression of the CMAQ predicted primary source contributions and observation at the urban site. Good correlations between predictions and observations are obtained for most elements studied with R>0.5, except for crustal elements Al, Si and Ca, particularly in spring. Predicted annual and seasonal average concentrations of Mn, Fe, Zn and Pb in Nanjing and Chengdu are also consistently improved using the adjusted emission factors. Annual average concentration of Fe is as high as 2.0μgm -3 with large contributions from power generation and transportation. Annual average concentration of Pb reaches 300-500ngm -3 in vast areas, mainly from residential activities, transportation and power generation. The impact of high concentrations of Fe on secondary sulfate formation and Pb on human health should be evaluated carefully in future studies. Copyright © 2017 Elsevier B.V. All rights reserved.

Changes in anthropometry and performance, and their interrelationships, across three seasons in elite youth rugby league players.

PubMed

Waldron, Mark; Worsfold, Paul; Twist, Craig; Lamb, Kevin

2014-11-01

This study investigated the changes in anthropometry and performance, and their interrelationships, across 3 consecutive seasons (under-15 to under-17 age groups) in elite youth rugby league players. Each player participated in annual anthropometrical and performance assessments, comprising measurements of stature; body mass; limb lengths and circumference; skinfolds; predicted muscle cross-sectional area (CSA); 20-m speed, countermovement jump height, vertical power, and aerobic power. Lean body mass percentage changed (p ≤ 0.05) between the under-15 (70.9 ± 5.9%), under-16 (72.0 ± 5.8%), and the under-17 age groups (74.1 ± 5.7%). Likewise, predicted quadriceps muscle CSA also changed (p ≤ 0.05) between each age group (under-15 = 120.9 ± 37.8 cm; under-16 = 133.2 ± 36.0 cm; under-17 = 154.8 ± 28.3 cm). Concomitant changes between the under-15 and under-16 groups were found for 20-m speed (3.5 ± 0.1 cf. 3.4 ± 0.2 seconds; p = 0.008) and predicted jumping power (3,611.3 ± 327.3 W cf. 4,081.5 ± 453.9 W; p = 0.003). Both lean body mass and quadriceps muscle CSA consistently, related to both 20-m sprint time and jumping power, with r values ranging between -0.39 and -0.63 (20-m sprint time) and 0.55 to 0.75 (jumping power). Our findings demonstrate the importance of gains in lean body mass across later adolescence that support the ability to generate horizontal speed and predicted vertical power. This information informs the expectations and subsequent training programs of elite rugby league practitioners.

Phase boundaries of power-law Anderson and Kondo models: A poor man's scaling study

NASA Astrophysics Data System (ADS)

Cheng, Mengxing; Chowdhury, Tathagata; Mohammed, Aaron; Ingersent, Kevin

2017-07-01

We use the poor man's scaling approach to study the phase boundaries of a pair of quantum impurity models featuring a power-law density of states ρ (ɛ ) ∝|ɛ| r , either vanishing (for r >0 ) or diverging (for r <0 ) at the Fermi energy ɛ =0 , that gives rise to quantum phase transitions between local-moment and Kondo-screened phases. For the Anderson model with a pseudogap (i.e., r >0 ), we find the phase boundary for (a) 0 1 , where the phases are separated by first-order quantum phase transitions that are accessible only for broken p-h symmetry. For the p-h-symmetric Kondo model with easy-axis or easy-plane anisotropy of the impurity-band spin exchange, the phase boundary and scaling trajectories are obtained for both r >0 and r <0 . Throughout the regime of weak-to-moderate impurity-band coupling in which poor man's scaling is expected to be valid, the approach predicts phase boundaries in excellent qualitative and good quantitative agreement with the nonperturbative numerical renormalization group, while also establishing the functional relations between model parameters along these boundaries.

Flow Accelerated Erosion-Corrosion (FAC) considerations for secondary side piping in the AP1000{sup R} nuclear power plant design

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

Vanderhoff, J. F.; Rao, G. V.; Stein, A.

2012-07-01

The issue of Flow Accelerated Erosion-Corrosion (FAC) in power plant piping is a known phenomenon that has resulted in material replacements and plant accidents in operating power plants. Therefore, it is important for FAC resistance to be considered in the design of new nuclear power plants. This paper describes the design considerations related to FAC that were used to develop a safe and robust AP1000{sup R} plant secondary side piping design. The primary FAC influencing factors include: - Fluid Temperature - Pipe Geometry/layout - Fluid Chemistry - Fluid Velocity - Pipe Material Composition - Moisture Content (in steam lines) Duemore » to the unknowns related to the relative impact of the influencing factors and the complexities of the interactions between these factors, it is difficult to accurately predict the expected wear rate in a given piping segment in a new plant. This paper provides: - a description of FAC and the factors that influence the FAC degradation rate, - an assessment of the level of FAC resistance of AP1000{sup R} secondary side system piping, - an explanation of options to increase FAC resistance and associated benefits/cost, - discussion of development of a tool for predicting FAC degradation rate in new nuclear power plants. (authors)« less

Subjective experiences of family caregivers of patients with dementia as predictive factors of quality of life.

PubMed

Takai, Michiko; Takahashi, Megumi; Iwamitsu, Yumi; Oishi, Satoru; Miyaoka, Hitoshi

2011-06-01

The aim of the present study was to investigate predictive factors of quality of life (QOL) in home caregivers of patients with dementia. A total of 118 home caregivers (48 male, 70 female) were asked to complete the World Health Organization (WHO) Quality of Life 26 (WHO/QOL-26) questionnaire, the Pines Burnout Measure (BM), and the Beck Depression Inventory, second edition (BDI-II). Patient demographics and clinical data regarding cognitive impairment, neuropsychiatric symptoms, and dementia severity were obtained from medical records. Spearman rank correlation coefficients revealed that caregiver QOL was significantly correlated with patients' neuropsychiatric symptoms (r=-0.19; P < 0.05), as well as depressive symptoms (r=-0.59, P < 0.01) and burnout (r=-0.59, P < 0.01) in caregivers. Stepwise multiple regression analysis revealed that depressive symptoms in caregivers was the strongest predictor for caregiver QOL (R(2) = 0.37, P < 0.001) and that caregiver QOL was best predicted by the combination of depressive symptoms, burnout, and the cognitive impairment of patients (R(2) = 0.46, P < 0.05). The results of the present study demonstrate that subjective experiences of caregivers are more strongly correlated with caregiver QOL than patient-related variables and are thus powerful determinants of caregiver QOL. These findings suggest that caregiver intervention, which aims to increase QOL, may benefit from the incorporation of strategies to reduce depressive symptoms and burnout. © 2011 The Authors; Psychogeriatrics © 2011 Japanese Psychogeriatric Society.

Predicting High-Power Performance in Professional Cyclists.

PubMed

Sanders, Dajo; Heijboer, Mathieu; Akubat, Ibrahim; Meijer, Kenneth; Hesselink, Matthijs K

2017-03-01

To assess if short-duration (5 to ~300 s) high-power performance can accurately be predicted using the anaerobic power reserve (APR) model in professional cyclists. Data from 4 professional cyclists from a World Tour cycling team were used. Using the maximal aerobic power, sprint peak power output, and an exponential constant describing the decrement in power over time, a power-duration relationship was established for each participant. To test the predictive accuracy of the model, several all-out field trials of different durations were performed by each cyclist. The power output achieved during the all-out trials was compared with the predicted power output by the APR model. The power output predicted by the model showed very large to nearly perfect correlations to the actual power output obtained during the all-out trials for each cyclist (r = .88 ± .21, .92 ± .17, .95 ± .13, and .97 ± .09). Power output during the all-out trials remained within an average of 6.6% (53 W) of the predicted power output by the model. This preliminary pilot study presents 4 case studies on the applicability of the APR model in professional cyclists using a field-based approach. The decrement in all-out performance during high-intensity exercise seems to conform to a general relationship with a single exponential-decay model describing the decrement in power vs increasing duration. These results are in line with previous studies using the APR model to predict performance during brief all-out trials. Future research should evaluate the APR model with a larger sample size of elite cyclists.

Shape shifting predicts ontogenetic changes in metabolic scaling in diverse aquatic invertebrates

PubMed Central

Glazier, Douglas S.; Hirst, Andrew G.; Atkinson, David

2015-01-01

Metabolism fuels all biological activities, and thus understanding its variation is fundamentally important. Much of this variation is related to body size, which is commonly believed to follow a 3/4-power scaling law. However, during ontogeny, many kinds of animals and plants show marked shifts in metabolic scaling that deviate from 3/4-power scaling predicted by general models. Here, we show that in diverse aquatic invertebrates, ontogenetic shifts in the scaling of routine metabolic rate from near isometry (bR = scaling exponent approx. 1) to negative allometry (bR < 1), or the reverse, are associated with significant changes in body shape (indexed by bL = the scaling exponent of the relationship between body mass and body length). The observed inverse correlations between bR and bL are predicted by metabolic scaling theory that emphasizes resource/waste fluxes across external body surfaces, but contradict theory that emphasizes resource transport through internal networks. Geometric estimates of the scaling of surface area (SA) with body mass (bA) further show that ontogenetic shifts in bR and bA are positively correlated. These results support new metabolic scaling theory based on SA influences that may be applied to ontogenetic shifts in bR shown by many kinds of animals and plants. PMID:25652833

Anodic microbial community diversity as a predictor of the power output of microbial fuel cells.

PubMed

Stratford, James P; Beecroft, Nelli J; Slade, Robert C T; Grüning, André; Avignone-Rossa, Claudio

2014-03-01

The relationship between the diversity of mixed-species microbial consortia and their electrogenic potential in the anodes of microbial fuel cells was examined using different diversity measures as predictors. Identical microbial fuel cells were sampled at multiple time-points. Biofilm and suspension communities were analysed by denaturing gradient gel electrophoresis to calculate the number and relative abundance of species. Shannon and Simpson indices and richness were examined for association with power using bivariate and multiple linear regression, with biofilm DNA as an additional variable. In simple bivariate regressions, the correlation of Shannon diversity of the biofilm and power is stronger (r=0.65, p=0.001) than between power and richness (r=0.39, p=0.076), or between power and the Simpson index (r=0.5, p=0.018). Using Shannon diversity and biofilm DNA as predictors of power, a regression model can be constructed (r=0.73, p<0.001). Ecological parameters such as the Shannon index are predictive of the electrogenic potential of microbial communities. Copyright © 2014 Elsevier Ltd. All rights reserved.

Assessment of nonlethal methods for predicting muscle tissue mercury concentrations in coastal marine fishes

PubMed Central

Piraino, Maria N.; Taylor, David L.

2013-01-01

Caudal fin clips and dorsolateral scales were analyzed in this study as a potential nonlethal approach for predicting muscle tissue mercury (Hg) concentrations in marine fishes. Target fishes were collected from the Narragansett Bay (RI, USA), and included black sea bass Centropristis striata (n = 54, 14–55 cm total length, TL), bluefish Pomatomus saltatrix (n = 113, 31–73 cm TL), striped bass Morone saxatilis (n = 40, 34–102 cm TL), summer flounder Paralichthys dentatus (n = 64, 18–55 cm TL), and tautog Tautoga onitis (n = 102, 27–61 cm TL). For all fish species, Hg concentrations were greatest in muscle tissue (mean muscle Hg = 0.47–1.18 mg/kg dry weight), followed by fin clips (0.03–0.09 mg/kg dry weight) and scales (0.01–0.07 mg/kg dry weight). The coefficient of determination (R2) derived from power regressions of intra-species muscle Hg against fin and scale Hg ranged between 0.35–0.78 (mean R2 = 0.57) and 0.14–0.37 (mean R2 = 0.30), respectively. The inclusion of fish body size interaction effects in the regression models improved the predictive ability of fins (R2 = 0.63–0.80; mean = 0.71) and scales (R2 = 0.33–0.71; mean = 0.53). According to the high level of uncertainty within the regression models (R2 values) and confidence interval widths, scale analysis was deemed an ineffective tool for estimating muscle tissue Hg concentrations in the target species. In contrast, the examination of fin clips as predictors of muscle Hg had value as a cursory screening tool, but this method should not be the foundation for developing human consumption advisories. It is also noteworthy that the efficacy of these nonlethal techniques was highly variable across fishes, and likely depends on species-specific life history characteristics. PMID:23929385

A New Hybrid Spatio-temporal Model for Estimating Daily Multi-year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

NASA Technical Reports Server (NTRS)

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

2014-01-01

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter PM(sub 2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data.We developed and cross validated models to predict daily PM(sub 2.5) at a 1X 1 km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1 X 1 km grid predictions. We used mixed models regressing PM(sub 2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R(sup 2) = 0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R(sup 2) = 0.87, R(sup)2 = 0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

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

PubMed

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

2014-10-01

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter (PM 2.5 ) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data. We developed and cross validated models to predict daily PM 2.5 at a 1×1km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1×1 km grid predictions. We used mixed models regressing PM 2.5 measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R 2 =0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R 2 =0.87, R 2 =0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

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

PubMed Central

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

2017-01-01

Background The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter (PM2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. Methods We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data. We developed and cross validated models to predict daily PM2.5 at a 1×1km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003–2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1×1 km grid predictions. We used mixed models regressing PM2.5 measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Results Our model performance was excellent (mean out-of-sample R2=0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R2=0.87, R2=0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Conclusion Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region. PMID:28966552

Multiband superconductivity in BiS2-based layered compounds

NASA Astrophysics Data System (ADS)

Griffith, M. A.; Puel, T. O.; Continentino, M. A.; Martins, G. B.

2017-08-01

A mean-field treatment is presented of a square lattice two-orbital-model for \\text{Bi}{{\\text{S}}2} taking into account intra- and inter-orbital superconductivity. A rich phase diagram involving both types of superconductivity is presented as a function of the ratio between the couplings of electrons in the same and different orbitals (η ={{\\text{V}}\\text{XX}}/{{\\text{V}}\\text{XY}} ) and electron doping x. With the help of a quantity we call orbital-mixing ratio, denoted as R(φ ) , the phase diagram is analyzed using a simple and intuitive picture based on how R(φ ) varies as electron doping increases. The predictive power of R(φ ) suggests that it could be a useful tool in qualitatively (or even semi-quantitatively) analyzing multiband superconductivity in BCS-like superconductors.

Memory testing in dementia: how much is enough?

PubMed

Derrer, D S; Howieson, D B; Mueller, E A; Camicioli, R M; Sexton, G; Kaye, J A

2001-01-01

Analyses of eight widely used memory measures (Word List Acquisition and Recall used in the Alzheimer's Disease Assessment Scale and the Consortium to Establish a Registry for Alzheimer's Disease neuropsychology battery, Wechsler Memory Scale-Revised [WMS-R] Logical Memory I and II, WMS-R Visual Reproduction I and II, the memory scores from the Neurobehavioral Cognitive Status Examination [NCSE], memory scores from the Mini-Mental State Examination [MMSE]), and the MMSE total score showed each to have moderate predictive power in differentiating between patients with mild dementia and healthy normal controls. When these instruments were combined in a logistic regression analysis, three of them had substantial predictive power. Together, the Word List Acquisition, WMS-R Logical Memory II, and WMS-R Visual Reproduction II were 97.26% accurate (100% sensitive and 94.59% specific) in distinguishing these two groups. The Word List Acquisition is a brief test that alone had high accuracy (92%). These memory tests are highly useful in the diagnosis of mild dementia.

Prediction of textural attributes using color values of banana (Musa sapientum) during ripening.

PubMed

Jaiswal, Pranita; Jha, Shyam Narayan; Kaur, Poonam Preet; Bhardwaj, Rishi; Singh, Ashish Kumar; Wadhawan, Vishakha

2014-06-01

Banana is an important sub-tropical fruit in international trade. It undergoes significant textural and color transformations during ripening process, which in turn influence the eating quality of the fruit. In present study, color ('L', 'a' and 'b' value) and textural attributes of bananas (peel, fruit and pulp firmness; pulp toughness; stickiness) were studied simultaneously using Hunter Color Lab and Texture Analyser, respectively, during ripening period of 10 days at ambient atmosphere. There was significant effect of ripening period on all the considered textural characteristics and color properties of bananas except color value 'b'. In general, textural descriptors (peel, fruit and pulp firmness; and pulp toughness) decreased during ripening except stickiness, while color values viz 'a' and 'b' increased with ripening barring 'L' value. Among various textural attributes, peel toughness and pulp firmness showed highest correlation (r) with 'a' value of banana peel. In order to predict textural properties using color values of banana, five types of equations (linear/polynomial/exponential/logarithmic/power) were fitted. Among them, polynomial equation was found to be the best fit (highest coefficient of determination, R(2)) for prediction of texture using color properties for bananas. The pulp firmness, peel toughness and pulp toughness showed R(2) above 0.84 with indicating its potentiality of the fitted equations for prediction of textural profile of bananas non-destructively using 'a' value.

The Study of Rain Specific Attenuation for the Prediction of Satellite Propagation in Malaysia

NASA Astrophysics Data System (ADS)

Mandeep, J. S.; Ng, Y. Y.; Abdullah, H.; Abdullah, M.

2010-06-01

Specific attenuation is the fundamental quantity in the calculation of rain attenuation for terrestrial path and slant paths representing as rain attenuation per unit distance (dB/km). Specific attenuation is an important element in developing the predicted rain attenuation model. This paper deals with the empirical determination of the power law coefficients which allow calculating the specific attenuation in dB/km from the knowledge of the rain rate in mm/h. The main purpose of the paper is to obtain the coefficients of k and α of power law relationship between specific attenuation. Three years (from 1st January 2006 until 31st December 2008) rain gauge and beacon data taken from USM, Nibong Tebal have been used to do the empirical procedure analysis of rain specific attenuation. The data presented are semi-empirical in nature. A year-to-year variation of the coefficients has been indicated and the empirical measured data was compared with ITU-R provided regression coefficient. The result indicated that the USM empirical measured data was significantly vary from ITU-R predicted value. Hence, ITU-R recommendation for regression coefficients of rain specific attenuation is not suitable for predicting rain attenuation at Malaysia.

Multivariate models for prediction of rheological characteristics of filamentous fermentation broth from the size distribution.

PubMed

Petersen, Nanna; Stocks, Stuart; Gernaey, Krist V

2008-05-01

The main purpose of this article is to demonstrate that principal component analysis (PCA) and partial least squares regression (PLSR) can be used to extract information from particle size distribution data and predict rheological properties. Samples from commercially relevant Aspergillus oryzae fermentations conducted in 550 L pilot scale tanks were characterized with respect to particle size distribution, biomass concentration, and rheological properties. The rheological properties were described using the Herschel-Bulkley model. Estimation of all three parameters in the Herschel-Bulkley model (yield stress (tau(y)), consistency index (K), and flow behavior index (n)) resulted in a large standard deviation of the parameter estimates. The flow behavior index was not found to be correlated with any of the other measured variables and previous studies have suggested a constant value of the flow behavior index in filamentous fermentations. It was therefore chosen to fix this parameter to the average value thereby decreasing the standard deviation of the estimates of the remaining rheological parameters significantly. Using a PLSR model, a reasonable prediction of apparent viscosity (micro(app)), yield stress (tau(y)), and consistency index (K), could be made from the size distributions, biomass concentration, and process information. This provides a predictive method with a high predictive power for the rheology of fermentation broth, and with the advantages over previous models that tau(y) and K can be predicted as well as micro(app). Validation on an independent test set yielded a root mean square error of 1.21 Pa for tau(y), 0.209 Pa s(n) for K, and 0.0288 Pa s for micro(app), corresponding to R(2) = 0.95, R(2) = 0.94, and R(2) = 0.95 respectively. Copyright 2007 Wiley Periodicals, Inc.

Polygenic scores predict alcohol problems in an independent sample and show moderation by the environment.

PubMed

Salvatore, Jessica E; Aliev, Fazil; Edwards, Alexis C; Evans, David M; Macleod, John; Hickman, Matthew; Lewis, Glyn; Kendler, Kenneth S; Loukola, Anu; Korhonen, Tellervo; Latvala, Antti; Rose, Richard J; Kaprio, Jaakko; Dick, Danielle M

2014-04-10

Alcohol problems represent a classic example of a complex behavioral outcome that is likely influenced by many genes of small effect. A polygenic approach, which examines aggregate measured genetic effects, can have predictive power in cases where individual genes or genetic variants do not. In the current study, we first tested whether polygenic risk for alcohol problems-derived from genome-wide association estimates of an alcohol problems factor score from the age 18 assessment of the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 4304 individuals of European descent; 57% female)-predicted alcohol problems earlier in development (age 14) in an independent sample (FinnTwin12; n = 1162; 53% female). We then tested whether environmental factors (parental knowledge and peer deviance) moderated polygenic risk to predict alcohol problems in the FinnTwin12 sample. We found evidence for both polygenic association and for additive polygene-environment interaction. Higher polygenic scores predicted a greater number of alcohol problems (range of Pearson partial correlations 0.07-0.08, all p-values ≤ 0.01). Moreover, genetic influences were significantly more pronounced under conditions of low parental knowledge or high peer deviance (unstandardized regression coefficients (b), p-values (p), and percent of variance (R2) accounted for by interaction terms: b = 1.54, p = 0.02, R2 = 0.33%; b = 0.94, p = 0.04, R2 = 0.30%, respectively). Supplementary set-based analyses indicated that the individual top single nucleotide polymorphisms (SNPs) contributing to the polygenic scores were not individually enriched for gene-environment interaction. Although the magnitude of the observed effects are small, this study illustrates the usefulness of polygenic approaches for understanding the pathways by which measured genetic predispositions come together with environmental factors to predict complex behavioral outcomes.

From causal dynamical triangulations to astronomical observations

NASA Astrophysics Data System (ADS)

Mielczarek, Jakub

2017-09-01

This letter discusses phenomenological aspects of dimensional reduction predicted by the Causal Dynamical Triangulations (CDT) approach to quantum gravity. The deformed form of the dispersion relation for the fields defined on the CDT space-time is reconstructed. Using the Fermi satellite observations of the GRB 090510 source we find that the energy scale of the dimensional reduction is E* > 0.7 \\sqrt{4-d\\text{UV}} \\cdot 1010 \\text{GeV} at (95% CL), where d\\text{UV} is the value of the spectral dimension in the UV limit. By applying the deformed dispersion relation to the cosmological perturbations it is shown that, for a scenario when the primordial perturbations are formed in the UV region, the scalar power spectrum PS \\propto kn_S-1 , where n_S-1≈ \\frac{3 r (d\\text{UV}-2)}{(d\\text{UV}-1)r-48} . Here, r is the tensor-to-scalar ratio. We find that within the considered model, the predicted from CDT deviation from the scale invariance (n_S=1) is in contradiction with the up to date Planck and BICEP2.

CAN UPPER EXTREMITY FUNCTIONAL TESTS PREDICT THE SOFTBALL THROW FOR DISTANCE: A PREDICTIVE VALIDITY INVESTIGATION

PubMed Central

Hanney, William J.; Kolber, Morey J.; Davies, George J.; Riemann, Bryan

2011-01-01

Introduction: Understanding the relationships between performance tests and sport activity is important to the rehabilitation specialist. The purpose of this study was two- fold: 1) To identify if relationships exist between tests of upper body strength and power (Single Arm Seated Shot Put, Timed Push-Up, Timed Modified Pull-Up, and The Davies Closed Kinetic Chain Upper Extremity Stability Test, and the softball throw for distance), 2) To determine which variable or group of variables best predicts the performance of a sport specific task (the softball throw for distance). Methods: One hundred eighty subjects (111 females and 69 males, aged 18-45 years) performed the 5 upper extremity tests. The Pearson product moment correlation and a stepwise regression were used to determine whether relationships existed between performance on the tests and which upper extremity test result best explained the performance on the softball throw for distance. Results: There were significant correlations (r=.33 to r=.70, p=0.001) between performance on all of the tests. The modified pull-up test was the best predictor of the performance on the softball throw for distance (r2= 48.7), explaining 48.7% of variation in performance. When weight, height, and age were added to the regression equation the r2 values increased to 64.5, 66.2, and 67.5 respectively. Conclusion: The results of this study indicate that several upper extremity tests demonstrate significant relationships with one another and with the softball throw for distance. The modified pull up test was the best predictor of performance on the softball throw for distance. PMID:21712942

The role of the mitochondrial ribosome in human disease: searching for mutations in 12S mitochondrial rRNA with high disruptive potential

PubMed Central

Smith, Paul M.; Elson, Joanna L.; Greaves, Laura C.; Wortmann, Saskia B.; Rodenburg, Richard J.T.; Lightowlers, Robert N.; Chrzanowska-Lightowlers, Zofia M.A.; Taylor, Robert W.; Vila-Sanjurjo, Antón

2014-01-01

Mutations of mitochondrial DNA are linked to many human diseases. Despite the identification of a large number of variants in the mitochondrially encoded rRNA (mt-rRNA) genes, the evidence supporting their pathogenicity is, at best, circumstantial. Establishing the pathogenicity of these variations is of major diagnostic importance. Here, we aim to estimate the disruptive effect of mt-rRNA variations on the function of the mitochondrial ribosome. In the absence of direct biochemical methods to study the effect of mt-rRNA variations, we relied on the universal conservation of the rRNA fold to infer their disruptive potential. Our method, named heterologous inferential analysis or HIA, combines conservational information with functional and structural data obtained from heterologous ribosomal sources. Thus, HIA's predictive power is superior to the traditional reliance on simple conservation indexes. By using HIA, we have been able to evaluate the disruptive potential for a subset of uncharacterized 12S mt-rRNA variations. Our analysis revealed the existence of variations in the rRNA component of the human mitoribosome with different degrees of disruptive power. In cases where sufficient information regarding the genetic and pathological manifestation of the mitochondrial phenotype is available, HIA data can be used to predict the pathogenicity of mt-rRNA mutations. In other cases, HIA analysis will allow the prioritization of variants for additional investigation. Eventually, HIA-inspired analysis of potentially pathogenic mt-rRNA variations, in the context of a scoring system specifically designed for these variants, could lead to a powerful diagnostic tool. PMID:24092330

Thinking styles and emotions.

PubMed

Zhang, Li-Fang

2008-09-01

This study aimed to explore the relationship between thinking styles and emotions among university students in Hong Kong. Participants were 99 2nd-year students (23 men and 76 women) who responded to the Thinking Styles Inventory-Revised (TSI-R), based on R. J. Sternberg's (1988) theory of mental self-government, and to the Iowa Managing Emotions Inventory (IMEI), based on A. Chickering's (1969) theory of psychosocial development. Results indicated not only that thinking styles were associated with emotions but also that thinking styles had predictive power for emotions beyond age. The author discusses implications of these findings for faculty members and student-development educators.

Quasiballistic heat removal from small sources studied from first principles

NASA Astrophysics Data System (ADS)

Vermeersch, Bjorn; Mingo, Natalio

2018-01-01

Heat sources whose characteristic dimension R is comparable to phonon mean free paths display thermal resistances that exceed conventional diffusive predictions. This has direct implications to (opto)electronics thermal management and phonon spectroscopy. Theoretical analyses have so far limited themselves to particular experimental configurations. Here, we build upon the multidimensional Boltzmann transport equation (BTE) to derive universal expressions for the apparent conductivity suppression S (R ) =κeff(R ) /κbulk experienced by radially symmetric 2D and 3D sources. In striking analogy to cross-plane heat conduction in thin films, a distinct quasiballistic regime emerges between ballistic (κeff˜R ) and diffusive (κeff≃κbulk ) asymptotes that displays a logarithmic dependence κeff˜ln(R ) in single crystals and fractional power dependence κeff˜R2 -α in alloys (with α the Lévy superdiffusion exponent). Analytical solutions and Monte Carlo simulations for spherical and circular heat sources in Si, GaAs, Si0.99Ge0.01 , and Si0.82Ge0.18 , all carried out from first principles, confirm the predicted generic tendencies. Contrary to the thin film case, common approximations like kinetic theory estimates κeff≃∑Sωgreyκω and modified Fourier temperature curves perform relatively poorly. Up to threefold deviations from the BTE solutions for sub-100 nm sources underline the need for rigorous treatment of multidimensional nondiffusive transport.

The validity of Iran’s national university entrance examination (Konkoor) for predicting medical students’ academic performance

PubMed Central

2012-01-01

Background In Iran, admission to medical school is based solely on the results of the highly competitive, nationwide Konkoor examination. This paper examines the predictive validity of Konkoor scores, alone and in combination with high school grade point averages (hsGPAs), for the academic performance of public medical school students in Iran. Methods This study followed the cohort of 2003 matriculants at public medical schools in Iran from entrance through internship. The predictor variables were Konkoor total and subsection scores and hsGPAs. The outcome variables were (1) Comprehensive Basic Sciences Exam (CBSE) scores; (2) Comprehensive Pre-Internship Exam (CPIE) scores; and (3) medical school grade point averages (msGPAs) for the courses taken before internship. Pearson correlation and regression analyses were used to assess the relationships between the selection criteria and academic performance. Results There were 2126 matriculants (1374 women and 752 men) in 2003. Among the outcome variables, the CBSE had the strongest association with the Konkoor total score (r = 0.473), followed by msGPA (r = 0.339) and the CPIE (r = 0.326). While adding hsGPAs to the Konkoor total score almost doubled the power to predict msGPAs (R2 = 0.225), it did not have a substantial effect on CBSE or CPIE prediction. Conclusions The Konkoor alone, and even in combination with hsGPA, is a relatively poor predictor of medical students’ academic performance, and its predictive validity declines over the academic years of medical school. Care should be taken to develop comprehensive admissions criteria, covering both cognitive and non-cognitive factors, to identify the best applicants to become "good doctors" in the future. The findings of this study can be helpful for policy makers in the medical education field. PMID:22840211

Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort.

PubMed

Gao, Ying-Duo; Hu, Yuan; Crespo, Alejandro; Wang, Deping; Armacost, Kira A; Fells, James I; Fradera, Xavier; Wang, Hongwu; Wang, Huijun; Sherborne, Brad; Verras, Andreas; Peng, Zhengwei

2018-01-01

The 2016 D3R Grand Challenge 2 includes both pose and affinity or ranking predictions. This article is focused exclusively on affinity predictions submitted to the D3R challenge from a collaborative effort of the modeling and informatics group. Our submissions include ranking of 102 ligands covering 4 different chemotypes against the FXR ligand binding domain structure, and the relative binding affinity predictions of the two designated free energy subsets of 15 and 18 compounds. Using all the complex structures prepared in the same way allowed us to cover many types of workflows and compare their performances effectively. We evaluated typical workflows used in our daily structure-based design modeling support, which include docking scores, force field-based scores, QM/MM, MMGBSA, MD-MMGBSA, and MacroModel interaction energy estimations. The best performing methods for the two free energy subsets are discussed. Our results suggest that affinity ranking still remains very challenging; that the knowledge of more structural information does not necessarily yield more accurate predictions; and that visual inspection and human intervention are considerably important for ranking. Knowledge of the mode of action and protein flexibility along with visualization tools that depict polar and hydrophobic maps are very useful for visual inspection. QM/MM-based workflows were found to be powerful in affinity ranking and are encouraged to be applied more often. The standardized input and output enable systematic analysis and support methodology development and improvement for high level blinded predictions.

Workflows and performances in the ranking prediction of 2016 D3R Grand Challenge 2: lessons learned from a collaborative effort

NASA Astrophysics Data System (ADS)

Gao, Ying-Duo; Hu, Yuan; Crespo, Alejandro; Wang, Deping; Armacost, Kira A.; Fells, James I.; Fradera, Xavier; Wang, Hongwu; Wang, Huijun; Sherborne, Brad; Verras, Andreas; Peng, Zhengwei

2018-01-01

The 2016 D3R Grand Challenge 2 includes both pose and affinity or ranking predictions. This article is focused exclusively on affinity predictions submitted to the D3R challenge from a collaborative effort of the modeling and informatics group. Our submissions include ranking of 102 ligands covering 4 different chemotypes against the FXR ligand binding domain structure, and the relative binding affinity predictions of the two designated free energy subsets of 15 and 18 compounds. Using all the complex structures prepared in the same way allowed us to cover many types of workflows and compare their performances effectively. We evaluated typical workflows used in our daily structure-based design modeling support, which include docking scores, force field-based scores, QM/MM, MMGBSA, MD-MMGBSA, and MacroModel interaction energy estimations. The best performing methods for the two free energy subsets are discussed. Our results suggest that affinity ranking still remains very challenging; that the knowledge of more structural information does not necessarily yield more accurate predictions; and that visual inspection and human intervention are considerably important for ranking. Knowledge of the mode of action and protein flexibility along with visualization tools that depict polar and hydrophobic maps are very useful for visual inspection. QM/MM-based workflows were found to be powerful in affinity ranking and are encouraged to be applied more often. The standardized input and output enable systematic analysis and support methodology development and improvement for high level blinded predictions.

FDG-PET/CT at the end of immuno-chemotherapy in follicular lymphoma: the prognostic role of the ratio between target lesion and liver SUVmax (rPET).

PubMed

Annunziata, Salvatore; Cuccaro, Annarosa; Tisi, Maria Chiara; Hohaus, Stefan; Rufini, Vittoria

2018-06-01

To retrospectively investigate the prognostic role of the ratio between target lesion and liver SUV max (rPET) in patients with follicular lymphoma (FL) submitted to FDG-PET/CT at the end of immuno-chemotherapy (PI-PET), and to compare rPET with International Harmonization Project criteria (IHP), Deauville Score (5p-DS) and FL International Prognostic Index at diagnosis (FLIPI). Eighty-nine patients with FL undergoing PI-PET were evaluated. The receiver operating characteristic (ROC) approach was applied to identify the optimal cut-point of rPET with respect to 5-years progression free survival (PFS). The prognostic significance of rPET was compared with IHP, DS and FLIPI. Positive predictive value (PPV) and negative predictive value (NPV) were calculated using the presence of adverse events as gold standard. The ROC analysis for rPET as predictor of progression showed an optimal rPET cut-point of 0.98. Patients with positive values of IHP, DS and rPET had a PFS of 50, 30 and 31%. PPV were of 56, 80 and 80%, NPV of 83, 86 and 88%, respectively. DS and rPET differed only in two patients. FLIPI was not predictive of progression and relapse. rPET is a prognostic factor in patients with FL submitted to PI-PET. Although it has a similar prognostic power as DS, it can have methodological advantages over visual analysis. PI-PET with different evaluation systems has a stronger prognostic power than FLIPI at diagnosis, so it could be useful to identify patients with FL at risk for early relapse after immuno-chemotherapy.

Combining self- and cross-docking as benchmark tools: the performance of DockBench in the D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

Salmaso, Veronica; Sturlese, Mattia; Cuzzolin, Alberto; Moro, Stefano

2018-01-01

Molecular docking is a powerful tool in the field of computer-aided molecular design. In particular, it is the technique of choice for the prediction of a ligand pose within its target binding site. A multitude of docking methods is available nowadays, whose performance may vary depending on the data set. Therefore, some non-trivial choices should be made before starting a docking simulation. In the same framework, the selection of the target structure to use could be challenging, since the number of available experimental structures is increasing. Both issues have been explored within this work. The pose prediction of a pool of 36 compounds provided by D3R Grand Challenge 2 organizers was preceded by a pipeline to choose the best protein/docking-method couple for each blind ligand. An integrated benchmark approach including ligand shape comparison and cross-docking evaluations was implemented inside our DockBench software. The results are encouraging and show that bringing attention to the choice of the docking simulation fundamental components improves the results of the binding mode predictions.

Neuroeconomics and public health

PubMed Central

Larsen, Torben

2010-01-01

Objective To design an economic evaluation strategy for general health promotion projects. Method Identification of key parameters of behavioral health from neuroeconomic studies. Results The Frontal Power of Concentration (C) is a quadripartite executive integrator depending on four key parameters: 1) The Limbic system originating ambivalent emotions (L). 2) Volition in the Prefrontal Cortex (c) controlling cognitive prediction and emotions with a view on Frontopolar long-term goals. 3) Semantic memories in the Temporal lobe (R). 4) An intuitive visuospatial sketchpad in the Parietal lobe (I). C aiming to minimize error between preferences and predictions is directly determined by the following equation including I as a stochastic knowledge component: C =Rc2/L +εI→ 1 Discussion All of the parameters of C are object to improvement by training: Cognitive predictions are improved by open-mindedness towards feedback (R).The effect of emotional regrets is reinforced by an appropriate level of fitness (c, L).Our imagination may be unfolded by in-depth-relaxation-procedures and visualization (I). Conclusion Economic evaluation of general public health should focus on the subset of separate and integrated interventions that directly affect the parameters of Formula C in individuals.

The clinical role of microRNA-21 as a promising biomarker in the diagnosis and prognosis of colorectal cancer: a systematic review and meta-analysis.

PubMed

Peng, Qiliang; Zhang, Xueli; Min, Ming; Zou, Li; Shen, Peipei; Zhu, Yaqun

2017-07-04

This systematic analysis aimed to investigate the value of microRNA-21 (miR-21) in colorectal cancer for multiple purposes, including diagnosis and prognosis, as well as its predictive power in combination biomarkers. Fifty-seven eligible studies were included in our meta-analysis, including 25 studies for diagnostic meta-analysis and 32 for prognostic meta-analysis. For the diagnostic meta-analysis of miR-21 alone, the overall pooled results for sensitivity, specificity, and area under the curve (AUC) were 0.64 (95% CI: 0.53-0.74), 0.85 (0.79-0.90), and 0.85 (0.81-0.87), respectively. Circulating samples presented corresponding values of 0.72 (0.63-0.79), 0.84 (0.78-0.89), and 0.86 (0.83-0.89), respectively. For the diagnostic meta-analysis of miR-21-related combination biomarkers, the above three parameters were 0.79 (0.69-0.86), 0.79 (0.68-0.87), and 0.86 (0.83-0.89), respectively. Notably, subgroup analysis suggested that miRNA combination markers in circulation exhibited high predictive power, with sensitivity of 0.85 (0.70-0.93), specificity of 0.86 (0.77-0.92), and AUC of 0.92 (0.89-0.94). For the prognostic meta-analysis, patients with higher expression of miR-21 had significant shorter disease-free survival [DFS; pooled hazard ratio (HR): 1.60; 95% CI: 1.20-2.15] and overall survival (OS; 1.54; 1.27-1.86). The combined HR in tissues for DFS and OS were 1.76 (1.31-2.36) and 1.58 (1.30-1.93), respectively. Our comprehensive systematic review revealed that circulating miR-21 may be suitable as a diagnostic biomarker, while tissue miR-21 could be a prognostic marker for colorectal cancer. In addition, miRNA combination biomarkers may provide a new approach for clinical application.

Predicting Increased Blood Pressure Using Machine Learning

PubMed Central

Golino, Hudson Fernandes; Amaral, Liliany Souza de Brito; Duarte, Stenio Fernando Pimentel; Soares, Telma de Jesus; dos Reis, Luciana Araujo

2014-01-01

The present study investigates the prediction of increased blood pressure by body mass index (BMI), waist (WC) and hip circumference (HC), and waist hip ratio (WHR) using a machine learning technique named classification tree. Data were collected from 400 college students (56.3% women) from 16 to 63 years old. Fifteen trees were calculated in the training group for each sex, using different numbers and combinations of predictors. The result shows that for women BMI, WC, and WHR are the combination that produces the best prediction, since it has the lowest deviance (87.42), misclassification (.19), and the higher pseudo R 2 (.43). This model presented a sensitivity of 80.86% and specificity of 81.22% in the training set and, respectively, 45.65% and 65.15% in the test sample. For men BMI, WC, HC, and WHC showed the best prediction with the lowest deviance (57.25), misclassification (.16), and the higher pseudo R 2 (.46). This model had a sensitivity of 72% and specificity of 86.25% in the training set and, respectively, 58.38% and 69.70% in the test set. Finally, the result from the classification tree analysis was compared with traditional logistic regression, indicating that the former outperformed the latter in terms of predictive power. PMID:24669313

Predicting increased blood pressure using machine learning.

PubMed

Golino, Hudson Fernandes; Amaral, Liliany Souza de Brito; Duarte, Stenio Fernando Pimentel; Gomes, Cristiano Mauro Assis; Soares, Telma de Jesus; Dos Reis, Luciana Araujo; Santos, Joselito

2014-01-01

The present study investigates the prediction of increased blood pressure by body mass index (BMI), waist (WC) and hip circumference (HC), and waist hip ratio (WHR) using a machine learning technique named classification tree. Data were collected from 400 college students (56.3% women) from 16 to 63 years old. Fifteen trees were calculated in the training group for each sex, using different numbers and combinations of predictors. The result shows that for women BMI, WC, and WHR are the combination that produces the best prediction, since it has the lowest deviance (87.42), misclassification (.19), and the higher pseudo R (2) (.43). This model presented a sensitivity of 80.86% and specificity of 81.22% in the training set and, respectively, 45.65% and 65.15% in the test sample. For men BMI, WC, HC, and WHC showed the best prediction with the lowest deviance (57.25), misclassification (.16), and the higher pseudo R (2) (.46). This model had a sensitivity of 72% and specificity of 86.25% in the training set and, respectively, 58.38% and 69.70% in the test set. Finally, the result from the classification tree analysis was compared with traditional logistic regression, indicating that the former outperformed the latter in terms of predictive power.

The two-photon absorptivity of rotational transitions in the A2 Sigma hyperon + (v prime = O) - X-2 pion (v prime prime = O) gamma band of nitric oxide

NASA Technical Reports Server (NTRS)

Gross, K. P.; Mckenzie, R. L.

1982-01-01

A predominantly single-mode pulsed dye laser system giving a well characterized spatial and temporal output suitable for absolute two-photon absorptivity measurements was used to study the NO gamma(0,0) S11 + R21 (J double prime = 7-1/2) transition. Using a calibrated induced-fluorescence technique, an absorptivity parameter of 2.8 + or - 1.4 x 10 to the minus 51st power cm to the 6th power was obtained. Relative strengths of other rotational transitions in the gamma(0,0) band were also measured and shown to compare well with predicted values in all cases except the O12 (J double prime = 10-1/2) transition.

High-potential Working Fluids for Next Generation Binary Cycle Geothermal Power Plants

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

Zia, Jalal; Sevincer, Edip; Chen, Huijuan

2013-06-29

A thermo-economic model has been built and validated for prediction of project economics of Enhanced Geothermal Projects. The thermo-economic model calculates and iteratively optimizes the LCOE (levelized cost of electricity) for a prospective EGS (Enhanced Geothermal) site. It takes into account the local subsurface temperature gradient, the cost of drilling and reservoir creation, stimulation and power plant configuration. It calculates and optimizes the power plant configuration vs. well depth. Thus outputs from the model include optimal well depth and power plant configuration for the lowest LCOE. The main focus of this final report was to experimentally validate the thermodynamic propertiesmore » that formed the basis of the thermo-economic model built in Phase 2, and thus build confidence that the predictions of the model could be used reliably for process downselection and preliminary design at a given set of geothermal (and/or waste heat) boundary conditions. The fluid and cycle downselected was based on a new proprietary fluid from a vendor in a supercritical ORC cycle at a resource condition of 200°C inlet temperature. The team devised and executed a series of experiments to prove the suitability of the new fluid in realistic ORC cycle conditions. Furthermore, the team performed a preliminary design study for a MW-scale turbo expander that would be used for a supercritical ORC cycle with this new fluid. The following summarizes the main findings in the investigative campaign that was undertaken: 1. Chemical compatibility of the new fluid with common seal/gasket/Oring materials was found to be problematic. Neoprene, Viton, and silicone materials were found to be incompatible, suffering chemical decomposition, swelling and/or compression set issues. Of the materials tested, only TEFLON was found to be compatible under actual ORC temperature and pressure conditions. 2. Thermal stability of the new fluid at 200°C and 40 bar was found to be acceptable after 399 hours of exposure?only 3% of the initial charge degraded into by products. The main degradation products being an isomer and a dimer. 3. In a comparative experiment between R245fa and the new fluid under subcritical conditions, it was found that the new fluid operated at 1 bar lower than R245fa for the same power output, which was also predicted in the Aspen HSYSY model. As a drop-in replacement fluid for R245fa, this new fluid was found to be at least as good as R245fa in terms of performance and stability. Further optimization of the subcritical cycle may lead to a significant improvement in performance for the new fluid. 4. For supercritical conditions, the experiment found a good match between the measured and model predicted state point property data and duties from the energy balance. The largest percent differences occurred with densities and evaporator duty (see Figure 78). It is therefore reasonable to conclude that the state point model was experimentally validated with a realistic ORC system. 5. The team also undertook a preliminary turbo-expander design study for a supercritical ORC cycle with the new working fluid. Variants of radial and axial turbo expander geometries went through preliminary design and rough costing. It was found that at 15MWe or higher power rating, a multi-stage axial turbine is most suitable providing the best performance and cost. However, at lower power ratings in the 5MWe range, the expander technology to be chosen depends on the application of the power block. For EGS power blocks, it is most optimal to use multi-stage axial machines. In conclusion, the predictions of the LCOE model that showed a supercritical cycle based on the new fluid to be most advantageous for geothermal power production at a resource temperature of ~ 200C have been experimentally validated. It was found that the cycle based on the new fluid is lower in LCOE and higher in net power output (for the same boundary conditions). The project, therefore has found a new optimal configuration for low temperature geothermal power production in the form of a supercritical ORC cycle based on a new vendor fluid.« less

Predictions of H-mode performance in ITER

NASA Astrophysics Data System (ADS)

Budny, Robert

2008-11-01

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

Validation of the FAST skating protocol to predict aerobic power in ice hockey players.

PubMed

Petrella, Nicholas J; Montelpare, William J; Nystrom, Murray; Plyley, Michael; Faught, Brent E

2007-08-01

Few studies have reported a sport-specific protocol to measure the aerobic power of ice hockey players using a predictive process. The purpose of our study was to validate an ice hockey aerobic field test on players of varying ages, abilities, and levels. The Faught Aerobic Skating Test (FAST) uses an on-ice continuous skating protocol on a course measuring 160 feet (48.8 m) using a CD to pace the skater with a beep signal to cross the starting line at each end of the course. The FAST incorporates the principle of increasing workload at measured time intervals during a continuous skating exercise. Step-wise multiple regression modelling was used to determine the estimate of aerobic power. Participants completed a maximal aerobic power test using a modified Bruce incremental treadmill protocol, as well as the on-ice FAST. Normative data were collected on 406 ice hockey players (291 males, 115 females) ranging in age from 9 to 25 y. A regression to predict maximum aerobic power was developed using body mass (kg), height (m), age (y), and maximum completed lengths of the FAST as the significant predictors of skating aerobic power (adjusted R2 = 0.387, SEE = 7.25 mL.kg-1.min-1, p < 0.0001). These results support the application of the FAST in estimating aerobic power among male and female competitive ice hockey players between the ages of 9 and 25 years.

Gender Role Conflict, Interest in Casual Sex, and Relationship Satisfaction Among Gay Men

PubMed Central

Sanchez, Fráncisco J.; Bocklandt, Sven; Vilain, Eric

2010-01-01

This study compared single (n = 129) and partnered gay men (n = 114) to determine if they differed in their concerns over traditional masculine roles and interest in casual sex, and to measure the relationship between concerns over masculine roles and interest in casual sex. Additionally, a regression model to predict relationship satisfaction was tested. Participants were recruited at two Southern California Gay Pride festivals. Group comparisons showed single men were more restrictive in their affectionate behavior with other men (effect-size r = .14) and were more interested in casual sex than partnered men (effect-size r = .13); and partnered men were more concerned with being successful, powerful, and competitive than single men (effect-size r = .20). Different masculine roles were predictive of interest in casual sex among the two groups of men. Finally, a hierarchical regression analysis found that interest in casual sex and the length of one’s current relationship served as unique predictors of relationship satisfaction among the partnered gay men (Cohen’s f2 = .52). PMID:20721305

Shape shifting predicts ontogenetic changes in metabolic scaling in diverse aquatic invertebrates.

PubMed

Glazier, Douglas S; Hirst, Andrew G; Atkinson, David

2015-03-07

Metabolism fuels all biological activities, and thus understanding its variation is fundamentally important. Much of this variation is related to body size, which is commonly believed to follow a 3/4-power scaling law. However, during ontogeny, many kinds of animals and plants show marked shifts in metabolic scaling that deviate from 3/4-power scaling predicted by general models. Here, we show that in diverse aquatic invertebrates, ontogenetic shifts in the scaling of routine metabolic rate from near isometry (bR = scaling exponent approx. 1) to negative allometry (bR < 1), or the reverse, are associated with significant changes in body shape (indexed by bL = the scaling exponent of the relationship between body mass and body length). The observed inverse correlations between bR and bL are predicted by metabolic scaling theory that emphasizes resource/waste fluxes across external body surfaces, but contradict theory that emphasizes resource transport through internal networks. Geometric estimates of the scaling of surface area (SA) with body mass (bA) further show that ontogenetic shifts in bR and bA are positively correlated. These results support new metabolic scaling theory based on SA influences that may be applied to ontogenetic shifts in bR shown by many kinds of animals and plants. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Low speed maneuvering flight of the rose-breasted cockatoo (Eolophus roseicapillus). II. Inertial and aerodynamic reorientation.

PubMed

Hedrick, T L; Usherwood, J R; Biewener, A A

2007-06-01

The reconfigurable, flapping wings of birds allow for both inertial and aerodynamic modes of reorientation. We found evidence that both these modes play important roles in the low speed turning flight of the rose-breasted cockatoo Eolophus roseicapillus. Using three-dimensional kinematics recorded from six cockatoos making a 90 degrees turn in a flight corridor, we developed predictions of inertial and aerodynamic reorientation from estimates of wing moments of inertia and flapping arcs, and a blade-element aerodynamic model. The blade-element model successfully predicted weight support (predicted was 88+/-17% of observed, N=6) and centripetal force (predicted was 79+/-29% of observed, N=6) for the maneuvering cockatoos and provided a reasonable estimate of mechanical power. The estimated torque from the model was a significant predictor of roll acceleration (r(2)=0.55, P<0.00001), but greatly overestimated roll magnitude when applied with no roll damping. Non-dimensional roll damping coefficients of approximately -1.5, 2-6 times greater than those typical of airplane flight dynamics (approximately -0.45), were required to bring our estimates of reorientation due to aerodynamic torque back into conjunction with the measured changes in orientation. Our estimates of inertial reorientation were statistically significant predictors of the measured reorientation within wingbeats (r(2) from 0.2 to 0.37, P<0.0005). Components of both our inertial reorientation and aerodynamic torque estimates correlated, significantly, with asymmetries in the activation profile of four flight muscles: the pectoralis, supracoracoideus, biceps brachii and extensor metacarpi radialis (r(2) from 0.27 to 0.45, P<0.005). Thus, avian flight maneuvers rely on production of asymmetries throughout the flight apparatus rather than in a specific set of control or turning muscles.

Advanced 2-dimensional quantitative coronary angiographic analysis for prediction of fractional flow reserve in intermediate coronary stenoses.

PubMed

Opolski, Maksymilian P; Pregowski, Jerzy; Kruk, Mariusz; Kepka, Cezary; Staruch, Adam D; Witkowski, Adam

2014-07-01

The widespread clinical application of coronary computed tomography angiography (CCTA) has resulted in increased referral patterns of patients with intermediate coronary stenoses to invasive coronary angiography. We evaluated the application of advanced quantitative coronary angiography (A-QCA) for predicting fractional flow reserve (FFR) in intermediate coronary lesions detected on CCTA. Fifty-six patients with 66 single intermediate coronary lesions (≥ 50% to 80% stenosis) on CCTA prospectively underwent coronary angiography and FFR. A-QCA including calculation of the Poiseuille-based index defined as the ratio of lesion length to the fourth power of the minimal lumen diameter (MLD) was performed. Significant stenosis was defined as FFR ≤ 0.80. The mean FFR was 0.86 ± 0.09, and 18 lesions (27%) were functionally significant. FFR correlated with lesion length (R=-0.303, P=0.013), MLD (R=0.527, P<0.001), diameter stenosis (R=-0.404, P=0.001), minimum lumen area (MLA) (R=0.530, P<0.001), lumen stenosis (R=-0.400, P=0.001), and Poiseuille-based index (R=-0.602, P<0.001). The optimal cutoff values for MLD, MLA, diameter stenosis, and lumen stenosis were ≤ 1.3 mm, ≤ 1.5 mm, >44%, and >69%, respectively (maximum negative predictive value of 94% for MLA, maximum positive predictive value of 58% for diameter stenosis). The Poiseuille-based index was the most accurate (C statistic 0.86, sensitivity 100%, specificity 71%, positive predictive value 56%, and negative predictive value 100%) predictor of FFR ≤ 0.80, but showed the lowest interobserver agreement (intraclass correlation coefficient 0.37). A-QCA might be used to rule out significant ischemia in intermediate stenoses detected by CCTA. The diagnostic application of the Poiseuille-based angiographic index is precluded by its high interobserver variability.

The distinct emotional flavor of Gnostic writings from the early Christian era.

PubMed

Whissell, Cynthia

2008-02-01

More than 500,000 scored words in 83 documents were used to conclude that it is possible to identify the source of documents (proto-orthodox Christian versus early Gnostic) on the basis of the emotions underlying the words. Twenty-seven New Testament works and seven Gnostic documents (including the gospels of Thomas, Judas, and Mary [Magdalene]) were scored with the Dictionary of Affect in Language. Patterns of emotional word use focusing on eight types of extreme emotional words were employed in a discriminant function analysis to predict source. Prediction was highly successful (canonical r = .81, 97% correct identification of source). When the discriminant function was tested with more than 30 additional Gnostic and Christian works including a variety of translations and some wisdom books, it correctly classified all of them. The majority of the predictive power of the function (97% of all correct categorizations, 70% of the canonical r2) was associated with the preferential presence of passive and passive/pleasant words in Gnostic documents.

A Risk Prediction Model for Sporadic CRC Based on Routine Lab Results.

PubMed

Boursi, Ben; Mamtani, Ronac; Hwang, Wei-Ting; Haynes, Kevin; Yang, Yu-Xiao

2016-07-01

Current risk scores for colorectal cancer (CRC) are based on demographic and behavioral factors and have limited predictive values. To develop a novel risk prediction model for sporadic CRC using clinical and laboratory data in electronic medical records. We conducted a nested case-control study in a UK primary care database. Cases included those with a diagnostic code of CRC, aged 50-85. Each case was matched with four controls using incidence density sampling. CRC predictors were examined using univariate conditional logistic regression. Variables with p value <0.25 in the univariate analysis were further evaluated in multivariate models using backward elimination. Discrimination was assessed using receiver operating curve. Calibration was evaluated using the McFadden's R2. Net reclassification index (NRI) associated with incorporation of laboratory results was calculated. Results were internally validated. A model similar to existing CRC prediction models which included age, sex, height, obesity, ever smoking, alcohol dependence, and previous screening colonoscopy had an AUC of 0.58 (0.57-0.59) with poor goodness of fit. A laboratory-based model including hematocrit, MCV, lymphocytes, and neutrophil-lymphocyte ratio (NLR) had an AUC of 0.76 (0.76-0.77) and a McFadden's R2 of 0.21 with a NRI of 47.6 %. A combined model including sex, hemoglobin, MCV, white blood cells, platelets, NLR, and oral hypoglycemic use had an AUC of 0.80 (0.79-0.81) with a McFadden's R2 of 0.27 and a NRI of 60.7 %. Similar results were shown in an internal validation set. A laboratory-based risk model had good predictive power for sporadic CRC risk.

Enhanced transdermal delivery of ondansetron using nanovesicular systems: Fabrication, characterization, optimization and ex-vivo permeation study-Box-Cox transformation practical example.

PubMed

Habib, Basant A; Sayed, Sinar; Elsayed, Ghada M

2018-03-30

This study aimed to formulate suitable nanovesicles (NVs) for transdermal delivery of Ondansetron. It also illustrated a practical example for the importance of Box-Cox transformation. A 2 3 full factorial design was used to enable testing transfersomes, ethosomes, and transethosomes of Ondansetron simultaneously. The independent variables (IVs) studied were sodium taurocholate amount, ethanol volume in hydration medium and sonication time. The studied dependent variables (DVs) were: particle size (PS), zeta potential (ZP) and entrapment efficiency (EE). Polynomial equations were used to study the influence of IVs on each DV. Numerical multiple response optimization was applied to select an optimized formula (OF) with the goals of minimizing PS and maximizing ZP absolute value and EE. Box-Cox transformation was adopted to enable modeling PS raised to the power of 1.2 with an excellent prediction R 2 of 1.000. ZP and EE were adequately represented directly with prediction R 2 of 0.9549 and 0.9892 respectively. Response surface plots helped in explaining the influence of IVs on each DV. Two-sided 95% prediction interval test and percent deviation of actual values from predicted ones proved the validity of the elucidated models. The OF was a transfersomal formula with desirability of 0.866 and showed promising results in ex-vivo permeation study. Copyright © 2018 Elsevier B.V. All rights reserved.

Predicting Successful Treatment Outcome of Web-Based Self-help for Problem Drinkers: Secondary Analysis From a Randomized Controlled Trial

PubMed Central

Kramer, Jeannet; Keuken, Max; Smit, Filip; Schippers, Gerard; Cuijpers, Pim

2008-01-01

Background Web-based self-help interventions for problem drinking are coming of age. They have shown promising results in terms of cost-effectiveness, and they offer opportunities to reach out on a broad scale to problem drinkers. The question now is whether certain groups of problem drinkers benefit more from such Web-based interventions than others. Objective We sought to identify baseline, client-related predictors of the effectiveness of Drinking Less, a 24/7, free-access, interactive, Web-based self-help intervention without therapist guidance for problem drinkers who want to reduce their alcohol consumption. The intervention is based on cognitive-behavioral and self-control principles. Methods We conducted secondary analysis of data from a pragmatic randomized trial with follow-up at 6 and 12 months. Participants (N = 261) were adult problem drinkers in the Dutch general population with a weekly alcohol consumption above 210 g of ethanol for men or 140 g for women, or consumption of at least 60 g (men) or 40 g (women) one or more days a week over the past 3 months. Six baseline participant characteristics were designated as putative predictors of treatment response: (1) gender, (2) education, (3) Internet use competence (sociodemographics), (4) mean weekly alcohol consumption, (5) prior professional help for alcohol problems (level of problem drinking), and (6) participants’ expectancies of Web-based interventions for problem drinking. Intention-to-treat (ITT) analyses, using last-observation-carried-forward (LOCF) data, and regression imputation (RI) were performed to deal with loss to follow-up. Statistical tests for interaction terms were conducted and linear regression analysis was performed to investigate whether the participants’ characteristics as measured at baseline predicted positive treatment responses at 6- and 12-month follow-ups. Results At 6 months, prior help for alcohol problems predicted a small, marginally significant positive treatment outcome in the RI model only (beta = .18, P = .05, R2 = .11). At 12 months, females displayed modest predictive power in both imputation models (LOCF: beta = .22, P = .045, R2 = .02; regression: beta = .27, P = .01, R2 = .03). Those with higher levels of education exhibited modest predictive power in the LOCF model only (beta = .33, P = .01, R2 = .03). Conclusions Although female and more highly educated users appeared slightly more likely to derive benefit from the Drinking Less intervention, none of the baseline characteristics we studied persuasively predicted a favorable treatment outcome. The Web-based intervention therefore seems well suited for a heterogeneous group of problem drinkers and could hence be offered as a first-step treatment in a stepped-care approach directed at problem drinkers in the general population. Trial Registration International Standard Randomized Controlled Trial Number (ISRCTN): 47285230; http://www.controlled-trials.com/isrctn47285230 (Archived by WebCite at http://www.webcitation.org/5cSR2sMkp). PMID:19033150

Predicting successful treatment outcome of web-based self-help for problem drinkers: secondary analysis from a randomized controlled trial.

PubMed

Riper, Heleen; Kramer, Jeannet; Keuken, Max; Smit, Filip; Schippers, Gerard; Cuijpers, Pim

2008-11-22

Web-based self-help interventions for problem drinking are coming of age. They have shown promising results in terms of cost-effectiveness, and they offer opportunities to reach out on a broad scale to problem drinkers. The question now is whether certain groups of problem drinkers benefit more from such Web-based interventions than others. We sought to identify baseline, client-related predictors of the effectiveness of Drinking Less, a 24/7, free-access, interactive, Web-based self-help intervention without therapist guidance for problem drinkers who want to reduce their alcohol consumption. The intervention is based on cognitive-behavioral and self-control principles. We conducted secondary analysis of data from a pragmatic randomized trial with follow-up at 6 and 12 months. Participants (N = 261) were adult problem drinkers in the Dutch general population with a weekly alcohol consumption above 210 g of ethanol for men or 140 g for women, or consumption of at least 60 g (men) or 40 g (women) one or more days a week over the past 3 months. Six baseline participant characteristics were designated as putative predictors of treatment response: (1) gender, (2) education, (3) Internet use competence (sociodemographics), (4) mean weekly alcohol consumption, (5) prior professional help for alcohol problems (level of problem drinking), and (6) participants' expectancies of Web-based interventions for problem drinking. Intention-to-treat (ITT) analyses, using last-observation-carried-forward (LOCF) data, and regression imputation (RI) were performed to deal with loss to follow-up. Statistical tests for interaction terms were conducted and linear regression analysis was performed to investigate whether the participants' characteristics as measured at baseline predicted positive treatment responses at 6- and 12-month follow-ups. At 6 months, prior help for alcohol problems predicted a small, marginally significant positive treatment outcome in the RI model only (beta = .18, P = .05, R(2) = .11). At 12 months, females displayed modest predictive power in both imputation models (LOCF: beta = .22, P = .045, R(2) = .02; regression: beta = .27, P = .01, R(2) = .03). Those with higher levels of education exhibited modest predictive power in the LOCF model only (beta = .33, P = .01, R(2) = .03). Although female and more highly educated users appeared slightly more likely to derive benefit from the Drinking Less intervention, none of the baseline characteristics we studied persuasively predicted a favorable treatment outcome. The Web-based intervention therefore seems well suited for a heterogeneous group of problem drinkers and could hence be offered as a first-step treatment in a stepped-care approach directed at problem drinkers in the general population. International Standard Randomized Controlled Trial Number (ISRCTN): 47285230; http://www.controlled-trials.com/isrctn47285230 (Archived by WebCite at http://www.webcitation.org/5cSR2sMkp).

Hurricane destructive power predictions based on historical storm and sea surface temperature data.

PubMed

Bogen, Kenneth T; Jones, Edwin D; Fischer, Larry E

2007-12-01

Forecasting destructive hurricane potential is complicated by substantial, unexplained intraannual variation in storm-specific power dissipation index (PDI, or integrated third power of wind speed), and interannual variation in annual accumulated PDI (APDI). A growing controversy concerns the recent hypothesis that the clearly positive trend in North Atlantic Ocean (NAO) sea surface temperature (SST) since 1970 explains increased hurricane intensities over this period, and so implies ominous PDI and APDI growth as global warming continues. To test this "SST hypothesis" and examine its quantitative implications, a combination of statistical and probabilistic methods were applied to National Hurricane Center HURDAT best-track data on NAO hurricanes during 1880-2002, and corresponding National Oceanographic and Atmospheric Administration Extended Reconstruction SST estimates. Notably, hurricane behavior was compared to corresponding hurricane-specific (i.e., spatiotemporally linked) SST; previous similar comparisons considered only SST averaged over large NAO regions. Contrary to the SST hypothesis, SST was found to vary in a monthly pattern inconsistent with that of corresponding PDI, and to be at best weakly associated with PDI or APDI despite strong correlation with corresponding mean latitude (R(2)= 0.55) or with combined mean location and a approximately 90-year periodic trend (R(2)= 0.70). Over the last century, the lower 75% of APDIs appear randomly sampled from a nearly uniform distribution, and the upper 25% of APDIs from a nearly lognormal distribution. From the latter distribution, a baseline (SST-independent) stochastic model was derived predicting that over the next half century, APDI will not likely exceed its maximum value over the last half century by more than a factor of 1.5. This factor increased to 2 using a baseline model modified to assume SST-dependence conditioned on an upper bound of the increasing NAO SST trend observed since 1970. An additional model was developed that predicts PDI statistics conditional on APDI. These PDI and APDI models can be used to estimate upper bounds on indices of hurricane power likely to be realized over the next century, under divergent assumptions regarding SST influence.

Multipolar radiofrequency ablation with internally cooled electrodes: experimental study in ex vivo bovine liver with mathematic modeling.

PubMed

Clasen, Stephan; Schmidt, Diethard; Boss, Andreas; Dietz, Klaus; Kröber, Stefan M; Claussen, Claus D; Pereira, Philippe L

2006-03-01

To evaluate the size and geometry of thermally induced coagulation by using multipolar radiofrequency (RF) ablation and to determine a mathematic model to predict coagulation volume. Multipolar RF ablations (n = 80) were performed in ex vivo bovine livers by using three internally cooled bipolar applicators with two electrodes on the same shaft. Applicators were placed in a triangular array (spacing, 2-5 cm) and were activated in multipolar mode (power output, 75-225 W). The size and geometry of the coagulation zone, together with ablation time, were assessed. Mathematic functions were fitted, and the goodness of fit was assessed by using r(2). Coagulation volume, short-axis diameter, and ablation time were dependent on power output and applicator distance. The maximum zone of coagulation (volume, 324 cm(3); short-axis diameter, 8.4 cm; ablation time, 193 min) was induced with a power output of 75 W at an applicator distance of 5 cm. Coagulation volume and ablation time decreased as power output increased. Power outputs of 100-125 W at applicator distances of 2-4 cm led to a reasonable compromise between coagulation volume and ablation time. At 2 cm (100 W), coagulation volume, short-axis diameter, and ablation time were 66 cm(3), 4.5 cm, and 19 min, respectively; at 3 cm (100 W), 90 cm(3), 5.2 cm, and 22 min, respectively; at 4 cm (100 W), 132 cm(3), 6.1 cm, and 27 min, respectively; at 2 cm (125 W), 56 cm(3), 4.2 cm, and 9 min, respectively; at 3 cm (125 W), 73 cm(3), 4.9 cm, and 12 min, respectively; and at 4 cm (125 W), 103 cm(3), 5.5 cm, and 16 min, respectively. At applicator distances of 4 cm (>125 W) and 5 cm (>100 W), the zones of coagulation were not confluent. Coagulation volume (r(2) = 0.80) and RF ablation time (r(2) = 0.93) were determined by using the mathematic model. Multipolar RF ablation with three bipolar applicators may produce large volumes of confluent coagulation ex vivo. A compromise is necessary between prolonged RF ablations at lower power outputs, which produce larger volumes of coagulation, and faster RF ablations at higher power outputs, which produce smaller volumes of coagulation. Copyright RSNA, 2006.

Statistical models to predict type 2 diabetes remission after bariatric surgery.

PubMed

Ramos-Levi, Ana M; Matia, Pilar; Cabrerizo, Lucio; Barabash, Ana; Sanchez-Pernaute, Andres; Calle-Pascual, Alfonso L; Torres, Antonio J; Rubio, Miguel A

2014-09-01

Type 2 diabetes (T2D) remission may be achieved after bariatric surgery (BS), but rates vary according to patients' baseline characteristics. The present study evaluates the relevance of several preoperative factors and develops statistical models to predict T2D remission 1 year after BS. We retrospectively studied 141 patients (57.4% women), with a preoperative diagnosis of T2D, who underwent BS in a single center (2006-2011). Anthropometric and glucose metabolism parameters before surgery and at 1-year follow-up were recorded. Remission of T2D was defined according to consensus criteria: HbA1c <6%, fasting glucose (FG) <100 mg/dL, absence of pharmacologic treatment. The influence of several preoperative factors was explored and different statistical models to predict T2D remission were elaborated using logistic regression analysis. Three preoperative characteristics considered individually were identified as the most powerful predictors of T2D remission: C-peptide (R2  = 0.249; odds ratio [OR] 1.652, 95% confidence interval [CI] 1.181-2.309; P = 0.003), T2D duration (R2  = 0.197; OR 0.869, 95% CI 0.808-0.935; P < 0.001), and previous insulin therapy (R2  = 0.165; OR 4.670, 95% CI 2.257-9.665; P < 0.001). High C-peptide levels, a shorter duration of T2D, and the absence of insulin therapy favored remission. Different multivariate logistic regression models were designed. When considering sex, T2D duration, and insulin treatment, remission was correctly predicted in 72.4% of cases. The model that included age, FG and C-peptide levels resulted in 83.7% correct classifications. When sex, FG, C-peptide, insulin treatment, and percentage weight loss were considered, correct classification of T2D remission was achieved in 95.9% of cases. Preoperative characteristics determine T2D remission rates after BS to different extents. The use of statistical models may help clinicians reliably predict T2D remission rates after BS. © 2014 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and Wiley Publishing Asia Pty Ltd.

Determination of Aerobic Power Through a Specific Test for Taekwondo - A Predictive Equation Model

PubMed Central

Louro, Hugo; Matias, Ricardo; Brito, João; Costa, Aldo M.

2016-01-01

Abstract Our aim was to verify the concurrent validity of a maximal taekwondo specific test (TST) to predict VO2max through an explanatory model. Seventeen elite male taekwondo athletes (age: 17.59 ± 4.34 years; body height: 1.72 ± 6.5 m; body mass: 61.3 ± 8.7 kg) performed two graded maximal exercise tests on different days: a 20 m multistage shuttle run test (SRT) and an incremental TST. We recorded test time, VO2max, ventilation, a heart rate and time to exhaustion. Significant differences were found between observed and estimated VO2max values [F (2, 16) = 5.77, p < 0.01]; post-hoc subgroup analysis revealed the existence of significant differences (p = 0.04) between the estimated VO2max value in the SRT and the observed value recorded in the TST (58.4 ± 6.4 ml/kg/min and 52.6 ± 5.2 ml/kg/min, respectively). Our analysis also revealed a moderate correlation between both testing protocols regarding VO2max (r = 0.70; p = 0.005), test time (r = 0.77; p = 0.02) and ventilation (r = 0.69; p = 0.03). There was no proportional bias in the mean difference (t = -1.04; p = 0.313), and there was a level of agreement between both tests. An equation/model was used to estimate VO2max during the TST based on the mean heart rate, test time, body height and mass, which explained 74.3% of the observed VO2max variability. A moderate correlation was found between the observed and predicted VO2max values in the taekwondo TST (r = 0.74, p = 0.001). Our results suggest that an incremental specific test estimates VO2max of elite taekwondo athletes with acceptable concurrent validity. PMID:28149417

Interaction between platelet-derived microRNAs and CYP2C19*2 genotype on clopidogrel antiplatelet responsiveness in patients with ACS.

PubMed

Peng, Li; Liu, Jun; Qin, Liuan; Liu, Jia; Xi, Shaozhi; Lu, Caiyi; Yin, Tong

2017-09-01

Both platelet-derived microRNAs and the genotype of CYP2C19*2 were implicated for the variability of clopidogrel antiplatelet responsiveness. However, their interaction on the antiplatelet responsiveness of clopidogrel in patients with acute coronary syndrome (ACS) remains unknown. Consecutive clopidogrel-treated patients with ACS were recruited, with their antiplatelet responsiveness evaluated by the relative platelet inhibition (RI), as measured by light transmittance aggregometry (LTA) at baseline and 5days' after the maintenance treatment of clopidogrel. Extreme cases were selected according to the octiles of RI value. Expression of the microRNAs targeting the mRNAs of P2RY12 was analyzed in the platelet of the extreme cases. Genotyping of CYP2C19*2 was performed for each extreme case. Among the included 272 ACS patients, 21 cases were screened as the extremely high-responders with RI>84%, and 18 as the extremely low-responders with RI<10%. Bioinformatics tools predicted the candidate microRNAs of miR-223, miR-221, and miR-21 could bind directly to the mRNA of P2RY12. Compared with the extremely low-responders, the expression of miR-223, miR-221, and miR-21 was significantly higher in the extremely high-responders (miR-223: 7.18±2.95 vs. 0.99±0.64, p=0.022; miR-221: 3.60±2.54 vs. 1.14±0.81, p=0.004; miR-21: 4.36±3.33 vs. 2.31±1.69, p=0.01). ROC curve showed ideal discriminatory power of the platelet-derived miRNAs for the prediction of clopidogrel antiplatelet responsiveness (c-index=0.70 for miR-223; c-index=0.76 for miR-221; c-index=0.79 for miR-21). After stratified by the carrier status of CYP2C19*2, the association between platelet-derived miRNAs and clopidogrel antiplatelet responsiveness could be found only in CYP2C19*2 carriers, but not in non-carriers. Platelet-derived miRNAs (miR-223, miR-221 and miR-21) are independently associated with clopidogrel antiplatelet responsiveness in ACS patients. However, the association could be influenced by the interaction with CYP2C19*2 genotype. Copyright © 2017 Elsevier Ltd. All rights reserved.

Influence of performance level on anaerobic power and body composition in elite male judoists.

PubMed

Kim, Jongkyu; Cho, Hyun-Chul; Jung, Han-Sang; Yoon, Jong-Dae

2011-05-01

This study examined the relationship between 30-second anaerobic power and body composition by performance level in elite Judoists. During a 3-month period, 10 male Korean Judo national team athletes (NT), 26 male university varsity team athletes (VT), and 28 male junior varsity team athletes (JT) were assessed for 30-second anaerobic power and body composition at the Youngin University. Anaerobic power was measured using a 30-second Wingate test. Body composition was assessed via bioelectric impedance analysis in standardized conditions using BioSpace (Korean)-specific prediction formulas. All testing occurred at the beginning of the winter nonseason period but excluded a brief weight-loss period before the competition phase. Anaerobic power measures were significantly greater (p < 0.05) in NT and VT than in JT. Fat-free mass (FFM), muscle mass (MM), and total body water in JT were also greater than in VT and JT (p < 0.05). Muscle mass in VT was significantly lower than in NT (p < 0.05). Fat-free mass in NT was strongly correlated to mean and peak anaerobic power (r = 0.77, p = 0.009; r = 0.87, p < 0.001, respectively). Varsity team athletes also indicated a moderate association between FFM and peak and mean anaerobic power (r = 0.63, p < 0.001; r = 0.48, p = 0.013, respectively). However, relationship between FFM and anaerobic power was not statistically significantly correlated in JT (r = 0.14, p = 0.470; r = 0.23, p = 0.232, separately). In conclusion, our data indicated that anaerobic power is closely correlated with increase in FFM and MM and was different dependent among performance levels. Further research in the field is warranted to elucidate the Judo-specific relationship between FFM and performance.

Advanced Ultra-Violet (UV) Aircraft Fire Detection System. Volume 2. System Hardware Design, Software Design, and Test

DTIC Science & Technology

1982-08-01

REPORT SHT",, -ENGLAND A W*nson Match Company Saftey and Protion Division ISSUE " 3 (contd) HEADS 1 2 3 4 5 6 7 8 ,7 0 BITS iii ii The 832 tm inspection...input data buffering and output data buffering. 2.2.2.3.1. Power up, Reset Circuit To ensure correct system operation when power is first applied the...act in conjunction with R2, R3 and two buffer sections of IC2. When power is first applied , Cl is discharged, Via the pot chain divider of R2 and R3 the

“Slimming” of power-law tails by increasing market returns

NASA Astrophysics Data System (ADS)

Sornette, D.

2002-06-01

We introduce a simple generalization of rational bubble models which removes the fundamental problem discovered by Lux and Sornette (J. Money, Credit and Banking, preprint at http://xxx.lanl.gov/abs/cond-mat/9910141) that the distribution of returns is a power law with exponent <1, in contradiction with empirical data. The idea is that the price fluctuations associated with bubbles must on average grow with the mean market return r. When r is larger than the discount rate rδ, the distribution of returns of the observable price, sum of the bubble component and of the fundamental price, exhibits an intermediate tail with an exponent which can be larger than 1. This regime r> rδ corresponds to a generalization of the rational bubble model in which the fundamental price is no more given by the discounted value of future dividends. We explain how this is possible. Our model predicts that, the higher is the market remuneration r above the discount rate, the larger is the power-law exponent and thus the thinner is the tail of the distribution of price returns.

Estimating carcass fat and protein in northern pintails during the nonbreeding season

USGS Publications Warehouse

Miller, M.R.

1989-01-01

I used northern pintails (Anas acuta) collected from August through March 1979-82 in the Sacramento Valley, California to derive equations to predict ether-extracted carcass fat, carcass protein, and skeletal lean dry weight. Ether-extracted carcass fat was best predicted by total fat depot weight (wet skin, abdominal fat, and intestinal fat) (r2 = 0.94) and estimates based on carcass water content (r2 = 0.93-0.98). Measured carcass protein was best predicted by a multiple regression including total protein depot weight (breast muscles, leg muscles, and gizzard) and tarsus length (R2 = 0.79). I predicted skeletal lean dry weight by a multiple regression incorporating culmen, tarsus, and wing length (R2 = 0.77). Predicted carcass fat agreed well with measured carcass fat in an independent data set of 30 pintails using total fat depot (r2 = 0.92-0.96) and carcass water (r2 = 0.97-0.99), but predicted carcass protein agreed less well with measured protein.

A comparison of performance of several artificial intelligence methods for predicting the dynamic viscosity of TiO2/SAE 50 nano-lubricant

NASA Astrophysics Data System (ADS)

Hemmat Esfe, Mohammad; Tatar, Afshin; Ahangar, Mohammad Reza Hassani; Rostamian, Hossein

2018-02-01

Since the conventional thermal fluids such as water, oil, and ethylene glycol have poor thermal properties, the tiny solid particles are added to these fluids to increase their heat transfer improvement. As viscosity determines the rheological behavior of a fluid, studying the parameters affecting the viscosity is crucial. Since the experimental measurement of viscosity is expensive and time consuming, predicting this parameter is the apt method. In this work, three artificial intelligence methods containing Genetic Algorithm-Radial Basis Function Neural Networks (GA-RBF), Least Square Support Vector Machine (LS-SVM) and Gene Expression Programming (GEP) were applied to predict the viscosity of TiO2/SAE 50 nano-lubricant with Non-Newtonian power-law behavior using experimental data. The correlation factor (R2), Average Absolute Relative Deviation (AARD), Root Mean Square Error (RMSE), and Margin of Deviation were employed to investigate the accuracy of the proposed models. RMSE values of 0.58, 1.28, and 6.59 and R2 values of 0.99998, 0.99991, and 0.99777 reveal the accuracy of the proposed models for respective GA-RBF, CSA-LSSVM, and GEP methods. Among the developed models, the GA-RBF shows the best accuracy.

Universal scaling relations in scale-free structure formation

NASA Astrophysics Data System (ADS)

Guszejnov, Dávid; Hopkins, Philip F.; Grudić, Michael Y.

2018-07-01

A large number of astronomical phenomena exhibit remarkably similar scaling relations. The most well-known of these is the mass distribution dN/dM ∝ M-2 which (to first order) describes stars, protostellar cores, clumps, giant molecular clouds, star clusters, and even dark matter haloes. In this paper we propose that this ubiquity is not a coincidence and that it is the generic result of scale-free structure formation where the different scales are uncorrelated. We show that all such systems produce a mass function proportional to M-2 and a column density distribution with a power-law tail of dA/dln Σ ∝ Σ-1. In the case where structure formation is controlled by gravity the two-point correlation becomes ξ2D ∝ R-1. Furthermore, structures formed by such processes (e.g. young star clusters, DM haloes) tend to a ρ ∝ R-3 density profile. We compare these predictions with observations, analytical fragmentation cascade models, semi-analytical models of gravito-turbulent fragmentation, and detailed `full physics' hydrodynamical simulations. We find that these power laws are good first-order descriptions in all cases.

Universal Scaling Relations in Scale-Free Structure Formation

NASA Astrophysics Data System (ADS)

Guszejnov, Dávid; Hopkins, Philip F.; Grudić, Michael Y.

2018-04-01

A large number of astronomical phenomena exhibit remarkably similar scaling relations. The most well-known of these is the mass distribution dN/dM∝M-2 which (to first order) describes stars, protostellar cores, clumps, giant molecular clouds, star clusters and even dark matter halos. In this paper we propose that this ubiquity is not a coincidence and that it is the generic result of scale-free structure formation where the different scales are uncorrelated. We show that all such systems produce a mass function proportional to M-2 and a column density distribution with a power law tail of dA/d lnΣ∝Σ-1. In the case where structure formation is controlled by gravity the two-point correlation becomes ξ2D∝R-1. Furthermore, structures formed by such processes (e.g. young star clusters, DM halos) tend to a ρ∝R-3 density profile. We compare these predictions with observations, analytical fragmentation cascade models, semi-analytical models of gravito-turbulent fragmentation and detailed "full physics" hydrodynamical simulations. We find that these power-laws are good first order descriptions in all cases.

Electrically tunable transport and high-frequency dynamics in antiferromagnetic S r3I r2O7

NASA Astrophysics Data System (ADS)

Seinige, Heidi; Williamson, Morgan; Shen, Shida; Wang, Cheng; Cao, Gang; Zhou, Jianshi; Goodenough, John B.; Tsoi, Maxim

2016-12-01

We report dc and high-frequency transport properties of antiferromagnetic S r3I r2O7 . Temperature-dependent resistivity measurements show that the activation energy of this material can be tuned by an applied dc electrical bias. The latter allows for continuous variations in the sample resistivity of as much as 50% followed by a reversible resistive switching at higher biases. Such a switching is of high interest for antiferromagnetic applications in high-speed memory devices. Interestingly, we found the switching behavior to be strongly affected by a high-frequency (microwave) current applied to the sample. The microwaves at 3-7 GHz suppress the dc switching and produce resonancelike features that we tentatively associated with the dissipationless magnonics recently predicted to occur in antiferromagnetic insulators subject to ac electric fields. We have characterized the effects of microwave irradiation on electronic transport in S r3I r2O7 as a function of microwave frequency and power, strength and direction of external magnetic field, strength and polarity of applied dc bias, and temperature. Our observations support the potential of antiferromagnetic materials for high-speed/high-frequency spintronic applications.

SOVRaD - A Digest of Recent Soviet R and D Articles. Volume 2, Number 2, 1976

DTIC Science & Technology

1976-02-01

34""" ■■■I"" ^"■’ " """"^ R-F Heating of Sporadic E-Layer (abstract) Effects of ionospheric heating by powerful r-f emission on the sporadic E-layers are...situation is just the reverse. Here heating by powerful r-f fields decreases its electron density and increases its thickness. At mean latitudes...T - 2, it decreases by 18% [Ignat’yev, Yu. A. Effect on the sporadic E-layer of ionospheric heating by powerful r-f emission. IVUZ

2D-QSAR study, molecular docking, and molecular dynamics simulation studies of interaction mechanism between inhibitors and transforming growth factor-beta receptor I (ALK5).

PubMed

Jiang, Meng-Nan; Zhou, Xiao-Ping; Sun, Dong-Ru; Gao, Huan; Zheng, Qing-Chuan; Zhang, Hong-Xing; Liang, Di

2017-11-06

Transforming growth factor type 1 receptor (ALK5) is kinase associated with a wide variety of pathological processes, and inhibition of ALK5 is a good strategy to treat many kinds of cancer and fibrotic diseases. Recently, a series of compounds have been synthesized as ALK5 inhibitors. However, the study of their selectivity against other potential targets remains elusive. In this research, a data-set of ALK5 inhibitors were collected and studied based on the combination of 2D-QSAR, molecular docking and molecular dynamics simulation. The quality of QSAR models were assessed statistically by F, R 2 , and R 2 ADJ , proved to be credible. The cross-validations for the models (q 2 LOO  = 0.571 and 0.629, respectively) showed their robustness, while the external validations (r 2 test  = 0.703 and 0.764, respectively) showed their predictive power. Besides, the predicted binding free energy results calculated by MM/GBSA method were in accordance with the experimental data, and the van der Waals energy term was the factor that had the most significant impact on ligand binding. What is more, several important residues were found to significantly affect the binding affinity. Finally, based on our analyses above, a proposed series of molecules were designed.

Assessment of nonlethal methods for predicting muscle tissue mercury concentrations in coastal marine fishes.

PubMed

Piraino, Maria N; Taylor, David L

2013-11-01

Caudal fin clips and dorsolateral scales were analyzed as a potential nonlethal approach for predicting muscle tissue mercury (Hg) concentrations in marine fish. Target fish were collected from the Narragansett Bay (Rhode Island, USA) and included black sea bass Centropristis striata [n = 54, 14-55 cm total length (TL)], bluefish Pomatomus saltatrix (n = 113, 31-73 cm TL), striped bass Morone saxatilis (n = 40, 34-102 cm TL), summer flounder Paralichthys dentatus (n = 64, 18-55 cm TL), and tautog Tautoga onitis (n = 102, 27-61 cm TL). For all fish species, Hg concentrations were greatest in muscle tissue [mean muscle Hg = 0.47-1.18 mg/kg dry weight (dw)] followed by fin clips (0.03-0.09 mg/kg dw) and scales (0.01-0.07 mg/kg dw). The coefficient of determination (R (2)) derived from power regressions of intraspecies muscle Hg against fin and scale Hg ranged between 0.35 and 0.78 (mean R (2) = 0.57) and 0.14-0.37 (mean R (2) = 0.30), respectively. The inclusion of fish body size interaction effects in the regression models improved the predictive ability of fins (R (2) = 0.63-0.80; mean = 0.71) and scales (R (2) = 0.33-0.71; mean = 0.53). According to the high level of uncertainty within the regression models (R (2) values) and confidence interval widths, scale analysis was deemed an ineffective tool for estimating muscle tissue Hg concentrations in the target species. In contrast, the examination of fin clips as predictors of muscle Hg had value as a cursory screening tool; however, this method should not be the foundation for developing human consumption advisories. It is also noteworthy that the efficacy of these nonlethal techniques was highly variable across fishes and likely depends on species-specific life-history characteristics.

46. LONGITUDINAL SECTION POWER HOUSE S.A.R. NO. 2, EDISON ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

46. LONGITUDINAL SECTION - POWER HOUSE S.A.R. NO. 2, EDISON PROJECT, APR. 30, 1945. SCE drawing no. 523198 (sheet no. 8; for filing with Federal Power Commission). - Santa Ana River Hydroelectric System, SAR-2 Powerhouse, Redlands, San Bernardino County, CA

Do Cognitive Models Help in Predicting the Severity of Posttraumatic Stress Disorder, Phobia, and Depression After Motor Vehicle Accidents? A Prospective Longitudinal Study

PubMed Central

Ehring, Thomas; Ehlers, Anke; Glucksman, Edward

2008-01-01

The study investigated the power of theoretically derived cognitive variables to predict posttraumatic stress disorder (PTSD), travel phobia, and depression following injury in a motor vehicle accident (MVA). MVA survivors (N = 147) were assessed at the emergency department on the day of their accident and 2 weeks, 1 month, 3 months, and 6 months later. Diagnoses were established with the Structured Clinical Interview for DSM–IV. Predictors included initial symptom severities; variables established as predictors of PTSD in E. J. Ozer, S. R. Best, T. L. Lipsey, and D. S. Weiss's (2003) meta-analysis; and variables derived from cognitive models of PTSD, phobia, and depression. Results of nonparametric multiple regression analyses showed that the cognitive variables predicted subsequent PTSD and depression severities over and above what could be predicted from initial symptom levels. They also showed greater predictive power than the established predictors, although the latter showed similar effect sizes as in the meta-analysis. In addition, the predictors derived from cognitive models of PTSD and depression were disorder-specific. The results support the role of cognitive factors in the maintenance of emotional disorders following trauma. PMID:18377119

Vagal modulation and symptomatology following a 6-month aerobic exercise program for women with fibromyalgia.

PubMed

Sañudo, Borja; Carrasco, Luis; de Hoyo, Moisés; Figueroa, Arturo; Saxton, John M

2015-01-01

To examine the effects of a supervised aerobic exercise programme on heart rate variability (HRV) parameters and symptom severity in women with fibromyalgia (FM). Thirty-two women with FM were randomly allocated to one of two groups: aerobic exercise (AE) or usual care control for 24 weeks. Women allocated to AE performed two aerobic exercise sessions per week of 45-60 min duration including 15-20 min of steady-state aerobic exercise at 60-65% of predicted maximum heart rate (HRmax) and 15 min of interval training at 75-80% HRmax (six repetitions of 1.5 min, with 1 min interpolated rest intervals). Cardiac autonomic modulation was assessed using power spectral analysis of HRV. Symptom severity was assessed by a 10 cm visual analogue scale (VAS) for pain, sleep disturbances, stiffness, anxiety and depression. After 24 weeks, the women in the exercise group showed an increase (4.8 ± 0.2 to 5.2 ± 0.2) in total power (LnTP, p<0.001), low frequency power (LnLF, p<0.01), high frequency power (LnHF, p<0.001), and the root-mean-square of successive R-R intervals (rMSSD, p<0.001). In addition, significant group-by-time interaction effects were observed for LnHF (p=0.036) and LnLF/HF (p=0.014). Improvements in anxiety and depression were also observed in AE versus control patients. These results show that a programme of aerobic exercise training induced changes in cardiac autonomic nervous system modulation in FM and that these changes in HRV parameters were accompanied by changes in anxiety and depression.

Validity of the Myotest® in measuring force and power production in the squat and bench press.

PubMed

Comstock, Brett A; Solomon-Hill, Glenn; Flanagan, Shawn D; Earp, Jacob E; Luk, Hui-Ying; Dobbins, Kathryn A; Dunn-Lewis, Courtenay; Fragala, Maren S; Ho, Jen-Yu; Hatfield, Disa L; Vingren, Jakob L; Denegar, Craig R; Volek, Jeff S; Kupchak, Brian R; Maresh, Carl M; Kraemer, William J

2011-08-01

The purpose of this study was to verify the concurrent validity of a bar-mounted Myotest® instrument in measuring the force and power production in the squat and bench press exercises when compared to the gold standard of a computerized linear transducer and force platform system. Fifty-four men (bench press: 39-171 kg; squat: 75-221 kg) and 43 women (bench press: 18-80 kg; squat: 30-115 kg) (age range 18-30 years) performed a 1 repetition maximum (1RM) strength test in bench press and squat exercises. Power testing consisted of the jump squat and the bench throw at 30% of each subject's 1RM. During each measurement, both the Myotest® instrument and the Celesco linear transducer of the directly interfaced BMS system (Ballistic Measurement System [BMS] Innervations Inc, Fitness Technology force plate, Skye, South Australia, Australia) were mounted to the weight bar. A strong, positive correlation (r) between the Myotest and BMS systems and a high correlation of determination (R2) was demonstrated for bench throw force (r = 0.95, p < 0.05) (R2 = 0.92); bench throw power (r = 0.96, p < 0.05) (R2 = 0.93); squat jump force (r = 0.98, p < 0.05) (R2 = 0.97); and squat jump power (r = 0.91, p < 0.05) (R2 = 0.82). In conclusion, when fixed on the bar in the vertical axis, the Myotest is a valid field instrument for measuring force and power in commonly used exercise movements.

Predicting energy expenditure through hand rim propulsion power output in individuals who use wheelchairs.

PubMed

Conger, Scott A; Scott, Stacy N; Bassett, David R

2014-07-01

To examine the relationship between hand rim propulsion power and energy expenditure (EE) during wheelchair wheeling and to investigate whether adding other variables to the model could improve on the prediction of EE. Individuals who use manual wheelchairs (n=14) performed five different wheeling activities in a wheelchair with a PowerTap power meter hub built into the right rear wheel. Activities included wheeling on a smooth, level surface at three different speeds (4.5, 5.5 and 6.5 km/h), wheeling on a rubberised track at one speed (5.5 km/h) and wheeling on a sidewalk course that included uphill and downhill segments at a self-selected speed. EE was measured using a portable indirect calorimetry system. Stepwise linear regression was performed to predict EE from power output variables. A repeated-measures analysis of variance was used to compare the measured EE to the estimates from the power models. Bland-Altman plots were used to assess the agreement between the criterion values and the predicted values. EE and power were significantly correlated (r=0.694, p<0.001). Regression analysis yielded three significant prediction models utilising measured power; measured power and speed; and measured power, speed and heart rate. No significant differences were found between measured EE and any of the prediction models. EE can be accurately and precisely estimated based on hand rim propulsion power. These results indicate that power could be used as a method to assess EE in individuals who use wheelchairs. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Firmness prediction in Prunus persica 'Calrico' peaches by visible/short-wave near infrared spectroscopy and acoustic measurements using optimised linear and non-linear chemometric models.

PubMed

Lafuente, Victoria; Herrera, Luis J; Pérez, María del Mar; Val, Jesús; Negueruela, Ignacio

2015-08-15

In this work, near infrared spectroscopy (NIR) and an acoustic measure (AWETA) (two non-destructive methods) were applied in Prunus persica fruit 'Calrico' (n = 260) to predict Magness-Taylor (MT) firmness. Separate and combined use of these measures was evaluated and compared using partial least squares (PLS) and least squares support vector machine (LS-SVM) regression methods. Also, a mutual-information-based variable selection method, seeking to find the most significant variables to produce optimal accuracy of the regression models, was applied to a joint set of variables (NIR wavelengths and AWETA measure). The newly proposed combined NIR-AWETA model gave good values of the determination coefficient (R(2)) for PLS and LS-SVM methods (0.77 and 0.78, respectively), improving the reliability of MT firmness prediction in comparison with separate NIR and AWETA predictions. The three variables selected by the variable selection method (AWETA measure plus NIR wavelengths 675 and 697 nm) achieved R(2) values 0.76 and 0.77, PLS and LS-SVM. These results indicated that the proposed mutual-information-based variable selection algorithm was a powerful tool for the selection of the most relevant variables. © 2014 Society of Chemical Industry.

Occurrence of exact R 2 inflation in non-local UV-complete gravity

NASA Astrophysics Data System (ADS)

Koshelev, Alexey S.; Modesto, Leonardo; Rachwal, Leslaw; Starobinsky, Alexei A.

2016-11-01

The R + R 2, shortly named " R 2" ("Starobinsky") inflationary model, represents a fully consistent example of a one-parameter inflationary scenario. This model has a "graceful exit" from inflation and provides a mechanism for subsequent creation and final thermalization of the standard matter. Moreover, it produces a very good fit of the observed spectrum of primordial perturbations. In the present paper we show explicitly that the R 2 inflationary spacetime is an exact solution of a range of weakly non-local (quasi-polynomial) gravitational theories, which provide an ultraviolet completion of the R 2 theory. These theories are ghost-free, super-renormalizable or finite at quantum level, and perturbatively unitary. Their spectrum consists of the graviton and the scalaron that is responsible for driving the inflation. Notably, any further extension of the spectrum leads to propagating ghost degrees of freedom. We are aimed at presenting a detailed construction of such theories in the so called Weyl basis. Further, we give a special account to the cosmological implications of this theory by considering perturbations during inflation. The highlight of the non-local model is the prediction of a modified, in comparison to a local R 2 model, value for the ratio of tensor and scalar power spectra r, depending on the parameters of the theory. The relevant parameters are under control to be successfully confronted with existing observational data. Furthermore, the modified r can surely meet future observational constraints.

Influence of physical development on start and countermovement jump performance in adolescent sprint athletes.

PubMed

Aerenhouts, D; Debaere, S; Hagman, F; Van Gheluwe, B; Delecluse, C; Clarys, P

2013-02-01

The aim of the present study was to describe the effect of physical changes during adolescence on sprint start and countermovement jump (CMJ) performance. Twenty-eight girls and 25 boys (15.0±1.6 and 14.7±1.9 years at start respectively) were measured twice with a one year interval. Anthropometric data allowed skeletal muscle mass (SMM) estimation. Athletes performed a 10m sprint tracked from behind by a laser sensor, with starting blocks measuring propulsion forces. CMJ's were performed on a Kistler force plate. Between the two measurement occasions both genders increased in body height, weight and SMM. In girls and boys, impulse during the push-off, block leaving velocity and times at 5 and 10 m improved significantly. In both genders CMJ absolute power increased but not power.kg-1. Only in boys a higher CMJ was registered on occasion 2. For both genders on both occasions, impulse during the push-off correlated with body weight, SMM and CMJ power (r from .46 to .84), and in boys also with CMJ height and CMJ power.kg-1 (r from 0.43 to 0.76). Boys showed CMJ height and power to correlate with 5 and 10 m times (r from -0.42 to -0.79) and with block leaving velocity, however only on the first data collection (r=0.61 and 0.59, respectively). Sprint start performance is only partly related to muscular development and CMJ could predict start performance in boys only. Sprint start and CMJ rely on technical skills and, therefore, increasing muscularity should be accompanied with sufficient specific training to allow an optimal transfer to start performance.

Two-field analysis of no-scale supergravity inflation

DOE PAGES

Ellis, John; Garcia, Marcos A. G.; Nanopoulos, Dimitri V.; ...

2015-01-08

Since the building-blocks of supersymmetric models include chiral superfields containing pairs of effective scalar fields, a two-field approach is particularly appropriate for models of inflation based on supergravity. In this paper, we generalize the two-field analysis of the inflationary power spectrum to supergravity models with arbitrary Kähler potential. We show how two-field effects in the context of no-scale supergravity can alter the model predictions for the scalar spectral index n s and the tensor-to-scalar ratio r, yielding results that interpolate between the Planck-friendly Starobinsky model and BICEP2-friendly predictions. In particular, we show that two-field effects in a chaotic no-scale inflationmore » model with a quadratic potential are capable of reducing r to very small values << 0.1. Here, we also calculate the non-Gaussianity measure f NL, finding that is well below the current experimental sensitivity.« less

Systematic feature selection improves accuracy of methylation-based forensic age estimation in Han Chinese males.

PubMed

Feng, Lei; Peng, Fuduan; Li, Shanfei; Jiang, Li; Sun, Hui; Ji, Anquan; Zeng, Changqing; Li, Caixia; Liu, Fan

2018-03-23

Estimating individual age from biomarkers may provide key information facilitating forensic investigations. Recent progress has shown DNA methylation at age-associated CpG sites as the most informative biomarkers for estimating the individual age of an unknown donor. Optimal feature selection plays a critical role in determining the performance of the final prediction model. In this study we investigate methylation levels at 153 age-associated CpG sites from 21 previously reported genomic regions using the EpiTYPER system for their predictive power on individual age in 390 Han Chinese males ranging from 15 to 75 years of age. We conducted a systematic feature selection using a stepwise backward multiple linear regression analysis as well as an exhaustive searching algorithm. Both approaches identified the same subset of 9 CpG sites, which in linear combination provided the optimal model fitting with mean absolute deviation (MAD) of 2.89 years of age and explainable variance (R 2 ) of 0.92. The final model was validated in two independent Han Chinese male samples (validation set 1, N = 65, MAD = 2.49, R 2  = 0.95, and validation set 2, N = 62, MAD = 3.36, R 2  = 0.89). Other competing models such as support vector machine and artificial neural network did not outperform the linear model to any noticeable degree. The validation set 1 was additionally analyzed using Pyrosequencing technology for cross-platform validation and was termed as validation set 3. Directly applying our model, in which the methylation levels were detected by the EpiTYPER system, to the data from pyrosequencing technology showed, however, less accurate results in terms of MAD (validation set 3, N = 65 Han Chinese males, MAD = 4.20, R 2  = 0.93), suggesting the presence of a batch effect between different data generation platforms. This batch effect could be partially overcome by a z-score transformation (MAD = 2.76, R 2  = 0.93). Overall, our systematic feature selection identified 9 CpG sites as the optimal subset for forensic age estimation and the prediction model consisting of these 9 markers demonstrated high potential in forensic practice. An age estimator implementing our prediction model allowing missing markers is freely available at http://liufan.big.ac.cn/AgePrediction. Copyright © 2018 Elsevier B.V. All rights reserved.

Inertial confinement fusion ablator physics experiments on Saturn and Nova

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

Olson, R.E.; Porter, J.L.; Chandler, G.A.

1997-05-01

The Saturn pulsed power accelerator [R. B. Spielman {ital et al.}, in {ital Proceedings of the 2nd International Conference on Dense} Z-{ital pinches}, Laguna Beach, CA, 1989, edited by N. R. Pereira, J. Davis, and N. Rostoker (American Institute of Physics, New York, 1989), p. 3] at Sandia National Laboratories (SNL) and the Nova laser [J. T. Hunt and D. R. Speck, Opt. Eng. {bold 28}, 461 (1989)] at Lawrence Livermore National Laboratory (LLNL) have been used to explore techniques for studying the behavior of ablator material in x-ray radiation environments comparable in magnitude, spectrum, and duration to those thatmore » would be experienced in National Ignition Facility (NIF) hohlraums [J. D. Lindl, Phys. Plasmas {bold 2}, 3933 (1995)]. The large x-ray outputs available from the Saturn pulsed-power-driven z pinch have enabled us to drive hohlraums of full NIF ignition scale size at radiation temperatures and time scales comparable to those required for the low-power foot pulse of an ignition capsule. The high-intensity drives available in the Nova laser have allowed us to study capsule ablator physics in smaller-scale hohlraums at radiation temperatures and time scales relevant to the peak power pulse for an ignition capsule. Taken together, these experiments have pointed the way to possible techniques for testing radiation-hydrodynamics code predictions of radiation flow, opacity, equation of state, and ablator shock velocity over the range of radiation environments that will be encountered in a NIF hohlraum. {copyright} {ital 1997 American Institute of Physics.}« less

Galaxy formation with BECDM - I. Turbulence and relaxation of idealized haloes.

PubMed

Mocz, Philip; Vogelsberger, Mark; Robles, Victor H; Zavala, Jesús; Boylan-Kolchin, Michael; Fialkov, Anastasia; Hernquist, Lars

2017-11-01

We present a theoretical analysis of some unexplored aspects of relaxed Bose-Einstein condensate dark matter (BECDM) haloes. This type of ultralight bosonic scalar field dark matter is a viable alternative to the standard cold dark matter (CDM) paradigm, as it makes the same large-scale predictions as CDM and potentially overcomes CDM's small-scale problems via a galaxy-scale de Broglie wavelength. We simulate BECDM halo formation through mergers, evolved under the Schrödinger-Poisson equations. The formed haloes consist of a soliton core supported against gravitational collapse by the quantum pressure tensor and an asymptotic r -3 NFW-like profile. We find a fundamental relation of the core-to-halo mass with the dimensionless invariant Ξ ≡ | E |/ M 3 /( Gm/ħ ) 2 or M c / M ≃ 2.6Ξ 1/3 , linking the soliton to global halo properties. For r ≥ 3.5 r c core radii, we find equipartition between potential, classical kinetic and quantum gradient energies. The haloes also exhibit a conspicuous turbulent behaviour driven by the continuous reconnection of vortex lines due to wave interference. We analyse the turbulence 1D velocity power spectrum and find a k -1.1 power law. This suggests that the vorticity in BECDM haloes is homogeneous, similar to thermally-driven counterflow BEC systems from condensed matter physics, in contrast to a k -5/3 Kolmogorov power law seen in mechanically-driven quantum systems. The mode where the power spectrum peaks is approximately the soliton width, implying that the soliton-sized granules carry most of the turbulent energy in BECDM haloes.

PLANET OCCURRENCE WITHIN 0.25 AU OF SOLAR-TYPE STARS FROM KEPLER

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

Howard, Andrew W.; Marcy, Geoffrey W.; Bryson, Stephen T.

We report the distribution of planets as a function of planet radius, orbital period, and stellar effective temperature for orbital periods less than 50 days around solar-type (GK) stars. These results are based on the 1235 planets (formally 'planet candidates') from the Kepler mission that include a nearly complete set of detected planets as small as 2 R{sub Circled-Plus }. For each of the 156,000 target stars, we assess the detectability of planets as a function of planet radius, R{sub p}, and orbital period, P, using a measure of the detection efficiency for each star. We also correct for themore » geometric probability of transit, R{sub *}/a. We consider first Kepler target stars within the 'solar subset' having T{sub eff} = 4100-6100 K, log g 4.0-4.9, and Kepler magnitude Kp < 15 mag, i.e., bright, main-sequence GK stars. We include only those stars having photometric noise low enough to permit detection of planets down to 2 R{sub Circled-Plus }. We count planets in small domains of R{sub p} and P and divide by the included target stars to calculate planet occurrence in each domain. The resulting occurrence of planets varies by more than three orders of magnitude in the radius-orbital period plane and increases substantially down to the smallest radius (2 R{sub Circled-Plus }) and out to the longest orbital period (50 days, {approx}0.25 AU) in our study. For P < 50 days, the distribution of planet radii is given by a power law, df/dlog R = k{sub R}R{sup {alpha}} with k{sub R} = 2.9{sup +0.5}{sub -0.4}, {alpha} = -1.92 {+-} 0.11, and R {identical_to} R{sub p}/R{sub Circled-Plus }. This rapid increase in planet occurrence with decreasing planet size agrees with the prediction of core-accretion formation but disagrees with population synthesis models that predict a desert at super-Earth and Neptune sizes for close-in orbits. Planets with orbital periods shorter than 2 days are extremely rare; for R{sub p} > 2 R{sub Circled-Plus} we measure an occurrence of less than 0.001 planets per star. For all planets with orbital periods less than 50 days, we measure occurrence of 0.130 {+-} 0.008, 0.023 {+-} 0.003, and 0.013 {+-} 0.002 planets per star for planets with radii 2-4, 4-8, and 8-32 R{sub Circled-Plus }, in agreement with Doppler surveys. We fit occurrence as a function of P to a power-law model with an exponential cutoff below a critical period P{sub 0}. For smaller planets, P{sub 0} has larger values, suggesting that the 'parking distance' for migrating planets moves outward with decreasing planet size. We also measured planet occurrence over a broader stellar T{sub eff} range of 3600-7100 K, spanning M0 to F2 dwarfs. Over this range, the occurrence of 2-4 R{sub Circled-Plus} planets in the Kepler field increases with decreasing T{sub eff}, with these small planets being seven times more abundant around cool stars (3600-4100 K) than the hottest stars in our sample (6600-7100 K).« less

Predicting plant uptake of cadmium: validated with long-term contaminated soils.

PubMed

Lamb, Dane T; Kader, Mohammed; Ming, Hui; Wang, Liang; Abbasi, Sedigheh; Megharaj, Mallavarapu; Naidu, Ravi

2016-10-01

Cadmium accumulates in plant tissues at low soil loadings and is a concern for human health. Yet at higher levels it is also of concern for ecological receptors. We determined Cd partitioning constants for 41 soils to examine the role of soil properties controlling Cd partitioning and plant uptake. From a series of sorption and dose response studies, transfer functions were developed for predicting Cd uptake in Cucumis sativa L. (cucumber). The parameter log K f was predicted with soil pH ca , logCEC and log OC. Transfer of soil pore-water Cd 2+ to shoots was described with a power function (R 2  = 0.73). The dataset was validated with 13 long-term contaminated soils (plus 2 control soils) ranging in Cd concentration from 0.2 to 300 mg kg -1 . The series of equations predicting Cd shoot from pore-water Cd 2+ were able to predict the measured data in the independent dataset (root mean square error = 2.2). The good relationship indicated that Cd uptake to cucumber shoots could be predicted with Cd pore and Cd 2+ without other pore-water parameters such as pH or Ca 2+ . The approach may be adapted to a range of plant species.

Relationship between relative net vertical impulse and jump height in jump squats performed to various squat depths and with various loads.

PubMed

McBride, Jeffrey M; Kirby, Tyler J; Haines, Tracie L; Skinner, Jared

2010-12-01

The purpose of the current investigation was to determine the relationship between relative net vertical impulse (net vertical impulse (VI)) and jump height in the jump squat (JS) going to different squat depths and utilizing various loads. Ten males with two years of jumping experience participated in this investigation (Age: 21.8 ± 1.9 y; Height: 176.9 ± 5.2 cm; Body Mass: 79.0 ± 7.1 kg, 1RM: 131.8 ± 29.5 kg, 1RM/BM: 1.66 ± 0.27). Subjects performed a series of static jumps (SJS) and countermovement jumps (CMJJS) with various loads (Body Mass, 20% of 1RM, 40% of 1RM) in a randomized fashion to a depth of 0.15, 0.30, 0.45, 0.60, and 0.75 m and a self-selected depth. During the concentric phase of each JS, peak force (PF), peak power (PP), jump height (JH) and relative VI were recorded and analyzed. Increasing squat depth corresponded to a decrease in PF and an increase in JH, relative VI for both SJS and CMJJS during all loads. Across all squat depths and loading conditions relative VI was statistically significantly correlated to JH in the SJS (r = .8956, P < .0001, power = 1.000) and CMJJS (r = .6007, P < .0001, power = 1.000). Across all squat depths and loading conditions PF was statistically nonsignificantly correlated to JH in the SJS (r = -0.1010, P = .2095, power = 0.2401) and CMJJS (r = -0.0594, P = .4527, power = 0.1131). Across all squat depths and loading conditions peak power (PP) was significantly correlated with JH during both the SJS (r = .6605, P < .0001, power = 1.000) and the CMJJS (r = .6631, P < .0001, power = 1.000). PP was statistically significantly higher at BM in comparison with 20% of 1RM and 40% of 1RM in the SJS and CMJJS across all squat depths. Results indicate that relative VI and PP can be used to predict JS performance, regardless of squat depth and loading condition. However, relative VI may be the best predictor of JS performance with PF being the worst predictor of JS performance.

Crosslinked enzyme aggregates of hydroxynitrile lyase partially purified from Prunus dulcis seeds and its application for the synthesis of enantiopure cyanohydrins.

PubMed

Yildirim, Deniz; Tükel, S Seyhan; Alagöz, Dilek

2014-01-01

Hydroxynitrile lyases are powerful catalysts in the synthesis of enantiopure cyanohydrins which are key synthons in the preparations of a variety of important chemicals. The response surface methodology including three-factor and three-level Box-Behnken design was applied to optimize immobilization of hydroxynitrile lyase purified partially from Prunus dulcis seeds as crosslinked enzyme aggregates (PdHNL-CLEAs). The quadratic model was developed for predicting the response and its adequacy was validated with the analysis of variance test. The optimized immobilization parameters were initial glutaraldehyde concentration, ammonium sulfate saturation concentration, and crosslinking time, and the response was relative activity of PdHNL-CLEA. The optimal conditions were determined as initial glutaraldehyde concentration of 25% w/v, ammonium sulfate saturation concentration of 43% w/v, and crosslinking time of 18 h. The preparations of PdHNL-CLEA were examined for the synthesis of (R)-mandelonitrile, (R)-2-chloromandelonitrile, (R)-3,4-dihydroxymandelonitrile, (R)-2-hydroxy-4-phenyl butyronitrile, (R)-4-bromomandelonitrile, (R)-4-fluoromandelonitrile, and (R)-4-nitromandelonitrile from their corresponding aldehydes and hydrocyanic acid. After 96-h reaction time, the yield-enantiomeric excess values (%) were 100-99, 100-21, 100-99, 83-91, 100-99, 100-72, and 100-14%, respectively, for (R)-mandelonitrile, (R)-2-chloromandelonitrile, (R)-3,4-dihydroxymandelonitrile, (R)-2-hydroxy-4-phenyl butyronitrile, (R)-4-bromomandelonitrile, (R)-4-fluoromandelonitrile, and (R)-4-nitromandelonitrile. The results show that PdHNL-CLEA offers a promising potential for the preparation of enantiopure (R)-mandelonitrile, (R)-3,4-dihydroxymandelonitrile, (R)-2-hydroxy-4-phenyl butyronitrile, and (R)-4-bromomandelonitrile with a high yield and enantiopurity. © 2014 American Institute of Chemical Engineers.

Quantitative Reactivity Scales for Dynamic Covalent and Systems Chemistry.

PubMed

Zhou, Yuntao; Li, Lijie; Ye, Hebo; Zhang, Ling; You, Lei

2016-01-13

Dynamic covalent chemistry (DCC) has become a powerful tool for the creation of molecular assemblies and complex systems in chemistry and materials science. Herein we developed for the first time quantitative reactivity scales capable of correlation and prediction of the equilibrium of dynamic covalent reactions (DCRs). The reference reactions are based upon universal DCRs between imines, one of the most utilized structural motifs in DCC, and a series of O-, N-, and S- mononucleophiles. Aromatic imines derived from pyridine-2-carboxyaldehyde exhibit capability for controlling the equilibrium through distinct substituent effects. Electron-donating groups (EDGs) stabilize the imine through quinoidal resonance, while electron-withdrawing groups (EWGs) stabilize the adduct by enhancing intramolecular hydrogen bonding, resulting in curvature in Hammett analysis. Notably, unique nonlinearity induced by both EDGs and EWGs emerged in Hammett plot when cyclic secondary amines were used. This is the first time such a behavior is observed in a thermodynamically controlled system, to the best of our knowledge. Unified quantitative reactivity scales were proposed for DCC and defined by the correlation log K = S(N) (R(N) + R(E)). Nucleophilicity parameters (R(N) and S(N)) and electrophilicity parameters (R(E)) were then developed from DCRs discovered. Furthermore, the predictive power of those parameters was verified by successful correlation of other DCRs, validating our reactivity scales as a general and useful tool for the evaluation and modeling of DCRs. The reactivity parameters proposed here should be complementary to well-established kinetics based parameters and find applications in many aspects, such as DCR discovery, bioconjugation, and catalysis.

Comparison of Mental Toughness and Power Test Performances in High-Level Kickboxers by Competitive Success.

PubMed

Slimani, Maamer; Miarka, Bianca; Briki, Walid; Cheour, Foued

2016-06-01

Kickboxing is a high-intensity intermittent striking combat sport, which is characterized by complex skills and tactical key actions with short duration. The present study compared and verified the relationship between mental toughness (MT), countermovement jump (CMJ) and medicine ball throw (MBT) power tests by outcomes of high-level kickboxers during National Championship. Thirty two high-level male kickboxers (winner = 16 and loser = 16: 21.2 ± 3.1 years, 1.73 ± 0.07 m, and 70.2 ± 9.4 kg) were analyzed using the CMJ, MBT tests and sports mental toughness questionnaire (SMTQ; based in confidence, constancy and control subscales), before the fights of the 2015 national championship (16 bouts). In statistical analysis, Mann-Withney test and a multiple linear regression were used to compare groups and to observe relationships, respectively, P ≤ 0.05. The present results showed significant differences between losers vs. winners, respectively, of total MT (7(7;8) vs. 11(10.2;11), confidence (3(3;3) vs. 4(4;4)), constancy (2(2;2) vs. 3(3;3)), control (2(2;3) vs. 4(4;4)) subscales and MBT (4.1(4;4.3) vs. 4.6(4.4;4.8)). The multiple linear regression showed a strong associations between MT results and outcome (r = 0.89), MBT (r = 0.84) and CMJ (r = 0.73). The findings suggest that MT will be more predictive of performance in those sports and in the outcome of competition.

Five-Axis Goniometric Stage

DTIC Science & Technology

2011-02-01

PS4 , Anaheim Automation PSAM24V2.7A) and a custom built variable 24 VDC 5 A power supply (PS5). The input voltage to the variable power supply is...provide power for the four brushless DC motor controllers (Anaheim Automation, MDC050-050051). PS4 supplies power to the optional position sensors...blue) X R15 - (green) 21 R14 + (red) Y R14 - (brown) 22 Z P1 P2 P3 P4 P9 P8 P5 PS1 PS2 PS3 PS4 PS5 19 Pending Distribution A

Prediction Models for Dynamic Demand Response

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

Aman, Saima; Frincu, Marc; Chelmis, Charalampos

2015-11-02

As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D 2R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D 2R, which we address inmore » this paper. Our first contribution is the formal definition of D 2R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D 2R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D 2R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D 2R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D 2R. Also, prediction models require just few days’ worth of data indicating that small amounts of historical training data can be used to make reliable predictions, simplifying the complexity of big data challenge associated with D 2R.« less

The Reliability and Predictive Ability of a Biomarker of Oxidative DNA Damage on Functional Outcomes after Stroke Rehabilitation

PubMed Central

Hsieh, Yu-Wei; Lin, Keh-Chung; Korivi, Mallikarjuna; Lee, Tsong-Hai; Wu, Ching-Yi; Wu, Kuen-Yuh

2014-01-01

We evaluated the reliability of 8-hydroxy-2′-deoxyguanosine (8-OHdG), and determined its ability to predict functional outcomes in stroke survivors. The rehabilitation effect on 8-OHdG and functional outcomes were also assessed. Sixty-one stroke patients received a 4-week rehabilitation. Urinary 8-OHdG levels were determined by liquid chromatography–tandem mass spectrometry. The test-retest reliability of 8-OHdG was good (interclass correlation coefficient = 0.76). Upper-limb motor function and muscle power determined by the Fugl-Meyer Assessment (FMA) and Medical Research Council (MRC) scales before rehabilitation showed significant negative correlation with 8-OHdG (r = −0.38, r = −0.30; p < 0.05). After rehabilitation, we found a fair and significant correlation between 8-OHdG and FMA (r = −0.34) and 8-OHdG and pain (r = 0.26, p < 0.05). Baseline 8-OHdG was significantly correlated with post-treatment FMA, MRC, and pain scores (r = −0.34, −0.31, and 0.25; p < 0.05), indicating its ability to predict functional outcomes. 8-OHdG levels were significantly decreased, and functional outcomes were improved after rehabilitation. The exploratory study findings conclude that 8-OHdG is a reliable and promising biomarker of oxidative stress and could be a valid predictor of functional outcomes in patients. Monitoring of behavioral indicators along with biomarkers may have crucial benefits in translational stroke research. PMID:24743892

Corneal power evaluation after myopic corneal refractive surgery using artificial neural networks.

PubMed

Koprowski, Robert; Lanza, Michele; Irregolare, Carlo

2016-11-15

Efficacy and high availability of surgery techniques for refractive defect correction increase the number of patients who undergo to this type of surgery. Regardless of that, with increasing age, more and more patients must undergo cataract surgery. Accurate evaluation of corneal power is an extremely important element affecting the precision of intraocular lens (IOL) power calculation and errors in this procedure could affect quality of life of patients and satisfaction with the service provided. The available device able to measure corneal power have been tested to be not reliable after myopic refractive surgery. Artificial neural networks with error backpropagation and one hidden layer were proposed for corneal power prediction. The article analysed the features acquired from the Pentacam HR tomograph, which was necessary to measure the corneal power. Additionally, several billion iterations of artificial neural networks were conducted for several hundred simulations of different network configurations and different features derived from the Pentacam HR. The analysis was performed on a PC with Intel ® Xeon ® X5680 3.33 GHz CPU in Matlab ® Version 7.11.0.584 (R2010b) with Signal Processing Toolbox Version 7.1 (R2010b), Neural Network Toolbox 7.0 (R2010b) and Statistics Toolbox (R2010b). A total corneal power prediction error was obtained for 172 patients (113 patients forming the training set and 59 patients in the test set) with an average age of 32 ± 9.4 years, including 67% of men. The error was at an average level of 0.16 ± 0.14 diopters and its maximum value did not exceed 0.75 dioptres. The Pentacam parameters (measurement results) providing the above result are tangential anterial/posterior. The corneal net power and equivalent k-reading power. The analysis time for a single patient (a single eye) did not exceed 0.1 s, whereas the time of network training was about 3 s for 1000 iterations (the number of neurons in the hidden layer was 400).

Can next-generation soil data products improve soil moisture modelling at the continental scale? An assessment using a new microclimate package for the R programming environment

NASA Astrophysics Data System (ADS)

Kearney, Michael R.; Maino, James L.

2018-06-01

Accurate models of soil moisture are vital for solving core problems in meteorology, hydrology, agriculture and ecology. The capacity for soil moisture modelling is growing rapidly with the development of high-resolution, continent-scale gridded weather and soil data together with advances in modelling methods. In particular, the GlobalSoilMap.net initiative represents next-generation, depth-specific gridded soil products that may substantially increase soil moisture modelling capacity. Here we present an implementation of Campbell's infiltration and redistribution model within the NicheMapR microclimate modelling package for the R environment, and use it to assess the predictive power provided by the GlobalSoilMap.net product Soil and Landscape Grid of Australia (SLGA, ∼100 m) as well as the coarser resolution global product SoilGrids (SG, ∼250 m). Predictions were tested in detail against 3 years of root-zone (3-75 cm) soil moisture observation data from 35 monitoring sites within the OzNet project in Australia, with additional tests of the finalised modelling approach against cosmic-ray neutron (CosmOz, 0-50 cm, 9 sites from 2011 to 2017) and satellite (ASCAT, 0-2 cm, continent-wide from 2007 to 2009) observations. The model was forced by daily 0.05° (∼5 km) gridded meteorological data. The NicheMapR system predicted soil moisture to within experimental error for all data sets. Using the SLGA or the SG soil database, the OzNet soil moisture could be predicted with a root mean square error (rmse) of ∼0.075 m3 m-3 and a correlation coefficient (r) of 0.65 consistently through the soil profile without any parameter tuning. Soil moisture predictions based on the SLGA and SG datasets were ≈ 17% closer to the observations than when using a chloropleth-derived soil data set (Digital Atlas of Australian Soils), with the greatest improvements occurring for deeper layers. The CosmOz observations were predicted with similar accuracy (r = 0.76 and rmse of ∼0.085 m3 m-3). Comparisons at the continental scale to 0-2 cm satellite data (ASCAT) showed that the SLGA/SG datasets increased model fit over simulations using the DAAS soil properties (r ∼ 0.63 &rmse 15% vs. r 0.48 &rmse 18%, respectively). Overall, our results demonstrate the advantages of using GlobalSoilMap.net products in combination with gridded weather data for modelling soil moisture at fine spatial and temporal resolution at the continental scale.

Understanding usage of a hybrid website and smartphone app for weight management: a mixed-methods study.

PubMed

Morrison, Leanne G; Hargood, Charlie; Lin, Sharon Xiaowen; Dennison, Laura; Joseph, Judith; Hughes, Stephanie; Michaelides, Danius T; Johnston, Derek; Johnston, Marie; Michie, Susan; Little, Paul; Smith, Peter Wf; Weal, Mark J; Yardley, Lucy

2014-10-22

Advancements in mobile phone technology offer huge potential for enhancing the timely delivery of health behavior change interventions. The development of smartphone-based health interventions (apps) is a rapidly growing field of research, yet there have been few longitudinal examinations of how people experience and use these apps within their day-to-day routines, particularly within the context of a hybrid Web- and app-based intervention. This study used an in-depth mixed-methods design to examine individual variation in (1) impact on self-reported goal engagement (ie, motivation, self-efficacy, awareness, effort, achievement) of access to a weight management app (POWeR Tracker) when provided alongside a Web-based weight management intervention (POWeR) and (2) usage and views of POWeR Tracker. Thirteen adults were provided access to POWeR and were monitored over a 4-week period. Access to POWeR Tracker was provided in 2 alternate weeks (ie, weeks 1 and 3 or weeks 2 and 4). Participants' goal engagement was measured daily via self-report. Mixed effects models were used to examine change in goal engagement between the weeks when POWeR Tracker was and was not available and whether the extent of change in goal engagement varied between individual participants. Usage of POWeR and POWeR Tracker was automatically recorded for each participant. Telephone interviews were conducted and analyzed using inductive thematic analysis to further explore participants' experiences using POWeR and POWeR Tracker. Access to POWeR Tracker was associated with a significant increase in participants' awareness of their eating (β1=0.31, P=.04) and physical activity goals (β1=0.28, P=.03). The level of increase varied between individual participants. Usage data showed that participants used the POWeR website for similar amounts of time during the weeks when POWeR Tracker was (mean 29 minutes, SD 31 minutes) and was not available (mean 27 minutes, SD 33 minutes). POWeR Tracker was mostly accessed in short bursts (mean 3 minutes, SD 2 minutes) during convenient moments or moments when participants deemed the intervention content most relevant. The qualitative data indicated that nearly all participants agreed that it was more convenient to access information on-the-go via their mobiles compared to a computer. However, participants varied in their views and usage of the Web- versus app-based components and the informational versus tracking tools provided by POWeR Tracker. This study provides evidence that smartphones have the potential to improve individuals' engagement with their health-related goals when used as a supplement to an existing online intervention. The perceived convenience of mobile access to information does not appear to deter use of Web-based interventions or strengthen the impact of app access on goal engagement. A mixed-methods design enabled exploration of individual variation in daily usage of the app-based tools.

Understanding Usage of a Hybrid Website and Smartphone App for Weight Management: A Mixed-Methods Study

PubMed Central

Hargood, Charlie; Lin, Sharon Xiaowen; Dennison, Laura; Joseph, Judith; Hughes, Stephanie; Michaelides, Danius T; Johnston, Derek; Johnston, Marie; Michie, Susan; Little, Paul; Smith, Peter WF; Weal, Mark J; Yardley, Lucy

2014-01-01

Background Advancements in mobile phone technology offer huge potential for enhancing the timely delivery of health behavior change interventions. The development of smartphone-based health interventions (apps) is a rapidly growing field of research, yet there have been few longitudinal examinations of how people experience and use these apps within their day-to-day routines, particularly within the context of a hybrid Web- and app-based intervention. Objective This study used an in-depth mixed-methods design to examine individual variation in (1) impact on self-reported goal engagement (ie, motivation, self-efficacy, awareness, effort, achievement) of access to a weight management app (POWeR Tracker) when provided alongside a Web-based weight management intervention (POWeR) and (2) usage and views of POWeR Tracker. Methods Thirteen adults were provided access to POWeR and were monitored over a 4-week period. Access to POWeR Tracker was provided in 2 alternate weeks (ie, weeks 1 and 3 or weeks 2 and 4). Participants’ goal engagement was measured daily via self-report. Mixed effects models were used to examine change in goal engagement between the weeks when POWeR Tracker was and was not available and whether the extent of change in goal engagement varied between individual participants. Usage of POWeR and POWeR Tracker was automatically recorded for each participant. Telephone interviews were conducted and analyzed using inductive thematic analysis to further explore participants’ experiences using POWeR and POWeR Tracker. Results Access to POWeR Tracker was associated with a significant increase in participants’ awareness of their eating (β1=0.31, P=.04) and physical activity goals (β1=0.28, P=.03). The level of increase varied between individual participants. Usage data showed that participants used the POWeR website for similar amounts of time during the weeks when POWeR Tracker was (mean 29 minutes, SD 31 minutes) and was not available (mean 27 minutes, SD 33 minutes). POWeR Tracker was mostly accessed in short bursts (mean 3 minutes, SD 2 minutes) during convenient moments or moments when participants deemed the intervention content most relevant. The qualitative data indicated that nearly all participants agreed that it was more convenient to access information on-the-go via their mobiles compared to a computer. However, participants varied in their views and usage of the Web- versus app-based components and the informational versus tracking tools provided by POWeR Tracker. Conclusions This study provides evidence that smartphones have the potential to improve individuals’ engagement with their health-related goals when used as a supplement to an existing online intervention. The perceived convenience of mobile access to information does not appear to deter use of Web-based interventions or strengthen the impact of app access on goal engagement. A mixed-methods design enabled exploration of individual variation in daily usage of the app-based tools. PMID:25355131

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

PubMed

So, Hon-Cheong; Sham, Pak C

2017-03-15

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

Maximizing Computational Capability with Minimal Power

DTIC Science & Technology

2009-03-01

Chip -Scale Energy and Power... and Heat Report Documentation Page Form ApprovedOMB No. 0704-0188 Public reporting burden for the collection of...OpticalBench Mounting Posts Imager Chip LCDinterfaced withthecomputer P o l a r i z e r P o l a r i z e r XYZ Translator Optical Slide VMM Computational Pixel...Signal routing power / memory: ? Power does not include comm off chip (i.e. accessing memory) Power = ½ C Vdd2 f for CMOS Chip to Chip (10pF load min

Circulating Myeloid‐Related Protein–8/14 is Related to Thromboxane‐Dependent Platelet Activation in Patients With Acute Coronary Syndrome, With and Without Ongoing Low‐Dose Aspirin Treatment

PubMed Central

Santilli, Francesca; Paloscia, Leonardo; Liani, Rossella; Di Nicola, Marta; Di Marco, Massimo; Lattanzio, Stefano; La Barba, Sara; Pascale, Silvia; Mascellanti, Marco; Davì, Giovanni

2014-01-01

Background Platelet activation is involved in acute coronary syndromes (ACS). Incomplete suppression by low‐dose aspirin treatment of thromboxane (TX) metabolite excretion (urinary 11‐dehydro‐TXB2) is predictive of vascular events in high‐risk patients. Myeloid‐related protein (MRP)‐8/14 is a heterodimer secreted on activation of platelets, monocytes, and neutrophils, regulating inflammation and predicting cardiovascular events. Among platelet transcripts, MRP‐14 has emerged as a powerful predictor of ACS. Methods and Results We enrolled 68 stable ischemic heart disease (IHD) and 63 ACS patients, undergoing coronary angiography, to evaluate whether MRP‐8/14 release in the circulation is related to TX‐dependent platelet activation in ACS and IHD patients and to residual TX biosynthesis in low‐dose aspirin–treated ACS patients. In ACS patients, plasma MRP‐8/14 and urinary 11‐dehydro‐TXB2 levels were linearly correlated (r=0.651, P<0.001) but significantly higher than those in IHD patients (P=0.012, P=0.044) only among subjects not receiving aspirin. In aspirin‐treated ACS patients, MRP‐8/14 and 11‐dehydro‐TXB2 were lower versus those not receiving aspirin (P<0.001) and still significantly correlated (r=0.528, P<0.001). Higher 11‐dehydro‐TXB2 significantly predicted higher MRP‐8/14 in both all ACS patients and ACS receiving aspirin (P<0.001, adj R2=0.463 and adj R2=0.497) after multivariable adjustment. Conversely, plasma MRP‐8/14 (P<0.001) and higher urinary 8‐iso‐prostaglandin F2α (P=0.050) levels were significant predictors of residual, on‐aspirin, TX biosynthesis in ACS (adjusted R2=0.384). Conclusions Circulating MRP‐8/14 is associated with TX‐dependent platelet activation in ACS, even during low‐dose aspirin treatment, suggesting a contribution of residual TX to MRP‐8/14 shedding, which may further amplify platelet activation. Circulating MRP‐8/14 may be a target to test different antiplatelet strategies in ACS. PMID:25037196

Indicators of hypertriglyceridemia from anthropometric measures based on data mining.

PubMed

Lee, Bum Ju; Kim, Jong Yeol

2015-02-01

The best indicator for the prediction of hypertriglyceridemia derived from anthropometric measures of body shape remains a matter of debate. The objectives are to determine the strongest predictor of hypertriglyceridemia from anthropometric measures and to investigate whether a combination of measures can improve the prediction accuracy compared with individual measures. A total of 5517 subjects aged 20-90 years participated in this study. The numbers of normal and hypertriglyceridemia subjects were 3022 and 653 females, respectively, and 1306 and 536 males, respectively. We evaluated 33 anthropometric measures for the prediction of hypertriglyceridemia using statistical analysis and data mining. In the 20-90-year-old groups, age in women was the variable that exhibited the highest predictive power; however, this was not the case in men in all age groups. Of the anthropometric measures, the waist-to-height ratio (WHtR) was the best predictor of hypertriglyceridemia in women. In men, the rib-to-forehead circumference ratio (RFcR) was the strongest indicator. The use of a combination of measures provides better predictive power compared with individual measures in both women and men. However, in the subgroups of ages 20-50 and 51-90 years, the strongest indicators for hypertriglyceridemia were rib circumference in the 20-50-year-old group and WHtR in the 51-90-year-old group in women and RFcR in the 20-50-year-old group and BMI in the 51-90-year-old group in men. Our results demonstrated that the best predictor of hypertriglyceridemia may differ according to gender and age. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Regional oxygen saturation index (rSO2) in brachioradialis and deltoid muscle. Correlation and prognosis in patients with respiratory sepsis.

PubMed

Rodríguez, A; Claverias, L; Marín, J; Magret, M; Rosich, S; Bodí, M; Trefler, S; Pascual, S; Gea, J

2015-03-01

To compare oxygen saturation index (rSO2) obtained simultaneously in two different brachial muscles. Prospective and observational study. Intensive care unit. Critically ill patients with community-acquired pneumonia. Two probes of NIRS device (INVOS 5100) were simultaneously placed on the brachioradialis (BR) and deltoid (D) muscles. rSO2 measurements were recorded at baseline (ICU admission) and at 24h. Demographic and clinical variables were registered. Pearson's correlation coefficient was used to assess the association between continuous variables. The consistency of the correlation was assessed using the intraclass correlation coefficient (ICC) and Bland-Altman plot. The predictive value of the rSO2 for mortality was calculated by ROC curve. Nineteen patients were included with an ICU mortality of 21.1%. The rSO2 values at baseline and at 24h were significantly higher in D than in BR muscle. Values obtained simultaneously in both limbs showed a strong correlation and adequate consistency: BR (r=0.95; p<0.001; ICC=0.94; 95% CI: 0.90-0.96; p<0.001), D (r=0.88; p=0.01; ICC=0.88; 95% CI: 0.80-0.90; p>0.001) but a wide limit of agreement. Non-survivors had rSO2 values significantly lower than survivors at all times of the study. No patient with rSO2 >60% in BR died, and only 17.6% died with an rSO2 value >60% in D. Both muscles showed consistent discriminatory power for mortality. Both BR and D muscles were appropriate for measuring rSO2. Copyright © 2013 Elsevier España, S.L.U. and SEMICYUC. All rights reserved.

Light Water Reactor Sustainability (LWRS) Program – Non-Destructive Evaluation (NDE) R&D Roadmap for Determining Remaining Useful Life of Aging Cables in Nuclear Power Plants

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

Simmons, Kevin L.; Ramuhalli, Pradeep; Brenchley, David L.

2012-09-14

The purpose of the non-destructive evaluation (NDE) R&D Roadmap for Cables is to support the Materials Aging and Degradation (MAaD) R&D pathway. The focus of the workshop was to identify the technical gaps in detecting aging cables and predicting their remaining life expectancy. The workshop was held in Knoxville, Tennessee, on July 30, 2012, at Analysis and Measurement Services Corporation (AMS) headquarters. The workshop was attended by 30 experts in materials, electrical engineering, U.S. Nuclear Regulatory Commission (NRC), U.S. Department of Energy (DOE) National Laboratories (Oak Ridge National Laboratory, Pacific Northwest National Laboratory, Argonne National Laboratory, and Idaho National Engineeringmore » Laboratory), NDE instrumentation development, universities, commercial NDE services and cable manufacturers, and Electric Power Research Institute (EPRI). The motivation for the R&D roadmap comes from the need to address the aging management of in-containment cables at nuclear power plants (NPPs).« less

Bayesian regression models outperform partial least squares methods for predicting milk components and technological properties using infrared spectral data

PubMed Central

Ferragina, A.; de los Campos, G.; Vazquez, A. I.; Cecchinato, A.; Bittante, G.

2017-01-01

The aim of this study was to assess the performance of Bayesian models commonly used for genomic selection to predict “difficult-to-predict” dairy traits, such as milk fatty acid (FA) expressed as percentage of total fatty acids, and technological properties, such as fresh cheese yield and protein recovery, using Fourier-transform infrared (FTIR) spectral data. Our main hypothesis was that Bayesian models that can estimate shrinkage and perform variable selection may improve our ability to predict FA traits and technological traits above and beyond what can be achieved using the current calibration models (e.g., partial least squares, PLS). To this end, we assessed a series of Bayesian methods and compared their prediction performance with that of PLS. The comparison between models was done using the same sets of data (i.e., same samples, same variability, same spectral treatment) for each trait. Data consisted of 1,264 individual milk samples collected from Brown Swiss cows for which gas chromatographic FA composition, milk coagulation properties, and cheese-yield traits were available. For each sample, 2 spectra in the infrared region from 5,011 to 925 cm−1 were available and averaged before data analysis. Three Bayesian models: Bayesian ridge regression (Bayes RR), Bayes A, and Bayes B, and 2 reference models: PLS and modified PLS (MPLS) procedures, were used to calibrate equations for each of the traits. The Bayesian models used were implemented in the R package BGLR (http://cran.r-project.org/web/packages/BGLR/index.html), whereas the PLS and MPLS were those implemented in the WinISI II software (Infrasoft International LLC, State College, PA). Prediction accuracy was estimated for each trait and model using 25 replicates of a training-testing validation procedure. Compared with PLS, which is currently the most widely used calibration method, MPLS and the 3 Bayesian methods showed significantly greater prediction accuracy. Accuracy increased in moving from calibration to external validation methods, and in moving from PLS and MPLS to Bayesian methods, particularly Bayes A and Bayes B. The maximum R2 value of validation was obtained with Bayes B and Bayes A. For the FA, C10:0 (% of each FA on total FA basis) had the highest R2 (0.75, achieved with Bayes A and Bayes B), and among the technological traits, fresh cheese yield R2 of 0.82 (achieved with Bayes B). These 2 methods have proven to be useful instruments in shrinking and selecting very informative wavelengths and inferring the structure and functions of the analyzed traits. We conclude that Bayesian models are powerful tools for deriving calibration equations, and, importantly, these equations can be easily developed using existing open-source software. As part of our study, we provide scripts based on the open source R software BGLR, which can be used to train customized prediction equations for other traits or populations. PMID:26387015

Clinical verification of a theory for predicting side branch stenosis after main vessel stenting in coronary bifurcation lesions.

PubMed

Vassilev, Dobrin; Gil, Robert

2008-12-01

To verify in a clinical scenario a theory for predicting side branch (SB) stenosis after main vessel stent implantation in coronary bifurcation lesions. Many unresolved issues remain regarding SB compromise when the parent vessel is stented. Bifurcation lesions (all Medina types) were subjected to angiographic analysis to determine the angle, defined as alpha, between the axes of the parent vessel and the SB. Using the prediction that the percent diameter stenosis (%DS) is equal to the cosine of angle alpha and relating it to a formula to determine the minimal lumen diameter (MLD) led to the following equation: MLD = ds x (1 -cos alpha); ds refers to the diameter of the SB. The predicted and observed SB stenosis values following angiography were compared. Fifty-two patients with 57 lesions were included in the analysis. Patient demographics and characteristics were similar to those in previous studies. There was a high coefficient of determination between the predicted and observed values of %DS (r(2)= 0.82, P < 0.001) and MLD (r(2)= 0.86, P < 0.001). We determined a cutoff value of 70% for predicted %DS for SB closure. When using multivariate regression analysis, the only predictor of SB ostial stenosis after stenting was alpha angle, whereas the predictors of MLD included the angle alpha and the RVD of the SB. Our analysis shows that the most powerful independent predictor of SB compromise is a new variable angle alpha.

Yo-Yo IR1 vs. incremental continuous running test for prediction of 3000-m performance.

PubMed

Schmitz, Boris; Klose, Andreas; Schelleckes, Katrin; Jekat, Charlotte M; Krüger, Michael; Brand, Stefan-Martin

2017-11-01

This study aimed to compare physiological responses during the Yo-Yo intermittent recovery level 1 (Yo-Yo IR1) Test and an incremental continuous running field Test (ICRT) and to analyze their predictive value on 3000-m running performance. Forty moderately trained individuals (18 females) performed the ICRT and Yo-Yo IR1 Test to exhaustion. The ICRT was performed as graded running test with an increase of 2.0 km·h-1 after each 3 min interval for lactate diagnostic. In both tests, blood lactate levels were determined after the test and at 2 and 5 min of recovery. Heart rate (HR) was recorded to monitor differences in HR slopes and HR recovery. Comparison revealed a correlation between ICRT and Yo-Yo IR1 Test performance (R2=0.83, P<0.001), while significant differences in HRmax existed (Yo-Yo IR1, 189±10 bpm; ICRT, 195±16 bpm; P<0.005; ES=0.5). Maximum lactate levels were also different between test (Yo-Yo IR1, 10.1±2.1 mmol∙L-1; ICRT, 11.7±2.4 mmol∙L-1; P<0.01; ES=0.7). Significant inverse correlations were found between the Yo-Yo IR1 Test performance and 3000 m running time (R2=0.77, P<0.0001) as well as the ICRT and 3000 m time (R2=0.90, P<0.0001). Our data suggest that ICRT and Yo-Yo IR1 test are useful field test methods for the prediction of competitive running performances such as 3000-m runs but maximum HR and blood lactate values differ significantly. The ICRT may have higher predictive power for middle- to long- distance running performance such as 3000-m runs offering a reliable test for coaches in the recruitment of athletes or supervision of training concepts.

Using LMS tables to determine waist circumference and waist-to-height ratios in Colombian children and adolescents: the FUPRECOL study.

PubMed

Ramírez-Vélez, Robinson; Moreno-Jiménez, Javier; Correa-Bautista, Jorge Enrique; Martínez-Torres, Javier; González-Ruiz, Katherine; González-Jiménez, Emilio; Schmidt-RioValle, Jacqueline; Lobelo, Felipe; Garcia-Hermoso, Antonio

2017-07-11

Waist circumference (WC) and waist-to-height ratio (WHtR) are often used as indices predictive of central obesity. The aims of this study were: 1) to obtain smoothed centile charts and LMS tables for WC and WHtR among Colombian children and adolescents; 2) to evaluate the utility of these parameters as predictors of overweight and obesity. A cross-sectional study was conducted of a sample population of 7954 healthy Colombian schoolchildren [3460 boys and 4494 girls, mean age 12.8 (±2.3) years]. Weight, height, body mass index (BMI), WC and WHtR were measured, and percentiles were calculated using the LMS method (Box-Cox, median and coefficient of variation). Appropriate cut-off points of WC and WHtR for overweight and obesity, according to International Obesity Task Force definitions, were selected using receiver operating characteristic (ROC) analysis. The discriminating power of WC and WHtR is expressed as area under the curve (AUC). Reference values for WC and WHtR are presented. Mean WC increased and WHtR decreased with age for both genders. A moderate positive correlation was observed between WC and BMI (r = 0.756, P < 0.01) and between WHtR and BMI (r = 0.604, P < 0.01). ROC analysis revealed strong discrimination power in the identification of overweight and obesity for both measures in our sample population. Overall, WHtR was a slightly better predictor of overweight/obesity (AUC 95% CI 0.868-0.916) than WC (AUC 95% CI 0.862-0.904). This paper presents the first sex and age-specific WC and WHtR percentiles for Colombian children and adolescents aged 9.0-17.9 years. The LMS tables obtained, based on Colombian reference data, can be used as quantitative tools for the study of obesity and its comorbidities.

Rapid detection of kernel rots and mycotoxins in maize by near-infrared reflectance spectroscopy.

PubMed

Berardo, Nicola; Pisacane, Vincenza; Battilani, Paola; Scandolara, Andrea; Pietri, Amedeo; Marocco, Adriano

2005-10-19

Near-infrared (NIR) spectroscopy is a practical spectroscopic procedure for the detection of organic compounds in matter. It is particularly useful because of its nondestructiveness, accuracy, rapid response, and easy operation. This work assesses the applicability of NIR for the rapid identification of micotoxigenic fungi and their toxic metabolites produced in naturally and artificially contaminated products. Two hundred and eighty maize samples were collected both from naturally contaminated maize crops grown in 16 areas in north-central Italy and from ears artificially inoculated with Fusarium verticillioides. All samples were analyzed for fungi infection, ergosterol, and fumonisin B1 content. The results obtained indicated that NIR could accurately predict the incidence of kernels infected by fungi, and by F. verticillioides in particular, as well as the quantity of ergosterol and fumonisin B1 in the meal. The statistics of the calibration and of the cross-validation for mold infection and for ergosterol and fumonisin B1 contents were significant. The best predictive ability for the percentage of global fungal infection and F. verticillioides was obtained using a calibration model utilizing maize kernels (r2 = 0.75 and SECV = 7.43) and maize meals (r2 = 0.79 and SECV = 10.95), respectively. This predictive performance was confirmed by the scatter plot of measured F. verticillioides infection versus NIR-predicted values in maize kernel samples (r2 = 0.80). The NIR methodology can be applied for monitoring mold contamination in postharvest maize, in particular F. verticilliodes and fumonisin presence, to distinguish contaminated lots from clean ones, and to avoid cross-contamination with other material during storage and may become a powerful tool for monitoring the safety of the food supply.

The value of surrogate endpoints for predicting real-world survival across five cancer types.

PubMed

Shafrin, Jason; Brookmeyer, Ron; Peneva, Desi; Park, Jinhee; Zhang, Jie; Figlin, Robert A; Lakdawalla, Darius N

2016-01-01

It is unclear how well different outcome measures in randomized controlled trials (RCTs) perform in predicting real-world cancer survival. We assess the ability of RCT overall survival (OS) and surrogate endpoints - progression-free survival (PFS) and time to progression (TTP) - to predict real-world OS across five cancers. We identified 20 treatments and 31 indications for breast, colorectal, lung, ovarian, and pancreatic cancer that had a phase III RCT reporting median OS and median PFS or TTP. Median real-world OS was determined using a Kaplan-Meier estimator applied to patients in the Surveillance and Epidemiology End Results (SEER)-Medicare database (1991-2010). Performance of RCT OS and PFS/TTP in predicting real-world OS was measured using t-tests, median absolute prediction error, and R(2) from linear regressions. Among 72,600 SEER-Medicare patients similar to RCT participants, median survival was 5.9 months for trial surrogates, 14.1 months for trial OS, and 13.4 months for real-world OS. For this sample, regression models using clinical trial OS and trial surrogates as independent variables predicted real-world OS significantly better than models using surrogates alone (P = 0.026). Among all real-world patients using sample treatments (N = 309,182), however, adding trial OS did not improve predictive power over predictions based on surrogates alone (P = 0.194). Results were qualitatively similar using median absolute prediction error and R(2) metrics. Among the five tumor types investigated, trial OS and surrogates were each independently valuable in predicting real-world OS outcomes for patients similar to trial participants. In broader real-world populations, however, trial OS added little incremental value over surrogates alone.

The relation between knee muscle strength and performance tests in orienteering athletes.

PubMed

Çinar-Medeni, Özge; Colakoglu, Fatma F; Yüce, Koray; Ipekoğlu, Gökhan; Baltaci, Gul

2016-11-01

The aim of this study was to analyze the effect of knee muscle strength on performance tests in orienteers. Thirty-seven orienteers were voluntarily included in this study. Isokinetic knee flexor and extensor muscles' strength was assessed at 120°/s velocity for both "dominant leg" (DL) and "non-dominant leg" (NDL). "Single-legged hop test" (SLHT), "flamingo balance test" (FBT), "star excursion balance test" (SEBT), vertical jump-and-reach test (for anaerobic power), T-drill test and 20-meter shuttle run test (for aerobic power) were carried out. Correlation and regression analyses were performed on the data. VO2max levels showed moderate correlations with DL's "flexor peak torque" (FPT) and NDL's "extensor peak torque" (EPT) and FPT values respectively (r=0.49, r=0.38, r=0.58). FPT of NDL was a predictor of VO2max level (R2=0.33). Anaerobic power has a relationship with EPT of NDL (r=0.43) and T-drill test with EPT and FPT values of both DL and NDL respectively (r=-0.35, r=-0.63, r=-0.53, r=-0.58). EPT of NDL was a predictor for anaerobic power (R2=0.19) and FPT of DL for agility (R2=0.40). Nonparametric linear regression results showed that EPT is a predictor in DL (median slope=-0.71, P=0.01), and FPT in NDL (median slope=-0.90, P=0.006) for FBT. FPT was a predictor of SEBT scores for both legs (0.13

Wind power application research on the fusion of the determination and ensemble prediction

NASA Astrophysics Data System (ADS)

Lan, Shi; Lina, Xu; Yuzhu, Hao

2017-07-01

The fused product of wind speed for the wind farm is designed through the use of wind speed products of ensemble prediction from the European Centre for Medium-Range Weather Forecasts (ECMWF) and professional numerical model products on wind power based on Mesoscale Model5 (MM5) and Beijing Rapid Update Cycle (BJ-RUC), which are suitable for short-term wind power forecasting and electric dispatch. The single-valued forecast is formed by calculating the different ensemble statistics of the Bayesian probabilistic forecasting representing the uncertainty of ECMWF ensemble prediction. Using autoregressive integrated moving average (ARIMA) model to improve the time resolution of the single-valued forecast, and based on the Bayesian model averaging (BMA) and the deterministic numerical model prediction, the optimal wind speed forecasting curve and the confidence interval are provided. The result shows that the fusion forecast has made obvious improvement to the accuracy relative to the existing numerical forecasting products. Compared with the 0-24 h existing deterministic forecast in the validation period, the mean absolute error (MAE) is decreased by 24.3 % and the correlation coefficient (R) is increased by 12.5 %. In comparison with the ECMWF ensemble forecast, the MAE is reduced by 11.7 %, and R is increased 14.5 %. Additionally, MAE did not increase with the prolongation of the forecast ahead.

Topography of Slow Sigma Power during Sleep is Associated with Processing Speed in Preschool Children

PubMed Central

Doucette, Margaret R.; Kurth, Salome; Chevalier, Nicolas; Munakata, Yuko; LeBourgeois, Monique K.

2015-01-01

Cognitive development is influenced by maturational changes in processing speed, a construct reflecting the rapidity of executing cognitive operations. Although cognitive ability and processing speed are linked to spindles and sigma power in the sleep electroencephalogram (EEG), little is known about such associations in early childhood, a time of major neuronal refinement. We calculated EEG power for slow (10–13 Hz) and fast (13.25–17 Hz) sigma power from all-night high-density electroencephalography (EEG) in a cross-sectional sample of healthy preschool children (n = 10, 4.3 ± 1.0 years). Processing speed was assessed as simple reaction time. On average, reaction time was 1409 ± 251 ms; slow sigma power was 4.0 ± 1.5 μV2; and fast sigma power was 0.9 ± 0.2 μV2. Both slow and fast sigma power predominated over central areas. Only slow sigma power was correlated with processing speed in a large parietal electrode cluster (p < 0.05, r ranging from −0.6 to −0.8), such that greater power predicted faster reaction time. Our findings indicate regional correlates between sigma power and processing speed that are specific to early childhood and provide novel insights into the neurobiological features of the EEG that may underlie developing cognitive abilities. PMID:26556377

Effect of work and recovery durations on W' reconstitution during intermittent exercise.

PubMed

Skiba, Philip F; Jackman, Sarah; Clarke, David; Vanhatalo, Anni; Jones, Andrew M

2014-07-01

We recently presented an integrating model of the curvature constant of the hyperbolic power-time relationship (W') that permits the calculation of the W' balance (W'BAL) remaining at any time during intermittent exercise. Although a relationship between recovery power and the rate of W' recovery was demonstrated, the effect of the length of work or recovery intervals remains unclear. After determining VO2max, critical power, and W', 11 subjects completed six separate exercise tests on a cycle ergometer on different days, and in random order. Tests consisted of a period of intermittent severe-intensity exercise until the subject depleted approximately 50% of their predicted W'BAL, followed by a constant work rate (CWR) exercise bout until exhaustion. Work rates were kept constant between trials; however, either work or recovery durations during intermittent exercise were varied. The actual W' measured during the CWR (W'ACT) was compared with the amount of W' predicted to be available by the W'BAL model. Although some differences between W'BAL and W'ACT were noted, these amounted to only -1.6 ± 1.1 kJ when averaged across all conditions. The W'ACT was linearly correlated with the difference between VO2 at the start of CWR and VO2max (r = 0.79, P < 0.01). The W'BAL model provided a generally robust prediction of CWR W'. There may exist a physiological optimum formulation of work and recovery intervals such that baseline VO2 can be minimized, leading to an enhancement of subsequent exercise tolerance. These results may have important implications for athletic training and racing.

Prognostic scoring systems for myelodysplastic syndromes (MDS) in a population-based setting: a report from the Swedish MDS register.

PubMed

Moreno Berggren, Daniel; Folkvaljon, Yasin; Engvall, Marie; Sundberg, Johan; Lambe, Mats; Antunovic, Petar; Garelius, Hege; Lorenz, Fryderyk; Nilsson, Lars; Rasmussen, Bengt; Lehmann, Sören; Hellström-Lindberg, Eva; Jädersten, Martin; Ejerblad, Elisabeth

2018-06-01

The myelodysplastic syndromes (MDS) have highly variable outcomes and prognostic scoring systems are important tools for risk assessment and to guide therapeutic decisions. However, few population-based studies have compared the value of the different scoring systems. With data from the nationwide Swedish population-based MDS register we validated the International Prognostic Scoring System (IPSS), revised IPSS (IPSS-R) and the World Health Organization (WHO) Classification-based Prognostic Scoring System (WPSS). We also present population-based data on incidence, clinical characteristics including detailed cytogenetics and outcome from the register. The study encompassed 1329 patients reported to the register between 2009 and 2013, 14% of these had therapy-related MDS (t-MDS). Based on the MDS register, the yearly crude incidence of MDS in Sweden was 2·9 per 100 000 inhabitants. IPSS-R had a significantly better prognostic power than IPSS (P < 0·001). There was a trend for better prognostic power of IPSS-R compared to WPSS (P = 0·05) and for WPSS compared to IPSS (P = 0·07). IPSS-R was superior to both IPSS and WPSS for patients aged ≤70 years. Patients with t-MDS had a worse outcome compared to de novo MDS (d-MDS), however, the validity of the prognostic scoring systems was comparable for d-MDS and t-MDS. In conclusion, population-based studies are important to validate prognostic scores in a 'real-world' setting. In our nationwide cohort, the IPSS-R showed the best predictive power. © 2018 John Wiley & Sons Ltd.

Note: An online testing method for lifetime projection of high power light-emitting diode under accelerated reliability test.

PubMed

Chen, Qi; Chen, Quan; Luo, Xiaobing

2014-09-01

In recent years, due to the fast development of high power light-emitting diode (LED), its lifetime prediction and assessment have become a crucial issue. Although the in situ measurement has been widely used for reliability testing in laser diode community, it has not been applied commonly in LED community. In this paper, an online testing method for LED life projection under accelerated reliability test was proposed and the prototype was built. The optical parametric data were collected. The systematic error and the measuring uncertainty were calculated to be within 0.2% and within 2%, respectively. With this online testing method, experimental data can be acquired continuously and sufficient amount of data can be gathered. Thus, the projection fitting accuracy can be improved (r(2) = 0.954) and testing duration can be shortened.

Defining the determinants of endurance running performance in the heat

PubMed Central

James, Carl A.; Hayes, Mark; Willmott, Ashley G. B.; Gibson, Oliver R.; Schlader, Zachary J.; Maxwell, Neil S.

2017-01-01

ABSTRACT In cool conditions, physiologic markers accurately predict endurance performance, but it is unclear whether thermal strain and perceived thermal strain modify the strength of these relationships. This study examined the relationships between traditional determinants of endurance performance and time to complete a 5-km time trial in the heat. Seventeen club runners completed graded exercise tests (GXT) in hot (GXTHOT; 32°C, 60% RH, 27.2°C WBGT) and cool conditions (GXTCOOL; 13°C, 50% RH, 9.3°C WBGT) to determine maximal oxygen uptake (V̇O2max), running economy (RE), velocity at V̇O2max (vV̇O2max), and running speeds corresponding to the lactate threshold (LT, 2 mmol.l−1) and lactate turnpoint (LTP, 4 mmol.l−1). Simultaneous multiple linear regression was used to predict 5 km time, using these determinants, indicating neither GXTHOT (R2 = 0.72) nor GXTCOOL (R2 = 0.86) predicted performance in the heat as strongly has previously been reported in cool conditions. vV̇O2max was the strongest individual predictor of performance, both when assessed in GXTHOT (r = −0.83) and GXTCOOL (r = −0.90). The GXTs revealed the following correlations for individual predictors in GXTHOT; V̇O2max r = −0.7, RE r = 0.36, LT r = −0.77, LTP r = −0.78 and in GXTCOOL; V̇O2max r = −0.67, RE r = 0.62, LT r = −0.79, LTP r = −0.8. These data indicate (i) GXTHOT does not predict 5 km running performance in the heat as strongly as a GXTCOOL, (ii) as in cool conditions, vV̇O2max may best predict running performance in the heat. PMID:28944273

Multi-MW K-Band Harmonic Multiplier: RF Source For High-Gradient Accelerator R & D

NASA Astrophysics Data System (ADS)

Solyak, N. A.; Yakovlev, V. P.; Kazakov, S. Yu.; Hirshfield, J. L.

2009-01-01

A preliminary design is presented for a two-cavity harmonic multiplier, intended as a high-power RF source for use in experiments aimed at developing high-gradient structures for a future collider. The harmonic multiplier is to produce power at selected frequencies in K-band (18-26.5 GHz) using as an RF driver an XK-5 S-band klystron (2.856 GHz). The device is to be built with a TE111 rotating mode input cavity and interchangeable output cavities running in the TEn11 rotating mode, with n = 7,8,9 at 19.992, 22.848, and 25.704 GHz. An example for a 7th harmonic multiplier is described, using a 250 kV, 20 A injected laminar electron beam; with 10 MW of S-band drive power, 4.7 MW of 20-GHz output power is predicted. Details are described of the magnetic circuit, cavities, and output coupler.

Reliability, Validity, and Minimal Detectable Change of Four-Step Stair Climb Power Test in Community-Dwelling Older Adults.

PubMed

Ni, Meng; Brown, Lorna G; Lawler, Danielle; Bean, Jonathan F

2017-07-01

Stair climb power is an important clinical measure of lower-extremity power. The stair climb power test (SCPT) was validated by requiring individuals to climb a full flight of stairs. A 4-step SCPT (4SCPT) would be more clinically feasible and easier to perform, yet its reliability and validity are unknown. To evaluate reliability, validity, and minimal detectable change of 4SCPT among community-dwelling older adults. This study is a cross-sectional analysis of baseline data from a clinical trial. Fifty older adults ≥65 years of age, at risk for mobility decline, consented to participate in this ancillary study. Test-retest reliability was derived from 2 measurements within each participant measured by a single assessor. Pearson correlation analyses among leg power measures (4SCPT, SCPT, single leg press power at 40% and 70% of the 1-repetition maximum [SLP40, SLP70]) were performed. Separate multivariate linear regressions were conducted evaluating the associations between each leg power measure and 2 mobility outcomes, the Short Physical Performance Battery (SPPB) and habitual gait speed (HGS). Minimal detectable change was based on a 90% confidence interval (MDC 90 ). The 4SCPT had excellent test-retest reliability (ICC(2,1) = 0.951), and strong correlation with SCPT, SLP40, and SLP70 ( r = 0.85-0.96). The 4SCPT explained a greater amount of variance in the SPPB (R 2 = 0.31) than other leg power measurements (R 2 = 0.23-0.25). The 4SCPT (R 2 = 0.41) and SCPT (R 2 = 0.42) described equivalent amounts of variance in HGS, and greater than that with SLP40 (R 2 = 0.28) and SLP70 (R 2 = 0.30). The MDC 90 for 4SCPT was 44.0 watts. This was a cross-sectional analysis within a small, nonrepresentative sample. Interrater reliability was not evaluated. The 4SCPT shows scientific promise as a valid and reliable leg power measurement among community-dwelling older adults. © 2017 American Physical Therapy Association

A rapid and low energy consumption method to decolorize the high concentration triphenylmethane dye wastewater: operational parameters optimization for the ultrasonic-assisted ozone oxidation process.

PubMed

Zhou, Xian-Jiao; Guo, Wan-Qian; Yang, Shan-Shan; Ren, Nan-Qi

2012-02-01

This research set up an ultrasonic-assisted ozone oxidation process (UAOOP) to decolorize the triphenylmethane dyes wastewater. Five factors - temperature, initial pH, reaction time, ultrasonic power (low frequency 20 kHz), and ozone concentration - were investigated. Response surface methodology was used to find out the major factors influencing color removal rate and the interactions between these factors, and optimized the operating parameters as well. Under the experimental conditions: reaction temperature 39.81 °C, initial pH 5.29, ultrasonic power 60 W and ozone concentration 0.17 g/L, the highest color removals were achieved with 10 min reaction time and the initial concentration of the MG solution was 1000 mg/L. The optimal results indicated that the UAOOP was a rapid, efficient and low energy consumption technique to decolorize the high concentration MG wastewater. The predicted model was approximately in accordance with the experimental cases with correlation coefficients R(2) and R(adj)(2) of 0.9103 and 0.8386. Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.

Isolation and identification of age-related DNA methylation markers for forensic age-prediction.

PubMed

Yi, Shao Hua; Xu, Long Chang; Mei, Kun; Yang, Rong Zhi; Huang, Dai Xin

2014-07-01

Age-prediction is an important part of forensic science. There is no available method of individual age-prediction for general forensic biological samples at crime scenes. Accumulating evidence indicates that aging resembles a developmentally regulated process tightly controlled by specific age-associated methylation exists in human genome. This study isolated and identified eight gene fragments in which the degree of cytosine methylation is significantly correlated with age in blood of 40 donors. Furthermore, we validated two CpG sites of each gene fragment and replicated our results in a general population sample of 40 males and 25 females with a wide age-range (11-72 years). The methylation of these fragments is linear with age over a range of six decades (Fragment P1 (r=-0.64), P2 (r=-0.58), P3 (r=-0.79), R1 (r=0.82), R2 (r=0.63), R3 (r=0.59), R4 (r=0.63) and R5 (r=0.62)). Using average methylation of two CpG sites from each fragment, we built a regression model that explained 95% of the variance in age and is able to predict the age of an individual with great accuracy (R(2)=0.918). The predicted values are highly correlated with the observed age in the sample (r=0.91). This study implicates that DNA methylation will be an available biological marker of age-prediction. Furthermore, measurement of relevant sites in the genome could be a tool in routine forensic screening to predict age of biological samples. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

High-resolution vertical profiles of groundwater electrical conductivity (EC) and chloride from direct-push EC logs

NASA Astrophysics Data System (ADS)

Bourke, Sarah A.; Hermann, Kristian J.; Hendry, M. Jim

2017-11-01

Elevated groundwater salinity associated with produced water, leaching from landfills or secondary salinity can degrade arable soils and potable water resources. Direct-push electrical conductivity (EC) profiling enables rapid, relatively inexpensive, high-resolution in-situ measurements of subsurface salinity, without requiring core collection or installation of groundwater wells. However, because the direct-push tool measures the bulk EC of both solid and liquid phases (ECa), incorporation of ECa data into regional or historical groundwater data sets requires the prediction of pore water EC (ECw) or chloride (Cl-) concentrations from measured ECa. Statistical linear regression and physically based models for predicting ECw and Cl- from ECa profiles were tested on a brine plume in central Saskatchewan, Canada. A linear relationship between ECa/ECw and porosity was more accurate for predicting ECw and Cl- concentrations than a power-law relationship (Archie's Law). Despite clay contents of up to 96%, the addition of terms to account for electrical conductance in the solid phase did not improve model predictions. In the absence of porosity data, statistical linear regression models adequately predicted ECw and Cl- concentrations from direct-push ECa profiles (ECw = 5.48 ECa + 0.78, R 2 = 0.87; Cl- = 1,978 ECa - 1,398, R 2 = 0.73). These statistical models can be used to predict ECw in the absence of lithologic data and will be particularly useful for initial site assessments. The more accurate linear physically based model can be used to predict ECw and Cl- as porosity data become available and the site-specific ECw-Cl- relationship is determined.

Predicting dimensions of personality disorder from domains and facets of the Five-Factor Model.

PubMed

Reynolds, S K; Clark, L A

2001-04-01

We compared the utility of several trait models for describing personality disorder in a heterogeneous clinical sample (N = 94). Participants completed the Schedule for Nonadaptive and Adaptive Personality (SNAP; Clark, 1993b), a self-report measure that assesses traits relevant to personality disorder, and two measures of the Five-Factor Model: the Revised NEO Personality Inventory (NEO-PI-R; Costa and McCrae, 1992) and the Big Five Inventory (BFI; John, Donahue, & Kentle, 1991). Regression analyses indicated substantial overlap between the SNAP scales and the NEO-PI-R facets. In addition, use of the NEO-PI-R facets afforded substantial improvement over the Five-Factor Model domains in predicting interview-based ratings of DSM-IV personality disorder (American Psychiatric Association, 1994), such that the NEO facets and the SNAP scales demonstrated roughly equivalent levels of predictive power. Results support assessment of the full range of NEO-PI-R facets over the Five-Factor Model domains for both research and clinical use.

Bayesian regression models outperform partial least squares methods for predicting milk components and technological properties using infrared spectral data.

PubMed

Ferragina, A; de los Campos, G; Vazquez, A I; Cecchinato, A; Bittante, G

2015-11-01

The aim of this study was to assess the performance of Bayesian models commonly used for genomic selection to predict "difficult-to-predict" dairy traits, such as milk fatty acid (FA) expressed as percentage of total fatty acids, and technological properties, such as fresh cheese yield and protein recovery, using Fourier-transform infrared (FTIR) spectral data. Our main hypothesis was that Bayesian models that can estimate shrinkage and perform variable selection may improve our ability to predict FA traits and technological traits above and beyond what can be achieved using the current calibration models (e.g., partial least squares, PLS). To this end, we assessed a series of Bayesian methods and compared their prediction performance with that of PLS. The comparison between models was done using the same sets of data (i.e., same samples, same variability, same spectral treatment) for each trait. Data consisted of 1,264 individual milk samples collected from Brown Swiss cows for which gas chromatographic FA composition, milk coagulation properties, and cheese-yield traits were available. For each sample, 2 spectra in the infrared region from 5,011 to 925 cm(-1) were available and averaged before data analysis. Three Bayesian models: Bayesian ridge regression (Bayes RR), Bayes A, and Bayes B, and 2 reference models: PLS and modified PLS (MPLS) procedures, were used to calibrate equations for each of the traits. The Bayesian models used were implemented in the R package BGLR (http://cran.r-project.org/web/packages/BGLR/index.html), whereas the PLS and MPLS were those implemented in the WinISI II software (Infrasoft International LLC, State College, PA). Prediction accuracy was estimated for each trait and model using 25 replicates of a training-testing validation procedure. Compared with PLS, which is currently the most widely used calibration method, MPLS and the 3 Bayesian methods showed significantly greater prediction accuracy. Accuracy increased in moving from calibration to external validation methods, and in moving from PLS and MPLS to Bayesian methods, particularly Bayes A and Bayes B. The maximum R(2) value of validation was obtained with Bayes B and Bayes A. For the FA, C10:0 (% of each FA on total FA basis) had the highest R(2) (0.75, achieved with Bayes A and Bayes B), and among the technological traits, fresh cheese yield R(2) of 0.82 (achieved with Bayes B). These 2 methods have proven to be useful instruments in shrinking and selecting very informative wavelengths and inferring the structure and functions of the analyzed traits. We conclude that Bayesian models are powerful tools for deriving calibration equations, and, importantly, these equations can be easily developed using existing open-source software. As part of our study, we provide scripts based on the open source R software BGLR, which can be used to train customized prediction equations for other traits or populations. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

HEAO 1 measurements of the galactic ridge

NASA Technical Reports Server (NTRS)

Worrall, D. M.; Marshall, F. E.; Boldt, E. A.; Swank, J. H.

1981-01-01

The HEAO A2 experiment data was systematically searched for unresolved galactic disc emission. Although there were suggestions of non-uniformities in the emission, the data were consistent with a disc of half-thickness 241 + 22 pc and surface emissivity (2-10 keV) at galactic radius R(kpc) of 2.2 10 to the minus 7th power exp(-R/3.5) erg/sq cm to the (-2)power/s (R 7.8 kpc). giving a luminosity of approximately 4.4 10 to the 37th power erg S to the (-1) power. If the model is extrapolated to radii less than 7.8 kpc, the unresolved disc emission is approximately 1.4 10 to the 38th power erg S to the (-1) power (2-10 keV) i.e., a few percent of the luminosity of the galaxy in resolved sources. the disc emission has a spectrum which is significantly softer than that of the high galactic latitude diffuse X-ray background and it is most probably of discrete source origin.

Experimental study on heat transfer performance of pulsating heat pipe with refrigerants

NASA Astrophysics Data System (ADS)

Wang, Xingyu; Jia, Li

2016-10-01

The effects of different refrigerants on heat transfer performance of pulsating heat pipe (PHP) are investigated experimentally. The working temperature of pulsating heat pipe is kept in the range of 20°C-50°C. The startup time of the pulsating heat pipe with refrigerants can be shorter than 4 min, when heating power is in the range of 10W?100W. The startup time decreases with heating power. Thermal resistances of PHP with filling ratio 20.55% were obviously larger than those with other filling ratios. Thermal resistance of the PHP with R134a is much smaller than that with R404A and R600a. It indicates that the heat transfer ability of R134a is better. In addition, a correlation to predict thermal resistance of PHP with refrigerants was suggested.

Scattering by inhomogeneous systems with rough internal surfaces: Porous solids and random-field Ising systems

NASA Astrophysics Data System (ADS)

Wong, Po-Zen

1985-12-01

For a two-component inhomogeneous system consisting of compact domains of characteristic size R, I show that if the domain walls are ``rough'' and their root-mean-square fluctuation w over a distance r obeys a power law w=b(r/a)x (a is the lattice constant and x>0), then the geometrical correlation function γ(r) has leading terms proportional to rx and r for r<>R-1, where d is the dimension of the system. Two possible applications of this result are discussed. (i) In granular porous solids which have a minimum grain size Rmin, the above result implies that surface roughness can cause I(q) to fall off like 1/qα for q>>Rmin-1, where α=3+x>3 for d=3. In particular, when x>1, the surface becomes a fractal with dimension D=1+x=α-2, which can be extracted from the scattering data. On the other hand, if the grains are smooth and their size distribution obeys a power law dN(R)/dR~R-β over a range Rmin

Using Plasticity Values Determined from Systematic Hardness Indentation Measurements for Predicting Impact Behavior in Structural Ceramics: A New, Simple Screening Technique

DTIC Science & Technology

2008-12-01

oxynitride (AlON), silicon carbide, aluminum oxide and boron carbide. A power-law equation (H = kFc ) is shown to fit the Knoop data quite well. A plot...20 22 24 26 0 20 40 60 80 100 120 140 a/F + b kFc HK= 24.183 F-0.0699 R2= 0.97 H K (G Pa ) Load (N) HK = a/F + b ErrorValue 0.919483.7367a

Prediction of canned black bean texture (Phaseolus vulgaris L.) from intact dry seeds using visible/near infrared spectroscopy and hyperspectral imaging data.

PubMed

Mendoza, Fernando A; Cichy, Karen A; Sprague, Christy; Goffnett, Amanda; Lu, Renfu; Kelly, James D

2018-01-01

Texture is a major quality parameter for the acceptability of canned whole beans. Prior knowledge of this quality trait before processing would be useful to guide variety development by bean breeders and optimize handling protocols by processors. The objective of this study was to evaluate and compare the predictive power of visible and near infrared reflectance spectroscopy (visible/NIRS, 400-2498 nm) and hyperspectral imaging (HYPERS, 400-1000 nm) techniques for predicting texture of canned black beans from intact dry seeds. Black beans were grown in Michigan (USA) over three field seasons. The samples exhibited phenotypic variability for canned bean texture due to genetic variability and processing practice. Spectral preprocessing methods (i.e. smoothing, first and second derivatives, continuous wavelet transform, and two-band ratios), coupled with a feature selection method, were tested for optimizing the prediction accuracy in both techniques based on partial least squares regression (PLSR) models. Visible/NIRS and HYPERS were effective in predicting texture of canned beans using intact dry seeds, as indicated by their correlation coefficients for prediction (R pred ) and standard errors of prediction (SEP). Visible/NIRS was superior (R pred = 0.546-0.923, SEP = 7.5-1.9 kg 100 g -1 ) to HYPERS (R pred = 0.401-0.883, SEP = 7.6-2.4 kg 100 g -1 ), which is likely due to the wider wavelength range collected in visible/NIRS. However, a significant improvement was reached in both techniques when the two-band ratios preprocessing method was applied to the data, reducing SEP by at least 10.4% and 16.2% for visible/NIRS and HYPERS, respectively. Moreover, results from using the combination of the three-season data sets based on the two-band ratios showed that visible/NIRS (R pred = 0.886, SEP = 4.0 kg 100 g -1 ) and HYPERS (R pred = 0.844, SEP = 4.6 kg 100 g -1 ) models were consistently successful in predicting texture over a wide range of measurements. Visible/NIRS and HYPERS have great potential for predicting the texture of canned beans; the robustness of the models is impacted by genotypic diversity, planting year and phenotypic variability for canned bean texture used for model building, and hence, robust models can be built based on data sets with high phenotypic diversity in textural properties, and periodically maintained and updated with new data. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Large scale structure constraints for a class of f(R) theories of gravity

NASA Astrophysics Data System (ADS)

Abebe, Amare; de la Cruz-Dombriz, Álvaro; Dunsby, Peter K. S.

2013-08-01

Over the past few years much attention has been given to the study of modified gravity theories in order to find a more natural explanation for the late time acceleration of the Universe. Nevertheless, a comparison of the matter power spectrum predictions made by these theories with available data has not yet been subjected to a detailed analysis. In the context of f(R) theories of gravity we study the predicted power spectra using both a dynamical systems approach for the background and solving for the matter perturbations without using the quasistatic approximation, comparing the theoretical results with several Sloan Digital Sky Survey data. The importance of studying the first order perturbed equations by assuming the correct background evolution and the relevance of the initial conditions are also stressed. We determine the statistical significance in relation to the observational data and demonstrate their conflict with existing observations.

Effect of walking velocity on hindlimb kinetics during stance in normal horses.

PubMed

Khumsap, S; Clayton, H M; Lanovaz, J L

2001-04-01

The objectives of this study were to measure the effect of walking velocity on net joint moments and joint powers in the hindlimb during stance and to use the data to predict these variables at different walking velocities. Videographic and force data were collected synchronously from 5 sound horses walking over a force plate at a range of velocities. Force and kinematic data from 56 trials were combined using an inverse dynamic solution to determine net joint moments and joint powers. Analysis by simple regression and correlation (P < 0.05, r2 > or = 0.30, r > 0.50) showed that, in early stance, there were significant velocity-dependent increases in the peak magnitudes of the following variables: extensor moment and positive power at the hip, flexor moment and positive power at the stifle, extensor moment, negative and positive power at the tarsus, and flexor moment and negative power at the fetlock. In late stance, there were significant velocity-dependent increases in the peak magnitudes of the following variables: flexor moment at the hip, negative power at the stifle and flexor moment and positive power at the tarsus. As velocity increased, the hip showed an increase in energy generation, whereas the tarsus showed increases in both energy generation and absorption. It is concluded that an increase in walking velocity is associated with increases in peak magnitudes of the net joint moments and joint powers in the hindlimb; and that energy generation at the hip makes the largest contribution to the increase in velocity.

Prediction of a new body shape index and body adiposity estimator for development of type 2 diabetes mellitus: The Rural Chinese Cohort Study.

PubMed

Han, Chengyi; Liu, Yu; Sun, Xizhuo; Luo, Xinping; Zhang, Lu; Wang, Bingyuan; Ren, Yongcheng; Zhou, Junmei; Zhao, Yang; Zhang, Dongdong; Liu, Xuejiao; Zhang, Ming; Hu, Dongsheng

2017-11-01

To compare the ability of a body shape index (ABSI) and body adiposity estimator (BAE) to BMI, waist circumference (WC) and waist:height ratio (WHtR) for predicting development of type 2 diabetes mellitus (T2DM) in rural adult Chinese. The prospective cohort study included 11 687 eligible participants who were free of T2DM at baseline. The risk of new-onset T2DM for ABSI, BAE, BMI, WC and WHtR quintiles was estimated by Cox proportional-hazards regression at follow-up. We also compared the power of ABSI and BAE to BMI, WC and WHtR for predicting the development of T2DM. With increasing ABSI, BAE, BMI, WC and WHtR, T2DM incidence was substantially increased (P trend<0·0001). After adjustment for multi-covariates, risk of T2DM was increased from the second to fifth quintile as compared with first quintile for ABSI (1·27; 95 % CI 0·95, 1·69; 1·35; 95 % CI 1·00, 1·82; 1·75; 95 % CI 1·33, 2·32 and 1·87; 95 % CI 1·40, 2·49; P trend<0·0001); BAE (1·82; 95 % CI 1·38, 2·41; 1·93; 95 % CI 1·38, 2·68; 2·73; 95 % CI 1·94, 3·84 and 4·18; 95 % CI 2·98, 5·87; P trend<0·0001); BMI (1·42; 95 % CI 1·03, 1·97; 1·62; 95 % CI 1·18, 2·23; 2·59; 95 % CI 1·92, 3·50 and 3·90; 95 % CI 2·90, 5·26; P trend<0·0001); WC (1·53; 95 % CI 1·08, 2·17; 1·66; 95 % CI 1·18, 2·33; 2·72; 1·97, 3·76 and 4·09; 95 % CI 2·97, 5·62; P trend<0·0001); and WHtR (1·40; 95 % CI 0·98, 1·99; 2·06; 95 % CI 1·47, 2·88; 2·90; 95 % CI 2·10, 4·01 and 4·22; 95 % CI 3·05, 5·85; P trend<0·0001). ABSI, BAE, BMI, WC and WHR were effective and comparable in discriminating cases from non-cases of T2DM. Risk of T2DM was increased with elevated ABSI and BAE, but the predictive ability for T2DM did not differ than that of BMI, WC and WHtR in a rural Chinese population.

Predictive value of T2 relative signal intensity for response to somatostatin analogs in newly diagnosed acromegaly.

PubMed

Shen, Ming; Zhang, Qilin; Liu, Wenjuan; Wang, Meng; Zhu, Jingjing; Ma, Zengyi; He, Wenqiang; Li, Shiqi; Shou, Xuefei; Li, Yiming; Zhang, Zhaoyun; Ye, Hongying; He, Min; Lu, Bin; Yao, Zhenwei; Lu, Yun; Qiao, Nidan; Ye, Zhao; Zhang, Yichao; Yang, Yeping; Zhao, Yao; Wang, Yongfei

2016-11-01

The difficulty of predicting the efficacy of somatostatin analogs (SSA) is not fully resolved. Here, we quantitatively evaluated the predictive value of relative signal intensity (rSI) on T1- and T2-weighted magnetic resonance imaging (MRI) for the short-term efficacy (3 months) of SSA therapy in patients with active acromegaly and assessed the correlation between MRI rSI and expression of somatostatin receptors (SSTR). This was a retrospective review of prospectively recorded data. Ninety-two newly diagnosed patients (37 males and 55 females) with active acromegaly were recruited. All patients were treated with pre-surgical SSA, followed by reassessment and transspenoidal surgery. rSI values were generated by calculating the ratio of SI in the tumor to the SI of normal frontal white matter. The Youden indices were calculated to determine the optimal cutoff of rSI to determine the efficacy of SSA. The correlation between rSI and expression of SSTR2/5 was analyzed by the Spearman rank correlation coefficient. T2 rSI was strongly correlated with biochemical sensitivity to SSA. The cutoff value of T2 rSI to distinguish biochemical sensitivity was 1.205, with a positive predictive value (PPV) of 81.5 % and a negative predictive value (NPV) of 77.3 %. No correlation was found between MRI and tumor size sensitivity. Moreover, T2 rSI was negatively correlated with the expression of SSTR5. T2 rSI correlates with the expression of SSTR5 and quantitatively predicts the biochemical efficacy of SSA in acromegaly.

Methods of increasing net work output of organic Rankine cycles for low-grade waste heat recovery with a detailed analysis using a zeotropic working fluid mixture and scroll expander

NASA Astrophysics Data System (ADS)

Woodland, Brandon Jay

An organic Rankine cycle (ORC) is a thermodynamic cycle that is well-suited for waste heat recovery. It is generally employed for waste heat with temperatures in the range of 80 °C -- 300 °C. When the application is strictly to convert waste heat into work, thermal efficiency is not recommended as a key performance metric. In such an application, maximization of the net power output should be the objective rather than maximization of the thermal efficiency. Two alternative cycle configurations that can increase the net power produced from a heat source with a given temperature and flow rate are proposed and analyzed. These cycle configurations are 1) an ORC with two-phase flash expansion and 2) an ORC with a zeotropic working fluid mixture (ZRC). A design-stage ORC model is presented for consistent comparison of multiple ORC configurations. The finite capacity of the heat source and heat sink fluids is a key consideration in this model. Of all working fluids studied for the baseline ORC, R134a and R245fa yield the highest net power output from a given heat source. Results of the design-stage model indicate that the ORC with two-phase flash expansion offers the most improvement over the baseline ORC. However, the level of improvement that could be achieved in practice is highly uncertain due to the requirement of highly efficient two-phase expansion. The ZRC shows improvement over the baseline as long as the condenser fan power requirement is not negligible. At the highest estimated condenser fan power, the ZRC shows the most improvement, while the ORC with flash expansion is no longer beneficial. The ZRC was selected for detailed study because it does not require two-phase expansion. An experimental test rig was used to evaluate baseline ORC performance with R134a and with R245fa. The ZRC was tested on the same rig with a mixture of 62.5% R134a and 37.5% R245fa. The tested expander is a minimally-modified, of-the-shelf automotive scroll compressor. The high performance to cost ratio of this machine lends significant credence to the economic viability of small-scale, low-temperature ORCs. The experimental campaign covered two heat source temperatures, the full range of pump and expander speeds, a full range of heat source and heat sink fluid flow rates, and various charge levels for the three working fluids. This resulted in 366 steady-state measurements. The steady state measurements are used to develop a detailed ORC model. The model is based on multi-fluid performance maps for the pump and expander and a robust moving-boundary heat exchanger model. It is validated against the measured data and predicts the net power output of the tested ORC with a mean absolute percent error of 7.16%. Comparisons made with the detailed model confirm the predictions of the design-stage model. Using a conservative estimate of the condenser fan power, 19.1% improvement of the ZRC over the baseline ORC is indicated for a source temperature of 80 °C. For a 100 °C source temperature, 13.8% improvement is indicated. A key feature of the detailed ORC model is that it calculates the charge inventory of the working fluid in each heat exchanger and line set. Total system charge can also be specified as a model input. The model can represent the total charge well for R134a at low measured charge levels. As the measured charge level increases, the model becomes less accurate. Reasons for the deviation of the model at higher charge are investigated. It is expected that a charge tuning scheme could be employed to improve the accuracy of model-predicted charge.

The Importance of Strength and Power on Key Performance Indicators in Elite Youth Soccer.

PubMed

Wing, Christopher E; Turner, Anthony N; Bishop, Chris J

2018-01-24

The purpose of this investigation was to examine the importance of strength and power in relation to key performance indicators (KPI's) within competitive soccer match play. This was achieved through using an experimental approach where fifteen subjects were recruited from a professional soccer club's scholarship squad during the 2013/14 season. Following anthropometric measures, power and strength were assessed across a range of tests which included the squat jump (SJ), countermovement jump (CMJ), 20 metre (m) sprint and arrowhead change of direction test. A predicted 1-repetition maximum (RM) was also obtained for strength by performing a 3RM test for both the back squat and bench press and a total score of athleticism (TSA) was provided by summing z-scores for all fitness tests together, providing one complete score for athleticism. Performance analysis data was collected during 16 matches for the following KPIs: passing, shooting, dribbling, tackling and heading. Alongside this, data concerning player ball involvements (touches) was recorded. Results showed that there was a significant correlation (p < 0.05) between CMJ (r = 0.80), SJ (r = 0.79) and TSA (r = 0.64) in relation to heading success. Similarly, a significant correlation (p < 0.05) between predicted 1RM squat strength and tackle success (r = 0.61). These data supports the notion that strength and power training are important to soccer performance, particularly when players are required to win duels of a physical nature. There were no other relationships found between the fitness data and the KPI's recorded during match play which may indicate that other aspects of player's development such as technical skill, cognitive function and sensory awareness are more important for soccer-specific performance.

Comparison of Mental Toughness and Power Test Performances in High-Level Kickboxers by Competitive Success

PubMed Central

Slimani, Maamer; Miarka, Bianca; Briki, Walid; Cheour, Foued

2016-01-01

Background Kickboxing is a high-intensity intermittent striking combat sport, which is characterized by complex skills and tactical key actions with short duration. Objectives The present study compared and verified the relationship between mental toughness (MT), countermovement jump (CMJ) and medicine ball throw (MBT) power tests by outcomes of high-level kickboxers during National Championship. Materials and Methods Thirty two high-level male kickboxers (winner = 16 and loser = 16: 21.2 ± 3.1 years, 1.73 ± 0.07 m, and 70.2 ± 9.4 kg) were analyzed using the CMJ, MBT tests and sports mental toughness questionnaire (SMTQ; based in confidence, constancy and control subscales), before the fights of the 2015 national championship (16 bouts). In statistical analysis, Mann-Withney test and a multiple linear regression were used to compare groups and to observe relationships, respectively, P ≤ 0.05. Results The present results showed significant differences between losers vs. winners, respectively, of total MT (7(7;8) vs. 11(10.2;11), confidence (3(3;3) vs. 4(4;4)), constancy (2(2;2) vs. 3(3;3)), control (2(2;3) vs. 4(4;4)) subscales and MBT (4.1(4;4.3) vs. 4.6(4.4;4.8)). The multiple linear regression showed a strong associations between MT results and outcome (r = 0.89), MBT (r = 0.84) and CMJ (r = 0.73). Conclusions The findings suggest that MT will be more predictive of performance in those sports and in the outcome of competition. PMID:27625755

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

3D-QSAR comparative molecular field analysis on opioid receptor antagonists: pooling data from different studies.

PubMed

Peng, Youyi; Keenan, Susan M; Zhang, Qiang; Kholodovych, Vladyslav; Welsh, William J

2005-03-10

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were constructed using comparative molecular field analysis (CoMFA) on a series of opioid receptor antagonists. To obtain statistically significant and robust CoMFA models, a sizable data set of naltrindole and naltrexone analogues was assembled by pooling biological and structural data from independent studies. A process of "leave one data set out", similar to the traditional "leave one out" cross-validation procedure employed in partial least squares (PLS) analysis, was utilized to study the feasibility of pooling data in the present case. These studies indicate that our approach yields statistically significant and highly predictive CoMFA models from the pooled data set of delta, mu, and kappa opioid receptor antagonists. All models showed excellent internal predictability and self-consistency: q(2) = 0.69/r(2) = 0.91 (delta), q(2) = 0.67/r(2) = 0.92 (mu), and q(2) = 0.60/r(2) = 0.96 (kappa). The CoMFA models were further validated using two separate test sets: one test set was selected randomly from the pooled data set, while the other test set was retrieved from other published sources. The overall excellent agreement between CoMFA-predicted and experimental binding affinities for a structurally diverse array of ligands across all three opioid receptor subtypes gives testimony to the superb predictive power of these models. CoMFA field analysis demonstrated that the variations in binding affinity of opioid antagonists are dominated by steric rather than electrostatic interactions with the three opioid receptor binding sites. The CoMFA steric-electrostatic contour maps corresponding to the delta, mu, and kappa opioid receptor subtypes reflected the characteristic similarities and differences in the familiar "message-address" concept of opioid receptor ligands. Structural modifications to increase selectivity for the delta over mu and kappa opioid receptors have been predicted on the basis of the CoMFA contour maps. The structure-activity relationships (SARs) together with the CoMFA models should find utility for the rational design of subtype-selective opioid receptor antagonists.

A model of prediction and cross-validation of fat-free mass in men with motor complete spinal cord injury.

PubMed

Gorgey, Ashraf S; Dolbow, David R; Gater, David R

2012-07-01

To establish and validate prediction equations by using body weight to predict legs, trunk, and whole-body fat-free mass (FFM) in men with chronic complete spinal cord injury (SCI). Cross-sectional design. Research setting in a large medical center. Individuals with SCI (N=63) divided into prediction (n=42) and cross-validation (n=21) groups. Not applicable. Whole-body FFM and regional FFM were determined by using dual-energy x-ray absorptiometry. Body weight was measured by using a wheelchair weighing scale after subtracting the weight of the chair. Body weight predicted legs FFM (legs FFM=.09×body weight+6.1; R(2)=.25, standard error of the estimate [SEE]=3.1kg, P<.01), trunk FFM (trunk FFM=.21×body weight+8.6; R(2)=.56, SEE=3.6kg, P<.0001), and whole-body FFM (whole-body FFM=.288×body weight+26.3; R(2)=.53, SEE=5.3kg, P<.0001). The whole-body FFM(predicted) (FFM predicted from the derived equations) shared 86% of the variance in whole-body FFM(measured) (FFM measured using dual-energy x-ray absorptiometry scan) (R(2)=.86, SEE=1.8kg, P<.0001), 69% of trunk FFM(measured), and 66% of legs FFM(measured). The trunk FFM(predicted) shared 69% of the variance in trunk FFM(measured) (R(2)=.69, SEE=2.7kg, P<.0001), and legs FFM(predicted) shared 67% of the variance in legs FFM(measured) (R(2)=.67, SEE=2.8kg, P<.0001). Values of FFM did not differ between the prediction and validation groups. Body weight can be used to predict whole-body FFM and regional FFM. The predicted whole-body FFM improved the prediction of trunk FFM and legs FFM. Copyright © 2012 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

QSAR Modeling of Rat Acute Toxicity by Oral Exposure

PubMed Central

Zhu, Hao; Martin, Todd M.; Ye, Lin; Sedykh, Alexander; Young, Douglas M.; Tropsha, Alexander

2009-01-01

Few Quantitative Structure-Activity Relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity endpoints. In this study, a comprehensive dataset of 7,385 compounds with their most conservative lethal dose (LD50) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire dataset was selected that included all 3,472 compounds used in the TOPKAT’s training set. The remaining 3,913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R2 of linear regression between actual and predicted LD50 values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R2 ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD50 for every compound using all 5 models. The consensus models afforded higher prediction accuracy for the external validation dataset with the higher coverage as compared to individual constituent models. The validated consensus LD50 models developed in this study can be used as reliable computational predictors of in vivo acute toxicity. PMID:19845371

Quantitative structure-activity relationship modeling of rat acute toxicity by oral exposure.

PubMed

Zhu, Hao; Martin, Todd M; Ye, Lin; Sedykh, Alexander; Young, Douglas M; Tropsha, Alexander

2009-12-01

Few quantitative structure-activity relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity end points. In this study, a comprehensive data set of 7385 compounds with their most conservative lethal dose (LD(50)) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire data set was selected that included all 3472 compounds used in TOPKAT's training set. The remaining 3913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R(2) of linear regression between actual and predicted LD(50) values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R(2) ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD(50) for every compound using all five models. The consensus models afforded higher prediction accuracy for the external validation data set with the higher coverage as compared to individual constituent models. The validated consensus LD(50) models developed in this study can be used as reliable computational predictors of in vivo acute toxicity.

Correlates of a Single-Item Indicator Versus a Multi-Item Scale of Outness About Same-Sex Attraction

PubMed Central

Noor, Syed W.; Galos, Dylan L.; Simon Rosser, B. R.

2017-01-01

In this study, we investigated if a single-item indicator measured the degree to which people were open about their same-sex attraction (“out”) as accurately as a multi-item scale. For the multi-item scale, we used the Outness Inventory, which includes three subscales: family, world, and religion. We examined correlations between the single- and multi-item measures; between the single-item indicator and the subscales of the multi-item scale; and between the measures and internalized homonegativity, social attitudes towards homosexuality, and depressive symptoms. In addition, we calculated Tjur’s R2 as a measure of predictive power of the single-item indicator, multi-item scale, and subscales of the multi-item scale in predicting two health-related outcomes: depressive symptoms and condomless anal sex with multiple partners. There was a strong correlation between the single- and multi-item measures (r = 0.73). Furthermore, there were strong correlations between the single-item indicator and each subscale of the multi-item scale: family (r = 0.70), world (r = 0.77), and religion (r = 0.50). In addition, the correlations between the single-item indicator and internalized homonegativity (r = −0.63), social attitudes towards homosexuality (r = −0.38), and depression (r = −0.14) were higher than those between the multi-item scale and internalized homonegativity (r = −0.55), social attitudes towards homosexuality (r = −0.21), and depression (r = −0.13). Contrary to the premise that multi-item measures are superior to single-item measures, our collective findings indicate that the single-item indicator of outness performs better than the multi-item scale of outness. PMID:26292840

[Spectral reflectance characteristics and modeling of typical Takyr Solonetzs water content].

PubMed

Zhang, Jun-hua; Jia, Ke-li

2015-03-01

Based on the analysis of the spectral reflectance of the typical Takyr Solonetzs soil in Ningxia, the relationship of soil water content and spectral reflectance was determined, and a quantitative model for the prediction of soil water content was constructed. The results showed that soil spectral reflectance decreased with the increasing soil water content when it was below the water holding capacity but increased with the increasing soil water content when it was higher than the water holding capacity. Soil water content presented significantly negative correlation with original reflectance (r), smooth reflectance (R), logarithm of reflectance (IgR), and positive correlation with the reciprocal of R and logarithm of reciprocal [lg (1/R)]. The correlation coefficient of soil water content and R in the whole wavelength was 0.0013, 0.0397 higher than r and lgR, respectively. Average correlation coefficient of soil water content with 1/R and [lg (1/R)] at the wavelength of 950-1000 nm was 0.2350 higher than that of 400-950 nm. The relationships of soil water content with the first derivate differential (R') , the first derivate differential of logarithm (lgR)' and the first derivate differential of logarithm of reciprocal [lg(1/R)]' were unstable. Base on the coefficients of r, lg(1/R), R' and (lgR)', different regression models were established to predict soil water content, and the coefficients of determination were 0.7610, 0.8184, 0.8524 and 0.8255, respectively. The determination coefficient for power function model of R'. reached 0.9447, while the fitting degree between the predicted value based on this model and on-site measured value was 0.8279. The model of R' had the highest fitted accuracy, while that of r had the lowest one. The results could provide a scientific basis for soil water content prediction and field irrigation in the Takyr Solonetzs region.

Assessment of Fecal Near-infrared Spectroscopy to Predict Feces Chemical Composition and Apparent Total Tract Digestibility of Nutrients in Pigs.

PubMed

Nirea, K G; Pérez de Nanclares, M; Skugor, A; Afseth, N K; Meuwissen, T H E; Hansen, J Ø; Mydland, L T; Øverland, M

2018-05-08

Apparent total tract digestibility (ATTD) of nutrients could be an alternative measure of feed efficiency when breeding for robust animals that are fed fiber-rich diets. Apparent total tract digestibility of nutrients requires measuring individual feed intake of a large number of animals which is expensive and complex. Alternatively, ATTD of nutrients and feces chemical composition can be predicted using fecal near-infrared spectroscopy (FNIRS). The objective of this study was to assess if the feces chemical composition and ATTD of nutrients can be predicted using FNIRS that originate from various pig experimental datasets. Fecal samples together with detailed information on the feces chemical composition and ATTD of nutrients were obtained from four different pig experiments. Feces near-infrared spectroscopy were analyzed from fecal samples of a complete dataset. The model was calibrated using the FNIRS and reference samples of feces chemical composition and ATTD of nutrients. The robustness and predictability of the model was evaluated by the r2 and the closeness between SE of calibration (SEC) and SE of cross-validation (SECV). Prediction of the feces chemical components and ATTD of nutrients was successful as SEC and SECV were equivalent. Calibration model was developed to estimate the ATTD of nutrients and fecal chemical composition from the FNIRS and worked well for OM (r2 = 0.94; SEC = 48.5; SECV = 56.6), CP ( r2 = 0.89; SEC = 18.1; SECV = 18.8), GE ( r2 = 0.92; SEC = 1.2; SECV = 1.4), NDF (r2 = 0.94 ; SEC = 55; SECV = 60.2), OM digestibility (r2 = 0.94; SEC = 5.5; SECV = 6.7), GE digestibility (r2 = 0.88; SEC = 2.3; SECV = 2.6) and fat digestibility (r2 = 0.79 ; SEC = 6, SECV = 6.8). However, the SE of prediction was slightly higher than what has been reported in another study. The prediction of feces chemical composition for fat (r2 = 0.69; SEC = 11.7, SECV = 12.3), CP digestibility (r2 = 0.63; SEC = 2.3; SECV = 2.7) and NDF digestibility (r2 = 0.64, SEC = 7.7, SECV = 8.8) was moderate. We conclude that the FNIRS accurately predicts the chemical composition of feces and ATTD of nutrients for OM, CP and GE. The approach of FNIRS is a cost-effective method for measuring digestibility and feed efficiency in a large-scale pig breeding programs.

Efficacy of extracting indices from large-scale acoustic recordings to monitor biodiversity.

PubMed

Buxton, Rachel; McKenna, Megan F; Clapp, Mary; Meyer, Erik; Stabenau, Erik; Angeloni, Lisa M; Crooks, Kevin; Wittemyer, George

2018-04-20

Passive acoustic monitoring has the potential to be a powerful approach for assessing biodiversity across large spatial and temporal scales. However, extracting meaningful information from recordings can be prohibitively time consuming. Acoustic indices offer a relatively rapid method for processing acoustic data and are increasingly used to characterize biological communities. We examine the ability of acoustic indices to predict the diversity and abundance of biological sounds within recordings. First we reviewed the acoustic index literature and found that over 60 indices have been applied to a range of objectives with varying success. We then implemented a subset of the most successful indices on acoustic data collected at 43 sites in temperate terrestrial and tropical marine habitats across the continental U.S., developing a predictive model of the diversity of animal sounds observed in recordings. For terrestrial recordings, random forest models using a suite of acoustic indices as covariates predicted Shannon diversity, richness, and total number of biological sounds with high accuracy (R 2 > = 0.94, mean squared error MSE < = 170.2). Among the indices assessed, roughness, acoustic activity, and acoustic richness contributed most to the predictive ability of models. Performance of index models was negatively impacted by insect, weather, and anthropogenic sounds. For marine recordings, random forest models predicted Shannon diversity, richness, and total number of biological sounds with low accuracy (R 2 < = 0.40, MSE > = 195), indicating that alternative methods are necessary in marine habitats. Our results suggest that using a combination of relevant indices in a flexible model can accurately predict the diversity of biological sounds in temperate terrestrial acoustic recordings. Thus, acoustic approaches could be an important contribution to biodiversity monitoring in some habitats in the face of accelerating human-caused ecological change. This article is protected by copyright. All rights reserved.

S100b and BNP predict functional neurological outcome after intracerebral hemorrhage

PubMed Central

James, Michael L.; Blessing, Robert; Phillips-Bute, Barbara G.; Bennett, Ellen; Laskowitz, Daniel T.

2009-01-01

Objective To determine the predictive value of S100b and brain natriuretic peptide (BNP) to accurately and quickly determine discharge prognosis after primary supratentorial intracerebral hemorrhage (ICH). Methods After IRB approval and informed consent, blood samples were obtained and analyzed from 28 adult patients consecutively admitted to the neuroscience intensive care unit with computed tomography-proven supratentorial ICH from June 2003 and December 2004 within the first 24 h after symptom onset for S100b and BNP. Functional outcomes on discharge were dichotomized to favorable (mRS<3) or unfavorable. Results BNP (a neurohormone) and S100b (a marker of glial activation) were found to be independently highly predictive of functional neurological outcome at the time of discharge as measured by modified Rankin Score (BNP:p<0.01, r=0.46; S100b: p<0.01, r=0.42) and Barthel Index (BNP:p<0.01, r=0.54; s100b:p<0.01, r=0.50). Although inclusion of either biomarker produced additive value when included with traditional clinical prognostic variables, such as the ICH Score (Barthel index: p<0.01, r=0.66; mRS:p<0.01, r=0.96), little predictive power is added with inclusion of both biomarkers in a regression model for neurological outcome. Conclusions Serum S100b and BNP levels in the first 24 h after injury accurately predict neurological function at discharge after supratentorial ICH. PMID:19505208

Will Big Data Close the Missing Heritability Gap?

PubMed

Kim, Hwasoon; Grueneberg, Alexander; Vazquez, Ana I; Hsu, Stephen; de Los Campos, Gustavo

2017-11-01

Despite the important discoveries reported by genome-wide association (GWA) studies, for most traits and diseases the prediction R-squared (R-sq.) achieved with genetic scores remains considerably lower than the trait heritability. Modern biobanks will soon deliver unprecedentedly large biomedical data sets: Will the advent of big data close the gap between the trait heritability and the proportion of variance that can be explained by a genomic predictor? We addressed this question using Bayesian methods and a data analysis approach that produces a surface response relating prediction R-sq. with sample size and model complexity ( e.g. , number of SNPs). We applied the methodology to data from the interim release of the UK Biobank. Focusing on human height as a model trait and using 80,000 records for model training, we achieved a prediction R-sq. in testing ( n = 22,221) of 0.24 (95% C.I.: 0.23-0.25). Our estimates show that prediction R-sq. increases with sample size, reaching an estimated plateau at values that ranged from 0.1 to 0.37 for models using 500 and 50,000 (GWA-selected) SNPs, respectively. Soon much larger data sets will become available. Using the estimated surface response, we forecast that larger sample sizes will lead to further improvements in prediction R-sq. We conclude that big data will lead to a substantial reduction of the gap between trait heritability and the proportion of interindividual differences that can be explained with a genomic predictor. However, even with the power of big data, for complex traits we anticipate that the gap between prediction R-sq. and trait heritability will not be fully closed. Copyright © 2017 by the Genetics Society of America.

Will Big Data Close the Missing Heritability Gap?

PubMed Central

Kim, Hwasoon; Grueneberg, Alexander; Vazquez, Ana I.; Hsu, Stephen; de los Campos, Gustavo

2017-01-01

Despite the important discoveries reported by genome-wide association (GWA) studies, for most traits and diseases the prediction R-squared (R-sq.) achieved with genetic scores remains considerably lower than the trait heritability. Modern biobanks will soon deliver unprecedentedly large biomedical data sets: Will the advent of big data close the gap between the trait heritability and the proportion of variance that can be explained by a genomic predictor? We addressed this question using Bayesian methods and a data analysis approach that produces a surface response relating prediction R-sq. with sample size and model complexity (e.g., number of SNPs). We applied the methodology to data from the interim release of the UK Biobank. Focusing on human height as a model trait and using 80,000 records for model training, we achieved a prediction R-sq. in testing (n = 22,221) of 0.24 (95% C.I.: 0.23–0.25). Our estimates show that prediction R-sq. increases with sample size, reaching an estimated plateau at values that ranged from 0.1 to 0.37 for models using 500 and 50,000 (GWA-selected) SNPs, respectively. Soon much larger data sets will become available. Using the estimated surface response, we forecast that larger sample sizes will lead to further improvements in prediction R-sq. We conclude that big data will lead to a substantial reduction of the gap between trait heritability and the proportion of interindividual differences that can be explained with a genomic predictor. However, even with the power of big data, for complex traits we anticipate that the gap between prediction R-sq. and trait heritability will not be fully closed. PMID:28893854

A computational biology approach of a genome-wide screen connected miRNAs to obesity and type 2 diabetes.

PubMed

Gottmann, Pascal; Ouni, Meriem; Saussenthaler, Sophie; Roos, Julian; Stirm, Laura; Jähnert, Markus; Kamitz, Anne; Hallahan, Nicole; Jonas, Wenke; Fritsche, Andreas; Häring, Hans-Ulrich; Staiger, Harald; Blüher, Matthias; Fischer-Posovszky, Pamela; Vogel, Heike; Schürmann, Annette

2018-05-01

Obesity and type 2 diabetes (T2D) arise from the interplay between genetic, epigenetic, and environmental factors. The aim of this study was to combine bioinformatics and functional studies to identify miRNAs that contribute to obesity and T2D. A computational framework (miR-QTL-Scan) was applied by combining QTL, miRNA prediction, and transcriptomics in order to enhance the power for the discovery of miRNAs as regulative elements. Expression of several miRNAs was analyzed in human adipose tissue and blood cells and miR-31 was manipulated in a human fat cell line. In 17 partially overlapping QTL for obesity and T2D 170 miRNAs were identified. Four miRNAs (miR-15b, miR-30b, miR-31, miR-744) were recognized in gWAT (gonadal white adipose tissue) and six (miR-491, miR-455, miR-423-5p, miR-132-3p, miR-365-3p, miR-30b) in BAT (brown adipose tissue). To provide direct functional evidence for the achievement of the miR-QTL-Scan, miR-31 located in the obesity QTL Nob6 was experimentally analyzed. Its expression was higher in gWAT of obese and diabetic mice and humans than of lean controls. Accordingly, 10 potential target genes involved in insulin signaling and adipogenesis were suppressed. Manipulation of miR-31 in human SGBS adipocytes affected the expression of GLUT4, PPARγ, IRS1, and ACACA. In human peripheral blood mononuclear cells (PBMC) miR-15b levels were correlated to baseline blood glucose concentrations and might be an indicator for diabetes. Thus, miR-QTL-Scan allowed the identification of novel miRNAs relevant for obesity and T2D. Copyright © 2018 The Authors. Published by Elsevier GmbH.. All rights reserved.

Computer-Aided Decision Making.

DTIC Science & Technology

1988-04-01

Center at Gunter APS, Alabama, 1% predicts that 150.000 more microcomputers, with integrated software, will be VP aided !,: the A:r Fcrce inventory...a computer’s power when he said, ’it is also useful to anticipate or predict changes in the data Pondering ’what if’ situations enabled me to answer... predict future b) experts forecast In Isolation, then consensus is found C. Group decision making (3t30-34) Slide i-i 1. Advantages a. broader background 1

Prediction of Tennis Performance in Junior Elite Tennis Players

PubMed Central

Kramer, Tamara; Huijgen, Barbara C.H.; Elferink-Gemser, Marije T.; Visscher, Chris

2017-01-01

Predicting current and future tennis performance can lead to improving the development of junior tennis players. The aim of this study is to investigate whether age, maturation, or physical fitness in junior elite tennis players in U13 can explain current and future tennis performance. The value of current tennis performance for future tennis performance is also investigated. A total of 86 junior elite tennis players (boys, n = 44; girls, n = 42) U13 (aged: 12.5 ± 0.3 years), and followed to U16, took part in this study. All players were top-30 ranked on the Dutch national ranking list at U13, and top-50 at U16. Age, maturation, and physical fitness, were measured at U13. A principal component analysis was used to extract four physical components from eight tests (medicine ball throwing overhead and reverse, ball throwing, SJ, CMJas, Sprint 5 and 10 meter, and the spider test). The possible relationship of age, maturation, and the physical components; “upper body power”, “lower body power”, “speed”, and “agility” with tennis performance at U13 and U16 was analyzed. Tennis performance was measured by using the ranking position on the Dutch national ranking list at U13 and U16. Regression analyses were conducted based on correlations between variables and tennis performance for boys and girls, separately. In boys U13, positive correlations were found between upper body power and tennis performance (R2 is 25%). In girls, positive correlations between maturation and lower body power with tennis performance were found at U13. Early maturing players were associated with a better tennis performance (R2 is 15%). In girls U16, only maturation correlated with tennis performance (R2 is 13%); later-maturing girls at U13 had better tennis performances at U16. Measuring junior elite tennis players at U13 is important for monitoring their development. These measurements did not predict future tennis performance of junior elite tennis players three years later. Future research should focus on other aspects in order to predict tennis performance better. Key points In boys, tennis performance can be partly explained by upper body power at U13, it is not a predictor for performance at U16. In girls, APHV is of influence for tennis performance at U13 and U16. At younger age earlier-matured girls were ranked higher, however at U16 later-matured girls were ranked higher. Overall, physical fitness in junior tennis is important for monitoring physical fitness development however this should not solely be used for selection criteria in a homogenous group of junior elite players. PMID:28344446

Evaluation of body weight of sea cucumber Apostichopus japonicus by computer vision

NASA Astrophysics Data System (ADS)

Liu, Hui; Xu, Qiang; Liu, Shilin; Zhang, Libin; Yang, Hongsheng

2015-01-01

A postichopus japonicus (Holothuroidea, Echinodermata) is an ecological and economic species in East Asia. Conventional biometric monitoring method includes diving for samples and weighing above water, with highly variable in weight measurement due to variation in the quantity of water in the respiratory tree and intestinal content of this species. Recently, video survey method has been applied widely in biometric detection on underwater benthos. However, because of the high flexibility of A. japonicus body, video survey method of monitoring is less used in sea cucumber. In this study, we designed a model to evaluate the wet weight of A. japonicus, using machine vision technology combined with a support vector machine (SVM) that can be used in field surveys on the A. japonicus population. Continuous dorsal images of free-moving A. japonicus individuals in seawater were captured, which also allows for the development of images of the core body edge as well as thorn segmentation. Parameters that include body length, body breadth, perimeter and area, were extracted from the core body edge images and used in SVM regression, to predict the weight of A. japonicus and for comparison with a power model. Results indicate that the use of SVM for predicting the weight of 33 A. japonicus individuals is accurate ( R 2=0.99) and compatible with the power model ( R 2 =0.96). The image-based analysis and size-weight regression models in this study may be useful in body weight evaluation of A. japonicus in lab and field study.

Resistance profile of darunavir: combined 24-week results from the POWER trials.

PubMed

de Meyer, Sandra; Vangeneugden, Tony; van Baelen, Ben; de Paepe, Els; van Marck, Herwig; Picchio, Gaston; Lefebvre, Eric; de Béthune, Marie-Pierre

2008-03-01

The resistance profile of darunavir (TMC114) in treatment-experienced patients was explored using pooled week 24 data from POWER 1, 2, and 3 at the recommended dose of darunavir with low-dose ritonavir (darunavir/r, 600/100 mg bid, N = 458). Baseline darunavir fold change in EC(50) was a strong predictor of virological response at week 24. Preliminary phenotypic clinical cut-offs of 10 and 40 were established. Virological response to darunavir/r was maintained in the presence at baseline of a high number of IAS-USA PI resistance-associated mutations (IAS-USA PI RAMS); a diminished response occurred with >or=14. Eleven protease mutations associated with diminished darunavir/r virological response were identified (V11I, V32I, L33F, I47V, I50V, I54L/M, G73S, L76V, I84V, and L89V). These darunavir resistance-associated mutations (DRV RAMS) occurred in the presence of a high number of IAS-USA PI RAMS. Virological response was diminished with three or more DRV RAMS in the background of a high number of IAS-USA PI RAMS. Incremental numbers of DRV RAMS were more predictive of outcome than were IAS-USA PI RAMS. Mutations developing during darunavir/r virological failure (V32I, L33F, I47V, I54L, and L89V) were also featured in the DRV RAMS list. Site-directed mutants carrying these five mutations, or any one of these mutations either alone or together with one or two IAS-USA PI RAMS, showed no reduced darunavir susceptibility, suggesting that a high number of additional background mutations is required for darunavir resistance. In this population of treatment-experienced patients, darunavir/r demonstrated significantly greater efficacy than investigator-selected control PIs of trials POWER 1 and 2, regardless of baseline viral genotype or phenotype, while exhibiting a high genetic barrier to the development of resistance.

Properties and Cycle Performance of Refrigerant Blends Operating Near and Above the Refrigerant Critical Point, Task 2: Air Conditioner System Study

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

Piotr A. Domanski; W. Vance Payne

2002-10-31

The main goal of this project was to investigate and compare the performance of an R410A air conditioner to that of an R22 air conditioner, with specific interest in performance at high ambient temperatures at which the condenser of the R410A system may be operating above the refrigerant's critical point. Part 1 of this project consisted of conducting comprehensive measurements of thermophysical for refrigerant R125 and refrigerant blends R410A and R507A and developing new equation of state formulations and mixture models for predicting thermophysical properties of HFC refrigerant blends. Part 2 of this project conducted performance measurements of split-system, 3-tonmore » R22 and R410A residential air conditioners in the 80 to 135 F (27.8 to 57.2 C) outdoor temperature range and development of a system performance model. The performance data was used in preparing a beta version of EVAP-COND, a windows-based simulation package for predicting performance of finned-tube evaporators and condensers. The modeling portion of this project also included the formulation of a model for an air-conditioner equipped with a thermal expansion valve (TXV). Capacity and energy efficiency ratio (EER) were measured and compared. The R22 system's performance was measured over the outdoor ambient temperature range of 80 to 135 F (27.8 to 57.2 C). The same test range was planned for the R410A system. However, the compressor's safety system cut off the compressor at the 135.0 F (57.2 C) test temperature. The highest measurement on this system was at 130.0 F (54.4 C). Subsequently, a custom-manufactured R410A compressor with a disabled safety system and a more powerful motor was installed and performance was measured at outdoor temperatures up to 155.0 F (68.3 C). Both systems had similar capacity and EER performance at 82.0 F (27.8 C). The capacity and EER degradation of both systems were nearly linearly dependent with rising ambient outdoor ambient test temperatures. The performance degradation of R410A at higher temperatures was greater than R22. However, the R22 and R410A systems both operated normally during all tests. Visual observations of the R410A system provided no indication of vibrations or TXV hunting at high ambient outdoor test conditions with the compressor operating in the transcritical regime.« less

EOL performance comparison of GaAs/Ge and Si BSF/R solar arrays

NASA Technical Reports Server (NTRS)

Woike, Thomas J.

1993-01-01

EOL power estimates for solar array designs are significantly influenced by the predicted degradation due to charged particle radiation. New radiation-induced power degradation data for GaAs/Ge solar arrays applicable to missions ranging from low earth orbit (LEO) to geosynchronous earth orbit (GEO) and compares these results to silicon BSF/R arrays. These results are based on recently published radiation damage coefficients for GaAs/Ge cells. The power density ratio (GaAs/Ge to Si BSF/R) was found to be as high as 1.83 for the proton-dominated worst-case altitude of 7408 km medium Earth orbit (MEO). Based on the EOL GaAs/Ge solar array power density results for MEO, missions which were previously considered infeasible may be reviewed based on these more favorable results. The additional life afforded by using GaAs/Ge cells is an important factor in system-level trade studies when selecting a solar cell technology for a mission and needs to be considered. The data presented supports this decision since the selected orbits have characteristics similar to most orbits of interest.

Predicting Soil Organic Carbon and Total Nitrogen in the Russian Chernozem from Depth and Wireless Color Sensor Measurements

NASA Astrophysics Data System (ADS)

Mikhailova, E. A.; Stiglitz, R. Y.; Post, C. J.; Schlautman, M. A.; Sharp, J. L.; Gerard, P. D.

2017-12-01

Color sensor technologies offer opportunities for affordable and rapid assessment of soil organic carbon (SOC) and total nitrogen (TN) in the field, but the applicability of these technologies may vary by soil type. The objective of this study was to use an inexpensive color sensor to develop SOC and TN prediction models for the Russian Chernozem (Haplic Chernozem) in the Kursk region of Russia. Twenty-one dried soil samples were analyzed using a Nix Pro™ color sensor that is controlled through a mobile application and Bluetooth to collect CIEL*a*b* (darkness to lightness, green to red, and blue to yellow) color data. Eleven samples were randomly selected to be used to construct prediction models and the remaining ten samples were set aside for cross validation. The root mean squared error (RMSE) was calculated to determine each model's prediction error. The data from the eleven soil samples were used to develop the natural log of SOC (lnSOC) and TN (lnTN) prediction models using depth, L*, a*, and b* for each sample as predictor variables in regression analyses. Resulting residual plots, root mean square errors (RMSE), mean squared prediction error (MSPE) and coefficients of determination ( R 2, adjusted R 2) were used to assess model fit for each of the SOC and total N prediction models. Final models were fit using all soil samples, which included depth and color variables, for lnSOC ( R 2 = 0.987, Adj. R 2 = 0.981, RMSE = 0.003, p-value < 0.001, MSPE = 0.182) and lnTN ( R 2 = 0.980 Adj. R 2 = 0.972, RMSE = 0.004, p-value < 0.001, MSPE = 0.001). Additionally, final models were fit for all soil samples, which included only color variables, for lnSOC ( R 2 = 0.959 Adj. R 2 = 0.949, RMSE = 0.007, p-value < 0.001, MSPE = 0.536) and lnTN ( R 2 = 0.912 Adj. R 2 = 0.890, RMSE = 0.015, p-value < 0.001, MSPE = 0.001). The results suggest that soil color may be used for rapid assessment of SOC and TN in these agriculturally important soils.

Reduced-order model for inertial locomotion of a slender swimmer

NASA Astrophysics Data System (ADS)

Mahalinkam, Raksha; Gong, Felicity; Khair, Aditya S.

2018-04-01

The inertial locomotion of an elongated model swimmer in a Newtonian fluid is quantified, wherein self-propulsion is achieved via steady tangential surface treadmilling. The swimmer has a length 2 l and a circular cross section of longitudinal profile a R (z ) , where a is the characteristic width of the cross section, R (z ) is a dimensionless shape function, and z is a dimensionless coordinate, normalized by l , along the centerline of the body. It is assumed that the swimmer is slender, ɛ =a /l ≪1 . Hence, we utilize slender-body theory to analyze the Navier-Stokes equations that describe the flow around the swimmer. Therefrom, we compute an asymptotic approximation to the swimming speed, U , as U /us=1 -β [V (Re ) -1/2 ∫-11z lnR (z ) d z ] /ln(1 /ɛ ) +O [1 /ln2(1 /ɛ ) ], where us is the characteristic speed of the surface treadmilling, Re is the Reynolds number based on the body length, and β is a dimensionless parameter that differentiates between "pusher" (propelled from the rear, β <0 ) and "puller" (propelled from the front, β >0 ) -type swimmers. The function V (Re ) increases monotonically with increasing Re ; hence, fluid inertia causes an increase (decrease) in the swimming speed of a pusher (puller). Next, we demonstrate that the power expenditure of the swimmer increases monotonically with increasing Re . Further, the power expenditures of a puller and pusher with the same value of |β | are equal. Therefore, pushers are superior in inertial locomotion as compared to pullers, in that they achieve a faster swimming speed for the same power expended. Finally, it is demonstrated that the flow structure predicted from our reduced-order model is consistent with that from direct numerical simulation of swimmers at intermediate Re .

Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms

DOE PAGES

Tramontana, Gianluca; Jung, Martin; Schwalm, Christopher R.; ...

2016-07-29

Spatio-temporal fields of land–atmosphere fluxes derived from data-driven models can complement simulations by process-based land surface models. While a number of strategies for empirical models with eddy-covariance flux data have been applied, a systematic intercomparison of these methods has been missing so far. In this study, we performed a cross-validation experiment for predicting carbon dioxide, latent heat, sensible heat and net radiation fluxes across different ecosystem types with 11 machine learning (ML) methods from four different classes (kernel methods, neural networks, tree methods, and regression splines). We applied two complementary setups: (1) 8-day average fluxes based on remotely sensed data andmore » (2) daily mean fluxes based on meteorological data and a mean seasonal cycle of remotely sensed variables. The patterns of predictions from different ML and experimental setups were highly consistent. There were systematic differences in performance among the fluxes, with the following ascending order: net ecosystem exchange ( R 2 < 0.5), ecosystem respiration ( R 2 > 0.6), gross primary production ( R 2> 0.7), latent heat ( R 2 > 0.7), sensible heat ( R 2 > 0.7), and net radiation ( R 2 > 0.8). The ML methods predicted the across-site variability and the mean seasonal cycle of the observed fluxes very well ( R 2 > 0.7), while the 8-day deviations from the mean seasonal cycle were not well predicted ( R 2 < 0.5). Fluxes were better predicted at forested and temperate climate sites than at sites in extreme climates or less represented by training data (e.g., the tropics). Finally, the evaluated large ensemble of ML-based models will be the basis of new global flux products.« less

Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms

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

Tramontana, Gianluca; Jung, Martin; Schwalm, Christopher R.

Spatio-temporal fields of land–atmosphere fluxes derived from data-driven models can complement simulations by process-based land surface models. While a number of strategies for empirical models with eddy-covariance flux data have been applied, a systematic intercomparison of these methods has been missing so far. In this study, we performed a cross-validation experiment for predicting carbon dioxide, latent heat, sensible heat and net radiation fluxes across different ecosystem types with 11 machine learning (ML) methods from four different classes (kernel methods, neural networks, tree methods, and regression splines). We applied two complementary setups: (1) 8-day average fluxes based on remotely sensed data andmore » (2) daily mean fluxes based on meteorological data and a mean seasonal cycle of remotely sensed variables. The patterns of predictions from different ML and experimental setups were highly consistent. There were systematic differences in performance among the fluxes, with the following ascending order: net ecosystem exchange ( R 2 < 0.5), ecosystem respiration ( R 2 > 0.6), gross primary production ( R 2> 0.7), latent heat ( R 2 > 0.7), sensible heat ( R 2 > 0.7), and net radiation ( R 2 > 0.8). The ML methods predicted the across-site variability and the mean seasonal cycle of the observed fluxes very well ( R 2 > 0.7), while the 8-day deviations from the mean seasonal cycle were not well predicted ( R 2 < 0.5). Fluxes were better predicted at forested and temperate climate sites than at sites in extreme climates or less represented by training data (e.g., the tropics). Finally, the evaluated large ensemble of ML-based models will be the basis of new global flux products.« less

Intermittency in 2D soap film turbulence

NASA Astrophysics Data System (ADS)

Cerbus, R. T.; Goldburg, W. I.

2013-10-01

The Reynolds number dependency of intermittency for 2D turbulence is studied in a flowing soap film. The Reynolds number used here is the Taylor microscale Reynolds number Rλ, which ranges from 20 to 800. Strong intermittency is found for both the inverse energy and direct enstrophy cascades as measured by (a) the pdf of velocity differences P(δu(r)) at inertial scales r, (b) the kurtosis of P(∂xu), and (c) the scaling of the so-called intermittency exponent μ, which is zero if intermittency is absent. Measures (b) and (c) are quantitative, while (a) is qualitative. These measurements are in disagreement with some previous results but not all. The velocity derivatives are nongaussian at all Rλ but show signs of becoming gaussian as Rλ increases beyond the largest values that could be reached. The kurtosis of P(δu(r)) at various r indicates that the intermittency is scale dependent. The structure function scaling exponents also deviate strongly from the Kraichnan prediction. For the enstrophy cascade, the intermittency decreases as a power law in Rλ. This study suggests the need for a new look at the statistics of 2D turbulence.

The use of dual-energy X-ray absorptiometry to estimate the dissected composition of lamb carcasses.

PubMed

Mercier, J; Pomar, C; Marcoux, M; Goulet, F; Thériault, M; Castonguay, F W

2006-06-01

A total of 140 male and female Dorset and Suffolk lambs were slaughtered according to four live weight classes (36-39kg, 41-44kg, 46-49kg and 51-54kg). Total tissue, fat and lean masses, and bone mineral content measured by dual-energy X-ray absorptiometry (DXA) were used to predict dissected tissue weights. The DXA total weights accurately predict half-carcasses and primal cuts weights (shoulder, leg, loin and flank) (R(2)>0.99, CVe<1.3%). The prediction of the half-carcass dissected fat percentage is weaker (R(2)=0.77, CVe=10.4%). Fatness prediction accuracy is equivalent for the shoulder, leg and loin (R(2) between 0.68 and 0.78, CVe between 10% and 13%). The R(2) obtained when predicting dissected lean content from DXA variables is 0.93 for the half-carcass and higher than 0.83 for all cuts other than flank (CVe are between 3.5% and 6.5%, except for the flank, which is 9.1%). The prediction of bone weight using the bone mineral content is not very accurate for the half-carcass, shoulder and leg (R(2): 0.48, 0.47 and 0.43; CVe: 10.2%, 12.0% and 11.6%, respectively). The situation improves, however, for the loin (R(2)=0.70, CVe=10.7%). In conclusion, DXA is an effective technology for predicting total weight and the amount of lean and fat in lamb carcasses and their primal cuts.

Large-Scale Clustering of Galaxies in the CFA Survey

NASA Astrophysics Data System (ADS)

Park, Changbom

1992-03-01

The power spectrum of the galaxy distribution is accuarately measured up to wavelengths over 100h-1 Mpc from the CfA 1 and 2 catalogs. We find that our results agree with power spectra calculated by others from smaller samples of optical, radio and infrared galaxies. The power spectrum of an open CDM model (Omega h = 0.2 and delta8 = 1; see below for definitions) best approximates the observed power spectrum. The power spectrum of the standard CDM model(Omega h = 0.5 and delta8 = 1) is inconsistent with the observed one at the 99% confidence level. Our best estimation of the corresponding correlation function in real space is Xi(r) = (r/6.2h-1 Mpc)^-1.8 for r < 20h-1 Mpc.

Nuclear ribosome biogenesis mediated by the DIM1A rRNA dimethylase is required for organized root growth and epidermal patterning in Arabidopsis.

PubMed

Wieckowski, Yana; Schiefelbein, John

2012-07-01

Position-dependent patterning of hair and non-hair cells in the Arabidopsis thaliana root epidermis is a powerful system to study the molecular basis of cell fate specification. Here, we report an epidermal patterning mutant affecting the ADENOSINE DIMETHYL TRANSFERASE 1A (DIM1A) rRNA dimethylase gene, predicted to participate in rRNA posttranscriptional processing and base modification. Consistent with a role in ribosome biogenesis, DIM1A is preferentially expressed in regions of rapid growth, and its product is nuclear localized with nucleolus enrichment. Furthermore, DIM1A preferentially accumulates in the developing hair cells, and the dim1A point mutant alters the cell-specific expression of the transcriptional regulators GLABRA2, CAPRICE, and WEREWOLF. Together, these findings suggest that establishment of cell-specific gene expression during root epidermis development is dependent upon proper ribosome biogenesis, possibly due to the sensitivity of the cell fate decision to relatively small differences in gene regulatory activities. Consistent with its effect on the predicted S-adenosyl-l-Met binding site, dim1A plants lack the two 18S rRNA base modifications but exhibit normal pre-rRNA processing. In addition to root epidermal defects, the dim1A mutant exhibits abnormal root meristem division, leaf development, and trichome branching. Together, these findings provide new insights into the importance of rRNA base modifications and translation regulation for plant growth and development.

Nuclear Ribosome Biogenesis Mediated by the DIM1A rRNA Dimethylase Is Required for Organized Root Growth and Epidermal Patterning in Arabidopsis[C][W

PubMed Central

Wieckowski, Yana; Schiefelbein, John

2012-01-01

Position-dependent patterning of hair and non-hair cells in the Arabidopsis thaliana root epidermis is a powerful system to study the molecular basis of cell fate specification. Here, we report an epidermal patterning mutant affecting the ADENOSINE DIMETHYL TRANSFERASE 1A (DIM1A) rRNA dimethylase gene, predicted to participate in rRNA posttranscriptional processing and base modification. Consistent with a role in ribosome biogenesis, DIM1A is preferentially expressed in regions of rapid growth, and its product is nuclear localized with nucleolus enrichment. Furthermore, DIM1A preferentially accumulates in the developing hair cells, and the dim1A point mutant alters the cell-specific expression of the transcriptional regulators GLABRA2, CAPRICE, and WEREWOLF. Together, these findings suggest that establishment of cell-specific gene expression during root epidermis development is dependent upon proper ribosome biogenesis, possibly due to the sensitivity of the cell fate decision to relatively small differences in gene regulatory activities. Consistent with its effect on the predicted S-adenosyl-l-Met binding site, dim1A plants lack the two 18S rRNA base modifications but exhibit normal pre-rRNA processing. In addition to root epidermal defects, the dim1A mutant exhibits abnormal root meristem division, leaf development, and trichome branching. Together, these findings provide new insights into the importance of rRNA base modifications and translation regulation for plant growth and development. PMID:22829145

[Quantitative structure-gas chromatographic retention relationship of polycyclic aromatic sulfur heterocycles using molecular electronegativity-distance vector].

PubMed

Li, Zhenghua; Cheng, Fansheng; Xia, Zhining

2011-01-01

The chemical structures of 114 polycyclic aromatic sulfur heterocycles (PASHs) have been studied by molecular electronegativity-distance vector (MEDV). The linear relationships between gas chromatographic retention index and the MEDV have been established by a multiple linear regression (MLR) model. The results of variable selection by stepwise multiple regression (SMR) and the powerful predictive abilities of the optimization model appraised by leave-one-out cross-validation showed that the optimization model with the correlation coefficient (R) of 0.994 7 and the cross-validated correlation coefficient (Rcv) of 0.994 0 possessed the best statistical quality. Furthermore, when the 114 PASHs compounds were divided into calibration and test sets in the ratio of 2:1, the statistical analysis showed our models possesses almost equal statistical quality, the very similar regression coefficients and the good robustness. The quantitative structure-retention relationship (QSRR) model established may provide a convenient and powerful method for predicting the gas chromatographic retention of PASHs.

Exploration of shoulder load during hand-rim wheelchair start-up with and without power-assisted propulsion in experienced wheelchair users.

PubMed

Kloosterman, Marieke G M; Buurke, Jaap H; Schaake, Leendert; Van der Woude, Lucas H V; Rietman, Johan S

2016-05-01

Frequent start movements occurred during the day, yielding high upper-extremity stress. The high incidence and impact of shoulder injury on daily life wheelchair use made it clinically relevant to investigate whether power-assisted propulsion is beneficial during the start. Eleven hand-rim wheelchair users performed a start-movement in an instrumented wheelchair on a flat surface. Test order was randomly assigned to propulsion with and without power-assist. For each subject, parameters were averaged over 3 repeated starts. For statistical analysis Wilcoxon Signed Rank test was used. Intensity of mechanical shoulder loading decreased during power-assisted propulsion for anterior (147.0 (44.8) versus 121.9 (27.4) N; effect size (r)=-.75), posterior (4.8 (14.1) versus 2.7 (11.6) N; r=-.64) and inferior directed forces (82.6 (27.9) versus 68.9 (22.6) N; r=-.78) and abduction (20.2 (14.6) versus 12.9 (7.8) Nm; r=-.88) and extension moments (20.3 (10.7) versus 13.7 (9.1 Nm; r=-.88). Peak resultant force at the rim significantly decreased from 133.5 (38.4) N to 112.2 (25.4) N (r=-.64) and was accompanied by significant decreased shoulder abduction (35.3 (6.7) versus 33.3 (6.8); r=-.67) and significant increased shoulder extension (13.6 (16.3) versus 20.3 (19.1); r=-.78) during power-assisted start-up. Power-assist hand-rim wheelchairs are effective in reducing external shoulder load and partly effective in reducing force generation in extremes of shoulder motion during start-up. The use of power-assist wheels might reduce the risk of developing shoulder overuse injuries. NTR2661. Copyright © 2016 Elsevier Ltd. All rights reserved.

Simulated X-ray galaxy clusters at the virial radius: Slopes of the gas density, temperature and surface brightness profiles

NASA Astrophysics Data System (ADS)

Roncarelli, M.; Ettori, S.; Dolag, K.; Moscardini, L.; Borgani, S.; Murante, G.

2006-12-01

Using a set of hydrodynamical simulations of nine galaxy clusters with masses in the range 1.5 × 1014 < Mvir < 3.4 × 1015Msolar, we have studied the density, temperature and X-ray surface brightness profiles of the intracluster medium in the regions around the virial radius. We have analysed the profiles in the radial range well above the cluster core, the physics of which are still unclear and matter of tension between simulated and observed properties, and up to the virial radius and beyond, where present observations are unable to provide any constraints. We have modelled the radial profiles between 0.3R200 and 3R200 with power laws with one index, two indexes and a rolling index. The simulated temperature and [0.5-2] keV surface brightness profiles well reproduce the observed behaviours outside the core. The shape of all these profiles in the radial range considered depends mainly on the activity of the gravitational collapse, with no significant difference among models including extraphysics. The profiles steepen in the outskirts, with the slope of the power-law fit that changes from -2.5 to -3.4 in the gas density, from -0.5 to -1.8 in the gas temperature and from -3.5 to -5.0 in the X-ray soft surface brightness. We predict that the gas density, temperature and [0.5-2] keV surface brightness values at R200 are, on average, 0.05, 0.60, 0.008 times the measured values at 0.3R200. At 2R200, these values decrease by an order of magnitude in the gas density and surface brightness, by a factor of 2 in the temperature, putting stringent limits on the detectable properties of the intracluster-medium (ICM) in the virial regions.

A Neural Network Design for the Estimation of Nonlinear Behavior of a Magnetically-Excited Piezoelectric Harvester

NASA Astrophysics Data System (ADS)

Çelik, Emre; Uzun, Yunus; Kurt, Erol; Öztürk, Nihat; Topaloğlu, Nurettin

2018-01-01

An application of an artificial neural network (ANN) has been implemented in this article to model the nonlinear relationship of the harvested electrical power of a recently developed piezoelectric pendulum with respect to its resistive load R L and magnetic excitation frequency f. Prediction of harvested power for a wide range is a difficult task, because it increases dramatically when f gets closer to the natural frequency f 0 of the system. The neural model of the concerned system is designed upon the basis of a standard multi-layer network with a back propagation learning algorithm. Input data, termed input patterns, to present to the network and the respective output data, termed output patterns, describing desired network output that are carefully collected from the experiment under several conditions in order to train the developed network accurately. Results have indicated that the designed ANN is an effective means for predicting the harvested power of the piezoelectric harvester as functions of R L and f with a root mean square error of 6.65 × 10-3 for training and 1.40 for different test conditions. Using the proposed approach, the harvested power can be estimated reasonably without tackling the difficulty of experimental studies and complexity of analytical formulas representing the concerned system.

MODELING THE NONLINEAR CLUSTERING IN MODIFIED GRAVITY MODELS. I. A FITTING FORMULA FOR THE MATTER POWER SPECTRUM OF f(R) GRAVITY

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

Zhao, Gong-Bo, E-mail: gongbo@icosmology.info; Institute of Cosmology and Gravitation, University of Portsmouth, Portsmouth PO1 3FX

2014-04-01

Based on a suite of N-body simulations of the Hu-Sawicki model of f(R) gravity with different sets of model and cosmological parameters, we develop a new fitting formula with a numeric code, MGHalofit, to calculate the nonlinear matter power spectrum P(k) for the Hu-Sawicki model. We compare the MGHalofit predictions at various redshifts (z ≤ 1) to the f(R) simulations and find that the relative error of the MGHalofit fitting formula of P(k) is no larger than 6% at k ≤ 1 h Mpc{sup –1} and 12% at k in (1, 10] h Mpc{sup –1}, respectively. Based on a sensitivitymore » study of an ongoing and a future spectroscopic survey, we estimate the detectability of a signal of modified gravity described by the Hu-Sawicki model using the power spectrum up to quasi-nonlinear scales.« less

Detailed Structure of the Outer Disk Around HD 169142 with Polarized Light in H-band

NASA Technical Reports Server (NTRS)

Momose, Munetake; Morita, Ayaka; Fukagawa, Misato; Muto, Takayuki; Takeuchi, Taku; Hashimoto, Jun; Honda, Mitsuhiko; Kudo, Tomoyuki; Okamoto, Yoshiko K.; Kanagawa, Kazuhiro D.;

Physiological correlates of pulmonary function in children with cystic fibrosis.

PubMed

Wells, Greg D; Wilkes, Donna L; Schneiderman, Jane E; Thompson, Sara; Coates, Allan L; Ratjen, Felix

2014-09-01

Although peak aerobic capacity (VO(2peak)) has been linked to outcome in patients with cystic fibrosis (CF), measuring is time consuming, and requires expensive equipment and expertise that is not readily available in all centers. Other fitness parameters such as peak anaerobic power, measures of power and strength may be simpler to deliver in the clinic. The relationship between these measures and established outcomes such as forced expiratory volume in one second (FEV(1)) and peak aerobic power (VO(2peak)) in CF remains unclear. Therefore we evaluated (a) aerobic fitness, (b) anaerobic fitness, and (c) upper and lower body muscle strength to determine their relationship to FEV(1) and VO(2peak) in children with CF. Eighty-two patients (7-18 years) with CF (40 female) from the CF clinic at The Hospital for Sick Children in Toronto performed a maximal incremental cycling test to exhaustion. Anaerobic power (W) for 10 and 30 sec cycling trials as well as vertical jump (VJ) and hand grip strength (HG) were compared to FEV(1) and VO(2peak). Absolute VO(2peak) (R(2)  = 0.16, P < 0.001), anaerobic power (R(2)  = 0.21, P < 0.001), and hand grip strength (R(2)  = 0.10, P = 0.003) were significantly correlated to lung function whereas measures of explosive lower body strength (VJ) were not. Anaerobic power (R(2)  = 0.16, P = 0.001) and hand grip strength (R(2)  = 0.08, P = 0.01) were related to VO(2peak). Vertical jump was correlated with VO(2peak) (R(2)  = 0.29, P < 0.001) but not FEV(1). Simple fitness tests such as hand grip strength and anaerobic cycle tests may be useful indicators of lung health and fitness. © 2013 Wiley Periodicals, Inc.

Hair and bone as predictors of tissular mercury concentration in the western Alaska red fox, Vulpes vulpes.

PubMed

Dainowski, B H; Duffy, L K; McIntyre, J; Jones, P

2015-06-15

We evaluated if total mercury (THg) concentrations of keratin-based and bone-based tissues can predict THg concentrations in skeletal muscle, renal medulla, renal cortex, and liver. The THg concentration in matched tissues of 65 red foxes, Vulpes vulpes, from western Alaska was determined. Hair THg concentration had a significant positive correlation with liver, renal medulla, renal cortex, and muscle. The THg concentration for males and females is moderately predictive of THg concentration in the renal cortex and liver for these foxes based on R(2) values (R(2)=0.61 and 0.63, respectively). Bone is weakly predictive of THg concentration in muscle (R(2)=0.40), but not a reliable tissue to predict THg concentration in liver (R(2)=0.24), renal cortex (R(2)=0.35), or renal medulla (R(2)=0.25). These results confirm the potential use of trapped animals, specifically foxes, as useful Arctic sentinel species to inform researchers about patterns in THg levels over time as industrialization of the Arctic continues. Copyright © 2015 Elsevier B.V. All rights reserved.

Clinical tests of ankle plantarflexor strength do not predict ankle power generation during walking.

PubMed

Kahn, Michelle; Williams, Gavin

2015-02-01

The aim of this study was to investigate the relationship between a clinical test of ankle plantarflexor strength and ankle power generation (APG) at push-off during walking. This is a prospective cross-sectional study of 102 patients with traumatic brain injury. Handheld dynamometry was used to measure ankle plantarflexor strength. Three-dimensional gait analysis was performed to quantify ankle power generation at push-off during walking. Ankle plantarflexor strength was only moderately correlated with ankle power generation at push-off (r = 0.43, P < 0.001; 95% confidence interval, 0.26-0.58). There was also a moderate correlation between ankle plantarflexor strength and self-selected walking velocity (r = 0.32, P = 0.002; 95% confidence interval, 0.13-0.48). Handheld dynamometry measures of ankle plantarflexor strength are only moderately correlated with ankle power generation during walking. This clinical test of ankle plantarflexor strength is a poor predictor of calf muscle function during gait in people with traumatic brain injury.

Self-Powered UV-Near Infrared Photodetector Based on Reduced Graphene Oxide/n-Si Vertical Heterojunction.

PubMed

Li, Guanghui; Liu, Lin; Wu, Guan; Chen, Wei; Qin, Sujie; Wang, Yi; Zhang, Ting

2016-09-01

A novel self-powered photodetector based on reduced graphene oxide (rGO)/n-Si p-n vertical heterojunction with high sensitivity and fast response time is presented. The photodetector contains a p-n vertical heterojunction between a drop-casted rGO thin film and n-Si. Contacts between the semiconductor layer (rGO, n-Si) and source-drain Ti/Au electrodes allow efficient transfer of photogenerated charge carriers. The self-powered UV-near infrared photodetector shows high sensitivity toward a spectrum of light from 365 to 1200 nm. Under the 600 nm illumination (0.81 mW cm -2 ), the device has a photoresponsivity of 1.52 A W -1 , with fast response and recover time (2 ms and 3.7 ms), and the ON/OFF ratios exceed 10 4 when the power density reaches ≈2.5 mW cm -2 . The high photoresponse primarily arises from the built-in electric field formed at the interface of n-Si and rGO film. The effect of rGO thickness, rGO reduction level, and layout of rGO/n-Si effective contact area on device performance are also systematically investigated. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Individual moral judgment and cultural ideologies.

PubMed

Narvaez, D; Getz, I; Rest, J R; Thoma, S J

1999-03-01

Moral judgment cannot be reduced to cultural ideology, or vice versa. But when each construct is measured separately, then combined, the product predicts powerfully to moral thinking. In Study 1, 2 churches (N = 96) were selected for their differences on religious ideology, political identity, and moral judgment. By combining these 3 variables, a multiple correlation of .79 predicted to members' moral thinking (opinions on human rights issues). Study 2 replicated this finding in a secular sample, with the formula established in Study 1 (R = .77). Individual conceptual development in moral judgment and socialization into cultural ideology co-occur, simultaneously and reciprocally, in parallel, and not serially. Individual development in moral judgment provides the epistemological categories for cultural ideology, which in turn influences the course of moral judgment, to produce moral thinking (e.g., opinions about abortion, free speech).

Estimation of body density based on hydrostatic weighing without head submersion in young Japanese adults.

PubMed

Demura, S; Sato, S; Kitabayashi, T

2006-06-01

This study examined a method of predicting body density based on hydrostatic weighing without head submersion (HWwithoutHS). Donnelly and Sintek (1984) developed a method to predict body density based on hydrostatic weight without head submersion. This method predicts the difference (D) between HWwithoutHS and hydrostatic weight with head submersion (HWwithHS) from anthropometric variables (head length and head width), and then calculates body density using D as a correction factor. We developed several prediction equations to estimate D based on head anthropometry and differences between the sexes, and compared their prediction accuracy with Donnelly and Sintek's equation. Thirty-two males and 32 females aged 17-26 years participated in the study. Multiple linear regression analysis was performed to obtain the prediction equations, and the systematic errors of their predictions were assessed by Bland-Altman plots. The best prediction equations obtained were: Males: D(g) = -164.12X1 - 125.81X2 - 111.03X3 + 100.66X4 + 6488.63, where X1 = head length (cm), X2 = head circumference (cm), X3 = head breadth (cm), X4 = head thickness (cm) (R = 0.858, R2 = 0.737, adjusted R2 = 0.687, standard error of the estimate = 224.1); Females: D(g) = -156.03X1 - 14.03X2 - 38.45X3 - 8.87X4 + 7852.45, where X1 = head circumference (cm), X2 = body mass (g), X3 = head length (cm), X4 = height (cm) (R = 0.913, R2 = 0.833, adjusted R2 = 0.808, standard error of the estimate = 137.7). The effective predictors in these prediction equations differed from those of Donnelly and Sintek's equation, and head circumference and head length were included in both equations. The prediction accuracy was improved by statistically selecting effective predictors. Since we did not assess cross-validity, the equations cannot be used to generalize to other populations, and further investigation is required.

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

NASA Astrophysics Data System (ADS)

Anand, Jasdeep S.; Monks, Paul S.

2017-07-01

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

Evaluating internal and ocular residual astigmatism in Chinese myopic children.

PubMed

Liu, Yanlin; Cheng, Yong; Zhang, Yue; Zhang, Lu; Zhao, Mingwei; Wang, Kai

2017-11-01

To investigate the nature of internal astigmatism (IA) and ocular residual astigmatism (ORA) in Chinese myopic children and to identify factors that may influence IA and ORA. A total of 206 eyes of 206 myopic children (97 boys and 109 girls; 10.95 ± 2.2 years) were enrolled in this cross sectional study. Total ocular astigmatism (TOA), anterior corneal astigmatism (ACA), posterior corneal astigmatism (PCA) and total corneal astigmatism (TCA) were measured directly using either a Hartmann-Shack wavefront sensor or a Pentacam. IA and ORA were calculated by Fourier vector analyses (the definitions of IA and ORA are: IA = TOA - ACA - PCA, ORA = TOA - ACA). Spearman or Pearson correlation was adopted to detect multiple factors that may influence IA and ORA, which were then predicted by linear regressions. Modified compensation factors were applied to evaluate the inter-relationship between corneal astigmatism and ORA. While the mean values of IA and ORA were -0.52 DC × 94.8° and -0.63 DC × 93.0°, respectively, the percentage of ORA power over 1.00 D was as high as 28.64%. Full or under-compensation of ACA by ORA predominated in the enrolled subjects. The mean ORA J 0 and J 45 were -0.311 ± 0.236 and -0.032 ± 0.156 D, respectively, negatively correlated with the corresponding ACA components (J 0 : r = -0.276, J 45 : r = -0.616, p < 0.001). While age was not correlated with either IA or ORA (p > 0.1), the power of IA or ORA was correlated inversely with the axial length (IA: r = -0.193, p = 0.005; ORA: r = -0.169, p = 0.015) and positively with the spherical equivalent refraction (IA r = 0.195, p = 0.005; ORA r = 0.213, p = 0.002) and power of corneal astigmatism (IA-ACA: r = 0.302, IA-TCA: r = 0.368, ORA-ACA: r = 0.334, ORA-TCA: r = 0.293). Girls had larger IA powers than boys (0.741 ± 0.345 D vs 0.651 ± 0.340, p = 0.036). Full or under-compensation of ACA by ORA is common in Chinese myopic children, and the compensation efficiency may decrease with age. Among Chinese children with myopia, a larger ORA is more prevalent with less myopia and greater corneal astigmatism.

Development and Validation of a High-Density SNP Genotyping Array for African Oil Palm.

PubMed

Kwong, Qi Bin; Teh, Chee Keng; Ong, Ai Ling; Heng, Huey Ying; Lee, Heng Leng; Mohamed, Mohaimi; Low, Joel Zi-Bin; Apparow, Sukganah; Chew, Fook Tim; Mayes, Sean; Kulaveerasingam, Harikrishna; Tammi, Martti; Appleton, David Ross

2016-08-01

High-density single nucleotide polymorphism (SNP) genotyping arrays are powerful tools that can measure the level of genetic polymorphism within a population. To develop a whole-genome SNP array for oil palms, SNP discovery was performed using deep resequencing of eight libraries derived from 132 Elaeis guineensis and Elaeis oleifera palms belonging to 59 origins, resulting in the discovery of >3 million putative SNPs. After SNP filtering, the Illumina OP200K custom array was built with 170 860 successful probes. Phenetic clustering analysis revealed that the array could distinguish between palms of different origins in a way consistent with pedigree records. Genome-wide linkage disequilibrium declined more slowly for the commercial populations (ranging from 120 kb at r(2) = 0.43 to 146 kb at r(2) = 0.50) when compared with the semi-wild populations (19.5 kb at r(2) = 0.22). Genetic fixation mapping comparing the semi-wild and commercial population identified 321 selective sweeps. A genome-wide association study (GWAS) detected a significant peak on chromosome 2 associated with the polygenic component of the shell thickness trait (based on the trait shell-to-fruit; S/F %) in tenera palms. Testing of a genomic selection model on the same trait resulted in good prediction accuracy (r = 0.65) with 42% of the S/F % variation explained. The first high-density SNP genotyping array for oil palm has been developed and shown to be robust for use in genetic studies and with potential for developing early trait prediction to shorten the oil palm breeding cycle. Copyright © 2016 The Author. Published by Elsevier Inc. All rights reserved.

Generation of Underwater Sound by a Moving High-Power Laser Source.

DTIC Science & Technology

1985-08-01

convolution 63 2. Laser beamwidth effects 67 3. Numerical predictions 69 V Table of Contents (Cont.) Page B. Experimental results 72 1. Pressure...source - II 53 17 Nerfield ef f ects: t as a ftunction of ro and cc 55 19 Nearfield effects : @max as a function of r. and a 56 • 20 Nearfield directivity...of a " photophone " or apparatus for the production of sound by light. Bell’s invention of the photophone was neglected for many years, but recently it

The Interrelationships of Mathematical Precursors in Kindergarten

PubMed Central

Cirino, Paul T.

2011-01-01

This study evaluated the interrelations among cognitive precursors across quantitative, linguistic, and spatial attention domains that have been implicated for math achievement in young children. The dimensionality of the quantity precursors was evaluated in 286 Kindergarteners via latent variable techniques, and the contribution of precursors from each domain was established for small sums addition. Results showed a five factor structure for the quantity precursors with the major distinction between nonsymbolic and symbolic tasks. The overall model demonstrated good fit, and strong predictive power (R2 = 55%) for addition number combinations. Linguistic and spatial attention domains showed indirect relationships with outcomes, with their effects mediated by symbolic quantity measures. These results have implications for the measurement of mathematical precursors, and yield promise for predicting future math performance. PMID:21194711

Cultural variation in seasonal depression: cross-national differences in winter versus summer patterns of seasonal affective disorder.

PubMed

Kasof, Joseph

2009-05-01

Research suggests that two dimensions of national culture, individualism-collectivism and power distance, predict affective responses to the seasonally varying levels of ambient sunlight that may underlie regular cycles of mood and behavior in Seasonal Affective Disorder (SAD). Specifically, negative affect is predicted by the diminished sunlight of fall-winter in countries higher in individualism and lower in power distance, and by the increased sunlight of spring-summer in countries lower in individualism and higher in power distance. This study tests whether individualism correlates positively, and power distance negatively, with the frequency of winter-SAD relative to that of summer-SAD. A search for studies reporting frequencies of both winter-SAD and summer-SAD identified 55 samples encompassing 18 countries and 38,408 participants, including 1931 with SAD. The frequency of winter-SAD, relative to that of summer-SAD, correlated positively with individualism (r=.67, p=.001) and negatively with power distance (r=-.72, p=.0001). Countries in which winter-SAD was more common than summer-SAD were significantly more individualistic and less power-distant than countries in which summer-SAD was more common than winter-SAD. Results survived various tests of threats to validity. The study is limited by the quantity, quality, diversity, and representativeness of the research under review and by its correlational design. Individualism and power distance are strongly related to the relative prevalence of winter-SAD and summer-SAD. Culture may play an important but previously overlooked role in the etiology of SAD.

Quantitative EEG correlations with brain glucose metabolic rate during anesthesia in volunteers.

PubMed

Alkire, M T

1998-08-01

To help elucidate the relationship between anesthetic-induced changes in the electroencephalogram (EEG) and the concurrent cerebral metabolic changes caused by anesthesia, positron emission tomography data of cerebral metabolism obtained in volunteers during anesthesia were correlated retrospectively with various concurrently measured EEG descriptors. Volunteers underwent functional brain imaging using the 18fluorodeoxyglucose technique; one scan always assessed awake-baseline cerebral metabolism (n = 7), and the other scans assessed metabolism during propofol sedation (n = 4), propofol anesthesia (n = 4), or isoflurane anesthesia (n = 5). The EEG was recorded continuously during metabolism assessment using a frontal-mastoid montage. Power spectrum variables, median frequency, 95% spectral edge, and bispectral index (BIS) values subsequently were correlated with the percentage of absolute cerebral metabolic reduction (PACMR) of glucose utilization caused by anesthesia. The percentage of absolute cerebral metabolic reduction, evident during anesthesia, trended median frequency (r = -0.46, P = 0.11), and the spectral edge (r = -0.52, P = 0.07), and correlated with anesthetic type (r = -0.70, P < 0.05), relative beta power (r = -0.60, P < 0.05), total power (r = 0.71,P < 0.01), and bispectral index (r = -0.81,P < 0.001). After controlling for anesthetic type, only bispectral index (r = 0.40, P = 0.08) and alpha power (r = 0.37, P = 0.10) approached significance for explaining residual percentage of absolute cerebral metabolic reduction prediction error. Some EEG descriptors correlated linearly with the magnitude of the cerebral metabolic reduction caused by propofol and isoflurane anesthesia. These data suggest that a physiologic link exists between the EEG and cerebral metabolism during anesthesia that is mathematically quantifiable.

Adding anthropometric measures of regional adiposity to BMI improves prediction of cardiometabolic, inflammatory and adipokines profiles in youths: a cross-sectional study.

PubMed

Samouda, Hanen; de Beaufort, Carine; Stranges, Saverio; Guinhouya, Benjamin C; Gilson, Georges; Hirsch, Marco; Jacobs, Julien; Leite, Sonia; Vaillant, Michel; Dadoun, Frédéric

2015-10-24

Paediatric research analysing the relationship between the easy-to-use anthropometric measures for adiposity and cardiometabolic risk factors remains highly controversial in youth. Several studies suggest that only body mass index (BMI), a measure of relative weight, constitutes an accurate predictor, whereas others highlight the potential role of waist-to-hip ratio (WHR), waist circumference (Waist C), and waist-to-height ratio (WHtR). In this study, we examined the effectiveness of adding anthropometric measures of body fat distribution (Waist C Z Score, WHR Z Score and/or WHtR) to BMI Z Score to predict cardiometabolic risk factors in overweight and obese youth. We also examined the consistency of these associations with the "total fat mass + trunk/legs fat mass" and/or the "total fat mass + trunk fat mass" combinations, as assessed by dual energy X-ray absorptiometry (DXA), the gold standard measurement of body composition. Anthropometric and DXA measurements of total and regional adiposity, as well as a comprehensive assessment of cardiometabolic, inflammatory and adipokines profiles were performed in 203 overweight and obese 7-17 year-old youths from the Paediatrics Clinic, Centre Hospitalier de Luxembourg. Adding only one anthropometric surrogate of regional fat to BMI Z Score improved the prediction of insulin resistance (WHR Z Score, R(2): 45.9%. Waist C Z Score, R(2): 45.5%), HDL-cholesterol (WHR Z Score, R(2): 9.6%. Waist C Z Score, R(2): 10.8%. WHtR, R(2): 6.5%), triglycerides (WHR Z Score, R(2): 11.7%. Waist C Z Score, R(2): 12.2%), adiponectin (WHR Z Score, R(2): 14.3%. Waist C Z Score, R(2): 17.7%), CRP (WHR Z Score, R(2): 18.2%. WHtR, R(2): 23.3%), systolic (WHtR, R(2): 22.4%), diastolic blood pressure (WHtR, R(2): 20%) and fibrinogen (WHtR, R(2): 21.8%). Moreover, WHR Z Score, Waist C Z Score and/or WHtR showed an independent significant contribution according to these models. These results were in line with the DXA findings. Adding anthropometric measures of regional adiposity to BMI Z Score improves the prediction of cardiometabolic, inflammatory and adipokines profiles in youth.

Allometric biomass partitioning under nitrogen enrichment: Evidence from manipulative experiments around the world.

PubMed

Peng, Yunfeng; Yang, Yuanhe

2016-06-28

Allometric and optimal hypotheses have been widely used to explain biomass partitioning in response to resource changes for individual plants; however, little evidence has been reported from measurements at the community level across a broad geographic scale. This study assessed the nitrogen (N) effect on community-level root to shoot (R/S) ratios and biomass partitioning functions by synthesizing global manipulative experiments. Results showed that, in aggregate, N addition decreased the R/S ratios in various biomes. However, the scaling slopes of the allometric equations were not significantly altered by the N enrichment, possibly indicating that N-induced reduction of the R/S ratio is a consequence of allometric allocation as a function of increasing plant size rather than an optimal partitioning model. To further illustrate this point, we developed power function models to explore the relationships between aboveground and belowground biomass for various biomes; then, we generated the predicted root biomass from the observed shoot biomass and predicted R/S ratios. The comparison of predicted and observed N-induced changes of the R/S ratio revealed no significant differences between each other, supporting the allometric allocation hypothesis. These results suggest that allometry, rather than optimal allocation, explains the N-induced reduction in the R/S ratio across global biomes.

Controlled breathing protocols probe human autonomic cardiovascular rhythms

NASA Technical Reports Server (NTRS)

Cooke, W. H.; Cox, J. F.; Diedrich, A. M.; Taylor, J. A.; Beightol, L. A.; Ames, J. E. 4th; Hoag, J. B.; Seidel, H.; Eckberg, D. L.

1998-01-01

The purpose of this study was to determine how breathing protocols requiring varying degrees of control affect cardiovascular dynamics. We measured inspiratory volume, end-tidal CO2, R-R interval, and arterial pressure spectral power in 10 volunteers who followed the following 5 breathing protocols: 1) uncontrolled breathing for 5 min; 2) stepwise frequency breathing (at 0.3, 0.25, 0.2, 0.15, 0.1, and 0.05 Hz for 2 min each); 3) stepwise frequency breathing as above, but with prescribed tidal volumes; 4) random-frequency breathing (approximately 0.5-0.05 Hz) for 6 min; and 5) fixed-frequency breathing (0.25 Hz) for 5 min. During stepwise breathing, R-R interval and arterial pressure spectral power increased as breathing frequency decreased. Control of inspired volume reduced R-R interval spectral power during 0.1 Hz breathing (P < 0.05). Stepwise and random-breathing protocols yielded comparable coherence and transfer functions between respiration and R-R intervals and systolic pressure and R-R intervals. Random- and fixed-frequency breathing reduced end-tidal CO2 modestly (P < 0.05). Our data suggest that stringent tidal volume control attenuates low-frequency R-R interval oscillations and that fixed- and random-rate breathing may decrease CO2 chemoreceptor stimulation. We conclude that autonomic rhythms measured during different breathing protocols have much in common but that a stepwise protocol without stringent control of inspired volume may allow for the most efficient assessment of short-term respiratory-mediated autonomic oscillations.

Incorporating local land use regression and satellite aerosol optical depth in a hybrid model of spatiotemporal PM2.5 exposures in the Mid-Atlantic states.

PubMed

Kloog, Itai; Nordio, Francesco; Coull, Brent A; Schwartz, Joel

2012-11-06

Satellite-derived aerosol optical depth (AOD) measurements have the potential to provide spatiotemporally resolved predictions of both long and short-term exposures, but previous studies have generally shown moderate predictive power and lacked detailed high spatio- temporal resolution predictions across large domains. We aimed at extending our previous work by validating our model in another region with different geographical and metrological characteristics, and incorporating fine scale land use regression and nonrandom missingness to better predict PM(2.5) concentrations for days with or without satellite AOD measures. We start by calibrating AOD data for 2000-2008 across the Mid-Atlantic. We used mixed models regressing PM(2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We used inverse probability weighting to account for nonrandom missingness of AOD, nested regions within days to capture spatial variation in the daily calibration, and introduced a penalization method that reduces the dimensionality of the large number of spatial and temporal predictors without selecting different predictors in different locations. We then take advantage of the association between grid-cell specific AOD values and PM(2.5) monitoring data, together with associations between AOD values in neighboring grid cells to develop grid cell predictions when AOD is missing. Finally to get local predictions (at the resolution of 50 m), we regressed the residuals from the predictions for each monitor from these previous steps against the local land use variables specific for each monitor. "Out-of-sample" 10-fold cross-validation was used to quantify the accuracy of our predictions at each step. For all days without AOD values, model performance was excellent (mean "out-of-sample" R(2) = 0.81, year-to-year variation 0.79-0.84). Upon removal of outliers in the PM(2.5) monitoring data, the results of the cross validation procedure was even better (overall mean "out of sample"R(2) of 0.85). Further, cross validation results revealed no bias in the predicted concentrations (Slope of observed vs predicted = 0.97-1.01). Our model allows one to reliably assess short-term and long-term human exposures in order to investigate both the acute and effects of ambient particles, respectively.

Determining spherical lens correction for astronaut training underwater.

PubMed

Porter, Jason; Gibson, C Robert; Strauss, Samuel

2011-09-01

To develop a model that will accurately predict the distance spherical lens correction needed to be worn by National Aeronautics and Space Administration astronauts while training underwater. The replica space suit's helmet contains curved visors that induce refractive power when submersed in water. Anterior surface powers and thicknesses were measured for the helmet's protective and inside visors. The impact of each visor on the helmet's refractive power in water was analyzed using thick lens calculations and Zemax optical design software. Using geometrical optics approximations, a model was developed to determine the optimal distance spherical power needed to be worn underwater based on the helmet's total induced spherical power underwater and the astronaut's manifest spectacle plane correction in air. The validity of the model was tested using data from both eyes of 10 astronauts who trained underwater. The helmet's visors induced a total power of -2.737 D when placed underwater. The required underwater spherical correction (FW) was linearly related to the spectacle plane spherical correction in air (FAir): FW = FAir + 2.356 D. The mean magnitude of the difference between the actual correction worn underwater and the calculated underwater correction was 0.20 ± 0.11 D. The actual and calculated values were highly correlated (r = 0.971) with 70% of eyes having a difference in magnitude of <0.25 D between values. We devised a model to calculate the spherical spectacle lens correction needed to be worn underwater by National Aeronautics and Space Administration astronauts. The model accurately predicts the actual values worn underwater and can be applied (more generally) to determine a suitable spectacle lens correction to be worn behind other types of masks when submerged underwater.

Determining spherical lens correction for astronaut training underwater

PubMed Central

Porter, Jason; Gibson, C. Robert; Strauss, Samuel

2013-01-01

Purpose To develop a model that will accurately predict the distance spherical lens correction needed to be worn by National Aeronautics and Space Administration (NASA) astronauts while training underwater. The replica space suit’s helmet contains curved visors that induce refractive power when submersed in water. Methods Anterior surface powers and thicknesses were measured for the helmet’s protective and inside visors. The impact of each visor on the helmet’s refractive power in water was analyzed using thick lens calculations and Zemax optical design software. Using geometrical optics approximations, a model was developed to determine the optimal distance spherical power needed to be worn underwater based on the helmet’s total induced spherical power underwater and the astronaut’s manifest spectacle plane correction in air. The validity of the model was tested using data from both eyes of 10 astronauts who trained underwater. Results The helmet visors induced a total power of −2.737 D when placed underwater. The required underwater spherical correction (FW) was linearly related to the spectacle plane spherical correction in air (FAir): FW = FAir + 2.356 D. The mean magnitude of the difference between the actual correction worn underwater and the calculated underwater correction was 0.20 ± 0.11 D. The actual and calculated values were highly correlated (R = 0.971) with 70% of eyes having a difference in magnitude of < 0.25 D between values. Conclusions We devised a model to calculate the spherical spectacle lens correction needed to be worn underwater by National Aeronautics and Space Administration astronauts. The model accurately predicts the actual values worn underwater and can be applied (more generally) to determine a suitable spectacle lens correction to be worn behind other types of masks when submerged underwater. PMID:21623249

Epitope Spreading of Autoantibody Response to PLA2R Associates with Poor Prognosis in Membranous Nephropathy.

PubMed

Seitz-Polski, Barbara; Dolla, Guillaume; Payré, Christine; Girard, Christophe A; Polidori, Joel; Zorzi, Kevin; Birgy-Barelli, Eléonore; Jullien, Perrine; Courivaud, Cécile; Krummel, Thierry; Benzaken, Sylvia; Bernard, Ghislaine; Burtey, Stéphane; Mariat, Christophe; Esnault, Vincent L M; Lambeau, Gérard

2016-05-01

The phospholipase A2 receptor (PLA2R1) is the major autoantigen in idiopathic membranous nephropathy. However, the value of anti-PLA2R1 antibody titers in predicting patient outcomes is unknown. Here, we screened serum samples from 50 patients positive for PLA2R1 for immunoreactivity against a series of PLA2R1 deletion mutants covering the extracellular domains. We identified reactive epitopes in the cysteine-rich (CysR), C-type lectin domain 1 (CTLD1), and C-type lectin domain 7 (CTLD7) domains and confirmed the reactivity with soluble forms of each domain. We then used ELISAs to stratify 69 patients positive for PLA2R1 by serum reactivity to one or more of these domains: CysR (n=23), CysRC1 (n=14), and CysRC1C7 (n=32). Median ELISA titers measured using the full-length PLA2R1 antigens were not statistically different between subgroups. Patients with anti-CysR-restricted activity were younger (P=0.008), had less nephrotic range proteinuria (P=0.02), and exhibited a higher rate of spontaneous remission (P=0.03) and lower rates of renal failure progression (P=0.002) and ESRD (P=0.01) during follow-up. Overall, 31 of 69 patients had poor renal prognosis (urinary protein/creatinine ratio >4 g/g or eGFR<45 ml/min per 1.73 m(2) at end of follow-up). High anti-PLA2R1 activity and epitope spreading beyond the CysR epitope were independent risk factors of poor renal prognosis in multivariable Cox regression analysis. Epitope spreading during follow-up associated with disease worsening (n=3), whereas reverse spreading from a CysRC1C7 profile back to a CysR profile associated with favorable outcome (n=1). We conclude that analysis of the PLA2R1 epitope profile and spreading is a powerful tool for monitoring disease severity and stratifying patients by renal prognosis. Copyright © 2016 by the American Society of Nephrology.

Power hand tool kinetics associated with upper limb injuries in an automobile assembly plant.

PubMed

Ku, Chia-Hua; Radwin, Robert G; Karsh, Ben-Tzion

2007-06-01

This study investigated the relationship between pneumatic nutrunner handle reactions, workstation characteristics, and prevalence of upper limb injuries in an automobile assembly plant. Tool properties (geometry, inertial properties, and motor characteristics), fastener properties, orientation relative to the fastener, and the position of the tool operator (horizontal and vertical distances) were measured for 69 workstations using 15 different pneumatic nutrunners. Handle reaction response was predicted using a deterministic mechanical model of the human operator and tool that was previously developed in our laboratory, specific to the measured tool, workstation, and job factors. Handle force was a function of target torque, tool geometry and inertial properties, motor speed, work orientation, and joint hardness. The study found that tool target torque was not well correlated with predicted handle reaction force (r=0.495) or displacement (r=0.285). The individual tool, tool shape, and threaded fastener joint hardness all affected predicted forces and displacements (p<0.05). The average peak handle force and displacement for right-angle tools were twice as great as pistol grip tools. Soft-threaded fastener joints had the greatest average handle forces and displacements. Upper limb injury cases were identified using plant OSHA 200 log and personnel records. Predicted handle forces for jobs where injuries were reported were significantly greater than those jobs free of injuries (p<0.05), whereas target torque and predicted handle displacement did not show statistically significant differences. The study concluded that quantification of handle reaction force, rather than target torque alone, is necessary for identifying stressful power hand tool operations and for controlling exposure to forces in manufacturing jobs involving power nutrunners. Therefore, a combination of tool, work station, and task requirements should be considered.

Vertical Jump and Leg Power Normative Data for Colombian Schoolchildren Aged 9-17.9 Years: The FUPRECOL Study.

PubMed

Ramírez-Vélez, Robinson; Correa-Bautista, Jorge E; Lobelo, Felipe; Cadore, Eduardo L; Alonso-Martinez, Alicia M; Izquierdo, Mikel

2017-04-01

Ramírez-Vélez, R, Correa-Bautista, JE, Lobelo, F, Cadore, EL, Alonso-Martinez, AM, and Izquierdo, M. Vertical jump and leg power normative data for Colombian schoolchildren aged 9-17.9 years: the FUPRECOL study. J Strength Cond Res 31(4): 990-998, 2017-The aims of the present study were to generate normative vertical jump height and predicted peak power (Ppeak) data for 9- to 17.9-year-olds and to investigate between-sex and age group differences in these measures. This was a cross-sectional study of 7,614 healthy schoolchildren (boys n = 3,258 and girls n = 4,356, mean [SD] age 12.8 [2.3] years). Each participant performed 2 countermovement jumps; jump height was calculated using a Takei 5414 Jump-DF Digital Vertical (Takei Scientific Instruments Co., Ltd.). The highest jump was used for analysis and in the calculation of predicted Ppeak. Centile smoothed curves, percentiles, and tables for the 3rd, 10th, 25th, 50th, 75th, 90th, and 97th percentiles were calculated using Cole's LMS (L [curve Box-Cox], M [curve median], and S [curve coefficient of variation]) method. The 2-way analysis of variance tests showed that maximum jump height (in centimeters) and predicted Ppeak (in watts) were higher in boys than in girls (p < 0.01). Post hoc analyses within sexes showed yearly increases in jump height and Ppeak in all ages. In boys, the maximum jump height and predicted Ppeak 50th percentile ranged from 24.0 to 38.0 cm and from 845.5 to 3061.6 W, respectively. In girls, the 50th percentile for jump height ranged from 22.3 to 27.0 cm, and the predicted Ppeak was 710.1-2036.4 W. For girls, jump height increased yearly from 9 to 17.9 years old. Our results provide, for the first time, sex- and age-specific vertical jump height and predicted Ppeak reference standards for Colombian schoolchildren aged 9-17.9 years.

The bitter pill: clinical drugs that activate the human bitter taste receptor TAS2R14.

PubMed

Levit, Anat; Nowak, Stefanie; Peters, Maximilian; Wiener, Ayana; Meyerhof, Wolfgang; Behrens, Maik; Niv, Masha Y

2014-03-01

Bitter taste receptors (TAS2Rs) mediate aversive response to toxic food, which is often bitter. These G-protein-coupled receptors are also expressed in extraoral tissues, and emerge as novel targets for therapeutic indications such as asthma and infection. Our goal was to identify ligands of the broadly tuned TAS2R14 among clinical drugs. Molecular properties of known human bitter taste receptor TAS2R14 agonists were incorporated into pharmacophore- and shape-based models and used to computationally predict additional ligands. Predictions were tested by calcium imaging of TAS2R14-transfected HEK293 cells. In vitro testing of the virtual screening predictions resulted in 30-80% success rates, and 15 clinical drugs were found to activate the TAS2R14. hERG potassium channel, which is predominantly expressed in the heart, emerged as a common off-target of bitter drugs. Despite immense chemical diversity of known TAS2R14 ligands, novel ligands and previously unknown polypharmacology of drugs were unraveled by in vitro screening of computational predictions. This enables rational repurposing of traditional and standard drugs for bitter taste signaling modulation for therapeutic indications.

A statistical learning framework for groundwater nitrate models of the Central Valley, California, USA

USGS Publications Warehouse

Nolan, Bernard T.; Fienen, Michael N.; Lorenz, David L.

2015-01-01

We used a statistical learning framework to evaluate the ability of three machine-learning methods to predict nitrate concentration in shallow groundwater of the Central Valley, California: boosted regression trees (BRT), artificial neural networks (ANN), and Bayesian networks (BN). Machine learning methods can learn complex patterns in the data but because of overfitting may not generalize well to new data. The statistical learning framework involves cross-validation (CV) training and testing data and a separate hold-out data set for model evaluation, with the goal of optimizing predictive performance by controlling for model overfit. The order of prediction performance according to both CV testing R2 and that for the hold-out data set was BRT > BN > ANN. For each method we identified two models based on CV testing results: that with maximum testing R2 and a version with R2 within one standard error of the maximum (the 1SE model). The former yielded CV training R2 values of 0.94–1.0. Cross-validation testing R2 values indicate predictive performance, and these were 0.22–0.39 for the maximum R2 models and 0.19–0.36 for the 1SE models. Evaluation with hold-out data suggested that the 1SE BRT and ANN models predicted better for an independent data set compared with the maximum R2 versions, which is relevant to extrapolation by mapping. Scatterplots of predicted vs. observed hold-out data obtained for final models helped identify prediction bias, which was fairly pronounced for ANN and BN. Lastly, the models were compared with multiple linear regression (MLR) and a previous random forest regression (RFR) model. Whereas BRT results were comparable to RFR, MLR had low hold-out R2 (0.07) and explained less than half the variation in the training data. Spatial patterns of predictions by the final, 1SE BRT model agreed reasonably well with previously observed patterns of nitrate occurrence in groundwater of the Central Valley.

GENERAL: The Analytic Solution of Schrödinger Equation with Potential Function Superposed by Six Terms with Positive-power and Inverse-power Potentials

NASA Astrophysics Data System (ADS)

Hu, Xian-Quan; Luo, Guang; Cui, Li-Peng; Li, Fang-Yu; Niu, Lian-Bin

2009-03-01

The analytic solution of the radial Schrödinger equation is studied by using the tight coupling condition of several positive-power and inverse-power potential functions in this article. Furthermore, the precisely analytic solutions and the conditions that decide the existence of analytic solution have been searched when the potential of the radial Schrödinger equation is V(r) = α1r8 + α2r3 + α3r2 + β3r-1 + β2r-3 + β1r-4. Generally speaking, there is only an approximate solution, but not analytic solution for Schrödinger equation with several potentials' superposition. However, the conditions that decide the existence of analytic solution have been found and the analytic solution and its energy level structure are obtained for the Schrödinger equation with the potential which is motioned above in this paper. According to the single-value, finite and continuous standard of wave function in a quantum system, the authors firstly solve the asymptotic solution through the radial coordinate r → and r → 0; secondly, they make the asymptotic solutions combining with the series solutions nearby the neighborhood of irregular singularities; and then they compare the power series coefficients, deduce a series of analytic solutions of the stationary state wave function and corresponding energy level structure by tight coupling among the coefficients of potential functions for the radial Schrödinger equation; and lastly, they discuss the solutions and make conclusions.

Fully Roll-to-Roll Gravure Printable Wireless (13.56 MHz) Sensor-Signage Tags for Smart Packaging

NASA Astrophysics Data System (ADS)

Kang, Hwiwon; Park, Hyejin; Park, Yongsu; Jung, Minhoon; Kim, Byung Chul; Wallace, Gordon; Cho, Gyoujin

2014-06-01

Integration of sensing capabilities with an interactive signage through wireless communication is enabling the development of smart packaging wherein wireless (13.56 MHz) power transmission is used to interlock the smart packaging with a wireless (13.56 MHz) reader or a smart phone. Assembly of the necessary componentry for smart packaging on plastic or paper foils is limited by the manufacturing costs involved with Si based technologies. Here, the issue of manufacturing cost for smart packaging has been obviated by materials that allow R2R (roll-to-roll) gravure in combination with R2R coating processes to be employed. R2R gravure was used to print the wireless power transmission device, called rectenna (antenna, diode and capacitor), and humidity sensor on poly(ethylene terephtalate) (PET) films while electrochromic signage units were fabricated by R2R coating. The signage units were laminated with the R2R gravure printed rectenna and sensor to complete the prototype smart packaging.

Fully Roll-to-Roll Gravure Printable Wireless (13.56 MHz) Sensor-Signage Tags for Smart Packaging

PubMed Central

Kang, Hwiwon; Park, Hyejin; Park, Yongsu; Jung, Minhoon; Kim, Byung Chul; Wallace, Gordon; Cho, Gyoujin

2014-01-01

Integration of sensing capabilities with an interactive signage through wireless communication is enabling the development of smart packaging wherein wireless (13.56 MHz) power transmission is used to interlock the smart packaging with a wireless (13.56 MHz) reader or a smart phone. Assembly of the necessary componentry for smart packaging on plastic or paper foils is limited by the manufacturing costs involved with Si based technologies. Here, the issue of manufacturing cost for smart packaging has been obviated by materials that allow R2R (roll-to-roll) gravure in combination with R2R coating processes to be employed. R2R gravure was used to print the wireless power transmission device, called rectenna (antenna, diode and capacitor), and humidity sensor on poly(ethylene terephtalate) (PET) films while electrochromic signage units were fabricated by R2R coating. The signage units were laminated with the R2R gravure printed rectenna and sensor to complete the prototype smart packaging. PMID:24953037

Fully roll-to-roll gravure printable wireless (13.56 MHz) sensor-signage tags for smart packaging.

PubMed

Kang, Hwiwon; Park, Hyejin; Park, Yongsu; Jung, Minhoon; Kim, Byung Chul; Wallace, Gordon; Cho, Gyoujin

2014-06-23

Integration of sensing capabilities with an interactive signage through wireless communication is enabling the development of smart packaging wherein wireless (13.56 MHz) power transmission is used to interlock the smart packaging with a wireless (13.56 MHz) reader or a smart phone. Assembly of the necessary componentry for smart packaging on plastic or paper foils is limited by the manufacturing costs involved with Si based technologies. Here, the issue of manufacturing cost for smart packaging has been obviated by materials that allow R2R (roll-to-roll) gravure in combination with R2R coating processes to be employed. R2R gravure was used to print the wireless power transmission device, called rectenna (antenna, diode and capacitor), and humidity sensor on poly(ethylene terephtalate) (PET) films while electrochromic signage units were fabricated by R2R coating. The signage units were laminated with the R2R gravure printed rectenna and sensor to complete the prototype smart packaging.

Use of e-rater[R] in Scoring of the TOEFL iBT[R] Writing Test. Research Report. ETS RR-11-25

ERIC Educational Resources Information Center

Haberman, Shelby J.

2011-01-01

Alternative approaches are discussed for use of e-rater[R] to score the TOEFL iBT[R] Writing test. These approaches involve alternate criteria. In the 1st approach, the predicted variable is the expected rater score of the examinee's 2 essays. In the 2nd approach, the predicted variable is the expected rater score of 2 essay responses by the…

Simple inflationary models in Gauss-Bonnet brane-world cosmology

NASA Astrophysics Data System (ADS)

Okada, Nobuchika; Okada, Satomi

2016-06-01

In light of the recent Planck 2015 results for the measurement of the cosmic microwave background (CMB) anisotropy, we study simple inflationary models in the context of the Gauss-Bonnet (GB) brane-world cosmology. The brane-world cosmological effect modifies the power spectra of scalar and tensor perturbations generated by inflation and causes a dramatic change for the inflationary predictions of the spectral index (n s) and the tensor-to-scalar ratio (r) from those obtained in the standard cosmology. In particular, the predicted r values in the inflationary models favored by the Planck 2015 results are suppressed due to the GB brane-world cosmological effect, which is in sharp contrast with inflationary scenario in the Randall-Sundrum brane-world cosmology, where the r values are enhanced. Hence, these two brane-world cosmological scenarios are distinguishable. With the dramatic change of the inflationary predictions, the inflationary scenario in the GB brane-world cosmology can be tested by more precise measurements of n s and future observations of the CMB B-mode polarization.

3x2 Classroom Goal Structures, Motivational Regulations, Self-Concept, and Affectivity in Secondary School.

PubMed

Méndez-Giménez, Antonio; Cecchini-Estrada, José-Antonio; Fernández-Río, Javier; Prieto Saborit, José Antonio; Méndez-Alonso, David

2017-09-20

The main objective was to analyze relationships and predictive patterns between 3x2 classroom goal structures (CGS), and motivational regulations, dimensions of self-concept, and affectivity in the context of secondary education. A sample of 1,347 secondary school students (56.6% young men, 43.4% young women) from 10 different provinces of Spain agreed to participate (M age = 13.43, SD = 1.05). Hierarchical regression analyses indicated the self-approach CGS was the most adaptive within the spectrum of self-determination, followed by the task-approach CGS. The other-approach CGS had an ambivalent influence on motivation. Task-approach and self-approach CGS predicted academic self-concept (p < .01; p < .001, respectively; R 2 = .134), and both along with other-approach CGS (negatively) predicted family self-concept (p < .05; p < .001; p < .01, respectively; R 2 = .064). Physical self-concept was predicted by the task-approach and other-approach CGS's (p < .05; p < .001, respectively; R 2 = .078). Finally, positive affect was predicted by all three approach-oriented CGS's (p < .001; R 2 = .137), whereas negative affect was predicted by other-approach (positively) and self-approach (negatively) CGS (p < .001; p < .05, respectively; R 2 = .028). These results expand the 3x2 achievement goal framework to include environmental factors, and reiterate that teachers should focus on raising levels of self- and task-based goals for students in their classes.

Replicability and Robustness of GWAS for Behavioral Traits

PubMed Central

Rietveld, Cornelius A.; Conley, Dalton; Eriksson, Nicholas; Esko, Tõnu; Medland, Sarah E.; Vinkhuyzen, Anna A.E.; Yang, Jian; Boardman, Jason D.; Chabris, Christopher F.; Dawes, Christopher T.; Domingue, Benjamin W.; Hinds, David A.; Johannesson, Magnus; Kiefer, Amy K.; Laibson, David; Magnusson, Patrik K. E.; Mountain, Joanna L.; Oskarsson, Sven; Rostapshova, Olga; Teumer, Alexander; Tung, Joyce Y.; Visscher, Peter M.; Benjamin, Daniel J.; Cesarini, David; Koellinger, Philipp D.

2015-01-01

A recent genome-wide association study (GWAS) of educational attainment identified three single-nucleotide polymorphisms (SNPs) that, despite their small effect sizes (each R2 ≈ 0.02%), reached genome-wide significance (p < 5×10−8) in a large discovery sample and replicated in an independent sample (p < 0.05). The study also reported associations between educational attainment and indices of SNPs called “polygenic scores.” We evaluate the robustness of these findings. Study 1 finds that all three SNPs replicate in another large (N = 34,428) independent sample. We also find that the scores remain predictive (R2 ≈ 2%) with stringent controls for stratification (Study 2) and in new within-family analyses (Study 3). Our results show that large and therefore well-powered GWASs can identify replicable genetic associations with behavioral traits. The small effect sizes of individual SNPs are likely to be a major contributing explanation for the striking contrast between our results and the disappointing replication record of most candidate gene studies. PMID:25287667

High-efficiency L-band T/R Module: Development Results

NASA Technical Reports Server (NTRS)

Edelstein, Wendy N.; Andricos, Constantine; Wang, Feiyu; Rutled, David B.

2005-01-01

Future interferometric synthetic aperture radar (InSAR) systems require electronically scanned phased-array antennas, where the transmit/receive (T/R) module is a key component. The T/R module efficiency is a critical figure of merit and has direct implications on the power dissipation and power generation requirements of the system. Significant improvements in the efficiency of the T/R module will make SAR missions more feasible and affordable. The results of two high-efficiency T/R modules are presented, each based on different power amplifier technologies. One module uses a 30W GaAs Class-AlB power amplifier and the second module uses a 70W LD-MOS Class-ElF power amplifier, where both modules use a common low power section. Each module operates over an 80MHz bandwidth at L-band (1.2GHz) with an overall module efficiency greater than 58%. We will present the results of these two T/R modules that have been designed, built and tested.

Molecular electronegativity distance vector model for the prediction of bioconcentration factors in fish.

PubMed

Liu, Shu-Shen; Qin, Li-Tang; Liu, Hai-Ling; Yin, Da-Qiang

2008-02-01

Molecular electronegativity distance vector (MEDV) derived directly from the molecular topological structures was used to describe the structures of 122 nonionic organic compounds (NOCs) and a quantitative relationship between the MEDV descriptors and the bioconcentration factors (BCF) of NOCs in fish was developed using the variable selection and modeling based on prediction (VSMP). It was found that some main structural factors influencing the BCFs of NOCs are the substructures expressed by four atomic types of nos. 2, 3, 5, and 13, i.e., atom groups -CH(2)- or =CH-, -CH< or =C<, -NH(2), and -Cl or -Br where the former two groups exist in the molecular skeleton of NOC and the latter three groups are related closely to the substituting groups on a benzene ring. The best 5-variable model, with the correlation coefficient (r(2)) of 0.9500 and the leave-one-out cross-validation correlation coefficient (q(2)) of 0.9428, was built by multiple linear regressions, which shows a good estimation ability and stability. A predictive power for the external samples was tested by the model from the training set of 80 NOCs and the predictive correlation coefficient (u(2)) for the 42 external samples in the test set was 0.9028.

Mobility Fuels for the Navy.

DTIC Science & Technology

1982-01-01

aircraft powered by gas turbines through the year 2000. The study also predicted that some types of diesels and steam powerplants could potentially...figure 3. Diesels are more efficient even at high- power settings. CHANGES TO FUELS Interrelationships between the price and quality of fuel have...emaIcal Physics 20 (1979) pp. 6446- PP 252 899), AD) A061 938 Nunn, Wolter R.. -Poeltion Finding with Prior Kowledge of .Eonrience Parameters," 5 pp., Jun

Epitope Spreading of Autoantibody Response to PLA2R Associates with Poor Prognosis in Membranous Nephropathy

PubMed Central

Seitz-Polski, Barbara; Dolla, Guillaume; Payré, Christine; Girard, Christophe A.; Polidori, Joel; Zorzi, Kevin; Birgy-Barelli, Eléonore; Jullien, Perrine; Courivaud, Cécile; Krummel, Thierry; Benzaken, Sylvia; Bernard, Ghislaine; Burtey, Stéphane; Mariat, Christophe; Esnault, Vincent L.M.

2016-01-01

The phospholipase A2 receptor (PLA2R1) is the major autoantigen in idiopathic membranous nephropathy. However, the value of anti-PLA2R1 antibody titers in predicting patient outcomes is unknown. Here, we screened serum samples from 50 patients positive for PLA2R1 for immunoreactivity against a series of PLA2R1 deletion mutants covering the extracellular domains. We identified reactive epitopes in the cysteine-rich (CysR), C-type lectin domain 1 (CTLD1), and C-type lectin domain 7 (CTLD7) domains and confirmed the reactivity with soluble forms of each domain. We then used ELISAs to stratify 69 patients positive for PLA2R1 by serum reactivity to one or more of these domains: CysR (n=23), CysRC1 (n=14), and CysRC1C7 (n=32). Median ELISA titers measured using the full-length PLA2R1 antigens were not statistically different between subgroups. Patients with anti-CysR–restricted activity were younger (P=0.008), had less nephrotic range proteinuria (P=0.02), and exhibited a higher rate of spontaneous remission (P=0.03) and lower rates of renal failure progression (P=0.002) and ESRD (P=0.01) during follow-up. Overall, 31 of 69 patients had poor renal prognosis (urinary protein/creatinine ratio >4 g/g or eGFR<45 ml/min per 1.73 m2 at end of follow-up). High anti-PLA2R1 activity and epitope spreading beyond the CysR epitope were independent risk factors of poor renal prognosis in multivariable Cox regression analysis. Epitope spreading during follow-up associated with disease worsening (n=3), whereas reverse spreading from a CysRC1C7 profile back to a CysR profile associated with favorable outcome (n=1). We conclude that analysis of the PLA2R1 epitope profile and spreading is a powerful tool for monitoring disease severity and stratifying patients by renal prognosis. PMID:26567246

Measurement of heat pump processes induced by laser radiation

NASA Technical Reports Server (NTRS)

Garbuny, M.; Henningsen, T.

1983-01-01

A series of experiments was performed in which a suitably tuned CO2 laser, frequency doubled by a Tl3AsSe37 crystal, was brought into resonance with a P-line or two R-lines in the fundamental vibration spectrum of CO. Cooling or heating produced by absorption in CO was measured in a gas-thermometer arrangement. P-line cooling and R-line heating could be demonstrated, measured, and compared. The experiments were continued with CO mixed with N2 added in partial pressures from 9 to 200 Torr. It was found that an efficient collisional resonance energy transfer from CO to N2 existed which increased the cooling effects by one to two orders of magnitude over those in pure CO. Temperature reductions in the order of tens of degrees Kelvin were obtained by a single pulse in the core of the irradiated volume. These measurements followed predicted values rather closely, and it is expected that increase of pulse energies and durations will enhance the heat pump effects. The experiments confirm the feasibility of quasi-isentropic engines which convert laser power into work without the need for heat rejection. Of more immediate potential interest is the possibility of remotely powered heat pumps for cryogenic use, such applications are discussed to the extent possible at the present stage.

Estimation of inflation parameters for Perturbed Power Law model using recent CMB measurements

NASA Astrophysics Data System (ADS)

Mukherjee, Suvodip; Das, Santanu; Joy, Minu; Souradeep, Tarun

2015-01-01

Cosmic Microwave Background (CMB) is an important probe for understanding the inflationary era of the Universe. We consider the Perturbed Power Law (PPL) model of inflation which is a soft deviation from Power Law (PL) inflationary model. This model captures the effect of higher order derivative of Hubble parameter during inflation, which in turn leads to a non-zero effective mass meff for the inflaton field. The higher order derivatives of Hubble parameter at leading order sources constant difference in the spectral index for scalar and tensor perturbation going beyond PL model of inflation. PPL model have two observable independent parameters, namely spectral index for tensor perturbation νt and change in spectral index for scalar perturbation νst to explain the observed features in the scalar and tensor power spectrum of perturbation. From the recent measurements of CMB power spectra by WMAP, Planck and BICEP-2 for temperature and polarization, we estimate the feasibility of PPL model with standard ΛCDM model. Although BICEP-2 claimed a detection of r=0.2, estimates of dust contamination provided by Planck have left open the possibility that only upper bound on r will be expected in a joint analysis. As a result we consider different upper bounds on the value of r and show that PPL model can explain a lower value of tensor to scalar ratio (r<0.1 or r<0.01) for a scalar spectral index of ns=0.96 by having a non-zero value of effective mass of the inflaton field m2eff/H2. The analysis with WP + Planck likelihood shows a non-zero detection of m2eff/H2 with 5.7 σ and 8.1 σ respectively for r<0.1 and r<0.01. Whereas, with BICEP-2 likelihood m2eff/H2 = -0.0237 ± 0.0135 which is consistent with zero.

Cosmology of f(R) gravity in the metric variational approach

NASA Astrophysics Data System (ADS)

Li, Baojiu; Barrow, John D.

2007-04-01

We consider the cosmologies that arise in a subclass of f(R) gravity with f(R)=R+μ2n+2/(-R)n and n∈(-1,0) in the metric (as opposed to the Palatini) variational approach to deriving the gravitational field equations. The calculations of the isotropic and homogeneous cosmological models are undertaken in the Jordan frame and at both the background and the perturbation levels. For the former, we also discuss the connection to the Einstein frame in which the extra degree of freedom in the theory is associated with a scalar field sharing some of the properties of a “chameleon” field. For the latter, we derive the cosmological perturbation equations in general theories of f(R) gravity in covariant form and implement them numerically to calculate the cosmic microwave background (CMB) temperature and matter power spectra of the cosmological model. The CMB power is shown to reduce at low l’s, and the matter power spectrum is almost scale independent at small scales, thus having a similar shape to that in standard general relativity. These are in stark contrast with what was found in the Palatini f(R) gravity, where the CMB power is largely amplified at low l’s and the matter spectrum is strongly scale dependent at small scales. These features make the present model more adaptable than that arising from the Palatini f(R) field equations, and none of the data on background evolution, CMB power spectrum, or matter power spectrum currently rule it out.

Early changes of parotid density and volume predict modifications at the end of therapy and intensity of acute xerostomia.

PubMed

Belli, Maria Luisa; Scalco, Elisa; Sanguineti, Giuseppe; Fiorino, Claudio; Broggi, Sara; Dinapoli, Nicola; Ricchetti, Francesco; Valentini, Vincenzo; Rizzo, Giovanna; Cattaneo, Giovanni Mauro

2014-10-01

To quantitatively assess the predictive power of early variations of parotid gland volume and density on final changes at the end of therapy and, possibly, on acute xerostomia during IMRT for head-neck cancer. Data of 92 parotids (46 patients) were available. Kinetics of the changes during treatment were described by the daily rate of density (rΔρ) and volume (rΔvol) variation based on weekly diagnostic kVCT images. Correlation between early and final changes was investigated as well as the correlation with prospective toxicity data (CTCAEv3.0) collected weekly during treatment for 24/46 patients. A higher rΔρ was observed during the first compared to last week of treatment (-0,50 vs -0,05HU, p-value = 0.0001). Based on early variations, a good estimation of the final changes may be obtained (Δρ: AUC = 0.82, p = 0.0001; Δvol: AUC = 0.77, p = 0.0001). Both early rΔρ and rΔvol predict a higher "mean" acute xerostomia score (≥ median value, 1.57; p-value = 0.01). Median early density rate changes for patients with mean xerostomia score ≥ / < 1.57 were -0.98 vs -0.22 HU/day respectively (p = 0.05). Early density and volume variations accurately predict final changes of parotid glands. A higher longitudinally assessed score of acute xerostomia is well predicted by higher rΔρ and rΔvol in the first two weeks of treatment: best cut-off values were -0.50 HU/day and -380 mm(3)/day for rΔρ and rΔvol respectively. Further studies are necessary to definitively assess the potential of early density/volume changes in identifying more sensitive patients at higher risk of experiencing xerostomia.

Estimation of chemical carcass composition from 8th rib characteristics with Belgian blue double-muscled bulls.

PubMed

De Campeneere, S; Fiems, L O; Van de Voorde, G; Vanacker, J M; Boucque, C V; Demeyer, D I

1999-01-01

Characteristics from the 8th rib cut: chemical composition, tissue composition after dissection, specific gravity (SG) and m. longissimus thoracis (LT) composition, collected on 17 Belgian Blue double-muscled fattening bulls were used to generate equations for predicting chemical carcass composition. Carcass composition was best predicted from chemical analysis of the 8th rib cut and the empty body weight (EBW) of the bull. Carcass chemical fat content (CCF, kg) was predicted from the 8th rib cut fat content (ether extract, 8RF, kg) by the following regression: CCF=1.94+27.37 8RF (R(2)=0.957, RSD =9.89%). A higher coefficient was found for carcass water (CCW, kg) predicted from 8RF and EBW: CCW=-2.26+0.28 EBW-34.28 8RF (R(2)=0.997, RSD=1.48%). No parameter was found to improve the prediction of CCP from EBW solely: CCP=-0.86+0.08 EBW (R(2) =0.992, RSD=2.61%). Prediction equations based solely on LT composition had low R(2) values of between 0.38 and 0.67, whereas no significant equations were found using SG. However, equations based on EBW had R(2) values between 0.78 and 0.99. Chemical components of the 8th rib cut in combination with EBW are most useful in predicting the chemical composition of the carcass of Belgian-Blue double-muscled bulls.

Improving satellite-driven PM2.5 models with Moderate Resolution Imaging Spectroradiometer fire counts in the southeastern U.S.

PubMed

Hu, Xuefei; Waller, Lance A; Lyapustin, Alexei; Wang, Yujie; Liu, Yang

2014-10-16

Multiple studies have developed surface PM 2.5 (particle size less than 2.5 µm in aerodynamic diameter) prediction models using satellite-derived aerosol optical depth as the primary predictor and meteorological and land use variables as secondary variables. To our knowledge, satellite-retrieved fire information has not been used for PM 2.5 concentration prediction in statistical models. Fire data could be a useful predictor since fires are significant contributors of PM 2.5 . In this paper, we examined whether remotely sensed fire count data could improve PM 2.5 prediction accuracy in the southeastern U.S. in a spatial statistical model setting. A sensitivity analysis showed that when the radius of the buffer zone centered at each PM 2.5 monitoring site reached 75 km, fire count data generally have the greatest predictive power of PM 2.5 across the models considered. Cross validation (CV) generated an R 2 of 0.69, a mean prediction error of 2.75 µg/m 3 , and root-mean-square prediction errors (RMSPEs) of 4.29 µg/m 3 , indicating a good fit between the dependent and predictor variables. A comparison showed that the prediction accuracy was improved more substantially from the nonfire model to the fire model at sites with higher fire counts. With increasing fire counts, CV RMSPE decreased by values up to 1.5 µg/m 3 , exhibiting a maximum improvement of 13.4% in prediction accuracy. Fire count data were shown to have better performance in southern Georgia and in the spring season due to higher fire occurrence. Our findings indicate that fire count data provide a measurable improvement in PM 2.5 concentration estimation, especially in areas and seasons prone to fire events.

Improving satellite-driven PM2.5 models with Moderate Resolution Imaging Spectroradiometer fire counts in the southeastern U.S

PubMed Central

Hu, Xuefei; Waller, Lance A.; Lyapustin, Alexei; Wang, Yujie; Liu, Yang

2017-01-01

Multiple studies have developed surface PM2.5 (particle size less than 2.5 µm in aerodynamic diameter) prediction models using satellite-derived aerosol optical depth as the primary predictor and meteorological and land use variables as secondary variables. To our knowledge, satellite-retrieved fire information has not been used for PM2.5 concentration prediction in statistical models. Fire data could be a useful predictor since fires are significant contributors of PM2.5. In this paper, we examined whether remotely sensed fire count data could improve PM2.5 prediction accuracy in the southeastern U.S. in a spatial statistical model setting. A sensitivity analysis showed that when the radius of the buffer zone centered at each PM2.5 monitoring site reached 75 km, fire count data generally have the greatest predictive power of PM2.5 across the models considered. Cross validation (CV) generated an R2 of 0.69, a mean prediction error of 2.75 µg/m3, and root-mean-square prediction errors (RMSPEs) of 4.29 µg/m3, indicating a good fit between the dependent and predictor variables. A comparison showed that the prediction accuracy was improved more substantially from the nonfire model to the fire model at sites with higher fire counts. With increasing fire counts, CV RMSPE decreased by values up to 1.5 µg/m3, exhibiting a maximum improvement of 13.4% in prediction accuracy. Fire count data were shown to have better performance in southern Georgia and in the spring season due to higher fire occurrence. Our findings indicate that fire count data provide a measurable improvement in PM2.5 concentration estimation, especially in areas and seasons prone to fire events. PMID:28967648

The Design of the 4-Megawatt Induction Heating Power Supply at AEDC

DTIC Science & Technology

1976-04-01

AEDC-TR-76-26 p ’ t . ~ F i , .~ r),’, • #, THE DESIGN OF THE 4-MEGAWATT INDUCTION HEATING POWER SUPPLY AT AEDC PROPULSION WIND TUNNEL...NUMBER ]2 GOVT ACCESSION NO. [ AEDC-TR-76-26 4. T I T L E ( ~ d 5ubll l le) THE DESIGN OF THE 4-MEGAWATT INDUCTION HEATING POWER SUPPLY AT AEDC 7...e m and the supply of e l e c t r i c a l power to the o s c i l l a t o r were des igned by J. B. Carson , ARO, Inc. Ashley Bock, who was r

Earthquake prediction in California using regression algorithms and cloud-based big data infrastructure

NASA Astrophysics Data System (ADS)

Asencio-Cortés, G.; Morales-Esteban, A.; Shang, X.; Martínez-Álvarez, F.

2018-06-01

Earthquake magnitude prediction is a challenging problem that has been widely studied during the last decades. Statistical, geophysical and machine learning approaches can be found in literature, with no particularly satisfactory results. In recent years, powerful computational techniques to analyze big data have emerged, making possible the analysis of massive datasets. These new methods make use of physical resources like cloud based architectures. California is known for being one of the regions with highest seismic activity in the world and many data are available. In this work, the use of several regression algorithms combined with ensemble learning is explored in the context of big data (1 GB catalog is used), in order to predict earthquakes magnitude within the next seven days. Apache Spark framework, H2 O library in R language and Amazon cloud infrastructure were been used, reporting very promising results.

Statistical modeling of an integrated boiler for coal fired thermal power plant.

PubMed

Chandrasekharan, Sreepradha; Panda, Rames Chandra; Swaminathan, Bhuvaneswari Natrajan

2017-06-01

The coal fired thermal power plants plays major role in the power production in the world as they are available in abundance. Many of the existing power plants are based on the subcritical technology which can produce power with the efficiency of around 33%. But the newer plants are built on either supercritical or ultra-supercritical technology whose efficiency can be up to 50%. Main objective of the work is to enhance the efficiency of the existing subcritical power plants to compensate for the increasing demand. For achieving the objective, the statistical modeling of the boiler units such as economizer, drum and the superheater are initially carried out. The effectiveness of the developed models is tested using analysis methods like R 2 analysis and ANOVA (Analysis of Variance). The dependability of the process variable (temperature) on different manipulated variables is analyzed in the paper. Validations of the model are provided with their error analysis. Response surface methodology (RSM) supported by DOE (design of experiments) are implemented to optimize the operating parameters. Individual models along with the integrated model are used to study and design the predictive control of the coal-fired thermal power plant.

Topography of Slow Sigma Power during Sleep is Associated with Processing Speed in Preschool Children.

PubMed

Doucette, Margaret R; Kurth, Salome; Chevalier, Nicolas; Munakata, Yuko; LeBourgeois, Monique K

2015-11-04

Cognitive development is influenced by maturational changes in processing speed, a construct reflecting the rapidity of executing cognitive operations. Although cognitive ability and processing speed are linked to spindles and sigma power in the sleep electroencephalogram (EEG), little is known about such associations in early childhood, a time of major neuronal refinement. We calculated EEG power for slow (10-13 Hz) and fast (13.25-17 Hz) sigma power from all-night high-density electroencephalography (EEG) in a cross-sectional sample of healthy preschool children (n = 10, 4.3 ± 1.0 years). Processing speed was assessed as simple reaction time. On average, reaction time was 1409 ± 251 ms; slow sigma power was 4.0 ± 1.5 μV²; and fast sigma power was 0.9 ± 0.2 μV². Both slow and fast sigma power predominated over central areas. Only slow sigma power was correlated with processing speed in a large parietal electrode cluster (p < 0.05, r ranging from -0.6 to -0.8), such that greater power predicted faster reaction time. Our findings indicate regional correlates between sigma power and processing speed that are specific to early childhood and provide novel insights into the neurobiological features of the EEG that may underlie developing cognitive abilities.

Prediction of dendrite arm spacings in unsteady-and steady-state heat flow of unidirectionally solidified binary alloys

NASA Astrophysics Data System (ADS)

Bouchard, Dominique; Kirkaldy, John S.

1997-08-01

Various theoretical dendrite and cell spacing formulas have been tested against experimental data obtained in unsteady- and steady-state heat flow conditions. An iterative assessment strategy satisfactorily overcomes the circumstances that certain constitutive parameters are inadequately established and/or highly variable and that many of the data sets, in terms of gradients, velocities, and/or cooling rates, are unreliable. The accessed unsteady- and steady-state observations on near-terminal binary alloys for primary and secondary spacings were first examined within conventional power law representations, the deduced exponents and confidence limits for each alloy being tabularly recorded. Through this analysis, it became clear that to achieve predictive generality the many constitutive parameters must be included in a rational way, this being achievable only through extant or new theoretical formulations. However, in the case of primary spacings, all formulas, including our own, failed within the unsteady heat flow algorithm while performing adequately within their steady-state context. An earlier untested, heuristically derived steady-state formula after modification, λ _1 = 120 ( {{16X_0^{{1/2}} G_0 (\\varepsilon σ )T_M D}/{(1 - k)mΔ H G R}} )^{{1/2}} ultimately proved its utility in the unsteady regime, and so it is recommended for purposes of predictions for general terminal alloys. For secondary spacings, a Mullins and Sekerka type formula proved from the start to be adequate in both unsteady- and steady-state heat flows, and so it recommends itself in calibrated form, λ _2 = 12π ( {{4σ }/{X_0 (1 - k)^2 Δ H}( {D/R} )^2 } )^{{1/3}}

Can we identify mothers at-risk for postpartum anxiety in the immediate postpartum period using the State-Trait Anxiety Inventory?

PubMed

Dennis, Cindy-Lee; Coghlan, Michelle; Vigod, Simone

2013-09-25

This study assessed the stability of maternal anxiety and concordance between State-Trait Anxiety Inventory (STAI) scores in the immediate postpartum period to 8 weeks postpartum. A population-based sample of 522 mothers completed the STAI at 1, 4, and 8 weeks postpartum. Sensitivity, specificity, and predictive power of the 1-week STAI in relation to identifying mothers with elevated STAI scores at 4 and 8 weeks was determined. Predictive power of the STAI was further assessed using odds ratios and receiver operator characteristic (ROC) curves. At 1 week postpartum, 22.6% of mothers scored >40 on the STAI, decreasing to 17.2% at 4 weeks and 14.8% at 8 weeks. Using the cut-off score of >40, the 1-week STAI accurately classified 84.0% mothers at 4 weeks and 83.6% at 8 weeks with or without anxiety symptomatology. The 1-week STAI was significantly correlated to the 4-week (r=0.68, p<0.001) and 8-week (r=0.64, p<0.001) STAI. Mothers with a 1-week STAI score >40 were 15.2 times more likely at 4 weeks (95% CI=8.9-26.1) and 14.0 times more likely at 8 weeks (95% CI=7.9-24.8) to exhibit postpartum anxiety symptomatology. Psychiatric interviews were not completed in collaboration with the STAI and specific types of anxiety disorders were not identified. A cut-off score of >40 on the STAI administered early in the postpartum period is recommended in a 2-phase identification program in order to not miss mothers with postpartum anxiety. © 2013 Elsevier B.V. All rights reserved.

Objective approach for analysis of noise source characteristics and acoustic conditions in noisy computerized embroidery workrooms.

PubMed

Aliabadi, Mohsen; Golmohammadi, Rostam; Mansoorizadeh, Muharram

2014-03-01

It is highly important to analyze the acoustic properties of workrooms in order to identify best noise control measures from the standpoint of noise exposure limits. Due to the fact that sound pressure is dependent upon environments, it cannot be a suitable parameter for determining the share of workroom acoustic characteristics in producing noise pollution. This paper aims to empirically analyze noise source characteristics and acoustic properties of noisy embroidery workrooms based on special parameters. In this regard, reverberation time as the special room acoustic parameter in 30 workrooms was measured based on ISO 3382-2. Sound power quantity of embroidery machines was also determined based on ISO 9614-3. Multiple linear regression was employed for predicting reverberation time based on acoustic features of the workrooms using MATLAB software. The results showed that the measured reverberation times in most of the workrooms were approximately within the ranges recommended by ISO 11690-1. Similarity between reverberation time values calculated by the Sabine formula and measured values was relatively poor (R (2) = 0.39). This can be due to the inaccurate estimation of the acoustic influence of furniture and formula preconditions. Therefore, this value cannot be considered representative of an actual acoustic room. However, the prediction performance of the regression method with root mean square error (RMSE) = 0.23 s and R (2) = 0.69 is relatively acceptable. Because the sound power of the embroidery machines was relatively high, these sources get the highest priority when it comes to applying noise controls. Finally, an objective approach for the determination of the share of workroom acoustic characteristics in producing noise could facilitate the identification of cost-effective noise controls.

Surface complexation modeling of Cd(II) sorption to montmorillonite, bacteria, and their composite

NASA Astrophysics Data System (ADS)

Wang, Ning; Du, Huihui; Huang, Qiaoyun; Cai, Peng; Rong, Xingmin; Feng, Xionghan; Chen, Wenli

2016-10-01

Surface complexation modeling (SCM) has emerged as a powerful tool for simulating heavy metal adsorption processes on the surface of soil solid components under different geochemical conditions. The component additivity (CA) approach is one of the strategies that have been widely used in multicomponent systems. In this study, potentiometric titration, isothermal adsorption, zeta potential measurement, and extended X-ray absorption fine-structure (EXAFS) spectra analysis were conducted to investigate Cd adsorption on 2 : 1 clay mineral montmorillonite, on Gram-positive bacteria Bacillus subtilis, and their mineral-organic composite. We developed constant capacitance models of Cd adsorption on montmorillonite, bacterial cells, and mineral-organic composite. The adsorption behavior of Cd on the surface of the composite was well explained by CA-SCM. Some deviations were observed from the model simulations at pH < 5, where the values predicted by the model were lower than the experimental results. The Cd complexes of X2Cd, SOCd+, R-COOCd+, and R-POCd+ were the predominant species on the composite surface over the pH range of 3 to 8. The distribution ratio of the adsorbed Cd between montmorillonite and bacterial fractions in the composite as predicted by CA-SCM closely coincided with the estimated value of EXAFS at pH 6. The model could be useful for the prediction of heavy metal distribution at the interface of multicomponents and their risk evaluation in soils and associated environments.

Nine months in space: effects on human autonomic cardiovascular regulation.

PubMed

Cooke, W H; Ames JE, I V; Crossman, A A; Cox, J F; Kuusela, T A; Tahvanainen, K U; Moon, L B; Drescher, J; Baisch, F J; Mano, T; Levine, B D; Blomqvist, C G; Eckberg, D L

2000-09-01

We studied three Russian cosmonauts to better understand how long-term exposure to microgravity affects autonomic cardiovascular control. We recorded the electrocardiogram, finger photoplethysmographic pressure, and respiratory flow before, during, and after two 9-mo missions to the Russian space station Mir. Measurements were made during four modes of breathing: 1) uncontrolled spontaneous breathing; 2) stepwise breathing at six different frequencies; 3) fixed-frequency breathing; and 4) random-frequency breathing. R wave-to-R wave (R-R) interval standard deviations decreased in all and respiratory frequency R-R interval spectral power decreased in two cosmonauts in space. Two weeks after the cosmonauts returned to Earth, R-R interval spectral power was decreased, and systolic pressure spectral power was increased in all. The transfer function between systolic pressures and R-R intervals was reduced in-flight, was reduced further the day after landing, and had not returned to preflight levels by 14 days after landing. Our results suggest that long-duration spaceflight reduces vagal-cardiac nerve traffic and decreases vagal baroreflex gain and that these changes may persist as long as 2 wk after return to Earth.

Chest wall mobility is related to respiratory muscle strength and lung volumes in healthy subjects.

PubMed

Lanza, Fernanda de Cordoba; de Camargo, Anderson Alves; Archija, Lilian Rocha Ferraz; Selman, Jessyca Pachi Rodrigues; Malaguti, Carla; Dal Corso, Simone

2013-12-01

Chest wall mobility is often measured in clinical practice, but the correlations between chest wall mobility and respiratory muscle strength and lung volumes are unknown. We investigate the associations between chest wall mobility, axillary and thoracic cirtometry values, respiratory muscle strength (maximum inspiratory pressure and maximum expiratory pressure), and lung volumes (expiratory reserve volume, FEV(1), inspiratory capacity, FEV(1)/FVC), and the determinants of chest mobility in healthy subjects. In 64 healthy subjects we measured inspiratory capacity, FVC, FEV(1), expiratory reserve volume, maximum inspiratory pressure, and maximum expiratory pressure, and chest wall mobility via axillary and thoracic cirtometry. We used linear regression to evaluate the influence of the measured variables on chest wall mobility. The subjects' mean ± SD values were: age 24 ± 3 years, axillary cirtometry 6.3 ± 2.0 cm, thoracic cirtometry 7.5 ± 2.3 cm; maximum inspiratory pressure 90.4 ± 10.6% of predicted, maximum expiratory pressure 92.8 ± 13.5% of predicted, inspiratory capacity 99.7 ± 8.6% of predicted, FVC 101.9 ± 10.6% of predicted, FEV(1) 98.2 ± 10.3% of predicted, expiratory reserve volume 90.9 ± 19.9% of predicted. There were significant correlations between axillary cirtometry and FVC (r = 0.32), FEV(1) (r = 0.30), maximum inspiratory pressure (r = 0.48), maximum expiratory pressure (r = 0.25), and inspiratory capacity (r = 0.24), and between thoracic cirtometry and FVC (r = 0.50), FEV(1) (r = 0.48), maximum inspiratory pressure (r = 0.46), maximum expiratory pressure (r = 0.37), inspiratory capacity (r = 0.39), and expiratory reserve volume (r = 0.47). In multiple regression analysis the variable that best explained the axillary cirtometry variation was maximum inspiratory pressure (R(2) 0.23), and for thoracic cirtometry it was FVC and maximum inspiratory pressure (R(2) 0.32). Chest mobility in healthy subjects is related to respiratory muscle strength and lung function; the higher the axillary cirtometry and thoracic cirtometry values, the greater the maximum inspiratory pressure, maximum expiratory pressure, and lung volumes in healthy subjects.

Assessment of Passive Intestinal Permeability Using an Artificial Membrane Insert System.

PubMed

Berben, Philippe; Brouwers, Joachim; Augustijns, Patrick

2018-01-01

Despite reasonable predictive power of current cell-based and cell-free absorption models for the assessment of intestinal drug permeability, high costs and lengthy preparation steps hamper their use. The use of a simple artificial membrane (without any lipids present) as intestinal barrier substitute would overcome these hurdles. In the present study, a set of 14 poorly water-soluble drugs, dissolved in 2 different media (fasted state simulated/human intestinal fluids [FaSSIF/FaHIF]), were applied to the donor compartment of an artificial membrane insert system (AMI-system) containing a regenerated cellulose membrane. Furthermore, to investigate the predictive capacity of the AMI-system as substitute for the well-established Caco-2 system to assess intestinal permeability, the same set of 14 drugs dissolved in FaHIF were applied to the donor compartment of a Caco-2 system. For 14 drugs, covering a broad range of physicochemical parameters, a reasonable correlation between both absorption systems was observed, characterized by a Pearson correlation coefficient r of 0.95 (FaHIF). Using the AMI-system, an excellent predictive capacity of FaSSIF as surrogate medium for FaHIF was demonstrated (r = 0.96). Based on the acquired data, the AMI-system appears to be a time- and cost-effective tool for the early-stage estimation of passive intestinal permeability for poorly water-soluble drugs. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Galaxy formation with BECDM - I. Turbulence and relaxation of idealized haloes

NASA Astrophysics Data System (ADS)

Mocz, Philip; Vogelsberger, Mark; Robles, Victor H.; Zavala, Jesús; Boylan-Kolchin, Michael; Fialkov, Anastasia; Hernquist, Lars

2017-11-01

We present a theoretical analysis of some unexplored aspects of relaxed Bose-Einstein condensate dark matter (BECDM) haloes. This type of ultralight bosonic scalar field dark matter is a viable alternative to the standard cold dark matter (CDM) paradigm, as it makes the same large-scale predictions as CDM and potentially overcomes CDM's small-scale problems via a galaxy-scale de Broglie wavelength. We simulate BECDM halo formation through mergers, evolved under the Schrödinger-Poisson equations. The formed haloes consist of a soliton core supported against gravitational collapse by the quantum pressure tensor and an asymptotic r-3 NFW-like profile. We find a fundamental relation of the core-to-halo mass with the dimensionless invariant Ξ ≡ |E|/M3/(Gm/ℏ)2 or Mc/M ≃ 2.6Ξ1/3, linking the soliton to global halo properties. For r ≥ 3.5 rc core radii, we find equipartition between potential, classical kinetic and quantum gradient energies. The haloes also exhibit a conspicuous turbulent behaviour driven by the continuous reconnection of vortex lines due to wave interference. We analyse the turbulence 1D velocity power spectrum and find a k-1.1 power law. This suggests that the vorticity in BECDM haloes is homogeneous, similar to thermally-driven counterflow BEC systems from condensed matter physics, in contrast to a k-5/3 Kolmogorov power law seen in mechanically-driven quantum systems. The mode where the power spectrum peaks is approximately the soliton width, implying that the soliton-sized granules carry most of the turbulent energy in BECDM haloes.

Cerebral and somatic near-infrared spectroscopy measurements during fluid challenge in cardiac surgery patients: a descriptive pilot study.

PubMed

Fellahi, Jean-Luc; Fischer, Marc-Olivier; Rebet, Olivier; Dalbera, Audrey; Massetti, Massimo; Gérard, Jean-Louis; Hanouz, Jean-Luc

2013-04-01

Little is known about changes in near-infrared spectroscopy (NIRS)-derived cerebral (rSO(2)b) and somatic (rSO(2)s) oxygen saturation during a fluid challenge. The authors tested the hypothesis that they could differ from central venous oxygen saturation (ScvO(2)) and from one site to another. A prospective observational study. A teaching university hospital. Fifty consecutive adult patients. Admission to the intensive care unit after cardiac surgery and investigation before and after a fluid challenge. Simultaneous comparative ScvO(2), rSO(2)b, and rSO(2)s data points were collected from a blood-gas analyzer and the EQUANOX monitor (Nonin Medical, Inc, Plymouth, MN). Correlations were determined by linear regression. Multiple stepwise linear regression models were used to assess independent variables associated with changes in ScvO(2), rSO(2)b, and rSO(2)s. A statistically significant relationship was found between absolute values of ScvO(2) and rSO(2)b (r = 0.42, p < 0.001) but not between absolute values of ScvO(2) and rSO(2)s (r = 0.18, p = 0.066). No relationship was found between percent changes in ScvO(2) and rSO(2)b (r = 0.05, p = 0.715) and between percent changes in ScvO(2) and rSO(2)s (r = 0.02, p = 0.886) after the fluid challenge. Cardiac index contributed to the prediction of changes in ScvO(2) (regression coefficient = -4.09, p = 0.006), whereas the mean arterial pressure contributed to the prediction of changes in rSO(2)b (regression coefficient = -0.05, p = 0.027). rSO(2)b and rSO(2)s cannot be used to provide noninvasive estimation of ScvO(2), and trends in rSO(2)b and rSO(2)s cannot be considered as noninvasive surrogates for the trend in ScvO(2) after cardiac surgery. Different independent variables contribute to the prediction of ScvO(2), rSO(2)b, and rSO(2)s. Copyright © 2013 Elsevier Inc. All rights reserved.

Light Water Reactor Sustainability (LWRS) Program – Non-Destructive Evaluation (NDE) R&D Roadmap for Determining Remaining Useful Life of Aging Cables in Nuclear Power Plants

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

Simmons, K.L.; Ramuhali, P.; Brenchley, D.L.

2012-09-01

Executive Summary [partial] The purpose of the non-destructive evaluation (NDE) R&D Roadmap for Cables is to support the Materials Aging and Degradation (MAaD) R&D pathway. A workshop was held to gather subject matter experts to develop the NDE R&D Roadmap for Cables. The focus of the workshop was to identify the technical gaps in detecting aging cables and predicting their remaining life expectancy. The workshop was held in Knoxville, Tennessee, on July 30, 2012, at Analysis and Measurement Services Corporation (AMS) headquarters. The workshop was attended by 30 experts in materials, electrical engineering, and NDE instrumentation development from the U.S.more » Nuclear Regulatory Commission (NRC), U.S. Department of Energy (DOE) National Laboratories (Oak Ridge National Laboratory, Pacific Northwest National Laboratory, Argonne National Laboratory, and Idaho National Engineering Laboratory), universities, commercial NDE service vendors and cable manufacturers, and the Electric Power Research Institute (EPRI).« less

Spatial Distribution of Large Cloud Drops

NASA Technical Reports Server (NTRS)

Marshak, A.; Knyazikhin, Y.; Larsen, M.; Wiscombe, W.

2004-01-01

By analyzing aircraft measurements of individual drop sizes in clouds, we have shown in a companion paper (Knyazikhin et al., 2004) that the probability of finding a drop of radius r at a linear scale l decreases as l(sup D(r)) where 0 less than or equal to D(r) less than or equal to 1. This paper shows striking examples of the spatial distribution of large cloud drops using models that simulate the observed power laws. In contrast to currently used models that assume homogeneity and therefore a Poisson distribution of cloud drops, these models show strong drop clustering, the more so the larger the drops. The degree of clustering is determined by the observed exponents D(r). The strong clustering of large drops arises naturally from the observed power-law statistics. This clustering has vital consequences for rain physics explaining how rain can form so fast. It also helps explain why remotely sensed cloud drop size is generally biased and why clouds absorb more sunlight than conventional radiative transfer models predict.

Simple prediction method of lumbar lordosis for planning of lumbar corrective surgery: radiological analysis in a Korean population.

PubMed

Lee, Chong Suh; Chung, Sung Soo; Park, Se Jun; Kim, Dong Min; Shin, Seong Kee

2014-01-01

This study aimed at deriving a lordosis predictive equation using the pelvic incidence and to establish a simple prediction method of lumbar lordosis for planning lumbar corrective surgery in Asians. Eighty-six asymptomatic volunteers were enrolled in the study. The maximal lumbar lordosis (MLL), lower lumbar lordosis (LLL), pelvic incidence (PI), and sacral slope (SS) were measured. The correlations between the parameters were analyzed using Pearson correlation analysis. Predictive equations of lumbar lordosis through simple regression analysis of the parameters and simple predictive values of lumbar lordosis using PI were derived. The PI strongly correlated with the SS (r = 0.78), and a strong correlation was found between the SS and LLL (r = 0.89), and between the SS and MLL (r = 0.83). Based on these correlations, the predictive equations of lumbar lordosis were found (SS = 0.80 + 0.74 PI (r = 0.78, R (2) = 0.61), LLL = 5.20 + 0.87 SS (r = 0.89, R (2) = 0.80), MLL = 17.41 + 0.96 SS (r = 0.83, R (2) = 0.68). When PI was between 30° to 35°, 40° to 50° and 55° to 60°, the equations predicted that MLL would be PI + 10°, PI + 5° and PI, and LLL would be PI - 5°, PI - 10° and PI - 15°, respectively. This simple calculation method can provide a more appropriate and simpler prediction of lumbar lordosis for Asian populations. The prediction of lumbar lordosis should be used as a reference for surgeons planning to restore the lumbar lordosis in lumbar corrective surgery.

CONSTRAINING POLARIZED FOREGROUNDS FOR EoR EXPERIMENTS. I. 2D POWER SPECTRA FROM THE PAPER-32 IMAGING ARRAY

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

Kohn, S. A.; Aguirre, J. E.; Moore, D. F.

2016-06-01

Current generation low-frequency interferometers constructed with the objective of detecting the high-redshift 21 cm background aim to generate power spectra of the brightness temperature contrast of neutral hydrogen in primordial intergalactic medium. Two-dimensional (2D) power spectra (power in Fourier modes parallel and perpendicular to the line of sight) that formed from interferometric visibilities have been shown to delineate a boundary between spectrally smooth foregrounds (known as the wedge ) and spectrally structured 21 cm background emission (the EoR window ). However, polarized foregrounds are known to possess spectral structure due to Faraday rotation, which can leak into the EoR window.more » In this work we create and analyze 2D power spectra from the PAPER-32 imaging array in Stokes I, Q, U, and V. These allow us to observe and diagnose systematic effects in our calibration at high signal-to-noise within the Fourier space most relevant to EoR experiments. We observe well-defined windows in the Stokes visibilities, with Stokes Q, U, and V power spectra sharing a similar wedge shape to that seen in Stokes I. With modest polarization calibration, we see no evidence that polarization calibration errors move power outside the wedge in any Stokes visibility to the noise levels attained. Deeper integrations will be required to confirm that this behavior persists to the depth required for EoR detection.« less

The status and predictors of hypertension preventive nutritional behaviors in adolescents based on the constructs of the Theory of Planned Behavior.

PubMed

Matlabi, Mohammad; Esmaeili, Reza; Moshki, Mahdi; Ranaei, Afsaneh; Haji, Alireza; Mehrabi, Rahele

2018-01-01

Malnutrition is an important factor affecting hypertensive incidence. Since the unhealthiest nutritional behaviors are rooted in childhood attitudes and experiences, applying educational interventions to these age groups will be most useful in the formation of preventive nutritional behaviors. To determine the predictive power of the TPB on hypertension in junior high-school students. The present cross-sectional study was conducted on 160 junior high-school students in Kashmar, Iran in academic year commencing 2-13-2014, selected through random sampling. The participants completed a researcher-made questionnaire consisting of a demographic information form and a section to evaluate the constructs of the TPB. The data collected were analyzed in SPSS-16 using the correlation Wilcoxon statistics test, the one-way ANOVA and multiple linear regression analysis. The mean age of the students was 13.51. A total of 47% of the students had snacked on potato chips and cheese puffs, 45% had eaten high-fat foods and 51.2% had eaten cookies and chocolates within the past week. The variable of behavioral intention predicted 32% of the variations in preventive nutritional behaviors by itself. The Pearson product-moment correlation analysis found that hypertension preventive nutritional behaviors were significantly correlated with attitude (p<0.001, r=0.38), perceived behavioral control (p<0.001, r=0.38), and behavioral intention. Moreover, significant correlations were observed between subjective norms and attitude (p<0.028, r=0.173), perceived behavioral control and attitude (p<0.003, r=0.231), behavioral intention and attitude (p<0.001, r=0.370), behavioral intention and subjective norms (p<0.030, r=0.171) and between behavioral intention and perceived behavioral control (p<0.001, r=0.484). The examined students revealed an adequate adherence to preventive nutritional behaviors. Nutrition education interventions should be developed based on variables such as behavioral intention and its determinants, i.e. attitude, perceived behavioral control and subjective norms.

A new phenomenological /τ-/α interaction

NASA Astrophysics Data System (ADS)

Heiberg-Andersen, H.; Mackintosh, R. S.; Vaagen, J. S.

2003-01-01

We present a potential model, with distinctive features, reproducing angular distributions and analyzing power data for τ- α scattering from 20 to 30 MeV τ energy with regular variation of the parameters. The distinctive features are: (1) a spin-orbit term which incorporates the influence of central depression in the α nucleus, and, (2) central terms which are strongly parity dependent. The parity dependence of the real central term is such that the odd-parity component has both a greater rms radius and greater volume integral than the even-parity component. These parity dependence characteristics had been predicted by the inversion of the RGM S-matrix. Our result supports a considerable contribution from three-nucleon exchange processes. The predicted 1/2 - level of 7Be is shifted 3 MeV relative to a previous one-level R-matrix formula fit, and depends strongly on the geometry of the spin-orbit potential.

Propulsion and Power Rapid Response R&D Support Delivery Order 0041: Power Dense Solid Oxide Fuel Cell Systems: High Performance, High Power Density Solid Oxide Fuel Cells - Materials and Load Control

DTIC Science & Technology

2008-12-01

respectively. 2.3.1.2 Brushless DC Motor Brushless direct current ( BLDC ) motors feature high efficiency, ease of control , and astonishingly high power...modeling purposes, we ignore the modeling complexity of the BLDC controller and treat the motor and controller “as commutated”, i.e. we assume the...High Performance, High Power Density Solid Oxide Fuel Cells− Materials and Load Control Stephen W. Sofie, Steven R. Shaw, Peter A. Lindahl, and Lee H

Evolutionary search for novel superhard phases, or can TiO2 be the hardest oxide? (Invited)

NASA Astrophysics Data System (ADS)

Oganov, A. R.; Lyakhov, A. O.

2010-12-01

Synthesis of novel superhard materials, frequently achieved with high-pressure experimental techniques, is a difficult task. Study of such materials, usually first obtained in very small quantities, is complicated, and this field is full of controversies and artefacts (see, e.g. [1]). Hardness was long believed to be an exceedingly difficult property to model or predict; however, a number of simple models have recently been proposed and shown to yield surprisingly accurate results (see reviews in [2]). We have found [3] a way to further improve these models, by augmenting them with bond-valence model and graph theory. Combining such models with our structure prediction method [4], we have developed a powerful [5] approach for computational design of novel superhard materials. Using this method, we recently addressed [3] the previously proposed [6] possibility that C3N4 may be harder than diamond, and the claim [7] that TiO2-cotunnite is the hardest oxide with the Vickers hardness of 38 GPa. Our results unequivocally suggest that the latter suggestion is incorrect. No TiO2 polymorph can attain hardness greater than 17 GPa [3], i.e. all possible structures of TiO2 are softer than common corundum (Al2O3). Furthermore, TiO2-cotunnite is dynamically unstable at atmospheric pressure [8]. REFERENCES: [1] Oganov A.R., Solozhenko V.L., Kurakevych O.O., Gatti C., Ma Y., Chen J., Liu Z., and Hemley R.J., http://arxiv.org/abs/ 0908.2126 (2009). [2] Theory of Superhard Materials (Special Issue), J. Superhard Materials, issue 3 (2010). [3] Lyakhov A.O., Oganov A.R., in prep. (2010). [4] Oganov A.R., Glass C.W., J. Chem. Phys. 124, 244704 (2006). [5] Oganov A.R., Lyakhov A.O., J. Superhard Mater. 32, 143-147 (2010). [6] Liu A.Y., Cohen M.L., Science 245, 841-842 (1989). [7] Dubrovinsky L.S., Dubrovinskaia N.A., et al., Nature 410, 653-654 (2001). [8] Kim D.Y., et al., Appl. Phys. Lett. 90, 171903 (2007).

Continuous-wave Nd:GYSGG laser at 1.1 μm

NASA Astrophysics Data System (ADS)

Lin, Hongyi; Liu, Hong; Huang, Xiaohua; Copner, Nigel; Sun, Dong

2018-02-01

We demonstrated a compact and simple continuous-wave (CW) Nd:GYSGG laser with triple-wavelength lines at 1105, 1107 and 1110 nm based on R2 → Y6, R1 → Y5 and R1 → Y6 of the 4F3/2 → 4I11/2 transition. The total output power of the triple-wavelength lines was 480 mW. Moreover, we obtained an efficient CW Nd:GYSGG laser at 1110 nm with the output power of 1560 mW at the pump power of 11.05 W. Those lines at 1058 and 1062 nm were suppressed completely by the simple output mirror of high transmission at 1.06 μm.

Exploring the Effects of Low Power Schemas in Mothers.

ERIC Educational Resources Information Center

Mills, Rosemary S. L.

1999-01-01

Assessed whether low perceived maternal power and temperamentally fearful preschool-aged daughters predicted subsequent maternal overcontrol and internalizing symptoms in daughters 2 years later. Found that low perceived maternal power predicted subsequent maternal overcontrol with initially fearful daughters but did not predict subsequent…

Controls on delta formation, area, and topset slope: New predictive relationships developed using a global delta dataset

NASA Astrophysics Data System (ADS)

Caldwell, R. L.; Edmonds, D. A.; Baumgardner, S. E.; Paola, C.; Roy, S.; Nienhuis, J.

2017-12-01

River deltas are irreplaceable natural and societal resources, though they are at risk of drowning due to sea-level rise and decreased sediment delivery. To enhance hazard mitigation efforts in the face of global environmental change, we must understand the controls on delta growth. Previous empirical studies of delta growth are based on small datasets and often biased towards large, river-dominated deltas. We are currently lacking relationships that predict delta formation, area, or topset slope across the full breadth of global deltas. To this end, we developed a global dataset of 5,229 rivers (with and without deltas) paired with nine upstream (e.g., sediment discharge) and four downstream (e.g., wave height) environmental variables. Using Google Earth imagery, we identify all coastal river mouths (≥ 50 m wide) connected to an upstream catchment, and define deltas as river mouths that split into two or more distributary channels, end in a depositional protrusion from the shoreline, or do both. Delta area is defined as the area of the polygon connecting the delta node, two lateral shoreline extent points, and the basinward-most extent of the delta. Topset slope is calculated as the average, linear slope from the delta node elevation (extracted from SRTM data) to the main channel mouth, and shoreline and basinward extent points. Of the 5,229 rivers in our dataset, 1,816 (35%) have a delta. Using 495 rivers (those with data available for all variables), we build an empirically-derived relationship that predicts delta formation with 76% success. Delta formation is controlled predominantly by upstream water and sediment discharge, with secondary control by downstream waves and tides that suppress delta formation. For those rivers that do form deltas, we show that delta area is best predicted by sediment discharge, bathymetric slope, and drainage basin area (R2 = 0.95, n = 170), and exhibits a negative power-law relationship with topset slope (R2 = 0.85, n = 1,342). Topset slope is best predicted by grain size and wave height (R2 = 0.50, n = 358). These empirical relationships can aid in forecasting delta response to continued global environmental change.

Implementation of model predictive control for resistive wall mode stabilization on EXTRAP T2R

NASA Astrophysics Data System (ADS)

Setiadi, A. C.; Brunsell, P. R.; Frassinetti, L.

2015-10-01

A model predictive control (MPC) method for stabilization of the resistive wall mode (RWM) in the EXTRAP T2R reversed-field pinch is presented. The system identification technique is used to obtain a linearized empirical model of EXTRAP T2R. MPC employs the model for prediction and computes optimal control inputs that satisfy performance criterion. The use of a linearized form of the model allows for compact formulation of MPC, implemented on a millisecond timescale, that can be used for real-time control. The design allows the user to arbitrarily suppress any selected Fourier mode. The experimental results from EXTRAP T2R show that the designed and implemented MPC successfully stabilizes the RWM.

On the relationships between hardness and the elastic and plastic properties of isotropic power-law hardening materials

NASA Astrophysics Data System (ADS)

Lan, Hongzhi; Venkatesh, T. A.

2014-01-01

A comprehensive understanding of the relationship between the hardness and the elastic and plastic properties for a wide range of materials is obtained by analysing the hardness characteristics (that are predicted by experimentally verified indentation analyses) of over 9000 distinct combinations of material properties that represent isotropic, homogeneous, power-law hardening metallic materials. Finite element analysis has been used to develop the indentation algorithms that provide the relationships between the elastic and plastic properties of the indented material and its indentation hardness. Based on computational analysis and virtual testing, the following observations are made. The hardness (H) of a material tends to increase with an increase in the elastic modulus (E), yield strength (σy) and the strain-hardening exponent (n). Several materials with different combinations of elastic and plastic properties can exhibit identical true hardness (for a particular indenter geometry/apex angle). In general, combinations of materials that exhibit relatively low elastic modulus and high yield strength or strain-hardening exponents and those that exhibit relatively high elastic modulus and low yield strength or strain-hardening exponents exhibit similar hardness properties. Depending on the strain-hardening characteristics of the indented material, (i.e. n = 0 or ?), the ratio H/σy ranges, respectively, from 2.2 to 2.6 or 2 to 20 (for indentations with a cone angle of 70.3°). The materials that have lower σy/E and higher n exhibit higher H/σy ratios. The commonly invoked relationship between hardness and the yield strength, i.e. H ≈ 3σy, is not generally valid or applicable for all power-law hardening materials. The indentation hardness of a power law hardening material can be taken as following the relationship H ≈ (2.1-2.8)σr where σr is the representative stress based on Tabor's representative strain for a wide range of materials.

efficient association study design via power-optimized tag SNP selection

PubMed Central

HAN, BUHM; KANG, HYUN MIN; SEO, MYEONG SEONG; ZAITLEN, NOAH; ESKIN, ELEAZAR

2008-01-01

Discovering statistical correlation between causal genetic variation and clinical traits through association studies is an important method for identifying the genetic basis of human diseases. Since fully resequencing a cohort is prohibitively costly, genetic association studies take advantage of local correlation structure (or linkage disequilibrium) between single nucleotide polymorphisms (SNPs) by selecting a subset of SNPs to be genotyped (tag SNPs). While many current association studies are performed using commercially available high-throughput genotyping products that define a set of tag SNPs, choosing tag SNPs remains an important problem for both custom follow-up studies as well as designing the high-throughput genotyping products themselves. The most widely used tag SNP selection method optimizes over the correlation between SNPs (r2). However, tag SNPs chosen based on an r2 criterion do not necessarily maximize the statistical power of an association study. We propose a study design framework that chooses SNPs to maximize power and efficiently measures the power through empirical simulation. Empirical results based on the HapMap data show that our method gains considerable power over a widely used r2-based method, or equivalently reduces the number of tag SNPs required to attain the desired power of a study. Our power-optimized 100k whole genome tag set provides equivalent power to the Affymetrix 500k chip for the CEU population. For the design of custom follow-up studies, our method provides up to twice the power increase using the same number of tag SNPs as r2-based methods. Our method is publicly available via web server at http://design.cs.ucla.edu. PMID:18702637

Prediction of parenteral nutrition osmolarity by digital refractometry.

PubMed

Chang, Wei-Kuo; Yeh, Ming-Kung

2011-05-01

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

Evaluating diagnosis-based risk-adjustment methods in a population with spinal cord dysfunction.

PubMed

Warner, Grace; Hoenig, Helen; Montez, Maria; Wang, Fei; Rosen, Amy

2004-02-01

To examine performance of models in predicting health care utilization for individuals with spinal cord dysfunction. Regression models compared 2 diagnosis-based risk-adjustment methods, the adjusted clinical groups (ACGs) and diagnostic cost groups (DCGs). To improve prediction, we added to our model: (1) spinal cord dysfunction-specific diagnostic information, (2) limitations in self-care function, and (3) both 1 and 2. Models were replicated in 3 populations. Samples from 3 populations: (1) 40% of veterans using Veterans Health Administration services in fiscal year 1997 (FY97) (N=1,046,803), (2) veteran sample with spinal cord dysfunction identified by codes from the International Statistical Classification of Diseases, 9th Revision, Clinical Modifications (N=7666), and (3) veteran sample identified in Veterans Affairs Spinal Cord Dysfunction Registry (N=5888). Not applicable. Inpatient, outpatient, and total days of care in FY97. The DCG models (R(2) range,.22-.38) performed better than ACG models (R(2) range,.04-.34) for all outcomes. Spinal cord dysfunction-specific diagnostic information improved prediction more in the ACG model than in the DCG model (R(2) range for ACG,.14-.34; R(2) range for DCG,.24-.38). Information on self-care function slightly improved performance (R(2) range increased from 0 to.04). The DCG risk-adjustment models predicted health care utilization better than ACG models. ACG model prediction was improved by adding information.

The construction, testing, and installation of a 6500 r/min 15 000-hp adjustable-speed electric drive for a centrifugal gas compressor

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

Lawrence, R.G.; Finney, D.; Davidson, D.F.

1988-07-01

The construction, testing, and installation of a 6500 r/min 15 000-hp adjustable-speed electric drive for a centrifugal gas compressor is presented. A power electronic converter is applied to control the speed of a 5-kV motor. The motor is directly coupled to a 6500 r/min compressor and replaced a steam turbine. Dual converters are used in a twelve-pulse arrangement at both the utility and the motor. The motor is of solid rotor construction, with dual 30/sup 0/ displaced stator windings. Finite-element analysis is used to optimize the motor designs for use with a variable-frequency static converter. Full-power tests are completed whichmore » confirm theoretical predictions on losses, performance, and operation. The electrical drive takes up considerably less space and is much more efficient than the steam turbine it replaced.« less

The Mach number of the cosmic flow - A critical test for current theories

NASA Technical Reports Server (NTRS)

Ostriker, Jeremiah P.; Suto, Yusushi

1990-01-01

A new cosmological, self-contained test using the ratio of mean velocity and the velocity dispersion in the mean flow frame of a group of test objects is presented. To allow comparison with linear theory, the velocity field must first be smoothed on a suitable scale. In the context of linear perturbation theory, the Mach number M(R) which measures the ratio of power on scales larger than to scales smaller than the patch size R, is independent of the perturbation amplitude and also of bias. An apparent inconsistency is found for standard values of power-law index n = 1 and cosmological density parameter Omega = 1, when comparing values of M(R) predicted by popular models with tentative available observations. Nonstandard models based on adiabatic perturbations with either negative n or small Omega value also fail, due to creation of unacceptably large microwave background fluctuations.

Development of prediction equations for estimating appendicular skeletal muscle mass in Japanese men and women.

PubMed

Furushima, Taishi; Miyachi, Motohiko; Iemitsu, Motoyuki; Murakami, Haruka; Kawano, Hiroshi; Gando, Yuko; Kawakami, Ryoko; Sanada, Kiyoshi

2017-08-29

This study aimed to develop and cross-validate prediction equations for estimating appendicular skeletal muscle mass (ASM) and to examine the relationship between sarcopenia defined by the prediction equations and risk factors for cardiovascular diseases (CVD) or osteoporosis in Japanese men and women. Subjects were healthy men and women aged 20-90 years, who were randomly allocated to the following two groups: the development group (D group; 257 men, 913 women) and the cross-validation group (V group; 119 men, 112 women). To develop prediction equations, stepwise multiple regression analyses were performed on data obtained from the D group, using ASM measured by dual-energy X-ray absorptiometry (DXA) as a dependent variable and five easily obtainable measures (age, height, weight, waist circumference, and handgrip strength) as independent variables. When the prediction equations for ASM estimation were applied to the V group, a significant correlation was found between DXA-measured ASM and predicted ASM in both men and women (R 2  = 0.81 and R 2  = 0.72). Our prediction equations had higher R 2 values compared to previously developed equations (R 2  = 0.75-0.59 and R 2  = 0.69-0.40) in both men and women. Moreover, sarcopenia defined by predicted ASM was related to risk factors for osteoporosis and CVD, as well as sarcopenia defined by DXA-measured ASM. In this study, novel prediction equations were developed and cross-validated in Japanese men and women. Our analyses validated the clinical significance of these prediction equations and showed that previously reported equations were not applicable in a Japanese population.

Predicting meat quality traits of ovine m. semimembranosus, both fresh and following freezing and thawing, using a hand held Raman spectroscopic device.

PubMed

Fowler, Stephanie M; Schmidt, Heinar; van de Ven, Remy; Wynn, Peter; Hopkins, David L

2015-10-01

Complementary studies were conducted to determine the potential for a Raman spectroscopic hand held device to predict meat quality traits of fresh lamb m. semimembranosus (topside) after ageing and freezing/thawing. Spectra were collected from 80 fresh muscles at 24h and 5d PM, another 80 muscles were measured at 24h, 5d and following freezing/thawing. Shear force, cooking loss, sarcomere length, colour, particle size, collagen content, pH24, pHu, purge and thaw loss were also measured. Results indicated a potential to predict pHu (R(2)cv=0.59), pH24 (R(2)cv=0.48) and purge (R(2)cv=0.42) using spectra collected 24h PM. L* could be predicted using spectra collected 24h (R(2)cv=0.33) or 5d PM (R(2)cv=0.33). This suggests that Raman spectroscopy is suited to identifying carcases which deviate from the normal metabolic processes and related meat quality traits. Copyright © 2015. Published by Elsevier Ltd.

The effect of dissolved oxygen on the relaxation rates of blood plasma: Implications for hyperoxia calibrated BOLD.

PubMed

Ma, Yuhan; Berman, Avery J L; Pike, G Bruce

2016-12-01

To determine the contribution of paramagnetic dissolved oxygen in blood plasma to blood-oxygenation-level-dependent (BOLD) signal changes in hyperoxic calibrated BOLD studies. Bovine blood plasma samples were prepared with partial pressures of oxygen (pO 2 ) ranging from 110 to 600 mmHg. R 1 , R 2 , and R 2 * of the plasma with dissolved oxygen were measured using quantitative MRI sequences at 3 Tesla. Simulations were performed to predict the relative effects of dissolved oxygen and deoxyhemoglobin changes in hyperoxia calibrated BOLD. The relaxivities of dissolved oxygen in plasma were found to be r 1, O2 =1.97 ± 0.09 ×10 -4 s -1 mmHg -1 , r 2, O2 =2.3 ± 0.7 ×10 -4 s -1 mmHg -1 , and r 2, O2 * = 2.3 ± 0.7 ×10 -4 s -1 mmHg -1 . Simulations predict that neither the transverse nor longitudinal relaxation rates of dissolved oxygen contribute significantly to the BOLD signal during hyperoxia. During hyperoxia, the increases in R 2 and R 2 * of blood from dissolved oxygen in plasma are considerably less than the decreases in R 2 and R 2 * from venous deoxyhemoglobin. R 1 effects due to dissolved oxygen are also predicted to be negligible. As a result, dissolved oxygen in arteries should not contribute significantly to the hyperoxic calibrated BOLD signal. Magn Reson Med 76:1905-1911, 2016. © 2015 International Society for Magnetic Resonance in Medicine. © 2015 International Society for Magnetic Resonance in Medicine.

FOUR Score Predicts Early Outcome in Patients After Traumatic Brain Injury.

PubMed

Nyam, Tee-Tau Eric; Ao, Kam-Hou; Hung, Shu-Yu; Shen, Mei-Li; Yu, Tzu-Chieh; Kuo, Jinn-Rung

2017-04-01

The aim of the study was to determine whether the Full Outline of UnResponsiveness (FOUR) score, which includes eyes opening (E), motor function (M), brainstem reflex (B), and respiratory pattern (R), can be used as an alternate method to the Glasgow Coma Scale (GCS) in predicting intensive care unit (ICU) mortality in traumatic brain injury (TBI) patients. From January 2015 to June 2015, patients with isolated TBI admitted to the ICU were enrolled. Three advanced practice nurses administered the FOUR score, GCS, Acute Physiology and Chronic Health Evaluation II (APACHE II), and Therapeutic Intervention Scoring System (TISS) concurrently from ICU admissions. The endpoint of observation was mortality when the patients left the ICU. Data are presented as frequency with percentages, mean with standard deviation, or median with interquartile range. Each measurement tool used area under the receiver operating characteristic curve to compare the predictive power between these four tools. In addition, the difference between survival and death was estimated using the Wilcoxon rank sum test. From 55 TBI patients, males (72.73 %) were represented more than females, the mean age was 63.1 ± 17.9, and 19 of 55 observations (35 %) had a maximum FOUR score of 16. The overall mortality rate was 14.6 %. The area under the receiver operating characteristic curve was 74.47 % for the FOUR score, 74.73 % for the GCS, 81.78 % for the APACHE II, and 53.32 % for the TISS. The FOUR score has similar predictive power of mortality compared to the GCS and APACHE II. Each of the parameters-E, M, B, and R-of the FOUR score showed a significant difference between mortality and survival group, while the verbal and eye-opening components of the GCS did not. Having similar predictive power of mortality compared to the GCS and APACHE II, the FOUR score can be used as an alternative in the prediction of early mortality in TBI patients in the ICU.

Fast sintering of silver nanoparticle and flake layers by infrared module assistance in large area roll-to-roll gravure printing system

PubMed Central

Park, Janghoon; Kang, Hyi Jae; Shin, Kee-Hyun; Kang, Hyunkyoo

2016-01-01

We present fast sintering for silver (Ag) nanoparticle (NP) and flake layers printed using roll-to-roll (R2R) gravure printing. An infrared (IR) sintering module was applied to an R2R system to shorten the sintering duration of an R2R gravure-printed Ag layer. IR sintering of the conductive layer was improved by optimising the process condition. After printing of the Ag NP and Ag flake layers, additional IR sintering was performed in the R2R system. The lowest sheet resistance obtained in the Ag NP layer was 0.294 Ω/□, the distance between the substrate and lamp was 50-mm long, the IR lamp power was 500 W, and the sintering time was 5.4 s. The fastest sintering of 0.34 Ω/□ was achieved with 50-mm distance, 1,000-W IR lamp power, and 1.08-s sintering time. In the Ag flake layer, the lowest sheet resistance obtained was 0.288 Ω/□ with a 20-mm distance, 1,000-W IR lamp power, and 10.8-s sintering time. Meanwhile, the fastest sintering was obtained with a 3.83 Ω/□ sheet resistance, 20-mm distance, 1000-W IR lamp, and 1.08-s sintering time. Thus, the IR sintering module can easily be employed in an R2R system to obtain excellent layer sheet resistance. PMID:27713469

Fully roll-to-roll gravure printed rectenna on plastic foils for wireless power transmission at 13.56 MHz.

PubMed

Park, Hyejin; Kang, Hwiwon; Lee, Yonggil; Park, Yongsu; Noh, Jinsoo; Cho, Gyoujin

2012-08-31

Wireless power transmission to inexpensive and disposable smart electronic devices is one of the key issues for the realization of a ubiquitous society where sensor networks such as RFID tags, price tags, smart logos, signage and sensors could be fully interconnected and utilized by DC power of less than 0.3 W. This DC power can be provided by inductively coupled AC from a 13.56 MHz power transmitter through a rectenna, consisting of an antenna, a diode and a capacitor, which would be cheap to integrate with inexpensive smart electronic devices. To integrate the rectenna with a minimum cost, a roll-to-roll (R2R) gravure printing process has been considered to print the rectenna on plastic foils. In this paper, R2R gravure printing systems including printing condition and four different nanoparticle based inks will be reported to print the rectenna (antenna, diode and capacitor) on plastic foils at a printing speed of 8 m min(-1) and more than 90% device yield for a wireless power transmission of 0.3 W using a standard 13.56 MHz power transmitter.

Fully roll-to-roll gravure printed rectenna on plastic foils for wireless power transmission at 13.56 MHz

NASA Astrophysics Data System (ADS)

Park, Hyejin; Kang, Hwiwon; Lee, Yonggil; Park, Yongsu; Noh, Jinsoo; Cho, Gyoujin

2012-08-01

Wireless power transmission to inexpensive and disposable smart electronic devices is one of the key issues for the realization of a ubiquitous society where sensor networks such as RFID tags, price tags, smart logos, signage and sensors could be fully interconnected and utilized by DC power of less than 0.3 W. This DC power can be provided by inductively coupled AC from a 13.56 MHz power transmitter through a rectenna, consisting of an antenna, a diode and a capacitor, which would be cheap to integrate with inexpensive smart electronic devices. To integrate the rectenna with a minimum cost, a roll-to-roll (R2R) gravure printing process has been considered to print the rectenna on plastic foils. In this paper, R2R gravure printing systems including printing condition and four different nanoparticle based inks will be reported to print the rectenna (antenna, diode and capacitor) on plastic foils at a printing speed of 8 m min-1 and more than 90% device yield for a wireless power transmission of 0.3 W using a standard 13.56 MHz power transmitter.

Sneutrinos as mixed inflaton and curvaton

NASA Astrophysics Data System (ADS)

Haba, Naoyuki; Takahashi, Tomo; Yamada, Toshifumi

2018-06-01

We investigate a scenario where the supersymmetric partners of two right-handed neutrinos (sneutrinos) work as mixed inflaton and curvaton, motivated by the fact that the curvaton contribution to scalar perturbations can reduce the tensor-to-scalar ratio r so that chaotic inflation models with a quadratic potential are made consistent with the experimental bound on r. After confirming that the scenario evades the current bounds on r and the scalar perturbation spectral index ns, we make a prediction on the local non-Gaussianity in bispectrum, fNL, and one in trispectrum, τNL. Remarkably, since the sneutrino decay widths are determined by the neutrino Dirac Yukawa coupling, which can be estimated from the measured active neutrino mass differences in the seesaw model, our scenario has a strong predictive power about local non-Gaussianities, as they heavily depend on the inflaton and curvaton decay rates. Using this fact, we can constrain the sneutrino mass from the experimental bounds on ns, r and fNL.

Ensemble predictive model for more accurate soil organic carbon spectroscopic estimation

NASA Astrophysics Data System (ADS)

Vašát, Radim; Kodešová, Radka; Borůvka, Luboš

2017-07-01

A myriad of signal pre-processing strategies and multivariate calibration techniques has been explored in attempt to improve the spectroscopic prediction of soil organic carbon (SOC) over the last few decades. Therefore, to come up with a novel, more powerful, and accurate predictive approach to beat the rank becomes a challenging task. However, there may be a way, so that combine several individual predictions into a single final one (according to ensemble learning theory). As this approach performs best when combining in nature different predictive algorithms that are calibrated with structurally different predictor variables, we tested predictors of two different kinds: 1) reflectance values (or transforms) at each wavelength and 2) absorption feature parameters. Consequently we applied four different calibration techniques, two per each type of predictors: a) partial least squares regression and support vector machines for type 1, and b) multiple linear regression and random forest for type 2. The weights to be assigned to individual predictions within the ensemble model (constructed as a weighted average) were determined by an automated procedure that ensured the best solution among all possible was selected. The approach was tested at soil samples taken from surface horizon of four sites differing in the prevailing soil units. By employing the ensemble predictive model the prediction accuracy of SOC improved at all four sites. The coefficient of determination in cross-validation (R2cv) increased from 0.849, 0.611, 0.811 and 0.644 (the best individual predictions) to 0.864, 0.650, 0.824 and 0.698 for Site 1, 2, 3 and 4, respectively. Generally, the ensemble model affected the final prediction so that the maximal deviations of predicted vs. observed values of the individual predictions were reduced, and thus the correlation cloud became thinner as desired.

Aerobic power and field test results of amateur 15-a-side rugby union players.

PubMed

Sant'anna, Ricardo T; de Souza Castro, Flávio A

2017-12-01

The aim of the present study was to verify whether it is possible to predict aerobic power in amateur 15-a-side rugby union players through the Yo-Yo Intermittent Recovery Test Level 1 (Yo-Yo IRT1) and the 5-meter Multiple Shuttle Test (5-m MST). Forty-two amateur players - 22 forwards and 20 backs - were evaluated in three phases: 1) maximum treadmill test in the laboratory; 2) field test set by a drawing in the first phase; and 3) second field test. Descriptive, comparison, correlation, regression and level of agreement analyses were performed. Backs, when compared to forwards, showed a higher VO2max (61.7±15 mL/kg/min and 51.6±10.1 mL/kg/min, respectively), Yo-Yo IRT1 final level (16.4±0.8 and 14.9±0.9, respectively) and Yo-Yo IRT1 total distance (1283.3±312.5 m and 792±277.6 m, respectively), and a higher final distance in the 5-m MST (686.8±36.6 and 642.9±46.5, respectively). Significant correlations were found between the result and the total distance on the Yo-Yo IRT1 and the VO2max (r=0.425 and r=0.459, respectively). Using the total distance covered in the Yo-Yo IRT1, the VO2max of amateur 15-a-side rugby union players can be estimated through the equation VO2max = 0.016 × (DIST Yo‑Yo) + 40.578. Yo-Yo IRT1 is most useful when the objective is to evaluate the aerobic power of amateur RU players in comparison with the 5-m MST.

Feasibility of body roundness index for identifying a clustering of cardiometabolic abnormalities compared to BMI, waist circumference and other anthropometric indices: the China Health and Nutrition Survey, 2008 to 2009

PubMed Central

Tian, Simiao; Zhang, Xiuzhi; Xu, Yang; Dong, Huimin

2016-01-01

Abstract The body mass index (BMI) and waist circumference (WC) are commonly used anthropometric measures for predicting cardiovascular diseases risk factors, but it is uncertain which specific measure might be the most appropriate predictor of a cluster of cardiometabolic abnormalities (CMA) in Chinese adults. A body shape index (ABSI) and body roundness index (BRI) have been recently developed as alternative anthropometric indices that may better reflect health status. The main aims of this study were to investigate the predictive capacity of ABSI and BRI in identifying various CMA compared to BMI, WC, waist-to-hip ratio (WHpR), and waist-to-height ratio (WHtR), and to determine whether there exists a best single predictor of all CMA. We used data from the 2009 wave of the China Health and Nutrition Survey, and the final analysis included 8126 adults aged 18 to 85 years with available fasting blood samples and anthropometric measurements. Receiver-operating characteristic (ROC) analyses were conducted to assess the best anthropometric indices to predict the risk of hypertension, diabetes, dyslipidemia, hyperuricemia, and metabolic syndrome (MetS). Logistic regression models were fit to evaluate the OR of each CMA according to anthropometric indices. In women, the ROC analysis showed that BRI and WHtR had the best predictive capability in identifying all of CMA (area under the curves [AUCs] ranged from 0.658 to 0.721). In men, BRI and WHtR were better predictor of hypertension, diabetes, and at least 1 CMA (AUC: 0.668, 0.708, and 0.698, respectively), whereas BMI and WC were more sensitive predictor of dyslipidemia, hyperuricemia, and MetS. Furthermore, the ABSI showed the lowest AUCs for each CMA. According to the multivariate logistic regression analysis, BRI and WHtR were superior in discriminating hyperuricemia and at least 1 CMA while BMI performed better in predicting hypertension, diabetes, and MetS in women. In men, WC and BRI were the 2 best predictor of all CMA except MetS, and the ABSI was the worst. Our results showed the novel index BRI could be used as a single suitable anthropometric measure in simultaneously identifying a cluster of CMA compared to BMI and WHtR, especially in Chinese women, whereas the ABSI showed the weakest discriminative power. PMID:27559964

Feasibility of body roundness index for identifying a clustering of cardiometabolic abnormalities compared to BMI, waist circumference and other anthropometric indices: the China Health and Nutrition Survey, 2008 to 2009.

PubMed

Tian, Simiao; Zhang, Xiuzhi; Xu, Yang; Dong, Huimin

2016-08-01

The body mass index (BMI) and waist circumference (WC) are commonly used anthropometric measures for predicting cardiovascular diseases risk factors, but it is uncertain which specific measure might be the most appropriate predictor of a cluster of cardiometabolic abnormalities (CMA) in Chinese adults. A body shape index (ABSI) and body roundness index (BRI) have been recently developed as alternative anthropometric indices that may better reflect health status. The main aims of this study were to investigate the predictive capacity of ABSI and BRI in identifying various CMA compared to BMI, WC, waist-to-hip ratio (WHpR), and waist-to-height ratio (WHtR), and to determine whether there exists a best single predictor of all CMA.We used data from the 2009 wave of the China Health and Nutrition Survey, and the final analysis included 8126 adults aged 18 to 85 years with available fasting blood samples and anthropometric measurements. Receiver-operating characteristic (ROC) analyses were conducted to assess the best anthropometric indices to predict the risk of hypertension, diabetes, dyslipidemia, hyperuricemia, and metabolic syndrome (MetS). Logistic regression models were fit to evaluate the OR of each CMA according to anthropometric indices.In women, the ROC analysis showed that BRI and WHtR had the best predictive capability in identifying all of CMA (area under the curves [AUCs] ranged from 0.658 to 0.721). In men, BRI and WHtR were better predictor of hypertension, diabetes, and at least 1 CMA (AUC: 0.668, 0.708, and 0.698, respectively), whereas BMI and WC were more sensitive predictor of dyslipidemia, hyperuricemia, and MetS. Furthermore, the ABSI showed the lowest AUCs for each CMA. According to the multivariate logistic regression analysis, BRI and WHtR were superior in discriminating hyperuricemia and at least 1 CMA while BMI performed better in predicting hypertension, diabetes, and MetS in women. In men, WC and BRI were the 2 best predictor of all CMA except MetS, and the ABSI was the worst.Our results showed the novel index BRI could be used as a single suitable anthropometric measure in simultaneously identifying a cluster of CMA compared to BMI and WHtR, especially in Chinese women, whereas the ABSI showed the weakest discriminative power.

External Validation and Evaluation of Reliability and Validity of the Modified Seoul National University Renal Stone Complexity Scoring System to Predict Stone-Free Status After Retrograde Intrarenal Surgery.

PubMed

Park, Juhyun; Kang, Minyong; Jeong, Chang Wook; Oh, Sohee; Lee, Jeong Woo; Lee, Seung Bae; Son, Hwancheol; Jeong, Hyeon; Cho, Sung Yong

2015-08-01

The modified Seoul National University Renal Stone Complexity scoring system (S-ReSC-R) for retrograde intrarenal surgery (RIRS) was developed as a tool to predict stone-free rate (SFR) after RIRS. We externally validated the S-ReSC-R. We retrospectively reviewed 159 patients who underwent RIRS. The S-ReSC-R was assigned from 1 to 12 according to the location and number of sites involved. The stone-free status was defined as no evidence of a stone or with clinically insignificant residual fragment stones less than 2 mm. Interobserver and test-retest reliabilities were evaluated. Statistical performance of the prediction model was assessed by its predictive accuracy, predictive probability, and clinical usefulness. Overall SFR was 73.0%. The SFRs were 86.7%, 70.2%, and 48.6% in low-score (1-2), intermediate-score (3-4), and high-score (5-12) groups, respectively (p<0.001). External validation of S-ReSC-R revealed an area under the curve (AUC) of 0.731 (95% CI 0.650-0.813). The AUC of the three-titered S-ReSC-R was 0.701 (95% CI 0.609-0.794). The calibration plot showed that the predicted probability of SFR had a concordance comparable to that of observed frequency. The Hosmer-Lemeshow goodness of fit test revealed a p-value of 0.01 for the S-ReSC-R and 0.90 for the three-titered S-ReSC-R. Interobserver and test-retest reliabilities revealed an almost perfect level of agreement. The present study proved the predictive value of S-ReSC-R to predict SFR following RIRS in an independent cohort. Interobserver and test-retest reliabilities confirmed that S-ReSC-R was reliable and valid.

Evaluation of SAMe-TT2R2 Score on Predicting Success With Extended-Interval Warfarin Monitoring.

PubMed

Hwang, Andrew Y; Carris, Nicholas W; Dietrich, Eric A; Gums, John G; Smith, Steven M

2018-06-01

In patients with stable international normalized ratios, 12-week extended-interval warfarin monitoring can be considered; however, predictors of success with this strategy are unknown. The previously validated SAMe-TT 2 R 2 score (considering sex, age, medical history, treatment, tobacco, and race) predicts anticoagulation control during standard follow-up (every 4 weeks), with lower scores associated with greater time in therapeutic range. To evaluate the ability of the SAMe-TT 2 R 2 score in predicting success with extended-interval warfarin follow-up in patients with previously stable warfarin doses. In this post hoc analysis of a single-arm feasibility study, baseline SAMe-TT 2 R 2 scores were calculated for patients with ≥1 extended-interval follow-up visit. The primary analysis assessed achieved weeks of extended-interval follow-up according to baseline SAMe-TT 2 R 2 scores. A total of 47 patients receiving chronic anticoagulation completed a median of 36 weeks of extended-interval follow-up. The median baseline SAMe-TT 2 R 2 score was 1 (range 0-5). Lower SAMe-TT 2 R 2 scores appeared to be associated with greater duration of extended-interval follow-up achieved, though the differences between scores were not statistically significant. No individual variable of the SAMe-TT 2 R 2 score was associated with achieved weeks of extended-interval follow-up. Analysis of additional patient factors found that longer duration (≥24 weeks) of prior stable treatment was significantly associated with greater weeks of extended-interval follow-up completed ( P = 0.04). Conclusion and Relevance: This pilot study provides limited evidence that the SAMe-TT 2 R 2 score predicts success with extended-interval warfarin follow-up but requires confirmation in a larger study. Further research is also necessary to establish additional predictors of successful extended-interval warfarin follow-up.

Core or Cusps: The Central Dark Matter Profile of a Strong Lensing Cluster with a Bright Central Image at Redshift 1

NASA Astrophysics Data System (ADS)

Collett, Thomas E.; Buckley-Geer, Elizabeth; Lin, Huan; Bacon, David; Nichol, Robert C.; Nord, Brian; Morice-Atkinson, Xan; Amara, Adam; Birrer, Simon; Kuropatkin, Nikolay; More, Anupreeta; Papovich, Casey; Romer, Kathy K.; Tessore, Nicolas; Abbott, Tim M. C.; Allam, Sahar; Annis, James; Benoit-Lévy, Aurlien; Brooks, David; Burke, David L.; Carrasco Kind, Matias; Castander, Francisco Javier J.; D'Andrea, Chris B.; da Costa, Luiz N.; Desai, Shantanu; Diehl, H. Thomas; Doel, Peter; Eifler, Tim F.; Flaugher, Brenna; Frieman, Josh; Gerdes, David W.; Goldstein, Daniel A.; Gruen, Daniel; Gschwend, Julia; Gutierrez, Gaston; James, David J.; Kuehn, Kyler; Kuhlmann, Steve; Lahav, Ofer; Li, Ting S.; Lima, Marcos; Maia, Marcio A. G.; March, Marisa; Marshall, Jennifer L.; Martini, Paul; Melchior, Peter; Miquel, Ramon; Plazas, Andrs A.; Rykoff, Eli S.; Sanchez, Eusebio; Scarpine, Vic; Schindler, Rafe; Schubnell, Michael; Sevilla-Noarbe, Ignacio; Smith, Mathew; Sobreira, Flavia; Suchyta, Eric; Swanson, Molly E. C.; Tarle, Gregory; Tucker, Douglas L.; Walker, Alistair R.

2017-07-01

We report on SPT-CLJ2011-5228, a giant system of arcs created by a cluster at z = 1.06. The arc system is notable for the presence of a bright central image. The source is a Lyman break galaxy at z s = 2.39 and the mass enclosed within the Einstein ring of radius 14 arcsec is ˜ {10}14.2 {M}⊙ . We perform a full reconstruction of the light profile of the lensed images to precisely infer the parameters of the mass distribution. The brightness of the central image demands that the central total density profile of the lens be shallow. By fitting the dark matter as a generalized Navarro-Frenk-White profile—with a free parameter for the inner density slope—we find that the break radius is {270}-76+48 kpc, and that the inner density falls with radius to the power -0.38 ± 0.04 at 68% confidence. Such a shallow profile is in strong tension with our understanding of relaxed cold dark matter halos; dark matter-only simulations predict that the inner density should fall as {r}-1. The tension can be alleviated if this cluster is in fact a merger; a two-halo model can also reconstruct the data, with both clumps (density varying as {r}-0.8 and {r}-1.0) much more consistent with predictions from dark matter-only simulations. At the resolution of our Dark Energy Survey imaging, we are unable to choose between these two models, but we make predictions for forthcoming Hubble Space Telescope imaging that will decisively distinguish between them.

Core or Cusps: The Central Dark Matter Profile of a Strong Lensing Cluster with a Bright Central Image at Redshift 1

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

Collett, Thomas E.; Buckley-Geer, Elizabeth; Lin, Huan

We report on SPT-CLJ2011-5228, a giant system of arcs created by a cluster atmore » $z=1.06$. The arc system is notable for the presence of a bright central image. The source is a Lyman Break galaxy at $$z_s=2.39$$ and the mass enclosed within the 14 arc second radius Einstein ring is $$10^{14.2}$$ solar masses. We perform a full light profile reconstruction of the lensed images to precisely infer the parameters of the mass distribution. The brightness of the central image demands that the central total density profile of the lens be shallow. By fitting the dark matter as a generalized Navarro-Frenk-White profile---with a free parameter for the inner density slope---we find that the break radius is $$270^{+48}_{-76}$$ kpc, and that the inner density falls with radius to the power $$-0.38\\pm0.04$$ at 68 percent confidence. Such a shallow profile is in strong tension with our understanding of relaxed cold dark matter halos; dark matter only simulations predict the inner density should fall as $$r^{-1}$$. The tension can be alleviated if this cluster is in fact a merger; a two halo model can also reconstruct the data, with both clumps (density going as $$r^{-0.8}$$ and $$r^{-1.0}$$) much more consistent with predictions from dark matter only simulations. At the resolution of our Dark Energy Survey imaging, we are unable to choose between these two models, but we make predictions for forthcoming Hubble Space Telescope imaging that will decisively distinguish between them.« less

Examination of DNA methylation status of the ELOVL2 marker may be useful for human age prediction in forensic science.

PubMed

Zbieć-Piekarska, Renata; Spólnicka, Magdalena; Kupiec, Tomasz; Makowska, Żanetta; Spas, Anna; Parys-Proszek, Agnieszka; Kucharczyk, Krzysztof; Płoski, Rafał; Branicki, Wojciech

2015-01-01

Age estimation in forensic investigations may complement the prediction of externally visible characteristics and the inference of biogeographical ancestry, thus allowing a better description of an unknown individual. Multiple CpG sites that show linear correlation between age and degree of DNA methylation have been identified in the human genome, providing a selection of candidates for age prediction. In this study, we optimized an assay based on bisulfite conversion and pyrosequencing of 7 CpG sites located in the ELOVL2 gene. Examination of 303 blood samples collected from individuals aged 2-75 years allowed selection of the most informative site, explaining 83% of variation in age. The final linear regression model included two CpG sites in ELOVL2 and enabled age prediction with R(2)=0.859, prediction error=6.85 and mean absolute deviation MAD=5.03. Examination of a testing set of 124 blood samples (MAD=5.75) showed that 68.5% of samples were correctly predicted, assuming that chronological and predicted ages matched ± 7 years. It was found that the ELOVL2 methylation status in bloodstains had not changed significantly after 4 weeks of storage in room temperature conditions. Analysis of 45 bloodstains deposited on tissue paper after 5, 10 and 15 years of storage in room conditions indicated that although a gradual decrease of positive PCR results was observed, the general age prediction success rate remained similar and equaled 60-78%. The obtained results show that the ELOVL2 locus provides a very good source of information about human chronological age based on analysis of blood, including bloodstains, and it may constitute a powerful and reliable predictor in future forensic age estimation models. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Predicted impact of thermal power generation emission control measures in the Beijing-Tianjin-Hebei region on air pollution over Beijing, China.

PubMed

Wang, Liqiang; Li, Pengfei; Yu, Shaocai; Mehmood, Khalid; Li, Zhen; Chang, Shucheng; Liu, Weiping; Rosenfeld, Daniel; Flagan, Richard C; Seinfeld, John H

2018-01-17

Widespread economic growth in China has led to increasing episodes of severe air pollution, especially in major urban areas. Thermal power plants represent a particularly important class of emissions. Here we present an evaluation of the predicted effectiveness of a series of recently proposed thermal power plant emission controls in the Beijing-Tianjin-Hebei (BTH) region on air quality over Beijing using the Community Multiscale Air Quality(CMAQ) atmospheric chemical transport model to predict CO, SO 2 , NO 2 , PM 2.5 , and PM 10 levels. A baseline simulation of the hypothetical removal of all thermal power plants in the BTH region is predicted to lead to 38%, 23%, 23%, 24%, and 24% reductions in current annual mean levels of CO, SO 2 , NO 2 , PM 2.5 , and PM 10 in Beijing, respectively. Similar percentage reductions are predicted in the major cities in the BTH region. Simulations of the air quality impact of six proposed thermal power plant emission reduction strategies over the BTH region provide an estimate of the potential improvement in air quality in the Beijing metropolitan area, as a function of the time of year.

Prediction of Wind Energy Resources (PoWER) Users Guide

DTIC Science & Technology

2016-01-01

ARL-TR-7573● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER) User’s Guide by David P Sauter...not return it to the originator. ARL-TR-7573 ● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER...2016 2. REPORT TYPE Final 3. DATES COVERED (From - To) 09/2015–11/2015 4. TITLE AND SUBTITLE Prediction of Wind Energy Resources (PoWER) User’s

A novel logic-based approach for quantitative toxicology prediction.

PubMed

Amini, Ata; Muggleton, Stephen H; Lodhi, Huma; Sternberg, Michael J E

2007-01-01

There is a pressing need for accurate in silico methods to predict the toxicity of molecules that are being introduced into the environment or are being developed into new pharmaceuticals. Predictive toxicology is in the realm of structure activity relationships (SAR), and many approaches have been used to derive such SAR. Previous work has shown that inductive logic programming (ILP) is a powerful approach that circumvents several major difficulties, such as molecular superposition, faced by some other SAR methods. The ILP approach reasons with chemical substructures within a relational framework and yields chemically understandable rules. Here, we report a general new approach, support vector inductive logic programming (SVILP), which extends the essentially qualitative ILP-based SAR to quantitative modeling. First, ILP is used to learn rules, the predictions of which are then used within a novel kernel to derive a support-vector generalization model. For a highly heterogeneous dataset of 576 molecules with known fathead minnow fish toxicity, the cross-validated correlation coefficients (R2CV) from a chemical descriptor method (CHEM) and SVILP are 0.52 and 0.66, respectively. The ILP, CHEM, and SVILP approaches correctly predict 55, 58, and 73%, respectively, of toxic molecules. In a set of 165 unseen molecules, the R2 values from the commercial software TOPKAT and SVILP are 0.26 and 0.57, respectively. In all calculations, SVILP showed significant improvements in comparison with the other methods. The SVILP approach has a major advantage in that it uses ILP automatically and consistently to derive rules, mostly novel, describing fragments that are toxicity alerts. The SVILP is a general machine-learning approach and has the potential of tackling many problems relevant to chemoinformatics including in silico drug design.

A Bayesian antedependence model for whole genome prediction.

PubMed

Yang, Wenzhao; Tempelman, Robert J

2012-04-01

Hierarchical mixed effects models have been demonstrated to be powerful for predicting genomic merit of livestock and plants, on the basis of high-density single-nucleotide polymorphism (SNP) marker panels, and their use is being increasingly advocated for genomic predictions in human health. Two particularly popular approaches, labeled BayesA and BayesB, are based on specifying all SNP-associated effects to be independent of each other. BayesB extends BayesA by allowing a large proportion of SNP markers to be associated with null effects. We further extend these two models to specify SNP effects as being spatially correlated due to the chromosomally proximal effects of causal variants. These two models, that we respectively dub as ante-BayesA and ante-BayesB, are based on a first-order nonstationary antedependence specification between SNP effects. In a simulation study involving 20 replicate data sets, each analyzed at six different SNP marker densities with average LD levels ranging from r(2) = 0.15 to 0.31, the antedependence methods had significantly (P < 0.01) higher accuracies than their corresponding classical counterparts at higher LD levels (r(2) > 0. 24) with differences exceeding 3%. A cross-validation study was also conducted on the heterogeneous stock mice data resource (http://mus.well.ox.ac.uk/mouse/HS/) using 6-week body weights as the phenotype. The antedependence methods increased cross-validation prediction accuracies by up to 3.6% compared to their classical counterparts (P < 0.001). Finally, we applied our method to other benchmark data sets and demonstrated that the antedependence methods were more accurate than their classical counterparts for genomic predictions, even for individuals several generations beyond the training data.

Origin and Consequences of the Relationship between Protein Mean and Variance

PubMed Central

Vallania, Francesco Luigi Massimo; Sherman, Marc; Goodwin, Zane; Mogno, Ilaria; Cohen, Barak Alon; Mitra, Robi David

2014-01-01

Cell-to-cell variance in protein levels (noise) is a ubiquitous phenomenon that can increase fitness by generating phenotypic differences within clonal populations of cells. An important challenge is to identify the specific molecular events that control noise. This task is complicated by the strong dependence of a protein's cell-to-cell variance on its mean expression level through a power-law like relationship (σ2∝μ1.69). Here, we dissect the nature of this relationship using a stochastic model parameterized with experimentally measured values. This framework naturally recapitulates the power-law like relationship (σ2∝μ1.6) and accurately predicts protein variance across the yeast proteome (r2 = 0.935). Using this model we identified two distinct mechanisms by which protein variance can be increased. Variables that affect promoter activation, such as nucleosome positioning, increase protein variance by changing the exponent of the power-law relationship. In contrast, variables that affect processes downstream of promoter activation, such as mRNA and protein synthesis, increase protein variance in a mean-dependent manner following the power-law. We verified our findings experimentally using an inducible gene expression system in yeast. We conclude that the power-law-like relationship between noise and protein mean is due to the kinetics of promoter activation. Our results provide a framework for understanding how molecular processes shape stochastic variation across the genome. PMID:25062021

Predicting herbivore faecal nitrogen using a multispecies near-infrared reflectance spectroscopy calibration.

PubMed

Villamuelas, Miriam; Serrano, Emmanuel; Espunyes, Johan; Fernández, Néstor; López-Olvera, Jorge R; Garel, Mathieu; Santos, João; Parra-Aguado, María Ángeles; Ramanzin, Maurizio; Fernández-Aguilar, Xavier; Colom-Cadena, Andreu; Marco, Ignasi; Lavín, Santiago; Bartolomé, Jordi; Albanell, Elena

2017-01-01

Optimal management of free-ranging herbivores requires the accurate assessment of an animal's nutritional status. For this purpose 'near-infrared reflectance spectroscopy' (NIRS) is very useful, especially when nutritional assessment is done through faecal indicators such as faecal nitrogen (FN). In order to perform an NIRS calibration, the default protocol recommends starting by generating an initial equation based on at least 50-75 samples from the given species. Although this protocol optimises prediction accuracy, it limits the use of NIRS with rare or endangered species where sample sizes are often small. To overcome this limitation we tested a single NIRS equation (i.e., multispecies calibration) to predict FN in herbivores. Firstly, we used five herbivore species with highly contrasting digestive physiologies to build monospecies and multispecies calibrations, namely horse, sheep, Pyrenean chamois, red deer and European rabbit. Secondly, the equation accuracy was evaluated by two procedures using: (1) an external validation with samples from the same species, which were not used in the calibration process; and (2) samples from different ungulate species, specifically Alpine ibex, domestic goat, European mouflon, roe deer and cattle. The multispecies equation was highly accurate in terms of the coefficient of determination for calibration R2 = 0.98, standard error of validation SECV = 0.10, standard error of external validation SEP = 0.12, ratio of performance to deviation RPD = 5.3, and range error of prediction RER = 28.4. The accuracy of the multispecies equation to predict other herbivore species was also satisfactory (R2 > 0.86, SEP < 0.27, RPD > 2.6, and RER > 8.1). Lastly, the agreement between multi- and monospecies calibrations was also confirmed by the Bland-Altman method. In conclusion, our single multispecies equation can be used as a reliable, cost-effective, easy and powerful analytical method to assess FN in a wide range of herbivore species.

A Spatio-temporal Model of African Animal Trypanosomosis Risk

PubMed Central

Dicko, Ahmadou H.; Percoma, Lassane; Sow, Adama; Adam, Yahaya; Mahama, Charles; Sidibé, Issa; Dayo, Guiguigbaza-Kossigan; Thévenon, Sophie; Fonta, William; Sanfo, Safietou; Djiteye, Aligui; Salou, Ernest; Djohan, Vincent; Cecchi, Giuliano; Bouyer, Jérémy

2015-01-01

Background African animal trypanosomosis (AAT) is a major constraint to sustainable development of cattle farming in sub-Saharan Africa. The habitat of the tsetse fly vector is increasingly fragmented owing to demographic pressure and shifts in climate, which leads to heterogeneous risk of cyclical transmission both in space and time. In Burkina Faso and Ghana, the most important vectors are riverine species, namely Glossina palpalis gambiensis and G. tachinoides, which are more resilient to human-induced changes than the savannah and forest species. Although many authors studied the distribution of AAT risk both in space and time, spatio-temporal models allowing predictions of it are lacking. Methodology/Principal Findings We used datasets generated by various projects, including two baseline surveys conducted in Burkina Faso and Ghana within PATTEC (Pan African Tsetse and Trypanosomosis Eradication Campaign) national initiatives. We computed the entomological inoculation rate (EIR) or tsetse challenge using a range of environmental data. The tsetse apparent density and their infection rate were separately estimated and subsequently combined to derive the EIR using a “one layer-one model” approach. The estimated EIR was then projected into suitable habitat. This risk index was finally validated against data on bovine trypanosomosis. It allowed a good prediction of the parasitological status (r2 = 67%), showed a positive correlation but less predictive power with serological status (r2 = 22%) aggregated at the village level but was not related to the illness status (r2 = 2%). Conclusions/Significance The presented spatio-temporal model provides a fine-scale picture of the dynamics of AAT risk in sub-humid areas of West Africa. The estimated EIR was high in the proximity of rivers during the dry season and more widespread during the rainy season. The present analysis is a first step in a broader framework for an efficient risk management of climate-sensitive vector-borne diseases. PMID:26154506

Comparison of different models for ground-level atmospheric turbulence strength (C(n)(2)) prediction with a new model according to local weather data for FSO applications.

PubMed

Arockia Bazil Raj, A; Arputha Vijaya Selvi, J; Durairaj, S

2015-02-01

Atmospheric parameters strongly affect the performance of free-space optical communication (FSOC) systems when the optical wave is propagating through the inhomogeneous turbulence transmission medium. Developing a model to get an accurate prediction of the atmospheric turbulence strength (C(n)(2)) according to meteorological parameters (weather data) becomes significant to understand the behavior of the FSOC channel during different seasons. The construction of a dedicated free-space optical link for the range of 0.5 km at an altitude of 15.25 m built at Thanjavur (Tamil Nadu) is described in this paper. The power level and beam centroid information of the received signal are measured continuously with weather data at the same time using an optoelectronic assembly and the developed weather station, respectively, and are recorded in a data-logging computer. Existing models that exhibit relatively fewer prediction errors are briefed and are selected for comparative analysis. Measured weather data (as input factors) and C(n)(2) (as a response factor) of size [177,147×4] are used for linear regression analysis and to design mathematical models more suitable in the test field. Along with the model formulation methodologies, we have presented the contributions of the input factors' individual and combined effects on the response surface and the coefficient of determination (R(2)) estimated using analysis of variance tools. An R(2) value of 98.93% is obtained using the new model, model equation V, from a confirmatory test conducted with a testing data set of size [2000×4]. In addition, the prediction accuracies of the selected and the new models are investigated during different seasons in a one-year period using the statistics of day, week-averaged, month-averaged, and seasonal-averaged diurnal Cn2 profiles, and are verified in terms of the sum of absolute error (SAE). A Cn2 prediction maximum average SAE of 2.3×10(-13)  m(-2/3) is achieved using the new model in a longer range of dynamic meteorological parameters during the different local seasons.

On the use of seminumerical simulations in predicting the 21-cm signal from the epoch of reionization

NASA Astrophysics Data System (ADS)

Majumdar, Suman; Mellema, Garrelt; Datta, Kanan K.; Jensen, Hannes; Choudhury, T. Roy; Bharadwaj, Somnath; Friedrich, Martina M.

2014-10-01

We present a detailed comparison of three different simulations of the epoch of reionization (EoR). The radiative transfer simulation (C2-RAY) among them is our benchmark. Radiative transfer codes can produce realistic results, but are computationally expensive. We compare it with two seminumerical techniques: one using the same haloes as C2-RAY as its sources (Sem-Num), and one using a conditional Press-Schechter scheme (CPS+GS). These are vastly more computationally efficient than C2-RAY, but use more simplistic physical assumptions. We evaluate these simulations in terms of their ability to reproduce the history and morphology of reionization. We find that both Sem-Num and CPS+GS can produce an ionization history and morphology that is very close to C2-RAY, with Sem-Num performing slightly better compared to CPS+GS. We also study different redshift-space observables of the 21-cm signal from EoR: the variance, power spectrum and its various angular multipole moments. We find that both seminumerical models perform reasonably well in predicting these observables at length scales relevant for present and future experiments. However, Sem-Num performs slightly better than CPS+GS in producing the reionization history, which is necessary for interpreting the future observations. The CPS+GS scheme, however, has the advantage that it is not restricted by the mass resolution of the dark matter density field.

Modelling by partial least squares the relationship between the HPLC mobile phases and analytes on phenyl column.

PubMed

Markopoulou, Catherine K; Kouskoura, Maria G; Koundourellis, John E

2011-06-01

Twenty-five descriptors and 61 structurally different analytes have been used on a partial least squares (PLS) to latent structure technique in order to study chromatographically their interaction mechanism on a phenyl column. According to the model, 240 different retention times of the analytes, expressed as Y variable (log k), at different % MeOH mobile-phase concentrations have been correlated with their theoretical most important structural or molecular descriptors. The goodness-of-fit was estimated by the coefficient of multiple determinations r(2) (0.919), and the root mean square error of estimation (RMSEE=0.1283) values with a predictive ability (Q(2)) of 0.901. The model was further validated using cross-validation (CV), validated by 20 response permutations r(2) (0.0, 0.0146), Q(2) (0.0, -0.136) and validated by external prediction. The contribution of certain mechanism interactions between the analytes, the mobile phase and the column, proportional or counterbalancing is also studied. Trying to evaluate the influence on Y of every variable in a PLS model, VIP (variables importance in the projection) plot provides evidence that lipophilicity (expressed as Log D, Log P), polarizability, refractivity and the eluting power of the mobile phase are dominant in the retention mechanism on a phenyl column. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Monitoring Tumor Response to Carbogen Breathing by Oxygen-Sensitive Magnetic Resonance Parameters to Predict the Outcome of Radiation Therapy: A Preclinical Study

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

Cao-Pham, Thanh-Trang; Tran, Ly-Binh-An; Colliez, Florence

Purpose: In an effort to develop noninvasive in vivo methods for mapping tumor oxygenation, magnetic resonance (MR)-derived parameters are being considered, including global R{sub 1}, water R{sub 1}, lipids R{sub 1}, and R{sub 2}*. R{sub 1} is sensitive to dissolved molecular oxygen, whereas R{sub 2}* is sensitive to blood oxygenation, detecting changes in dHb. This work compares global R{sub 1}, water R{sub 1}, lipids R{sub 1}, and R{sub 2}* with pO{sub 2} assessed by electron paramagnetic resonance (EPR) oximetry, as potential markers of the outcome of radiation therapy (RT). Methods and Materials: R{sub 1}, R{sub 2}*, and EPR were performed onmore » rhabdomyosarcoma and 9L-glioma tumor models, under air and carbogen breathing conditions (95% O{sub 2}, 5% CO{sub 2}). Because the models demonstrated different radiosensitivity properties toward carbogen, a growth delay (GD) assay was performed on the rhabdomyosarcoma model and a tumor control dose 50% (TCD50) was performed on the 9L-glioma model. Results: Magnetic resonance imaging oxygen-sensitive parameters detected the positive changes in oxygenation induced by carbogen within tumors. No consistent correlation was seen throughout the study between MR parameters and pO{sub 2}. Global and lipids R{sub 1} were found to be correlated to pO{sub 2} in the rhabdomyosarcoma model, whereas R{sub 2}* was found to be inversely correlated to pO{sub 2} in the 9L-glioma model (P=.05 and .03). Carbogen increased the TCD50 of 9L-glioma but did not increase the GD of rhabdomyosarcoma. Only R{sub 2}* was predictive (P<.05) for the curability of 9L-glioma at 40 Gy, a dose that showed a difference in response to RT between carbogen and air-breathing groups. {sup 18}F-FAZA positron emission tomography imaging has been shown to be a predictive marker under the same conditions. Conclusion: This work illustrates the sensitivity of oxygen-sensitive R{sub 1} and R{sub 2}* parameters to changes in tumor oxygenation. However, R{sub 1} parameters showed limitations in terms of predicting the outcome of RT in the tumor models studied, whereas R{sub 2}* was found to be correlated with the outcome in the responsive model.« less

GAPIT: genome association and prediction integrated tool.

PubMed

Lipka, Alexander E; Tian, Feng; Wang, Qishan; Peiffer, Jason; Li, Meng; Bradbury, Peter J; Gore, Michael A; Buckler, Edward S; Zhang, Zhiwu

2012-09-15

Software programs that conduct genome-wide association studies and genomic prediction and selection need to use methodologies that maximize statistical power, provide high prediction accuracy and run in a computationally efficient manner. We developed an R package called Genome Association and Prediction Integrated Tool (GAPIT) that implements advanced statistical methods including the compressed mixed linear model (CMLM) and CMLM-based genomic prediction and selection. The GAPIT package can handle large datasets in excess of 10 000 individuals and 1 million single-nucleotide polymorphisms with minimal computational time, while providing user-friendly access and concise tables and graphs to interpret results. http://www.maizegenetics.net/GAPIT. zhiwu.zhang@cornell.edu Supplementary data are available at Bioinformatics online.

Clinical Prediction Model for Time in Therapeutic Range While on Warfarin in Newly Diagnosed Atrial Fibrillation.

PubMed

Williams, Brent A; Evans, Michael A; Honushefsky, Ashley M; Berger, Peter B

2017-10-12

Though warfarin has historically been the primary oral anticoagulant for stroke prevention in newly diagnosed atrial fibrillation (AF), several new direct oral anticoagulants may be preferred when anticoagulation control with warfarin is expected to be poor. This study developed a prediction model for time in therapeutic range (TTR) among newly diagnosed AF patients on newly initiated warfarin as a tool to assist decision making between warfarin and direct oral anticoagulants. This electronic medical record-based, retrospective study included newly diagnosed, nonvalvular AF patients with no recent warfarin exposure receiving primary care services through a large healthcare system in rural Pennsylvania. TTR was estimated as the percentage of time international normalized ratio measurements were between 2.0 and 3.0 during the first year following warfarin initiation. Candidate predictors of TTR were chosen from data elements collected during usual clinical care. A TTR prediction model was developed and temporally validated and its predictive performance was compared with the SAMe-TT 2 R 2 score (sex, age, medical history, treatment, tobacco, race) using R 2 and c-statistics. A total of 7877 newly diagnosed AF patients met study inclusion criteria. Median (interquartile range) TTR within the first year of starting warfarin was 51% (32, 67). Of 85 candidate predictors evaluated, 15 were included in the final validated model with an R 2 of 15.4%. The proposed model showed better predictive performance than the SAMe-TT 2 R 2 score ( R 2 =3.0%). The proposed prediction model may assist decision making on the proper mode of oral anticoagulant among newly diagnosed AF patients. However, predicting TTR on warfarin remains challenging. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Anthropometric parameters of nutritional assessment as predictive factors of arteriovenous fistula malfunction in patients undergoing hemodialysis.

PubMed

Gagliardi, Gian Manlio; Mancuso, Domenico; Falbo, Enrica; Mollica, Francesco; Mollica, Agata; Barcellona, Elisabetta; Senatore, Massimo; Bonofiglio, Renzo

2012-01-01

To evaluate the role of body mass index (BMI), waist circumference (W-C) and waist/hip ratio (WHR) on arteriovenous fistula (AVF) dysfunction. We evaluated 84 HD patients with an average follow-up period of 31.3 ± 8.1 months, identifying 8 stenosis (STN) and 17 thrombosis (THR) cases. The association between paired variables was tested with Pearson's coefficient (r) and p-value, whereas the prognostic value on STN and THR was analysed using Cox's regression. The significant independent variables were indentified with an inverse step-wise approach defining the data as hazard ratio (HR). A double-event (Stenosis/Thrombosis) model, function of Body mass index and Waist/hip ratio was used. Arteriovenous fistula survival was assessed with the Kaplan-Meyer curve and the calculations were carried out with Graph-Pad. On univariate analysis, THR showed direct correlation with BMI (r=0.44, p<0.01), W-C (r=0.39, p<0.05) WHR (r=0.37, p<0.01), Hemoglobin (p<0.001), C-Reactive protein (p=0.01), Calcium/Phosforus product (p=0.03), Parathyroid hormone (p=0.03) and inverse with albumin (p<0.001) and systolic blood pressure (p=0.003). On multivariate analysis, BMI variations were not predictive of STN and THR, whereas each unitary WHR and W-C increase was predictive of an increase of risk of events (3.8% and 2.1% respectively). The prognostic power of W-C per STN (HR 1: 1.19; p<0.05) and THR (HR: 1.28; p<0.01) remained significant even after being adjusted to account for traditional risk factors. Abdominal obesity increases the risk of AVF dysfunction. The W-C and WHR parameters, not BMI, emerge as independent STN and THR predictors.

Prediction of retention times in comprehensive two-dimensional gas chromatography using thermodynamic models.

PubMed

McGinitie, Teague M; Harynuk, James J

2012-09-14

A method was developed to accurately predict both the primary and secondary retention times for a series of alkanes, ketones and alcohols in a flow-modulated GC×GC system. This was accomplished through the use of a three-parameter thermodynamic model where ΔH, ΔS, and ΔC(p) for an analyte's interaction with the stationary phases in both dimensions are known. Coupling this thermodynamic model with a time summation calculation it was possible to accurately predict both (1)t(r) and (2)t(r) for all analytes. The model was able to predict retention times regardless of the temperature ramp used, with an average error of only 0.64% for (1)t(r) and an average error of only 2.22% for (2)t(r). The model shows promise for the accurate prediction of retention times in GC×GC for a wide range of compounds and is able to utilize data collected from 1D experiments. Copyright © 2012 Elsevier B.V. All rights reserved.

Estimation of inflation parameters for Perturbed Power Law model using recent CMB measurements

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

Mukherjee, Suvodip; Das, Santanu; Souradeep, Tarun

2015-01-01

Cosmic Microwave Background (CMB) is an important probe for understanding the inflationary era of the Universe. We consider the Perturbed Power Law (PPL) model of inflation which is a soft deviation from Power Law (PL) inflationary model. This model captures the effect of higher order derivative of Hubble parameter during inflation, which in turn leads to a non-zero effective mass m{sub eff} for the inflaton field. The higher order derivatives of Hubble parameter at leading order sources constant difference in the spectral index for scalar and tensor perturbation going beyond PL model of inflation. PPL model have two observable independentmore » parameters, namely spectral index for tensor perturbation ν{sub t} and change in spectral index for scalar perturbation ν{sub st} to explain the observed features in the scalar and tensor power spectrum of perturbation. From the recent measurements of CMB power spectra by WMAP, Planck and BICEP-2 for temperature and polarization, we estimate the feasibility of PPL model with standard ΛCDM model. Although BICEP-2 claimed a detection of r=0.2, estimates of dust contamination provided by Planck have left open the possibility that only upper bound on r will be expected in a joint analysis. As a result we consider different upper bounds on the value of r and show that PPL model can explain a lower value of tensor to scalar ratio (r<0.1 or r<0.01) for a scalar spectral index of n{sub s}=0.96 by having a non-zero value of effective mass of the inflaton field m{sup 2}{sub eff}/H{sup 2}. The analysis with WP + Planck likelihood shows a non-zero detection of m{sup 2}{sub eff}/H{sup 2} with 5.7 σ and 8.1 σ respectively for r<0.1 and r<0.01. Whereas, with BICEP-2 likelihood m{sup 2}{sub eff}/H{sup 2} = −0.0237 ± 0.0135 which is consistent with zero.« less

Randomised controlled trial and economic analysis of an internet-based weight management programme: POWeR+ (Positive Online Weight Reduction).

PubMed

Little, Paul; Stuart, Beth; Hobbs, Fd Richard; Kelly, Jo; Smith, Emily R; Bradbury, Katherine J; Hughes, Stephanie; Smith, Peter Wf; Moore, Michael V; Lean, Mike Ej; Margetts, Barrie M; Byrne, Christopher D; Griffin, Simon; Davoudianfar, Mina; Hooper, Julie; Yao, Guiqing; Zhu, Shihua; Raftery, James; Yardley, Lucy

2017-01-01

Behavioural counselling with intensive follow-up for obesity is effective, but in resource-constrained primary care settings briefer approaches are needed. To estimate the clinical effectiveness and cost-effectiveness of an internet-based behavioural intervention with regular face-to-face or remote support in primary care, compared with brief advice. Individually randomised three-arm parallel trial with health economic evaluation and nested qualitative interviews. Primary care general practices in the UK. Patients with a body mass index of ≥ 30 kg/m 2 (or ≥ 28 kg/m 2 with risk factors) identified from general practice records, recruited by postal invitation. Positive Online Weight Reduction (POWeR+) is a 24-session, web-based weight management intervention completed over 6 months. Following online registration, the website randomly allocated participants using computer-generated random numbers to (1) the control intervention ( n  = 279), which had previously been demonstrated to be clinically effective (brief web-based information that minimised pressure to cut down foods, instead encouraging swaps to healthier choices and increasing fruit and vegetables, plus 6-monthly nurse weighing); (2) POWeR+F ( n  = 269), POWeR+ supplemented by face-to-face nurse support (up to seven contacts); or (3) POWeR+R ( n  = 270), POWeR+ supplemented by remote nurse support (up to five e-mails or brief telephone calls). The primary outcome was a modelled estimate of average weight reduction over 12 months, assessed blind to group where possible, using multiple imputation for missing data. The secondary outcome was the number of participants maintaining a 5% weight reduction at 12 months. A total of 818 eligible individuals were randomised using computer-generated random numbers. Weight change, averaged over 12 months, was documented in 666 out of 818 participants (81%; control, n  = 227; POWeR+F, n  = 221; POWeR+R, n  = 218). The control group maintained nearly 3 kg of weight loss per person (mean weight per person: baseline, 104.4 kg; 6 months, 101.9 kg; 12 months, 101.7 kg). Compared with the control group, the estimated additional weight reduction with POWeR+F was 1.5 kg [95% confidence interval (CI) 0.6 to 2.4 kg; p  = 0.001] and with POWeR+R was 1.3 kg (95% CI 0.34 to 2.2 kg; p  = 0.007). By 12 months the mean weight loss was not statistically significantly different between groups, but 20.8% of control participants, 29.2% of POWeR+F participants (risk ratio 1.56, 95% CI 0.96 to 2.51; p  = 0.070) and 32.4% of POWeR+R participants (risk ratio 1.82, 95% CI 1.31 to 2.74; p  = 0.004) maintained a clinically significant 5% weight reduction. The POWeR+R group had fewer individuals who reported doing another activity to help lose weight [control, 47.1% (64/136); POWeR+F, 37.2% (51/137); POWeR+R, 26.7% (40/150)]. The incremental cost to the health service per kilogram weight lost, compared with the control group, was £18 (95% CI -£129 to £195) for POWeR+F and -£25 (95% CI -£268 to £157) for POWeR+R. The probability of being cost-effective at a threshold of £100 per kilogram was 88% and 98% for POWeR+F and POWeR+R, respectively. POWeR+R was dominant compared with the control group. No harms were reported and participants using POWeR+ felt more enabled in managing their weight. The qualitative studies documented that POWeR+ was viewed positively by patients and that health-care professionals generally enjoyed supporting patients using POWeR+. Maintenance of weight loss after 1 year is unknown. Identifying strategies for longer-term engagement, impact in community settings and increasing physical activity. Clinically valuable weight loss (> 5%) is maintained in 20% of individuals using novel written materials with brief follow-up. A web-based behavioural programme and brief support results in greater mean weight loss and 10% more participants maintain valuable weight loss; it achieves greater enablement and fewer participants undertaking other weight-loss activities; and it is likely to be cost-effective. Current Controlled Trials ISRCTN21244703. This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment ; Vol. 21, No. 4. See the NIHR Journals Library website for further project information.

3D-QSAR and docking studies of 3-Pyridine heterocyclic derivatives as potent PI3K/mTOR inhibitors

NASA Astrophysics Data System (ADS)

Yang, Wenjuan; Shu, Mao; Wang, Yuanqiang; Wang, Rui; Hu, Yong; Meng, Lingxin; Lin, Zhihua

2013-12-01

Phosphoinosmde-3-kinase/ mammalian target of rapamycin (PI3K/mTOR) dual inhibitors have attracted a great deal of interest as antitumor drugs research. In order to design and optimize these dual inhibitors, two types of 3D-quantitative structure-activity relationship (3D-QSAR) studies based on the ligand alignment and receptor alignment were applied using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). In the study based on ligands alignment, models of PI3K (CoMFA with r2, 0.770; q2, 0.622; CoMSIA with r2, 0.945; q2, 0.748) and mTOR (CoMFA with r2, 0.850; q2, 0.654; CoMSIA with r2, 0.983; q2, 0.676) have good predictability. And in the study based on receptor alignment, models of PI3K (CoMFA with r2, 0.745; q2, 0.538; CoMSIA with r2, 0.938; q2, 0.630) and mTOR (CoMFA with r2, 0.977; q2, 0.825; CoMSIA with r2, 0.985; q2, 0.728) also have good predictability. 3D contour maps and docking results suggested different groups on the core parts of the compounds could enhance the biological activities. Finally, ten derivatives as potential candidates of PI3K/mTOR inhibitors with good predicted activities were designed.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Are EMS call volume predictions based on demand pattern analysis accurate?

PubMed

Brown, Lawrence H; Lerner, E Brooke; Larmon, Baxter; LeGassick, Todd; Taigman, Michael

2007-01-01

Most EMS systems determine the number of crews they will deploy in their communities and when those crews will be scheduled based on anticipated call volumes. Many systems use historical data to calculate their anticipated call volumes, a method of prediction known as demand pattern analysis. To evaluate the accuracy of call volume predictions calculated using demand pattern analysis. Seven EMS systems provided 73 consecutive weeks of hourly call volume data. The first 20 weeks of data were used to calculate three common demand pattern analysis constructs for call volume prediction: average peak demand (AP), smoothed average peak demand (SAP), and 90th percentile rank (90%R). The 21st week served as a buffer. Actual call volumes in the last 52 weeks were then compared to the predicted call volumes by using descriptive statistics. There were 61,152 hourly observations in the test period. All three constructs accurately predicted peaks and troughs in call volume but not exact call volume. Predictions were accurate (+/-1 call) 13% of the time using AP, 10% using SAP, and 19% using 90%R. Call volumes were overestimated 83% of the time using AP, 86% using SAP, and 74% using 90%R. When call volumes were overestimated, predictions exceeded actual call volume by a median (Interquartile range) of 4 (2-6) calls for AP, 4 (2-6) for SAP, and 3 (2-5) for 90%R. Call volumes were underestimated 4% of time using AP, 4% using SAP, and 7% using 90%R predictions. When call volumes were underestimated, call volumes exceeded predictions by a median (Interquartile range; maximum under estimation) of 1 (1-2; 18) call for AP, 1 (1-2; 18) for SAP, and 2 (1-3; 20) for 90%R. Results did not vary between systems. Generally, demand pattern analysis estimated or overestimated call volume, making it a reasonable predictor for ambulance staffing patterns. However, it did underestimate call volume between 4% and 7% of the time. Communities need to determine if these rates of over-and underestimation are acceptable given their resources and local priorities.

MRI Detects Myocardial Iron in the Human Heart

PubMed Central

Ghugre, Nilesh R.; Enriquez, Cathleen M.; Gonzalez, Ignacio; Nelson, Marvin D.; Coates, Thomas D.; Wood, John C.

2010-01-01

Iron-induced cardiac dysfunction is a leading cause of death in transfusion-dependent anemia. MRI relaxation rates R2(1/T2) and R2∗(1∕T2∗) accurately predict liver iron concentration, but their ability to predict cardiac iron has been challenged by some investigators. Studies in animal models support similar R2 and R2∗ behavior with heart and liver iron, but human studies are lacking. To determine the relationship between MRI relaxivities and cardiac iron, regional variations in R2 and R2∗ were compared with iron distribution in one freshly deceased, unfixed, iron-loaded heart. R2 and R2∗ were proportionally related to regional iron concentrations and highly concordant with one another within the interventricular septum. A comparison of postmortem and in vitro measurements supports the notion that cardiac R2∗ should be assessed in the septum rather than the whole heart. These data, along with measurements from controls, provide bounds on MRI-iron calibration curves in human heart and further support the clinical use of cardiac MRI in iron-overload syndromes. PMID:16888797

A cascaded QSAR model for efficient prediction of overall power conversion efficiency of all-organic dye-sensitized solar cells.

PubMed

Li, Hongzhi; Zhong, Ziyan; Li, Lin; Gao, Rui; Cui, Jingxia; Gao, Ting; Hu, Li Hong; Lu, Yinghua; Su, Zhong-Min; Li, Hui

2015-05-30

A cascaded model is proposed to establish the quantitative structure-activity relationship (QSAR) between the overall power conversion efficiency (PCE) and quantum chemical molecular descriptors of all-organic dye sensitizers. The cascaded model is a two-level network in which the outputs of the first level (JSC, VOC, and FF) are the inputs of the second level, and the ultimate end-point is the overall PCE of dye-sensitized solar cells (DSSCs). The model combines quantum chemical methods and machine learning methods, further including quantum chemical calculations, data division, feature selection, regression, and validation steps. To improve the efficiency of the model and reduce the redundancy and noise of the molecular descriptors, six feature selection methods (multiple linear regression, genetic algorithms, mean impact value, forward selection, backward elimination, and +n-m algorithm) are used with the support vector machine. The best established cascaded model predicts the PCE values of DSSCs with a MAE of 0.57 (%), which is about 10% of the mean value PCE (5.62%). The validation parameters according to the OECD principles are R(2) (0.75), Q(2) (0.77), and Qcv2 (0.76), which demonstrate the great goodness-of-fit, predictivity, and robustness of the model. Additionally, the applicability domain of the cascaded QSAR model is defined for further application. This study demonstrates that the established cascaded model is able to effectively predict the PCE for organic dye sensitizers with very low cost and relatively high accuracy, providing a useful tool for the design of dye sensitizers with high PCE. © 2015 Wiley Periodicals, Inc.

THE CLUSTERING CHARACTERISTICS OF H I-SELECTED GALAXIES FROM THE 40% ALFALFA SURVEY

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

Martin, Ann M.; Giovanelli, Riccardo; Haynes, Martha P.

The 40% Arecibo Legacy Fast ALFA survey catalog ({alpha}.40) of {approx}10,150 H I-selected galaxies is used to analyze the clustering properties of gas-rich galaxies. By employing the Landy-Szalay estimator and a full covariance analysis for the two-point galaxy-galaxy correlation function, we obtain the real-space correlation function and model it as a power law, {xi}(r) = (r/r{sub 0}){sup -{gamma}}, on scales <10 h{sup -1} Mpc. As the largest sample of blindly H I-selected galaxies to date, {alpha}.40 provides detailed understanding of the clustering of this population. We find {gamma} = 1.51 {+-} 0.09 and r{sub 0} = 3.3 + 0.3, -0.2more » h{sup -1} Mpc, reinforcing the understanding that gas-rich galaxies represent the most weakly clustered galaxy population known; we also observe a departure from a pure power-law shape at intermediate scales, as predicted in {Lambda}CDM halo occupation distribution models. Furthermore, we measure the bias parameter for the {alpha}.40 galaxy sample and find that H I galaxies are severely antibiased on small scales, but only weakly antibiased on large scales. The robust measurement of the correlation function for gas-rich galaxies obtained via the {alpha}.40 sample constrains models of the distribution of H I in simulated galaxies, and will be employed to better understand the role of gas in environmentally dependent galaxy evolution.« less

Prediction of biodegradability of aromatics in water using QSAR modeling.

PubMed

Cvetnic, Matija; Juretic Perisic, Daria; Kovacic, Marin; Kusic, Hrvoje; Dermadi, Jasna; Horvat, Sanja; Bolanca, Tomislav; Marin, Vedrana; Karamanis, Panaghiotis; Loncaric Bozic, Ana

2017-05-01

The study was aimed at developing models for predicting the biodegradability of aromatic water pollutants. For that purpose, 36 single-benzene ring compounds, with different type, number and position of substituents, were used. The biodegradability was estimated according to the ratio of the biochemical (BOD 5 ) and chemical (COD) oxygen demand values determined for parent compounds ((BOD 5 /COD) 0 ), as well as for their reaction mixtures in half-life achieved by UV-C/H 2 O 2 process ((BOD 5 /COD) t1/2 ). The models correlating biodegradability and molecular structure characteristics of studied pollutants were derived using quantitative structure-activity relationship (QSAR) principles and tools. Upon derivation of the models and calibration on the training and subsequent testing on the test set, 3- and 5-variable models were selected as the most predictive for (BOD 5 /COD) 0 and (BOD 5 /COD) t1/2 , respectively, according to the values of statistical parameters R 2 and Q 2 . Hence, 3-variable model predicting (BOD 5 /COD) 0 possessed R 2 =0.863 and Q 2 =0.799 for training set, and R 2 =0.710 for test set, while 5-variable model predicting (BOD 5 /COD) 1/2 possessed R 2 =0.886 and Q 2 =0.788 for training set, and R 2 =0.564 for test set. The selected models are interpretable and transparent, reflecting key structural features that influence targeted biodegradability and can be correlated with the degradation mechanisms of studied compounds by UV-C/H 2 O 2 . Copyright © 2017 Elsevier Inc. All rights reserved.

Lower limb alactic anaerobic power output assessed with different techniques in morbid obesity.

PubMed

Lafortuna, C L; Fumagalli, E; Vangeli, V; Sartorio, A

2002-02-01

Short-term alactic anaerobic performance in jumping (5 consecutive jumps with maximal effort), sprint running (8 m) and stair climbing (modified Margaria test) were measured in 75 obese subjects (BMI: 40.3+/-5.0 kg/m2) and in 36 lean control subjects (BMI: 22.4+/-3.2 kg/m2) of the same age and gender distribution. The results show that obese subjects attained a significantly lower specific (per unit body mass) power output both in jumping (W(spec,j); p<0.001) and stair climbing (W(spec,s); p<0.001) and run at a significantly lower average velocity (v; p<0.001) during sprinting. In spite of the different motor skillfulness required to accomplish the jumping and climbing tests, W(spec,s) (and hence the vertical velocity in climbing, v(v)) was closely correlated with W(spec,j) (R2=0.427, p<0.001). In jumping, although the average force during the positive work phase was significantly higher in obese subjects (p<0.001), no difference between the 2 groups was detected in absolute power. In stair climbing the absolute power output of obese resulted significantly higher (18%) than that of lean controls (p<0.001). In sprint running, the lower average horizontal velocity attained by obese subjects also entailed a different locomotion pattern with shorter step length (L(s); p<0.001), lower frequency (p<0.001) and longer foot contact time with ground (T(c,r); p<0.001). W(spec,j) seems to be a determinant of the poorer motor performance of obese, being significantly correlated with: I) the vertical displacement of the centre of gravity (R2=0.853, p<0.001) in jumping; II) with v(v) in stair climbing; and III) with T(c,r) (R2=0.492, p<0.001), L(s) (R2=0.266, p<0.001) and v (R2=0.454, p<0.001) in sprinting. The results suggest that obese individuals, although partially hampered in kinetic movements, largely rely on their effective specific power output to perform complex anaerobic tasks, and they suffer from the disproportionate excess of inert mass of fat. Furthermore, in view of the sedentary style of life and the consequent degree of muscle de-conditioning accompanying this condition, it may prove useful to implement rehabilitation programs for obesity with effective power training protocols.

A novel structure-based multimode QSAR method affords predictive models for phosphodiesterase inhibitors.

PubMed

Dong, Xialan; Ebalunode, Jerry O; Cho, Sung Jin; Zheng, Weifan

2010-02-22

Quantitative structure-activity relationship (QSAR) methods aim to build quantitatively predictive models for the discovery of new molecules. It has been widely used in medicinal chemistry for drug discovery. Many QSAR techniques have been developed since Hansch's seminal work, and more are still being developed. Motivated by Hopfinger's receptor-dependent QSAR (RD-QSAR) formalism and the Lukacova-Balaz scheme to treat multimode issues, we have initiated studies that focus on a structure-based multimode QSAR (SBMM QSAR) method, where the structure of the target protein is used in characterizing the ligand, and the multimode issue of ligand binding is systematically treated with a modified Lukacova-Balaz scheme. All ligand molecules are first docked to the target binding pocket to obtain a set of aligned ligand poses. A structure-based pharmacophore concept is adopted to characterize the binding pocket. Specifically, we represent the binding pocket as a geometric grid labeled by pharmacophoric features. Each pose of the ligand is also represented as a labeled grid, where each grid point is labeled according to the atom types of nearby ligand atoms. These labeled grids or three-dimensional (3D) maps (both the receptor map (R-map) and the ligand map (L-map)) are compared to each other to derive descriptors for each pose of the ligand, resulting in a multimode structure-activity relationship (SAR) table. Iterative partial least-squares (PLS) is employed to build the QSAR models. When we applied this method to analyze PDE-4 inhibitors, predictive models have been developed, obtaining models with excellent training correlation (r(2) = 0.65-0.66), as well as test correlation (R(2) = 0.64-0.65). A comparative analysis with 4 other QSAR techniques demonstrates that this new method affords better models, in terms of the prediction power for the test set.

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.

The seated medicine ball throw as a test of upper body power in older adults.

PubMed

Harris, Chad; Wattles, Andrew P; DeBeliso, Mark; Sevene-Adams, Patricia G; Berning, Joseph M; Adams, Kent J

2011-08-01

Practitioners training the older adult may benefit from a low-cost, easy-to-administer field test of upper body power. This study evaluated validity and reliability of the seated medicine ball throw (SMBT) in older adults. Subjects (n = 33; age 72.4 ± 5.2 years) completed 6 trials of an SMBT in each of 2 testing days and 2 ball masses (1.5 and 3.0 kg). Subjects also completed 6 trials of an explosive push-up (EPU) on a force plate over 2 testing days. Validity was assessed via a Pearson Product-Moment correlation (PPM) between SMBT and EPU maximal vertical force. Reliability of the SMBT was determined using PPMs (r), Intraclass correlation (ICC, R) and Bland-Altman plots (BAPs). For validity, the association between the SMBT and the EPU revealed a PPM of r = 0.641 and r = 0.614 for the 1.5- and 3.0-kg medicine balls, respectively. Test-retest reliability of the 1.5- and 3.0-kg SMBT was r = 0.967 and r = 0.958, respectively. The ICC values of the 1.5- and 3.0-kg SMBT were R = 0.994 and 0.989, respectively. The BAPs revealed 94% of the differences between day 1 and 2 scores were within the 95% confidence interval of the mean difference. Test-retest reliability for the EPU was r = 0.944, R = 0.969. The BAPs showed 94% of the differences between day 1 and 2 scores were within the 95% confidence interval of the mean difference, for both medicine ball throws. In conclusion, for the older adult, the SMBT appears to be highly reliable test of upper body power. Its validity relative to the maximal force exerted during the EPU is modest. The SMBT is an inexpensive, safe, and repeatable measure of upper body power for the older adult.

An Inductively Powered Scalable 32-Channel Wireless Neural Recording System-on-a-Chip for Neuroscience Applications

PubMed Central

Lee, Seung Bae; Lee, Hyung-Min; Kiani, Mehdi; Jow, Uei-Ming; Ghovanloo, Maysam

2014-01-01

We present an inductively powered 32-channel wireless integrated neural recording (WINeR) system-on-a-chip (SoC) to be ultimately used for one or more small freely behaving animals. The inductive powering is intended to relieve the animals from carrying bulky batteries used in other wireless systems, and enables long recording sessions. The WINeR system uses time-division multiplexing along with a novel power scheduling method that reduces the current in unused low-noise amplifiers (LNAs) to cut the total SoC power consumption. In addition, an on-chip high-efficiency active rectifier with optimized coils help improve the overall system power efficiency, which is controlled in a closed loop to supply stable power to the WINeR regardless of the coil displacements. The WINeR SoC has been implemented in a 0.5-µm standard complementary metal–oxide semiconductor process, measuring 4.9 × 3.3 mm2 and consuming 5.85 mW at ± 1.5 V when 12 out of 32 LNAs are active at any time by power scheduling. Measured input-referred noise for the entire system, including the receiver located at 1.2 m, is 4.95 µVrms in the 1 Hz~10 kHz range when the system is inductively powered with 7-cm separation between aligned coils. PMID:23850753

The Sex, Age, Medical History, Treatment, Tobacco Use, Race Risk (SAMe TT2R2) Score Predicts Warfarin Control in a Singaporean Population.

PubMed

Bernaitis, Nijole; Ching, Chi Keong; Chen, Liping; Hon, Jin Shing; Teo, Siew Chong; Davey, Andrew K; Anoopkumar-Dukie, Shailendra

2017-01-01

Warfarin reduces stroke risk in atrial fibrillation (AF) patients but requires ongoing monitoring. Time in therapeutic range (TTR) is used as a measure of warfarin control, with a TTR less than 60% associated with adverse patient outcomes. The Sex, Age, Medical history, Treatment, Tobacco use, Race (SAMe-TT 2 R 2 ) score has been identified as a model able to predict warfarin control, but this has been tested in mainly Caucasian populations. Therefore, the aim of this study was to determine the ability of the SAMe-TT 2 R 2 score to predict warfarin control in a Singaporean population consisting of Chinese, Malay, and Indian race. Retrospective data were collected from the National Heart Centre Singapore for AF patients receiving warfarin between January and June 2014. The TTR and the SAMe-TT 2 R 2 score were calculated for each patient. The 1137 non-valvular AF patients had a mean TTR of 58.0 ± 34.3% and a median SAMe-TT 2 R 2 score of 3. The categorized SAMe-TT 2 R 2 scores (2 versus >2) showed a significant reduction in mean TTR for the entire population (63.2% versus 55.8%, P = .0004) and also when categorized according to race for Chinese (62.7% versus 56.9%, P = .0075) and Malay (68.4% versus 50.6%, P = .0131) populations. The SAMe-TT 2 R 2 tool is effective in predicting warfarin control in a Singaporean population as patients with a score greater than 2 had poor control. The minimum score for non-Caucasian patients is 2; thus, in these patients, the presence of any additional risk factors identified in the SAMe-TT 2 R 2 tool categorizes them as unlikely to achieve adequate warfarin control and possible candidates for alternative anticoagulants. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Video image analysis in the Australian meat industry - precision and accuracy of predicting lean meat yield in lamb carcasses.

PubMed

Hopkins, D L; Safari, E; Thompson, J M; Smith, C R

2004-06-01

A wide selection of lamb types of mixed sex (ewes and wethers) were slaughtered at a commercial abattoir and during this process images of 360 carcasses were obtained online using the VIAScan® system developed by Meat and Livestock Australia. Soft tissue depth at the GR site (thickness of tissue over the 12th rib 110 mm from the midline) was measured by an abattoir employee using the AUS-MEAT sheep probe (PGR). Another measure of this thickness was taken in the chiller using a GR knife (NGR). Each carcass was subsequently broken down to a range of trimmed boneless retail cuts and the lean meat yield determined. The current industry model for predicting meat yield uses hot carcass weight (HCW) and tissue depth at the GR site. A low level of accuracy and precision was found when HCW and PGR were used to predict lean meat yield (R(2)=0.19, r.s.d.=2.80%), which could be improved markedly when PGR was replaced by NGR (R(2)=0.41, r.s.d.=2.39%). If the GR measures were replaced by 8 VIAScan® measures then greater prediction accuracy could be achieved (R(2)=0.52, r.s.d.=2.17%). A similar result was achieved when the model was based on principal components (PCs) computed from the 8 VIAScan® measures (R(2)=0.52, r.s.d.=2.17%). The use of PCs also improved the stability of the model compared to a regression model based on HCW and NGR. The transportability of the models was tested by randomly dividing the data set and comparing coefficients and the level of accuracy and precision. Those models based on PCs were superior to those based on regression. It is demonstrated that with the appropriate modeling the VIAScan® system offers a workable method for predicting lean meat yield automatically.

Predicting change over time in career planning and career exploration for high school students.

PubMed

Creed, Peter A; Patton, Wendy; Prideaux, Lee-Ann

2007-06-01

This study assessed 166 high school students in Grade 8 and again in Grade 10. Four models were tested: (a) whether the T1 predictor variables (career knowledge, indecision, decision-making self efficacy, self-esteem, demographics) predicted the outcome variable (career planning/exploration) at T1; (b) whether the T1 predictor variables predicted the outcome variable at T2; (c) whether the T1 predictor variables predicted change in the outcome variable from T1-T2; and (d) whether changes in the predictor variables from T1-T2 predicted change in the outcome variable from T1-T2. Strong associations (R(2)=34%) were identified for the T1 analysis (confidence, ability and paid work experience were positively associated with career planning/exploration). T1 variables were less useful predictors of career planning/exploration at T2 (R(2)=9%; having more confidence at T1 was associated with more career planning/exploration at T2) and change in career planning/exploration from T1-T2 (R(2)=11%; less confidence and no work experience were associated with change in career planning/exploration from T1-T2). When testing effect of changes in predictor variables predicting changes in outcome variable (R(2)=22%), three important predictors, indecision, work experience and confidence, were identified. Overall, results indicated important roles for self-efficacy and early work experiences in current and future career planning/exploration of high school students.

Tools for Early Prediction of Drug Loading in Lipid-Based Formulations

PubMed Central

2015-01-01

Identification of the usefulness of lipid-based formulations (LBFs) for delivery of poorly water-soluble drugs is at date mainly experimentally based. In this work we used a diverse drug data set, and more than 2,000 solubility measurements to develop experimental and computational tools to predict the loading capacity of LBFs. Computational models were developed to enable in silico prediction of solubility, and hence drug loading capacity, in the LBFs. Drug solubility in mixed mono-, di-, triglycerides (Maisine 35-1 and Capmul MCM EP) correlated (R2 0.89) as well as the drug solubility in Carbitol and other ethoxylated excipients (PEG400, R2 0.85; Polysorbate 80, R2 0.90; Cremophor EL, R2 0.93). A melting point below 150 °C was observed to result in a reasonable solubility in the glycerides. The loading capacity in LBFs was accurately calculated from solubility data in single excipients (R2 0.91). In silico models, without the demand of experimentally determined solubility, also gave good predictions of the loading capacity in these complex formulations (R2 0.79). The framework established here gives a better understanding of drug solubility in single excipients and of LBF loading capacity. The large data set studied revealed that experimental screening efforts can be rationalized by solubility measurements in key excipients or from solid state information. For the first time it was shown that loading capacity in complex formulations can be accurately predicted using molecular information extracted from calculated descriptors and thermal properties of the crystalline drug. PMID:26568134

Tools for Early Prediction of Drug Loading in Lipid-Based Formulations.

PubMed

Alskär, Linda C; Porter, Christopher J H; Bergström, Christel A S

2016-01-04

Identification of the usefulness of lipid-based formulations (LBFs) for delivery of poorly water-soluble drugs is at date mainly experimentally based. In this work we used a diverse drug data set, and more than 2,000 solubility measurements to develop experimental and computational tools to predict the loading capacity of LBFs. Computational models were developed to enable in silico prediction of solubility, and hence drug loading capacity, in the LBFs. Drug solubility in mixed mono-, di-, triglycerides (Maisine 35-1 and Capmul MCM EP) correlated (R(2) 0.89) as well as the drug solubility in Carbitol and other ethoxylated excipients (PEG400, R(2) 0.85; Polysorbate 80, R(2) 0.90; Cremophor EL, R(2) 0.93). A melting point below 150 °C was observed to result in a reasonable solubility in the glycerides. The loading capacity in LBFs was accurately calculated from solubility data in single excipients (R(2) 0.91). In silico models, without the demand of experimentally determined solubility, also gave good predictions of the loading capacity in these complex formulations (R(2) 0.79). The framework established here gives a better understanding of drug solubility in single excipients and of LBF loading capacity. The large data set studied revealed that experimental screening efforts can be rationalized by solubility measurements in key excipients or from solid state information. For the first time it was shown that loading capacity in complex formulations can be accurately predicted using molecular information extracted from calculated descriptors and thermal properties of the crystalline drug.

Power law signature of media exposure in human response waiting time distributions

NASA Astrophysics Data System (ADS)

Crane, Riley; Schweitzer, Frank; Sornette, Didier

2010-05-01

We study the humanitarian response to the destruction brought by the tsunami generated by the Sumatra earthquake of December 26, 2004, as measured by donations, and find that it decays in time as a power law ˜1/tα with α=2.5±0.1 . This behavior is suggested to be the rare outcome of a priority queuing process in which individuals execute tasks at a rate slightly faster than the rate at which new tasks arise. We believe this to be an empirical evidence documenting the recently predicted [G. Grinstein and R. Linsker, Phys. Rev. E 77, 012101 (2008)] regime, and provide additional independent evidence that suggests that this “highly attentive regime” arises as a result of the intense focus placed on this donation “task” by the media.

Aerodynamics model for a generic ASTOVL lift-fan aircraft

NASA Technical Reports Server (NTRS)

Birckelbaw, Lourdes G.; Mcneil, Walter E.; Wardwell, Douglas A.

1995-01-01

This report describes the aerodynamics model used in a simulation model of an advanced short takeoff and vertical landing (ASTOVL) lift-fan fighter aircraft. The simulation model was developed for use in piloted evaluations of transition and hover flight regimes, so that only low speed (M approximately 0.2) aerodynamics are included in the mathematical model. The aerodynamic model includes the power-off aerodynamic forces and moments and the propulsion system induced aerodynamic effects, including ground effects. The power-off aerodynamics data were generated using the U.S. Air Force Stability and Control Digital DATCOM program and a NASA Ames in-house graphics program called VORVIEW which allows the user to easily analyze arbitrary conceptual aircraft configurations using the VORLAX program. The jet-induced data were generated using the prediction methods of R. E. Kuhn et al., as referenced in this report.

Chromatic microlensing in HE0047-1756 and SDSS1155+6346

NASA Astrophysics Data System (ADS)

Rojas, K.; Motta, V.; Mediavilla, E.; Falco, E.; Muñoz, J. A.

2014-10-01

The gravitational lens effect occurs when the light is deflected in the presence of a gravitational field, generating multiple images or arcs. Microlensing happens when a compact object, in the lens galaxy halo, passes across a quasar lensed image. We analyzed two double systems: HE0047-1756 and SDSS1155+6346. We used spectra obtained with Magellan/IMACS (2007) and MMT/Blue-Channel (2008). The flux of emission line cores was separated from the continuum flux under them and integrated using DIPSO software. Comparing the magnitude differences in the emission line cores with the magnitude differences in the continuum under the lines (Motta et. al 2012), we found evidence of chromatic microlensing in HE0047-1756 and SDSS1155+6346. Emission line core fluxes are used to model the systems with lensmodel. SIS + γ are the best models in both cases, which are in agreement with literature. SDSS1155+6346 model shows a large shear, due to the presence of MaxBCG J178.81693+63.83446 cluster. We follow Mediavilla et al. 2011, modeling the accretion disk as a Gaussian intensity profile I(R) ∝ exp(-R^{2}/2r_{s}^{2}), with r_s(λ) ∝ λ^{p}, where r_{s} is the accretion disk size and p is the power law related to the temperature of the disk p = 1/β. We estimate the probability of r_{s} and p using the measured microlensing magnification with linear and logarithmic priors on r_{s}. We found within 1σ of uncertainty, sizes between 3 and 15 light days and temperature profiles values between 1 and 1.2. These values are in agreement with the literature and Shakura & Sunyaev (1973) prediction. We acknowledge to FONDECYT 1120741 and Centro de Astrofísica, Universidad de Valparaíso.

[Comparison of three methods for measuring multiple morbidity according to the use of health resources in primary healthcare].

PubMed

Sicras-Mainar, Antoni; Velasco-Velasco, Soledad; Navarro-Artieda, Ruth; Blanca Tamayo, Milagrosa; Aguado Jodar, Alba; Ruíz Torrejón, Amador; Prados-Torres, Alexandra; Violan-Fors, Concepción

2012-06-01

To compare three methods of measuring multiple morbidity according to the use of health resources (cost of care) in primary healthcare (PHC). Retrospective study using computerized medical records. Thirteen PHC teams in Catalonia (Spain). Assigned patients requiring care in 2008. The socio-demographic variables were co-morbidity and costs. Methods of comparison were: a) Combined Comorbidity Index (CCI): an index itself was developed from the scores of acute and chronic episodes, b) Charlson Index (ChI), and c) Adjusted Clinical Groups case-mix: resource use bands (RUB). The cost model was constructed by differentiating between fixed (operational) and variable costs. 3 multiple lineal regression models were developed to assess the explanatory power of each measurement of co-morbidity which were compared from the determination coefficient (R(2)), p< .05. The study included 227,235 patients. The mean unit of cost was €654.2. The CCI explained an R(2)=50.4%, the ChI an R(2)=29.2% and BUR an R(2)=39.7% of the variability of the cost. The behaviour of the ICC is acceptable, albeit with low scores (1 to 3 points), showing inconclusive results. The CCI may be a simple method of predicting PHC costs in routine clinical practice. If confirmed, these results will allow improvements in the comparison of the case-mix. Copyright © 2011 Elsevier España, S.L. All rights reserved.

An Effect Size for Regression Predictors in Meta-Analysis

ERIC Educational Resources Information Center

Aloe, Ariel M.; Becker, Betsy Jane

2012-01-01

A new effect size representing the predictive power of an independent variable from a multiple regression model is presented. The index, denoted as r[subscript sp], is the semipartial correlation of the predictor with the outcome of interest. This effect size can be computed when multiple predictor variables are included in the regression model…

Policies, Local Control, and Other Antiquities.

ERIC Educational Resources Information Center

Davies, Daniel R.; And Others

1988-01-01

This bulletin focuses on the views of four authors. The first, Daniel R. Davies, describes the rise and fall of local control and local school board policies and predicts how the vacuum will be filled. Specifically, he analyzes the concomitant waning of local control and school board policymaking power and forecasts stages in the transition from…

Predicting marching capacity while carrying extremely heavy loads.

PubMed

Koerhuis, Claudy L; Veenstra, Bertil J; van Dijk, Jos J; Delleman, Nico J

2009-12-01

The objective of this study was to establish the best prediction for endurance time of combat soldiers marching with extremely heavy loads. It was hypothesized that loads relative to individual characteristics (% maximal load carry capacity [MLCC], % body mass, % lean body mass) would better predict endurance time than load itself. Twenty-three male combat soldiers participated. MLCC was determined by increasing the load by 7.5 kg every 4 minutes until exhaustion. The marching velocity and gradient were 3 km.h(-1) and 5%, respectively. Endurance time was determined carrying 70, 80, and 90% of MLCC. MLCC was on average 102.6 kg +/- 11.6. Load expressed as % MLCC was the best predictor for endurance time (R2 = 0.45). Load expressed as % body mass, as % lean body mass, and absolute load predicted endurance time less well (R2 = 0.30, R2 = 0.24, and R2 = 0.23, respectively). On the basis of these results, it is recommended to assess the MLCC of individual combat soldiers.

Gallium phosphide energy converters

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

Sims, P.E.; Dinetta, L.C.; Goetz, M.A.

1995-10-01

Gallium phosphide (GaP) energy converters may be successfully deployed to provide new mission capabilities for spacecraft. Betavoltaic power supplies based on the conversion of tritium beta decay to electricity using GaP energy converters can supply long term low-level power with high reliability. High temperature solar cells, also based on GaP, can be used in inward-bound missions greatly reducing the need for thermal dissipation. Results are presented for GaP direct conversion devices powered by Ni-63 and compared to the conversion of light emitted by tritiarated phosphors. Leakage currents as low as 1.2 x 10(exp {minus}17) A/sq cm have been measured andmore » the temperature dependence of the reverse saturation current is found to have ideal behavior. Temperature dependent IV, QE, R(sub sh), and V(sub oc) results are also presented. These data are used to predict the high-temperature solar cell and betacell performance of GaP devices and suggest appropriate applications for the deployment of this technology.« less

Gallium phosphide energy converters

NASA Astrophysics Data System (ADS)

Sims, P. E.; Dinetta, L. C.; Goetz, M. A.

1995-10-01

Gallium phosphide (GaP) energy converters may be successfully deployed to provide new mission capabilities for spacecraft. Betavoltaic power supplies based on the conversion of tritium beta decay to electricity using GaP energy converters can supply long term low-level power with high reliability. High temperature solar cells, also based on GaP, can be used in inward-bound missions greatly reducing the need for thermal dissipation. Results are presented for GaP direct conversion devices powered by Ni-63 and compared to the conversion of light emitted by tritiarated phosphors. Leakage currents as low as 1.2 x 10(exp -17) A/sq cm have been measured and the temperature dependence of the reverse saturation current is found to have ideal behavior. Temperature dependent IV, QE, R(sub sh), and V(sub oc) results are also presented. These data are used to predict the high-temperature solar cell and betacell performance of GaP devices and suggest appropriate applications for the deployment of this technology.

Gallium phosphide energy converters

NASA Technical Reports Server (NTRS)

Sims, P. E.; Dinetta, L. C.; Goetz, M. A.

1995-01-01

Gallium phosphide (GaP) energy converters may be successfully deployed to provide new mission capabilities for spacecraft. Betavoltaic power supplies based on the conversion of tritium beta decay to electricity using GaP energy converters can supply long term low-level power with high reliability. High temperature solar cells, also based on GaP, can be used in inward-bound missions greatly reducing the need for thermal dissipation. Results are presented for GaP direct conversion devices powered by Ni-63 and compared to the conversion of light emitted by tritiarated phosphors. Leakage currents as low as 1.2 x 10(exp -17) A/sq cm have been measured and the temperature dependence of the reverse saturation current is found to have ideal behavior. Temperature dependent IV, QE, R(sub sh), and V(sub oc) results are also presented. These data are used to predict the high-temperature solar cell and betacell performance of GaP devices and suggest appropriate applications for the deployment of this technology.

Divertor extreme ultraviolet (EUV) survey spectroscopy in DIII-D

NASA Astrophysics Data System (ADS)

McLean, Adam; Allen, Steve; Ellis, Ron; Jarvinen, Aaro; Soukhanovskii, Vlad; Boivin, Rejean; Gonzales, Eduardo; Holmes, Ian; Kulchar, James; Leonard, Anthony; Williams, Bob; Taussig, Doug; Thomas, Dan; Marcy, Grant

2017-10-01

An extreme ultraviolet spectrograph measuring resonant emissions of D and C in the lower divertor has been added to DIII-D to help resolve an 2X discrepancy between bolometrically measured radiated power and that predicted by boundary codes for DIII-D, JET and ASDEX-U. With 290 and 450 gr/mm gratings, the DivSPRED spectrometer, an 0.3 m flat-field McPherson model 251, measures ground state transitions for D (the Lyman series) and C (e.g., C IV, 155 nm) which account for >75% of radiated power in the divertor. Combined with Thomson scattering and imaging in the DIII-D divertor, measurements of position, temperature and fractional power emission from plasma components are made and compared to UEDGE/SOLPS-ITER. Mechanical, optical, electrical, vacuum, and shielding aspects of DivSPRED are presented. Work supported under USDOE Cooperative Agreement DE-FC02-04ER54698 and DE-AC52-07NA27344, and by the LLNL Laboratory Directed R&D Program, project #17-ERD-020.

Contributions of tidal lung inflation to human R-R interval and arterial pressure fluctuations

NASA Technical Reports Server (NTRS)

Koh, J.; Brown, T. E.; Beightol, L. A.; Eckberg, D. L.

1998-01-01

We studied the effects of mechanical lung inflation on respiratory frequency R-R interval and arterial pressure fluctuations in nine healthy young adults undergoing elective orthopedic surgery. We conducted this research to define the contribution of pulmonary and thoracic stretch receptor input to respiratory sinus arrhythmia. We compared fast Fourier transform spectral power during three modes of ventilation: (1) spontaneous, frequency-controlled (0.25 Hz) breathing, (2) intermittent positive pressure ventilation (0.25 Hz, with a tidal volume of 8 ml/kg) and (3) high frequency jet ventilation (5.0 Hz, 2.5 kg/cm2), after sedation and vecuronium paralysis. Mean R-R intervals, arterial pressures and arterial blood gas levels were comparable during all three breathing conditions. Respiratory frequency systolic pressure spectral power was comparable during spontaneous breathing and conventional mechanical ventilation, but was significantly reduced during high frequency jet ventilation (P < 0.05). Respiratory frequency R-R interval spectral power (used as an index of respiratory sinus arrhythmia) declined dramatically with sedation and muscle paralysis (P < 0.05), but was greater during conventional mechanical, than high frequency jet ventilation (P < 0.05). These results suggest that although phasic inputs from pulmonary and thoracic stretch receptors make a statistically significant contribution to respiratory sinus arrhythmia, that contribution is small.

The influence of somatotype on anaerobic performance

PubMed Central

Faulkner, James; Jobson, Simon

2018-01-01

The link between athlete physique and performance in sports is well established. However, a direct link between somatotype three-numeral rating and anaerobic performance has not yet been reported. The purpose of this study was to assess the relations between somatotype and anaerobic performance using both singular and multivariate analyses. Thirty-six physically active males (mean ± standard deviation age 26.0 ± 9.8 years; body mass 79.5 ± 12.9 kg; height 1.82 ± 0.07 m) were somatotype-rated using the Heath-Carter method. Subjects were assessed for 3 repetition maximum (3 RM) bench press and back squat, and completed a 30-second maximal sprint cycle test. Positive correlations were observed between mesomorphy and 3 RM bench press (r = 0.560, p < 0.001), mesomorphy and 3 RM back squat (r = 0.550, p = 0.001) and between mesomorphy and minimum power output (r = 0.357, p = 0.033). Negative correlations were observed between ectomorphy and 3 RM bench press (r = -0.381, p = 0.022), and ectomorphy and 3 RM back squat (r = -0.336, p = 0.045). Individual regression analysis indicated that mesomorphy was the best predictor of 3 RM bench press performance, with 31.4% of variance in 3 RM bench press performance accounted for by the mesomorphy rating (p < 0.001). A combination of mesomorphy and ectomorphy best predicted 3 RM back squat performance (R2 = 0.388, p < 0.04). Around one third of strength performance is predicted by somatotype-assessed physique in physically active males. This could have important implications for the identification of those predisposed to perform well in sports containing strength-based movements and prescription of training programmes. PMID:29787610

The influence of somatotype on anaerobic performance.

PubMed

Ryan-Stewart, Helen; Faulkner, James; Jobson, Simon

2018-01-01

The link between athlete physique and performance in sports is well established. However, a direct link between somatotype three-numeral rating and anaerobic performance has not yet been reported. The purpose of this study was to assess the relations between somatotype and anaerobic performance using both singular and multivariate analyses. Thirty-six physically active males (mean ± standard deviation age 26.0 ± 9.8 years; body mass 79.5 ± 12.9 kg; height 1.82 ± 0.07 m) were somatotype-rated using the Heath-Carter method. Subjects were assessed for 3 repetition maximum (3 RM) bench press and back squat, and completed a 30-second maximal sprint cycle test. Positive correlations were observed between mesomorphy and 3 RM bench press (r = 0.560, p < 0.001), mesomorphy and 3 RM back squat (r = 0.550, p = 0.001) and between mesomorphy and minimum power output (r = 0.357, p = 0.033). Negative correlations were observed between ectomorphy and 3 RM bench press (r = -0.381, p = 0.022), and ectomorphy and 3 RM back squat (r = -0.336, p = 0.045). Individual regression analysis indicated that mesomorphy was the best predictor of 3 RM bench press performance, with 31.4% of variance in 3 RM bench press performance accounted for by the mesomorphy rating (p < 0.001). A combination of mesomorphy and ectomorphy best predicted 3 RM back squat performance (R2 = 0.388, p < 0.04). Around one third of strength performance is predicted by somatotype-assessed physique in physically active males. This could have important implications for the identification of those predisposed to perform well in sports containing strength-based movements and prescription of training programmes.

Determinants of a simulated cross-country skiing sprint competition using V2 skating technique on roller skis.

PubMed

Mikkola, Jussi; Laaksonen, Marko; Holmberg, Hans-Christer; Vesterinen, Ville; Nummela, Ari

2010-04-01

The present study investigated the performance-predicting factors of a simulated cross-country (XC) skiing sprint competition on roller skis, on a slow surface. Sixteen elite male XC skiers performed a simulated sprint competition (4 x 850 m heat with a 20-minute recovery) using V2 skating technique on an indoor tartan track. Heat velocities, oxygen consumption, and peak lactate were measured during or after the heats. Maximal skiing velocity was measured by performing a 30-m speed test. Explosive and maximal force production in the upper body was determined by bench press (BP). Subjects also performed maximal anaerobic skiing test (MAST) and the 2 x 2-km double poling (DP) test. The maximal velocity of MAST (VMAST) and velocities at 3 (V3), 5 (V5), 7 (V7) mmol.L lactate levels in MAST were determined. In the 2 x 2-km test, DP economy (VO2SUBDP) and maximal 2-km DP velocity (VDP2KM) were determined. The best single performance-predicting factors for the sprint performance were VDP2KM (r = 0.73, p < 0.01), V7 (r = 0.70, p < 0.01), and VO2SUBDP (r = -0.70, p < 0.01). Faster skiers in sprint simulation had a higher absolute VO2 (L.min) (p < 0.05-0.01) during sprint heats, and higher anaerobic skiing power (VMAST, p < 0.05) and better anaerobic skiing economy (V3, V5, V7, p < 0.05-0.001) than slower skiers. Faster skiers were also stronger in BP, with regard to both absolute (p < 0.01) and relative (p < 0.05) values. In addition, anaerobic characteristics seem to be of importance at the beginning of the XC skiing sprint competition, whereas the aerobic characteristics become more important as the XC skiing sprint competition progressed. This study indicates that sprint skiers should emphasize sport-specific upper body training, and training skiing economy at high speeds.

Identification of novel histone deacetylase 1 inhibitors by combined pharmacophore modeling, 3D-QSAR analysis, in silico screening and Density Functional Theory (DFT) approaches

NASA Astrophysics Data System (ADS)

Choubey, Sanjay K.; Mariadasse, Richard; Rajendran, Santhosh; Jeyaraman, Jeyakanthan

2016-12-01

Overexpression of HDAC1, a member of Class I histone deacetylase is reported to be implicated in breast cancer. Epigenetic alteration in carcinogenesis has been the thrust of research for few decades. Increased deacetylation leads to accelerated cell proliferation, cell migration, angiogenesis and invasion. HDAC1 is pronounced as the potential drug target towards the treatment of breast cancer. In this study, the biochemical potential of 6-aminonicotinamide derivatives was rationalized. Five point pharmacophore model with one hydrogen-bond acceptor (A3), two hydrogen-bond donors (D5, D6), one ring (R12) and one hydrophobic group (H8) was developed using 6-aminonicotinamide derivatives. The pharmacophore hypothesis yielded a 3D-QSAR model with correlation-coefficient (r2 = 0.977, q2 = 0.801) and it was externally validated with (r2pred = 0.929, r2cv = 0.850 and r2m = 0.856) which reveals the statistical significance of the model having high predictive power. The model was then employed as 3D search query for virtual screening against compound libraries (Zinc, Maybridge, Enamine, Asinex, Toslab, LifeChem and Specs) in order to identify novel scaffolds which can be experimentally validated to design future drug molecule. Density Functional Theory (DFT) at B3LYP/6-31G* level was employed to explore the electronic features of the ligands involved in charge transfer reaction during receptor ligand interaction. Binding free energy (ΔGbind) calculation was done using MM/GBSA which defines the affinity of ligands towards the receptor.

The Chip-Scale Atomic Clock - Low-Power Physics Package

DTIC Science & Technology

2004-12-01

36th Annual Precise Time and Time Interval (PTTI) Meeting 339 THE CHIP-SCALE ATOMIC CLOCK – LOW-POWER PHYSICS PACKAGE R. Lutwak ...pdf/documents/ds-x72.pdf [2] R. Lutwak , D. Emmons, W. Riley, and R. M. Garvey, 2003, “The Chip-Scale Atomic Clock – Coherent Population Trapping vs...2002, Reston, Virginia, USA (U.S. Naval Observatory, Washington, D.C.), pp. 539-550. [3] R. Lutwak , D. Emmons, T. English, and W. Riley, 2004

Improving the prediction of African savanna vegetation variables using time series of MODIS products

NASA Astrophysics Data System (ADS)

Tsalyuk, Miriam; Kelly, Maggi; Getz, Wayne M.

2017-09-01

African savanna vegetation is subject to extensive degradation as a result of rapid climate and land use change. To better understand these changes detailed assessment of vegetation structure is needed across an extensive spatial scale and at a fine temporal resolution. Applying remote sensing techniques to savanna vegetation is challenging due to sparse cover, high background soil signal, and difficulty to differentiate between spectral signals of bare soil and dry vegetation. In this paper, we attempt to resolve these challenges by analyzing time series of four MODIS Vegetation Products (VPs): Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), and Fraction of Photosynthetically Active Radiation (FPAR) for Etosha National Park, a semiarid savanna in north-central Namibia. We create models to predict the density, cover, and biomass of the main savanna vegetation forms: grass, shrubs, and trees. To calibrate remote sensing data we developed an extensive and relatively rapid field methodology and measured herbaceous and woody vegetation during both the dry and wet seasons. We compared the efficacy of the four MODIS-derived VPs in predicting vegetation field measured variables. We then compared the optimal time span of VP time series to predict ground-measured vegetation. We found that Multiyear Partial Least Square Regression (PLSR) models were superior to single year or single date models. Our results show that NDVI-based PLSR models yield robust prediction of tree density (R2 = 0.79, relative Root Mean Square Error, rRMSE = 1.9%) and tree cover (R2 = 0.78, rRMSE = 0.3%). EVI provided the best model for shrub density (R2 = 0.82) and shrub cover (R2 = 0.83), but was only marginally superior over models based on other VPs. FPAR was the best predictor of vegetation biomass of trees (R2 = 0.76), shrubs (R2 = 0.83), and grass (R2 = 0.91). Finally, we addressed an enduring challenge in the remote sensing of semiarid vegetation by examining the transferability of predictive models through space and time. Our results show that models created in the wetter part of Etosha could accurately predict trees' and shrubs' variables in the drier part of the reserve and vice versa. Moreover, our results demonstrate that models created for vegetation variables in the dry season of 2011 could be successfully applied to predict vegetation in the wet season of 2012. We conclude that extensive field data combined with multiyear time series of MODIS vegetation products can produce robust predictive models for multiple vegetation forms in the African savanna. These methods advance the monitoring of savanna vegetation dynamics and contribute to improved management and conservation of these valuable ecosystems.

Dissociation of heart rate variability and heart rate recovery in well-trained athletes.

PubMed

Lee, C Matthew; Mendoza, Albert

2012-07-01

The purpose of this investigation was to examine the relationships between aerobic fitness, volume of physical activity (PA), heart rate variability (HRV), and heart rate recovery (HRR) in a group of well-trained endurance athletes. Nineteen endurance athletes participated in this study and had aerobic capacities that placed them above the 99th percentile based on normative values (VO(2max): 67.1 ± 2 ml kg(-1) min(-1)). HRV was obtained via an EKG collected during supine rest and reported as high-frequency (HF), low-frequency (LF), and total power (TP). Natural log (ln) transformation was applied when variables violated assumptions of normality. HRR recovery was reported as the reduction in heart rate from peak exercise to the heart rate 1 min after cessation of exercise and PA was estimated from a questionnaire. HRR was significantly correlated with PA and VO(2max) (r = 0.67, P = 0.003 and 0.51, P = 0.039, respectively), but not with any index of HRV. Age was significantly correlated with lnHF (r = -0.49, P = 0.033), lnLF/lnHF (r = 0.48, P = 0.037), and normalized units (NU) of LF (r = 0.47, P = 0.042) and HF (r = -0.47, P = 0.042). Stepwise regression revealed that the strongest predictor of HRR was PA (R (2) = 0.45) and that VO(2max) did not add significant predictive value to the model. The relationship between HRV and age is evident in well-trained endurance athletes, whereas the relationship between HRV and PA/aerobic fitness is not. The maintained relationship between HRR and PA/aerobic fitness suggests that HRR may be a better marker of fitness-related differences in autonomic control in this population.

Species richness and patterns of invasion in plants, birds, and fishes in the United States

USGS Publications Warehouse

Stohlgren, Thomas J.; Barnett, David; Flather, Curtis; Fuller, Pamela L.; Peterjohn, Bruce G.; Kartesz, John; Master, Lawrence L.

2006-01-01

We quantified broad-scale patterns of species richness and species density (mean # species/km2) for native and non-indigenous plants, birds, and fishes in the continental USA and Hawaii. We hypothesized that the species density of native and non-indigenous taxa would generally decrease in northern latitudes and higher elevations following declines in potential evapotranspiration, mean temperature, and precipitation. County data on plants (n = 3004 counties) and birds (n=3074 counties), and drainage (6 HUC) data on fishes (n = 328 drainages) showed that the densities of native and non-indigenous species were strongly positively correlated for plant species (r = 0.86, P < 0.0001), bird species (r = 0.93, P<0.0001), and fish species (r = 0.41, P<0.0001). Multiple regression models showed that the densities of native plant and bird species could be strongly predicted (adj. R2 = 0.66 in both models) at county levels, but fish species densities were less predictable at drainage levels (adj. R2 = 0.31,P<0.0001). Similarly, non-indigenous plant and bird species densities were strongly predictable (adj. R2 = 0.84 and 0.91 respectively), but non-indigenous fish species density was less predictable (adj. R2 = 0.38). County level hotspots of native and non-indigenous plants, birds, and fishes were located in low elevation areas close to the coast with high precipitation and productivity (vegetation carbon). We show that (1) native species richness can be moderately well predicted with abiotic factors; (2) human populations have tended to settle in areas rich in native species; and (3) the richness and density of non-indigenous plant, bird, and fish species can be accurately predicted from biotic and abiotic factors largely because they are positively correlated to native species densities. We conclude that while humans facilitate the initial establishment, invasions of non-indigenous species, the spread and subsequent distributions of non-indigenous species may be controlled largely by environmental factors.

Rearing-environment-dependent hippocampal local field potential differences in wild-type and inositol trisphosphate receptor type 2 knockout mice.

PubMed

Tanaka, Mika; Wang, Xiaowen; Mikoshiba, Katsuhiko; Hirase, Hajime; Shinohara, Yoshiaki

2017-10-15

Mice reared in an enriched environment are demonstrated to have larger hippocampal gamma oscillations than those reared in isolation, thereby confirming previous observations in rats. To test whether astrocytic Ca 2+ surges are involved in this experience-dependent LFP pattern modulation, we used inositol trisphosphate receptor type 2 (IP 3 R2)-knockout (KO) mice, in which IP 3 /Ca 2+ signalling in astrocytes is largely diminished. We found that this experience-dependent gamma power alteration persists in the KO mice. Interestingly, hippocampal ripple events, the synchronized events critical for memory consolidation, are reduced in magnitude and frequency by both isolated rearing and IP 3 R2 deficiency. Rearing in an enriched environment (ENR) is known to enhance cognitive and memory abilities in rodents, whereas social isolation (ISO) induces depression-like behaviour. The hippocampus has been documented to undergo morphological and functional changes depending on these rearing environments. For example, rearing condition during juvenility alters CA1 stratum radiatum gamma oscillation power in rats. In the present study, hippocampal CA1 local field potentials (LFP) were recorded from bilateral CA1 in urethane-anaesthetized mice that were reared in either an ENR or ISO condition. Similar to previous findings in rats, gamma oscillation power during theta states was higher in the ENR group. Ripple events that occur during non-theta periods in the CA1 stratum pyramidale also had longer intervals in ISO mice. Because astrocytic Ca 2+ elevations play a key role in synaptic plasticity, we next tested whether these changes in LFP are also expressed in inositol trisphosphate receptor type 2 (IP 3 R2)-knockout (KO) mice, in which astrocytic Ca 2+ elevations are largely diminished. We found that the gamma power was also higher in IP 3 R2-KO-ENR mice compared to IP 3 R2-KO-ISO mice, suggesting that the rearing-environment-dependent gamma power alteration does not necessarily require the astrocytic IP 3 /Ca 2+ pathway. By contrast, ripple events showed genotype-dependent changes, as well as rearing condition-dependent changes: ISO housing and IP 3 R2 deficiency both lead to longer inter-ripple intervals. Moreover, we found that ripple magnitude in the right CA1 tended to be smaller in IP 3 R2-KO. Because IP 3 R2-KO mice have been reported to have depression phenotypes, our results suggest that ripple events and the mood of animals may be broadly correlated. © 2017 The Authors. The Journal of Physiology © 2017 The Physiological Society.

The impact of three recent coal-fired power plant closings on Pittsburgh air quality: A natural experiment.

PubMed

Russell, Marie C; Belle, Jessica H; Liu, Yang

2017-01-01

Relative to the rest of the United States, the region of southwestern Pennsylvania, including metropolitan Pittsburgh, experiences high ambient concentrations of fine particulate matter (PM 2.5 ), which is known to be associated with adverse respiratory and cardiovascular health impacts. This study evaluates whether the closing of three coal-fired power plants within the southwestern Pennsylvania region resulted in a significant decrease in PM 2.5 concentration. Both PM 2.5 data obtained from EPA ground stations in the study region and aerosol optical depth (AOD) data retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments onboard the Terra and Aqua satellites were used to investigate regional air quality from January 2011 through December 2014. The impact of the plant closings on PM 2.5 concentration and AOD was evaluated using a series of generalized additive models. The model results show that monthly fuel consumption of the Elrama plant, which closed in October of 2012, and monthly fuel consumption of both the Mitchell and Hatfield's Ferry plants, which closed in October of 2013, were significant predictors of both PM 2.5 concentration and AOD at EPA ground stations in the study region, after controlling for multiple meteorological factors and long-term, region-wide air quality improvements. The model's power to predict PM 2.5 concentration increased from an adjusted R 2 of 0.61 to 0.68 after excluding data from ground stations with higher uncertainty due to recent increases in unconventional natural gas extraction activities. After preliminary analyses of mean PM 2.5 concentration and AOD showed a downward trend following each power plant shutdown, results from a series of generalized additive models confirmed that the activity of the three plants that closed, measured by monthly fuel consumption, was highly significant in predicting both AOD and PM 2.5 at 12 EPA ground stations; further research on PM 2.5 emissions from unconventional natural gas extraction is needed. With many coal-fired power plants scheduled to close across the United States in the coming years, there is interest in the potential impact on regional PM 2.5 concentrations. In southwestern Pennsylvania, recent coal-fired power plant closings were coupled with a boom in unconventional natural gas extraction. Natural gas is currently seen as an economically viable bridge fuel between coal and renewable energy. This study provides policymakers with more information on the potential ambient concentration changes associated with coal-fired power plant closings as the nation's energy reliance shifts toward natural gas.

Impact of the Medical Faculty on Study Success in Freiburg: Results from Graduate Surveys.

PubMed

Biller, Silke; Boeker, Martin; Fabry, Götz; Giesler, Marianne

2015-01-01

Using the data from graduate surveys, this study aims to analyze which factors related to teaching and learning at the Freiburg Faculty of Medicine can influence study success. Study success and the factors influencing it have long been the subject of investigation, with study success being measured in terms of easily quantifiable indicators (final grades, student satisfaction, etc.). In recent years, it has also frequently been assessed in terms of graduate competency levels. Graduate surveys are considered suitable instruments for measuring these dimensions of study success. Data from three Freiburg graduate surveys conducted one and a half years after graduation were drawn upon for the analysis. Study success was operationalized using four indicators: results on the written section of the M2 exam, self-assessment of medical expertise and scientific expertise, and student satisfaction. Using multiple regression analyses, the predictive power was calculated for selected variables, also measured by the graduate surveys, for the different study success indicators. It was possible to identify models that contribute slightly or moderately to the prediction of study success. The score earned on the university entrance qualification demonstrated itself to be the strongest predictor for forecasting the M2 written exam: R(2) is between 0.08 and 0.22 for the three surveys. Different variables specific to degree program structure and teaching are helpful for predicting medical expertise (R(2)=0.04-0.32) and student satisfaction (R(2)=0.12-0.35). The two variables, structure and curricular sequencing of the degree program and combination of theory and practice, show themselves to be significant, sample-invariant predictors (β-weight(Structure)=0.21-0.58, β-weight(Combination)=0.27-0.56). For scientific expertise, no sample-independent predictors could be determined. Factors describing teaching hardly provide any assistance when predicting the written M2 exam score, which makes sense to the extent that teaching goes far beyond the heavily knowledge-based content of the written M2 exam. The lack of predictability for scientific expertise is most likely explained in that these have been only rarely included in the curriculum and often inexplicitly so. The variable combination of theory and practice appears to be significant for imparting medical expertise and the development of student satisfaction. The extent to which these relationships are practically relevant needs to be explored in further studies. A specific limitation is that the measurement of expertise and skill is based solely on self-assessments.

In silico prediction of microRNAs on fluoride induced sperm toxicity in mice.

PubMed

Raghunath, Azhwar; Jeyabaskar, Dhivyalakshmi; Sundarraj, Kiruthika; Panneerselvam, Lakshmikanthan; Perumal, Ekambaram

2016-12-01

Fluorosis is an endemic global problem causing male reproductive impairment. F mediates male reproductive toxicity in mice down-regulating 63 genes involved in diverse biological processes - apoptosis, cell cycle, cell signaling, chemotaxis, electron transport, glycolysis, oxidative stress, sperm capacitation and spermatogenesis. We predicted the miRNAs down-regulating these 63 genes using TargetScan, DIANA and MicroCosm. The prediction tools identified 3059 miRNAs targeting 63 genes. Of the predicted interactions, 11 miRNAs (mmu-miR-103, -107, -122, -188a, -199a-5p, -205, -340-5p, -345-3p, -452-5p, -499, -878-3p) were commonly found in the three tools utilized and seven miRNAs (miR-9-5p, miR-511-3p, miR-7b-5p, miR-30e-5p, miR-17-5p, miR-122-5p and miR-541-5p) targeting six genes (Traf3, Rock2, Rgs8, Atp1b2, Cacna2d1 and Aldoa) were already validated experimentally in mice. The miRNA-mRNA network of the predicted miRNAs with its respective targets revealed the complex interaction within a biological process leading to sperm dysfunction on exposure to F. Our findings not only suggest that the predicted miRs furnish evidence, but also have the potential to serve as non-invasive biomarkers on F-induced sperm dysfunction. Our data contribute towards elucidating the function of miRNAs in the fluoride induced infertility. miRNA molecular pathways in F intoxication will open new avenues on the use of antagomirs in recovering fertility. Copyright © 2016 Elsevier Ltd. All rights reserved.

The relationship between body temperature, heart rate, breathing rate, and rate of oxygen consumption, in the tegu lizard (Tupinambis merianae) at various levels of activity.

PubMed

Piercy, Joanna; Rogers, Kip; Reichert, Michelle; Andrade, Denis V; Abe, Augusto S; Tattersall, Glenn J; Milsom, William K

2015-12-01

The present study determined whether EEG and/or EMG recordings could be used to reliably define activity states in the Brazilian black and white tegu lizard (Tupinambis merianae) and then examined the interactive effects of temperature and activity states on strategies for matching O2 supply and demand. In a first series of experiments, the rate of oxygen consumption (VO2), breathing frequency (fR), heart rate (fH), and EEG and EMG (neck muscle) activity were measured in different sleep/wake states (sleeping, awake but quiet, alert, or moving). In general, metabolic and cardio-respiratory changes were better indictors of the transition from sleep to wake than were changes in the EEG and EMG. In a second series of experiments, the interactive effects of temperature (17, 27 and 37 °C) and activity states on fR, tidal volume (VT), the fraction of oxygen extracted from the lung per breath (FIO2-FEO2), fH, and the cardiac O2 pulse were quantified to determine the relative roles of each of these variables in accommodating changes in VO2. The increases in oxygen supply to meet temperature- and activity-induced increases in oxygen demand were produced almost exclusively by increases in fH and fR. Regression analysis showed that the effects of temperature and activity state on the relationships between fH, fR and VO2 was to extend a common relationship along a single curve, rather than separate relationships for each metabolic state. For these lizards, the predictive powers of fR and fH were maximized when the effects of changes in temperature, digestive state and activity were pooled. However, the best r(2) values obtained were 0.63 and 0.74 using fR and fH as predictors of metabolic rate, respectively.

Empirical prediction of net portal appearance of volatile fatty acids, glucose, and their secondary metabolites (beta-hydroxybutyrate, lactate) from dietary characteristics in ruminants: A meta-analysis approach.

PubMed

Loncke, C; Ortigues-Marty, I; Vernet, J; Lapierre, H; Sauvant, D; Nozière, P

2009-01-01

The current trend in energy feeding systems for ruminants toward a nutrient-based system requires dietary energy supply to be determined in terms of amount and nature of absorbed energy-yielding nutrients. The objective of this study was to establish response equations on the net portal appearance (NPA) of VFA and glucose, and their secondary metabolites beta-hydroxybutyrate (BHBA) and lactate, to changes in intake level and chemical dietary characteristics based on the Institut National de la Recherche Agronomique Feed Evaluation System for Ruminants. Meta-analyses were applied on published data compiled from the FLORA database, which pools the results on net splanchnic nutrient fluxes in multi-catheterized ruminants from international publications. For each nutrient, several prediction variables were tested. We obtained robust models for intakes up to 30 g of DM x d(-1) x kg of BW(-1) and diets containing less than 70 g of concentrate per 100 g of DM. These models were designed to predict the NPA (mmol x h(-1) x kg of BW(-1)) of total VFA based on the amount of ruminally fermented OM (RfOM) intake [adjusted R(2) (R(2)(adj)) = 0.95; residual means square errors (RMSE) = 0.24], to predict VFA profile (mol/100 mol of total VFA) based on type of RfOM intake (acetate: R(2)(adj) = 0.85, RMSE = 2.2; propionate: R(2)(adj) = 0.76, RMSE = 2.2; butyrate: R(2)(adj) = 0.76, RMSE = 1.09), and to predict the NPA (mmol x h(-1) x kg of BW(-1)) of glucose based on the starch digested in the small intestine independent of ruminant species, and while presenting no interfering factors on the residuals and individual slopes. The model predicting the NPA (mmol x h(-1) x kg of BW(-1)) of BHBA based on the amount of RfOM intake (R(2)(adj) = 0.91; RMSE = 0.036) was species-dependent, and the model predicting NPA (mmol x h(-1) x kg of BW(-1)) of lactate based on starch digested in the rumen (R(2)(adj) = 0.77; RMSE = 0.042) presented a wide dispersion. However, the NPA (mmol x h(-1) x kg of BW(-1)) of BHBA was related to the NPA of both butyrate (R(2)(adj) = 0.85; RMSE = 0.054) and acetate (R(2)(adj) = 0.85; RMSE = 0.052), and the NPA (mmol x h(-1) x kg of BW (-1)) of lactate was related to the NPA of propionate (R(2)(adj) = 0.51; RMSE = 0.096). This research showed that it is possible to accurately predict the amount and nature of absorbed nutrient fluxes based on dietary characteristics in both sheep and cattle. This work aims to quantify the consequences of digestion and portal-drained viscera metabolism on nutrient availability. These results can provide deeper insight into biological processes and help develop improved tools for dietary formulation.

Validation of finite element and boundary element methods for predicting structural vibration and radiated noise

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Wu, X. F.; Oswald, Fred B.

1992-01-01

Analytical and experimental validation of methods to predict structural vibration and radiated noise are presented. A rectangular box excited by a mechanical shaker was used as a vibrating structure. Combined finite element method (FEM) and boundary element method (BEM) models of the apparatus were used to predict the noise radiated from the box. The FEM was used to predict the vibration, and the surface vibration was used as input to the BEM to predict the sound intensity and sound power. Vibration predicted by the FEM model was validated by experimental modal analysis. Noise predicted by the BEM was validated by sound intensity measurements. Three types of results are presented for the total radiated sound power: (1) sound power predicted by the BEM modeling using vibration data measured on the surface of the box; (2) sound power predicted by the FEM/BEM model; and (3) sound power measured by a sound intensity scan. The sound power predicted from the BEM model using measured vibration data yields an excellent prediction of radiated noise. The sound power predicted by the combined FEM/BEM model also gives a good prediction of radiated noise except for a shift of the natural frequencies that are due to limitations in the FEM model.

[Role of angiotensin II receptor type 2 in predicting biochemical recurrence in the treatment of prostate cancer].

PubMed

Chibichyan, M B; Kogan, M I; Chernogubova, E A; Pavlenko, I A; Matishov, D G

2016-12-01

To identify markers for predicting aggressive forms of prostate cancer. The study retrospectively evaluated expression of angiotensin II type 2 receptors (AT2-R) in prostate needle biopsy tissue from patients with and without biochemical recurrence after combined hormone and radiation therapy. The study findings showed that low expression of AT2-R in prostate tissue was associated with a high risk of biochemical recurrence. The data on the nature of AT2-R expression in prostate tissue of prostate cancer patients may be considered as a tool for predicting biochemical recurrence after combined hormone and radiation therapy. The test has a sensitivity of 87.5% and specificity of 85.71%.

Gender and age related predictive value of walk test in heart failure: do anthropometrics matter in clinical practice?

PubMed

Frankenstein, L; Remppis, A; Graham, J; Schellberg, D; Sigg, C; Nelles, M; Katus, H A; Zugck, C

2008-07-21

The six-minute walk test (6 WT) is a valid and reliable predictor of morbidity and mortality in chronic heart failure (CHF) patients, frequently used as an endpoint or target in clinical trials. As opposed to spiroergometry, improvement of its prognostic accuracy by correction for height, weight, age and gender has not yet been attempted comprehensively despite known influences of these parameters. We recorded the 6 WT of 1035 CHF patients, attending clinic from 1995 to 2005. The 1-year prognostic value of 6 WT was calculated, alone and after correction for height, weight, BMI and/or age. Analysis was performed on the entire cohort, on males and females separately and stratified according to BMI (<25, 25-30 and >30 kg/m(2)). 6 WT weakly correlated with age (r=-0.32; p<0.0001), height (r=0.2; p<0.0001), weight (r=0.11; p<0.001), not with BMI (r=0.01; p=ns). The 6 WT was a strong predictor of 1-year mortality in both genders, both as a single and age corrected parameter. Parameters derived from correction of 6 WT for height, weight or BMI did not improve the prognostic value in univariate analysis for either gender. Comparison of the receiver operated characteristics showed no significant gain in prognostic accuracy from any derived variable, either for males or females. The six-minute walk test is a valid tool for risk prediction in both male and female CHF patients. In both genders, correcting 6 WT distance for height, weight or BMI alone, or adjusting for age, does not increase the prognostic power of this tool.

Prediction of consensus binding mode geometries for related chemical series of positive allosteric modulators of adenosine and muscarinic acetylcholine receptors.

PubMed

Sakkal, Leon A; Rajkowski, Kyle Z; Armen, Roger S

2017-06-05

Following insights from recent crystal structures of the muscarinic acetylcholine receptor, binding modes of Positive Allosteric Modulators (PAMs) were predicted under the assumption that PAMs should bind to the extracellular surface of the active state. A series of well-characterized PAMs for adenosine (A 1 R, A 2A R, A 3 R) and muscarinic acetylcholine (M 1 R, M 5 R) receptors were modeled using both rigid and flexible receptor CHARMM-based molecular docking. Studies of adenosine receptors investigated the molecular basis of the probe-dependence of PAM activity by modeling in complex with specific agonist radioligands. Consensus binding modes map common pharmacophore features of several chemical series to specific binding interactions. These models provide a rationalization of how PAM binding slows agonist radioligand dissociation kinetics. M 1 R PAMs were predicted to bind in the analogous M 2 R PAM LY2119620 binding site. The M 5 R NAM (ML-375) was predicted to bind in the PAM (ML-380) binding site with a unique induced-fit receptor conformation. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

High Altitude Affects Nocturnal Non-linear Heart Rate Variability: PATCH-HA Study

PubMed Central

Boos, Christopher J.; Bye, Kyo; Sevier, Luke; Bakker-Dyos, Josh; Woods, David R.; Sullivan, Mark; Quinlan, Tom; Mellor, Adrian

2018-01-01

Background: High altitude (HA) exposure can lead to changes in resting heart rate variability (HRV), which may be linked to acute mountain sickness (AMS) development. Compared with traditional HRV measures, non-linear HRV appears to offer incremental and prognostic data, yet its utility and relationship to AMS have been barely examined at HA. This study sought to examine this relationship at terrestrial HA. Methods: Sixteen healthy British military servicemen were studied at baseline (800 m, first night) and over eight consecutive nights, at a sleeping altitude of up to 3600 m. A disposable cardiac patch monitor was used, to record the nocturnal cardiac inter-beat interval data, over 1 h (0200–0300 h), for offline HRV assessment. Non-linear HRV measures included Sample entropy (SampEn), the short (α1, 4–12 beats) and long-term (α2, 13–64 beats) detrend fluctuation analysis slope and the correlation dimension (D2). The maximal rating of perceived exertion (RPE), during daily exercise, was assessed using the Borg 6–20 RPE scale. Results: All subjects completed the HA exposure. The average age of included subjects was 31.4 ± 8.1 years. HA led to a significant fall in SpO2 and increase in heart rate, LLS and RPE. There were no significant changes in the ECG-derived respiratory rate or in any of the time domain measures of HRV during sleep. The only notable changes in frequency domain measures of HRV were an increase in LF and fall in HFnu power at the highest altitude. Conversely, SampEn, SD1/SD2 and D2 all fell, whereas α1 and α2 increased (p < 0.05). RPE inversely correlated with SD1/SD2 (r = -0.31; p = 0.002), SampEn (r = -0.22; p = 0.03), HFnu (r = -0.27; p = 0.007) and positively correlated with LF (r = 0.24; p = 0.02), LF/HF (r = 0.24; p = 0.02), α1 (r = 0.32; p = 0.002) and α2 (r = 0.21; p = 0.04). AMS occurred in 7/16 subjects (43.8%) and was very mild in 85.7% of cases. HRV failed to predict AMS. Conclusion: Non-linear HRV is more sensitive to the effects of HA than time and frequency domain indices. HA leads to a compensatory decrease in nocturnal HRV and complexity, which is influenced by the RPE measured at the end of the previous day. HRV failed to predict AMS development. PMID:29713290

High Altitude Affects Nocturnal Non-linear Heart Rate Variability: PATCH-HA Study.

PubMed

Boos, Christopher J; Bye, Kyo; Sevier, Luke; Bakker-Dyos, Josh; Woods, David R; Sullivan, Mark; Quinlan, Tom; Mellor, Adrian

2018-01-01

Background: High altitude (HA) exposure can lead to changes in resting heart rate variability (HRV), which may be linked to acute mountain sickness (AMS) development. Compared with traditional HRV measures, non-linear HRV appears to offer incremental and prognostic data, yet its utility and relationship to AMS have been barely examined at HA. This study sought to examine this relationship at terrestrial HA. Methods: Sixteen healthy British military servicemen were studied at baseline (800 m, first night) and over eight consecutive nights, at a sleeping altitude of up to 3600 m. A disposable cardiac patch monitor was used, to record the nocturnal cardiac inter-beat interval data, over 1 h (0200-0300 h), for offline HRV assessment. Non-linear HRV measures included Sample entropy (SampEn), the short (α1, 4-12 beats) and long-term (α2, 13-64 beats) detrend fluctuation analysis slope and the correlation dimension (D2). The maximal rating of perceived exertion (RPE), during daily exercise, was assessed using the Borg 6-20 RPE scale. Results: All subjects completed the HA exposure. The average age of included subjects was 31.4 ± 8.1 years. HA led to a significant fall in SpO 2 and increase in heart rate, LLS and RPE. There were no significant changes in the ECG-derived respiratory rate or in any of the time domain measures of HRV during sleep. The only notable changes in frequency domain measures of HRV were an increase in LF and fall in HFnu power at the highest altitude. Conversely, SampEn, SD1/SD2 and D2 all fell, whereas α1 and α2 increased ( p < 0.05). RPE inversely correlated with SD1/SD2 ( r = -0.31; p = 0.002), SampEn ( r = -0.22; p = 0.03), HFnu ( r = -0.27; p = 0.007) and positively correlated with LF ( r = 0.24; p = 0.02), LF/HF ( r = 0.24; p = 0.02), α1 ( r = 0.32; p = 0.002) and α2 ( r = 0.21; p = 0.04). AMS occurred in 7/16 subjects (43.8%) and was very mild in 85.7% of cases. HRV failed to predict AMS. Conclusion: Non-linear HRV is more sensitive to the effects of HA than time and frequency domain indices. HA leads to a compensatory decrease in nocturnal HRV and complexity, which is influenced by the RPE measured at the end of the previous day. HRV failed to predict AMS development.

EDGE2D-EIRENE modelling of near SOL E r: possible impact on the H-mode power threshold

NASA Astrophysics Data System (ADS)

Chankin, A. V.; Delabie, E.; Corrigan, G.; Harting, D.; Maggi, C. F.; Meyer, H.; Contributors, JET

2017-04-01

Recent EDGE2D-EIRENE simulations of JET plasmas showed a significant difference between radial electric field (E r) profiles across the separatrix in two divertor configurations, with the outer strike point on the horizontal target (HT) and vertical target (VT) (Chankin et al 2016 Nucl. Mater. Energy, doi: 10.1016/j.nme.2016.10.004). Under conditions (input power, plasma density) where the HT plasma went into the H-mode, a large positive E r spike in the near scrape-off layer (SOL) was seen in the code output, leading to a very large E × B shear across the separatrix over a narrow region of a fraction of a cm width. No such E r feature was obtained in the code solution for the VT configuration, where the H-mode power threshold was found to be twice as high as in the HT configuration. It was hypothesised that the large E × B shear across the separatrix in the HT configuration could be responsible for the turbulence suppression leading to an earlier (at lower input power) L-H transition compared to the VT configuration. In the present work these ideas are extended to cover some other experimental observations on the H-mode power threshold variation with parameters which typically are not included in the multi-machine H-mode power threshold scalings, namely: ion mass dependence (isotope H-D-T exchange), dependence on the ion ∇B drift direction, and dependence on the wall material composition (ITER-like wall versus carbon wall in JET). In all these cases EDGE2D-EIRENE modelling shows larger positive E r spikes in the near SOL under conditions where the H-mode power threshold is lower, at least in the HT configuration.

Robonaut 2 on the International Space Station: Status Update and Preparations for IVA Mobility

NASA Technical Reports Server (NTRS)

Ahlstrom, Thomas D.; Diftler, Myron E.; Berka, Reginald B.; Badger, Julia M.; Yayathi, Sandeep; Curtis, Andrew W.; Joyce, Charles A.

2013-01-01

Robotics engineers, ground controllers and International Space Station (ISS) crew have been running successful experiments using Robonaut 2 (R2) on-board the ISS for more than a year. This humanoid upper body robot continues to expand its list of achievements and its capabilities to safely demonstrate maintenance and servicing tasks while working alongside human crewmembers. The next phase of the ISS R2 project will transition from a stationary Intra Vehicular Activity (IVA) upper body using a power/data umbilical, to an IVA mobile system with legs for repositioning, a battery backpack power supply, and wireless communications. These upgrades will enable the R2 team to evaluate hardware performance and to develop additional control algorithms and control verification techniques with R2 inside the ISS in preparation for the Extra Vehicular Activity (EVA) phase of R2 operations. As R2 becomes more capable in assisting with maintenance tasks, with minimal supervision, including repositioning itself to different work sites, the ISS crew will be burdened with fewer maintenance chores, leaving them more time to conduct other activities. R2's developers at the Johnson Space Center (JSC) are preparing the R2 IVA mobility hardware and software upgrades for delivery to the ISS in late 2013. This paper summarizes R2 ISS achievements to date, briefly describes the R2 IVA mobility upgrades, and discusses the R2 IVA mobility objectives and plans.

"The next Big Five Inventory (BFI-2): Developing and assessing a hierarchical model with 15 facets to enhance bandwidth, fidelity, and predictive power": Correction to Soto and John (2016).

PubMed

2017-07-01

Reports an error in "The Next Big Five Inventory (BFI-2): Developing and Assessing a Hierarchical Model With 15 Facets to Enhance Bandwidth, Fidelity, and Predictive Power" by Christopher J. Soto and Oliver P. John ( Journal of Personality and Social Psychology , Advanced Online Publication, Apr 7, 2016, np). In the article, all citations to McCrae and Costa (2008), except for the instance in which it appears in the first paragraph of the introduction, should instead appear as McCrae and Costa (2010). The complete citation should read as follows: McCrae, R. R., & Costa, P. T. (2010). NEO Inventories professional manual. Lutz, FL: Psychological Assessment Resources. The attribution to the BFI-2 items that appears in the Table 6 note should read as follows: BFI-2 items adapted from "Conceptualization, Development, and Initial Validation of the Big Five Inventory-2," by C. J. Soto and O. P. John, 2015, Paper presented at the biennial meeting of the Association for Research in Personality. Copyright 2015 by Oliver P. John and Christopher J. Soto. The complete citation in the References list should appear as follows: Soto, C. J., & John, O. P. (2015, June). Conceptualization, development, and initial validation of the Big Five Inventory-2. Paper presented at the biennial meeting of the Association for Research in Personality, St. Louis, MO. Available from http://www.colby.edu/psych/personality-lab/ All versions of this article have been corrected. (The following abstract of the original article appeared in record 2016-17156-001.) Three studies were conducted to develop and validate the Big Five Inventory-2 (BFI-2), a major revision of the Big Five Inventory (BFI). Study 1 specified a hierarchical model of personality structure with 15 facet traits nested within the Big Five domains, and developed a preliminary item pool to measure this structure. Study 2 used conceptual and empirical criteria to construct the BFI-2 domain and facet scales from the preliminary item pool. Study 3 used data from 2 validation samples to evaluate the BFI-2's measurement properties and substantive relations with self-reported and peer-reported criteria. The results of these studies indicate that the BFI-2 is a reliable and valid personality measure, and an important advance over the original BFI. Specifically, the BFI-2 introduces a robust hierarchical structure, controls for individual differences in acquiescent responding, and provides greater bandwidth, fidelity, and predictive power than the original BFI, while still retaining the original measure's conceptual focus, brevity, and ease of understanding. The BFI-2 therefore offers valuable new opportunities for research examining the structure, assessment, development, and life outcomes of personality traits. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Prior sprint cycling did not enhance training adaptation, but resting salivary hormones were related to workout power and strength.

PubMed

Crewther, Blair T; Lowe, Tim; Weatherby, Robert P; Gill, Nicholas

2009-04-01

This study examined the effect of cycle sprints as a potentiating stimulus for power and strength adaptation in semi-elite athletes. Eighteen rugby players were assigned into training groups that completed either a 40-s cycle sprint (T(SPRINT)) or rested (T(CONTROL)) before each workout (n = 6-8) of a 4-week programme. Squat jump (SJ) peak power (PP) and mean power (MP), and box squat (BS) one repetition maximum (1RM) strength were assessed every workout. Saliva was collected across each workout and assayed for testosterone (Sal-T) and cortisol (Sal-C). The T(SPRINT) and T(CONTROL) groups both showed significant improvements in SJ PP (8.2 +/- 2.9 vs. 11.9 +/- 3.6%), SJ MP (11.8 +/- 2.6 vs. 18.6 +/- 4.8%) and BS 1RM (20.5 +/- 2.6 vs. 23.2 +/- 1.3%), respectively. However, there were no group differences in training adaptation, workout performance or the workout hormonal responses. As a combined group (all players), significant relationships were demonstrated between resting Sal-T and/or Sal-C concentrations and absolute SJ power (r = 0.20-0.30) and BS strength (r = 0.36-0.44) across all workouts. For individual players, the respective relationships with SJ power (r = 0.22-0.42) and BS strength (r = 0.41-0.49) were, on average, found to be stronger. In conclusion, leg workouts performed with or without prior cycle sprints can produce similar power and strength improvements in semi-elite rugby players. Resting salivary hormone concentrations appear important for workout performance, especially for individuals, thereby potentially moderating training adaptation.

Neural Network Prediction of ICU Length of Stay Following Cardiac Surgery Based on Pre-Incision Variables

PubMed Central

Pothula, Venu M.; Yuan, Stanley C.; Maerz, David A.; Montes, Lucresia; Oleszkiewicz, Stephen M.; Yusupov, Albert; Perline, Richard

2015-01-01

Background Advanced predictive analytical techniques are being increasingly applied to clinical risk assessment. This study compared a neural network model to several other models in predicting the length of stay (LOS) in the cardiac surgical intensive care unit (ICU) based on pre-incision patient characteristics. Methods Thirty six variables collected from 185 cardiac surgical patients were analyzed for contribution to ICU LOS. The Automatic Linear Modeling (ALM) module of IBM-SPSS software identified 8 factors with statistically significant associations with ICU LOS; these factors were also analyzed with the Artificial Neural Network (ANN) module of the same software. The weighted contributions of each factor (“trained” data) were then applied to data for a “new” patient to predict ICU LOS for that individual. Results Factors identified in the ALM model were: use of an intra-aortic balloon pump; O2 delivery index; age; use of positive cardiac inotropic agents; hematocrit; serum creatinine ≥ 1.3 mg/deciliter; gender; arterial pCO2. The r2 value for ALM prediction of ICU LOS in the initial (training) model was 0.356, p <0.0001. Cross validation in prediction of a “new” patient yielded r2 = 0.200, p <0.0001. The same 8 factors analyzed with ANN yielded a training prediction r2 of 0.535 (p <0.0001) and a cross validation prediction r2 of 0.410, p <0.0001. Two additional predictive algorithms were studied, but they had lower prediction accuracies. Our validated neural network model identified the upper quartile of ICU LOS with an odds ratio of 9.8(p <0.0001). Conclusions ANN demonstrated a 2-fold greater accuracy than ALM in prediction of observed ICU LOS. This greater accuracy would be presumed to result from the capacity of ANN to capture nonlinear effects and higher order interactions. Predictive modeling may be of value in early anticipation of risks of post-operative morbidity and utilization of ICU facilities. PMID:26710254

Portfolio Purchasing Decision for Mobile Power Equipment of B2C E-Commerce Export Retailer Based on CVaR

NASA Astrophysics Data System (ADS)

Yanchun, Wan; Qiucen, Chen

2017-11-01

Purchasing is an important part of export e-commerce of B2C, which plays an important role on risk and cost control in supply management. From the perspective of risk control, the paper construct a CVaR model for portfolio purchase. We select a heavy sales mobile power equipment from a typical B2C e-commerce export retailer as study sample. This study optimizes the purchasing strategy of this type of mobile power equipment. The research has some reference for similar enterprises in purchasing portfolio decision.

The Influence of Oropalatal Dimensions on the Measurement of Tongue Strength.

PubMed

Pitts, Laura L; Stierwalt, Julie A G; Hageman, Carlin F; LaPointe, Leonard L

2017-12-01

Tongue strength is routinely evaluated in clinical swallowing evaluations since lingual weakness is an established contributor to dysphagia. Tongue strength may be clinically quantified by the maximum isometric tongue pressure (MIP) generated by the tongue against the palate; however, wide ranges in normal performance remain to be fully explained. Although orthodontic theory has long suggested a relation between lingual function and oral cavity dimensions, little attention has been given to the potential influence of oral and palatal structure(s) on healthy variance in MIP generation. Therefore, anterior and posterior tongue strength measures and oropalatal dimensions were obtained across 147 healthy adults (aged 18-88 years). Age was confirmed as a significant, independent predictor explaining approximately 10.2% of the variance in anterior tongue strength, but not a significant predictor of posterior tongue strength. However, oropalatal dimensions predicted anterior tongue strength with over three times the predictive power of age alone (p < .001). Significant models for anterior tongue strength (R 2  = .457) and posterior tongue strength (R 2  = .283) included a combination of demographic predictors (i.e., age and/or gender) and oropalatal dimensions. Palatal width, estimated tongue volume, and gender were significant predictors of posterior tongue strength (p < .001). Therefore, oropalatal dimensions may warrant consideration when accurately differentiating between pathological lingual weakness and healthy individual difference.

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.

Synergistic Use of Nighttime Satellite Data, Electric Utility Infrastructure, and Ambient Population to Improve Power Outage Detections in Urban Areas

NASA Technical Reports Server (NTRS)

Cole, Tony A.; Wanik, David W.; Molthan, Andrew L.; Roman, Miguel O.; Griffin, Robert E.

2017-01-01

Natural and anthropogenic hazards are frequently responsible for disaster events, leading to damaged physical infrastructure, which can result in loss of electrical power for affected locations. Remotely-sensed, nighttime satellite imagery from the Suomi National Polar-orbiting Partnership (Suomi-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) can monitor power outages in disaster-affected areas through the identification of missing city lights. When combined with locally-relevant geospatial information, these observations can be used to estimate power outages, defined as geographic locations requiring manual intervention to restore power. In this study, we produced a power outage product based on Suomi-NPP VIIRS DNB observations to estimate power outages following Hurricane Sandy in 2012. This product, combined with known power outage data and ambient population estimates, was then used to predict power outages in a layered, feedforward neural network model. We believe this is the first attempt to synergistically combine such data sources to quantitatively estimate power outages. The VIIRS DNB power outage product was able to identify initial loss of light following Hurricane Sandy, as well as the gradual restoration of electrical power. The neural network model predicted power outages with reasonable spatial accuracy, achieving Pearson coefficients (r) between 0.48 and 0.58 across all folds. Our results show promise for producing a continental United States (CONUS)- or global-scale power outage monitoring network using satellite imagery and locally-relevant geospatial data.

Development and Commercialization of the Lunar Solar Power System

NASA Astrophysics Data System (ADS)

Criswell, D. R.

2002-01-01

The proposed Lunar Solar Power (LSP) System consists of pairs of power bases located on opposite limbs of the Moon as seen from Earth. The power bases collect the solar energy and convert it to beams of microwaves. The microwaves are delivered directly to moonward-facing receivers on Earth or indirectly through relay satellites in orbit about Earth (1, 2, 3, 4). The LSP System may be the only reasonable method for establishing sustainable global energy prosperity within two generations. Commercial power prosperity requires at least 2 kWe/person. For ten billion people this implies 20 TWe and 2,000 TWe-y of electric energy or ~6,000 TWt-y of thermal energy per century (5, 6, 7, 8). A brief overview is presented of a reference LSP System that supplies 20 TWe by 2050. The engineering scales and the cost and benefits of this system are described. In order to provide low cost commercial electric energy, the power bases are made primarily of local lunar materials by machines, facilities, and people deployed from Earth (1, 2, 3). In addition, lunar production machinery can be made primarily from lunar materials. Advantages of this approach, versus the reference LSP System, are discussed. Full-scale production of a LSP System will certainly be proceeded by terrestrial and lunar operation of the production machinery and a small-scale demonstration of the operational system (1). Using government funds to establishing a permanent lunar base and the associated transportation system would significantly reduce the upfront cost for the demonstration of a commercial LSP System (2). The government program would provide a legal framework for commercial development of the LSP System (3, 9). The LSP System offers the opportunity to establish a materials industry on the Moon that can produce a growing mass and variety of goods and enable new services of benefit on the Earth and the Moon (10). New priorities are suggested for civilian space programs that can accelerate the establishment of a demonstration LSP System and growing commercialization of the Moon and cis-lunar space. 1. Criswell, David R. (2001) Lunar Solar Power System: Industrial Research, Development, and Demonstration, Session 1.2.2: Hydroelectricity, Nuclear Energy and New Renewables, 18th World Energy Congress. [http://www.wec.co.ukin the Congress Papers, Discussion Sessions] 2. Criswell, D. R. and Waldron, R. D. 1993. International Lunar Base and Lunar-based Power System to Supply Earth with Electric Power, Acta Astronautica, Vol. 29, No. 6, pp. 469-480. Pergamon Press Ltd. 3. NASA TASK FORCE. 1989 (July) Report of NASA Lunar Energy Enterprise Case Study Task Force. NASA Technical Memo 101652. 163pp. NASA Headquarters, Office of Exploration (Code Z), Washington, D.C. 20546. 4. Moore, T. (2000, Spring) "Renewed interest in space solar power," EPRI Journal, pp. 6-17. 5. World Energy Council (2000) Energy for Tomorrow's World - Acting Now!, 175pp., Atalink Projects Ltd, London. 6. Criswell, David R. (2002) Energy Prosperity within the 21st Century and Beyond: Options and the Unique Roles of the Sun and the Moon. Chapter 9: Innovative Solutions To CO2 Stabilization, R. Watts (editor), Cambridge Un. Press 7. Strong, Maurice (2001) Where on Earth are We Going?, (See p. 351-352), 419pp., Random House (forward by Kofi Annan) 8. Criswell, D. R. and Thompson, R. G. (1996), "Data envelopment analysis of space and terrestrial-based large scale commercial power systems for Earth: A prototype analysis of their relative economic advantages," Solar Energy, 56, No. 1: 119-131. 9 ILEWG (1997), Proc. 2nd International Lunar Workshop, organized by: International Lunar Exploration Working Group, Inst. Space and Astronautical Science, and National Space Development Agency of Japan, Kyoto, Japan, (October 14 - 17), 89pp. 10. Criswell, D.R. 2000 (October) Commercial power for Earth and lunar industrial development, 7pp., 51st Congress of the International Astronautical Federation (IAF). (Rio de Janeiro, Brazil). Paper #IAA-00-IAA.13.2.06.

Relationship between alcohol-related expectancies and anterior brain functioning in young men at risk for developing alcoholism.

PubMed

Deckel, A W; Hesselbrock, V; Bauer, L

1995-04-01

This experiment examined the relationship between anterior brain functioning and alcohol-related expectancies. Ninety-one young men at risk for developing alcoholism were assessed on the Alcohol Expectancy Questionnaire (AEQ) and administered neuropsychological and EEG tests. Three of the scales on the AEQ, including the "Enhanced Sexual Functioning" scale, the "Increased Social Assertiveness" scale, and items from the "Global/Positive Change scale," were used, because each of these scales has been found to discriminate alcohol-based expectancies adequately by at least two separate sets of investigators. Regression analysis found that anterior neuropsychological tests (including the Wisconsin Card Sorting test, the Porteus Maze test, the Controlled Oral Word Fluency test, and the Luria-Nebraska motor functioning tests) were predictive of the AEQ scale scores on regression analysis. One of the AEQ scales, "Enhanced Sexual Functioning," was also predicted by WAIS-R-Verbal scales, whereas the "Global/Positive" AEQ scale was predicted by the WAIS-R Performance scales. Regression analysis using EEG power as predictors found that left versus right hemisphere "difference" scores obtained from frontal EEG leads were predictive of the three AEQ scales. Conversely, parietal EEG power did not significantly predict any of the expectancy scales. It is concluded that anterior brain any of the expectancy scales. It is concluded that anterior brain functioning is associated with alcohol-related expectancies. These findings suggest that alcohol-related expectancy may be, in part, biologically determined by frontal/prefrontal systems, and that dysfunctioning in these systems may serve as a risk factor for the development of alcohol-related behaviors.

Added value of multiple versus single sessions of repetitive transcranial magnetic stimulation in predicting motor cortex stimulation efficacy for refractory neuropathic pain.

PubMed

Pommier, Benjamin; Quesada, Charles; Fauchon, Camille; Nuti, Christophe; Vassal, François; Peyron, Roland

2018-05-18

OBJECTIVE Selection criteria for offering patients motor cortex stimulation (MCS) for refractory neuropathic pain are a critical topic of research. A single session of repetitive transcranial magnetic stimulation (rTMS) has been advocated for selecting MCS candidates, but it has a low negative predictive value. Here the authors investigated whether multiple rTMS sessions would more accurately predict MCS efficacy. METHODS Patients included in this longitudinal study could access MCS after at least four rTMS sessions performed 3-4 weeks apart. The positive (PPV) and negative (NPV) predictive values of the four rTMS sessions and the correlation between the analgesic effects of the two treatments were assessed. RESULTS Twelve MCS patients underwent an average of 15.9 rTMS sessions prior to surgery; nine of the patients were rTMS responders. Postoperative follow-up was 57.8 ± 15.6 months (mean ± standard deviation). Mean percentage of pain relief (%R) was 21% and 40% after the first and fourth rTMS sessions, respectively. The corresponding mean durations of pain relief were respectively 2.4 and 12.9 days. A cumulative effect of the rTMS sessions was observed on both %R and duration of pain relief (p < 0.01). The %R value obtained with MCS was 35% after 6 months and 43% at the last follow-up. Both the PPV and NPV of rTMS were 100% after the fourth rTMS session (p = 0.0045). A significant correlation was found between %R or duration of pain relief after the fourth rTMS session and %R at the last MCS follow-up (R 2 = 0.83, p = 0.0003). CONCLUSIONS Four rTMS sessions predicted MCS efficacy better than a single session in neuropathic pain patients. Taking into account the cumulative effects of rTMS, the authors found a high-level correlation between the analgesic effects of rTMS and MCS.

Effect of various forms of physical training on the autonomic nervous system activity in patients with acute myocardial infarction.

PubMed

Daniłowicz-Szymanowicz, Ludmiła; Figura-Chmielewska, Monika; Ratkowski, Wojciech; Raczak, Grzegorz

2013-01-01

A shift in the dynamic autonomic nervous system (ANS) balance towards sympathetic activity in patients with acute myocardial infarction (AMI) predisposes them to life-threatening ventricular arrhythmias. Improvement of unfavourable changes in ANS can be expected in such patients as a result of physical training. A beneficial shift in ANS balance towards parasympathetic activity could be confirmed by demonstrating increased baroreceptor reflex sensitivity (BRS) as well as favourable changes in heart rate variability (HRV) parameters. To analyse the effect of different forms of physical training on ANS activity in patients with AMI after hospital discharge. The study included 38 patients with AMI (aged 59 ± 8 years) subjected to 2-month exercise training. Group 1 (n = 19)underwent 3-week supervised in-hospital cardiac rehabilitation followed by 5-week home-based training, and Group 2 (n = 19) underwent 8-week home-based training. BRS and HRV were determined based on a 10-min recording of systolic arterial pressure and the cardiac cycle. Measurements were performed one day before discharge (R1) and after 2 months of training (R2). A significant increase in the mean values of TP (total power), HF (high frequency power), rMSSD (square root of the mean of the squared differences between successive R-R intervals), and pNN50 (proportion of differences between successive R-R intervals that are greater than 50 ms) was observed in the overall study group, along with trends for higher SDNN (standard deviation of the mean of sinus rhythm R-R intervals) and HFnu (normalised HF power), and for lower LFnu (normalised LF power). Additionally, a significant increase in BRS (from 2.2 ± 0.6 to 5.1 ± 2.2 ms/mm Hg, p = 0.01) was found in patients with baseline BRS ≤ 3 ms/mm Hg. A significant increase in rMSSD, pNN50, HF and HFnu, as well as a decrease in LFnu and LF/HF (LF to HF ratio) was observed in Group 1. In contrast, a significant increase in BRS was noted in Group 2. Various forms of 2-month physical training led to a favourable shift in autonomic balance towards parasympathetic activity. Our findings suggest a clinically important effect of physical activity in patients after AMI.

Predicting recovery of voluntary upper extremity movement in subacute stroke patients with severe upper extremity paresis.

PubMed

Koh, Chia-Lin; Pan, Shin-Liang; Jeng, Jiann-Shing; Chen, Bang-Bin; Wang, Yen-Ho; Hsueh, I-Ping; Hsieh, Ching-Lin

2015-01-01

Prediction of voluntary upper extremity (UE) movement recovery is largely unknown in patients with little voluntary UE movement at admission. The present study aimed to investigate (1) the extent and variation of voluntary UE movement recovery, and (2) the best predictive model of the recovery of voluntary UE movement by clinical variables in patients with severe UE paresis. Prospective cohort study. 140 (out of 590) stroke patients with severe UE paresis completed all assessments. Voluntary UE movement was assessed using the UE subscale of the Stroke Rehabilitation Assessment of Movement (STREAM-UE). Two outcome measures, STREAM-UE scores at discharge (DC(STREAM-UE)) and changes between admission and discharge (Δ(STREAM-UE)), were investigated to represent the final states and improvement of the recovery of voluntary UE movement. Stepwise regression analyses were used to investigate 19 clinical variables and to find the best predictive models of the two outcome measures. The participants showed wide variation in both DC(STREAM-UE) and Δ(STREAM-UE). 3.6% of the participants almost fully recovered at discharge (DC(STREAM-UE) > 15). A large improvement (Δ(STREAM-UE) >= 10) occurred in 16.4% of the participants, while 32.9% of the participants did not have any improvement. The four predictors for the DC(STREAM-UE) (R(2) = 35.0%) were 'baseline STREAM-UE score', 'hemorrhagic stroke', 'baseline National Institutes of Health Stroke Scale (NIHSS) score', and 'cortical lesion excluding primary motor cortex'. The three predictors for the Δ(STREAM-UE) (R(2) = 22.0%) were 'hemorrhagic stroke', 'baseline NIHSS score', and 'cortical lesion excluding primary motor cortex'. Recovery of voluntary UE movement varied widely in patients with severe UE paresis after stroke. The predictive power of clinical variables was poor. Both results indicate the complex nature of voluntary UE movement recovery in patients with severe UE paresis after stroke.

75 FR 61779 - R.E. Ginna Nuclear Power Plant, LLC; R.E. Ginna Nuclear Power Plant Environmental Assessment and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-06

... 2003-18, Supplement 2, ``Use of Nuclear Energy Institute (NEI) 99-01, Methodology for Development of... radiological emergency. Environmental Impacts of the Proposed Action The NRC has completed its environmental... environmental impacts are [[Page 61780

Power Grid Data Analysis with R and Hadoop

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

Hafen, Ryan P.; Gibson, Tara D.; Kleese van Dam, Kerstin

This book chapter presents an approach to analysis of large-scale time-series sensor information based on our experience with power grid data. We use the R-Hadoop Integrated Programming Environment (RHIPE) to analyze a 2TB data set and present code and results for this analysis.

Localization in a random XY model with long-range interactions: Intermediate case between single-particle and many-body problems

NASA Astrophysics Data System (ADS)

Burin, Alexander L.

2015-09-01

Many-body localization in an XY model with a long-range interaction is investigated. We show that in the regime of a high strength of disordering compared to the interaction an off-resonant flip-flop spin-spin interaction (hopping) generates the effective Ising interactions of spins in the third order of perturbation theory in a hopping. The combination of hopping and induced Ising interactions for the power-law distance dependent hopping V (R ) ∝R-α always leads to the localization breakdown in a thermodynamic limit of an infinite system at α <3 d /2 where d is a system dimension. The delocalization takes place due to the induced Ising interactions U (R ) ∝R-2 α of "extended" resonant pairs. This prediction is consistent with the numerical finite size scaling in one-dimensional systems. Many-body localization in an XY model is more stable with respect to the long-range interaction compared to a many-body problem with similar Ising and Heisenberg interactions requiring α ≥2 d which makes the practical implementations of this model more attractive for quantum information applications. The full summary of dimension constraints and localization threshold size dependencies for many-body localization in the case of combined Ising and hopping interactions is obtained using this and previous work and it is the subject for the future experimental verification using cold atomic systems.

In vivo ultrasound and biometric measurements predict the empty body chemical composition in Nellore cattle.

PubMed

Castilhos, A M; Francisco, C L; Branco, R H; Bonilha, S F M; Mercadante, M E Z; Meirelles, P R L; Pariz, C M; Jorge, A M

2018-05-04

Evaluation of the body chemical composition of beef cattle can only be measured postmortem and those data cannot be used in real production scenarios to adjust nutritional plans. The objective of this study was to develop multiple linear regression equations from in vivo measurements, such as ultrasound parameters [backfat thickness (uBFT, mm), rump fat thickness (uRF, mm), and ribeye area (uLMA, cm2)], shrunk body weight (SBW, kg), age (AG, d), hip height (HH, m), as well as from postmortem measurements (composition of the 9th to 11th rib section) to predict the empty body and carcass chemical composition for Nellore cattle. Thirty-three young bulls were used (339 ± 36.15 kg and 448 ± 17.78 d for initial weight and age, respectively). Empty body chemical composition (protein, fat, water, and ash in kg) was obtained by combining noncarcass and carcass components. Data were analyzed using the PROC REG procedure of SAS software. Mallows' Cp values were close to the ideal value of number of independent variables in the prediction equations plus one. Equations to predict chemical components of both empty body and carcass using in vivo measurements presented higher R2 values than those determined by postmortem measurements. Chemical composition of the empty body using in vivo measurements was predicted with R2 > 0.73. Equations to predict chemical composition of the carcass from in vivo measurements showed R2 lower (R2< 0.68) than observed for empty body, except for the water (R2 = 0.84). The independent variables SBW, uRF, and AG were sufficient to predict the fat, water, energy components of the empty body, whereas for estimation of protein content the uRF, HH, and SBW were satisfactory. For the calculation of the ash, the SBW variable in the equation was sufficient. Chemical compounds from components of the empty body of Nellore cattle can be calculated by the following equations: protein (kg) = 47.92 + 0.18 × SBW - 1.46 × uRF - 30.72 × HH (R2 = 0.94, RMSPE = 1.79); fat (kg) = 11.33 + 0.16 × SBW + 2.09 × uRF - 0.06 × AG (R2 = 0.74, RMSPE = 4.18); water (kg) = - 34.00 + 0.55 × SBW + 0.10 × AG - 2.34 × uRF (R2 = 0.96, RMSPE = 5.47). In conclusion, the coefficients of determination (for determining the chemical composition of the empty body) of the equations derived from in vivo measures were higher than those of the equations obtained from rib section measurements taken postmortem, and better than coefficients of determination of the equations to predict the chemical composition of the carcass.

Regression-based reduced-order models to predict transient thermal output for enhanced geothermal systems

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

Mudunuru, Maruti Kumar; Karra, Satish; Harp, Dylan Robert

Reduced-order modeling is a promising approach, as many phenomena can be described by a few parameters/mechanisms. An advantage and attractive aspect of a reduced-order model is that it is computational inexpensive to evaluate when compared to running a high-fidelity numerical simulation. A reduced-order model takes couple of seconds to run on a laptop while a high-fidelity simulation may take couple of hours to run on a high-performance computing cluster. The goal of this paper is to assess the utility of regression-based reduced-order models (ROMs) developed from high-fidelity numerical simulations for predicting transient thermal power output for an enhanced geothermal reservoirmore » while explicitly accounting for uncertainties in the subsurface system and site-specific details. Numerical simulations are performed based on equally spaced values in the specified range of model parameters. Key sensitive parameters are then identified from these simulations, which are fracture zone permeability, well/skin factor, bottom hole pressure, and injection flow rate. We found the fracture zone permeability to be the most sensitive parameter. The fracture zone permeability along with time, are used to build regression-based ROMs for the thermal power output. The ROMs are trained and validated using detailed physics-based numerical simulations. Finally, predictions from the ROMs are then compared with field data. We propose three different ROMs with different levels of model parsimony, each describing key and essential features of the power production curves. The coefficients in the proposed regression-based ROMs are developed by minimizing a non-linear least-squares misfit function using the Levenberg–Marquardt algorithm. The misfit function is based on the difference between numerical simulation data and reduced-order model. ROM-1 is constructed based on polynomials up to fourth order. ROM-1 is able to accurately reproduce the power output of numerical simulations for low values of permeabilities and certain features of the field-scale data. ROM-2 is a model with more analytical functions consisting of polynomials up to order eight, exponential functions and smooth approximations of Heaviside functions, and accurately describes the field-data. At higher permeabilities, ROM-2 reproduces numerical results better than ROM-1, however, there is a considerable deviation from numerical results at low fracture zone permeabilities. ROM-3 consists of polynomials up to order ten, and is developed by taking the best aspects of ROM-1 and ROM-2. ROM-1 is relatively parsimonious than ROM-2 and ROM-3, while ROM-2 overfits the data. ROM-3 on the other hand, provides a middle ground for model parsimony. Based on R 2-values for training, validation, and prediction data sets we found that ROM-3 is better model than ROM-2 and ROM-1. For predicting thermal drawdown in EGS applications, where high fracture zone permeabilities (typically greater than 10 –15 m 2) are desired, ROM-2 and ROM-3 outperform ROM-1. As per computational time, all the ROMs are 10 4 times faster when compared to running a high-fidelity numerical simulation. In conclusion, this makes the proposed regression-based ROMs attractive for real-time EGS applications because they are fast and provide reasonably good predictions for thermal power output.« less

Regression-based reduced-order models to predict transient thermal output for enhanced geothermal systems

DOE PAGES

Mudunuru, Maruti Kumar; Karra, Satish; Harp, Dylan Robert; ...

2017-07-10

Reduced-order modeling is a promising approach, as many phenomena can be described by a few parameters/mechanisms. An advantage and attractive aspect of a reduced-order model is that it is computational inexpensive to evaluate when compared to running a high-fidelity numerical simulation. A reduced-order model takes couple of seconds to run on a laptop while a high-fidelity simulation may take couple of hours to run on a high-performance computing cluster. The goal of this paper is to assess the utility of regression-based reduced-order models (ROMs) developed from high-fidelity numerical simulations for predicting transient thermal power output for an enhanced geothermal reservoirmore » while explicitly accounting for uncertainties in the subsurface system and site-specific details. Numerical simulations are performed based on equally spaced values in the specified range of model parameters. Key sensitive parameters are then identified from these simulations, which are fracture zone permeability, well/skin factor, bottom hole pressure, and injection flow rate. We found the fracture zone permeability to be the most sensitive parameter. The fracture zone permeability along with time, are used to build regression-based ROMs for the thermal power output. The ROMs are trained and validated using detailed physics-based numerical simulations. Finally, predictions from the ROMs are then compared with field data. We propose three different ROMs with different levels of model parsimony, each describing key and essential features of the power production curves. The coefficients in the proposed regression-based ROMs are developed by minimizing a non-linear least-squares misfit function using the Levenberg–Marquardt algorithm. The misfit function is based on the difference between numerical simulation data and reduced-order model. ROM-1 is constructed based on polynomials up to fourth order. ROM-1 is able to accurately reproduce the power output of numerical simulations for low values of permeabilities and certain features of the field-scale data. ROM-2 is a model with more analytical functions consisting of polynomials up to order eight, exponential functions and smooth approximations of Heaviside functions, and accurately describes the field-data. At higher permeabilities, ROM-2 reproduces numerical results better than ROM-1, however, there is a considerable deviation from numerical results at low fracture zone permeabilities. ROM-3 consists of polynomials up to order ten, and is developed by taking the best aspects of ROM-1 and ROM-2. ROM-1 is relatively parsimonious than ROM-2 and ROM-3, while ROM-2 overfits the data. ROM-3 on the other hand, provides a middle ground for model parsimony. Based on R 2-values for training, validation, and prediction data sets we found that ROM-3 is better model than ROM-2 and ROM-1. For predicting thermal drawdown in EGS applications, where high fracture zone permeabilities (typically greater than 10 –15 m 2) are desired, ROM-2 and ROM-3 outperform ROM-1. As per computational time, all the ROMs are 10 4 times faster when compared to running a high-fidelity numerical simulation. In conclusion, this makes the proposed regression-based ROMs attractive for real-time EGS applications because they are fast and provide reasonably good predictions for thermal power output.« less

Retention modelling of polychlorinated biphenyls in comprehensive two-dimensional gas chromatography.

PubMed

D'Archivio, Angelo Antonio; Incani, Angela; Ruggieri, Fabrizio

2011-01-01

In this paper, we use a quantitative structure-retention relationship (QSRR) method to predict the retention times of polychlorinated biphenyls (PCBs) in comprehensive two-dimensional gas chromatography (GC×GC). We analyse the GC×GC retention data taken from the literature by comparing predictive capability of different regression methods. The various models are generated using 70 out of 209 PCB congeners in the calibration stage, while their predictive performance is evaluated on the remaining 139 compounds. The two-dimensional chromatogram is initially estimated by separately modelling retention times of PCBs in the first and in the second column ((1) t (R) and (2) t (R), respectively). In particular, multilinear regression (MLR) combined with genetic algorithm (GA) variable selection is performed to extract two small subsets of predictors for (1) t (R) and (2) t (R) from a large set of theoretical molecular descriptors provided by the popular software Dragon, which after removal of highly correlated or almost constant variables consists of 237 structure-related quantities. Based on GA-MLR analysis, a four-dimensional and a five-dimensional relationship modelling (1) t (R) and (2) t (R), respectively, are identified. Single-response partial least square (PLS-1) regression is alternatively applied to independently model (1) t (R) and (2) t (R) without the need for preliminary GA variable selection. Further, we explore the possibility of predicting the two-dimensional chromatogram of PCBs in a single calibration procedure by using a two-response PLS (PLS-2) model or a feed-forward artificial neural network (ANN) with two output neurons. In the first case, regression is carried out on the full set of 237 descriptors, while the variables previously selected by GA-MLR are initially considered as ANN inputs and subjected to a sensitivity analysis to remove the redundant ones. Results show PLS-1 regression exhibits a noticeably better descriptive and predictive performance than the other investigated approaches. The observed values of determination coefficients for (1) t (R) and (2) t (R) in calibration (0.9999 and 0.9993, respectively) and prediction (0.9987 and 0.9793, respectively) provided by PLS-1 demonstrate that GC×GC behaviour of PCBs is properly modelled. In particular, the predicted two-dimensional GC×GC chromatogram of 139 PCBs not involved in the calibration stage closely resembles the experimental one. Based on the above lines of evidence, the proposed approach ensures accurate simulation of the whole GC×GC chromatogram of PCBs using experimental determination of only 1/3 retention data of representative congeners.

Power output measurement during treadmill cycling.

PubMed

Coleman, D A; Wiles, J D; Davison, R C R; Smith, M F; Swaine, I L

2007-06-01

The study aim was to consider the use of a motorised treadmill as a cycling ergometry system by assessing predicted and recorded power output values during treadmill cycling. Fourteen male cyclists completed repeated cycling trials on a motorised treadmill whilst riding their own bicycle fitted with a mobile ergometer. The speed, gradient and loading via an external pulley system were recorded during 20-s constant speed trials and used to estimate power output with an assumption about the contribution of rolling resistance. These values were then compared with mobile ergometer measurements. To assess the reliability of measured power output values, four repeated trials were conducted on each cyclist. During level cycling, the recorded power output was 257.2 +/- 99.3 W compared to the predicted power output of 258.2 +/- 99.9 W (p > 0.05). For graded cycling, there was no significant difference between measured and predicted power output, 268.8 +/- 109.8 W vs. 270.1 +/- 111.7 W, p > 0.05, SEE 1.2 %. The coefficient of variation for mobile ergometer power output measurements during repeated trials ranged from 1.5 % (95 % CI 1.2 - 2.0 %) to 1.8 % (95 % CI 1.5 - 2.4 %). These results indicate that treadmill cycling can be used as an ergometry system to assess power output in cyclists with acceptable accuracy.

Hermes 3

NASA Astrophysics Data System (ADS)

Hasti, D. E.; Ramirez, J. J.; Prestwich, K. R.; Sanford, T. W. L.; Hamil, R. A.

Hermes 3 is a major new gamma-ray simulator that is part of the Simulation Technology Laboratory Project. This accelerator will significantly improve the capability to evaluate the effects of gamma-ray radiation from nuclear weapons on weapons subsystems. This accelerator will be designed to produce 10(5)R, 5 x 10 to the 12th power R/S and 2 x 10 to the 20th power R/S(2) over a 500 sq cm area. The radiation dose will vary less than a factor of two over this area and less than a factor of four throughout a volume found by extending this surface 15 cm further from the gamma-ray converter. The minimum dose in this volume will be greater than or equal to 5 x 10 to the 4th power R. The accelerator will be designed with sufficient reliability and short enough turn-around time to produce more than 600 radiation pulses per year. In Hermes 3 the peak power in the beam is to be increased from 1.2 TW of Hermes 2 to 16 TW. Two techniques for achieving these high powers have been successfully developed. The first technique is a high current linear induction accelerator with several parallel beams. Experiments to evaluate this concept were done on the MABE accelerator. The second concept uses induction cavities and a magnetically insulated transmission line (MITL) to form a multi-terawatt voltage adder.

Estimation of influential points in any data set from coefficient of determination and its leave-one-out cross-validated counterpart.

PubMed

Tóth, Gergely; Bodai, Zsolt; Héberger, Károly

2013-10-01

Coefficient of determination (R (2)) and its leave-one-out cross-validated analogue (denoted by Q (2) or R cv (2) ) are the most frequantly published values to characterize the predictive performance of models. In this article we use R (2) and Q (2) in a reversed aspect to determine uncommon points, i.e. influential points in any data sets. The term (1 - Q (2))/(1 - R (2)) corresponds to the ratio of predictive residual sum of squares and the residual sum of squares. The ratio correlates to the number of influential points in experimental and random data sets. We propose an (approximate) F test on (1 - Q (2))/(1 - R (2)) term to quickly pre-estimate the presence of influential points in training sets of models. The test is founded upon the routinely calculated Q (2) and R (2) values and warns the model builders to verify the training set, to perform influence analysis or even to change to robust modeling.

Sodium intake prediction with health promotion model constructs in rural hypertensive patients.

PubMed

Kamran, Aziz; Sharifirad, Gholamreza; Shafaeei, Yousef; Azadbakht, Leila

2015-01-01

Hypertension is the most common cause of cardiovascular disease, and the growing epidemic is a serious warning to pay more attention to this disease. The aims of this study were to examine the relationships between the health promotion model (HPM) constructs and sodium intake, and to determine the predictive power of the HPM constructs as the possible mediators of sodium intake in rural Iranian hypertensive patients. This cross-sectional study was conducted on 671 hypertensive patients in Ardabil, Iran in 2013. The data were obtained during a 25-40 min face-to-face conversation by validated and reliable instruments. The nutritional data were assessed with Nutritionist version 4 (N4) software. Descriptive statistics, Spearman's correlations were calculated using SPSS Statistics version 18.0. Structural equation modeling was conducted using AMOS version 18. Sodium intake was negatively correlated with perceived benefits (r = -0.707; P < 0.01), perceived self-efficacy (r = -0.719; P < 0.01), situational influences (r = -0.590; P < 0.01), interpersonal influences (r = -0.637; P < 0.01), commitment to action (r = -0.605; P < 0.01), affects related behavior (r = -0.499; P < 0.01), and positively associated with the perceived barriers score (r = 0.563; P < 0.01). The structural equation modeling showed that the model explained 63.0% of the variation in sodium intake. HPM constructs were significantly associated with sodium intake and dietary perceptions based on HPM constructs can predict acceptable rate of the variation of sodium intake. Therefore, we suggest using this model constructs to improve the effectiveness of nutritional interventions.

Simple, empirical approach to predict neutron capture cross sections from nuclear masses

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

Couture, Aaron Joseph; Casten, Richard F.; Cakirli, R. B.

Here, neutron capture cross sections are essential to understanding the astrophysical s and r processes, the modeling of nuclear reactor design and performance, and for a wide variety of nuclear forensics applications. Often, cross sections are needed for nuclei where experimental measurements are difficult. Enormous effort, over many decades, has gone into attempting to develop sophisticated statistical reaction models to predict these cross sections. Such work has met with some success but is often unable to reproduce measured cross sections to better than 40%, and has limited predictive power, with predictions from different models rapidly differing by an order ofmore » magnitude a few nucleons from the last measurement.« less

Simple, empirical approach to predict neutron capture cross sections from nuclear masses

DOE PAGES

Couture, Aaron Joseph; Casten, Richard F.; Cakirli, R. B.

2017-12-20

Here, neutron capture cross sections are essential to understanding the astrophysical s and r processes, the modeling of nuclear reactor design and performance, and for a wide variety of nuclear forensics applications. Often, cross sections are needed for nuclei where experimental measurements are difficult. Enormous effort, over many decades, has gone into attempting to develop sophisticated statistical reaction models to predict these cross sections. Such work has met with some success but is often unable to reproduce measured cross sections to better than 40%, and has limited predictive power, with predictions from different models rapidly differing by an order ofmore » magnitude a few nucleons from the last measurement.« less

Coalescence preference in dense packing of bubbles

NASA Astrophysics Data System (ADS)

Kim, Yeseul; Gim, Bopil; Gim, Bopil; Weon, Byung Mook

2015-11-01

Coalescence preference is the tendency that a merged bubble from the contact of two original bubbles (parent) tends to be near to the bigger parent. Here, we show that the coalescence preference can be blocked by densely packing of neighbor bubbles. We use high-speed high-resolution X-ray microscopy to clearly visualize individual coalescence phenomenon which occurs in micro scale seconds and inside dense packing of microbubbles with a local packing fraction of ~40%. Previous theory and experimental evidence predict a power of -5 between the relative coalescence position and the parent size. However, our new observation for coalescence preference in densely packed microbubbles shows a different power of -2. We believe that this result may be important to understand coalescence dynamics in dense packing of soft matter. This work (NRF-2013R1A22A04008115) was supported by Mid-career Researcher Program through NRF grant funded by the MEST and also was supported by Ministry of Science, ICT and Future Planning (2009-0082580) and by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry and Education, Science and Technology (NRF-2012R1A6A3A04039257).

Water soluble polysaccharides from Spirulina platensis: extraction and in vitro anti-cancer activity.

PubMed

Kurd, Forouzan; Samavati, Vahid

2015-03-01

Polysaccharides from Spirulina platensis algae (SP) were extracted by ultrasound-assisted extraction procedure. The optimal conditions for ultrasonic extraction of SP were determined by response surface methodology. The four parameters were, extraction time (X1), extraction temperature (X2), ultrasonic power (X3) and the ratio of water to raw material (X4), respectively. The experimental data obtained were fitted to a second-order polynomial equation. The optimum conditions were extraction time of 25 min, extraction temperature 85°C, ultrasonic power 90 W and ratio of water to raw material 20 mL/g. Under these optimal conditions, the experimental yield was 13.583±0.51%, well matched with the predicted models with the coefficients of determination (R2) of 0.9971. Then, we demonstrated that SP polysaccharides had strong scavenging activities in vitro on DPPH and hydroxyl radicals. Overall, SP may have potential applications in the medical and food industries. Copyright © 2015 Elsevier B.V. All rights reserved.

Comprehensive analysis of the simplest curvaton model

NASA Astrophysics Data System (ADS)

Byrnes, Christian T.; Cortês, Marina; Liddle, Andrew R.

2014-07-01

We carry out a comprehensive analysis of the simplest curvaton model, which is based on two noninteracting massive fields. Our analysis encompasses cases where the inflaton and curvaton both contribute to observable perturbations, and where the curvaton itself drives a second period of inflation. We consider both power spectrum and non-Gaussianity observables, and focus on presenting constraints in model parameter space. The fully curvaton-dominated regime is in some tension with observational data, while an admixture of inflaton-generated perturbations improves the fit. The inflating curvaton regime mimics the predictions of Nflation. Some parts of parameter space permitted by power spectrum data are excluded by non-Gaussianity constraints. The recent BICEP2 results [P. A. R. Ade et al. (BICEP2 Collaboration), Phys. Rev. Lett. 112, 241101 (2014)], if confirmed as of predominantly primordial origin, require that the inflaton perturbations provide a significant fraction of the total perturbation, ruling out the usual curvaton scenario in which the inflaton perturbations are negligible, though not the admixture regime where both inflaton and curvaton contribute to the spectrum.

Secondary structure prediction for complete rDNA sequences (18S, 5.8S, and 28S rDNA) of Demodex folliculorum, and comparison of divergent domains structures across Acari.

PubMed

Zhao, Ya-E; Wang, Zheng-Hang; Xu, Yang; Wu, Li-Ping; Hu, Li

2013-10-01

According to base pairing, the rRNA folds into corresponding secondary structures, which contain additional phylogenetic information. On the basis of sequencing for complete rDNA sequences (18S, ITS1, 5.8S, ITS2 and 28S rDNA) of Demodex, we predicted the secondary structure of the complete rDNA sequence (18S, 5.8S, and 28S rDNA) of Demodex folliculorum, which was in concordance with that of the main arthropod lineages in past studies. And together with the sequence data from GenBank, we also predicted the secondary structures of divergent domains in SSU rRNA of 51 species and in LSU rRNA of 43 species from four superfamilies in Acari (Cheyletoidea, Tetranychoidea, Analgoidea and Ixodoidea). The multiple alignment among the four superfamilies in Acari showed that, insertions from Tetranychoidea SSU rRNA formed two newly proposed helixes, and helix c3-2b of LSU rRNA was absent in Demodex (Cheyletoidea) taxa. Generally speaking, LSU rRNA presented more remarkable differences than SSU rRNA did, mainly in D2, D3, D5, D7a, D7b, D8 and D10. Copyright © 2013 Elsevier Inc. All rights reserved.

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

Mori, Taro; Kohri, Kazunori; White, Jonathan, E-mail: moritaro@post.kek.jp, E-mail: kohri@post.kek.jp, E-mail: jwhite@post.kek.jp

We consider inflation in the system containing a Ricci scalar squared term and a canonical scalar field with quadratic mass term. In the Einstein frame this model takes the form of a two-field inflation model with a curved field space, and under the slow-roll approximation contains four free parameters corresponding to the masses of the two fields and their initial positions. We investigate how the inflationary dynamics and predictions for the primordial curvature perturbation depend on these four parameters. Our analysis is based on the δ N formalism, which allows us to determine predictions for the non-Gaussianity of the curvaturemore » perturbation as well as for quantities relating to its power spectrum. Depending on the choice of parameters, we find predictions that range from those of R {sup 2} inflation to those of quadratic chaotic inflation, with the non-Gaussianity of the curvature perturbation always remaining small. Using our results we are able to put constraints on the masses of the two fields.« less

Accelerating 21st Century Economic Growth by Implementation of the Lunar Solar Power System

NASA Astrophysics Data System (ADS)

Criswell, D. R.

2002-01-01

The World Energy Council (1) makes this declaration. "Given this dramatically uneven distribution and the limited evidence of improvement in economic growth in many developing countries, WEC at the 17th World Congress in Houston in September 1998 concluded that the number one priority in sustainable energy development today for all decision-makers in all countries is to extend access to commercial energy services to the people who do not now have it and to those who will come into the world in the next two decades, largely in developing countries, without such access." By ~2050 the global systems should supply 10 billion people approximately 6.7 kilowatts of thermal power per person or 61,360 kWt-h/y-person of energy. The economic equivalent is ~2 - 3 kWe of electric power per person. The energy must be environmentally clean. The energy must be sufficiently low in cost that the 2 billion poorest people, who now make 1,000 /y-person, can be provided with the new power. A survey of twenty-five options for providing adequate commercial electric power, including solar power satellites in orbit about Earth, concludes that only the Lunar Solar Power System can meet the WEC challenge (2, 3, 4, 5). Maurice Strong is the former CEO of Ontario Hydro and organizer of the 1992 Rio Environmental Summit. Quoting Strong - "I have checked it (LSP System) out with a number of experts, all of whom confirmed that the idea, which has been mooted for some time, may now be ripe to carry forward. --- The project would deliver net new energy to the Earth that is independent of the biosphere, would produce no CO2 or other polluting emissions and have minimal environmental impact compared with other energy sources." (6). Electric energy provided by the LSP System can accelerate terrestrial economic growth in several ways. A cost of less than 1 cent per kilowatt electric hour seems achievable. This allows poor nations to buy adequate energy. Increasing per capita use of electric power is associated with better human health and longer life. This increases the economic value of human capital in developing nations (7). The power can be abundant and clean. This reduces the environmental cost of commercial power and greatly reduces the economic uncertainties associated with using the power. The net new power enables creation of a greater range of goods from common materials and the recycling of products without depletion of other terrestrial resources (8). Rectennas can enable dual use of land and reduce the total land area devoted to the production and delivery of commercial power. All these factors work together to accelerate net new economic growth on Earth. 1. World Energy Council (2000) Energy for Tomorrow's World - Acting Now!, 175pp., Atalink Projects Ltd, London. 2. Criswell, D. R. (2001) Characteristics of commercial power systems to support a prosperous global economy, IAF-01- R.1.03, 7PP., Toulouse, France. 3. Criswell, David R. (2001) Lunar Solar Power System: Industrial Research, Development, and Demonstration, Session 1.2.2: Hydroelectricity, Nuclear Energy and New Renewables, 18th World Energy Congress. [http://www.wec.co.uk] 4. Criswell, David R. (2002) Energy Prosperity within the 21st Century and Beyond: Options and the Unique Roles of the Sun and the Moon. Chapter 9: Innovative Solutions To CO2 Stabilization, R. Watts (editor), Cambridge Un. Press 5. National Research Council (2001) Laying the Foundation for Space Solar Power: An assessment of NASA's Space Solar Power Investment Strategy, 80pp., National Academy Press. 6. Strong, Marice (2001) Where on Earth are We Going?, (See p. 351-352), 419pp., Random House (forward by Kofi Annan) 7. Criswell, D. R. (2000) Human wealth and evolving requirements on large-scale commercial power systems, IAF-00- R.1.03, 6pp., (Rio de Janeiro). 8. Criswell, D. R. (1994) Net growth in the two-planet economy, IAA-94-IAA.8.1.704, 10pp.

Strength, power, and muscular endurance exercise and elite rowing ergometer performance.

PubMed

Lawton, Trent W; Cronin, John B; McGuigan, Michael R

2013-07-01

Knowledge of the relationship between weight room exercises and various rowing performance measures is limited; this information would prove useful for sport-specific assessment of individual needs and exercise prescription. The purpose of this study was to establish strength, power, and muscular endurance exercises for weight room training, which are strong determinants of success in specific performance measures used to assess elite rowers. Nineteen heavyweight elite males determined their repetition maximum (RM) loads for exercises using a Concept 2 DYNO [5, 30, 60 and 120RM leg pressing and seated arm pulling (in Joules)] and free weights [1RM power clean (in kilograms) and 6RM bench pull (in kilograms and watts)]. Rowing performance measures included a 7-stage blood lactate response ergometer test (aerobic condition), time trials (500, 2000, and 5000 m), a peak stroke power test, and a 60-minute distance trial. Pearson correlation moments (r ≥ 0.7) and stepwise multiple linear regression calculations (R ≥ 50%) were used to establish strong common variances between weight room exercises and rowing ergometer performance (p ≤ 0.05). Weight room exercises were strong predictors of 2000-m, 500-m time (in seconds), and peak stroke power performance measures only. Bench pull power (in watts) and 1RM power clean (in kilograms) were the best 2-factor predictors of peak stroke power (R = 73%; standard error of the estimates [SEE] = 59.6 W) and 500 m (R = 70%; SEE = 1.75 seconds); while 5RM leg pressing (in Joules) and either 6RM bench pull (kg) or 60RM seated arm pulling (in Joules) the best predictors of 2000 m (R = 59%; SEE = 6.3 seconds and R = 57%; SEE = 6.4 seconds, respectively). Recommended exercises for weight room training include a 1RM power clean, 6RM bench pull, 5RM leg press, and 60RM seated arm pulling.

Circulating microRNA signature in non-alcoholic fatty liver disease: from serum non-coding RNAs to liver histology and disease pathogenesis.

PubMed

Pirola, Carlos J; Fernández Gianotti, Tomas; Castaño, Gustavo O; Mallardi, Pablo; San Martino, Julio; Mora Gonzalez Lopez Ledesma, María; Flichman, Diego; Mirshahi, Faridodin; Sanyal, Arun J; Sookoian, Silvia

2015-05-01

We used a screening strategy of global serum microRNA (miRNA) profiling, followed by a second stage of independent replication and exploration of liver expression of selected miRNAs to study: (1) the circulating miRNA signature associated with non-alcoholic fatty liver disease (NAFLD) progression and predictive power, (2) the role of miRNAs in disease biology and (3) the association between circulating miRNAs and features of the metabolic syndrome. The study used a case-control design and included patients with NAFLD proven through biopsy and healthy controls. Among 84 circulating miRNAs analysed, miR-122, miR-192, miR-19a and miR-19b, miR-125b, and miR-375 were upregulated >2-fold (p<0.05) either in simple steatosis (SS) or non-alcoholic steatohepatitis (NASH). The most dramatic and significant fold changes were observed in the serum levels of miR-122 (7.2-fold change in NASH vs controls and 3.1-fold change in NASH vs SS) and miR-192 (4.4-fold change in NASH vs controls); these results were replicated in the validation set. The majority of serum miR-122 circulate in argonaute2-free forms. Circulating miR-19a/b and miR-125b were correlated with biomarkers of atherosclerosis. Liver miR-122 expression was 10-fold (p<0.03) downregulated in NASH compared with SS and was preferentially expressed at the edge of lipid-laden hepatocytes. In vitro exploration showed that overexpression of miR-122 enhances alanine aminotransferase activity. miR-122 plays a role of physiological significance in the biology of NAFLD; circulating miRNAs mirror the histological and molecular events occurring in the liver. NAFLD has a distinguishing circulating miRNA profile associated with a global dysmetabolic disease state and cardiovascular risk. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Predicting trace organic compound attenuation by ozone oxidation: Development of indicator and surrogate models.

PubMed

Park, Minkyu; Anumol, Tarun; Daniels, Kevin D; Wu, Shimin; Ziska, Austin D; Snyder, Shane A

2017-08-01

Ozone oxidation has been demonstrated to be an effective treatment process for the attenuation of trace organic compounds (TOrCs); however, predicting TOrC attenuation by ozone processes is challenging in wastewaters. Since ozone is rapidly consumed, determining the exposure times of ozone and hydroxyl radical proves to be difficult. As direct potable reuse schemes continue to gain traction, there is an increasing need for the development of real-time monitoring strategies for TOrC abatement in ozone oxidation processes. Hence, this study is primarily aimed at developing indicator and surrogate models for the prediction of TOrC attenuation by ozone oxidation. To this end, the second-order kinetic equations with a second-phase R ct value (ratio of hydroxyl radical exposure to molecular ozone exposure) were used to calculate comparative kinetics of TOrC attenuation and the reduction of indicator and spectroscopic surrogate parameters, including UV absorbance at 254 nm (UVA 254 ) and total fluorescence (TF). The developed indicator model using meprobamate as an indicator compound and the surrogate models with UVA 254 and TF exhibited good predictive power for the attenuation of 13 kinetically distinct TOrCs in five filtered and unfiltered wastewater effluents (R 2 values > 0.8). This study is intended to help provide a guideline for the implementation of indicator/surrogate models for real-time monitoring of TOrC abatement with ozone processes and integrate them into a regulatory framework in water reuse. Copyright © 2017 Elsevier Ltd. All rights reserved.

Length of stay of stroke rehabilitation inpatients: prediction through the functional independence measure.

PubMed

Franchignoni, F; Tesio, L; Martino, M T; Benevolo, E; Castagna, M

1998-01-01

A model for prediction of length of stay (LOS, in days) of stroke rehabilitation inpatients was developed, based on patients' age (years) and function at admission (scored on the Functional Independence Measure, FIMSM). One hundred and twenty-nine cases, consecutively admitted to three free-standing rehabilitation centres in Italy, were analyzed. A multiple linear regression using forward stepwise selection procedure was adopted. Median admission and discharge scores were: 57 and 75 for the total FIM score, 29 and 48 for the 13-item motor FIM subscore, 29 and 30 for the 5-item cognitive FIM subscore (potential range: 18-126, 13-91, 5-35, respectively). Median LOS was 44 days (interquartile range 30-62). The logLOS predictive model included three FIM items ("toilet transfer", TTr; "social interaction"; "expression") and patient's age (R2 = 0.48). TTr alone explained 31.3% of the variance of logLOS. These results are consistent with previous American studies, showing that FIM scores at admission are strong predictors of patients' LOS, with the transfer items having the greatest predictive power.

A reference equation for maximal aerobic power for treadmill and cycle ergometer exercise testing: Analysis from the FRIEND registry.

PubMed

de Souza E Silva, Christina G; Kaminsky, Leonard A; Arena, Ross; Christle, Jeffrey W; Araújo, Claudio Gil S; Lima, Ricardo M; Ashley, Euan A; Myers, Jonathan

2018-05-01

Background Maximal oxygen uptake (VO 2 max) is a powerful predictor of health outcomes. Valid and portable reference values are integral to interpreting measured VO 2 max; however, available reference standards lack validation and are specific to exercise mode. This study was undertaken to develop and validate a single equation for normal standards for VO 2 max for the treadmill or cycle ergometer in men and women. Methods Healthy individuals ( N = 10,881; 67.8% men, 20-85 years) who performed a maximal cardiopulmonary exercise test on either a treadmill or a cycle ergometer were studied. Of these, 7617 and 3264 individuals were randomly selected for development and validation of the equation, respectively. A Brazilian sample (1619 individuals) constituted a second validation cohort. The prediction equation was determined using multiple regression analysis, and comparisons were made with the widely-used Wasserman and European equations. Results Age, sex, weight, height and exercise mode were significant predictors of VO 2 max. The regression equation was: VO 2 max (ml kg -1  min -1 ) = 45.2 - 0.35*Age - 10.9*Sex (male = 1; female = 2) - 0.15*Weight (pounds) + 0.68*Height (inches) - 0.46*Exercise Mode (treadmill = 1; bike = 2) ( R = 0.79, R 2  = 0.62, standard error of the estimate = 6.6 ml kg -1  min -1 ). Percentage predicted VO 2 max for the US and Brazilian validation cohorts were 102.8% and 95.8%, respectively. The new equation performed better than traditional equations, particularly among women and individuals ≥60 years old. Conclusion A combined equation was developed for normal standards for VO 2 max for different exercise modes derived from a US national registry. The equation provided a lower average error between measured and predicted VO 2 max than traditional equations even when applied to an independent cohort. Additional studies are needed to determine its portability.

Can body mass index predict percent body fat and changes in percent body fat with weight loss in bariatric surgery patients?

PubMed

Carey, Daniel G; Raymond, Robert L

2008-07-01

The primary objective of this study was to assess the validity of body mass index (BMI) in predicting percent body fat and changes in percent body fat with weight loss in bariatric surgery patients. Twenty-two bariatric patients (17 female, five male) began the study designed to include 12 months of testing, including data collection within 1 week presurgery and 1 month, 3 months, 6 months, and 1 year postsurgery. Five female subjects were lost to the study between 6 months and 12 months postsurgery, resulting in 17 subjects (12 female, five male) completing the 12 months of testing. Variables measured in the study included height, weight, percent fat (% fat) by hydrostatic weighing, lean mass, fat mass, and basal metabolic rate. Regression analyses predicting % fat from BMI yielded the following results: presurgery r = 0.173, p = 0.479, standard error of estimate (SEE) = 3.86; 1 month r = 0.468, p = 0.043, SEE = 4.70; 3 months r = 0.553, p = 0.014, SEE = 6.2; 6 months r = 0.611, p = 0.005, SEE = 5.88; 12 months r = 0.596, p = 0.007, SEE = 7.13. Regression analyses predicting change in % fat from change in BMI produced the following results: presurgery to 1 month r = -0.134, p = 0.583, SEE = 2.44%; 1-3 months r = 0.265, p = 0.272, SEE = 2.36%; 3-6 months r = 0.206, p = 0.398, SEE = 3.75%; 6-12 months r = 0.784, p = 0.000, SEE = 3.20. Although some analyses resulted in significant correlation coefficients (p < 0.05), the relatively large SEE values would preclude the use of BMI in predicting % fat or change in % fat with weight loss in bariatric surgery patients.

Brain Natriuretic Hormone Predicts Stress Induced Alterations in Diastolic Function

PubMed Central

Choksy, Pratik; Davis, Harry C.; Januzzi, James; Thayer, Julian; Harshfield, Gregory; Robinson, Vincent JB; Kapuku, Gaston K.

2015-01-01

Background Mental stress (MS) reduces diastolic function (DF) and may lead to congestive heart failure with preserved systolic function. Whether brain natriuretic hormone (BNP) mediates the relationship of MS with DF is unknown. Method and Results 160 individuals aged 30 to 50 years underwent 2 hour protocol of 40 minutes rest, videogame stressor and recovery. Hemodynamics, pro-BNP samples and DF indices were obtained throughout the protocol. Separate regression analyses were conducted using rest and stress E/A, E’ and E/E’ as dependent variables. Predictor variables were entered into the stepwise regression models in a hierarchical fashion. At the first level age, sex, race, height, BMI, pro-BNP, and LVM were permitted to enter the models. The second level consisted of SBP, DBP and HR. The final level contained cross-product terms of race by SBP, DBP and HR. E/A ratio was lower during stress compared to rest, and recovery (p<0.01). Resting E/A ratio was predicted by a regression model of age (−.31), pro-BNP (.16), HR (−.40) and DBP (−.23) with an R2 = .33. Stress E/A ratio was predicted by age (−.24), pro-BNP (.08), HR (−.38), and SBP (−.21), total R2 = .22. Resting E’ model consisted of age (−.22), pro-BNP (.26), DBP (−.27) and LVM (−.15) with an R2 = .29. Stress E’ was predicted by age (−.18), pro-BNP (.35) and LVM (−.18) with an R2 = .18. Resting E/E’ was predicted by race (.17, B>W) and DBP (.24) with an R2 = .10. Stress E/E’ consisted of pro-BNP (−.36), height (−.26) and HR (−.21) with R2 = .15. Conclusion pro-BNP predicts both resting and stress DF suggesting that lower BNP during MS may be a maker of diastolic dysfunction in apparently healthy individuals. PMID:24841419

Modeling aboveground biomass of Tamarix ramosissima in the Arkansas River Basin of Southeastern Colorado, USA

USGS Publications Warehouse

Evangelista, P.; Kumar, S.; Stohlgren, T.J.; Crall, A.W.; Newman, G.J.

2007-01-01

Predictive models of aboveground biomass of nonnative Tamarix ramosissima of various sizes were developed using destructive sampling techniques on 50 individuals and four 100-m2 plots. Each sample was measured for average height (m) of stems and canopy area (m2) prior to cutting, drying, and weighing. Five competing regression models (P < 0.05) were developed to estimate aboveground biomass of T. ramosissima using average height and/or canopy area measurements and were evaluated using Akaike's Information Criterion corrected for small sample size (AICc). Our best model (AICc = -148.69, ??AICc = 0) successfully predicted T. ramosissima aboveground biomass (R2 = 0.97) and used average height and canopy area as predictors. Our 2nd-best model, using the same predictors, was also successful in predicting aboveground biomass (R2 = 0.97, AICc = -131.71, ??AICc = 16.98). A 3rd model demonstrated high correlation between only aboveground biomass and canopy area (R2 = 0.95), while 2 additional models found high correlations between aboveground biomass and average height measurements only (R2 = 0.90 and 0.70, respectively). These models illustrate how simple field measurements, such as height and canopy area, can be used in allometric relationships to accurately predict aboveground biomass of T. ramosissima. Although a correction factor may be necessary for predictions at larger scales, the models presented will prove useful for many research and management initiatives.

High Confinement Mode and Edge Localized Mode Characteristics in a Near-Unity Aspect Ratio Tokamak.

PubMed

Thome, K E; Bongard, M W; Barr, J L; Bodner, G M; Burke, M G; Fonck, R J; Kriete, D M; Perry, J M; Schlossberg, D J

2016-04-29

Tokamak experiments at near-unity aspect ratio A≲1.2 offer new insights into the self-organized H-mode plasma confinement regime. In contrast to conventional A∼3 plasmas, the L-H power threshold P_{LH} is ∼15× higher than scaling predictions, and it is insensitive to magnetic topology, consistent with modeling. Edge localized mode (ELM) instabilities shift to lower toroidal mode numbers as A decreases. These ultralow-A operations enable heretofore inaccessible J_{edge}(R,t) measurements through an ELM that show a complex multimodal collapse and the ejection of a current-carrying filament.

High confinement mode and edge localized mode characteristics in a near-unity aspect ratio tokamak

DOE PAGES

Thome, Kathreen E.; Bongard, Michael W.; Barr, Jayson L.; ...

2016-04-27

Tokamak experiments at near-unity aspect ratio A ≲ 1.2 offer new insights into the self-organized H-mode plasma confinement regime. In contrast to conventional A ~ 3 plasmas, the L–H power threshold P LH is ~15× higher than scaling predictions, and it is insensitive to magnetic topology, consistent with modeling. Edge localized mode (ELM) instabilities shift to lower toroidal mode numbers as A decreases. Furthermore, these ultralow-A operations enable heretofore inaccessible J edge(R,t) measurements through an ELM that show a complex multimodal collapse and the ejection of a current-carrying filament.

Triple Photoionization of Neon and Argon Near Threshold

NASA Astrophysics Data System (ADS)

Bluett, Jaques B.; Lukić, Dragan; Sellin, Ivan A.; Whitfield, Scott B.; Wehlitz, Ralf

2003-05-01

The threshold behavior of the triple ionization cross-section of neon and argon was investigated using monochromatized synchrotron radiation and ion time-of-flight spectrometry. The Ne^3+ and Ar^3+ cross-sections are found to follow the Wannier power law(G.H. Wannier, Phys. Rev. 90), 817 (1953). consistent with a Wannier exponent of 2.162 predicted by theory. This is also consistent with the findings of Samson and Angel(J.A.R. Samson and G.C. Angel, Phys. Lett. 61), 1584 (1988). for the case of Ne. In the case of argon we find a much shorter range of validity than for neon.

[Predictors of fighting spirit or helplessness/hopelessness in people with cancer].

PubMed

Oh, Pok-Ja; Lee, Yeon-Joo

2008-04-01

This study was done to identify predictors of the fighting spirit or helplessness/hopelessness in the patients' mental adjustment to cancer. Cancer patients' characteristics like performance status, metastasis and duration of diagnosis with demographic factors, spiritual support and social support were used as predictors of a fighting spirit or helplessness/hopelessness. A total of 124 ambulatory cancer patients completed the Mental Adjustment to Cancer (MAC) scale and responded in a structured instrument about their characteristics, spiritual and social support. The results of multiple regression analysis revealed that confidence in the supporter (R(2)=.114, p=.000), duration of cancer diagnosis (R(2)=.041, p=.000) and faith (R(2)=.030, p=.000) were predictive of a fighting spirit (R(2)=.185, p=.000); whereas, education (R(2)=.074, p=.001), performance status (R(2)=.055, p=.000), satisfaction with social support (R(2)=.046, p=.000), and metastasis (R(2)=.037, p=.000) were predictive of helplessness/hopelessness (R(2)=.202, p=.000). Social support, spiritual support and disease related factors like metastasis, performance status, and duration of cancer diagnosis need to be considered in a psychosocial nursing intervention for a fighting spirit or helplessness/hopelessness.

Randomised controlled trial and economic analysis of an internet-based weight management programme: POWeR+ (Positive Online Weight Reduction).

PubMed Central

Little, Paul; Stuart, Beth; Hobbs, Fd Richard; Kelly, Jo; Smith, Emily R; Bradbury, Katherine J; Hughes, Stephanie; Smith, Peter Wf; Moore, Michael V; Lean, Mike Ej; Margetts, Barrie M; Byrne, Christopher D; Griffin, Simon; Davoudianfar, Mina; Hooper, Julie; Yao, Guiqing; Zhu, Shihua; Raftery, James; Yardley, Lucy

2017-01-01

BACKGROUND Behavioural counselling with intensive follow-up for obesity is effective, but in resource-constrained primary care settings briefer approaches are needed. OBJECTIVES To estimate the clinical effectiveness and cost-effectiveness of an internet-based behavioural intervention with regular face-to-face or remote support in primary care, compared with brief advice. DESIGN Individually randomised three-arm parallel trial with health economic evaluation and nested qualitative interviews. SETTING Primary care general practices in the UK. PARTICIPANTS Patients with a body mass index of ≥ 30 kg/m(2) (or ≥ 28 kg/m(2) with risk factors) identified from general practice records, recruited by postal invitation. INTERVENTIONS Positive Online Weight Reduction (POWeR+) is a 24-session, web-based weight management intervention completed over 6 months. Following online registration, the website randomly allocated participants using computer-generated random numbers to (1) the control intervention (n = 279), which had previously been demonstrated to be clinically effective (brief web-based information that minimised pressure to cut down foods, instead encouraging swaps to healthier choices and increasing fruit and vegetables, plus 6-monthly nurse weighing); (2) POWeR+F (n = 269), POWeR+ supplemented by face-to-face nurse support (up to seven contacts); or (3) POWeR+R (n = 270), POWeR+ supplemented by remote nurse support (up to five e-mails or brief telephone calls). MAIN OUTCOME MEASURES The primary outcome was a modelled estimate of average weight reduction over 12 months, assessed blind to group where possible, using multiple imputation for missing data. The secondary outcome was the number of participants maintaining a 5% weight reduction at 12 months. RESULTS A total of 818 eligible individuals were randomised using computer-generated random numbers. Weight change, averaged over 12 months, was documented in 666 out of 818 participants (81%; control, n = 227; POWeR+F, n = 221; POWeR+R, n = 218). The control group maintained nearly 3 kg of weight loss per person (mean weight per person: baseline, 104.4 kg; 6 months, 101.9 kg; 12 months, 101.7 kg). Compared with the control group, the estimated additional weight reduction with POWeR+F was 1.5 kg [95% confidence interval (CI) 0.6 to 2.4 kg; p = 0.001] and with POWeR+R was 1.3 kg (95% CI 0.34 to 2.2 kg; p = 0.007). By 12 months the mean weight loss was not statistically significantly different between groups, but 20.8% of control participants, 29.2% of POWeR+F participants (risk ratio 1.56, 95% CI 0.96 to 2.51; p = 0.070) and 32.4% of POWeR+R participants (risk ratio 1.82, 95% CI 1.31 to 2.74; p = 0.004) maintained a clinically significant 5% weight reduction. The POWeR+R group had fewer individuals who reported doing another activity to help lose weight [control, 47.1% (64/136); POWeR+F, 37.2% (51/137); POWeR+R, 26.7% (40/150)]. The incremental cost to the health service per kilogram weight lost, compared with the control group, was £18 (95% CI -£129 to £195) for POWeR+F and -£25 (95% CI -£268 to £157) for POWeR+R. The probability of being cost-effective at a threshold of £100 per kilogram was 88% and 98% for POWeR+F and POWeR+R, respectively. POWeR+R was dominant compared with the control group. No harms were reported and participants using POWeR+ felt more enabled in managing their weight. The qualitative studies documented that POWeR+ was viewed positively by patients and that health-care professionals generally enjoyed supporting patients using POWeR+. STUDY LIMITATIONS Maintenance of weight loss after 1 year is unknown. FUTURE WORK Identifying strategies for longer-term engagement, impact in community settings and increasing physical activity. CONCLUSION Clinically valuable weight loss (> 5%) is maintained in 20% of individuals using novel written materials with brief follow-up. A web-based behavioural programme and brief support results in greater mean weight loss and 10% more participants maintain valuable weight loss; it achieves greater enablement and fewer participants undertaking other weight-loss activities; and it is likely to be cost-effective. TRIAL REGISTRATION Current Controlled Trials ISRCTN21244703. FUNDING This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 21, No. 4. See the NIHR Journals Library website for further project information. PMID:28122658

Comprehensive evaluation of the revised international staging system in multiple myeloma patients treated with novel agents as a primary therapy.

PubMed

Cho, Hyungwoo; Yoon, Dok Hyun; Lee, Jung Bok; Kim, Sung-Yong; Moon, Joon Ho; Do, Young Rok; Lee, Jae Hoon; Park, Yong; Lee, Ho Sup; Eom, Hyeon Seok; Shin, Ho-Jin; Min, Chang-Ki; Kim, Jin Seok; Jo, Jae-Cheol; Kang, Hye Jin; Mun, Yeung-Chul; Lee, Won Sik; Lee, Je-Jung; Suh, Cheolwon; Kim, Kihyun

2017-12-01

The revised International Staging System (R-ISS) has recently been developed to improve the risk stratification of multiple myeloma (MM) patients over the ISS. We assessed the R-ISS in MM patients who were treated with novel agents as a primary therapy and evaluated its discriminative power and ability to reclassify patients from the ISS. A total of 514 newly diagnosed MM patients treated with novel agents including thalidomide, bortezomib, and lenalidomide as a primary therapy were included in this retrospective analysis. With a median follow-up duration of 42.3 months (range, 40.5-44.1), the median overall survival (OS) was 61.0 months. There was a significant difference in median OS (not reached, 60.9, and 50.1 months for stages 1, 2, and 3, respectively, P < 0.001) among the three stages of R-ISS. The C-statistic was significantly greater for R-ISS than for ISS (0.769 vs. 0.696, P < 0.001). The event NRI was -0.08 (95% confidence interval [CI], -0.18-0.01) and the non-event NRI was 0.05 (95% CI, -0.03-0.10), resulting in a total NRI of -0.03 (95% CI, -0.14-0.08, P = 0.602). The R-ISS performs well and has significantly better discriminative power than the ISS in MM patients treated with novel agents as a primary therapy. However, it does not better reclassify patients from the ISS, suggesting that there is still room to improve the staging system. Moreover, new statistical measures for assessing and quantifying the risk prediction of new prognostic models are necessary in future studies. © 2017 Wiley Periodicals, Inc.

Galaxy power spectrum in redshift space: Combining perturbation theory with the halo model

NASA Astrophysics Data System (ADS)

Okumura, Teppei; Hand, Nick; Seljak, Uroš; Vlah, Zvonimir; Desjacques, Vincent

2015-11-01

Theoretical modeling of the redshift-space power spectrum of galaxies is crucially important to correctly extract cosmological information from galaxy redshift surveys. The task is complicated by the nonlinear biasing and redshift space distortion (RSD) effects, which change with halo mass, and by the wide distribution of halo masses and their occupations by galaxies. One of the main modeling challenges is the existence of satellite galaxies that have both radial distribution inside the halos and large virial velocities inside halos, a phenomenon known as the Finger-of-God (FoG) effect. We present a model for the redshift-space power spectrum of galaxies in which we decompose a given galaxy sample into central and satellite galaxies and relate different contributions to the power spectrum to 1-halo and 2-halo terms in a halo model. Our primary goal is to ensure that any parameters that we introduce have physically meaningful values, and are not just fitting parameters. For the lowest order 2-halo terms we use the previously developed RSD modeling of halos in the context of distribution function and perturbation theory approach. This term needs to be multiplied by the effect of radial distances and velocities of satellites inside the halo. To this one needs to add the 1-halo terms, which are nonperturbative. We show that the real space 1-halo terms can be modeled as almost constant, with the finite extent of the satellites inside the halo inducing a small k2R2 term over the range of scales of interest, where R is related to the size of the halo given by its halo mass. We adopt a similar model for FoG in redshift space, ensuring that FoG velocity dispersion is related to the halo mass. For FoG k2 type expansions do not work over the range of scales of interest and FoG resummation must be used instead. We test several simple damping functions to model the velocity dispersion FoG effect. Applying the formalism to mock galaxies modeled after the "CMASS" sample of the BOSS survey, we find that our predictions for the redshift-space power spectra are accurate up to k ≃0.4 h Mpc-1 within 1% if the halo power spectrum is measured using N -body simulations and within 3% if it is modeled using perturbation theory.

The effect of the oxygen uptake-power output relationship on the prediction of supramaximal oxygen demands.

PubMed

Muniz-Pumares, Daniel; Pedlar, Charles; Godfrey, Richard; Glaister, Mark

2017-01-01

The aim of this study was to investigate the relationship between oxygen uptake (V̇O2) and power output at intensities below and above the lactate threshold (LT) in cyclists; and to determine the reliability of supramaximal power outputs linearly projected from these relationships. Nine male cyclists (mean±standard deviation age: 41±8 years; mass: 77±6 kg, height: 1.79±0.05 m and V̇O2max: 54±7 mL∙kg-1∙min-1) completed two cycling trials each consisting of a step test (10×3 min stages at submaximal incremental intensities) followed by a maximal test to exhaustion. The lines of best fit for V̇O2 and power output were determined for: the entire step test; stages below and above the LT, and from rolling clusters of five consecutive stages. Lines were projected to determine a power output predicted to elicit 110% peak V̇O2. There were strong linear correlations (r≥0.953; P<0.01) between V̇O2 and power output using the three approaches; with the slope, intercept, and projected values of these lines unaffected (P≥0.05) by intensity. The coefficient of variation of the predicted power output at 110% V̇O2max was 6.7% when using all ten submaximal stages. Cyclists exhibit a linear V̇O2 and power output relationship when determined using 3 min stages, which allows for prediction of a supramaximal intensity with acceptable reliability.

[Assessment of Three Risk Adjustment Systems as Predictors of the Consumption of Medicines and Medical Supplies at Polyvalent Hospitalization Units. Spain].

PubMed

Mera Flores, Ana María; Del Busto Bonifaz, Sebastián; Bernal Sobrino, José Luis

2016-09-26

The use of medicines and medical supplies is a significant component of health expenditure, linked to healthcare quality and efficient resource allocation. This study aimed to evaluate three risk adjustment systems predictive power of the consumption of medicines and medical supplies at polyvalent hospitalization units (PHU). This is an observational, retrospective study of the resources utilization in PHU between 2010 and 2013. We fitted linear regression models and evaluated their goodness of fit for three different predictors: Charlson Comorbidity Index (CCI), All Patients DRG (AP-DRG) and All Patients Refined DRG (APR-DRG) relative weights, and each one of them corrected by the length of stay. We analyzed hospitalization episodes included in the Minimum Basic Data Set (MBDS) from Fuenlabrada University Hospital. Data about the use of medicines and medical supplies were obtained from pharmacy and supply chain management information systems. Significant correlation was found between the annual consumption and the predictors considered (r=0,879 for CCI; r=0,622 for AP-DRG and r=0,514 for APR-DRG). The CCI corrected by length of stay was the variable that best fit presented (Ṝ2=0,863). The best predictive ability of CCI indicates that resource utilization depends more of the concurrent presence of additional pathology than the case mix calculated for iso-resource groups.