Achievable accuracy of hip screw holding power estimation by insertion torque measurement.

PubMed

Erani, Paolo; Baleani, Massimiliano

2018-02-01

To ensure stability of proximal femoral fractures, the hip screw must firmly engage into the femoral head. Some studies suggested that screw holding power into trabecular bone could be evaluated, intraoperatively, through measurement of screw insertion torque. However, those studies used synthetic bone, instead of trabecular bone, as host material or they did not evaluate accuracy of predictions. We determined prediction accuracy, also assessing the impact of screw design and host material. We measured, under highly-repeatable experimental conditions, disregarding clinical procedure complexities, insertion torque and pullout strength of four screw designs, both in 120 synthetic and 80 trabecular bone specimens of variable density. For both host materials, we calculated the root-mean-square error and the mean-absolute-percentage error of predictions based on the best fitting model of torque-pullout data, in both single-screw and merged dataset. Predictions based on screw-specific regression models were the most accurate. Host material impacts on prediction accuracy: the replacement of synthetic with trabecular bone decreased both root-mean-square errors, from 0.54 ÷ 0.76 kN to 0.21 ÷ 0.40 kN, and mean-absolute-percentage errors, from 14 ÷ 21% to 10 ÷ 12%. However, holding power predicted on low insertion torque remained inaccurate, with errors up to 40% for torques below 1 Nm. In poor-quality trabecular bone, tissue inhomogeneities likely affect pullout strength and insertion torque to different extents, limiting the predictive power of the latter. This bias decreases when the screw engages good-quality bone. Under this condition, predictions become more accurate although this result must be confirmed by close in-vitro simulation of the clinical procedure. Copyright © 2018 Elsevier Ltd. All rights reserved.

QSPR for predicting chloroform formation in drinking water disinfection.

PubMed

Luilo, G B; Cabaniss, S E

2011-01-01

Chlorination is the most widely used technique for water disinfection, but may lead to the formation of chloroform (trichloromethane; TCM) and other by-products. This article reports the first quantitative structure-property relationship (QSPR) for predicting the formation of TCM in chlorinated drinking water. Model compounds (n = 117) drawn from 10 literature sources were divided into training data (n = 90, analysed by five-way leave-many-out internal cross-validation) and external validation data (n = 27). QSPR internal cross-validation had Q² = 0.94 and root mean square error (RMSE) of 0.09 moles TCM per mole compound, consistent with external validation Q2 of 0.94 and RMSE of 0.08 moles TCM per mole compound, and met criteria for high predictive power and robustness. In contrast, log TCM QSPR performed poorly and did not meet the criteria for predictive power. The QSPR predictions were consistent with experimental values for TCM formation from tannic acid and for model fulvic acid structures. The descriptors used are consistent with a relatively small number of important TCM precursor structures based upon 1,3-dicarbonyls or 1,3-diphenols.

Modelling sheet erosion on steep slopes in the loess region of China

NASA Astrophysics Data System (ADS)

Wu, Bing; Wang, Zhanli; Zhang, Qingwei; Shen, Nan; Liu, June

2017-10-01

The relationship of sheet erosion rate (SE), slope gradient (S) and rainfall intensity (I), and hydraulic parameters, such as flow velocity (V), shear stress (τ), stream power (Ω) and unit stream power (P), was investigated to derive an accurate experimental model. The experiment was conducted at slopes of 12.23%, 17.63%, 26.8%, 36.4%, 40.4% and 46.63% under I of 48, 60, 90, 120, 138 and 150 mm h-1, respectively, using simulated rainfall. Results showed that sheet erosion rate increased as a power function with rainfall intensity and slope gradient with R2 = 0.95 and Nash-Sutcliffe model efficiency (NSE) = 0.87. Sheet erosion rate was more sensitive to rainfall intensity than to slope gradient. It increased as a power function with flow velocity, which was satisfactory for predicting sheet erosion rate with R2 = 0.95 and NSE = 0.81. Shear stress and stream power could be used to predict sheet erosion rate accurately with a linear function equation. Stream power (R2 = 0.97, NSE = 0.97) was a better predictor of sheet erosion rather than shear stress (R2 = 0.90, NSE = 0.89). However, a prediction based on unit stream power was poor. The new equation (i.e. SE = 7.5 ×1012S1.43I3.04 and SE = 0.06 Ω - 0.0003 and SE = 0.011 τ - 0.01) would improve water erosion estimation on loess hillslopes of China.

Disease Staging and Prognosis in Smokers Using Deep Learning in Chest Computed Tomography.

PubMed

González, Germán; Ash, Samuel Y; Vegas-Sánchez-Ferrero, Gonzalo; Onieva Onieva, Jorge; Rahaghi, Farbod N; Ross, James C; Díaz, Alejandro; San José Estépar, Raúl; Washko, George R

2018-01-15

Deep learning is a powerful tool that may allow for improved outcome prediction. To determine if deep learning, specifically convolutional neural network (CNN) analysis, could detect and stage chronic obstructive pulmonary disease (COPD) and predict acute respiratory disease (ARD) events and mortality in smokers. A CNN was trained using computed tomography scans from 7,983 COPDGene participants and evaluated using 1,000 nonoverlapping COPDGene participants and 1,672 ECLIPSE participants. Logistic regression (C statistic and the Hosmer-Lemeshow test) was used to assess COPD diagnosis and ARD prediction. Cox regression (C index and the Greenwood-Nam-D'Agnostino test) was used to assess mortality. In COPDGene, the C statistic for the detection of COPD was 0.856. A total of 51.1% of participants in COPDGene were accurately staged and 74.95% were within one stage. In ECLIPSE, 29.4% were accurately staged and 74.6% were within one stage. In COPDGene and ECLIPSE, the C statistics for ARD events were 0.64 and 0.55, respectively, and the Hosmer-Lemeshow P values were 0.502 and 0.380, respectively, suggesting no evidence of poor calibration. In COPDGene and ECLIPSE, CNN predicted mortality with fair discrimination (C indices, 0.72 and 0.60, respectively), and without evidence of poor calibration (Greenwood-Nam-D'Agnostino P values, 0.307 and 0.331, respectively). A deep-learning approach that uses only computed tomography imaging data can identify those smokers who have COPD and predict who are most likely to have ARD events and those with the highest mortality. At a population level CNN analysis may be a powerful tool for risk assessment.

Automated assessment of early hypoxic brain edema in non-enhanced CT predicts outcome in patients after cardiac arrest.

PubMed

Hanning, Uta; Sporns, Peter Bernhard; Lebiedz, Pia; Niederstadt, Thomas; Zoubi, Tarek; Schmidt, Rene; Knecht, Stefan; Heindel, Walter; Kemmling, André

2016-07-01

Early prediction of potential neurological recovery in patients after cardiac arrest is challenging. Recent studies suggest that the densitrometic gray-white matter ratio (GWR) determined from cranial computed tomography (CT) scans may be a reliable predictor of poor outcome. We evaluated an automated, rater independent method to determine GWR in CT as an early objective imaging predictor of clinical outcome. We analyzed imaging data of 84 patients after cardiac arrest that underwent noncontrast CT within 24h after arrest. To determine GWR in CT we applied two methods using a recently published automated probabilistic gray-white matter segmentation algorithm (GWR_aut) and conventional manual measurements within gray-white regions of interest (GWR_man). Neurological outcome was graded by the cerebral performance category (CPC). As part of standard routine CPC was assessed by the treating physician in the intensive care unit at admission and at discharge to normal ward. The performance of GWR measures (automated and manual) to predict the binary clinical endpoints of poor (CPC3-5) and good outcome (CPC1-2) was assessed by ROC analysis with increasing discrimination thresholds. Results of GWR_aut were compared to GWR_man of two raters. Of 84 patients, 55 (65%) showed a poor outcome. ROC curve analysis revealed reliable outcome prediction of GWR_aut (AUC 0.860) and GWR_man (AUC 0.707 and 0.699, respectively). Predictive power of GWR_aut was higher than GWR_man by each rater (p=0.019 and p=0.021, respectively) at an optimal cut-off of 1.084 to predict poor outcome (optimal criterion with 92.7% sensitivity, 72.4% specificity). Interrater reliability of GWR_man by intra-class correlation coefficient (ICC) was moderate (0.551). Automated quantification of GWR in CT may be used as an objective observer-independent imaging marker for outcome in patients after cardiac arrest. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Poor Response Inhibition as a Predictor of Problem Drinking and Illicit Drug Use in Adolescents at Risk for Alcoholism and Other Substance Use Disorders

ERIC Educational Resources Information Center

Nigg, Joel T.; Wong, Maria M.; Martel, Michelle M.; Jester, Jennifer M.; Puttler, Leon I.; Glass, Jennifer M.; Adams, Kenneth M.; Fitzgerald, Hiram E.; Zucker, Robert A.

2006-01-01

Objective: To evaluate the predictive power of executive functions, in particular, response inhibition, in relation to alcohol-related problems and illicit drug use in adolescence. Method: A total of 498 children from 275 families from a longitudinal high-risk study completed executive function measures in early and late adolescence and lifetime…

Knowing what to sell, when, and to whom.

PubMed

Kumar, V; Venkatesan, Rajkumar; Reinartz, Werner

2006-03-01

Despite an abundance of data, most companies do a poor job of predicting the behavior of their customers. In fact, the authors' research suggests that even companies that take the greatest trouble over their predictions about whether a particular customer will buy a particular product are correct only around 55% of the time--a result that hardly justifies the costs of having a CRM system in the first place. Businesses usually conclude from studies like this that it's impossible to use the past to predict the future, so they revert to the timeworn marketing practice of inundating their customers with offers. But as the authors explain, the reason for the poor predictions is not any basic limitation of CRM systems or the predictive power of past behavior, but rather of the mathematical methods that companies use to interpret the data. The authors have developed a new way of predicting customer behavior, based on the work of the Nobel Prize-winning economist Daniel McFadden, that delivers vastly improved results. Indeed, the methodology increases the odds of successfully predicting a specific purchase by a specific customer at a specific time to about 85%, a number that will have a major impact on any company's marketing ROI. What's more, using this methodology, companies can increase revenues while reducing their frequency of customer contact-evidence that overcommunication with customers may actually damage a company's sales.

Fundamental investigation of ARC interruption in gas flows

NASA Astrophysics Data System (ADS)

Benenson, D. M.; Frind, G.; Kinsinger, R. E.; Nagamatsu, H. T.; Noeske, H. O.; Sheer, R. E., Jr.

1980-07-01

Thermal recovery in gas blast interrupters is discussed. The thermal recovery process was investigated with physical and aerodynamic methods, typically using reduced size nozzles and short sinusoidal current pulses. Aerodynamic characterization of the cold flow fields in several different nozzle types included measurements of the pressure and flow fields, both steady-state and turbulent components, with special attention given to wakes and shock structures. Special schlieren techniques on DC arcs and high speed photography on arcs in orifice nozzles show that shock heating broadens the arc independent of turbulence effects and produces a poorly recovering downstream arc section. Measured recovery speeds in both orifice and convergent-divergent nozzles agree with predictions of several arc theories assuming turbulent power losses. However, data on post-zero currents and power loss show values much smaller than theoretical predictions. Hydrogen, deuterium, and methane were measured.

The factor structure of complex posttraumatic stress disorder in traumatized refugees.

PubMed

Nickerson, Angela; Cloitre, Marylene; Bryant, Richard A; Schnyder, Ulrich; Morina, Naser; Schick, Matthis

2016-01-01

The construct of complex posttraumatic stress disorder (CPTSD) has attracted much research attention in previous years, however it has not been systematically evaluated in individuals exposed to persecution and displacement. Given that CPTSD has been proposed as a diagnostic category in the ICD-11, it is important that it be examined in refugee groups. In the current study, we proposed to test, for the first time, the factor structure of CPTSD proposed for the ICD-11 in a sample of resettled treatment-seeking refugees. The study sample consisted of 134 traumatized refugees from a variety of countries of origin, with approximately 93% of the sample having been exposed to torture. We used confirmatory factor analysis to examine the factor structure of CPTSD in this sample and examined the sensitivity, specificity, positive predictive power and negative predictive power of individual items in relation to the CPTSD diagnosis. Findings revealed that a two-factor higher-order model of CPTSD comprising PTSD and Difficulties in Self-Organization (χ 2 (47)=57.322, p =0.144, RMSEA=0.041, CFI=0.981, TLI=0.974) evidenced superior fit compared to a one-factor higher-order model of CPTSD (χ 2 (48)=65.745, p =0.045, RMSEA=0.053, CFI=0.968, TLI=0.956). Overall, items evidenced strong sensitivity and negative predictive power, moderate positive predictive power, and poor specificity. Findings provide preliminary evidence for the validity of the CPTSD construct with highly traumatized treatment-seeking refugees.

Update on results of SPRE testing at NASA Lewis

NASA Technical Reports Server (NTRS)

Cairelli, James E.; Swec, Diane M.; Wong, Wayne A.; Doeberling, Thomas J.; Madi, Frank J.

1991-01-01

The Space Power Research Engine (SPRE), a free-piston Stirling engine with a linear alternator, is being tested at NASA Lewis Research Center as part of the Civilian Space Technology Initiative (CSTI) as a candidate for high capacity space power. Results are presented from recent SPRE tests designed to investigated the effects of variation in the displacer seal clearance and piston centering port area on engine performance and dynamics. The impact of these variations on PV power and efficiency are presented. Comparisons of the displacer seal clearance tests results with HFAST code predictions show good agreement for PV power, but show poor agreement for PV efficiency. Correlations are presented relating the piston midstroke position to the dynamic Delta P across the piston and the centering port area. Test results indicate that a modest improvement in PV power and efficiency may be realized with a reduction in piston centering port area.

Update on results of SPRE testing at NASA Lewis

NASA Technical Reports Server (NTRS)

Cairelli, James E.; Swec, Diane M.; Wong, Wayne A.; Doeberling, Thomas J.; Madi, Frank J.

1991-01-01

The Space Power Research Engine (SPRE), a free-piston Stirling engine with a linear alternator, is being tested at NASA Lewis Research Center as part of the Civilian Space Technology Initiative (CSTI) as a candidate for high capacity space power. Results are presented from recent SPRE tests designed to investigate the effects of variation in the displacer seal clearance and piston centering port area on engine performance and dynamics. The effects of these variations on PV power and efficiency are presented. Comparisons of the displacer seal clearance test results with HFAST code predictions show good agreement for PV power but poor agreement for PV efficiency. Correlations are presented relating the piston mid-stroke position to the dynamic Delta P across the piston and the centering port area. Test results indicate that a modest improvement in PV power and efficiency may be realized with a reduction in piston centering port area.

Urinary Squamous Epithelial Cells Do Not Accurately Predict Urine Culture Contamination, but May Predict Urinalysis Performance in Predicting Bacteriuria.

PubMed

Mohr, Nicholas M; Harland, Karisa K; Crabb, Victoria; Mutnick, Rachel; Baumgartner, David; Spinosi, Stephanie; Haarstad, Michael; Ahmed, Azeemuddin; Schweizer, Marin; Faine, Brett

2016-03-01

The presence of squamous epithelial cells (SECs) has been advocated to identify urinary contamination despite a paucity of evidence supporting this practice. We sought to determine the value of using quantitative SECs as a predictor of urinalysis contamination. Retrospective cross-sectional study of adults (≥18 years old) presenting to a tertiary academic medical center who had urinalysis with microscopy and urine culture performed. Patients with missing or implausible demographic data were excluded (2.5% of total sample). The primary analysis aimed to determine an SEC threshold that predicted urine culture contamination using receiver operating characteristics (ROC) curve analysis. The a priori secondary analysis explored how demographic variables (age, sex, body mass index) may modify the SEC test performance and whether SECs impacted traditional urinalysis indicators of bacteriuria. A total of 19,328 records were included. ROC curve analysis demonstrated that SEC count was a poor predictor of urine culture contamination (area under the ROC curve = 0.680, 95% confidence interval [CI] = 0.671 to 0.689). In secondary analysis, the positive likelihood ratio (LR+) of predicting bacteriuria via urinalysis among noncontaminated specimens was 4.98 (95% CI = 4.59 to 5.40) in the absence of SECs, but the LR+ fell to 2.35 (95% CI = 2.17 to 2.54) for samples with more than 8 SECs/low-powered field (lpf). In an independent validation cohort, urinalysis samples with fewer than 8 SECs/lpf predicted bacteriuria better (sensitivity = 75%, specificity = 84%) than samples with more than 8 SECs/lpf (sensitivity = 86%, specificity = 70%; diagnostic odds ratio = 17.5 [14.9 to 20.7] vs. 8.7 [7.3 to 10.5]). Squamous epithelial cells are a poor predictor of urine culture contamination, but may predict poor predictive performance of traditional urinalysis measures. © 2016 by the Society for Academic Emergency Medicine.

Predictors of poor outcome despite recanalization: a multiple regression analysis of the NASA registry.

PubMed

Linfante, Italo; Starosciak, Amy K; Walker, Gail R; Dabus, Guilherme; Castonguay, Alicia C; Gupta, Rishi; Sun, Chung-Huan J; Martin, Coleman; Holloway, William E; Mueller-Kronast, Nils; English, Joey D; Malisch, Tim W; Marden, Franklin A; Bozorgchami, Hormozd; Xavier, Andrew; Rai, Ansaar T; Froehler, Michael T; Badruddin, Aamir; Nguyen, Thanh N; Taqi, M Asif; Abraham, Michael G; Janardhan, Vallabh; Shaltoni, Hashem; Novakovic, Roberta; Yoo, Albert J; Abou-Chebl, Alex; Chen, Peng R; Britz, Gavin W; Kaushal, Ritesh; Nanda, Ashish; Issa, Mohammad A; Nogueira, Raul G; Zaidat, Osama O

2016-03-01

Mechanical thrombectomy with stent-retrievers results in higher recanalization rates compared with previous devices. Despite successful recanalization rates (Thrombolysis in Cerebral Infarction (TICI) score ≥2b) of 70-83%, good outcomes by 90-day modified Rankin Scale (mRS) score ≤2 are achieved in only 40-55% of patients. We evaluated predictors of poor outcomes (mRS >2) despite successful recanalization (TICI ≥2b) in the North American Solitaire Stent Retriever Acute Stroke (NASA) registry. Logistic regression was used to evaluate baseline characteristics and recanalization outcomes for association with 90-day mRS score of 0-2 (good outcome) vs 3-6 (poor outcome). Univariate tests were carried out for all factors. A multivariable model was developed based on backwards selection from the factors with at least marginal significance (p≤0.10) on univariate analysis with the retention criterion set at p≤0.05. The model was refit to minimize the number of cases excluded because of missing covariate values; the c-statistic was a measure of predictive power. Of 354 patients, 256 (72.3%) were recanalized successfully. Based on 234 recanalized patients evaluated for 90-day mRS score, 116 (49.6%) had poor outcomes. Univariate analysis identified an increased risk of poor outcome for age ≥80 years, occlusion site of internal carotid artery (ICA)/basilar artery, National Institute of Health Stroke Scale (NIHSS) score ≥18, history of diabetes mellitus, TICI 2b, use of rescue therapy, not using a balloon-guided catheter or intravenous tissue plasminogen activator (IV t-PA), and >30 min to recanalization (p≤0.05). In multivariable analysis, age ≥80 years, occlusion site ICA/basilar, initial NIHSS score ≥18, diabetes, absence of IV t-PA, ≥3 passes, and use of rescue therapy were significant independent predictors of poor 90-day outcome in a model with good predictive power (c-index=0.80). Age, occlusion site, high NIHSS, diabetes, no IV t-PA, ≥3 passes, and use of rescue therapy are associated with poor 90-day outcome despite successful recanalization. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Which insulin resistance-based definition of metabolic syndrome has superior diagnostic value in detection of poor health-related quality of life? Cross-sectional findings from Tehran Lipid and Glucose Study.

PubMed

Deihim, Tina; Amiri, Parisa; Taherian, Reza; Tohidi, Maryam; Ghasemi, Asghar; Cheraghi, Leila; Azizi, Fereidoun

2015-12-09

The superiority of the diagnostic power of different definitions of metabolic syndrome (MetS) in detecting objective and subjective cardiovascular outcomes is under debate. We sought to compare diagnostic values of different insulin resistance (IR)-based definitions of MetS in detecting poor health-related quality of life (HRQoL) in a large sample of Tehranian adults. This cross-sectional study conducted within the framework of the Tehran Lipid and Glucose Study on a total sample of 742 individuals, aged ≥ 20 years. Metabolic syndrome was defined according to the World Health Organization (WHO), the European Group for the study of Insulin Resistance (EGIR), and the American Association of Clinical Endocrinology (AACE). Health-related quality of life was assessed using the Short Form Health Survey (SF-36). Logistic regression analysis and Receiver Operating Characteristic (ROC) curve were used to investigate the impact of the three IR-based definitions of MetS on HRQoL and compare their discriminative powers in predicting poor HRQoL. Compared with other definitions, the WHO definition identified more participants with MetS (41.8 %). Although the AACE definition had higher adjusted odds ratios for reporting poor physical HRQoL (OR: 1.95; CI: 0.84-4.53 and OR: 1.01; CI: 0.55-1.85 in men and women respectively) and mental HRQoL (OR: 0.97; CI: 0.41-2.28 and OR: 1.00; CI: 0.56-1.79 in men and women respectively), none of the three studied definitions were significantly associated with poor physical or mental HRQoL in either gender; nor did ROC curves show any significant difference in the discriminative powers of IR-based definitions in detecting poor HRQoL in either gender. None of the three studied IR-based definitions of MetS could significantly detect poor HRQoL in the physical or mental domains, indicating no significant superior diagnostic value for any of these definitions.

Performance of an inverted pendulum model directly applied to normal human gait.

PubMed

Buczek, Frank L; Cooney, Kevin M; Walker, Matthew R; Rainbow, Michael J; Concha, M Cecilia; Sanders, James O

2006-03-01

In clinical gait analysis, we strive to understand contributions to body support and propulsion as this forms a basis for treatment selection, yet the relative importance of gravitational forces and joint powers can be controversial even for normal gait. We hypothesized that an inverted pendulum model, propelled only by gravity, would be inadequate to predict velocities and ground reaction forces during gait. Unlike previous ballistic and passive dynamic walking studies, we directly compared model predictions to gait data for 24 normal children. We defined an inverted pendulum from the average center-of-pressure to the instantaneous center-of-mass, and derived equations of motion during single support that allowed a telescoping action. Forward and inverse dynamics predicted pendulum velocities and ground reaction forces, and these were statistically and graphically compared to actual gait data for identical strides. Results of forward dynamics replicated those in the literature, with reasonable predictions for velocities and anterior ground reaction forces, but poor predictions for vertical ground reaction forces. Deviations from actual values were explained by joint powers calculated for these subjects. With a telescoping action during inverse dynamics, predicted vertical forces improved dramatically and gained a dual-peak pattern previously missing in the literature, yet expected for normal gait. These improvements vanished when telescoping terms were set to zero. Because this telescoping action is difficult to explain without muscle activity, we believe these results support the need for both gravitational forces and joint powers in normal gait. Our approach also begins to quantify the relative contributions of each.

The Power of Implicit Social Relation in Rating Prediction of Social Recommender Systems

PubMed Central

Reafee, Waleed; Salim, Naomie; Khan, Atif

2016-01-01

The explosive growth of social networks in recent times has presented a powerful source of information to be utilized as an extra source for assisting in the social recommendation problems. The social recommendation methods that are based on probabilistic matrix factorization improved the recommendation accuracy and partly solved the cold-start and data sparsity problems. However, these methods only exploited the explicit social relations and almost completely ignored the implicit social relations. In this article, we firstly propose an algorithm to extract the implicit relation in the undirected graphs of social networks by exploiting the link prediction techniques. Furthermore, we propose a new probabilistic matrix factorization method to alleviate the data sparsity problem through incorporating explicit friendship and implicit friendship. We evaluate our proposed approach on two real datasets, Last.Fm and Douban. The experimental results show that our method performs much better than the state-of-the-art approaches, which indicates the importance of incorporating implicit social relations in the recommendation process to address the poor prediction accuracy. PMID:27152663

External validation of the international risk prediction algorithm for major depressive episode in the US general population: the PredictD-US study.

PubMed

Nigatu, Yeshambel T; Liu, Yan; Wang, JianLi

2016-07-22

Multivariable risk prediction algorithms are useful for making clinical decisions and for health planning. While prediction algorithms for new onset of major depression in the primary care attendees in Europe and elsewhere have been developed, the performance of these algorithms in different populations is not known. The objective of this study was to validate the PredictD algorithm for new onset of major depressive episode (MDE) in the US general population. Longitudinal study design was conducted with approximate 3-year follow-up data from a nationally representative sample of the US general population. A total of 29,621 individuals who participated in Wave 1 and 2 of the US National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) and who did not have an MDE in the past year at Wave 1 were included. The PredictD algorithm was directly applied to the selected participants. MDE was assessed by the Alcohol Use Disorder and Associated Disabilities Interview Schedule, based on the DSM-IV criteria. Among the participants, 8 % developed an MDE over three years. The PredictD algorithm had acceptable discriminative power (C-statistics = 0.708, 95 % CI: 0.696, 0.720), but poor calibration (p < 0.001) with the NESARC data. In the European primary care attendees, the algorithm had a C-statistics of 0.790 (95 % CI: 0.767, 0.813) with a perfect calibration. The PredictD algorithm has acceptable discrimination, but the calibration capacity was poor in the US general population despite of re-calibration. Therefore, based on the results, at current stage, the use of PredictD in the US general population for predicting individual risk of MDE is not encouraged. More independent validation research is needed.

High-Amplitude Atlantic Hurricanes Produce Disparate Mortality in Small, Low-Income Countries.

PubMed

Dresser, Caleb; Allison, Jeroan; Broach, John; Smith, Mary-Elise; Milsten, Andrew

2016-12-01

Hurricanes cause substantial mortality, especially in developing nations, and climate science predicts that powerful hurricanes will increase in frequency during the coming decades. This study examined the association of wind speed and national economic conditions with mortality in a large sample of hurricane events in small countries. Economic, meteorological, and fatality data for 149 hurricane events in 16 nations between 1958 and 2011 were analyzed. Mortality rate was modeled with negative binomial regression implemented by generalized estimating equations to account for variable population exposure, sequence of storm events, exposure of multiple islands to the same storm, and nonlinear associations. Low-amplitude storms caused little mortality regardless of economic status. Among high-amplitude storms (Saffir-Simpson category 4 or 5), expected mortality rate was 0.72 deaths per 100,000 people (95% confidence interval [CI]: 0.16-1.28) for nations in the highest tertile of per capita gross domestic product (GDP) compared with 25.93 deaths per 100,000 people (95% CI: 13.30-38.55) for nations with low per capita GDP. Lower per capita GDP and higher wind speeds were associated with greater mortality rates in small countries. Excessive fatalities occurred when powerful storms struck resource-poor nations. Predictions of increasing storm amplitude over time suggest increasing disparity between death rates unless steps are taken to modify the risk profiles of poor nations. (Disaster Med Public Health Preparedness. 2016;10:832-837).

Second trimester maternal urine for the diagnosis of trisomy 21 and prediction of poor pregnancy outcomes.

PubMed

Diaz, Sílvia O; Barros, António S; Goodfellow, Brian J; Duarte, Iola F; Galhano, Eulália; Pita, Cristina; Almeida, Maria do Céu; Carreira, Isabel M; Gil, Ana M

2013-06-07

Given the recognized lack of prenatal clinical methods for the early diagnosis of preterm delivery, intrauterine growth restriction, preeclampsia and gestational diabetes mellitus, and the continuing need for optimized diagnosis methods for specific chromosomal disorders (e.g., trisomy 21) and fetal malformations, this work sought specific metabolic signatures of these conditions in second trimester maternal urine, using (1)H Nuclear Magnetic Resonance ((1)H NMR) metabolomics. Several variable importance to the projection (VIP)- and b-coefficient-based variable selection methods were tested, both individually and through their intersection, and the resulting data sets were analyzed by partial least-squares discriminant analysis (PLS-DA) and submitted to Monte Carlo cross validation (MCCV) and permutation tests to evaluate model predictive power. The NMR data subsets produced significantly improved PLS-DA models for all conditions except for pre-premature rupture of membranes. Specific urinary metabolic signatures were unveiled for central nervous system malformations, trisomy 21, preterm delivery, gestational diabetes, intrauterine growth restriction and preeclampsia, and biochemical interpretations were proposed. This work demonstrated, for the first time, the value of maternal urine profiling as a complementary means of prenatal diagnostics and early prediction of several poor pregnancy outcomes.

What is interesting? Exploring the appraisal structure of interest.

PubMed

Silvia, Paul J

2005-03-01

Relative to other emotions, interest is poorly understood. On the basis of theories of appraisal process and structure, it was predicted that interest consists of appraisals of novelty (factors related to unfamiliarity and complexity) and appraisals of coping potential (the ability to understand the new, complex thing). Four experiments, using in vivo rather than retrospective methods, supported this appraisal structure. The findings were general across measured and manipulated appraisals, interesting stimuli (random polygons, visual art, poetry), and measures of interest (self-reports, forced-choice, behavioral measures). Furthermore, the appraisal structure was specific to interest (it did not predict enjoyment, a related positive emotion), and appraisals predicted interest beyond relevant traits (curiosity, openness). The appraisal perspective offers a powerful way of construing the causes of interest. Copyright 2005 APA, all rights reserved.

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.

Using the ovarian sensitivity index to define poor, normal, and high response after controlled ovarian hyperstimulation in the long gonadotropin-releasing hormone-agonist protocol: suggestions for a new principle to solve an old problem.

PubMed

Huber, Malin; Hadziosmanovic, Nermin; Berglund, Lars; Holte, Jan

2013-11-01

To explore the utility of using the ratio between oocyte yield and total dose of FSH, i.e., the ovarian sensitivity index (OSI), to define ovarian response patterns. Retrospective cross-sectional study. University-affiliated private center. The entire unselected cohort of 7,520 IVF/intracytoplasmic sperm injection treatments (oocyte pick-ups [OPUs]) during an 8-year period (long GnRH agonist-recombinant FSH protocol). None. The distribution of the OSI (oocytes recovered × 1,000/total dose of FSH), the cutoff levels for poor and high response, set at ±1 SD, and the relationship between OSI and treatment outcome. OSI showed a log-normal distribution with cutoff levels for poor and high response at 1.697/IU and 10.07/IU, respectively. A nomogram is presented. Live-birth rates per OPU were 10.5 ± 0.1%, 26.9 ± 0.6%, and 36.0 ± 1.4% for poor, normal, and high response treatments, respectively. The predictive power (C-statistic) for OSI to predict live birth was superior to that of oocyte yield. The OSI improves the definition of ovarian response patterns because it takes into account the degree of stimulation. The nomogram presents evidence-based cutoff levels for poor, normal, and high response and could be used for unifying study designs involving ovarian response patterns. Copyright © 2013 American Society for Reproductive Medicine. Published by Elsevier Inc. 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.

Comparison of Spot Sign, Blend Sign and Black Hole Sign for Outcome Prediction in Patients with Intracerebral Hemorrhage

PubMed Central

Sporns, Peter B.; Schwake, Michael; Kemmling, André; Minnerup, Jens; Schwindt, Wolfram; Niederstadt, Thomas; Schmidt, Rene; Hanning, Uta

2017-01-01

Background and Purpose Blend sign (BS) and black hole sign (BHS) on non-contrast computed tomography (NCCT) and spot sign (SS) on CT-angiography (CTA) are indicators of early hematoma expansion in spontaneous intracerebral hemorrhage (ICH). However, their independent contributions to outcome have not been well explored. Methods In this retrospective study, inclusion criteria were: 1) spontaneous ICH and 2) NCCT and CTA performed on admission within 6 hours after onset of symptoms. Discharge outcome was dichotomized as good (modified Rankin Scale [mRS] 0-3) and poor (mRS 4-6) outcomes. The impacts of BHS, BS and SS on outcome were assessed in univariate and multivariable logistic regression models. Results Of 182 patients with spontaneous ICH, 26 (14.3%) presented with BHS, 37 (20.3%) with BS and 39 (21.4%) with SS. There was a substantial correlation between SS and BS (κ=0.701) and a moderate correlation between SS and BHS (κ=0.424). In univariable logistic regression, higher baseline hematoma volume (P<0.001), intraventricular hemorrhage (P=0.002) and the presence of BHS/BS/SS (all P<0.001) on admission CT scan were associated with poor outcome. Multivariable analysis identified intraventricular haemorrhage (odds ratio [OR] 2.22 per mL, P=0.022), baseline hematoma volume (OR 1.03 per mL, P<0.001) and SS on CTA (OR 11.43, P<0.001) as independent predictors of poor outcome, showing that SS compared to BS and BHS was more powerful to predict poor outcome. Conclusions The NCCT BHS and BS are correlated with the CTA SS and are reliable predictors of poor outcome in patients with ICH. Of the CT variables indicating early hematoma expansion, SS on CTA was the most reliable outcome predictor. However, given their correlation with SS on CTA, BS and BHS on NCCT can be useful for predicting outcome if CTA is not obtainable. PMID:29037015

Comparison of Spot Sign, Blend Sign and Black Hole Sign for Outcome Prediction in Patients with Intracerebral Hemorrhage.

PubMed

Sporns, Peter B; Schwake, Michael; Kemmling, André; Minnerup, Jens; Schwindt, Wolfram; Niederstadt, Thomas; Schmidt, Rene; Hanning, Uta

2017-09-01

Blend sign (BS) and black hole sign (BHS) on non-contrast computed tomography (NCCT) and spot sign (SS) on CT-angiography (CTA) are indicators of early hematoma expansion in spontaneous intracerebral hemorrhage (ICH). However, their independent contributions to outcome have not been well explored. In this retrospective study, inclusion criteria were: 1) spontaneous ICH and 2) NCCT and CTA performed on admission within 6 hours after onset of symptoms. Discharge outcome was dichotomized as good (modified Rankin Scale [mRS] 0-3) and poor (mRS 4-6) outcomes. The impacts of BHS, BS and SS on outcome were assessed in univariate and multivariable logistic regression models. Of 182 patients with spontaneous ICH, 26 (14.3%) presented with BHS, 37 (20.3%) with BS and 39 (21.4%) with SS. There was a substantial correlation between SS and BS (κ=0.701) and a moderate correlation between SS and BHS (κ=0.424). In univariable logistic regression, higher baseline hematoma volume ( P <0.001), intraventricular hemorrhage ( P =0.002) and the presence of BHS/BS/SS (all P <0.001) on admission CT scan were associated with poor outcome. Multivariable analysis identified intraventricular haemorrhage (odds ratio [OR] 2.22 per mL, P =0.022), baseline hematoma volume (OR 1.03 per mL, P <0.001) and SS on CTA (OR 11.43, P <0.001) as independent predictors of poor outcome, showing that SS compared to BS and BHS was more powerful to predict poor outcome. The NCCT BHS and BS are correlated with the CTA SS and are reliable predictors of poor outcome in patients with ICH. Of the CT variables indicating early hematoma expansion, SS on CTA was the most reliable outcome predictor. However, given their correlation with SS on CTA, BS and BHS on NCCT can be useful for predicting outcome if CTA is not obtainable.

Correspondence between the CYP2C19 and CYP3A4 genotypes with the inferred metabolizer phenotype by omeprazole administration in Mexican healthy children.

PubMed

Favela-Mendoza, A F; Martínez-Cortes, G; Romero-Prado, M M; Romero-Tejeda, E M; Islas-Carbajal, M C; Sosa-Macias, M; Lares-Asseff, I; Rangel-Villalobos, H

2018-05-07

CYP2C19 genotypes presumably allow the prediction of the metabolizer phenotypes: poor (PMs), extensive (EMs) and ultra-rapid (UMs). However, evidence from previous studies regarding this predictive power is unclear, which is important because the benefits expected by healthcare institutions and patients are based on this premise. Therefore, we aimed to complete a formal evaluation of the diagnostic value of CYP2C19 and CYP3A4 genes for predicting metabolizer phenotypes established by omeprazole (OME) administration in 118 healthy children from Jalisco (western Mexico). The genotypes for CYP3A4*1B and CYP2C19*2, *3, *4, *5 and *17 alleles were determined. CYP2C19 and CYP3A4 phenotypes were obtained after 20 mg OME administration and HPLC quantification in plasma to estimate the Hydroxylation Index (HI = OME/HOME) and Sulfonation Index (SI = OME/SOME), respectively. The distribution of genotypes and phenotypes for CYP2C19 and CYP3A4 was similar to previous studies in Mexico and Latin America. We estimated the CYP2C19 UM, EM and PM phenotype frequency in 0.84%, 96.61% and 2.54%, respectively. Although differences in the HI distribution were observed between CYP2C19 genotypes, they showed a poor diagnostic ability to predict the CYP2C19 metabolizer phenotype. Similarly, the number of CYP2C19 and CYP3A4 functional alleles was correlated with the HI distribution, but also their diagnostic ability to predict the CYP2C19 phenotype was poor. The CYP2C19 phenotype is not predicted by the number of functional alleles of CYP2C19 and CYP3A4 genes. Phenotyping is still the most valuable alternative to dose individualization for CYP2C19 substrate drugs. © 2018 John Wiley & Sons Ltd.

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.

Radioallergosorbent testing for penicillin allergy in family practice.

PubMed Central

Worrall, G J; Hull, C; Briffett, E

1994-01-01

OBJECTIVES: To determine (a) the prevalence of patients supposedly allergic to penicillin who have a positive radioallergosorbent test (RAST) result for penicillin G or V and (b) the predictive power of family physicians' clinical judgement that a patient who is supposedly allergic to penicillin will have a positive RAST result. DESIGN: Prospective multicentre cross-sectional observational study. SETTING: Eleven primary care practices in Newfoundland; 10 were in a rural setting. PATIENTS: Of 110 consecutive adult patients with a supposed allergy to penicillin 97 agreed to participate in the study; 92 underwent RAST. INTERVENTIONS: Patients helped physicians complete a questionnaire and had a venous blood sample taken for the RAST. Physicians examined the clinical history and judged whether the patient was likely to have a positive RAST result. MEAN OUTCOME MEASURES: Rates of positive and negative RAST results for penicillin V and G. RESULTS: Of the 92 patients 8 had a positive RAST result and 84 a negative one. The positive predictive power of a "good" clinical history (e.g., urticaria, swollen eyes, tongue or lips, or an anaphylactic reaction witnessed by a physician) was low (10%); the negative predictive power of a "poor" clinical history (e.g., nausea, vomiting, diarrhea, fever, nonspecific rash or fainting) was 92%. CONCLUSIONS: Less than 10% of primary care patients with a supposed allergy to penicillin will have a positive RAST result. In addition, physicians' predictions of allergy in such patients are imprecise. PMID:8275407

Quantitative power Doppler ultrasound measures of peripheral joint synovitis in poor prognosis early rheumatoid arthritis predict radiographic progression.

PubMed

Sreerangaiah, Dee; Grayer, Michael; Fisher, Benjamin A; Ho, Meilien; Abraham, Sonya; Taylor, Peter C

2016-01-01

To assess the value of quantitative vascular imaging by power Doppler US (PDUS) as a tool that can be used to stratify patient risk of joint damage in early seropositive RA while still biologic naive but on synthetic DMARD treatment. Eighty-five patients with seropositive RA of <3 years duration had clinical, laboratory and imaging assessments at 0 and 12 months. Imaging assessments consisted of radiographs of the hands and feet, two-dimensional (2D) high-frequency and PDUS imaging of 10 MCP joints that were scored for erosions and vascularity and three-dimensional (3D) PDUS of MCP joints and wrists that were scored for vascularity. Severe deterioration on radiographs and ultrasonography was seen in 45 and 28% of patients, respectively. The 3D power Doppler volume and 2D vascularity scores were the most useful US predictors of deterioration. These variables were modelled in two equations that estimate structural damage over 12 months. The equations had a sensitivity of 63.2% and specificity of 80.9% for predicting radiographic structural damage and a sensitivity of 54.2% and specificity of 96.7% for predicting structural damage on ultrasonography. In seropositive early RA, quantitative vascular imaging by PDUS has clinical utility in predicting which patients will derive benefit from early use of biologic therapy. © The Author 2015. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Lateralization in Alpha-Band Oscillations Predicts the Locus and Spatial Distribution of Attention.

PubMed

Ikkai, Akiko; Dandekar, Sangita; Curtis, Clayton E

2016-01-01

Attending to a task-relevant location changes how neural activity oscillates in the alpha band (8-13Hz) in posterior visual cortical areas. However, a clear understanding of the relationships between top-down attention, changes in alpha oscillations in visual cortex, and attention performance are still poorly understood. Here, we tested the degree to which the posterior alpha power tracked the locus of attention, the distribution of attention, and how well the topography of alpha could predict the locus of attention. We recorded magnetoencephalographic (MEG) data while subjects performed an attention demanding visual discrimination task that dissociated the direction of attention from the direction of a saccade to indicate choice. On some trials, an endogenous cue predicted the target's location, while on others it contained no spatial information. When the target's location was cued, alpha power decreased in sensors over occipital cortex contralateral to the attended visual field. When the cue did not predict the target's location, alpha power again decreased in sensors over occipital cortex, but bilaterally, and increased in sensors over frontal cortex. Thus, the distribution and the topography of alpha reliably indicated the locus of covert attention. Together, these results suggest that alpha synchronization reflects changes in the excitability of populations of neurons whose receptive fields match the locus of attention. This is consistent with the hypothesis that alpha oscillations reflect the neural mechanisms by which top-down control of attention biases information processing and modulate the activity of neurons in visual cortex.

Preschool Neuropsychological Measures as Predictors of Later Attention Deficit Hyperactivity Disorder

PubMed Central

Breaux, Rosanna P.; Griffith, Shayl F.; Harvey, Elizabeth A.

2016-01-01

The present study examined preschool neuropsychological measures as predictors of school-age attention deficit hyperactivity disorder (ADHD). Participants included 168 children (91 males) who completed neuropsychological measures at ages 3 and 4, and who were evaluated for ADHD and oppositional defiant disorder at age 6. The Conners’ Kiddie Continuous Performance Test (K-CPT), NEPSY Statue subtest, and a delay aversion task significantly distinguished at-risk children who later did and did not meet criteria for ADHD, with poor to fair overall predictive power, specificity, and sensitivity. However, only the K-CPT ADHD Confidence Index and battery added incremental predictive validity beyond early ADHD symptoms. This battery approach, which required impairment on at least 2 of the 3 significant measures, yielded fair overall predictive power, specificity, and sensitivity, and correctly classified 67% of children. In addition, there was some support for the specificity hypothesis, with evidence that cool executive function measures (K-CPT and Statue subtest) tended to predict inattentive symptoms. These findings suggest that neuropsychological deficits are evident by preschool-age in children with ADHD, but neuropsychological tests may still misclassify approximately one-third of children if used alone. Thus, neuropsychological measures may be a useful component of early ADHD assessments, but should be used with caution and in combination with other assessment methods. PMID:26936037

The DSM-5 Self-Rated Level 1 Cross-Cutting Symptom Measure as a Screening Tool.

PubMed

Bastiaens, Leo; Galus, James

2018-03-01

The DSM-5 Self-Rated Level 1 Cross-Cutting Symptom Measure was developed to aid clinicians with a dimensional assessment of psychopathology; however, this measure resembles a screening tool for several symptomatic domains. The objective of the current study was to examine the basic parameters of sensitivity, specificity, positive and negative predictive power of the measure as a screening tool. One hundred and fifty patients in a correctional community center filled out the measure prior to a psychiatric evaluation, including the Mini International Neuropsychiatric Interview screen. The above parameters were calculated for the domains of depression, mania, anxiety, and psychosis. The results showed that the sensitivity and positive predictive power of the studied domains was poor because of a high rate of false positive answers on the measure. However, when the lowest threshold on the Cross-Cutting Symptom Measure was used, the sensitivity of the anxiety and psychosis domains and the negative predictive values for mania, anxiety and psychosis were good. In conclusion, while it is foreseeable that some clinicians may use the DSM-5 Self-Rated Level 1 Cross-Cutting Symptom Measure as a screening tool, it should not be relied on to identify positive findings. It functioned well in the negative prediction of mania, anxiety and psychosis symptoms.

A Large-scale Cross-sectional Study of ALK Rearrangements and EGFR Mutations in Non-small-cell Lung Cancer in Chinese Han Population

PubMed Central

Hong, Shaodong; Fang, Wenfeng; Hu, Zhihuang; Zhou, Ting; Yan, Yue; Qin, Tao; Tang, Yanna; Ma, Yuxiang; Zhao, Yuanyuan; Xue, Cong; Huang, Yan; Zhao, Hongyun; Zhang, Li

2014-01-01

The predictive power of age at diagnosis and smoking history for ALK rearrangements and EGFR mutations in non-small-cell lung cancer (NSCLC) remains not fully understood. In this cross-sectional study, 1160 NSCLC patients were prospectively enrolled and genotyped for EML4-ALK rearrangements and EGFR mutations. Multivariate logistic regression analysis was performed to explore the association between clinicopathological features and these two genetic aberrations. Receiver operating characteristic (ROC) curves methodology was applied to evaluate the predictive value. We showed that younger age at diagnosis was the only independent variable associated with EML4-ALK rearrangements (odds ratio (OR) per 5 years' increment, 0.68; p < 0.001), while lower tobacco exposure (OR per 5 pack-years' increment, 0.88; p < 0.001), adenocarcinoma (OR, 6.61; p < 0.001), and moderate to high differentiation (OR, 2.05; p < 0.001) were independently associated with EGFR mutations. Age at diagnosis was a very strong predictor of ALK rearrangements but poorly predicted EGFR mutations, while smoking pack-years may predict the presence of EGFR mutations and ALK rearrangements but with rather limited power. These findings should assist clinicians in assessing the likelihood of EML4-ALK rearrangements and EGFR mutations and understanding their biological implications in NSCLC. PMID:25434695

Study to determine and improve design for lithium-doped solar cells

NASA Technical Reports Server (NTRS)

Brucker, G.; Faith, T. J.; Holmes-Siedle, A.

1971-01-01

Solar cell experiments show that a single lithium density parameter, the lithium density gradient, calculated from nondestructive capacitance measurements, provides the basis for accurate predictions of lithium cell behavior in a 1-MeV electron environment for fluences ranging between 3 X 10 to the 13th power e/sq cm and 3 X 10 to the 15th power/e sq cm. The oxygen-rich (quartz crucible) lithium cell with phosphorous starting dopant and lithium gradient between approximately 5 X 10 to the 18th power and 1.5 x 10 to the 19th power/cm to the 4th power was found superior in performance to the commercial 10 ohm-cm n/p control cells. Post-recovery stability of oxygen-rich cells was satisfactory. An average post-recovery current drop of approximately 1 mA was observed for 70 crucible cells after 1 year-equivalent storage time at 80 C. In contrast the oxygen-poor (float zone and Lopex) lithium cells displayed spotty initial performance and stability problems at room temperature.

Thermospheric mass density model error variance as a function of time scale

NASA Astrophysics Data System (ADS)

Emmert, J. T.; Sutton, E. K.

2017-12-01

In the increasingly crowded low-Earth orbit environment, accurate estimation of orbit prediction uncertainties is essential for collision avoidance. Poor characterization of such uncertainty can result in unnecessary and costly avoidance maneuvers (false positives) or disregard of a collision risk (false negatives). Atmospheric drag is a major source of orbit prediction uncertainty, and is particularly challenging to account for because it exerts a cumulative influence on orbital trajectories and is therefore not amenable to representation by a single uncertainty parameter. To address this challenge, we examine the variance of measured accelerometer-derived and orbit-derived mass densities with respect to predictions by thermospheric empirical models, using the data-minus-model variance as a proxy for model uncertainty. Our analysis focuses mainly on the power spectrum of the residuals, and we construct an empirical model of the variance as a function of time scale (from 1 hour to 10 years), altitude, and solar activity. We find that the power spectral density approximately follows a power-law process but with an enhancement near the 27-day solar rotation period. The residual variance increases monotonically with altitude between 250 and 550 km. There are two components to the variance dependence on solar activity: one component is 180 degrees out of phase (largest variance at solar minimum), and the other component lags 2 years behind solar maximum (largest variance in the descending phase of the solar cycle).

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.

Determinants of work ability and its predictive value for disability.

PubMed

Alavinia, S M; de Boer, A G E M; van Duivenbooden, J C; Frings-Dresen, M H W; Burdorf, A

2009-01-01

Maintaining the ability of workers to cope with physical and psychosocial demands at work becomes increasingly important in prolonging working life. To analyse the effects of work-related factors and individual characteristics on work ability and to determine the predictive value of work ability on receiving a work-related disability pension. A longitudinal study was conducted among 850 construction workers aged 40 years and older, with average follow-up period of 23 months. Disability was defined as receiving a disability pension, granted to workers unable to continue working in their regular job. Work ability was assessed using the work ability index (WAI). Associations between work-related factors and individual characteristics with work ability at baseline were evaluated using linear regression analysis, and Cox regression analysis was used to evaluate the predictive value of work ability for disability. Work-related factors were associated with a lower work ability at baseline, but had little prognostic value for disability during follow-up. The hazard ratios for disability among workers with a moderate and poor work ability at baseline were 8 and 32, respectively. All separate scales in the WAI had predictive power for future disability with the highest influence of current work ability in relation to job demands and lowest influence of diseases diagnosed by a physician. A moderate or poor work ability was highly predictive for receiving a disability pension. Preventive measures should facilitate a good balance between work performance and health in order to prevent quitting labour participation.

Cerebral oxygenation in traumatic brain injury; Can a non-invasive frequency domain near-infrared spectroscopy device detect changes in brain tissue oxygen tension as well as the established invasive monitor?

PubMed

Davies, David James; Clancy, Michael; Dehghani, Hamid; Lucas, Samuel John Edwin; Forcione, Mario; Yakoub, Kamal Makram; Belli, Antonio

2018-06-07

The cost and highly invasive nature of brain monitoring modality in traumatic brain injury patients currently restrict its utility to specialist neurological intensive care settings. We aim to test the abilities of a frequency domain near-infrared spectroscopy (FD-NIRS) device in predicting changes in invasively measured brain tissue oxygen tension. Individuals admitted to a United Kingdom specialist major trauma centre were contemporaneously monitored with an FD-NIRS device and invasively measured brain tissue oxygen tension probe. Area under the curve receiver operating characteristic (AUROC) statistical analysis was utilised to assess the predictive power of FD-NIRS in detecting both moderate and severe hypoxia (20 and 10 mmHg, respectively), as measured invasively. 16 individuals were prospectively recruited to the investigation. Severe hypoxic episodes were detected in 9 of these individuals, with the NIRS demonstrating a broad range of predictive abilities (AUROC 0.68-0.88) from relatively poor to good. Moderate hypoxic episodes were detected in seven individuals with similar predictive performance (AUROC 0.576 - 0.905). A variable performance in the predictive powers of this FD-NIRS device to detect changes in brain tissue oxygen was demonstrated. Consequently, this enhanced NIRS technology has not demonstrated sufficient ability to replace the established invasive measurement.

Investigation of Rotor Performance and Loads of a UH-60A Individual Blade Control System

NASA Technical Reports Server (NTRS)

Yeo, Hyeonsoo; Romander, Ethan A.; Norman, Thomas R.

2011-01-01

Wind tunnel measurements of performance, loads, and vibration of a full-scale UH-60A Black Hawk main rotor with an individual blade control (IBC) system are compared with calculations obtained using the comprehensive helicopter analysis CAMRAD II and a coupled CAMRAD II/OVERFLOW 2 analysis. Measured data show a 5.1% rotor power reduction (8.6% rotor lift to effective-drag ratio increase) using 2/rev IBC actuation with 2.0 amplitude at = 0.4. At the optimum IBC phase for rotor performance, IBC actuator force (pitch link force) decreased, and neither flap nor chord bending moments changed significantly. CAMRAD II predicts the rotor power variations with the IBC phase reasonably well at = 0.35. However, the correlation degrades at = 0.4. Coupled CAMRAD II/OVERFLOW 2 shows excellent correlation with the measured rotor power variations with the IBC phase at both = 0.35 and = 0.4. Maximum reduction of IBC actuator force is better predicted with CAMRAD II, but general trends are better captured with the coupled analysis. The correlation of vibratory hub loads is generally poor by both methods, although the coupled analysis somewhat captures general trends.

Investigation of Rotor Performance and Loads of a UH-60A Individual Blade Control System

NASA Technical Reports Server (NTRS)

Yeo, Hyeonsoo; Romander, Ethan A.; Norman, Thomas R.

2011-01-01

Wind tunnel measurements of performance, loads, and vibration of a full-scale UH-60A Black Hawk main rotor with an individual blade control (IBC) system are compared with calculations obtained using the comprehensive helicopter analysis CAMRAD II and a coupled CAMRAD II/OVERFLOW 2 analysis. Measured data show a 5.1% rotor power reduction (8.6% rotor lift to effective-drag ratio increase) using 2/rev IBC actuation with 2.0. amplitude at u = 0.4. At the optimum IBC phase for rotor performance, IBC actuator force (pitch link force) decreased, and neither flap nor chord bending moments changed significantly. CAMRAD II predicts the rotor power variations with IBC phase reasonably well at u = 0.35. However, the correlation degrades at u = 0.4. Coupled CAMRAD II/OVERFLOW 2 shows excellent correlation with the measured rotor power variations with IBC phase at both u = 0.35 and u = 0.4. Maximum reduction of IBC actuator force is better predicted with CAMRAD II, but general trends are better captured with the coupled analysis. The correlation of vibratory hub loads is generally poor by both methods, although the coupled analysis somewhat captures general trends.

Predicting nutrient excretion of aquatic animals with metabolic ecology and ecological stoichiometry: a global synthesis.

PubMed

Vanni, Michael J; McIntyre, Peter B

2016-12-01

The metabolic theory of ecology (MTE) and ecological stoichiometry (ES) are both prominent frameworks for understanding energy and nutrient budgets of organisms. We tested their separate and joint power to predict nitrogen (N) and phosphorus (P) excretion rates of ectothermic aquatic invertebrate and vertebrate animals (10,534 observations worldwide). MTE variables (body size, temperature) performed better than ES variables (trophic guild, vertebrate classification, body N:P) in predicting excretion rates, but the best models included variables from both frameworks. Size scaling coefficients were significantly lower than predicted by MTE (<0.75), were lower for P than N, and varied greatly among species. Contrary to expectations under ES, vertebrates excreted both N and P at higher rates than invertebrates despite having more nutrient-rich bodies, and primary consumers excreted as much nutrients as carnivores despite having nutrient-poor diets. Accounting for body N:P hardly improved upon predictions from treating vertebrate classification categorically. We conclude that basic data on body size, water temperature, trophic guild, and vertebrate classification are sufficient to make general estimates of nutrient excretion rates for any animal taxon or aquatic ecosystem. Nonetheless, dramatic interspecific variation in size-scaling coefficients and counter-intuitive patterns with respect to diet and body composition underscore the need for field data on consumption and egestion rates. Together, MTE and ES provide a powerful conceptual basis for interpreting and predicting nutrient recycling rates of aquatic animals worldwide. © 2016 by the Ecological Society of America.

Robust regression and posterior predictive simulation increase power to detect early bursts of trait evolution.

PubMed

Slater, Graham J; Pennell, Matthew W

2014-05-01

A central prediction of much theory on adaptive radiations is that traits should evolve rapidly during the early stages of a clade's history and subsequently slowdown in rate as niches become saturated--a so-called "Early Burst." Although a common pattern in the fossil record, evidence for early bursts of trait evolution in phylogenetic comparative data has been equivocal at best. We show here that this may not necessarily be due to the absence of this pattern in nature. Rather, commonly used methods to infer its presence perform poorly when when the strength of the burst--the rate at which phenotypic evolution declines--is small, and when some morphological convergence is present within the clade. We present two modifications to existing comparative methods that allow greater power to detect early bursts in simulated datasets. First, we develop posterior predictive simulation approaches and show that they outperform maximum likelihood approaches at identifying early bursts at moderate strength. Second, we use a robust regression procedure that allows for the identification and down-weighting of convergent taxa, leading to moderate increases in method performance. We demonstrate the utility and power of these approach by investigating the evolution of body size in cetaceans. Model fitting using maximum likelihood is equivocal with regards the mode of cetacean body size evolution. However, posterior predictive simulation combined with a robust node height test return low support for Brownian motion or rate shift models, but not the early burst model. While the jury is still out on whether early bursts are actually common in nature, our approach will hopefully facilitate more robust testing of this hypothesis. We advocate the adoption of similar posterior predictive approaches to improve the fit and to assess the adequacy of macroevolutionary models in general.

Validation of the MARS: a combined physiological and laboratory risk prediction tool for 5- to 7-day in-hospital mortality.

PubMed

Öhman, M C; Atkins, T E H; Cooksley, T; Brabrand, M

2018-06-01

The Medical Admission Risk System (MARS) uses 11 physiological and laboratory data and had promising results in its derivation study for predicting 5- and 7- day mortality. To perform an external independent validation of the MARS score. An unplanned secondary cohort study. Patients admitted to the medical admission unit at The Hospital of South West Jutland were included from 2 October 2008 until 19 February 2009 and 23 February 2010 until 26 May 2010 were analysed. Validation of the MARS scores using 5- and 7- day mortality was the primary endpoint. Patients of 5858 were included in the study. Patients of 2923 (49.9%) were women with a median age of 65 years (15-107). The MARS score had an area under the receiving operator characteristic curve of 0.858 (95% CI: 0.831-0.884) for 5-day mortality and 0.844 (0.818-0.870) for 7 day mortality with poor calibration for both outcomes. The MARS score had excellent discriminatory power but poor calibration in predicting both 5- and 7-day mortality. The development of accurate combination physiological/laboratory data risk scores has the potential to improve the recognition of at risk patients.

Lateralization in Alpha-Band Oscillations Predicts the Locus and Spatial Distribution of Attention

PubMed Central

Ikkai, Akiko; Dandekar, Sangita; Curtis, Clayton E.

2016-01-01

Attending to a task-relevant location changes how neural activity oscillates in the alpha band (8–13Hz) in posterior visual cortical areas. However, a clear understanding of the relationships between top-down attention, changes in alpha oscillations in visual cortex, and attention performance are still poorly understood. Here, we tested the degree to which the posterior alpha power tracked the locus of attention, the distribution of attention, and how well the topography of alpha could predict the locus of attention. We recorded magnetoencephalographic (MEG) data while subjects performed an attention demanding visual discrimination task that dissociated the direction of attention from the direction of a saccade to indicate choice. On some trials, an endogenous cue predicted the target’s location, while on others it contained no spatial information. When the target’s location was cued, alpha power decreased in sensors over occipital cortex contralateral to the attended visual field. When the cue did not predict the target’s location, alpha power again decreased in sensors over occipital cortex, but bilaterally, and increased in sensors over frontal cortex. Thus, the distribution and the topography of alpha reliably indicated the locus of covert attention. Together, these results suggest that alpha synchronization reflects changes in the excitability of populations of neurons whose receptive fields match the locus of attention. This is consistent with the hypothesis that alpha oscillations reflect the neural mechanisms by which top-down control of attention biases information processing and modulate the activity of neurons in visual cortex. PMID:27144717

Fast, scalable prediction of deleterious noncoding variants from functional and population genomic data.

PubMed

Huang, Yi-Fei; Gulko, Brad; Siepel, Adam

2017-04-01

Many genetic variants that influence phenotypes of interest are located outside of protein-coding genes, yet existing methods for identifying such variants have poor predictive power. Here we introduce a new computational method, called LINSIGHT, that substantially improves the prediction of noncoding nucleotide sites at which mutations are likely to have deleterious fitness consequences, and which, therefore, are likely to be phenotypically important. LINSIGHT combines a generalized linear model for functional genomic data with a probabilistic model of molecular evolution. The method is fast and highly scalable, enabling it to exploit the 'big data' available in modern genomics. We show that LINSIGHT outperforms the best available methods in identifying human noncoding variants associated with inherited diseases. In addition, we apply LINSIGHT to an atlas of human enhancers and show that the fitness consequences at enhancers depend on cell type, tissue specificity, and constraints at associated promoters.

The Power of Poor Communications

ERIC Educational Resources Information Center

Schaub, Alfred R.

1975-01-01

Most breakdowns in communications are the result of the quest for power on behalf of organization members, not the result of poor communications training. Organizational power may be accrued by withholding information, sabotaging communications, refusing to communicate bad news to superiors, and avoiding confrontations by not communicating at all.…

Functional status and mortality prediction in community-acquired pneumonia.

PubMed

Jeon, Kyeongman; Yoo, Hongseok; Jeong, Byeong-Ho; Park, Hye Yun; Koh, Won-Jung; Suh, Gee Young; Guallar, Eliseo

2017-10-01

Poor functional status (FS) has been suggested as a poor prognostic factor in both pneumonia and severe pneumonia in elderly patients. However, it is still unclear whether FS is associated with outcomes and improves survival prediction in community-acquired pneumonia (CAP) in the general population. Data on hospitalized patients with CAP and FS, assessed by the Eastern Cooperative Oncology Group (ECOG) scale were prospectively collected between January 2008 and December 2012. The independent association of FS with 30-day mortality in CAP patients was evaluated using multivariable logistic regression. Improvement in mortality prediction when FS was added to the CRB-65 (confusion, respiratory rate, blood pressure and age 65) score was evaluated for discrimination, reclassification and calibration. The 30-day mortality of study participants (n = 1526) was 10%. Mortality significantly increased with higher ECOG score (P for trend <0.001). In multivariable analysis, ECOG ≥3 was strongly associated with 30-day mortality (adjusted OR: 5.70; 95% CI: 3.82-8.50). Adding ECOG ≥3 significantly improved the discriminatory power of CRB-65. Reclassification indices also confirmed the improvement in discrimination ability when FS was combined with the CRB-65, with a categorized net reclassification index (NRI) of 0.561 (0.437-0.686), a continuous NRI of 0.858 (0.696-1.019) and a relative integrated discrimination improvement in the discrimination slope of 139.8 % (110.8-154.6). FS predicted 30-day mortality and improved discrimination and reclassification in consecutive CAP patients. Assessment of premorbid FS should be considered in mortality prediction in patients with CAP. © 2017 Asian Pacific Society of Respirology.

Power Calculations to Select Instruments for Clinical Trial Secondary Endpoints. A Case Study of Instrument Selection for Post-Traumatic Stress Symptoms in Subjects with Acute Respiratory Distress Syndrome.

PubMed

Sjoding, Michael W; Schoenfeld, David A; Brown, Samuel M; Hough, Catherine L; Yealy, Donald M; Moss, Marc; Angus, Derek C; Iwashyna, Theodore J

2017-01-01

After the sample size of a randomized clinical trial (RCT) is set by the power requirement of its primary endpoint, investigators select secondary endpoints while unable to further adjust sample size. How the sensitivity and specificity of an instrument used to measure these outcomes, together with their expected underlying event rates, affect an RCT's power to measure significant differences in these outcomes is poorly understood. Motivated by the design of an RCT of neuromuscular blockade in acute respiratory distress syndrome, we examined how power to detect a difference in secondary endpoints varies with the sensitivity and specificity of the instrument used to measure such outcomes. We derived a general formula and Stata code for calculating an RCT's power to detect differences in binary outcomes when such outcomes are measured with imperfect sensitivity and specificity. The formula informed the choice of instrument for measuring post-traumatic stress-like symptoms in the Reevaluation of Systemic Early Neuromuscular Blockade RCT ( www.clinicaltrials.gov identifier NCT02509078). On the basis of published sensitivities and specificities, the Impact of Events Scale-Revised was predicted to measure a 36% symptom rate, whereas the Post-Traumatic Stress Symptoms instrument was predicted to measure a 23% rate, if the true underlying rate of post-traumatic stress symptoms were 25%. Despite its lower sensitivity, the briefer Post-Traumatic Stress Symptoms instrument provided superior power to detect a difference in rates between trial arms, owing to its higher specificity. Examining instruments' power to detect differences in outcomes may guide their selection when multiple instruments exist, each with different sensitivities and specificities.

Power Calculations to Select Instruments for Clinical Trial Secondary Endpoints. A Case Study of Instrument Selection for Post-Traumatic Stress Symptoms in Subjects with Acute Respiratory Distress Syndrome

PubMed Central

Schoenfeld, David A.; Brown, Samuel M.; Hough, Catherine L.; Yealy, Donald M.; Moss, Marc; Angus, Derek C.; Iwashyna, Theodore J.

2017-01-01

Rationale: After the sample size of a randomized clinical trial (RCT) is set by the power requirement of its primary endpoint, investigators select secondary endpoints while unable to further adjust sample size. How the sensitivity and specificity of an instrument used to measure these outcomes, together with their expected underlying event rates, affect an RCT’s power to measure significant differences in these outcomes is poorly understood. Objectives: Motivated by the design of an RCT of neuromuscular blockade in acute respiratory distress syndrome, we examined how power to detect a difference in secondary endpoints varies with the sensitivity and specificity of the instrument used to measure such outcomes. Methods: We derived a general formula and Stata code for calculating an RCT’s power to detect differences in binary outcomes when such outcomes are measured with imperfect sensitivity and specificity. The formula informed the choice of instrument for measuring post-traumatic stress–like symptoms in the Reevaluation of Systemic Early Neuromuscular Blockade RCT (www.clinicaltrials.gov identifier NCT02509078). Measurements and Main Results: On the basis of published sensitivities and specificities, the Impact of Events Scale-Revised was predicted to measure a 36% symptom rate, whereas the Post-Traumatic Stress Symptoms instrument was predicted to measure a 23% rate, if the true underlying rate of post-traumatic stress symptoms were 25%. Despite its lower sensitivity, the briefer Post-Traumatic Stress Symptoms instrument provided superior power to detect a difference in rates between trial arms, owing to its higher specificity. Conclusions: Examining instruments’ power to detect differences in outcomes may guide their selection when multiple instruments exist, each with different sensitivities and specificities. PMID:27788018

Mercury capture within coal-fired power plant electrostatic precipitators: model evaluation.

PubMed

Clack, Herek L

2009-03-01

Efforts to reduce anthropogenic mercury emissions worldwide have recently focused on a variety of sources, including mercury emitted during coal combustion. Toward that end, much research has been ongoing seeking to develop new processes for reducing coal combustion mercury emissions. Among air pollution control processes that can be applied to coal-fired boilers, electrostatic precipitators (ESPs) are by far the most common, both on a global scale and among the principal countries of India, China, and the U.S. that burn coal for electric power generation. A previously reported theoretical model of in-flight mercury capture within ESPs is herein evaluated against data from a number of full-scale tests of activated carbon injection for mercury emissions control. By using the established particle size distribution of the activated carbon and actual or estimated values of its equilibrium mercury adsorption capacity, the incremental reduction in mercury concentration across each ESP can be predicted and compared to experimental results. Because the model does not incorporate kinetics associated with gas-phase mercury transformation or surface adsorption, the model predictions representthe mass-transfer-limited performance. Comparing field data to model results reveals many facilities performing at or near the predicted mass-transfer-limited maximum, particularly at low rates of sorbent injection. Where agreement is poor between field data and model predictions, additional chemical or physical phenomena may be responsible for reducing mercury removal efficiencies.

Tree Morphologic Plasticity Explains Deviation from Metabolic Scaling Theory in Semi-Arid Conifer Forests, Southwestern USA

PubMed Central

O’Connor, Christopher D.; Lynch, Ann M.

2016-01-01

A significant concern about Metabolic Scaling Theory (MST) in real forests relates to consistent differences between the values of power law scaling exponents of tree primary size measures used to estimate mass and those predicted by MST. Here we consider why observed scaling exponents for diameter and height relationships deviate from MST predictions across three semi-arid conifer forests in relation to: (1) tree condition and physical form, (2) the level of inter-tree competition (e.g. open vs closed stand structure), (3) increasing tree age, and (4) differences in site productivity. Scaling exponent values derived from non-linear least-squares regression for trees in excellent condition (n = 381) were above the MST prediction at the 95% confidence level, while the exponent for trees in good condition were no different than MST (n = 926). Trees that were in fair or poor condition, characterized as diseased, leaning, or sparsely crowned had exponent values below MST predictions (n = 2,058), as did recently dead standing trees (n = 375). Exponent value of the mean-tree model that disregarded tree condition (n = 3,740) was consistent with other studies that reject MST scaling. Ostensibly, as stand density and competition increase trees exhibited greater morphological plasticity whereby the majority had characteristically fair or poor growth forms. Fitting by least-squares regression biases the mean-tree model scaling exponent toward values that are below MST idealized predictions. For 368 trees from Arizona with known establishment dates, increasing age had no significant impact on expected scaling. We further suggest height to diameter ratios below MST relate to vertical truncation caused by limitation in plant water availability. Even with environmentally imposed height limitation, proportionality between height and diameter scaling exponents were consistent with the predictions of MST. PMID:27391084

Tree Morphologic Plasticity Explains Deviation from Metabolic Scaling Theory in Semi-Arid Conifer Forests, Southwestern USA.

PubMed

Swetnam, Tyson L; O'Connor, Christopher D; Lynch, Ann M

2016-01-01

A significant concern about Metabolic Scaling Theory (MST) in real forests relates to consistent differences between the values of power law scaling exponents of tree primary size measures used to estimate mass and those predicted by MST. Here we consider why observed scaling exponents for diameter and height relationships deviate from MST predictions across three semi-arid conifer forests in relation to: (1) tree condition and physical form, (2) the level of inter-tree competition (e.g. open vs closed stand structure), (3) increasing tree age, and (4) differences in site productivity. Scaling exponent values derived from non-linear least-squares regression for trees in excellent condition (n = 381) were above the MST prediction at the 95% confidence level, while the exponent for trees in good condition were no different than MST (n = 926). Trees that were in fair or poor condition, characterized as diseased, leaning, or sparsely crowned had exponent values below MST predictions (n = 2,058), as did recently dead standing trees (n = 375). Exponent value of the mean-tree model that disregarded tree condition (n = 3,740) was consistent with other studies that reject MST scaling. Ostensibly, as stand density and competition increase trees exhibited greater morphological plasticity whereby the majority had characteristically fair or poor growth forms. Fitting by least-squares regression biases the mean-tree model scaling exponent toward values that are below MST idealized predictions. For 368 trees from Arizona with known establishment dates, increasing age had no significant impact on expected scaling. We further suggest height to diameter ratios below MST relate to vertical truncation caused by limitation in plant water availability. Even with environmentally imposed height limitation, proportionality between height and diameter scaling exponents were consistent with the predictions of MST.

Clinical value of the VMI supplemental tests: a modified replication study.

PubMed

Avi-Itzhak, Tamara; Obler, Doris Richard

2008-10-01

To carry out a modified replication of the study performed by Kulp and Sortor evaluating the clinical value of the information provided by Beery's visual-motor supplemental tests of Visual Perception (VP) and Motor Coordination (MC) in normally developed children. The objectives were to (a) estimate the correlations among the three tests scores; (b) assess the predictive power of the VP and MC scores in explaining the variance in Visual-Motor Integration (VMI) scores; and (c) examine whether poor performance on the VMI is related to poor performance on VP or MC. METHODS.: A convenience sample of 71 children ages 4 and 5 years (M = 4.62 +/- 0.43) participated in the study. The supplemental tests significantly (F = 9.59; dF = 2; p < or = 0. 001) explained 22% of the variance in VMI performance. Only VP was significantly related to VMI (beta = 0.39; T = 3.49) accounting for the total amount of explained variance. Using the study population norms, 11 children (16% of total sample) did poorly on the VMI; of those 11, 73% did poorly on the VP, and none did poorly on the MC. None of these 11 did poorly on both the VP and MC. Nine percent of total sample who did poorly on the VP performed within the norm on the VMI. Thirteen percent who performed poorly on the MC performed within the norm on the VMI. Using the VMI published norms, 14 children (20% of total sample) who did poorly on the VP performed within the norm on the VMI. Forty-eight percent who did poorly on MC performed within the norm on the VMI. Findings supported Kulp and Sortor's conclusions that each area should be individually evaluated during visual-perceptual assessment of children regardless of performance on the VMI.

Multiphysics Computational Analysis of a Solid-Core Nuclear Thermal Engine Thrust Chamber

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Canabal, Francisco; Cheng, Gary; Chen, Yen-Sen

2007-01-01

The objective of this effort is to develop an efficient and accurate computational heat transfer methodology to predict thermal, fluid, and hydrogen environments for a hypothetical solid-core, nuclear thermal engine - the Small Engine. In addition, the effects of power profile and hydrogen conversion on heat transfer efficiency and thrust performance were also investigated. The computational methodology is based on an unstructured-grid, pressure-based, all speeds, chemically reacting, computational fluid dynamics platform, while formulations of conjugate heat transfer were implemented to describe the heat transfer from solid to hydrogen inside the solid-core reactor. The computational domain covers the entire thrust chamber so that the afore-mentioned heat transfer effects impact the thrust performance directly. The result shows that the computed core-exit gas temperature, specific impulse, and core pressure drop agree well with those of design data for the Small Engine. Finite-rate chemistry is very important in predicting the proper energy balance as naturally occurring hydrogen decomposition is endothermic. Locally strong hydrogen conversion associated with centralized power profile gives poor heat transfer efficiency and lower thrust performance. On the other hand, uniform hydrogen conversion associated with a more uniform radial power profile achieves higher heat transfer efficiency, and higher thrust performance.

Intracranial mapping of auditory perception: event-related responses and electrocortical stimulation.

PubMed

Sinai, A; Crone, N E; Wied, H M; Franaszczuk, P J; Miglioretti, D; Boatman-Reich, D

2009-01-01

We compared intracranial recordings of auditory event-related responses with electrocortical stimulation mapping (ESM) to determine their functional relationship. Intracranial recordings and ESM were performed, using speech and tones, in adult epilepsy patients with subdural electrodes implanted over lateral left cortex. Evoked N1 responses and induced spectral power changes were obtained by trial averaging and time-frequency analysis. ESM impaired perception and comprehension of speech, not tones, at electrode sites in the posterior temporal lobe. There was high spatial concordance between ESM sites critical for speech perception and the largest spectral power (100% concordance) and N1 (83%) responses to speech. N1 responses showed good sensitivity (0.75) and specificity (0.82), but poor positive predictive value (0.32). Conversely, increased high-frequency power (>60Hz) showed high specificity (0.98), but poorer sensitivity (0.67) and positive predictive value (0.67). Stimulus-related differences were observed in the spatial-temporal patterns of event-related responses. Intracranial auditory event-related responses to speech were associated with cortical sites critical for auditory perception and comprehension of speech. These results suggest that the distribution and magnitude of intracranial auditory event-related responses to speech reflect the functional significance of the underlying cortical regions and may be useful for pre-surgical functional mapping.

Intracranial mapping of auditory perception: Event-related responses and electrocortical stimulation

PubMed Central

Sinai, A.; Crone, N.E.; Wied, H.M.; Franaszczuk, P.J.; Miglioretti, D.; Boatman-Reich, D.

2010-01-01

Objective We compared intracranial recordings of auditory event-related responses with electrocortical stimulation mapping (ESM) to determine their functional relationship. Methods Intracranial recordings and ESM were performed, using speech and tones, in adult epilepsy patients with subdural electrodes implanted over lateral left cortex. Evoked N1 responses and induced spectral power changes were obtained by trial averaging and time-frequency analysis. Results ESM impaired perception and comprehension of speech, not tones, at electrode sites in the posterior temporal lobe. There was high spatial concordance between ESM sites critical for speech perception and the largest spectral power (100% concordance) and N1 (83%) responses to speech. N1 responses showed good sensitivity (0.75) and specificity (0.82), but poor positive predictive value (0.32). Conversely, increased high-frequency power (>60 Hz) showed high specificity (0.98), but poorer sensitivity (0.67) and positive predictive value (0.67). Stimulus-related differences were observed in the spatial-temporal patterns of event-related responses. Conclusions Intracranial auditory event-related responses to speech were associated with cortical sites critical for auditory perception and comprehension of speech. Significance These results suggest that the distribution and magnitude of intracranial auditory event-related responses to speech reflect the functional significance of the underlying cortical regions and may be useful for pre-surgical functional mapping. PMID:19070540

The G8 screening tool detects relevant geriatric impairments and predicts survival in elderly patients with a haematological malignancy.

PubMed

Hamaker, Marije E; Mitrovic, M; Stauder, R

2014-06-01

The G8 screening tool was developed to separate fit older cancer patients who were able to receive standard treatment from those that should undergo a geriatric assessment to guide tailoring of therapy. We set out to determine the discriminative power and prognostic value of the G8 in older patients with a haematological malignancy. Between September 2009 and May 2013, a multi-dimensional geriatric assessment was performed in consecutive patients aged ≥67 years diagnosed with blood cancer at the Innsbruck University Hospital. The assessment included (instrumental) activities of daily living, cognition, mood, nutritional status, mobility, polypharmacy and social support. In parallel, the G8 was also administered (cut-off ≤ 14). Using a cut-off of ≥2 impaired domains, 70 % of the 108 included patients were considered as having an impaired geriatric assessment while 61 % had an impaired G8. The G8 lacked discriminative power for impairments on full geriatric assessment: sensitivity 69, specificity 79, positive predictive value 89 and negative predictive value 50 %. However, G8 was an independent predictor of mortality within the first year after inclusion (hazard ratio 3.93; 95 % confidence interval 1.67-9.22, p < 0.001). Remarkably, patients with impaired G8 fared poorly, irrespective of treatment choices (p < 0.001). This is the first report on the clinical and prognostic relevance of G8 in elderly patients with haematological malignancies. Although the G8 lacked discriminative power for outcome of multi-dimensional geriatric assessment, this score appears to be a powerful prognosticator and could potentially represent a useful tool in treatment decisions. This novel finding certainly deserves further exploration.

Assessing Probabilistic Risk Assessment Approaches for Insect Biological Control Introductions.

PubMed

Kaufman, Leyla V; Wright, Mark G

2017-07-07

The introduction of biological control agents to new environments requires host specificity tests to estimate potential non-target impacts of a prospective agent. Currently, the approach is conservative, and is based on physiological host ranges determined under captive rearing conditions, without consideration for ecological factors that may influence realized host range. We use historical data and current field data from introduced parasitoids that attack an endemic Lepidoptera species in Hawaii to validate a probabilistic risk assessment (PRA) procedure for non-target impacts. We use data on known host range and habitat use in the place of origin of the parasitoids to determine whether contemporary levels of non-target parasitism could have been predicted using PRA. Our results show that reasonable predictions of potential non-target impacts may be made if comprehensive data are available from places of origin of biological control agents, but scant data produce poor predictions. Using apparent mortality data rather than marginal attack rate estimates in PRA resulted in over-estimates of predicted non-target impact. Incorporating ecological data into PRA models improved the predictive power of the risk assessments.

Assessing Probabilistic Risk Assessment Approaches for Insect Biological Control Introductions

PubMed Central

Kaufman, Leyla V.; Wright, Mark G.

2017-01-01

The introduction of biological control agents to new environments requires host specificity tests to estimate potential non-target impacts of a prospective agent. Currently, the approach is conservative, and is based on physiological host ranges determined under captive rearing conditions, without consideration for ecological factors that may influence realized host range. We use historical data and current field data from introduced parasitoids that attack an endemic Lepidoptera species in Hawaii to validate a probabilistic risk assessment (PRA) procedure for non-target impacts. We use data on known host range and habitat use in the place of origin of the parasitoids to determine whether contemporary levels of non-target parasitism could have been predicted using PRA. Our results show that reasonable predictions of potential non-target impacts may be made if comprehensive data are available from places of origin of biological control agents, but scant data produce poor predictions. Using apparent mortality data rather than marginal attack rate estimates in PRA resulted in over-estimates of predicted non-target impact. Incorporating ecological data into PRA models improved the predictive power of the risk assessments. PMID:28686180

The contribution of attentional lapses to individual differences in visual working memory capacity.

PubMed

Adam, Kirsten C S; Mance, Irida; Fukuda, Keisuke; Vogel, Edward K

2015-08-01

Attentional control and working memory capacity are important cognitive abilities that substantially vary between individuals. Although much is known about how attentional control and working memory capacity relate to each other and to constructs like fluid intelligence, little is known about how trial-by-trial fluctuations in attentional engagement impact trial-by-trial working memory performance. Here, we employ a novel whole-report memory task that allowed us to distinguish between varying levels of attentional engagement in humans performing a working memory task. By characterizing low-performance trials, we can distinguish between models in which working memory performance failures are caused by either (1) complete lapses of attention or (2) variations in attentional control. We found that performance failures increase with set-size and strongly predict working memory capacity. Performance variability was best modeled by an attentional control model of attention, not a lapse model. We examined neural signatures of performance failures by measuring EEG activity while participants performed the whole-report task. The number of items correctly recalled in the memory task was predicted by frontal theta power, with decreased frontal theta power associated with poor performance on the task. In addition, we found that poor performance was not explained by failures of sensory encoding; the P1/N1 response and ocular artifact rates were equivalent for high- and low-performance trials. In all, we propose that attentional lapses alone cannot explain individual differences in working memory performance. Instead, we find that graded fluctuations in attentional control better explain the trial-by-trial differences in working memory that we observe.

The Contribution of Attentional Lapses to Individual Differences in Visual Working Memory Capacity

PubMed Central

Adam, Kirsten C. S.; Mance, Irida; Fukuda, Keisuke; Vogel, Edward K.

2015-01-01

Attentional control and working memory capacity are important cognitive abilities that substantially vary between individuals. Although much is known about how attentional control and working memory capacity relate to each other and to constructs like fluid intelligence, little is known about how trial-by-trial fluctuations in attentional engagement impact trial-by-trial working memory performance. Here, we employ a novel whole-report memory task that allowed us to distinguish between varying levels of attentional engagement in humans performing a working memory task. By characterizing low-performance trials, we can distinguish between models in which working memory performance failures are caused by either (1) complete lapses of attention or (2) variations in attentional control. We found that performance failures increase with set-size and strongly predict working memory capacity. Performance variability was best modeled by an attentional control model of attention, not a lapse model. We examined neural signatures of performance failures by measuring EEG activity while participants performed the whole-report task. The number of items correctly recalled in the memory task was predicted by frontal theta power, with decreased frontal theta power associated with poor performance on the task. In addition, we found that poor performance was not explained by failures of sensory encoding; the P1/N1 response and ocular artifact rates were equivalent for high- and low-performance trials. In all, we propose that attentional lapses alone cannot explain individual differences in working memory performance. Instead, we find that graded fluctuations in attentional control better explain the trial-by-trial differences in working memory that we observe. PMID:25811710

A summary of wind power prediction methods

NASA Astrophysics Data System (ADS)

Wang, Yuqi

2018-06-01

The deterministic prediction of wind power, the probability prediction and the prediction of wind power ramp events are introduced in this paper. Deterministic prediction includes the prediction of statistical learning based on histor ical data and the prediction of physical models based on NWP data. Due to the great impact of wind power ramp events on the power system, this paper also introduces the prediction of wind power ramp events. At last, the evaluation indicators of all kinds of prediction are given. The prediction of wind power can be a good solution to the adverse effects of wind power on the power system due to the abrupt, intermittent and undulation of wind power.

Cardiovascular risk

PubMed Central

Payne, Rupert A

2012-01-01

Cardiovascular disease is a major, growing, worldwide problem. It is important that individuals at risk of developing cardiovascular disease can be effectively identified and appropriately stratified according to risk. This review examines what we understand by the term risk, traditional and novel risk factors, clinical scoring systems, and the use of risk for informing prescribing decisions. Many different cardiovascular risk factors have been identified. Established, traditional factors such as ageing are powerful predictors of adverse outcome, and in the case of hypertension and dyslipidaemia are the major targets for therapeutic intervention. Numerous novel biomarkers have also been described, such as inflammatory and genetic markers. These have yet to be shown to be of value in improving risk prediction, but may represent potential therapeutic targets and facilitate more targeted use of existing therapies. Risk factors have been incorporated into several cardiovascular disease prediction algorithms, such as the Framingham equation, SCORE and QRISK. These have relatively poor predictive power, and uncertainties remain with regards to aspects such as choice of equation, different risk thresholds and the roles of relative risk, lifetime risk and reversible factors in identifying and treating at-risk individuals. Nonetheless, such scores provide objective and transparent means of quantifying risk and their integration into therapeutic guidelines enables equitable and cost-effective distribution of health service resources and improves the consistency and quality of clinical decision making. PMID:22348281

Modified ensemble Kalman filter for nuclear accident atmospheric dispersion: prediction improved and source estimated.

PubMed

Zhang, X L; Su, G F; Yuan, H Y; Chen, J G; Huang, Q Y

2014-09-15

Atmospheric dispersion models play an important role in nuclear power plant accident management. A reliable estimation of radioactive material distribution in short range (about 50 km) is in urgent need for population sheltering and evacuation planning. However, the meteorological data and the source term which greatly influence the accuracy of the atmospheric dispersion models are usually poorly known at the early phase of the emergency. In this study, a modified ensemble Kalman filter data assimilation method in conjunction with a Lagrangian puff-model is proposed to simultaneously improve the model prediction and reconstruct the source terms for short range atmospheric dispersion using the off-site environmental monitoring data. Four main uncertainty parameters are considered: source release rate, plume rise height, wind speed and wind direction. Twin experiments show that the method effectively improves the predicted concentration distribution, and the temporal profiles of source release rate and plume rise height are also successfully reconstructed. Moreover, the time lag in the response of ensemble Kalman filter is shortened. The method proposed here can be a useful tool not only in the nuclear power plant accident emergency management but also in other similar situation where hazardous material is released into the atmosphere. Copyright © 2014 Elsevier B.V. All rights reserved.

Hydraulic geometry of river cross sections; theory of minimum variance

USGS Publications Warehouse

Williams, Garnett P.

1978-01-01

This study deals with the rates at which mean velocity, mean depth, and water-surface width increase with water discharge at a cross section on an alluvial stream. Such relations often follow power laws, the exponents in which are called hydraulic exponents. The Langbein (1964) minimum-variance theory is examined in regard to its validity and its ability to predict observed hydraulic exponents. The variables used with the theory were velocity, depth, width, bed shear stress, friction factor, slope (energy gradient), and stream power. Slope is often constant, in which case only velocity, depth, width, shear and friction factor need be considered. The theory was tested against a wide range of field data from various geographic areas of the United States. The original theory was intended to produce only the average hydraulic exponents for a group of cross sections in a similar type of geologic or hydraulic environment. The theory does predict these average exponents with a reasonable degree of accuracy. An attempt to forecast the exponents at any selected cross section was moderately successful. Empirical equations are more accurate than the minimum variance, Gauckler-Manning, or Chezy methods. Predictions of the exponent of width are most reliable, the exponent of depth fair, and the exponent of mean velocity poor. (Woodard-USGS)

A Refined Prediction Model for Core and Lower Extremity Sprains and Strains Among Collegiate Football Players.

PubMed

Wilkerson, Gary B; Colston, Marisa A

2015-06-01

Researchers have identified high exposure to game conditions, low back dysfunction, and poor endurance of the core musculature as strong predictors for the occurrence of sprains and strains among collegiate football players. To refine a previously developed injury-prediction model through analysis of 3 consecutive seasons of data. Cohort study. National Collegiate Athletic Association Division I Football Championship Subdivision football program. For 3 consecutive years, all 152 team members (age = 19.7 ± 1.5 years, height = 1.84 ± 0.08 m, mass = 101.08 ± 19.28 kg) presented for a mandatory physical examination on the day before initiation of preseason practice sessions. Associations between preseason measurements and the subsequent occurrence of a core or lower extremity sprain or strain were established for 256 player-seasons of data. We used receiver operating characteristic analysis to identify optimal cut points for dichotomous categorizations of cases as high risk or low risk. Both logistic regression and Cox regression analyses were used to identify a multivariable injury-prediction model with optimal discriminatory power. Exceptionally good discrimination between injured and uninjured cases was found for a 3-factor prediction model that included equal to or greater than 1 game as a starter, Oswestry Disability Index score equal to or greater than 4, and poor wall-sit-hold performance. The existence of at least 2 of the 3 risk factors demonstrated 56% sensitivity, 80% specificity, an odds ratio of 5.28 (90% confidence interval = 3.31, 8.44), and a hazard ratio of 2.97 (90% confidence interval = 2.14, 4.12). High exposure to game conditions was the dominant injury risk factor for collegiate football players, but a surprisingly mild degree of low back dysfunction and poor core-muscle endurance appeared to be important modifiable risk factors that should be identified and addressed before participation.

A Refined Prediction Model for Core and Lower Extremity Sprains and Strains Among Collegiate Football Players

PubMed Central

Wilkerson, Gary B.; Colston, Marisa A.

2015-01-01

Context Researchers have identified high exposure to game conditions, low back dysfunction, and poor endurance of the core musculature as strong predictors for the occurrence of sprains and strains among collegiate football players. Objective To refine a previously developed injury-prediction model through analysis of 3 consecutive seasons of data. Design Cohort study. Setting National Collegiate Athletic Association Division I Football Championship Subdivision football program. Patients or Other Participants For 3 consecutive years, all 152 team members (age = 19.7 ± 1.5 years, height = 1.84 ± 0.08 m, mass = 101.08 ± 19.28 kg) presented for a mandatory physical examination on the day before initiation of preseason practice sessions. Main Outcome Measure(s) Associations between preseason measurements and the subsequent occurrence of a core or lower extremity sprain or strain were established for 256 player-seasons of data. We used receiver operating characteristic analysis to identify optimal cut points for dichotomous categorizations of cases as high risk or low risk. Both logistic regression and Cox regression analyses were used to identify a multivariable injury-prediction model with optimal discriminatory power. Results Exceptionally good discrimination between injured and uninjured cases was found for a 3-factor prediction model that included equal to or greater than 1 game as a starter, Oswestry Disability Index score equal to or greater than 4, and poor wall-sit–hold performance. The existence of at least 2 of the 3 risk factors demonstrated 56% sensitivity, 80% specificity, an odds ratio of 5.28 (90% confidence interval = 3.31, 8.44), and a hazard ratio of 2.97 (90% confidence interval = 2.14, 4.12). Conclusions High exposure to game conditions was the dominant injury risk factor for collegiate football players, but a surprisingly mild degree of low back dysfunction and poor core-muscle endurance appeared to be important modifiable risk factors that should be identified and addressed before participation. PMID:25844856

Power output of field-based downhill mountain biking.

PubMed

Hurst, Howard Thomas; Atkins, Stephen

2006-10-01

The purpose of this study was to assess the power output of field-based downhill mountain biking. Seventeen trained male downhill cyclists (age 27.1 +/- 5.1 years) competing nationally performed two timed runs of a measured downhill course. An SRM powermeter was used to simultaneously record power, cadence, and speed. Values were sampled at 1-s intervals. Heart rates were recorded at 5-s intervals using a Polar S710 heart rate monitor. Peak and mean power output were 834 +/- 129 W and 75 +/- 26 W respectively. Mean power accounted for only 9% of peak values. Paradoxically, mean heart rate was 168 +/- 9 beats x min(-1) (89% of age-predicted maximum heart rate). Mean cadence (27 +/- 5 rev x min(-1)) was significantly related to speed (r = 0.51; P < 0.01). Analysis revealed an average of 38 pedal actions per run, with average pedalling periods of 5 s. Power and cadence were not significantly related to run time or any other variable. Our results support the intermittent nature of downhill mountain biking. The poor relationships between power and run time and between cadence and run time suggest they are not essential pre-requisites to downhill mountain biking performance and indicate the importance of riding dynamics to overall performance.

A Monte Carlo Simulation Study of the Reliability of Intraindividual Variability

PubMed Central

Estabrook, Ryne; Grimm, Kevin J.; Bowles, Ryan P.

2012-01-01

Recent research has seen intraindividual variability (IIV) become a useful technique to incorporate trial-to-trial variability into many types of psychological studies. IIV as measured by individual standard deviations (ISDs) has shown unique prediction to several types of positive and negative outcomes (Ram, Rabbit, Stollery, & Nesselroade, 2005). One unanswered question regarding measuring intraindividual variability is its reliability and the conditions under which optimal reliability is achieved. Monte Carlo simulation studies were conducted to determine the reliability of the ISD compared to the intraindividual mean. The results indicate that ISDs generally have poor reliability and are sensitive to insufficient measurement occasions, poor test reliability, and unfavorable amounts and distributions of variability in the population. Secondary analysis of psychological data shows that use of individual standard deviations in unfavorable conditions leads to a marked reduction in statistical power, although careful adherence to underlying statistical assumptions allows their use as a basic research tool. PMID:22268793

Unfavorable polysomnographic sleep patterns predict poor sleep and poor psychological functioning 3 years later in patients with restless legs syndrome.

PubMed

Brand, Serge; Beck, Johannes; Hatzinger, Martin; Savic, Mirjana; Holsboer-Trachsler, Edith

2011-01-01

Amongst the variety of disorders affecting sleep, restless legs syndrome (RLS) merits particular attention. Little is known about long-term outcomes for sleep or psychological functioning following a diagnosis of RLS. The aim of the present study was thus to evaluate sleep and psychological functioning at a 3-year follow-up and based on polysomnographic measurements. Thirty-eight patients (18 female and 20 male patients; mean age: 56.06, SD = 12.07) with RLS and sleep electroencephalographic recordings were followed-up 33 months later. Participants completed a series of self-rating questionnaires related to sleep and psychological functioning. Additionally, they completed a sleep log for 7 consecutive days. Age, male gender, increased light sleep (S1, S2) and sleep onset latency, along with low sleep efficiency, predicted psychological functioning and sleep 33 months later. Specifically, sleep fragmentation predicted poor psychological functioning, and both sleep fragmentation and light sleep predicted poor sleep. In patients with RLS, irrespective of medication or duration of treatment, poor objective sleep patterns at diagnosis predicted both poor psychological functioning and poor sleep about 3 years after diagnosis. The pattern of results suggests the need for more thorough medical and psychotherapeutic treatment and monitoring of patients with RLS. © 2010 S. Karger AG, Basel.

Longitudinal Stability and Predictors of Poor Oral Comprehenders and Poor Decoders

PubMed Central

Elwér, Åsa; Keenan, Janice M.; Olson, Richard K.; Byrne, Brian; Samuelsson, Stefan

2012-01-01

Two groups of 4th grade children were selected from a population sample (N= 926) to either be Poor Oral Comprehenders (poor oral comprehension but normal word decoding), or Poor Decoders (poor decoding but normal oral comprehension). By examining both groups in the same study with varied cognitive and literacy predictors, and examining them both retrospectively and prospectively, we could assess how distinctive and stable the predictors of each deficit are. Predictors were assessed retrospectively at preschool, at the end of kindergarten, 1st, and 2nd grades. Group effects were significant at all test occasions, including those for preschool vocabulary (worse in poor oral comprehenders) and rapid naming (RAN) (worse in poor decoders). Preschool RAN and Vocabulary prospectively predicted grade 4 group membership (77–79% correct classification) within the selected samples. Reselection in preschool of at-risk poor decoder and poor oral comprehender subgroups based on these variables led to significant but relatively weak prediction of subtype membership at grade 4. Implications of the predictive stability of our results for identification and intervention of these important subgroups are discussed. PMID:23528975

Experimental investigation of geologically produced antineutrinos with KamLAND.

PubMed

Araki, T; Enomoto, S; Furuno, K; Gando, Y; Ichimura, K; Ikeda, H; Inoue, K; Kishimoto, Y; Koga, M; Koseki, Y; Maeda, T; Mitsui, T; Motoki, M; Nakajima, K; Ogawa, H; Ogawa, M; Owada, K; Ricol, J-S; Shimizu, I; Shirai, J; Suekane, F; Suzuki, A; Tada, K; Takeuchi, S; Tamae, K; Tsuda, Y; Watanabe, H; Busenitz, J; Classen, T; Djurcic, Z; Keefer, G; Leonard, D; Piepke, A; Yakushev, E; Berger, B E; Chan, Y D; Decowski, M P; Dwyer, D A; Freedman, S J; Fujikawa, B K; Goldman, J; Gray, F; Heeger, K M; Hsu, L; Lesko, K T; Luk, K-B; Murayama, H; O'Donnell, T; Poon, A W P; Steiner, H M; Winslow, L A; Mauger, C; McKeown, R D; Vogel, P; Lane, C E; Miletic, T; Guillian, G; Learned, J G; Maricic, J; Matsuno, S; Pakvasa, S; Horton-Smith, G A; Dazeley, S; Hatakeyama, S; Rojas, A; Svoboda, R; Dieterle, B D; Detwiler, J; Gratta, G; Ishii, K; Tolich, N; Uchida, Y; Batygov, M; Bugg, W; Efremenko, Y; Kamyshkov, Y; Kozlov, A; Nakamura, Y; Karwowski, H J; Markoff, D M; Nakamura, K; Rohm, R M; Tornow, W; Wendell, R; Chen, M-J; Wang, Y-F; Piquemal, F

2005-07-28

The detection of electron antineutrinos produced by natural radioactivity in the Earth could yield important geophysical information. The Kamioka liquid scintillator antineutrino detector (KamLAND) has the sensitivity to detect electron antineutrinos produced by the decay of 238U and 232Th within the Earth. Earth composition models suggest that the radiogenic power from these isotope decays is 16 TW, approximately half of the total measured heat dissipation rate from the Earth. Here we present results from a search for geoneutrinos with KamLAND. Assuming a Th/U mass concentration ratio of 3.9, the 90 per cent confidence interval for the total number of geoneutrinos detected is 4.5 to 54.2. This result is consistent with the central value of 19 predicted by geophysical models. Although our present data have limited statistical power, they nevertheless provide by direct means an upper limit (60 TW) for the radiogenic power of U and Th in the Earth, a quantity that is currently poorly constrained.

Analysis of automatic repeat request methods for deep-space downlinks

NASA Technical Reports Server (NTRS)

Pollara, F.; Ekroot, L.

1995-01-01

Automatic repeat request (ARQ) methods cannot increase the capacity of a memoryless channel. However, they can be used to decrease the complexity of the channel-coding system to achieve essentially error-free transmission and to reduce link margins when the channel characteristics are poorly predictable. This article considers ARQ methods on a power-limited channel (e.g., the deep-space channel), where it is important to minimize the total power needed to transmit the data, as opposed to a bandwidth-limited channel (e.g., terrestrial data links), where the spectral efficiency or the total required transmission time is the most relevant performance measure. In the analysis, we compare the performance of three reference concatenated coded systems used in actual deep-space missions to that obtainable by ARQ methods using the same codes, in terms of required power, time to transmit with a given number of retransmissions, and achievable probability of word error. The ultimate limits of ARQ with an arbitrary number of retransmissions are also derived.

Effects of 31 FDA approved small-molecule kinase inhibitors on isolated rat liver mitochondria.

PubMed

Zhang, Jun; Salminen, Alec; Yang, Xi; Luo, Yong; Wu, Qiangen; White, Matthew; Greenhaw, James; Ren, Lijun; Bryant, Matthew; Salminen, William; Papoian, Thomas; Mattes, William; Shi, Qiang

2017-08-01

The FDA has approved 31 small-molecule kinase inhibitors (KIs) for human use as of November 2016, with six having black box warnings for hepatotoxicity (BBW-H) in product labeling. The precise mechanisms and risk factors for KI-induced hepatotoxicity are poorly understood. Here, the 31 KIs were tested in isolated rat liver mitochondria, an in vitro system recently proposed to be a useful tool to predict drug-induced hepatotoxicity in humans. The KIs were incubated with mitochondria or submitochondrial particles at concentrations ranging from therapeutic maximal blood concentrations (Cmax) levels to 100-fold Cmax levels. Ten endpoints were measured, including oxygen consumption rate, inner membrane potential, cytochrome c release, swelling, reactive oxygen species, and individual respiratory chain complex (I-V) activities. Of the 31 KIs examined only three including sorafenib, regorafenib and pazopanib, all of which are hepatotoxic, caused significant mitochondrial toxicity at concentrations equal to the Cmax, indicating that mitochondrial toxicity likely contributes to the pathogenesis of hepatotoxicity associated with these KIs. At concentrations equal to 100-fold Cmax, 18 KIs were found to be toxic to mitochondria, and among six KIs with BBW-H, mitochondrial injury was induced by regorafenib, lapatinib, idelalisib, and pazopanib, but not ponatinib, or sunitinib. Mitochondrial liability at 100-fold Cmax had a positive predictive power (PPV) of 72% and negative predictive power (NPV) of 33% in predicting human KI hepatotoxicity as defined by product labeling, with the sensitivity and specificity being 62% and 44%, respectively. Similar predictive power was obtained using the criterion of Cmax ≥1.1 µM or daily dose ≥100 mg. Mitochondrial liability at 1-2.5-fold Cmax showed a 100% PPV and specificity, though the NPV and sensitivity were 32% and 14%, respectively. These data provide novel mechanistic insights into KI hepatotoxicity and indicate that mitochondrial toxicity at therapeutic levels can help identify hepatotoxic KIs.

Ford Class Aircraft Carrier: Poor Outcomes Are the Predictable Consequences of the Prevalent Acquisition Culture

DTIC Science & Technology

2015-10-01

FORD CLASS AIRCRAFT CARRIER Poor Outcomes Are the Predictable Consequences of the Prevalent Acquisition Culture...2. REPORT TYPE 3. DATES COVERED 00-00-2015 to 00-00-2015 4. TITLE AND SUBTITLE Ford Class Aircraft Carrier: Poor Outcomes Are the Predictable...This Study The Navy set ambitious goals for the Ford -class program, including an array of new technologies and design features that were intended

A known-groups evaluation of the response bias scale in a neuropsychological setting.

PubMed

Sullivan, Karen A; Elliott, Cameron D; Lange, Rael T; Anderson, Deborah S

2013-01-01

We evaluated the Minnesota Multiphasic Personality Inventory-Second Edition (MMPI-2) Response Bias Scale (RBS). Archival data from 83 individuals who were referred for neuropsychological assessment with no formal diagnosis (n = 10), following a known or suspected traumatic brain injury (n = 36), with a psychiatric diagnosis (n = 20), or with a history of both trauma and a psychiatric condition (n = 17) were retrieved. The criteria for malingered neurocognitive dysfunction (MNCD) were applied, and two groups of participants were formed: poor effort (n = 15) and genuine responders (n = 68). Consistent with previous studies, the difference in scores between groups was greatest for the RBS (d = 2.44), followed by two established MMPI-2 validity scales, F (d = 0.25) and K (d = 0.23), and strong significant correlations were found between RBS and F (rs = .48) and RBS and K (r = -.41). When MNCD group membership was predicted using logistic regression, the RBS failed to add incrementally to F. In a separate regression to predict group membership, K added significantly to the RBS. Receiver-operating curve analysis revealed a nonsignificant area under the curve statistic, and at the ideal cutoff in this sample of >12, specificity was moderate (.79), sensitivity was low (.47), and positive and negative predictive power values at a 13% base rate were .25 and .91, respectively. Although the results of this study require replication because of a number of limitations, this study has made an important first attempt to report RBS classification accuracy statistics for predicting poor effort at a range of base rates.

The Identification of a Threshold of Long Work Hours for Predicting Elevated Risks of Adverse Health Outcomes.

PubMed

Conway, Sadie H; Pompeii, Lisa A; Gimeno Ruiz de Porras, David; Follis, Jack L; Roberts, Robert E

2017-07-15

Working long hours has been associated with adverse health outcomes. However, a definition of long work hours relative to adverse health risk has not been established. Repeated measures of work hours among approximately 2,000 participants from the Panel Study of Income Dynamics (1986-2011), conducted in the United States, were retrospectively analyzed to derive statistically optimized cutpoints of long work hours that best predicted three health outcomes. Work-hours cutpoints were assessed for model fit, calibration, and discrimination separately for the outcomes of poor self-reported general health, incident cardiovascular disease, and incident cancer. For each outcome, the work-hours threshold that best predicted increased risk was 52 hours per week or more for a minimum of 10 years. Workers exposed at this level had a higher risk of poor self-reported general health (relative risk (RR) = 1.28; 95% confidence interval (CI): 1.06, 1.53), cardiovascular disease (RR = 1.42; 95% CI: 1.24, 1.63), and cancer (RR = 1.62; 95% CI: 1.22, 2.17) compared with those working 35-51 hours per week for the same duration. This study provides the first health risk-based definition of long work hours. Further examination of the predictive power of this cutpoint on other health outcomes and in other study populations is needed. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Universally Sloppy Parameter Sensitivities in Systems Biology Models

PubMed Central

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-01-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a “sloppy” spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters. PMID:17922568

Universally sloppy parameter sensitivities in systems biology models.

PubMed

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-10-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

Upregulation of c-mesenchymal epithelial transition expression and RAS mutations are associated with late lung metastasis and poor prognosis in colorectal carcinoma.

PubMed

Liu, Jianhua; Zeng, Weiqiang; Huang, Chengzhi; Wang, Junjiang; Xu, Lishu; Ma, Dong

2018-05-01

The present study aimed to investigate whether c-mesenchymal epithelial transition factor (C-MET) overexpression combined with RAS (including KRAS, NRAS and HRAS ) or BRAF mutations were associated with late distant metastases and the prognosis of patients with colorectal cancer (CRC). A total of 374 patients with stage III CRC were classified into 4 groups based on RAS/BRAF and C-MET status for comprehensive analysis. Mutations in RAS / BRAF were determined using Sanger sequencing and C-MET expression was examined using immunohistochemistry. The associations between RAS/BRAF mutations in combination with C-MET overexpression and clinicopathological variables including survival were evaluated. In addition, their predictive value for late distant metastases were statistically analyzed via logistic regression and receiver operating characteristic analysis. Among 374 patients, mutations in KRAS, NRAS, HRAS, BRAF and C-MET overexpression were observed in 43.9, 2.4, 0.3, 5.9 and 71.9% of cases, respectively. Considering RAS/BRAF mutations and C-MET overexpression, vascular invasion (P=0.001), high carcino-embryonic antigen level (P=0.031) and late distant metastases (P<0.001) were more likely to occur in patients of group 4. Furthermore, survival analyses revealed RAS/BRAF mutations may have a more powerful impact on survival than C-MET overexpression, although they were both predictive factors for adverse prognosis. Further logistic regression suggested that RAS/BRAF mutations and C-MET overexpression may predict late distant metastases. In conclusion, RAS/BRAF mutations and C-MET overexpression may serve as predictive indicators for metastatic behavior and poor prognosis of CRC.

Near real time wind energy forecasting incorporating wind tunnel modeling

NASA Astrophysics Data System (ADS)

Lubitz, William David

A series of experiments and investigations were carried out to inform the development of a day-ahead wind power forecasting system. An experimental near-real time wind power forecasting system was designed and constructed that operates on a desktop PC and forecasts 12--48 hours in advance. The system uses model output of the Eta regional scale forecast (RSF) to forecast the power production of a wind farm in the Altamont Pass, California, USA from 12 to 48 hours in advance. It is of modular construction and designed to also allow diagnostic forecasting using archived RSF data, thereby allowing different methods of completing each forecasting step to be tested and compared using the same input data. Wind-tunnel investigations of the effect of wind direction and hill geometry on wind speed-up above a hill were conducted. Field data from an Altamont Pass, California site was used to evaluate several speed-up prediction algorithms, both with and without wind direction adjustment. These algorithms were found to be of limited usefulness for the complex terrain case evaluated. Wind-tunnel and numerical simulation-based methods were developed for determining a wind farm power curve (the relation between meteorological conditions at a point in the wind farm and the power production of the wind farm). Both methods, as well as two methods based on fits to historical data, ultimately showed similar levels of accuracy: mean absolute errors predicting power production of 5 to 7 percent of the wind farm power capacity. The downscaling of RSF forecast data to the wind farm was found to be complicated by the presence of complex terrain. Poor results using the geostrophic drag law and regression methods motivated the development of a database search method that is capable of forecasting not only wind speeds but also power production with accuracy better than persistence.

A Prognostic Gene Expression Profile That Predicts Circulating Tumor Cell Presence in Breast Cancer Patients

PubMed Central

Molloy, Timothy J.; Roepman, Paul; Naume, Bjørn; van't Veer, Laura J.

2012-01-01

The detection of circulating tumor cells (CTCs) in the peripheral blood and microarray gene expression profiling of the primary tumor are two promising new technologies able to provide valuable prognostic data for patients with breast cancer. Meta-analyses of several established prognostic breast cancer gene expression profiles in large patient cohorts have demonstrated that despite sharing few genes, their delineation of patients into “good prognosis” or “poor prognosis” are frequently very highly correlated, and combining prognostic profiles does not increase prognostic power. In the current study, we aimed to develop a novel profile which provided independent prognostic data by building a signature predictive of CTC status rather than outcome. Microarray gene expression data from an initial training cohort of 72 breast cancer patients for which CTC status had been determined in a previous study using a multimarker QPCR-based assay was used to develop a CTC-predictive profile. The generated profile was validated in two independent datasets of 49 and 123 patients and confirmed to be both predictive of CTC status, and independently prognostic. Importantly, the “CTC profile” also provided prognostic information independent of the well-established and powerful ‘70-gene’ prognostic breast cancer signature. This profile therefore has the potential to not only add prognostic information to currently-available microarray tests but in some circumstances even replace blood-based prognostic CTC tests at time of diagnosis for those patients already undergoing testing by multigene assays. PMID:22384245

Factors related to poor asthma control in Latvian asthma patients between 2013 and 2015

PubMed Central

Smits, Dins; Brigis, Girts; Pavare, Jana; Maurina, Baiba; Barengo, Noël Christopher

2017-01-01

Objectives To investigate whether beliefs about asthma medication, cognitive and emotional factors are related to poor asthma control in a sample of Latvian asthma patients in 2015. Design Cross-sectional, self-administered survey. Subjects Three hundred and fifty two asthma patients (mean age 57.5 years) attending outpatient pulmonologist consultations in Riga, Latvia during September 2013 to December 2015. The sample size was calculated to detect a prevalence of poor asthma control of 50% with a margin of error of 5% and a power of 95%. Main outcome measures The validated Beliefs about Medication Questionnaire (BMQ) and the Brief Illness Perception Questionnaire (brief IPQ) were used. Good asthma control was assessed using the asthma control test (ACT), a validated five-item scale that reliably assesses asthma control over a recall period of four weeks. Logistic regression models were used to predict poor asthma control. Results Patients who had a good control of asthma medication (OR 0.70; 95% CI 0.61–0.79) or were confident that their asthma medication improves illness (OR 0.84; 95% CI 0.74–0.95) had a reduced risk of poor asthma control. The more symptoms (OR 1.63; 95% CI 1.44–1.84) the asthma patients perceived or the more their illness affects their life, the higher the probability of poor asthma control (OR 1.47; 95% CI 1.31–1.65). Some beliefs of necessity and concerns of asthma medication were also statistically significantly related to poor asthma control. Conclusions Beliefs of necessity of asthma medication, cognitive and emotional illness perception factors correlate well with poor asthma control in Latvian patients. PMID:28585881

Validation of an Algorithm to Predict the Likelihood of an 8/8 HLA-Matched Unrelated Donor at Search Initiation.

PubMed

Davis, Eric; Devlin, Sean; Cooper, Candice; Nhaissi, Melissa; Paulson, Jennifer; Wells, Deborah; Scaradavou, Andromachi; Giralt, Sergio; Papadopoulos, Esperanza; Kernan, Nancy A; Byam, Courtney; Barker, Juliet N

2018-05-01

A strategy to rapidly determine if a matched unrelated donor (URD) can be secured for allograft recipients is needed. We sought to validate the accuracy of (1) HapLogic match predictions and (2) a resultant novel Search Prognosis (SP) patient categorization that could predict 8/8 HLA-matched URD(s) likelihood at search initiation. Patient prognosis categories at search initiation were correlated with URD confirmatory typing results. HapLogic-based SP categorizations accurately predicted the likelihood of an 8/8 HLA-match in 830 patients (1530 donors tested). Sixty percent of patients had 8/8 URD(s) identified. Patient SP categories (217 very good, 104 good, 178 fair, 33 poor, 153 very poor, 145 futile) were associated with a marked progressive decrease in 8/8 URD identification and transplantation. Very good to good categories were highly predictive of identifying and receiving an 8/8 URD regardless of ancestry. Europeans in fair/poor categories were more likely to identify and receive an 8/8 URD compared with non-Europeans. In all ancestries very poor and futile categories predicted no 8/8 URDs. HapLogic permits URD search results to be predicted once patient HLA typing and ancestry is obtained, dramatically improving search efficiency. Poor, very poor, andfutile searches can be immediately recognized, thereby facilitating prompt pursuit of alternative donors. Copyright © 2017 The American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved.

The wind power prediction research based on mind evolutionary algorithm

NASA Astrophysics Data System (ADS)

Zhuang, Ling; Zhao, Xinjian; Ji, Tianming; Miao, Jingwen; Cui, Haina

2018-04-01

When the wind power is connected to the power grid, its characteristics of fluctuation, intermittent and randomness will affect the stability of the power system. The wind power prediction can guarantee the power quality and reduce the operating cost of power system. There were some limitations in several traditional wind power prediction methods. On the basis, the wind power prediction method based on Mind Evolutionary Algorithm (MEA) is put forward and a prediction model is provided. The experimental results demonstrate that MEA performs efficiently in term of the wind power prediction. The MEA method has broad prospect of engineering application.

The future is in the numbers: the power of predictive analysis in the biomedical educational environment.

PubMed

Gullo, Charles A

2016-01-01

Biomedical programs have a potential treasure trove of data they can mine to assist admissions committees in identification of students who are likely to do well and help educational committees in the identification of students who are likely to do poorly on standardized national exams and who may need remediation. In this article, we provide a step-by-step approach that schools can utilize to generate data that are useful when predicting the future performance of current students in any given program. We discuss the use of linear regression analysis as the means of generating that data and highlight some of the limitations. Finally, we lament on how the combination of these institution-specific data sets are not being fully utilized at the national level where these data could greatly assist programs at large.

Zebrafish Behavioral Profiling Links Drugs to Biological Targets and Rest/Wake Regulation

PubMed Central

Rihel, Jason; Prober, David A.; Arvanites, Anthony; Lam, Kelvin; Zimmerman, Steven; Jang, Sumin; Haggarty, Stephen J.; Kokel, David; Rubin, Lee L.; Peterson, Randall T.; Schier, Alexander F.

2010-01-01

A major obstacle for the discovery of psychoactive drugs is the inability to predict how small molecules will alter complex behaviors. We report the development and application of a high-throughput, quantitative screen for drugs that alter the behavior of larval zebrafish. We found that the multi-dimensional nature of observed phenotypes enabled the hierarchical clustering of molecules according to shared behaviors. Behavioral profiling revealed conserved functions of psychotropic molecules and predicted the mechanisms of action of poorly characterized compounds. In addition, behavioral profiling implicated new factors such as ether-a-go-go-related gene (ERG) potassium channels and immunomodulators in the control of rest and locomotor activity. These results demonstrate the power of high-throughput behavioral profiling in zebrafish to discover and characterize psychotropic drugs and to dissect the pharmacology of complex behaviors. PMID:20075256

Predictive validity of the Sødring Motor Evaluation of Stroke Patients (SMES).

PubMed

Wyller, T B; Sødring, K M; Sveen, U; Ljunggren, A E; Bautz-Holter, E

1996-12-01

The Sødring Motor Evaluation of Stroke Patients (SMES) has been developed as an instrument for the evaluation by physiotherapists of motor function and activities in stroke patients. The predictive validity of the instrument was studied in a consecutive sample of 93 acute stroke patients, assessed in the acute phase and after one year. The outcome measures were: survival, residence at home or in institution, the Barthel ADL index (dichotomized at 19/20), and the Frenchay Activities Index (FAI) (dichotomized at 9/10). The SMES, scored in the acute phase, demonstrated a marginally significant predictive power regarding survival, but was a highly significant predictor regarding the other outcomes. The adjusted odds ratio for a good versus a poor outcome for patients in the upper versus the lower tertile of the SMES arm subscore was 5.4 (95% confidence interval 0.9-59) for survival, 11.5 (2.1-88) for living at home, 86.3 (11-infinity) for a high Barthel score, and 31.4 (5.2-288) for a high FAI score. We conclude that SMES has high predictive validity.

On the predictability of land surface fluxes from meteorological variables

NASA Astrophysics Data System (ADS)

Haughton, Ned; Abramowitz, Gab; Pitman, Andy J.

2018-01-01

Previous research has shown that land surface models (LSMs) are performing poorly when compared with relatively simple empirical models over a wide range of metrics and environments. Atmospheric driving data appear to provide information about land surface fluxes that LSMs are not fully utilising. Here, we further quantify the information available in the meteorological forcing data that are used by LSMs for predicting land surface fluxes, by interrogating FLUXNET data, and extending the benchmarking methodology used in previous experiments. We show that substantial performance improvement is possible for empirical models using meteorological data alone, with no explicit vegetation or soil properties, thus setting lower bounds on a priori expectations on LSM performance. The process also identifies key meteorological variables that provide predictive power. We provide an ensemble of empirical benchmarks that are simple to reproduce and provide a range of behaviours and predictive performance, acting as a baseline benchmark set for future studies. We reanalyse previously published LSM simulations and show that there is more diversity between LSMs than previously indicated, although it remains unclear why LSMs are broadly performing so much worse than simple empirical models.

Comparing Quick Sequential Organ Failure Assessment Scores to End-tidal Carbon Dioxide as Mortality Predictors in Prehospital Patients with Suspected Sepsis.

PubMed

Hunter, Christopher L; Silvestri, Salvatore; Ralls, George; Stone, Amanda; Walker, Ayanna; Mangalat, Neal; Papa, Linda

2018-05-01

Early identification of sepsis significantly improves outcomes, suggesting a role for prehospital screening. An end-tidal carbon dioxide (ETCO 2 ) value ≤ 25 mmHg predicts mortality and severe sepsis when used as part of a prehospital screening tool. Recently, the Quick Sequential Organ Failure Assessment (qSOFA) score was also derived as a tool for predicting poor outcomes in potentially septic patients. We conducted a retrospective cohort study among patients transported by emergency medical services to compare the use of ETCO 2 ≤ 25 mmHg with qSOFA score of ≥ 2 as a predictor of mortality or diagnosis of severe sepsis in prehospital patients with suspected sepsis. By comparison of receiver operator characteristic curves, ETCO 2 had a higher discriminatory power to predict mortality, sepsis, and severe sepsis than qSOFA. Both non-invasive measures were easily obtainable by prehospital personnel, with ETCO 2 performing slightly better as an outcome predictor.

De Novo Chromosome Structure Prediction

NASA Astrophysics Data System (ADS)

di Pierro, Michele; Cheng, Ryan R.; Lieberman-Aiden, Erez; Wolynes, Peter G.; Onuchic, Jose'n.

Chromatin consists of DNA and hundreds of proteins that interact with the genetic material. In vivo, chromatin folds into nonrandom structures. The physical mechanism leading to these characteristic conformations, however, remains poorly understood. We recently introduced MiChroM, a model that generates chromosome conformations by using the idea that chromatin can be subdivided into types based on its biochemical interactions. Here we extend and complete our previous finding by showing that structural chromatin types can be inferred from ChIP-Seq data. Chromatin types, which are distinct from DNA sequence, are partially epigenetically controlled and change during cell differentiation, thus constituting a link between epigenetics, chromosomal organization, and cell development. We show that, for GM12878 lymphoblastoid cells we are able to predict accurate chromosome structures with the only input of genomic data. The degree of accuracy achieved by our prediction supports the viability of the proposed physical mechanism of chromatin folding and makes the computational model a powerful tool for future investigations.

Integration of biological data by kernels on graph nodes allows prediction of new genes involved in mitotic chromosome condensation

PubMed Central

Hériché, Jean-Karim; Lees, Jon G.; Morilla, Ian; Walter, Thomas; Petrova, Boryana; Roberti, M. Julia; Hossain, M. Julius; Adler, Priit; Fernández, José M.; Krallinger, Martin; Haering, Christian H.; Vilo, Jaak; Valencia, Alfonso; Ranea, Juan A.; Orengo, Christine; Ellenberg, Jan

2014-01-01

The advent of genome-wide RNA interference (RNAi)–based screens puts us in the position to identify genes for all functions human cells carry out. However, for many functions, assay complexity and cost make genome-scale knockdown experiments impossible. Methods to predict genes required for cell functions are therefore needed to focus RNAi screens from the whole genome on the most likely candidates. Although different bioinformatics tools for gene function prediction exist, they lack experimental validation and are therefore rarely used by experimentalists. To address this, we developed an effective computational gene selection strategy that represents public data about genes as graphs and then analyzes these graphs using kernels on graph nodes to predict functional relationships. To demonstrate its performance, we predicted human genes required for a poorly understood cellular function—mitotic chromosome condensation—and experimentally validated the top 100 candidates with a focused RNAi screen by automated microscopy. Quantitative analysis of the images demonstrated that the candidates were indeed strongly enriched in condensation genes, including the discovery of several new factors. By combining bioinformatics prediction with experimental validation, our study shows that kernels on graph nodes are powerful tools to integrate public biological data and predict genes involved in cellular functions of interest. PMID:24943848

EffectorP: predicting fungal effector proteins from secretomes using machine learning.

PubMed

Sperschneider, Jana; Gardiner, Donald M; Dodds, Peter N; Tini, Francesco; Covarelli, Lorenzo; Singh, Karam B; Manners, John M; Taylor, Jennifer M

2016-04-01

Eukaryotic filamentous plant pathogens secrete effector proteins that modulate the host cell to facilitate infection. Computational effector candidate identification and subsequent functional characterization delivers valuable insights into plant-pathogen interactions. However, effector prediction in fungi has been challenging due to a lack of unifying sequence features such as conserved N-terminal sequence motifs. Fungal effectors are commonly predicted from secretomes based on criteria such as small size and cysteine-rich, which suffers from poor accuracy. We present EffectorP which pioneers the application of machine learning to fungal effector prediction. EffectorP improves fungal effector prediction from secretomes based on a robust signal of sequence-derived properties, achieving sensitivity and specificity of over 80%. Features that discriminate fungal effectors from secreted noneffectors are predominantly sequence length, molecular weight and protein net charge, as well as cysteine, serine and tryptophan content. We demonstrate that EffectorP is powerful when combined with in planta expression data for predicting high-priority effector candidates. EffectorP is the first prediction program for fungal effectors based on machine learning. Our findings will facilitate functional fungal effector studies and improve our understanding of effectors in plant-pathogen interactions. EffectorP is available at http://effectorp.csiro.au. © 2015 CSIRO New Phytologist © 2015 New Phytologist Trust.

Modifying Bagnold's Sediment Transport Equation for Use in Watershed-Scale Channel Incision Models

NASA Astrophysics Data System (ADS)

Lammers, R. W.; Bledsoe, B. P.

2016-12-01

Destabilized stream channels may evolve through a sequence of stages, initiated by bed incision and followed by bank erosion and widening. Channel incision can be modeled using Exner-type mass balance equations, but model accuracy is limited by the accuracy and applicability of the selected sediment transport equation. Additionally, many sediment transport relationships require significant data inputs, limiting their usefulness in data-poor environments. Bagnold's empirical relationship for bedload transport is attractive because it is based on stream power, a relatively straightforward parameter to estimate using remote sensing data. However, the equation is also dependent on flow depth, which is more difficult to measure or estimate for entire drainage networks. We recast Bagnold's original sediment transport equation using specific discharge in place of flow depth. Using a large dataset of sediment transport rates from the literature, we show that this approach yields similar predictive accuracy as other stream power based relationships. We also explore the applicability of various critical stream power equations, including Bagnold's original, and support previous conclusions that these critical values can be predicted well based solely on sediment grain size. In addition, we propagate error in these sediment transport equations through channel incision modeling to compare the errors associated with our equation to alternative formulations. This new version of Bagnold's bedload transport equation has utility for channel incision modeling at larger spatial scales using widely available and remote sensing data.

Instability of different adolescent metabolic syndrome definitions tracked into early adulthood metabolic syndrome: Tehran Lipid and Glucose Study (TLGS).

PubMed

Asghari, Golaleh; Eftekharzadeh, Anita; Hosseinpanah, Farhad; Ghareh, Sahar; Mirmiran, Parvin; Azizi, Fereidoun

2017-02-01

There are substantial controversies about the clinical utility of adolescent metabolic syndrome (MetS). The current study examined the stability of adolescent MetS by assessing the agreement and discriminative abilities of four different definitions of adolescent MetS and the adult MetS definition during a 10.4-yr follow up. For this study, 1424 adolescents (55.2% female), who participated in the framework of the Tehran Lipid and Glucose Study were included. Kappa was calculated for agreement between adolescent MetS definitions [Cook, de Ferranti, pediatric National Cholesterol Education Program (NCEP) and pediatric International Diabetes Federation (IDF)] and the adulthood MetS definition defined by the joint interim statement (JIS) criteria. MetS persistence, instability, and incidence were assessed, and for each of the four adolescent definitions, sensitivity, specificity, and area under receiver operating curve (AUC) for the counting of categorical adulthood MetS components was evaluated. The agreement between the four adolescent MetS definitions and JIS was poor (κ = 0.094-0.255). All definitions showed low sensitivity and high specificity, except for de Ferranti's, which contrary to other definitions, had higher sensitivity and lower specificity. All four adolescent definitions revealed generally low AUCs (0.601-0.647). Compared with the pubertal group (11-14 yr), the predictive power was slightly higher in the late-pubertal group (15-18 yr). Cook's and de Ferranti's definitions showed fairly better predictive powers (0.647 and 0.644, respectively). Across all definitions, instability ranged between 5.4 and 19.6%. The adolescent definitions show considerable amount of instability defined as poor agreement and low discriminative abilities tracked into early adulthood. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Analysis and simulation of wireless signal propagation applying geostatistical interpolation techniques

NASA Astrophysics Data System (ADS)

Kolyaie, S.; Yaghooti, M.; Majidi, G.

2011-12-01

This paper is a part of an ongoing research to examine the capability of geostatistical analysis for mobile networks coverage prediction, simulation and tuning. Mobile network coverage predictions are used to find network coverage gaps and areas with poor serviceability. They are essential data for engineering and management in order to make better decision regarding rollout, planning and optimisation of mobile networks.The objective of this research is to evaluate different interpolation techniques in coverage prediction. In method presented here, raw data collected from drive testing a sample of roads in study area is analysed and various continuous surfaces are created using different interpolation methods. Two general interpolation methods are used in this paper with different variables; first, Inverse Distance Weighting (IDW) with various powers and number of neighbours and second, ordinary kriging with Gaussian, spherical, circular and exponential semivariogram models with different number of neighbours. For the result comparison, we have used check points coming from the same drive test data. Prediction values for check points are extracted from each surface and the differences with actual value are computed. The output of this research helps finding an optimised and accurate model for coverage prediction.

Nondestructive evaluation using dipole model analysis with a scan type magnetic camera

NASA Astrophysics Data System (ADS)

Lee, Jinyi; Hwang, Jiseong

2005-12-01

Large structures such as nuclear power, thermal power, chemical and petroleum refining plants are drawing interest with regard to the economic aspect of extending component life in respect to the poor environment created by high pressure, high temperature, and fatigue, securing safety from corrosion and exceeding their designated life span. Therefore, technology that accurately calculates and predicts degradation and defects of aging materials is extremely important. Among different methods available, nondestructive testing using magnetic methods is effective in predicting and evaluating defects on the surface of or surrounding ferromagnetic structures. It is important to estimate the distribution of magnetic field intensity for applicable magnetic methods relating to industrial nondestructive evaluation. A magnetic camera provides distribution of a quantitative magnetic field with a homogeneous lift-off and spatial resolution. It is possible to interpret the distribution of magnetic field when the dipole model was introduced. This study proposed an algorithm for nondestructive evaluation using dipole model analysis with a scan type magnetic camera. The numerical and experimental considerations of the quantitative evaluation of several sizes and shapes of cracks using magnetic field images of the magnetic camera were examined.

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.

A Method to Predict the Thickness of Poorly-Bonded Material Along Spray and Spray-Layer Boundaries in Cold Spray Deposition

NASA Astrophysics Data System (ADS)

Li, Yangfan; Hamada, Yukitaka; Otobe, Katsunori; Ando, Teiichi

2017-02-01

Multi-traverse CS provides a unique means for the production of thick coatings and bulk materials from powders. However, the material along spray and spray-layer boundaries is often poorly bonded as it is laid by the leading and trailing peripheries of the spray that carry powder particles with insufficient kinetic energy. For the same reason, the splats in the very first layer deposited on the substrate may not be bonded well either. A mathematical spray model was developed based on an axisymmetric Gaussian mass flow rate distribution and a stepped deposition yield to predict the thickness of such poorly-bonded layers in multi-traverse CS deposition. The predicted thickness of poorly-bonded layers in a multi-traverse Cu coating falls in the range of experimental values. The model also predicts that the material that contains poorly bonded splats could exceed 20% of the total volume of the coating.

Effect of genetic architecture on the prediction accuracy of quantitative traits in samples of unrelated individuals.

PubMed

Morgante, Fabio; Huang, Wen; Maltecca, Christian; Mackay, Trudy F C

2018-06-01

Predicting complex phenotypes from genomic data is a fundamental aim of animal and plant breeding, where we wish to predict genetic merits of selection candidates; and of human genetics, where we wish to predict disease risk. While genomic prediction models work well with populations of related individuals and high linkage disequilibrium (LD) (e.g., livestock), comparable models perform poorly for populations of unrelated individuals and low LD (e.g., humans). We hypothesized that low prediction accuracies in the latter situation may occur when the genetics architecture of the trait departs from the infinitesimal and additive architecture assumed by most prediction models. We used simulated data for 10,000 lines based on sequence data from a population of unrelated, inbred Drosophila melanogaster lines to evaluate this hypothesis. We show that, even in very simplified scenarios meant as a stress test of the commonly used Genomic Best Linear Unbiased Predictor (G-BLUP) method, using all common variants yields low prediction accuracy regardless of the trait genetic architecture. However, prediction accuracy increases when predictions are informed by the genetic architecture inferred from mapping the top variants affecting main effects and interactions in the training data, provided there is sufficient power for mapping. When the true genetic architecture is largely or partially due to epistatic interactions, the additive model may not perform well, while models that account explicitly for interactions generally increase prediction accuracy. Our results indicate that accounting for genetic architecture can improve prediction accuracy for quantitative traits.

Loss of Bad expression confers poor prognosis in non-small cell lung cancer.

PubMed

Huang, Yi; Liu, Dan; Chen, Bojiang; Zeng, Jing; Wang, Lei; Zhang, Shangfu; Mo, Xianming; Li, Weimin

2012-09-01

Proapoptotic BH-3-only protein Bad (Bcl-Xl/Bcl-2-associated death promoter homolog, Bad) initiates apoptosis in human cells, and contributes to tumorigenesis and chemotherapy resistant in malignancies. This study explored association between the Bad expression level and prognosis in patients with non-small cell lung cancer (NSCLC). In our study, a cohort of 88 resected primary NSCLC cases were collected and analyzed. Bad expression level was determined via immunohistochemical staining assay. The prognostic significances of Bad expression were evaluated with univariate and multivariate survival analysis. The results showed that compared with normal lung tissues, Bad expression level significantly decreased in NSCLC (P < 0.05). Bad expression was associated with adjuvant therapy status. Loss of Bad independently predicted poor prognosis in whole NSCLC cohort and early stage subjects (T1 + T2 and N0 + N1) (all P < 0.05). Overall survival time was also drastically shortened for Bad negative phenotype in NSCLC patients with smoking history, especially lung squamous cell carcinoma (all P < 0.05). In conclusion, this study provided clinical evidence that loss of Bad is an independent and powerful predictor of adverse prognosis in NSCLC. Bad protein could be a new biomarker for selecting individual therapy strategies and predicting therapeutic response in subjects with NSCLC.

Clinical utility of the Conners' Continuous Performance Test-II to detect poor effort in U.S. military personnel following traumatic brain injury.

PubMed

Lange, Rael T; Iverson, Grant L; Brickell, Tracey A; Staver, Tara; Pancholi, Sonal; Bhagwat, Aditya; French, Louis M

2013-06-01

The purpose of this study is to examine the clinical utility of the Conners' Continuous Performance Test (CPT-II) as an embedded marker of poor effort in military personnel undergoing neuropsychological evaluations following traumatic brain injury. Participants were 158 U.S. military service members divided into 3 groups on the basis of brain injury severity and performance (pass/fail) on 2 symptom validity tests: Mild Traumatic Brain Injury (MTBI)-Pass (n = 87), MTBI-Fail (n = 42), and severe traumatic brain injury (STBI)-Pass (n = 29). The MTBI-Fail group performed worse on the majority of CPT-II measures compared with both the MTBI-Pass and STBI-Pass groups. When comparing the MTBI-Fail group and MTBI-Pass groups, the most accurate measure for identifying poor effort was the Commission T score. When selected measures were combined (i.e., Omissions, Commissions, and Perseverations), there was a very small increase in sensitivity (from .26 to .29). When comparing the MTBI-Fail group and STBI-Pass groups, the most accurate measure for identifying poor effort was the Omission and Commissions T score. When selected measures were combined, sensitivity again increased (from .24 to .45). Overall, these results suggest that individual CPT-II measures can be useful for identifying people who are suspected of providing poor effort from those who have provided adequate effort. However, due to low sensitivity and modest negative predictive power values, this measure cannot be used in isolation to detect poor effort, and is largely useful as a test to "rule in," not "rule out" poor effort. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Low-metallicity (sub-SMC) massive stars

NASA Astrophysics Data System (ADS)

Garcia, Miriam; Herrero, Artemio; Najarro, Francisco; Camacho, Inés; Lennon, Daniel J.; Urbaneja, Miguel A.; Castro, Norberto

2017-11-01

The double distance and metallicity frontier marked by the SMC has been finally broken with the aid of powerful multi-object spectrographs installed at 8-10m class telescopes. VLT, GTC and Keck have enabled studies of massive stars in dwarf irregular galaxies of the Local Group with poorer metal-content than the SMC. The community is working to test the predictions of evolutionary models in the low-metallicity regime, set the new standard for the metal-poor high-redshift Universe, and test the extrapolation of the physics of massive stars to environments of decreasing metallicity. In this paper, we review current knowledge on this topic.

Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification.

PubMed

Shimoni, Yishai

2018-02-01

One of the goals of cancer research is to identify a set of genes that cause or control disease progression. However, although multiple such gene sets were published, these are usually in very poor agreement with each other, and very few of the genes proved to be functional therapeutic targets. Furthermore, recent findings from a breast cancer gene-expression cohort showed that sets of genes selected randomly can be used to predict survival with a much higher probability than expected. These results imply that many of the genes identified in breast cancer gene expression analysis may not be causal of cancer progression, even though they can still be highly predictive of prognosis. We performed a similar analysis on all the cancer types available in the cancer genome atlas (TCGA), namely, estimating the predictive power of random gene sets for survival. Our work shows that most cancer types exhibit the property that random selections of genes are more predictive of survival than expected. In contrast to previous work, this property is not removed by using a proliferation signature, which implies that proliferation may not always be the confounder that drives this property. We suggest one possible solution in the form of data-driven sub-classification to reduce this property significantly. Our results suggest that the predictive power of random gene sets may be used to identify the existence of sub-classes in the data, and thus may allow better understanding of patient stratification. Furthermore, by reducing the observed bias this may allow more direct identification of biologically relevant, and potentially causal, genes.

Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification

PubMed Central

2018-01-01

One of the goals of cancer research is to identify a set of genes that cause or control disease progression. However, although multiple such gene sets were published, these are usually in very poor agreement with each other, and very few of the genes proved to be functional therapeutic targets. Furthermore, recent findings from a breast cancer gene-expression cohort showed that sets of genes selected randomly can be used to predict survival with a much higher probability than expected. These results imply that many of the genes identified in breast cancer gene expression analysis may not be causal of cancer progression, even though they can still be highly predictive of prognosis. We performed a similar analysis on all the cancer types available in the cancer genome atlas (TCGA), namely, estimating the predictive power of random gene sets for survival. Our work shows that most cancer types exhibit the property that random selections of genes are more predictive of survival than expected. In contrast to previous work, this property is not removed by using a proliferation signature, which implies that proliferation may not always be the confounder that drives this property. We suggest one possible solution in the form of data-driven sub-classification to reduce this property significantly. Our results suggest that the predictive power of random gene sets may be used to identify the existence of sub-classes in the data, and thus may allow better understanding of patient stratification. Furthermore, by reducing the observed bias this may allow more direct identification of biologically relevant, and potentially causal, genes. PMID:29470520

External Validation of European System for Cardiac Operative Risk Evaluation II (EuroSCORE II) for Risk Prioritization in an Iranian Population

PubMed Central

Atashi, Alireza; Amini, Shahram; Tashnizi, Mohammad Abbasi; Moeinipour, Ali Asghar; Aazami, Mathias Hossain; Tohidnezhad, Fariba; Ghasemi, Erfan; Eslami, Saeid

2018-01-01

Introduction The European System for Cardiac Operative Risk Evaluation II (EuroSCORE II) is a prediction model which maps 18 predictors to a 30-day post-operative risk of death concentrating on accurate stratification of candidate patients for cardiac surgery. Objective The objective of this study was to determine the performance of the EuroSCORE II risk-analysis predictions among patients who underwent heart surgeries in one area of Iran. Methods A retrospective cohort study was conducted to collect the required variables for all consecutive patients who underwent heart surgeries at Emam Reza hospital, Northeast Iran between 2014 and 2015. Univariate and multivariate analysis were performed to identify covariates which significantly contribute to higher EuroSCORE II in our population. External validation was performed by comparing the real and expected mortality using area under the receiver operating characteristic curve (AUC) for discrimination assessment. Also, Brier Score and Hosmer-Lemeshow goodness-of-fit test were used to show the overall performance and calibration level, respectively. Results Two thousand five hundred eight one (59.6% males) were included. The observed mortality rate was 3.3%, but EuroSCORE II had a prediction of 4.7%. Although the overall performance was acceptable (Brier score=0.047), the model showed poor discriminatory power by AUC=0.667 (sensitivity=61.90, and specificity=66.24) and calibration (Hosmer-Lemeshow test, P<0.01). Conclusion Our study showed that the EuroSCORE II discrimination power is less than optimal for outcome prediction and less accurate for resource allocation programs. It highlights the need for recalibration of this risk stratification tool aiming to improve post cardiac surgery outcome predictions in Iran. PMID:29617500

Predictors of Mortality in the Critically Ill Cirrhotic Patient: Is the Model for End-Stage Liver Disease Enough?

PubMed

Annamalai, Alagappan; Harada, Megan Y; Chen, Melissa; Tran, Tram; Ko, Ara; Ley, Eric J; Nuno, Miriam; Klein, Andrew; Nissen, Nicholas; Noureddin, Mazen

2017-03-01

Critically ill cirrhotics require liver transplantation urgently, but are at high risk for perioperative mortality. The Model for End-stage Liver Disease (MELD) score, recently updated to incorporate serum sodium, estimates survival probability in patients with cirrhosis, but needs additional evaluation in the critically ill. The purpose of this study was to evaluate the predictive power of ICU admission MELD scores and identify clinical risk factors associated with increased mortality. This was a retrospective review of cirrhotic patients admitted to the ICU between January 2011 and December 2014. Patients who were discharged or underwent transplantation (survivors) were compared with those who died (nonsurvivors). Demographic characteristics, admission MELD scores, and clinical risk factors were recorded. Multivariate regression was used to identify independent predictors of mortality, and measures of model performance were assessed to determine predictive accuracy. Of 276 patients who met inclusion criteria, 153 were considered survivors and 123 were nonsurvivors. Survivor and nonsurvivor cohorts had similar demographic characteristics. Nonsurvivors had increased MELD, gastrointestinal bleeding, infection, mechanical ventilation, encephalopathy, vasopressors, dialysis, renal replacement therapy, requirement of blood products, and ICU length of stay. The MELD demonstrated low predictive power (c-statistic 0.73). Multivariate analysis identified MELD score (adjusted odds ratio [AOR] = 1.05), mechanical ventilation (AOR = 4.55), vasopressors (AOR = 3.87), and continuous renal replacement therapy (AOR = 2.43) as independent predictors of mortality, with stronger predictive accuracy (c-statistic 0.87). The MELD demonstrated relatively poor predictive accuracy in critically ill patients with cirrhosis and might not be the best indicator for prognosis in the ICU population. Prognostic accuracy is significantly improved when variables indicating organ support (mechanical ventilation, vasopressors, and continuous renal replacement therapy) are included in the model. Copyright © 2016. Published by Elsevier Inc.

Poor anaerobic power/capability and static balance predicted prospective musculoskeletal injuries among Soldiers of the 101st Airborne (Air Assault) Division.

PubMed

Nagai, Takashi; Lovalekar, Mita; Wohleber, Meleesa F; Perlsweig, Katherine A; Wirt, Michael D; Beals, Kim

2017-11-01

Musculoskeletal injuries have negatively impacted tactical readiness. The identification of prospective and modifiable risk factors of preventable musculoskeletal injuries can guide specific injury prevention strategies for Soldiers and health care providers. To analyze physiological and neuromuscular characteristics as predictors of preventable musculoskeletal injuries. Prospective-cohort study. A total of 491 Soldiers were enrolled and participated in the baseline laboratory testing, including body composition, aerobic capacity, anaerobic power/capacity, muscular strength, flexibility, static balance, and landing biomechanics. After reviewing their medical charts, 275 male Soldiers who met the criteria were divided into two groups: with injuries (INJ) and no injuries (NOI). Simple and multiple logistic regression analyses were used to calculate the odds ratio (OR) and significant predictors of musculoskeletal injuries (p<0.05). The final multiple logistic regression model included the static balance with eyes-closed and peak anaerobic power as predictors of future injuries (p<0.001). The current results highlighted the importance of anaerobic power/capacity and static balance. High intensity training and balance exercise should be incorporated in their physical training as countermeasures. Copyright © 2017 Sports Medicine Australia. All rights reserved.

Canary in a coal mine: does the plastic surgery market predict the american economy?

PubMed

Wong, Wendy W; Davis, Drew G; Son, Andrew K; Camp, Matthew C; Gupta, Subhas C

2010-08-01

Economic tools have been used in the past to predict the trends in plastic surgery procedures. Since 1992, U.S. cosmetic surgery volumes have increased overall, but the exact relationship between economic downturns and procedural volumes remains elusive. If an economic predicting role can be established from plastic surgery indicators, this could prove to be a very powerful tool. A rolling 3-month revenue average of an eight-plastic surgeon practice and various economic indicators were plotted and compared. An investigation of the U.S. procedural volumes was performed from the American Society of Plastic Surgeons statistics between 1996 and 2008. The correlations of different economic variables with plastic surgery volumes were evaluated. Lastly, search term frequencies were examined from 2004 to July of 2009 to study potential patient interest in major plastic surgery procedures. The self-payment revenue of the plastic surgery group consistently proved indicative of the market trends approximately 1 month in advance. The Standard and Poor's 500, Dow Jones Industrial Average, National Association of Securities Dealers Automated Quotations, and Standard and Poor's Retail Index demonstrated a very close relationship with the income of our plastic surgery group. The frequency of Internet search terms showed a constant level of interest in the patient population despite economic downturns. The data demonstrate that examining plastic surgery revenue can be a useful tool to analyze and possibly predict trends, as it is driven by a market and shows a close correlation to many leading economic indicators. The persisting and increasing interest in plastic surgery suggests hope for a recovering and successful market in the near future.

The future is in the numbers: the power of predictive analysis in the biomedical educational environment

PubMed Central

Gullo, Charles A.

2016-01-01

Biomedical programs have a potential treasure trove of data they can mine to assist admissions committees in identification of students who are likely to do well and help educational committees in the identification of students who are likely to do poorly on standardized national exams and who may need remediation. In this article, we provide a step-by-step approach that schools can utilize to generate data that are useful when predicting the future performance of current students in any given program. We discuss the use of linear regression analysis as the means of generating that data and highlight some of the limitations. Finally, we lament on how the combination of these institution-specific data sets are not being fully utilized at the national level where these data could greatly assist programs at large. PMID:27374246

Neurophysiological prediction of neurological good and poor outcome in post-anoxic coma.

PubMed

Grippo, A; Carrai, R; Scarpino, M; Spalletti, M; Lanzo, G; Cossu, C; Peris, A; Valente, S; Amantini, A

2017-06-01

Investigation of the utility of association between electroencephalogram (EEG) and somatosensory-evoked potentials (SEPs) for the prediction of neurological outcome in comatose patients resuscitated after cardiac arrest (CA) treated with therapeutic hypothermia, according to different recording times after CA. Glasgow Coma Scale, EEG and SEPs performed at 12, 24 and 48-72 h after CA were assessed in 200 patients. Outcome was evaluated by Cerebral Performance Category 6 months after CA. Within 12 h after CA, grade 1 EEG predicted good outcome and bilaterally absent (BA) SEPs predicted poor outcome. Because grade 1 EEG and BA-SEPs were never found in the same patient, the recording of both EEG and SEPs allows us to correctly prognosticate a greater number of patients with respect to the use of a single test within 12 h after CA. At 48-72 h after CA, both grade 2 EEG and BA-SEPs predicted poor outcome with FPR=0.0%. When these neurophysiological patterns are both present in the same patient, they confirm and strengthen their prognostic value, but because they also occurred independently in eight patients, poor outcome is predictable in a greater number of patients. The combination of EEG/SEP findings allows prediction of good and poor outcome (within 12 h after CA) and of poor outcome (after 48-72 h). Recording of EEG and SEPs in the same patients allows always an increase in the number of cases correctly classified, and an increase of the reliability of prognostication in a single patient due to concordance of patterns. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Poor outcome prediction by burst suppression ratio in adults with post-anoxic coma without hypothermia.

PubMed

Yang, Qinglin; Su, Yingying; Hussain, Mohammed; Chen, Weibi; Ye, Hong; Gao, Daiquan; Tian, Fei

2014-05-01

Burst suppression ratio (BSR) is a quantitative electroencephalography (qEEG) parameter. The purpose of our study was to compare the accuracy of BSR when compared to other EEG parameters in predicting poor outcomes in adults who sustained post-anoxic coma while not being subjected to therapeutic hypothermia. EEG was registered and recorded at least once within 7 days of post-anoxic coma onset. Electrodes were placed according to the international 10-20 system, using a 16-channel layout. Each EEG expert scored raw EEG using a grading scale adapted from Young and scored amplitude-integrated electroencephalography tracings, in addition to obtaining qEEG parameters defined as BSR with a defined threshold. Glasgow outcome scales of 1 and 2 at 3 months, determined by two blinded neurologists, were defined as poor outcome. Sixty patients with Glasgow coma scale score of 8 or less after anoxic accident were included. The sensitivity (97.1%), specificity (73.3%), positive predictive value (82.5%), and negative prediction value (95.0%) of BSR in predicting poor outcome were higher than other EEG variables. BSR1 and BSR2 were reliable in predicting death (area under the curve > 0.8, P < 0.05), with the respective cutoff points being 39.8% and 61.6%. BSR1 was reliable in predicting poor outcome (area under the curve  =  0.820, P < 0.05) with a cutoff point of 23.9%. BSR1 was also an independent predictor of increased risk of death (odds ratio  =  1.042, 95% confidence intervals: 1.012-1.073, P  =  0.006). BSR may be a better predictor in prognosticating poor outcomes in patients with post-anoxic coma who do not undergo therapeutic hypothermia when compared to other qEEG parameters.

What variables are important in predicting bovine viral diarrhea virus? A random forest approach.

PubMed

Machado, Gustavo; Mendoza, Mariana Recamonde; Corbellini, Luis Gustavo

2015-07-24

Bovine viral diarrhea virus (BVDV) causes one of the most economically important diseases in cattle, and the virus is found worldwide. A better understanding of the disease associated factors is a crucial step towards the definition of strategies for control and eradication. In this study we trained a random forest (RF) prediction model and performed variable importance analysis to identify factors associated with BVDV occurrence. In addition, we assessed the influence of features selection on RF performance and evaluated its predictive power relative to other popular classifiers and to logistic regression. We found that RF classification model resulted in an average error rate of 32.03% for the negative class (negative for BVDV) and 36.78% for the positive class (positive for BVDV).The RF model presented area under the ROC curve equal to 0.702. Variable importance analysis revealed that important predictors of BVDV occurrence were: a) who inseminates the animals, b) number of neighboring farms that have cattle and c) rectal palpation performed routinely. Our results suggest that the use of machine learning algorithms, especially RF, is a promising methodology for the analysis of cross-sectional studies, presenting a satisfactory predictive power and the ability to identify predictors that represent potential risk factors for BVDV investigation. We examined classical predictors and found some new and hard to control practices that may lead to the spread of this disease within and among farms, mainly regarding poor or neglected reproduction management, which should be considered for disease control and eradication.

Building spatially-explicit model predictions for ecological condition of streams in the Pacific Northwest: An assessment of landscape variables, models, endpoints and prediction scale

EPA Science Inventory

While large-scale, randomized surveys estimate the percentage of a region’s streams in poor ecological condition, identifying particular stream reaches or watersheds in poor condition is an equally important goal for monitoring and management. We built predictive models of strea...

Inertia may limit efficiency of slow flapping flight, but mayflies show a strategy for reducing the power requirements of loiter.

PubMed

Usherwood, James R

2009-03-01

Predictions from aerodynamic theory often match biological observations very poorly. Many insects and several bird species habitually hover, frequently flying at low advance ratios. Taking helicopter-based aerodynamic theory, wings functioning predominantly for hovering, even for quite small insects, should operate at low angles of attack. However, insect wings operate at very high angles of attack during hovering; reduction in angle of attack should result in considerable energetic savings. Here, I consider the possibility that selection of kinematics is constrained from being aerodynamically optimal due to the inertial power requirements of flapping. Potential increases in aerodynamic efficiency with lower angles of attack during hovering may be outweighed by increases in inertial power due to the associated increases in flapping frequency. For simple hovering, traditional rotary-winged helicopter-like micro air vehicles would be more efficient than their flapping biomimetic counterparts. However, flapping may confer advantages in terms of top speed and manoeuvrability. If flapping-winged micro air vehicles are required to hover or loiter more efficiently, dragonflies and mayflies suggest biomimetic solutions.

Testing the Trower and Chadwick model of paranoia: Is 'poor-me' and 'bad-me' paranoia acting as a defence?

PubMed

Marley, Charles; Jones, Jason; Jones, Christopher A

2017-12-01

The study tested the predicted differences in phenomenology (self-esteem and depression) and insecurity of the subgroups of paranoia proposed by the Trower and Chadwick (1995) model of paranoia. Thirty-two inpatients experiencing persecutory delusions were assigned to either the poor me or bad me paranoid group. Questionnaire assessment of depression and self-esteem were conducted. A Dot Probe task measured detection latency (reaction time) to poor me words, bad me words and neutral words. The poor me and bad me groups displayed the predicted phenomenological differences. The dot probe task did not support the predicted insecurities of the Trower and Chadwick model, but unexpected significant results for the poor me subgroup may offer support for an alternative explanation of paranoia as an unstable phenomenon. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Beyond Phonology: Visual Processes Predict Alphanumeric and Nonalphanumeric Rapid Naming in Poor Early Readers

ERIC Educational Resources Information Center

Kruk, Richard S.; Luther Ruban, Cassia

2018-01-01

Visual processes in Grade 1 were examined for their predictive influences in nonalphanumeric and alphanumeric rapid naming (RAN) in 51 poor early and 69 typical readers. In a lagged design, children were followed longitudinally from Grade 1 to Grade 3 over 5 testing occasions. RAN outcomes in early Grade 2 were predicted by speeded and nonspeeded…

A reinforcement sensitivity model of affective and behavioral dysregulation in marijuana use and associated problems.

PubMed

Emery, Noah N; Simons, Jeffrey S

2017-08-01

This study tested a model linking sensitivity to punishment (SP) and reward (SR) to marijuana use and problems via affect lability and poor control. A 6-month prospective design was used in a sample of 2,270 young-adults (64% female). The hypothesized SP × SR interaction did not predict affect lability or poor control, but did predict use likelihood at baseline. At low levels of SR, SP was associated with an increased likelihood of abstaining, which was attenuated as SR increased. SP and SR displayed positive main effects on both affect lability and poor control. Affect lability and poor control, in turn, mediated effects on the marijuana outcomes. Poor control predicted both increased marijuana use and, controlling for use level, greater intensity of problems. Affect lability predicted greater intensity of problems, but was not associated with use level. There were few prospective effects. SR consistently predicted greater marijuana use and problems. SP however, exhibited both risk and protective pathways. Results indicate that SP is associated with a decreased likelihood of marijuana use. However, once use is initiated SP is associated with increased risk of problems, in part, due to its effects on both affect and behavioral dysregulation. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Social Anxiety and Friendship Quality over Time.

PubMed

Rodebaugh, Thomas L; Lim, Michelle H; Shumaker, Erik A; Levinson, Cheri A; Thompson, Tess

2015-01-01

High social anxiety in adults is associated with self-report of impaired friendship quality, but not necessarily with impairment reported by friends. Further, prospective prediction of social anxiety and friendship quality over time has not been tested among adults. We therefore examined friendship quality and social anxiety prospectively in 126 young adults (67 primary participants and 59 friends, aged 17-22 years); the primary participants were screened to be extreme groups to increase power and relevance to clinical samples (i.e., they were recruited based on having very high or very low social interaction anxiety). The prospective relationships between friendship quality and social anxiety were then tested using an Actor-Partner Interdependence Model. Friendship quality prospectively predicted social anxiety over time within each individual in the friendship, such that higher friendship quality at Time 1 predicted lower social anxiety approximately 6 months later at Time 2. Social anxiety did not predict friendship quality. Although the results support the view that social anxiety and friendship quality have an important causal relationship, the results run counter to the assumption that high social anxiety causes poor friendship quality. Interventions to increase friendship quality merit further consideration.

Flight Stability and Control and Performance Results from the Linear Aerospike SR-71 Experiment (LASRE)

NASA Technical Reports Server (NTRS)

Moes, Timothy R.; Cobleigh, Brent R.; Cox, Timothy H.; Conners, Timothy R.; Iliff, Kenneth W.; Powers, Bruce G.

1998-01-01

The Linear Aerospike SR-71 Experiment (LASRE) is presently being conducted to test a 20-percent-scale version of the Linear Aerospike rocket engine. This rocket engine has been chosen to power the X-33 Single Stage to Orbit Technology Demonstrator Vehicle. The rocket engine was integrated into a lifting body configuration and mounted to the upper surface of an SR-71 aircraft. This paper presents stability and control results and performance results from the envelope expansion flight tests of the LASRE configuration up to Mach 1.8 and compares the results with wind tunnel predictions. Longitudinal stability and elevator control effectiveness were well-predicted from wind tunnel tests. Zero-lift pitching moment was mispredicted transonically. Directional stability, dihedral stability, and rudder effectiveness were overpredicted. The SR-71 handling qualities were never significantly impacted as a result of the missed predictions. Performance results confirmed the large amount of wind-tunnel-predicted transonic drag for the LASRE configuration. This drag increase made the performance of the vehicle so poor that acceleration through transonic Mach numbers could not be achieved on a hot day without depleting the available fuel.

Deep learning of the regulatory grammar of yeast 5′ untranslated regions from 500,000 random sequences

PubMed Central

Groves, Benjamin; Kuchina, Anna; Rosenberg, Alexander B.; Jojic, Nebojsa; Fields, Stanley; Seelig, Georg

2017-01-01

Our ability to predict protein expression from DNA sequence alone remains poor, reflecting our limited understanding of cis-regulatory grammar and hampering the design of engineered genes for synthetic biology applications. Here, we generate a model that predicts the protein expression of the 5′ untranslated region (UTR) of mRNAs in the yeast Saccharomyces cerevisiae. We constructed a library of half a million 50-nucleotide-long random 5′ UTRs and assayed their activity in a massively parallel growth selection experiment. The resulting data allow us to quantify the impact on protein expression of Kozak sequence composition, upstream open reading frames (uORFs), and secondary structure. We trained a convolutional neural network (CNN) on the random library and showed that it performs well at predicting the protein expression of both a held-out set of the random 5′ UTRs as well as native S. cerevisiae 5′ UTRs. The model additionally was used to computationally evolve highly active 5′ UTRs. We confirmed experimentally that the great majority of the evolved sequences led to higher protein expression rates than the starting sequences, demonstrating the predictive power of this model. PMID:29097404

The relation between statistical power and inference in fMRI

PubMed Central

Wager, Tor D.; Yarkoni, Tal

2017-01-01

Statistically underpowered studies can result in experimental failure even when all other experimental considerations have been addressed impeccably. In fMRI the combination of a large number of dependent variables, a relatively small number of observations (subjects), and a need to correct for multiple comparisons can decrease statistical power dramatically. This problem has been clearly addressed yet remains controversial—especially in regards to the expected effect sizes in fMRI, and especially for between-subjects effects such as group comparisons and brain-behavior correlations. We aimed to clarify the power problem by considering and contrasting two simulated scenarios of such possible brain-behavior correlations: weak diffuse effects and strong localized effects. Sampling from these scenarios shows that, particularly in the weak diffuse scenario, common sample sizes (n = 20–30) display extremely low statistical power, poorly represent the actual effects in the full sample, and show large variation on subsequent replications. Empirical data from the Human Connectome Project resembles the weak diffuse scenario much more than the localized strong scenario, which underscores the extent of the power problem for many studies. Possible solutions to the power problem include increasing the sample size, using less stringent thresholds, or focusing on a region-of-interest. However, these approaches are not always feasible and some have major drawbacks. The most prominent solutions that may help address the power problem include model-based (multivariate) prediction methods and meta-analyses with related synthesis-oriented approaches. PMID:29155843

Is acetaminophen safe in pregnancy?

PubMed

Toda, Katsuhiro

2017-10-01

Acetaminophen is thought to be the safest analgesic and antipyretic medicine for pregnant women, and it is widely used all over the world. However, prenatal acetaminophen was reported to be associated with asthma, lower performance intelligence quotient (IQ), shorter male infant anogenital distance (predicting poor male reproductive potential), autism spectrum disorder, neurodevelopmental problems (gross motor development, communication), attention-deficit/hyperactivity disorder, poorer attention and executive function, and behavioral problems in childhood. Each article has poor power to show risks of acetaminophen, however, the integration of the articles that showed adverse effects of acetaminophen may have power to show them. Acetaminophen use in childhood was associated with autism spectrum disorder, asthma symptoms, wheezing, and allergic disease. Acetaminophen is the safest medicine as analgesics for nociceptive pain and antipyretics in childhood and pregnancy. There is no alternative medication of acetaminophen. Acetaminophen should not be withheld from children or pregnant women for fears it might develop adverse effects. Acetaminophen should be used at the lowest effective dosage and for the shortest time. When we know the possible, rare but serious complications, we should use acetaminophen in pregnancy only when needed and no safer option for pain or fever relief is available. Health care providers should help inform the general lay public about this difficult dilemma. Copyright © 2017 Scandinavian Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

Early cumulative risk predicts externalizing behavior at age 10: The mediating role of adverse parenting.

PubMed

Gach, Emily J; Ip, Ka I; Sameroff, Arnold J; Olson, Sheryl L

2018-02-01

Multiple environmental risk factors in early childhood predict a broad range of adverse developmental outcomes. However, most prior longitudinal research has not illuminated explanatory mechanisms. Our main goals were to examine predictive associations between cumulative ecological risk factors in early childhood and children's later externalizing problems and to determine whether these associations were explained by variations in parenting quality. Participants were 241 children (118 girls) at risk for school-age conduct problems and their parents and teachers. Children were approximately 3 years old at Time 1 (T1) and 10 years old at Time 2 (T2). Reports of contextual risk at T1 were used to develop a cumulative risk index consisting of 6 singular risk variables from 3 ecological levels: social resources (low income; social isolation), family resources (marital aggression; poor total family functioning), and maternal resources (single parent status; poor maternal mental health). At T1, parenting variables were measured (corporal punishment, warm responsiveness, maternal efficacy, and negative perceptions of child behavior). At T2, mothers, fathers, and teachers reported child externalizing problems. Johnson's relative weight analysis revealed that the cumulative risk index was a more powerful predictor of age 10 years externalizing behavior than any of the singular contextual risk variables. Adverse parenting mediated the effects of cumulative risk on later child externalizing problems. Our findings have significant implications for understanding long-term effects of multiple contextual risk factors present in early childhood and for the implementation of positive parenting interventions early on. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

[Acute kidney injury after pediatric cardiac surgery: risk factors and outcomes. Proposal for a predictive model].

PubMed

Cardoso, Bárbara; Laranjo, Sérgio; Gomes, Inês; Freitas, Isabel; Trigo, Conceição; Fragata, Isabel; Fragata, José; Pinto, Fátima

2016-02-01

To characterize the epidemiology and risk factors for acute kidney injury (AKI) after pediatric cardiac surgery in our center, to determine its association with poor short-term outcomes, and to develop a logistic regression model that will predict the risk of AKI for the study population. This single-center, retrospective study included consecutive pediatric patients with congenital heart disease who underwent cardiac surgery between January 2010 and December 2012. Exclusion criteria were a history of renal disease, dialysis or renal transplantation. Of the 325 patients included, median age three years (1 day-18 years), AKI occurred in 40 (12.3%) on the first postoperative day. Overall mortality was 13 (4%), nine of whom were in the AKI group. AKI was significantly associated with length of intensive care unit stay, length of mechanical ventilation and in-hospital death (p<0.01). Patients' age and postoperative serum creatinine, blood urea nitrogen and lactate levels were included in the logistic regression model as predictor variables. The model accurately predicted AKI in this population, with a maximum combined sensitivity of 82.1% and specificity of 75.4%. AKI is common and is associated with poor short-term outcomes in this setting. Younger age and higher postoperative serum creatinine, blood urea nitrogen and lactate levels were powerful predictors of renal injury in this population. The proposed model could be a useful tool for risk stratification of these patients. Copyright © 2015 Sociedade Portuguesa de Cardiologia. Published by Elsevier España. All rights reserved.

Small-for-gestational age and large-for-gestational age thresholds to predict infants at risk of adverse delivery and neonatal outcomes: are current charts adequate? An observational study from the Born in Bradford cohort

PubMed Central

Norris, T; Johnson, W; Farrar, D; Tuffnell, D; Wright, J; Cameron, N

2015-01-01

Objectives Construct an ethnic-specific chart and compare the prediction of adverse outcomes using this chart with the clinically recommended UK-WHO and customised birth weight charts using cut-offs for small-for-gestational age (SGA: birth weight <10th centile) and large-for-gestational age (LGA: birth weight >90th centile). Design Prospective cohort study. Setting Born in Bradford (BiB) study, UK. Participants 3980 White British and 4448 Pakistani infants with complete data for gestational age, birth weight, ethnicity, maternal height, weight and parity. Main outcome measures Prevalence of SGA and LGA, using the three charts and indicators of diagnostic utility (sensitivity, specificity and area under the receiver operating characteristic (AUROC)) of these chart-specific cut-offs to predict delivery and neonatal outcomes and a composite outcome. Results In White British and Pakistani infants, the prevalence of SGA and LGA differed depending on the chart used. Increased risk of SGA was observed when using the UK-WHO and customised charts as opposed to the ethnic-specific chart, while the opposite was apparent when classifying LGA infants. However, the predictive utility of all three charts to identify adverse clinical outcomes was poor, with only the prediction of shoulder dystocia achieving an AUROC>0.62 on all three charts. Conclusions Despite being recommended in national clinical guidelines, the UK-WHO and customised birth weight charts perform poorly at identifying infants at risk of adverse neonatal outcomes. Being small or large may increase the risk of an adverse outcome; however, size alone is not sensitive or specific enough with current detection to be useful. However, a significant amount of missing data for some of the outcomes may have limited the power needed to determine true associations. PMID:25783424

Development of a Risk Score Based on Aortic Calcification to Predict 1-year Mortality After Transcatheter Aortic Valve Replacement.

PubMed

Lantelme, Pierre; Eltchaninoff, Hélène; Rabilloud, Muriel; Souteyrand, Géraud; Dupré, Marion; Spaziano, Marco; Bonnet, Marc; Becle, Clément; Riche, Benjamin; Durand, Eric; Bouvier, Erik; Dacher, Jean-Nicolas; Courand, Pierre-Yves; Cassagnes, Lucie; Dávila Serrano, Eduardo E; Motreff, Pascal; Boussel, Loic; Lefèvre, Thierry; Harbaoui, Brahim

2018-05-11

The aim of this study was to develop a new scoring system based on thoracic aortic calcification (TAC) to predict 1-year cardiovascular and all-cause mortality. A calcified aorta is often associated with poor prognosis after transcatheter aortic valve replacement (TAVR). A risk score encompassing aortic calcification may be valuable in identifying poor TAVR responders. The C 4 CAPRI (4 Cities for Assessing CAlcification PRognostic Impact) multicenter study included a training cohort (1,425 patients treated using TAVR between 2010 and 2014) and a contemporary test cohort (311 patients treated in 2015). TAC was measured by computed tomography pre-TAVR. CAPRI risk scores were based on the linear predictors of Cox models including TAC in addition to comorbidities and demographic, atherosclerotic disease and cardiac function factors. CAPRI scores were constructed and tested in 2 independent cohorts. Cardiovascular and all-cause mortality at 1 year was 13.0% and 17.9%, respectively, in the training cohort and 8.2% and 11.8% in the test cohort. The inclusion of TAC in the model improved prediction: 1-cm 3 increase in TAC was associated with a 6% increase in cardiovascular mortality and a 4% increase in all-cause mortality. The predicted and observed survival probabilities were highly correlated (slopes >0.9 for both cardiovascular and all-cause mortality). The model's predictive power was fair (AUC 68% [95% confidence interval [CI]: 64-72]) for both cardiovascular and all-cause mortality. The model performed similarly in the training and test cohorts. The CAPRI score, which combines the TAC variable with classical prognostic factors, is predictive of 1-year cardiovascular and all-cause mortality. Its predictive performance was confirmed in an independent contemporary cohort. CAPRI scores are highly relevant to current practice and strengthen the evidence base for decision making in valvular interventions. Its routine use may help prevent futile procedures. Copyright © 2018 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

News from the protein mutability landscape.

PubMed

Hecht, Maximilian; Bromberg, Yana; Rost, Burkhard

2013-11-01

Some mutations of protein residues matter more than others, and these are often conserved evolutionarily. The explosion of deep sequencing and genotyping increasingly requires the distinction between effect and neutral variants. The simplest approach predicts all mutations of conserved residues to have an effect; however, this works poorly, at best. Many computational tools that are optimized to predict the impact of point mutations provide more detail. Here, we expand the perspective from the view of single variants to the level of sketching the entire mutability landscape. This landscape is defined by the impact of substituting every residue at each position in a protein by each of the 19 non-native amino acids. We review some of the powerful conclusions about protein function, stability and their robustness to mutation that can be drawn from such an analysis. Large-scale experimental and computational mutagenesis experiments are increasingly furthering our understanding of protein function and of the genotype-phenotype associations. We also discuss how these can be used to improve predictions of protein function and pathogenicity of missense variants. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

What the Most Metal-poor Stars Tell Us About the Early Universe

NASA Astrophysics Data System (ADS)

Frebel, Anna

2008-05-01

The chemical evolution of the Galaxy and the early Universe is a key topic in modern astrophysics. The most metal-poor Galactic halo stars are now frequently used in an attempt to reconstruct the onset of the chemical and dynamical formation processes of the Galaxy. These stars are an easily-accessible local equivalent of the high-redshift Universe, and can thus be used to carry out field-field cosmology. The discovery of two astrophysically very important metal-poor objects has recently lead to a significant advance in the field. One object is the most iron-poor star yet found (with [Fe/H]=-5.4). The other stars displays the strongest known overabundances of heavy neutron-capture elements, such as uranium, and nucleo-chronometry yields a stellar age of 13 Gyr. Both stars already serve as benchmark objects for various theoretical studies with regard to nucleosynthesis processes in the early Galaxy. I will discuss how the abundance patterns of these and other metal-poor stars solidify and advance our understanding of the early Universe, and provide constraints on the nature of the first stars, as well as their explosion mechanisms and corresponding supernova nucleosynthesis yields. Large samples of these old objects are also employed to test theoretical predictions about the formation of the very first low-mass stars. In the near future, the combined power of near-field cosmology results with those of the next-generation facilities (e.g., MWA, JWST, GMT) may yield exceptional details about the formation processes of the first generations of stars and galaxies.

Predictable information in neural signals during resting state is reduced in autism spectrum disorder.

PubMed

Brodski-Guerniero, Alla; Naumer, Marcus J; Moliadze, Vera; Chan, Jason; Althen, Heike; Ferreira-Santos, Fernando; Lizier, Joseph T; Schlitt, Sabine; Kitzerow, Janina; Schütz, Magdalena; Langer, Anne; Kaiser, Jochen; Freitag, Christine M; Wibral, Michael

2018-04-04

The neurophysiological underpinnings of the nonsocial symptoms of autism spectrum disorder (ASD) which include sensory and perceptual atypicalities remain poorly understood. Well-known accounts of less dominant top-down influences and more dominant bottom-up processes compete to explain these characteristics. These accounts have been recently embedded in the popular framework of predictive coding theory. To differentiate between competing accounts, we studied altered information dynamics in ASD by quantifying predictable information in neural signals. Predictable information in neural signals measures the amount of stored information that is used for the next time step of a neural process. Thus, predictable information limits the (prior) information which might be available for other brain areas, for example, to build predictions for upcoming sensory information. We studied predictable information in neural signals based on resting-state magnetoencephalography (MEG) recordings of 19 ASD patients and 19 neurotypical controls aged between 14 and 27 years. Using whole-brain beamformer source analysis, we found reduced predictable information in ASD patients across the whole brain, but in particular in posterior regions of the default mode network. In these regions, epoch-by-epoch predictable information was positively correlated with source power in the alpha and beta frequency range as well as autocorrelation decay time. Predictable information in precuneus and cerebellum was negatively associated with nonsocial symptom severity, indicating a relevance of the analysis of predictable information for clinical research in ASD. Our findings are compatible with the assumption that use or precision of prior knowledge is reduced in ASD patients. © 2018 Wiley Periodicals, Inc.

Estimating Water Levels with Google Earth Engine

NASA Astrophysics Data System (ADS)

Lucero, E.; Russo, T. A.; Zentner, M.; May, J.; Nguy-Robertson, A. L.

2016-12-01

Reservoirs serve multiple functions and are vital for storage, electricity generation, and flood control. For many areas, traditional ground-based reservoir measurements may not be available or data dissemination may be problematic. Consistent monitoring of reservoir levels in data-poor areas can be achieved through remote sensing, providing information to researchers and the international community. Estimates of trends and relative reservoir volume can be used to identify water supply vulnerability, anticipate low power generation, and predict flood risk. Image processing with automated cloud computing provides opportunities to study multiple geographic areas in near real-time. We demonstrate the prediction capability of a cloud environment for identifying water trends at reservoirs in the US, and then apply the method to data-poor areas in North Korea, Iran, Azerbaijan, Zambia, and India. The Google Earth Engine cloud platform hosts remote sensing data and can be used to automate reservoir level estimation with multispectral imagery. We combine automated cloud-based analysis from Landsat image classification to identify reservoir surface area trends and radar altimetry to identify reservoir level trends. The study estimates water level trends using three years of data from four domestic reservoirs to validate the remote sensing method, and five foreign reservoirs to demonstrate the method application. We report correlations between ground-based reservoir level measurements in the US and our remote sensing methods, and correlations between the cloud analysis and altimetry data for reservoirs in data-poor areas. The availability of regular satellite imagery and an automated, near real-time application method provides the necessary datasets for further temporal analysis, reservoir modeling, and flood forecasting. All statements of fact, analysis, or opinion are those of the author and do not reflect the official policy or position of the Department of Defense or any of its components or the U.S. Government

Online and offline inferential and textual processing of poor comprehenders: Evidence from a probing method.

PubMed

Yeari, Menahem; Elentok, Shiri; Schiff, Rachel

2017-03-01

Numerous studies have demonstrated that poor inferential processing underlies the specific deficit of poor comprehenders. However, it is still not clear why poor comprehenders have difficulties in generating inferences while reading and whether this impairment is general or specific to one or more types of inferences. The current study employed an online probing method to examine the spontaneous immediate activation of two inference types-forward-predictive inferences and backward-explanatory inferences-during reading. In addition, we examined the ability of poor comprehenders to retain, suppress, and reactivate text information (relevant for inferencing) in working memory. The participants, 10- to 12-year-old good and poor comprehenders, read short narratives and name inference or text word probes following a predictive, intervening, or bridging sentence. Comparing the size of probe-naming facilitations revealed that poor comprehenders generate predictive inferences, albeit more slowly than good comprehenders, and generate explanatory inferences to a lesser extent than good comprehenders. Moreover, we found that this inferior inferential processing is presumably a result of poor retention and reactivation of inference-evoking text information during reading. Finally, poorer reading comprehension was associated with higher activation of information when it was less relevant following the intervening sentences. Taken together, the current findings demonstrate the manner in which poor regulation of relevant and less relevant information during reading underlies the specific comprehension difficulties experienced by poor comprehenders. Copyright © 2016 Elsevier Inc. All rights reserved.

Depressed heart rate variability as an independent predictor of death in chronic congestive heart failure secondary to ischemic or idiopathic dilated cardiomyopathy.

PubMed

Ponikowski, P; Anker, S D; Chua, T P; Szelemej, R; Piepoli, M; Adamopoulos, S; Webb-Peploe, K; Harrington, D; Banasiak, W; Wrabec, K; Coats, A J

1997-06-15

After acute myocardial infarction, depressed heart rate variability (HRV) has been proven to be a powerful independent predictor of a poor outcome. Although patients with chronic congestive heart failure (CHF) have also markedly impaired HRV, the prognostic value of HRV analysis in these patients remains unknown. The aim of this study was to investigate whether HRV parameters could predict survival in 102 consecutive patients with moderate to severe CHF (90 men, mean age 58 years, New York Heart Association [NYHA] class II to IV, CHF due to idiopathic dilated cardiomyopathy in 24 patients and ischemic heart disease in 78 patients, ejection fraction [EF], 26%; peak oxygen consumption, 16.9 ml/kg/min) after exclusion of patients in atrial fibrilation with diabetes or with chronic renal failure. In the prognostic analysis (Cox proportional-hazards model, Kaplan-Meier survival analysis), the following factors were investigated: age, CHF etiology, NYHA class, EF, peak oxygen consumption, presence of ventricular tachycardia on Holter monitoring, and HRV measures derived from 24-hour electrocardiography monitoring, calculated in the time (standard deviation of all normal RR intervals [SDNN], standard deviation of 5-minute RR intervals [SDANN], mean of all 5-minute standard deviations of RR intervals [SD], root-mean-square of difference of successive RR intervals [rMSSD], and percentage of adjacent RR intervals >50 ms different [pNN50]) and frequency domain (total power [TP], power within low-frequency band [LF], and power within high-frequency band [HF]). During follow-up of 584 +/- 405 days (365 days in all who survived), 19 patients (19%) died (mean time to death: 307 +/- 315 days, range 3 to 989). Cox's univariate analysis identified the following factors to be predictors of death: NYHA (p = 0.003), peak oxygen consumption (p = 0.01), EF (p = 0.02), ventricular tachycardia on Holter monitoring (p = 0.05), and among HRV measures: SDNN (p = 0.004), SDANN (p = 0.003), SD (p = 0.02), and LF (p = 0.003). In multivariate analysis, HRV parameters (SDNN, SDANN, LF) were found to predict survival independently of NYHA functional class, EF, peak oxygen consumption, and ventricular tachycardia on Holter monitoring. The Kaplan-Meier survival curves revealed SDNN < 100 ms to be a useful risk factor; 1-year survival in patients with SDNN < 100 ms was 78% when compared with 95% in those with SDNN > 100 ms (p = 0.008). The coexistence of SDNN < 100 ms and a peak oxygen consumption < 14 ml/kg/min allowed identification of a group of 18 patients with a particularly poor prognosis (1-year survival 63% vs 94% in the remaining patients, p <0.001). We conclude that depressed HRV on 24-hour ambulatory electrocardiography monitoring is an independent risk factor for a poor prognosis in patients with CHF. Whether analysis of HRV could be recommended in the risk stratification for better management of patients with CHF needs further investigation.

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.

Motor testing at 1 year improves the prediction of motor and mental outcome at 2 years after perinatal hypoxic-ischaemic encephalopathy.

PubMed

van Schie, Petra E M; Becher, Jules G; Dallmeijer, Annet J; Barkhof, Frederik; Van Weissenbruch, Mirjam M; Vermeulen, R Jeroen

2010-01-01

To investigate the predictive value of motor testing at 1 year for motor and mental outcome at 2 years after perinatal hypoxic-ischaemic encephalopathy (HIE) in term neonates. Motor and mental outcome at 2 years was assessed with the Bayley Scales of Infant Development, 2nd edition (BSID-II) in 32 surviving children (20 males, 12 females; mean gestational age 40.2 wk, SD 1.4; mean birthweight 3217g, SD 435) participating in a prospective cohort study of HIE. The predictive value of three motor tests (Alberta Infant Motor Scale [AIMS], BSID-II, and the Neurological Optimality Score [NOS]) at 1 year was analysed, in addition to predictions based on neonatal Sarnat staging and magnetic resonance imaging (MRI). Poor motor test results were defined as an AIMS z-score of <-2, a psychomotor developmental index of the BSID-II of <70, or a NOS of <26. Poor motor and poor mental outcome at 2 years was defined as a psychomotor developmental index or mental developmental index of the BSID-II of <70. Twelve children, all with Sarnat grade II, had a poor motor outcome and 12 children, of whom one had Sarnat grade I, had a poor mental outcome at 2 years. Nine children had cerebral palsy, of whom five had quadriplegia, three had dyskinesia, and one had hemiplegia. Poor motor tests at 1 year increased the probability of a poor motor outcome from 71% (range 92 to 100%), and a poor mental outcome from 59% (range 77 to 100%) in children with Sarnat grade II and abnormal MRI, assessed with the AIMS and BSID-II or NOS respectively. Additional motor testing at 1 year improves the prediction of motor and mental outcome at 2 years in children with Sarnat grade II and abnormal MRI.

Early EEG for outcome prediction of postanoxic coma: prospective cohort study with cost-minimization analysis.

PubMed

Sondag, Lotte; Ruijter, Barry J; Tjepkema-Cloostermans, Marleen C; Beishuizen, Albertus; Bosch, Frank H; van Til, Janine A; van Putten, Michel J A M; Hofmeijer, Jeannette

2017-05-15

We recently showed that electroencephalography (EEG) patterns within the first 24 hours robustly contribute to multimodal prediction of poor or good neurological outcome of comatose patients after cardiac arrest. Here, we confirm these results and present a cost-minimization analysis. Early prognosis contributes to communication between doctors and family, and may prevent inappropriate treatment. A prospective cohort study including 430 subsequent comatose patients after cardiac arrest was conducted at intensive care units of two teaching hospitals. Continuous EEG was started within 12 hours after cardiac arrest and continued up to 3 days. EEG patterns were visually classified as unfavorable (isoelectric, low-voltage, or burst suppression with identical bursts) or favorable (continuous patterns) at 12 and 24 hours after cardiac arrest. Outcome at 6 months was classified as good (cerebral performance category (CPC) 1 or 2) or poor (CPC 3, 4, or 5). Predictive values of EEG measures and cost-consequences from a hospital perspective were investigated, assuming EEG-based decision- making about withdrawal of life-sustaining treatment in the case of a poor predicted outcome. Poor outcome occurred in 197 patients (51% of those included in the analyses). Unfavorable EEG patterns at 24 hours predicted a poor outcome with specificity of 100% (95% CI 98-100%) and sensitivity of 29% (95% CI 22-36%). Favorable patterns at 12 hours predicted good outcome with specificity of 88% (95% CI 81-93%) and sensitivity of 51% (95% CI 42-60%). Treatment withdrawal based on an unfavorable EEG pattern at 24 hours resulted in a reduced mean ICU length of stay without increased mortality in the long term. This gave small cost reductions, depending on the timing of withdrawal. Early EEG contributes to reliable prediction of good or poor outcome of postanoxic coma and may lead to reduced length of ICU stay. In turn, this may bring small cost reductions.

Univariate Time Series Prediction of Solar Power Using a Hybrid Wavelet-ARMA-NARX Prediction Method

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

Nazaripouya, Hamidreza; Wang, Yubo; Chu, Chi-Cheng

This paper proposes a new hybrid method for super short-term solar power prediction. Solar output power usually has a complex, nonstationary, and nonlinear characteristic due to intermittent and time varying behavior of solar radiance. In addition, solar power dynamics is fast and is inertia less. An accurate super short-time prediction is required to compensate for the fluctuations and reduce the impact of solar power penetration on the power system. The objective is to predict one step-ahead solar power generation based only on historical solar power time series data. The proposed method incorporates discrete wavelet transform (DWT), Auto-Regressive Moving Average (ARMA)more » models, and Recurrent Neural Networks (RNN), while the RNN architecture is based on Nonlinear Auto-Regressive models with eXogenous inputs (NARX). The wavelet transform is utilized to decompose the solar power time series into a set of richer-behaved forming series for prediction. ARMA model is employed as a linear predictor while NARX is used as a nonlinear pattern recognition tool to estimate and compensate the error of wavelet-ARMA prediction. The proposed method is applied to the data captured from UCLA solar PV panels and the results are compared with some of the common and most recent solar power prediction methods. The results validate the effectiveness of the proposed approach and show a considerable improvement in the prediction precision.« less

Predictors of Poor Seizure Control in Children Managed at a Tertiary Care Hospital of Eastern Nepal

PubMed Central

POUDEL, Prakash; CHITLANGIA, Mohit; POKHAREL, Rita

2016-01-01

Objective Various factors have been claimed to predict outcome of afebrile seizures in children. This study was aimed to find out the predictors of poor seizure control in children at a resource limited setting. Materials & Methods This prospective study was done from July 1st, 2009 to January 31st, 2012 at B.P. Koirala Institute of Health Sciences, Nepal. Children (1 month-20 yr of age) with afebrile seizures presenting to pediatric neurology clinic were studied. Significant predictors on bivariate analysis were further analyzed with binary logistic model to find out the true predictors. Positive predictive values (PPVs) and negative predictive values (NPVs) for the true predictors were calculated. Results Out of 256 patients (male: female ratio 3:2) with afebrile seizures followed up for median duration of 27 (IQR 12-50) months, seizure was poorly controlled in 20% patients. Three factors predicted poor seizure control. They were frequent (≥1 per month) seizures at onset (OR 12.76, 95% CI 1.44-112.73, PPV 25%, NPV 98%); remote symptomatic etiology (OR 3.56, 95% CI 1.04-12.17, PPV 36%, NPV 92%); and need of more than one anticonvulsant drug (polytherapy) (OR 12.83, 95% CI 5.50-29.9, PPV 56%, NPV 96%). The strongest predictor was need of polytherapy. When all three factors were present, PPV and NPV for prediction of poor seizure control were 70% and 90% respectively. Conclusion Frequent seizures at onset, remote symptomatic etiology of seizure and need of polytherapy were associated with poor seizure control in children with afebrile seizures. PMID:27375756

Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction.

PubMed

Gao, Xiang-Ming; Yang, Shi-Feng; Pan, San-Bo

2017-01-01

Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.

Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction

PubMed Central

2017-01-01

Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization. PMID:28912803

Tutorial: Neural networks and their potential application in nuclear power plants

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

Uhrig, R.E.

A neural network is a data processing system consisting of a number of simple, highly interconnected processing elements in an architecture inspired by the structure of the cerebral cortex portion of the brain. Hence, neural networks are often capable of doing things which humans or animals do well but which conventional computers often do poorly. Neural networks have emerged in the past few years as an area of unusual opportunity for research, development and application to a variety of real world problems. Indeed, neural networks exhibit characteristics and capabilities not provided by any other technology. Examples include reading Japanese Kanjimore » characters and human handwriting, reading a typewritten manuscript aloud, compensating for alignment errors in robots, interpreting very noise'' signals (e.g. electroencephalograms), modeling complex systems that cannot be modelled mathematically, and predicting whether proposed loans will be good or fail. This paper presents a brief tutorial on neural networks and describes research on the potential applications to nuclear power plants.« less

Heat localization for targeted tumor treatment with nanoscale near-infrared radiation absorbers

PubMed Central

Xie, Bin; Singh, Ravi; Torti, F. M.; Keblinski, Pawel; Torti, Suzy

2012-01-01

Focusing heat delivery while minimizing collateral damage to normal tissues is essential for successful nanoparticle-mediated laser-induced thermal cancer therapy. We present thermal maps obtained via magnetic resonance imaging (MRI) characterizing laser heating of a phantom tissue containing a multiwalled carbon nanotube inclusion. The data demonstrate that heating continuously over tens of seconds leads to poor localization (~ 0.5 cm) of the elevated temperature region. By contrast, for the same energy input, heat localization can be reduced to the millimeter rather than centimeter range by increasing the laser power and shortening the pulse duration. The experimental data can be well understood within a simple diffusive heat conduction model. Analysis of the model indicates that to achieve 1 mm or better resolution, heating pulses of ~ 2s or less need to be used with appropriately higher heating power. Modeling these data using a diffusive heat conduction analysis predicts parameters for optimal targeted delivery of heat for ablative therapy. PMID:22948207

Sea-ice floe-size distribution in the context of spontaneous scaling emergence in stochastic systems.

PubMed

Herman, Agnieszka

2010-06-01

Sea-ice floe-size distribution (FSD) in ice-pack covered seas influences many aspects of ocean-atmosphere interactions. However, data concerning FSD in the polar oceans are still sparse and processes shaping the observed FSD properties are poorly understood. Typically, power-law FSDs are assumed although no feasible explanation has been provided neither for this one nor for other properties of the observed distributions. Consequently, no model exists capable of predicting FSD parameters in any particular situation. Here I show that the observed FSDs can be well represented by a truncated Pareto distribution P(x)=x(-1-α) exp[(1-α)/x] , which is an emergent property of a certain group of multiplicative stochastic systems, described by the generalized Lotka-Volterra (GLV) equation. Building upon this recognition, a possibility of developing a simple agent-based GLV-type sea-ice model is considered. Contrary to simple power-law FSDs, GLV gives consistent estimates of the total floe perimeter, as well as floe-area distribution in agreement with observations.

Sea-ice floe-size distribution in the context of spontaneous scaling emergence in stochastic systems

NASA Astrophysics Data System (ADS)

Herman, Agnieszka

2010-06-01

Sea-ice floe-size distribution (FSD) in ice-pack covered seas influences many aspects of ocean-atmosphere interactions. However, data concerning FSD in the polar oceans are still sparse and processes shaping the observed FSD properties are poorly understood. Typically, power-law FSDs are assumed although no feasible explanation has been provided neither for this one nor for other properties of the observed distributions. Consequently, no model exists capable of predicting FSD parameters in any particular situation. Here I show that the observed FSDs can be well represented by a truncated Pareto distribution P(x)=x-1-αexp[(1-α)/x] , which is an emergent property of a certain group of multiplicative stochastic systems, described by the generalized Lotka-Volterra (GLV) equation. Building upon this recognition, a possibility of developing a simple agent-based GLV-type sea-ice model is considered. Contrary to simple power-law FSDs, GLV gives consistent estimates of the total floe perimeter, as well as floe-area distribution in agreement with observations.

Selenide isotope generator for the Galileo mission. SIG/Galileo contract compliance power prediction technique

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

Hammel, T.E.; Srinivas, V.

1978-11-01

This initial definition of the power degradation prediction technique outlines a model for predicting SIG/Galileo mean EOM power using component test data and data from a module power degradation demonstration test program. (LCL)

Prediction models for intracranial hemorrhage or major bleeding in patients on antiplatelet therapy: a systematic review and external validation study.

PubMed

Hilkens, N A; Algra, A; Greving, J P

2016-01-01

ESSENTIALS: Prediction models may help to identify patients at high risk of bleeding on antiplatelet therapy. We identified existing prediction models for bleeding and validated them in patients with cerebral ischemia. Five prediction models were identified, all of which had some methodological shortcomings. Performance in patients with cerebral ischemia was poor. Background Antiplatelet therapy is widely used in secondary prevention after a transient ischemic attack (TIA) or ischemic stroke. Bleeding is the main adverse effect of antiplatelet therapy and is potentially life threatening. Identification of patients at increased risk of bleeding may help target antiplatelet therapy. This study sought to identify existing prediction models for intracranial hemorrhage or major bleeding in patients on antiplatelet therapy and evaluate their performance in patients with cerebral ischemia. We systematically searched PubMed and Embase for existing prediction models up to December 2014. The methodological quality of the included studies was assessed with the CHARMS checklist. Prediction models were externally validated in the European Stroke Prevention Study 2, comprising 6602 patients with a TIA or ischemic stroke. We assessed discrimination and calibration of included prediction models. Five prediction models were identified, of which two were developed in patients with previous cerebral ischemia. Three studies assessed major bleeding, one studied intracerebral hemorrhage and one gastrointestinal bleeding. None of the studies met all criteria of good quality. External validation showed poor discriminative performance, with c-statistics ranging from 0.53 to 0.64 and poor calibration. A limited number of prediction models is available that predict intracranial hemorrhage or major bleeding in patients on antiplatelet therapy. The methodological quality of the models varied, but was generally low. Predictive performance in patients with cerebral ischemia was poor. In order to reliably predict the risk of bleeding in patients with cerebral ischemia, development of a prediction model according to current methodological standards is needed. © 2015 International Society on Thrombosis and Haemostasis.

Nanoporous metal/oxide hybrid electrodes for electrochemical supercapacitors

NASA Astrophysics Data System (ADS)

Lang, Xingyou; Hirata, Akihiko; Fujita, Takeshi; Chen, Mingwei

2011-04-01

Electrochemical supercapacitors can deliver high levels of electrical power and offer long operating lifetimes, but their energy storage density is too low for many important applications. Pseudocapacitive transition-metal oxides such as MnO2 could be used to make electrodes in such supercapacitors, because they are predicted to have a high capacitance for storing electrical charge while also being inexpensive and not harmful to the environment. However, the poor conductivity of MnO2 (10-5-10-6 S cm-1) limits the charge/discharge rate for high-power applications. Here, we show that hybrid structures made of nanoporous gold and nanocrystalline MnO2 have enhanced conductivity, resulting in a specific capacitance of the constituent MnO2 (~1,145 F g-1) that is close to the theoretical value. The nanoporous gold allows electron transport through the MnO2, and facilitates fast ion diffusion between the MnO2 and the electrolytes while also acting as a double-layer capacitor. The high specific capacitances and charge/discharge rates offered by such hybrid structures make them promising candidates as electrodes in supercapacitors, combining high-energy storage densities with high levels of power delivery.

Nanoporous metal/oxide hybrid electrodes for electrochemical supercapacitors.

PubMed

Lang, Xingyou; Hirata, Akihiko; Fujita, Takeshi; Chen, Mingwei

2011-04-01

Electrochemical supercapacitors can deliver high levels of electrical power and offer long operating lifetimes, but their energy storage density is too low for many important applications. Pseudocapacitive transition-metal oxides such as MnO(2) could be used to make electrodes in such supercapacitors, because they are predicted to have a high capacitance for storing electrical charge while also being inexpensive and not harmful to the environment. However, the poor conductivity of MnO(2) (10(-5)-10(-6) S cm(-1)) limits the charge/discharge rate for high-power applications. Here, we show that hybrid structures made of nanoporous gold and nanocrystalline MnO(2) have enhanced conductivity, resulting in a specific capacitance of the constituent MnO(2) (~1,145 F g(-1)) that is close to the theoretical value. The nanoporous gold allows electron transport through the MnO(2), and facilitates fast ion diffusion between the MnO(2) and the electrolytes while also acting as a double-layer capacitor. The high specific capacitances and charge/discharge rates offered by such hybrid structures make them promising candidates as electrodes in supercapacitors, combining high-energy storage densities with high levels of power delivery.

Power load prediction based on GM (1,1)

NASA Astrophysics Data System (ADS)

Wu, Di

2017-05-01

Currently, Chinese power load prediction is highly focused; the paper deeply studies grey prediction and applies it to Chinese electricity consumption during the recent 14 years; through after-test test, it obtains grey prediction which has good adaptability to medium and long-term power load.

Effect of accuracy of wind power prediction on power system operator

NASA Technical Reports Server (NTRS)

Schlueter, R. A.; Sigari, G.; Costi, T.

1985-01-01

This research project proposed a modified unit commitment that schedules connection and disconnection of generating units in response to load. A modified generation control is also proposed that controls steam units under automatic generation control, fast responding diesels, gas turbines and hydro units under a feedforward control, and wind turbine array output under a closed loop array control. This modified generation control and unit commitment require prediction of trend wind power variation one hour ahead and the prediction of error in this trend wind power prediction one half hour ahead. An improved meter for predicting trend wind speed variation is developed. Methods for accurately simulating the wind array power from a limited number of wind speed prediction records was developed. Finally, two methods for predicting the error in the trend wind power prediction were developed. This research provides a foundation for testing and evaluating the modified unit commitment and generation control that was developed to maintain operating reliability at a greatly reduced overall production cost for utilities with wind generation capacity.

The Reciprocal Influence of Callous-Unemotional Traits, Oppositional Defiant Disorder and Parenting Practices in Preschoolers.

PubMed

Brown, Caitlin A; Granero, Roser; Ezpeleta, Lourdes

2017-04-01

The present study investigates reciprocal associations between positive parenting, parental monitoring, CU traits, and ODD in children assessed at age 3 and again at age 6. Data were collected from a sample of preschoolers (N = 419; 51.58 % female) through diagnostic interviews and questionnaires answered by parents and teachers. Structural equation modeling revealed a bidirectional relationship between poor monitoring and ODD, with poor monitoring at age 3 predicting ODD at age 6 (β = 0.11, p < 0.05), and ODD at age 3 predicting poor monitoring at age 6 (β = 0.10, p < 0.05). While poor monitoring at age 3 predicted CU traits at age 6 (β = 0.11, p < 0.05), CU traits at age 3 predicted positive parenting (β = 0.09, p < 0.05) and ODD (β = 0.13, p < 0.05) at age 6. Results have important implications for early targeted parenting interventions for CU traits and ODD.

Prediction of Poor Ovarian response by Biochemical and Biophysical Markers: A Logistic Regression Model.

PubMed

Jaiswar, S P; Natu, S M; Sujata; Sankhwar, P L; Manjari, Gupta

2015-12-01

To study correlation between ovarian reserve with biophysical markers (antral follicle count and ovarian volume) and biochemical markers (S. FSH, S. Inhibin B, and S. AMH) and use these markers to predict poor ovarian response to ovarian induction. This is a prospective observational study. One hundred infertile women attending the Obst & Gynae Dept, KGMU were recruited. Blood samples were collected on day 2/day 3 for assessment of S. FSH, S. Inhibin B, and S. AMH and TVS were done for antral follicle count and ovarian volume. Clomephene citrate 100 mg 1OD was given from day 2 to 6, and patients were followed up with serial USG measurements. The numbers of dominant follicles (> or = 14 mm) at the time of hCG administration were counted. Patients with <3 follicles in the 1st cycle were subjected to the 2nd cycle of clomephene 100 mg 1OD from day 2 to day 6 with Inj HMG 150 IU given i.m. starting from day 8 and every alternate day until at least one leading follicle attained ≥18 mm. Development of <3 follicles at end of the 2nd cycle was considered as poor response. Univariate analyses showed that s. inhibin B presented the highest (ROCAUC = 0.862) discriminating potential for predicting poor ovarian response, In multivariate logistic regression model, the variables age, FSH, AMH, INHIBIN B, and AFC remained significant, and the resulting model showed a predicted accuracy of 84.4 %. A derived multimarker computation by a logistic regression model for predicting poor ovarian response was obtained through this study. Thus, potential poor responders could be identified easily, and appropriate ovarian stimulation protocol could be devised for such pts.

Can somatosensory and visual evoked potentials predict neurological outcome during targeted temperature management in post cardiac arrest patients?

PubMed

Choi, Seung Pill; Park, Kyu Nam; Wee, Jung Hee; Park, Jeong Ho; Youn, Chun Song; Kim, Han Joon; Oh, Sang Hoon; Oh, Yoon Sang; Kim, Soo Hyun; Oh, Joo Suk

2017-10-01

In cardiac arrest patients treated with targeted temperature management (TTM), it is not certain if somatosensory evoked potentials (SEPs) and visual evoked potentials (VEPs) can predict neurological outcomes during TTM. The aim of this study was to investigate the prognostic value of SEPs and VEPs during TTM and after rewarming. This retrospective cohort study included comatose patients resuscitated from cardiac arrest and treated with TTM between March 2007 and July 2015. SEPs and VEPs were recorded during TTM and after rewarming in these patients. Neurological outcome was assessed at discharge by the Cerebral Performance Category (CPC) Scale. In total, 115 patients were included. A total of 175 SEPs and 150 VEPs were performed. Five SEPs during treated with TTM and nine SEPs after rewarming were excluded from outcome prediction by SEPs due to an indeterminable N20 response because of technical error. Using 80 SEPs and 85 VEPs during treated with TTM, absent SEPs yielded a sensitivity of 58% and a specificity of 100% for poor outcome (CPC 3-5), and absent VEPs predicted poor neurological outcome with a sensitivity of 44% and a specificity of 96%. The AUC of combination of SEPs and VEPs was superior to either test alone (0.788 for absent SEPs and 0.713 for absent VEPs compared with 0.838 for the combination). After rewarming, absent SEPs and absent VEPs predicted poor neurological outcome with a specificity of 100%. When SEPs and VEPs were combined, VEPs slightly increased the prognostic accuracy of SEPs alone. Although one patient with absent VEP during treated with TTM had a good neurological outcome, none of the patients with good neurological outcome had an absent VEP after rewarming. Absent SEPs could predict poor neurological outcome during TTM as well as after rewarming. Absent VEPs may predict poor neurological outcome in both periods and VEPs may provide additional prognostic value in outcome prediction. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Quantitative EEG Metrics Differ Between Outcome Groups and Change Over the First 72 h in Comatose Cardiac Arrest Patients.

PubMed

Wiley, Sara Leingang; Razavi, Babak; Krishnamohan, Prashanth; Mlynash, Michael; Eyngorn, Irina; Meador, Kimford J; Hirsch, Karen G

2018-02-01

Forty to sixty-six percent of patients resuscitated from cardiac arrest remain comatose, and historic outcome predictors are unreliable. Quantitative spectral analysis of continuous electroencephalography (cEEG) may differ between patients with good and poor outcomes. Consecutive patients with post-cardiac arrest hypoxic-ischemic coma undergoing cEEG were enrolled. Spectral analysis was conducted on artifact-free contiguous 5-min cEEG epochs from each hour. Whole band (1-30 Hz), delta (δ, 1-4 Hz), theta (θ, 4-8 Hz), alpha (α, 8-13 Hz), beta (β, 13-30 Hz), α/δ power ratio, percent suppression, and variability were calculated and correlated with outcome. Graphical patterns of quantitative EEG (qEEG) were described and categorized as correlating with outcome. Clinical outcome was dichotomized, with good neurologic outcome being consciousness recovery. Ten subjects with a mean age = 50 yrs (range = 18-65) were analyzed. There were significant differences in total power (3.50 [3.30-4.06] vs. 0.68 [0.52-1.02], p = 0.01), alpha power (1.39 [0.66-1.79] vs 0.27 [0.17-0.48], p < 0.05), delta power (2.78 [2.21-3.01] vs 0.55 [0.38-0.83], p = 0.01), percent suppression (0.66 [0.02-2.42] vs 73.4 [48.0-97.5], p = 0.01), and multiple measures of variability between good and poor outcome patients (all values median [IQR], good vs. poor). qEEG patterns with high or increasing power or large power variability were associated with good outcome (n = 6). Patterns with consistently low or decreasing power or minimal power variability were associated with poor outcome (n = 4). These preliminary results suggest qEEG metrics correlate with outcome. In some patients, qEEG patterns change over the first three days post-arrest.

Pooling of cross-cultural PRO data in multinational clinical trials: how much can poor measurement affect statistical power?

PubMed

Regnault, Antoine; Hamel, Jean-François; Patrick, Donald L

2015-02-01

Cultural differences and/or poor linguistic validation of patient-reported outcome (PRO) instruments may result in differences in the assessment of the targeted concept across languages. In the context of multinational clinical trials, these measurement differences may add noise and potentially measurement bias to treatment effect estimation. Our objective was to explore the potential effect on treatment effect estimation of the "contamination" of a cultural subgroup by a flawed PRO measurement. We ran a simulation exercise in which the distribution of the score in the overall sample was considered a mixture of two normal distributions: a standard normal distribution was assumed in a "main" subgroup and a normal distribution which differed either in mean (bias) or in variance (noise) in a "contaminated" subgroup (the subgroup with potential flaws in the PRO measurement). The observed power was compared to the expected power (i.e., the power that would have been observed if the subgroup had not been contaminated). Even if differences between the expected and observed power were small, some substantial differences were obtained (up to a 0.375 point drop in power). No situation was systematically protected against loss of power. The impact of poor PRO measurement in a cultural subgroup may induce a notable drop in the study power and consequently reduce the chance of showing an actual treatment effect. These results illustrate the importance of the efforts to optimize conceptual and linguistic equivalence of PRO measures when pooling data in international clinical trials.

Accurately Characterizing the Importance of Wave-Particle Interactions in Radiation Belt Dynamics: The Pitfalls of Statistical Wave Representations

NASA Technical Reports Server (NTRS)

Murphy, Kyle R.; Mann, Ian R.; Rae, I. Jonathan; Sibeck, David G.; Watt, Clare E. J.

2016-01-01

Wave-particle interactions play a crucial role in energetic particle dynamics in the Earths radiation belts. However, the relative importance of different wave modes in these dynamics is poorly understood. Typically, this is assessed during geomagnetic storms using statistically averaged empirical wave models as a function of geomagnetic activity in advanced radiation belt simulations. However, statistical averages poorly characterize extreme events such as geomagnetic storms in that storm-time ultralow frequency wave power is typically larger than that derived over a solar cycle and Kp is a poor proxy for storm-time wave power.

Electroencephalographic prodromal markers of dementia across conscious states in Parkinson’s disease

PubMed Central

Latreille, Véronique; Gaudet-Fex, Benjamin; Rodrigues-Brazète, Jessica; Panisset, Michel; Chouinard, Sylvain; Postuma, Ronald B.

2016-01-01

Abstract In Parkinson’s disease, electroencephalographic abnormalities during wakefulness and non-rapid eye movement sleep (spindles) were found to be predictive biomarkers of dementia. Because rapid eye movement sleep is regulated by the cholinergic system, which shows early degeneration in Parkinson’s disease with cognitive impairment, anomalies during this sleep stage might mirror dementia development. In this prospective study, we examined baseline electroencephalographic absolute spectral power across three states of consciousness (non-rapid eye movement sleep, rapid eye movement sleep, and wakefulness) in 68 non-demented patients with Parkinson’s disease and 44 healthy controls. All participants underwent baseline polysomnographic recordings and a comprehensive neuropsychological assessment. Power spectral analyses were performed on standard frequency bands. Dominant occipital frequency during wakefulness and ratios of slow-to-fast frequencies during rapid eye movement sleep and wakefulness were also computed. At follow-up (an average 4.5 years after baseline), 18 patients with Parkinson’s disease had developed dementia and 50 patients remained dementia-free. In rapid eye movement sleep, patients with Parkinson’s disease who later developed dementia showed, at baseline, higher absolute power in delta and theta bands and a higher slowing ratio, especially in temporal, parietal, and occipital regions, compared to patients who remained dementia-free and controls. In non-rapid eye movement sleep, lower baseline sigma power in parietal cortical regions also predicted development of dementia. During wakefulness, patients with Parkinson’s disease who later developed dementia showed lower dominant occipital frequency as well as higher delta and slowing ratio compared to patients who remained dementia-free and controls. At baseline, higher slowing ratios in temporo-occipital regions during rapid eye movement sleep were associated with poor performance on visuospatial tests in patients with Parkinson’s disease. Using receiver operating characteristic curves, we found that best predictors of dementia in Parkinson’s disease were rapid eye movement sleep slowing ratios in posterior regions, wakefulness slowing ratios in temporal areas, and lower dominant occipital frequency. These results suggest that electroencephalographic slowing during sleep is a new promising predictive biomarker for Parkinson’s disease dementia, perhaps as a marker of cholinergic denervation. PMID:26912643

Structure and stability of genetic variance-covariance matrices: A Bayesian sparse factor analysis of transcriptional variation in the three-spined stickleback.

PubMed

Siren, J; Ovaskainen, O; Merilä, J

2017-10-01

The genetic variance-covariance matrix (G) is a quantity of central importance in evolutionary biology due to its influence on the rate and direction of multivariate evolution. However, the predictive power of empirically estimated G-matrices is limited for two reasons. First, phenotypes are high-dimensional, whereas traditional statistical methods are tuned to estimate and analyse low-dimensional matrices. Second, the stability of G to environmental effects and over time remains poorly understood. Using Bayesian sparse factor analysis (BSFG) designed to estimate high-dimensional G-matrices, we analysed levels variation and covariation in 10,527 expressed genes in a large (n = 563) half-sib breeding design of three-spined sticklebacks subject to two temperature treatments. We found significant differences in the structure of G between the treatments: heritabilities and evolvabilities were higher in the warm than in the low-temperature treatment, suggesting more and faster opportunity to evolve in warm (stressful) conditions. Furthermore, comparison of G and its phenotypic equivalent P revealed the latter is a poor substitute of the former. Most strikingly, the results suggest that the expected impact of G on evolvability-as well as the similarity among G-matrices-may depend strongly on the number of traits included into analyses. In our results, the inclusion of only few traits in the analyses leads to underestimation in the differences between the G-matrices and their predicted impacts on evolution. While the results highlight the challenges involved in estimating G, they also illustrate that by enabling the estimation of large G-matrices, the BSFG method can improve predicted evolutionary responses to selection. © 2017 John Wiley & Sons Ltd.

Poor Gait Performance and Prediction of Dementia: Results From a Meta-Analysis.

PubMed

Beauchet, Olivier; Annweiler, Cédric; Callisaya, Michele L; De Cock, Anne-Marie; Helbostad, Jorunn L; Kressig, Reto W; Srikanth, Velandai; Steinmetz, Jean-Paul; Blumen, Helena M; Verghese, Joe; Allali, Gilles

2016-06-01

Poor gait performance predicts risk of developing dementia. No structured critical evaluation has been conducted to study this association yet. The aim of this meta-analysis was to systematically examine the association of poor gait performance with incidence of dementia. An English and French Medline search was conducted in June 2015, with no limit of date, using the medical subject headings terms "Gait" OR "Gait Disorders, Neurologic" OR "Gait Apraxia" OR "Gait Ataxia" AND "Dementia" OR "Frontotemporal Dementia" OR "Dementia, Multi-Infarct" OR "Dementia, Vascular" OR "Alzheimer Disease" OR "Lewy Body Disease" OR "Frontotemporal Dementia With Motor Neuron Disease" (Supplementary Concept). Poor gait performance was defined by standardized tests of walking, and dementia was diagnosed according to international consensus criteria. Four etiologies of dementia were identified: any dementia, Alzheimer disease (AD), vascular dementia (VaD), and non-AD (ie, pooling VaD, mixed dementias, and other dementias). Fixed effects meta-analyses were performed on the estimates in order to generate summary values. Of the 796 identified abstracts, 12 (1.5%) were included in this systematic review and meta-analysis. Poor gait performance predicted dementia [pooled hazard ratio (HR) combined with relative risk and odds ratio = 1.53 with P < .001 for any dementia, pooled HR = 1.79 with P < .001 for VaD, HR = 1.89 with P value < .001 for non-AD]. Findings were weaker for predicting AD (HR = 1.03 with P value = .004). This meta-analysis provides evidence that poor gait performance predicts dementia. This association depends on the type of dementia; poor gait performance is a stronger predictor of non-AD dementias than AD. Copyright © 2016 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Income gains predict cognitive functioning longitudinally throughout later childhood in poor children.

PubMed

Raffington, Laurel; Prindle, John J; Shing, Yee Lee

2018-04-26

Alleviating disadvantage in low-income environments predicts higher cognitive abilities during early childhood. It is less established whether family income continues to predict cognitive growth in later childhood or whether there may even be bidirectional dynamics. Notably, living in poverty may moderate income-cognition dynamics. In this study, we investigated longitudinal dynamics over 7 waves of data collection from 1,168 children between the ages of 4.6 and 12 years, 226 (19%) of whom lived in poverty in at least 1 wave, as part of the NICHD Study of Early Child Care and Youth Development. Two sets of dual change-score models evaluated, first, whether a score predicted change from that wave to the next and, second, whether change from 1 wave to the next predicted the following score. As previous comparisons have documented, poor children had substantially lower average starting points and cognitive growth slopes through later childhood. The first set of models showed that income scores did not predict cognitive change. In reverse, child cognitive scores positively predicted income change. We speculated that parents may reduce their work investment, thus reducing income gains, when their children fall behind. Second, income changes continued to positively predict higher cognitive scores at the following wave for poor children only, which suggests that income gains and losses continue to be a leading indicator in time of poor children's cognitive performance in later childhood. This study underlined the need to look at changes in income, allow for poverty moderation, and explore bidirectional income-cognition dynamics in middle childhood. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

A global approach to analysis and interpretation of metabolic data for plant natural product discovery.

PubMed

Hur, Manhoi; Campbell, Alexis Ann; Almeida-de-Macedo, Marcia; Li, Ling; Ransom, Nick; Jose, Adarsh; Crispin, Matt; Nikolau, Basil J; Wurtele, Eve Syrkin

2013-04-01

Discovering molecular components and their functionality is key to the development of hypotheses concerning the organization and regulation of metabolic networks. The iterative experimental testing of such hypotheses is the trajectory that can ultimately enable accurate computational modelling and prediction of metabolic outcomes. This information can be particularly important for understanding the biology of natural products, whose metabolism itself is often only poorly defined. Here, we describe factors that must be in place to optimize the use of metabolomics in predictive biology. A key to achieving this vision is a collection of accurate time-resolved and spatially defined metabolite abundance data and associated metadata. One formidable challenge associated with metabolite profiling is the complexity and analytical limits associated with comprehensively determining the metabolome of an organism. Further, for metabolomics data to be efficiently used by the research community, it must be curated in publicly available metabolomics databases. Such databases require clear, consistent formats, easy access to data and metadata, data download, and accessible computational tools to integrate genome system-scale datasets. Although transcriptomics and proteomics integrate the linear predictive power of the genome, the metabolome represents the nonlinear, final biochemical products of the genome, which results from the intricate system(s) that regulate genome expression. For example, the relationship of metabolomics data to the metabolic network is confounded by redundant connections between metabolites and gene-products. However, connections among metabolites are predictable through the rules of chemistry. Therefore, enhancing the ability to integrate the metabolome with anchor-points in the transcriptome and proteome will enhance the predictive power of genomics data. We detail a public database repository for metabolomics, tools and approaches for statistical analysis of metabolomics data, and methods for integrating these datasets with transcriptomic data to create hypotheses concerning specialized metabolisms that generate the diversity in natural product chemistry. We discuss the importance of close collaborations among biologists, chemists, computer scientists and statisticians throughout the development of such integrated metabolism-centric databases and software.

A global approach to analysis and interpretation of metabolic data for plant natural product discovery†

PubMed Central

Hur, Manhoi; Campbell, Alexis Ann; Almeida-de-Macedo, Marcia; Li, Ling; Ransom, Nick; Jose, Adarsh; Crispin, Matt; Nikolau, Basil J.

2013-01-01

Discovering molecular components and their functionality is key to the development of hypotheses concerning the organization and regulation of metabolic networks. The iterative experimental testing of such hypotheses is the trajectory that can ultimately enable accurate computational modelling and prediction of metabolic outcomes. This information can be particularly important for understanding the biology of natural products, whose metabolism itself is often only poorly defined. Here, we describe factors that must be in place to optimize the use of metabolomics in predictive biology. A key to achieving this vision is a collection of accurate time-resolved and spatially defined metabolite abundance data and associated metadata. One formidable challenge associated with metabolite profiling is the complexity and analytical limits associated with comprehensively determining the metabolome of an organism. Further, for metabolomics data to be efficiently used by the research community, it must be curated in publically available metabolomics databases. Such databases require clear, consistent formats, easy access to data and metadata, data download, and accessible computational tools to integrate genome system-scale datasets. Although transcriptomics and proteomics integrate the linear predictive power of the genome, the metabolome represents the nonlinear, final biochemical products of the genome, which results from the intricate system(s) that regulate genome expression. For example, the relationship of metabolomics data to the metabolic network is confounded by redundant connections between metabolites and gene-products. However, connections among metabolites are predictable through the rules of chemistry. Therefore, enhancing the ability to integrate the metabolome with anchor-points in the transcriptome and proteome will enhance the predictive power of genomics data. We detail a public database repository for metabolomics, tools and approaches for statistical analysis of metabolomics data, and methods for integrating these dataset with transcriptomic data to create hypotheses concerning specialized metabolism that generates the diversity in natural product chemistry. We discuss the importance of close collaborations among biologists, chemists, computer scientists and statisticians throughout the development of such integrated metabolism-centric databases and software. PMID:23447050

Does chemical composition of antler bone reflect the physiological effort made to grow it?

PubMed

Landete-Castillejos, T; Estevez, J A; Martínez, A; Ceacero, F; Garcia, A; Gallego, L

2007-04-01

In a previous study, antler bone chemical composition was found to differ between base and tip. If such variation is in part due to the physiological effort made to grow the antler, composition trends should differ between antlers from deer population differing in mineral or food availability, or body reserves. To assess this, we examined cortical thickness and bone composition along the antler shaft, and compared trends between antlers from two populations: captive, well-fed, health-managed deer (n=15), and free-ranging deer with lower food quality and no health treatment (n=10). Significant and clear divergent trends supporting greater physiological exhaustion in free-ranging deer and high or moderate predictive models were found for cortical thickness (R(2)=61.8%), content of Na (R(2)=68.6%), Mg (R(2)=56.3%), K (R(2)=40.0%), and Zn (34.6%); lower predictive power was found for protein (R(2)=25.6%) and ash content (R(2)=19.5%); and poor predictive power was found for Ca (R(2)=4.3%), Fe (R(2)=11.1%), and Si (R(2)=4.7%). A second part of the study assessed similar antler structures grown at the beginning (brow tine) and end (top tine) of antler growth within captive deer. Greater cortical thickness and ash content was found for brow tine, as well as a smaller protein, K and Mg content. In contrast, no difference was found for Ca, Na, Zn, Fe or Si. The results suggest that thickness and mineral composition reflect the physiological effort made to build antler bone.

Stochastic Short-term High-resolution Prediction of Solar Irradiance and Photovoltaic Power Output

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

Melin, Alexander M.; Olama, Mohammed M.; Dong, Jin

The increased penetration of solar photovoltaic (PV) energy sources into electric grids has increased the need for accurate modeling and prediction of solar irradiance and power production. Existing modeling and prediction techniques focus on long-term low-resolution prediction over minutes to years. This paper examines the stochastic modeling and short-term high-resolution prediction of solar irradiance and PV power output. We propose a stochastic state-space model to characterize the behaviors of solar irradiance and PV power output. This prediction model is suitable for the development of optimal power controllers for PV sources. A filter-based expectation-maximization and Kalman filtering mechanism is employed tomore » estimate the parameters and states in the state-space model. The mechanism results in a finite dimensional filter which only uses the first and second order statistics. The structure of the scheme contributes to a direct prediction of the solar irradiance and PV power output without any linearization process or simplifying assumptions of the signal’s model. This enables the system to accurately predict small as well as large fluctuations of the solar signals. The mechanism is recursive allowing the solar irradiance and PV power to be predicted online from measurements. The mechanism is tested using solar irradiance and PV power measurement data collected locally in our lab.« less

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

PubMed

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

2018-04-01

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

Top-quark loop corrections in Z+jet and Z + 2 jet production

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

Campbell, John M.; Keith Ellis, R.

2017-01-01

The sophistication of current predictions formore » $Z+$jet production at hadron colliders necessitates a re-evaluation of any approximations inherent in the theoretical calculations. In this paper we address one such issue, the inclusion of mass effects in top-quark loops. We ameliorate an existing calculation of $Z+1$~jet and $Z+2$~jet production by presenting exact analytic formulae for amplitudes containing top-quark loops that enter at next-to-leading order in QCD. Although approximations based on an expansion in powers of $$1/m_t^2$$ can lead to poor high-energy behavior, an exact treatment of top-quark loops demonstrates that their effect is small and has limited phenomenological interest.« less

Rapid nitrous oxide cycling in the suboxic ocean

NASA Astrophysics Data System (ADS)

Babbin, Andrew R.; Bianchi, Daniele; Jayakumar, Amal; Ward, Bess B.

2015-06-01

Nitrous oxide (N2O) is a powerful greenhouse gas and a major cause of stratospheric ozone depletion, yet its sources and sinks remain poorly quantified in the oceans. We used isotope tracers to directly measure N2O reduction rates in the eastern tropical North Pacific. Because of incomplete denitrification, N2O cycling rates are an order of magnitude higher than predicted by current models in suboxic regions, and the spatial distribution suggests strong dependence on both organic carbon and dissolved oxygen concentrations. Furthermore, N2O turnover is 20 times higher than the net atmospheric efflux. The rapid rate of this cycling coupled to an expected expansion of suboxic ocean waters implies future increases in N2O emissions.

Pressure Distributions for the GA(W)-2 Airfoil with 20% Aileron, 25% Slotted Flap and 30% Fowler Flap

NASA Technical Reports Server (NTRS)

Wentz, W. H., Jr.; Fiscko, K. A.

1978-01-01

Surface pressure distributions were measured for the 13% thick GA(W)-2 airfoil section fitted with 20% aileron, 25% slotted flap and 30% Fowler flap. All tests were conducted at a Reynolds number of 2.2 x 10 to the 6th power and a Mach number of 0.13. Pressure distribution and force and moment coefficient measurements are compared with theoretical results for a number of cases. Agreement between theory and experiment is generally good for low angles of attack and small flap deflections. For high angles and large flap deflections where regions of separation are present, the theory is inadequate. Theoretical drag predictions are poor for all flap-extended cases.

SU-D-204-03: Comparison of Patient Positioning Methods Through Modeling of Acute Rectal Toxicity in Intensity Modulated Radiation Therapy for Prostate Cancer. Does Quality of Data Matter More Than the Quantity?

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

Liu, X; Fatyga, M; Vora, S

Purpose: To determine if differences in patient positioning methods have an impact on the incidence and modeling of grade >=2 acute rectal toxicity in prostate cancer patients who were treated with Intensity Modulated Radiation Therapy (IMRT). Methods: We compared two databases of patients treated with radiation therapy for prostate cancer: a database of 79 patients who were treated with 7 field IMRT and daily image guided positioning based on implanted gold markers (IGRTdb), and a database of 302 patients who were treated with 5 field IMRT and daily positioning using a trans-abdominal ultrasound system (USdb). Complete planning dosimetry was availablemore » for IGRTdb patients while limited planning dosimetry, recorded at the time of planning, was available for USdb patients. We fit Lyman-Kutcher-Burman (LKB) model to IGRTdb only, and Univariate Logistic Regression (ULR) NTCP model to both databases. We perform Receiver Operating Characteristics analysis to determine the predictive power of NTCP models. Results: The incidence of grade >= 2 acute rectal toxicity in IGRTdb was 20%, while the incidence in USdb was 54%. Fits of both LKB and ULR models yielded predictive NTCP models for IGRTdb patients with Area Under the Curve (AUC) in the 0.63 – 0.67 range. Extrapolation of the ULR model from IGRTdb to planning dosimetry in USdb predicts that the incidence of acute rectal toxicity in USdb should not exceed 40%. Fits of the ULR model to the USdb do not yield predictive NTCP models and their AUC is consistent with AUC = 0.5. Conclusion: Accuracy of a patient positioning system affects clinically observed toxicity rates and the quality of NTCP models that can be derived from toxicity data. Poor correlation between planned and clinically delivered dosimetry may lead to erroneous or poorly performing NTCP models, even if the number of patients in a database is large.« less

Is decision-making ability related to food choice and facets of eating behaviour in adolescents?

PubMed

Macchi, Rosemarie; MacKew, Laura; Davis, Caroline

2017-09-01

To test the prediction that poor decision-making would predict poor eating-related behaviours, which in turn would relate to elevated body mass index (BMI) percentile. Associations among decision-making ability, eating behaviours, and BMI percentile were examined in a sample of 311 healthy male and female adolescents, aged 14-18 years. Structural equation modelling was used to test the proposed relationships. The predicted model was a good fit to the data and all paths between latent and indicator variables were significant. Impulsive responding significantly predicted poor food choice and overeating. No significant relationships emerged between eating-related variables and BMI percentile. Findings from this study extend the existing research in adults and offer a more comprehensive understanding of factors that may contribute to eating behaviours and weight status in teenagers. Copyright © 2017 Elsevier Ltd. All rights reserved.

Elevated platelet count as predictor of recurrence in rectal cancer patients undergoing preoperative chemoradiotherapy followed by surgery.

PubMed

Toiyama, Yuji; Inoue, Yasuhiro; Kawamura, Mikio; Kawamoto, Aya; Okugawa, Yoshinaga; Hiro, Jyunichiro; Saigusa, Susumu; Tanaka, Koji; Mohri, Yasuhiko; Kusunoki, Masato

2015-02-01

The impact of systemic inflammatory response (SIR) on prognostic and predictive outcome in rectal cancer after neoadjuvant chemoradiotherapy (CRT) has not been fully investigated. This retrospective study enrolled 89 patients with locally advanced rectal cancer who underwent neoadjuvant CRT and for whom platelet (PLT) counts and SIR status [neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR)] were available. Both clinical values of PLT and SIR status in rectal cancer patients were investigated. Elevated PLT, NLR, PLR, and pathologic TNM stage III [ypN(+)] were associated with significantly poor overall survival (OS). Elevated PLT, NLR, and ypN(+) were shown to independently predict OS. Elevated PLT and ypN(+) significantly predicted poor disease-free survival (DFS). Elevated PLT was identified as the only independent predictor of DFS. PLT counts are a promising pre-CRT biomarker for predicting recurrence and poor prognosis in rectal cancer.

Poverty and behavior problems trajectories from 1.5 to 8 years of age: Is the gap widening between poor and non-poor children?

PubMed

Mazza, Julia Rachel S E; Boivin, Michel; Tremblay, Richard E; Michel, Gregory; Salla, Julie; Lambert, Jean; Zunzunegui, Maria Victoria; Côté, Sylvana M

2016-08-01

Poverty has been associated with high levels of behavior problems across childhood, yet patterns of associations over time remain understudied. This study aims: (a) to examine whether poverty predicts changes in behavior problems between 1.5 and 8 years of age; (b) to estimate potential selection bias for the observed associations. We used the 1998-2006 waves of the Quebec Longitudinal Study of Child Development (N = 2120). Main outcomes were maternal ratings of hyperactivity, opposition and physical aggression from 1.5 to 8 years of age. Linear mixed-effects models were used to assess the longitudinal association between poverty and behavior problems. Models were re-estimated adjusting for wave nonresponse and using multiple imputation to account for attrition. Poverty predicted higher levels of behavior problems between 1.5 and 8 years of age. Poverty predicted hyperactivity and opposition in a time dependent manner. Hyperactivity [Bpoverty*age = 0.052; CI 95 % (0.002; 0.101)] and opposition [Bpoverty*age = 0.049; CI 95 % (0.018; 0.079)] increased at a faster rate up to age 5 years, and then decreased at a slower rate for poor than non-poor children. Physical aggression decreased at a steady rate over time for all children [Bpoverty*age = -0.030; p = 0.064). Estimates remained similar when accounting for attrition. Poverty predicted higher levels of behavior problems between 1.5 and 8 years of age. The difference between poor and non-poor children was stable over time for physical aggression, but increased with age for hyperactivity and opposition. Attrition among poor children did not compromise the validity of results.

Development and testing of watershed-scale models for poorly drained soils

Treesearch

Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

2005-01-01

Watershed-scale hydrology and water quality models were used to evaluate the crrmulative impacts of land use and management practices on dowrzstream hydrology and nitrogen loading of poorly drained watersheds. Field-scale hydrology and nutrient dyyrutmics are predicted by DRAINMOD in both models. In the first model (DRAINMOD-DUFLOW), field-scale predictions are coupled...

Phonology and Handedness in Primary School: Predictions of the Right Shift Theory

ERIC Educational Resources Information Center

Smythe, Pamela; Annett, Marian

2006-01-01

Background: The right shift (RS) theory of handedness suggests that poor phonology may occur in the general population as a risk associated with absence of an agent of left cerebral speech, the hypothesised RS + gene. The theory predicts that poor phonology is associated with reduced bias to right-handedness. Methods: A representative cohort of…

Little pigeons can carry great messages: potential distribution and ecology of Uranotaenia (Pseudoficalbia) unguiculata Edwards, 1913 (Diptera: Culicidae), a lesser-known mosquito species from the Western Palaearctic.

PubMed

Filatov, Serhii

2017-10-10

Uranotaenia unguiculata is a Palaearctic mosquito species with poorly known distribution and ecology. This study is aimed at filling the gap in our understanding of the species potential distribution and its environmental requirements through a species distribution modelling (SDM) exercise. Furthermore, aspects of the mosquito ecology that may be relevant to the epidemiology of certain zoonotic vector-borne diseases in Europe are discussed. A maximum entropy (Maxent) modelling approach has been applied to predict the potential distribution of Ur. unguiculata in the Western Palaearctic. Along with the high accuracy and predictive power, the model reflects well the known species distribution and predicts as highly suitable some areas where the occurrence of the species is hitherto unknown. To our knowledge, the potential distribution of a mosquito species from the genus Uranotaenia is modelled for the first time. Provided that Ur. unguiculata is a widely-distributed species, and some pathogens of zoonotic concern have been detected in this mosquito on several occasions, the question regarding its host associations and possible epidemiological role warrants further investigation.

Employing conservation of co-expression to improve functional inference

PubMed Central

Daub, Carsten O; Sonnhammer, Erik LL

2008-01-01

Background Observing co-expression between genes suggests that they are functionally coupled. Co-expression of orthologous gene pairs across species may improve function prediction beyond the level achieved in a single species. Results We used orthology between genes of the three different species S. cerevisiae, D. melanogaster, and C. elegans to combine co-expression across two species at a time. This led to increased function prediction accuracy when we incorporated expression data from either of the other two species and even further increased when conservation across both of the two other species was considered at the same time. Employing the conservation across species to incorporate abundant model organism data for the prediction of protein interactions in poorly characterized species constitutes a very powerful annotation method. Conclusion To be able to employ the most suitable co-expression distance measure for our analysis, we evaluated the ability of four popular gene co-expression distance measures to detect biologically relevant interactions between pairs of genes. For the expression datasets employed in our co-expression conservation analysis above, we used the GO and the KEGG PATHWAY databases as gold standards. While the differences between distance measures were small, Spearman correlation showed to give most robust results. PMID:18808668

Pervasive Defaunation of Forest Remnants in a Tropical Biodiversity Hotspot

PubMed Central

Canale, Gustavo R.; Peres, Carlos A.; Guidorizzi, Carlos E.; Gatto, Cassiano A. Ferreira; Kierulff, Maria Cecília M.

2012-01-01

Tropical deforestation and forest fragmentation are among the most important biodiversity conservation issues worldwide, yet local extinctions of millions of animal and plant populations stranded in unprotected forest remnants remain poorly explained. Here, we report unprecedented rates of local extinctions of medium to large-bodied mammals in one of the world's most important tropical biodiversity hotspots. We scrutinized 8,846 person-years of local knowledge to derive patch occupancy data for 18 mammal species within 196 forest patches across a 252,669-km2 study region of the Brazilian Atlantic Forest. We uncovered a staggering rate of local extinctions in the mammal fauna, with only 767 from a possible 3,528 populations still persisting. On average, forest patches retained 3.9 out of 18 potential species occupancies, and geographic ranges had contracted to 0–14.4% of their former distributions, including five large-bodied species that had been extirpated at a regional scale. Forest fragments were highly accessible to hunters and exposed to edge effects and fires, thereby severely diminishing the predictive power of species-area relationships, with the power model explaining only ∼9% of the variation in species richness per patch. Hence, conventional species-area curves provided over-optimistic estimates of species persistence in that most forest fragments had lost species at a much faster rate than predicted by habitat loss alone. PMID:22905103

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

PubMed Central

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

2017-01-01

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

A model combining age, equivalent uniform dose and IL-8 may predict radiation esophagitis in patients with non-small cell lung cancer.

PubMed

Wang, Shulian; Campbell, Jeff; Stenmark, Matthew H; Stanton, Paul; Zhao, Jing; Matuszak, Martha M; Ten Haken, Randall K; Kong, Feng-Ming

2018-03-01

To study whether cytokine markers may improve predictive accuracy of radiation esophagitis (RE) in non-small cell lung cancer (NSCLC) patients. A total of 129 patients with stage I-III NSCLC treated with radiotherapy (RT) from prospective studies were included. Thirty inflammatory cytokines were measured in platelet-poor plasma samples. Logistic regression was performed to evaluate the risk factors of RE. Stepwise Akaike information criterion (AIC) and likelihood ratio test were used to assess model predictions. Forty-nine of 129 patients (38.0%) developed grade ≥2 RE. Univariate analysis showed that age, stage, concurrent chemotherapy, and eight dosimetric parameters were significantly associated with grade ≥2 RE (p < 0.05). IL-4, IL-5, IL-8, IL-13, IL-15, IL-1α, TGFα and eotaxin were also associated with grade ≥2 RE (p < 0.1). Age, esophagus generalized equivalent uniform dose (EUD), and baseline IL-8 were independently associated grade ≥2 RE. The combination of these three factors had significantly higher predictive power than any single factor alone. Addition of IL-8 to toxicity model significantly improves RE predictive accuracy (p = 0.019). Combining baseline level of IL-8, age and esophagus EUD may predict RE more accurately. Refinement of this model with larger sample sizes and validation from multicenter database are warranted. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Wind tunnel wall effects in a linear oscillating cascade

NASA Technical Reports Server (NTRS)

Buffum, Daniel H.; Fleeter, Sanford

1991-01-01

Experiments in a linear oscillating cascade reveal that the wind tunnel walls enclosing the airfoils have, in some cases, a detrimental effect on the oscillating cascade aerodynamics. In a subsonic flow field, biconvex airfoils are driven simultaneously in harmonic, torsion-mode oscillations for a range of interblade phase angle values. It is found that the cascade dynamic periodicity - the airfoil to airfoil variation in unsteady surface pressure - is good for some values of interblade phase angle but poor for others. Correlation of the unsteady pressure data with oscillating flat plate cascade predictions is generally good for conditions where the periodicity is good and poor where the periodicity is poor. Calculations based upon linearized unsteady aerodynamic theory indicate that pressure waves reflected from the wind tunnel walls are responsible for the cases where there is poor periodicity and poor correlation with the predictions.

Modeling wind energy potential in a data-poor region: A geographic information systems model for Iraq

NASA Astrophysics Data System (ADS)

Khayyat, Abdulkareem Hawta Abdullah Kak Ahmed

Scope and Method of Study: Most developing countries, including Iraq, have very poor wind data. Existing wind speed measurements of poor quality may therefore be a poor guide to where to look for the best wind resources. The main focus of this study is to examine how effectively a GIS spatial model estimates wind power potential in regions where high-quality wind data are very scarce, such as Iraq. The research used a mixture of monthly and hourly wind data from 39 meteorological stations. The study applied spatial analysis statistics and GIS techniques in modeling wind power potential. The model weighted important human, environmental and geographic factors that impact wind turbine siting, such as roughness length, land use⪉nd cover type, airport locations, road access, transmission lines, slope and aspect. Findings and Conclusions: The GIS model provided estimations for wind speed and wind power density and identified suitable areas for wind power projects. Using a high resolution (30*30m) digital elevation model DEM improved the GIS wind suitability model. The model identified areas suitable for wind farm development on different scales. The model showed that there are many locations available for large-scale wind turbines in the southern part of Iraq. Additionally, there are many places in central and northern parts (Kurdistan Region) for smaller scale wind turbine placement.

High Tumor Volume to Fetal Weight Ratio Is Associated with Worse Fetal Outcomes and Increased Maternal Risk in Fetuses with Sacrococcygeal Teratoma.

PubMed

Gebb, Juliana S; Khalek, Nahla; Qamar, Huma; Johnson, Mark P; Oliver, Edward R; Coleman, Beverly G; Peranteau, William H; Hedrick, Holly L; Flake, Alan W; Adzick, N Scott; Moldenhauer, Julie S

2018-03-01

Tumor volume to fetal weight ratio (TFR) > 0.12 before 24 weeks has been associated with poor outcome in fetuses with sacrococcygeal teratoma (SCT). We evaluated TFR in predicting poor fetal outcome and increased maternal operative risk in our cohort of SCT pregnancies. This is a retrospective, single-center review of fetuses seen with SCT from 1997 to 2015. Patients who chose termination of pregnancy (TOP), delivered elsewhere, or had initial evaluation at > 24 weeks were excluded. Receiver operating characteristic (ROC) analysis determined the optimal TFR to predict poor fetal outcome and increased maternal operative risk. Poor fetal outcome included fetal demise, neonatal demise, or fetal deterioration warranting open fetal surgery or delivery < 32 weeks. Increased maternal operative risk included cases necessitating open fetal surgery, classical cesarean delivery, or ex utero intrapartum treatment (EXIT). Of 139 pregnancies with SCT, 27 chose TOP, 14 delivered elsewhere, and 40 had initial evaluation at > 24 weeks. Thus, 58 fetuses were reviewed. ROC analysis revealed that at ≤24 weeks, TFR > 0.095 was predictive of poor fetal outcome and TFR > 0.12 was predictive of increased maternal operative risk. This study supports the use of TFR at ≤24 weeks for risk stratification of pregnancies with SCT. © 2018 S. Karger AG, Basel.

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

Scaling and characterisation of a 2-DoF velocity amplified electromagnetic vibration energy harvester

NASA Astrophysics Data System (ADS)

O’Donoghue, D.; Frizzell, R.; Punch, J.

2018-07-01

Vibration energy harvesters (VEHs) offer an alternative to batteries for the autonomous operation of low-power electronics. Understanding the influence of scaling on VEHs is of great importance in the design of reduced scale harvesters. The nonlinear harvesters investigated here employ velocity amplification, a technique used to increase velocity through impacts, to improve the power output of multiple-degree-of-freedom VEHs, compared to linear resonators. Such harvesters, employing electromagnetic induction, are referred to as velocity amplified electromagnetic generators (VAEGs), with gains in power achieved by increasing the relative velocity between the magnet and coil in the transducer. The influence of scaling on a nonlinear 2-DoF VAEG is presented. Due to the increased complexity of VAEGs, compared to linear systems, linear scaling theory cannot be directly applied to VAEGs. Therefore, a detailed nonlinear scaling method is utilised. Experimental and numerical methods are employed. This nonlinear scaling method can be used for analysing the scaling behaviour of all nonlinear electromagnetic VEHs. It is demonstrated that the electromagnetic coupling coefficient degrades more rapidly with scale for systems with larger displacement amplitudes, meaning that systems operating at low frequencies will scale poorly compared to those operating at higher frequencies. The load power of the 2-DoF VAEG is predicted to scale as {P}L\\propto {s}5.51 (s = volume1/3), suggesting that achieving high power densities in a VAEG with low device volume is extremely challenging.

Circulating basal anti-Müllerian hormone levels as predictor of ovarian response in women undergoing ovarian stimulation for in vitro fertilization.

PubMed

Nardo, Luciano G; Gelbaya, Tarek A; Wilkinson, Hannah; Roberts, Stephen A; Yates, Allen; Pemberton, Phil; Laing, Ian

2009-11-01

To evaluate the clinical value of basal anti-Müllerian hormone (AMH) measurements compared with other available determinants, apart from chronologic age, in the prediction of ovarian response to gonadotrophin stimulation. Prospective cohort study. Tertiary referral center for reproductive medicine and an IVF unit. Women undergoing their first cycle of controlled ovarian hyperstimulation (COH) for in vitro fertilization (IVF). Basal levels of FSH and AMH as well as antral follicle count (AFC) were measured in 165 subjects. All patients were followed prospectively and their cycle outcomes recorded. Predictive value of FSH, AMH, and AFC for extremes of ovarian response to stimulation. Out of the 165 women, 134 were defined as normal responders, 15 as poor responders, and 16 as high responders. Subjects in the poor response group were significantly older then those in the other two groups. Anti-Müllerian hormone levels and AFC were markedly raised in the high responders and decreased in the poor responders. Compared with FSH and AFC, AMH performed better in the prediction of excessive response to ovarian stimulation-AMH area under receiver operating characteristic curve (ROC(AUC)) 0.81, FSH ROC(AUC) 0.66, AFC ROC(AUC) 0.69. For poor response, AMH (ROC(AUC) 0.88) was a significantly better predictor than FSH (ROC(AUC) 0.63) but not AFC (ROC(AUC) 0.81). AMH prediction of ovarian response was independent of age and PCOS. Anti-Müllerian hormone cutoffs of >3.75 ng/mL and <1.0 ng/mL would have modest sensitivity and specificity in predicting the extremes of response. Circulating AMH has the ability to predict excessive and poor response to stimulation with exogenous gonadotrophins. Overall, this biomarker is superior to basal FSH and AFC, and has the potential to be incorporated in to work-up protocols to predict patient's ovarian response to treatment and to individualize strategies aiming at reducing the cancellation rate and the iatrogenic complications of COH.

Analysis and experimental evaluation of shunt active power filter for power quality improvement based on predictive direct power control.

PubMed

Aissa, Oualid; Moulahoum, Samir; Colak, Ilhami; Babes, Badreddine; Kabache, Nadir

2017-10-12

This paper discusses the use of the concept of classical and predictive direct power control for shunt active power filter function. These strategies are used to improve the active power filter performance by compensation of the reactive power and the elimination of the harmonic currents drawn by non-linear loads. A theoretical analysis followed by a simulation using MATLAB/Simulink software for the studied techniques has been established. Moreover, two test benches have been carried out using the dSPACE card 1104 for the classic and predictive DPC control to evaluate the studied methods in real time. Obtained results are presented and compared in this paper to confirm the superiority of the predictive technique. To overcome the pollution problems caused by the consumption of fossil fuels, renewable energies are the alternatives recommended to ensure green energy. In the same context, the tested predictive filter can easily be supplied by a renewable energy source that will give its impact to enhance the power quality.

Value of neutrophil-to-lymphocyte ratio for predicting lung cancer prognosis: A meta-analysis of 7,219 patients.

PubMed

Yu, Yu; Qian, Lei; Cui, Jiuwei

2017-09-01

Current evidence suggests that the neutrophil-to-lymphocyte ratio (NLR) may be a biomarker for poor prognosis in lung cancer, although this association remains controversial. Therefore, a meta-analysis was performed to evaluate the association between NLR and lung cancer outcome. A systematic literature search was performed through the PubMed, Embase and Cochrane Library databases (until July 30, 2016), to identify studies evaluating the association between NLR and overall survival (OS) and/or progression-free survival (PFS) among patients with lung cancer. Based on the results of this search, data from 18 studies involving 7,219 patients with lung cancer were evaluated. The pooled hazard ratio (HR) suggested that elevated pretreatment NLR predicted poor OS [HR=1.46, 95% confidence interval (CI): 1.30-1.64] and poor PFS (HR=1.42, 95% CI: 1.15-1.75) among patients with lung cancer. Subgroup analysis revealed that the prognostic value of NLR for predicting poor OS increased among patients who underwent surgery (HR=1.50, 95% CI: 1.21-1.84) or patients with early-stage disease (HR=1.64, 95% CI: 1.37-1.97). An NLR cut-off value of ≥4 significantly predicted poor OS (HR=1.56, 95% CI: 1.31-1.85) and PFS (HR=1.54, 95% CI: 1.13-1.82), particularly in the cases of small-cell lung cancer. Thus, the results of the present meta-analysis suggested that an elevated pretreatment NLR (e.g., ≥4) may be considered as a biomarker for poor prognosis in patients with lung cancer.

The aerodynamic cost of flight in the short-tailed fruit bat (Carollia perspicillata): comparing theory with measurement

PubMed Central

von Busse, Rhea; Waldman, Rye M.; Swartz, Sharon M.; Voigt, Christian C.; Breuer, Kenneth S.

2014-01-01

Aerodynamic theory has long been used to predict the power required for animal flight, but widely used models contain many simplifications. It has been difficult to ascertain how closely biological reality matches model predictions, largely because of the technical challenges of accurately measuring the power expended when an animal flies. We designed a study to measure flight speed-dependent aerodynamic power directly from the kinetic energy contained in the wake of bats flying in a wind tunnel. We compared these measurements with two theoretical predictions that have been used for several decades in diverse fields of vertebrate biology and to metabolic measurements from a previous study using the same individuals. A high-accuracy displaced laser sheet stereo particle image velocimetry experimental design measured the wake velocities in the Trefftz plane behind four bats flying over a range of speeds (3–7 m s−1). We computed the aerodynamic power contained in the wake using a novel interpolation method and compared these results with the power predicted by Pennycuick's and Rayner's models. The measured aerodynamic power falls between the two theoretical predictions, demonstrating that the models effectively predict the appropriate range of flight power, but the models do not accurately predict minimum power or maximum range speeds. Mechanical efficiency—the ratio of aerodynamic power output to metabolic power input—varied from 5.9% to 9.8% for the same individuals, changing with flight speed. PMID:24718450

Blend sign predicts poor outcome in patients with intracerebral hemorrhage.

PubMed

Li, Qi; Yang, Wen-Song; Wang, Xing-Chen; Cao, Du; Zhu, Dan; Lv, Fa-Jin; Liu, Yang; Yuan, Liang; Zhang, Gang; Xiong, Xin; Li, Rui; Hu, Yun-Xin; Qin, Xin-Yue; Xie, Peng

2017-01-01

Blend sign has been recently described as a novel imaging marker that predicts hematoma expansion. The purpose of our study was to investigate the prognostic value of CT blend sign in patients with ICH. Patients with intracerebral hemorrhage who underwent baseline CT scan within 6 hours were included. The presence of blend sign on admission nonenhanced CT was independently assessed by two readers. The functional outcome was assessed by using the modified Rankin Scale (mRS) at 90 days. Blend sign was identified in 40 of 238 (16.8%) patients on admission CT scan. The proportion of patients with a poor functional outcome was significantly higher in patients with blend sign than those without blend sign (75.0% versus 47.5%, P = 0.001). The multivariate logistic regression analysis demonstrated that age, intraventricular hemorrhage, admission GCS score, baseline hematoma volume and presence of blend sign on baseline CT independently predict poor functional outcome at 90 days. The CT blend sign independently predicts poor outcome in patients with ICH (odds ratio 3.61, 95% confidence interval [1.47-8.89];p = 0.005). Early identification of blend sign is useful in prognostic stratification and may serve as a potential therapeutic target for prospective interventional studies.

High power diode pumped solid state (DPSS) laser systems active media robust modeling and analysis

NASA Astrophysics Data System (ADS)

Kashef, Tamer M.; Mokhtar, Ayman M.; Ghoniemy, Samy A.

2018-02-01

Diode side-pumped solid-state lasers have the potential to yield high quality laser beams with high efficiency and reliability. This paper summarizes the results of simulation of the most predominant active media that are used in high power diode pumped solid-state (DPSS) laser systems. Nd:YAG, Nd:glass, and Nd:YLF rods laser systems were simulated using the special finite element analysis software program LASCAD. A performance trade off analysis for Nd:YAG, Nd:glass, and Nd:YLF rods was performed in order to predict the system optimized parameters and to investigate thermally induced thermal fracture that may occur due to heat load and mechanical stress. The simulation results showed that at the optimized values Nd:YAG rod achieved the highest output power of 175W with 43% efficiency and heat load of 1.873W/mm3. A negligible changes in laser output power, heat load, stress, and temperature distributions were observed when the Nd:YAG rod length was increased from 72 to 80mm. Simulation of Nd:glass at different rod diameters at the same pumping conditions showed better results for mechanical stress and thermal load than that of Nd:YAG and Nd:YLF which makes it very suitable for high power laser applications especially for large rod diameters. For large rod diameters Nd:YLF is mechanically weaker and softer crystal compared to Nd:YAG and Nd:glass due to its poor thermomechanical properties which limits its usage to only low to medium power systems.

Mothers' early depressive symptoms and children's first-grade adjustment: a transactional analysis of child withdrawal as a mediator.

PubMed

Yan, Ni; Dix, Theodore

2014-05-01

The depression-inhibition hypothesis suggests that mothers' depressive symptoms undermine development because they lead children to withdraw from social contact. To test this, this study examined whether poor first-grade adjustment among children of mothers with depressive symptoms is mediated by the emergence of child withdrawal in early development. Based on 1,364 dyads, four waves of data spanning from 24 months to first grade (7 years) were used to examine paths by which children's withdrawal mediates relations between mothers' early depressive symptoms and three first-grade outcomes: social competence, academic performance, and externalizing behavior problems. Structural equation modeling revealed three principal paths. First, direct relations were observed: Mothers' depressive symptoms predicted early child withdrawal and increases in child withdrawal over time, which predicted poor first-grade adjustment. Second, reciprocal relations were observed: Mothers' depressive symptoms predicted child withdrawal, which predicted increases in depressive symptoms. Third, relations via mother-child mutual responsiveness were observed: Depression-related increases in child withdrawal predicted declines in mutual responsiveness, which predicted poor first-grade adjustment. The findings suggest that, due to its interdependence with maternal depression and low mother-child mutual responsiveness over time, child withdrawal may play an important role in the poor first-grade adjustment of children whose mothers are high in depressive symptoms. © 2013 The Authors. Journal of Child Psychology and Psychiatry. © 2013 Association for Child and Adolescent Mental Health.

Prediction of anaerobic power values from an abbreviated WAnT protocol.

PubMed

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

2008-05-01

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

Vouchers, Class Size Reduction, and Student Achievement: Considering the Evidence.

ERIC Educational Resources Information Center

Molnar, Alex

Proponents of private school vouchers argue that vouchers empower poor families and raise the academic achievement of poor children. They also argue that vouchers may improve achievement by forcing the public schools to compete in an education marketplace in which poor parents hold the power of the purse. Juxtaposed against this issue of vouchers…

HOW DO WE INVOLVE THE POOR IN WESTCHESTER'S WAR ON POVERTY.

ERIC Educational Resources Information Center

BECK, BERTRAM M.

THE SPEAKER SUGGESTED THAT THE POOR SHOULD PARTICIPATE IN POLICY-MAKING DECISIONS IN ANTIPOVERTY PROGRAMS AND BE GIVEN THE OPPORTUNITY FOR EMPLOYMENT WITHIN THE PROGRAMS THEMSELVES. HE FURTHER SUGGESTS SOME OF THE POWER NOW HELD BY OTHERS SHOULD BE RELINQUISHED TO THE POOR, WHO SHOULD HAVE THE RIGHT TO HELP DECIDE WHAT THEY WANT. PRIORITIES FOR…

Low Cerebral Blood Volume Identifies Poor Outcome in Stent Retriever Thrombectomy

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

Protto, Sara, E-mail: sara.protto@pshp.fi; Pienimäki, Juha-Pekka; Seppänen, Janne

BackgroundMechanical thrombectomy (MT) is an efficient treatment of acute stroke caused by large-vessel occlusion. We evaluated the factors predicting poor clinical outcome (3-month modified Rankin Scale, mRS >2) although MT performed with modern stent retrievers.MethodsWe prospectively collected the clinical and imaging data of 105 consecutive anterior circulation stroke patients who underwent MT after multimodal CT imaging. Patients with occlusion of the internal carotid artery and/or middle cerebral artery up to the M2 segment were included. We recorded baseline clinical, procedural and imaging variables, technical outcome, 24-h imaging outcome and the clinical outcome. Differences between the groups were studied with appropriatemore » statistical tests and binary logistic regression analysis.ResultsLow cerebral blood volume Alberta stroke program early CT score (CBV-ASPECTS) was associated with poor clinical outcome (median 7 vs. 9, p = 0.01). Lower collateral score (CS) significantly predicted poor outcome in regression modelling with CS = 0 increasing the odds of poor outcome 4.4-fold compared to CS = 3 (95% CI 1.27–15.5, p = 0.02). Lower CBV-ASPECTS significantly predicted poor clinical outcome among those with moderate or severe stroke (OR 0.82, 95% CI 0.68–1, p = 0.05) or poor collateral circulation (CS 0–1, OR 0.66, 95% CI 0.48–0.90, p = 0.009) but not among those with mild strokes or good collaterals.ConclusionsCBV-ASPECTS estimating infarct core is a significant predictor of poor clinical outcome among anterior circulation stroke patients treated with MT, especially in the setting of poor collateral circulation and/or moderate or severe stroke.« less

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…

Comparing the utility of the theory of planned behavior between boys and girls for predicting snack food consumption: implications for practice.

PubMed

Branscum, Paul; Sharma, Manoj

2014-01-01

The purpose of this study was to use the theory of planned behavior to explain two types of snack food consumption among boys and girls (girls n = 98; boys n = 69), which may have implications for future theory-based health promotion interventions. Between genders, there was a significant difference for calorie-dense/nutrient-poor snacks (p = .002), but no difference for fruit and vegetable snacks. Using stepwise multiple regression, attitudes, perceived behavioral control, and subjective norms accounted for a large amount of the variance of intentions (girls = 43.3%; boys = 55.9%); however, for girls, subjective norms accounted for the most variance, whereas for boys, attitudes accounted for the most variance. Calories from calorie-dense/nutrient-poor snacks and fruit and vegetable snacks were also predicted by intentions. For boys, intentions predicted 6.4% of the variance for fruit and vegetable snacks (p = .03) but was not significant for calorie-dense/nutrient-poor snacks, whereas for girls, intentions predicted 6.0% of the variance for fruit and vegetable snacks (p = .007), and 7.2% of the variance for calorie-dense/nutrient-poor snacks (p = .004). Results suggest that the theory of planned behavior is a useful framework for predicting snack foods among children; however, there are important differences between genders that should be considered in future health promotion interventions.

Subjective Sleep Quality in Women With Divorce Histories: The Role of Intimate Partner Victimization.

PubMed

Newton, Tamara L; Burns, Vicki Ellison; Miller, James J; Fernandez-Botran, G Rafael

2016-05-01

A marital status of divorced or separated, as opposed to married, predicts increased risk of health problems, but not for all persons. Focusing on one established health risk that has been linked with divorce--poor subjective sleep quality--the present cross-sectional study examined whether a history of physical intimate partner victimization (IPV) helps identify divorced women at potentially greater risk of health problems. Community midlife women with divorce histories, all of whom were free of current IPV, reported on their past month sleep quality and lifetime IPV. The predicted odds of poor sleep quality were significantly greater for women with, versus without, IPV histories. This held after adjusting for socioemotional, medical, or sociodemographic risks. A dose-response relationship between IPV chronicity and poor quality sleep was observed. IPV history may help identify divorced women at increased risk of poor quality sleep and, more broadly, poor health. © The Author(s) 2015.

Calculating the Responses of Self-Powered Radiation Detectors.

NASA Astrophysics Data System (ADS)

Thornton, D. A.

Available from UMI in association with The British Library. The aim of this research is to review and develop the theoretical understanding of the responses of Self -Powered Radiation Detectors (SPDs) in Pressurized Water Reactors (PWRs). Two very different models are considered. A simple analytic model of the responses of SPDs to neutrons and gamma radiation is presented. It is a development of the work of several previous authors and has been incorporated into a computer program (called GENSPD), the predictions of which have been compared with experimental and theoretical results reported in the literature. Generally, the comparisons show reasonable consistency; where there is poor agreement explanations have been sought and presented. Two major limitations of analytic models have been identified; neglect of current generation in insulators and over-simplified electron transport treatments. Both of these are developed in the current work. A second model based on the Explicit Representation of Radiation Sources and Transport (ERRST) is presented and evaluated for several SPDs in a PWR at beginning of life. The model incorporates simulation of the production and subsequent transport of neutrons, gamma rays and electrons, both internal and external to the detector. Neutron fluxes and fuel power ratings have been evaluated with core physics calculations. Neutron interaction rates in assembly and detector materials have been evaluated in lattice calculations employing deterministic transport and diffusion methods. The transport of the reactor gamma radiation has been calculated with Monte Carlo, adjusted diffusion and point-kernel methods. The electron flux associated with the reactor gamma field as well as the internal charge deposition effects of the transport of photons and electrons have been calculated with coupled Monte Carlo calculations of photon and electron transport. The predicted response of a SPD is evaluated as the sum of contributions from individual response mechanisms.

Single season changes in resting state network power and the connectivity between regions distinguish head impact exposure level in high school and youth football players

NASA Astrophysics Data System (ADS)

Murugesan, Gowtham; Saghafi, Behrouz; Davenport, Elizabeth; Wagner, Ben; Urban, Jillian; Kelley, Mireille; Jones, Derek; Powers, Alex; Whitlow, Christopher; Stitzel, Joel; Maldjian, Joseph; Montillo, Albert

2018-02-01

The effect of repetitive sub-concussive head impact exposure in contact sports like American football on brain health is poorly understood, especially in the understudied populations of youth and high school players. These players, aged 9-18 years old may be particularly susceptible to impact exposure as their brains are undergoing rapid maturation. This study helps fill the void by quantifying the association between head impact exposure and functional connectivity, an important aspect of brain health measurable via resting-state fMRI (rs-fMRI). The contributions of this paper are three fold. First, the data from two separate studies (youth and high school) are combined to form a high-powered analysis with 60 players. These players experience head acceleration within overlapping impact exposure making their combination particularly appropriate. Second, multiple features are extracted from rs-fMRI and tested for their association with impact exposure. One type of feature is the power spectral density decomposition of intrinsic, spatially distributed networks extracted via independent components analysis (ICA). Another feature type is the functional connectivity between brain regions known often associated with mild traumatic brain injury (mTBI). Third, multiple supervised machine learning algorithms are evaluated for their stability and predictive accuracy in a low bias, nested cross-validation modeling framework. Each classifier predicts whether a player sustained low or high levels of head impact exposure. The nested cross validation reveals similarly high classification performance across the feature types, and the Support Vector, Extremely randomized trees, and Gradboost classifiers achieve F1-score up to 75%.

The role of ovarian reserve markers in prediction of clinical pregnancy.

PubMed

Zebitay, Ali G; Cetin, Orkun; Verit, Fatma F; Keskin, Seda; Sakar, M Nafi; Karahuseyinoglu, Sercin; Ilhan, Gulsah; Sahmay, Sezai

2017-05-01

To evaluate the role of ovarian reserve markers in the prediction of clinical pregnancy and embryo transfer accomplishment among poor responder IVF applicants. 304 female poor responder IVF applicants were included in this prospective cohort study conducted at the IVF-unit. Antral follicle count, FSH, LH, E2, AMH and IVF outcomes were compared in pregnant and non-pregnant groups as well as in ET vs. non-ET groups. The number of retrieved oocytes was significantly correlated positively with AMH and AFC, and negatively with FSH and age. Quartiles of FSH and AFC were similar to the rate of pregnancy. Quartiles of AMH (<25%/25-75% and <25%/>75%) were statistically significant. Mean serum levels for AMH were significantly lower in the non-ET group. Our findings seem to indicate that day 3 AMH values can predict ET accomplishment with a sensitivity of 96% and a specificity of 35%. Quartiles of AMH <25% (< 0.21 ng/mL) can predict the IVF results among poor responder IVF applicants. Impact statement Various cut-off values have been determined for day 3 serum AMH values. These values help to determine the groups that are expected to give normal, high or low response to stimulation and decide the treatment options. In contrast to other groups of patients, poor responders cannot reach the embryo transfer stage for several reasons. These are; absence of a mature oocyte after oocyte pick-up, fertilisation failure without male factor or poor embryo quality. In the present study; a cut-off value of 0.33 ng/mL for the prediction of ET accomplishment in poor responder patients was determined with a sensitivity of 96%. Additionally, clinical pregnancy could not be achieved under the value of 0.21 ng/mL day 3 AMH values. It is important to clarify the embryo transfer success of poor responder patients prior to expected treatment success. Pre-treatment counselling for these patients would lessen the disappointment that may develop after treatment. The cost-effectiveness of treatments below these AMH values can be determined by further studies.

Logistic regression models for predicting physical and mental health-related quality of life in rheumatoid arthritis patients.

PubMed

Alishiri, Gholam Hossein; Bayat, Noushin; Fathi Ashtiani, Ali; Tavallaii, Seyed Abbas; Assari, Shervin; Moharamzad, Yashar

2008-01-01

The aim of this work was to develop two logistic regression models capable of predicting physical and mental health related quality of life (HRQOL) among rheumatoid arthritis (RA) patients. In this cross-sectional study which was conducted during 2006 in the outpatient rheumatology clinic of our university hospital, Short Form 36 (SF-36) was used for HRQOL measurements in 411 RA patients. A cutoff point to define poor versus good HRQOL was calculated using the first quartiles of SF-36 physical and mental component scores (33.4 and 36.8, respectively). Two distinct logistic regression models were used to derive predictive variables including demographic, clinical, and psychological factors. The sensitivity, specificity, and accuracy of each model were calculated. Poor physical HRQOL was positively associated with pain score, disease duration, monthly family income below 300 US$, comorbidity, patient global assessment of disease activity or PGA, and depression (odds ratios: 1.1; 1.004; 15.5; 1.1; 1.02; 2.08, respectively). The variables that entered into the poor mental HRQOL prediction model were monthly family income below 300 US$, comorbidity, PGA, and bodily pain (odds ratios: 6.7; 1.1; 1.01; 1.01, respectively). Optimal sensitivity and specificity were achieved at a cutoff point of 0.39 for the estimated probability of poor physical HRQOL and 0.18 for mental HRQOL. Sensitivity, specificity, and accuracy of the physical and mental models were 73.8, 87, 83.7% and 90.38, 70.36, 75.43%, respectively. The results show that the suggested models can be used to predict poor physical and mental HRQOL separately among RA patients using simple variables with acceptable accuracy. These models can be of use in the clinical decision-making of RA patients and to recognize patients with poor physical or mental HRQOL in advance, for better management.

Model predictive direct power control for active power decoupled single-phase quasi- Z -source inverter

DOE PAGES

Liu, Yushan; Ge, Baoming; Abu-Rub, Haitham; ...

2016-06-14

In this study, the active power filter (APF) that consists of a half-bridge leg and an ac capacitor is integrated in the single-phase quasi-Z-source inverter (qZSI) in this paper to avoid the second harmonic power flowing into the dc side. The capacitor of APF buffers the second harmonic power of the load, and the ac capacitor allows highly pulsating ac voltage, so that the capacitances of both dc and ac sides can be small. A model predictive direct power control (DPC) is further proposed to achieve the purpose of this newtopology through predicting the capacitor voltage of APF at eachmore » sampling period and ensuring the APF power to track the second harmonic power of single-phase qZSI. Simulation and experimental results verify the model predictive DPC for the APF-integrated single-phase qZSI.« less

Potentiality Prediction of Electric Power Replacement Based on Power Market Development Strategy

NASA Astrophysics Data System (ADS)

Miao, Bo; Yang, Shuo; Liu, Qiang; Lin, Jingyi; Zhao, Le; Liu, Chang; Li, Bin

2017-05-01

The application of electric power replacement plays an important role in promoting the development of energy conservation and emission reduction in our country. To exploit the potentiality of regional electric power replacement, the regional GDP (gross domestic product) and energy consumption are taken as potentiality evaluation indicators. The principal component factors are extracted with PCA (principal component analysis), and the integral potentiality analysis is made to the potentiality of electric power replacement in the national various regions; a region is taken as a research object, and the potentiality of electric power replacement is defined and quantified. The analytical model for the potentiality of multi-scenario electric power replacement is developed, and prediction is made to the energy consumption with the grey prediction model. The relevant theoretical research is utilized to realize prediction analysis on the potentiality amount of multi-scenario electric power replacement.

Model predictive direct power control for active power decoupled single-phase quasi- Z -source inverter

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

Liu, Yushan; Ge, Baoming; Abu-Rub, Haitham

In this study, the active power filter (APF) that consists of a half-bridge leg and an ac capacitor is integrated in the single-phase quasi-Z-source inverter (qZSI) in this paper to avoid the second harmonic power flowing into the dc side. The capacitor of APF buffers the second harmonic power of the load, and the ac capacitor allows highly pulsating ac voltage, so that the capacitances of both dc and ac sides can be small. A model predictive direct power control (DPC) is further proposed to achieve the purpose of this newtopology through predicting the capacitor voltage of APF at eachmore » sampling period and ensuring the APF power to track the second harmonic power of single-phase qZSI. Simulation and experimental results verify the model predictive DPC for the APF-integrated single-phase qZSI.« less

Bayesian predictive power: choice of prior and some recommendations for its use as probability of success in drug development.

PubMed

Rufibach, Kaspar; Burger, Hans Ulrich; Abt, Markus

2016-09-01

Bayesian predictive power, the expectation of the power function with respect to a prior distribution for the true underlying effect size, is routinely used in drug development to quantify the probability of success of a clinical trial. Choosing the prior is crucial for the properties and interpretability of Bayesian predictive power. We review recommendations on the choice of prior for Bayesian predictive power and explore its features as a function of the prior. The density of power values induced by a given prior is derived analytically and its shape characterized. We find that for a typical clinical trial scenario, this density has a u-shape very similar, but not equal, to a β-distribution. Alternative priors are discussed, and practical recommendations to assess the sensitivity of Bayesian predictive power to its input parameters are provided. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Predicting the extent of metabolism using in vitro permeability rate measurements and in silico permeability rate predictions

PubMed Central

Hosey, Chelsea M; Benet, Leslie Z

2015-01-01

The Biopharmaceutics Drug Disposition Classification System (BDDCS) can be utilized to predict drug disposition, including interactions with other drugs and transporter or metabolizing enzyme effects based on the extent of metabolism and solubility of a drug. However, defining the extent of metabolism relies upon clinical data. Drugs exhibiting high passive intestinal permeability rates are extensively metabolized. Therefore, we aimed to determine if in vitro measures of permeability rate or in silico permeability rate predictions could predict the extent of metabolism, to determine a reference compound representing the permeability rate above which compounds would be expected to be extensively metabolized, and to predict the major route of elimination of compounds in a two-tier approach utilizing permeability rate and a previously published model predicting the major route of elimination of parent drug. Twenty-two in vitro permeability rate measurement data sets in Caco-2 and MDCK cell lines and PAMPA were collected from the literature, while in silico permeability rate predictions were calculated using ADMET Predictor™ or VolSurf+. The potential for permeability rate to differentiate between extensively and poorly metabolized compounds was analyzed with receiver operating characteristic curves. Compounds that yielded the highest sensitivity-specificity average were selected as permeability rate reference standards. The major route of elimination of poorly permeable drugs was predicted by our previously published model and the accuracies and predictive values were calculated. The areas under the receiver operating curves were >0.90 for in vitro measures of permeability rate and >0.80 for the VolSurf+ model of permeability rate, indicating they were able to predict the extent of metabolism of compounds. Labetalol and zidovudine predicted greater than 80% of extensively metabolized drugs correctly and greater than 80% of poorly metabolized drugs correctly in Caco-2 and MDCK, respectively, while theophylline predicted greater than 80% of extensively and poorly metabolized drugs correctly in PAMPA. A two-tier approach predicting elimination route predicts 72±9%, 49±10%, and 66±7% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly when the permeability rate is predicted in silico and 74±7%, 85±2%, and 73±8% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly, respectively when the permeability rate is determined in vitro. PMID:25816851

Development of a prediction tool for patients presenting with acute cough in primary care: a prognostic study spanning six European countries.

PubMed

Bruyndonckx, Robin; Hens, Niel; Verheij, Theo Jm; Aerts, Marc; Ieven, Margareta; Butler, Christopher C; Little, Paul; Goossens, Herman; Coenen, Samuel

2018-05-01

Accurate prediction of the course of an acute cough episode could curb antibiotic overprescribing, but is still a major challenge in primary care. The authors set out to develop a new prediction rule for poor outcome (re-consultation with new or worsened symptoms, or hospital admission) in adults presenting to primary care with acute cough. Data were collected from 2604 adults presenting to primary care with acute cough or symptoms suggestive of lower respiratory tract infection (LRTI) within the Genomics to combat Resistance against Antibiotics in Community-acquired LRTI in Europe (GRACE; www.grace-lrti.org) Network of Excellence. Important signs and symptoms for the new prediction rule were found by combining random forest and logistic regression modelling. Performance to predict poor outcome in acute cough patients was compared with that of existing prediction rules, using the models' area under the receiver operator characteristic curve (AUC), and any improvement obtained by including additional test results (C-reactive protein [CRP], blood urea nitrogen [BUN], chest radiography, or aetiology) was evaluated using the same methodology. The new prediction rule, included the baseline Risk of poor outcome, Interference with daily activities, number of years stopped Smoking (> or <45 years), severity of Sputum, presence of Crackles, and diastolic blood pressure (> or <85 mmHg) (RISSC85). Though performance of RISSC85 was moderate (sensitivity 62%, specificity 59%, positive predictive value 27%, negative predictive value 86%, AUC 0.63, 95% confidence interval [CI] = 0.61 to 0.67), it outperformed all existing prediction rules used today (highest AUC 0.53, 95% CI = 0.51 to 0.56), and could not be significantly improved by including additional test results (highest AUC 0.64, 95% CI = 0.62 to 0.68). The new prediction rule outperforms all existing alternatives in predicting poor outcome in adult patients presenting to primary care with acute cough and could not be improved by including additional test results. © British Journal of General Practice 2018.

History, Structure and Agency in Global Health Governance

PubMed Central

Gill, Stephen; Benatar, Solomon R.

2017-01-01

Ilona Kickbusch’s thought provoking editorial is criticized in this commentary, partly because she fails to refer to previous critical work on the global conditions and policies that sustain inequality, poverty, poor health and damage to the biosphere and, as a result, she misreads global power and elides consideration of the fundamental historical structures of political and material power that shape agency in global health governance. We also doubt that global health can be improved through structures and processes of multilateralism that are premised on the continued reproduction of the ecologically myopic and socially unsustainable market civilization model of capitalist development that currently prevails in the world economy. This model drives net financial flows from poor to rich countries and from the poor to the affluent and super wealthy individuals. By contrast, we suggest that significant progress in global health requires a profound and socially just restructuring of global power, greater global solidarity and the "development of sustainability." PMID:28812808

Pharmacological strategies for the management of cancer pain in developing countries

PubMed Central

Omoti, Afekhide E.; Omoti, Caroline E.

Pain associated with cancer is often under treated especially in the developing countries where there are problems of poor economy, poor purchasing power of the citizens, absence of effective national health insurance schemes, poor manpower, fake adulterated and expired drugs, poor drug storage conditions; adverse temperature conditions combined with poor power supply which may affect drug efficacy. There is also poor understanding of the physiopharmacology of cancer pain management by health care providers. Assessment of the severity of the pain by location, oncological type, as well as psychosocial, emotional and environmental factors are necessary. The pain often occurs from malignancy, from procedures done to diagnose, stage and treat the malignancy, and from the toxicities of therapy used in treating the cancer. The first priority of treatment is to control pain rapidly and completely, as judged by the patient. The second priority is to prevent recurrence of pain. Analgesic drugs are given ‘by the ladder,’ ‘by the clock’ and ‘by the appropriate route’ using the analgesic ladder guideline proposed by the World Health Organization (WHO). The pharmacological aspects of various drugs used in the management of cancer pain are discussed. PMID:25247009

Power maximization of a point absorber wave energy converter using improved model predictive control

NASA Astrophysics Data System (ADS)

Milani, Farideh; Moghaddam, Reihaneh Kardehi

2017-08-01

This paper considers controlling and maximizing the absorbed power of wave energy converters for irregular waves. With respect to physical constraints of the system, a model predictive control is applied. Irregular waves' behavior is predicted by Kalman filter method. Owing to the great influence of controller parameters on the absorbed power, these parameters are optimized by imperialist competitive algorithm. The results illustrate the method's efficiency in maximizing the extracted power in the presence of unknown excitation force which should be predicted by Kalman filter.

Reconsidering the logic of World Federation of Neurosurgical Societies grading in patients with severe subarachnoid hemorrhage.

PubMed

Fung, Christian; Inglin, Fabienne; Murek, Michael; Balmer, Mathias; Abu-Isa, Janine; Z'Graggen, Werner J; Ozdoba, Christoph; Gralla, Jan; Jakob, Stephan M; Takala, Jukka; Beck, Jürgen; Raabe, Andreas

2016-02-01

Current data show a favorable outcome in up to 50% of patients with World Federation of Neurosurgical Societies (WFNS) Grade V subarachnoid hemorrhage (SAH) and a rather poor prediction of worst cases. Thus, the usefulness of the current WFNS grading system for identifying the worst scenarios for clinical studies and for making treatment decisions is limited. One reason for this lack of differentiation is the use of "negative" or "silent" diagnostic signs as part of the WFNS Grade V definition. The authors therefore reevaluated the WFNS scale by using "positive" clinical signs and the logic of the Glasgow Coma Scale as a progressive herniation score. The authors performed a retrospective analysis of 182 patients with SAH who had poor grades on the WFNS scale. Patients were graded according to the original WFNS scale and additionally according to a modified classification, the WFNS herniation (hWFNS) scale (Grade IV, no clinical signs of herniation; Grade V, clinical signs of herniation). The prediction of poor outcome was compared between these two grading systems. The positive predictive values of Grade V for poor outcome were 74.3% (OR 3.79, 95% CI 1.94-7.54) for WFNS Grade V and 85.7% (OR 8.27, 95% CI 3.78-19.47) for hWFNS Grade V. With respect to mortality, the positive predictive values were 68.3% (OR 3.9, 95% CI 2.01-7.69) for WFNS Grade V and 77.9% (OR 6.22, 95% CI 3.07-13.14) for hWFNS Grade V. Limiting WFNS Grade V to the positive clinical signs of the Glasgow Coma Scale such as flexion, extension, and pupillary abnormalities instead of including "no motor response" increases the prediction of mortality and poor outcome in patients with severe SAH.

Identifying Medical Students Likely to Exhibit Poor Professionalism and Knowledge During Internship

PubMed Central

Durning, Steven J.; Cohen, Daniel L.; Cruess, David; Jackson, Jeffrey L.

2007-01-01

CONTEXT Identifying medical students who will perform poorly during residency is difficult. OBJECTIVE Determine whether commonly available data predicts low performance ratings during internship by residency program directors. DESIGN Prospective cohort involving medical school data from graduates of the Uniformed Services University (USU), surveys about experiences at USU, and ratings of their performance during internship by their program directors. SETTING Uniformed Services University. PARTICIPANTS One thousand sixty-nine graduates between 1993 and 2002. MAIN OUTCOME MEASURE(S) Residency program directors completed an 18-item survey assessing intern performance. Factor analysis of these items collapsed to 2 domains: knowledge and professionalism. These domains were scored and performance dichotomized at the 10th percentile. RESULTS Many variables showed a univariate relationship with ratings in the bottom 10% of both domains. Multivariable logistic regression modeling revealed that grades earned during the third year predicted low ratings in both knowledge (odds ratio [OR] = 4.9; 95%CI = 2.7–9.2) and professionalism (OR = 7.3; 95%CI = 4.1–13.0). USMLE step 1 scores (OR = 1.03; 95%CI = 1.01–1.05) predicted knowledge but not professionalism. The remaining variables were not independently predictive of performance ratings. The predictive ability for the knowledge and professionalism models was modest (respective area under ROC curves = 0.735 and 0.725). CONCLUSIONS A strong association exists between the third year GPA and internship ratings by program directors in professionalism and knowledge. In combination with third year grades, either the USMLE step 1 or step 2 scores predict poor knowledge ratings. Despite a wealth of available markers and a large data set, predicting poor performance during internship remains difficult. PMID:17952512

A response to Edzi (AIDS): Malawi faith-based organizations' impact on HIV prevention and care.

PubMed

Lindgren, Teri; Schell, Ellen; Rankin, Sally; Phiri, Joel; Fiedler, Rachel; Chakanza, Joseph

2013-01-01

African faith-based organization (FBO) leaders influence their members' HIV knowledge, beliefs, and practices, but their roles in HIV prevention and care are poorly understood. This article expands the work of Garner (2000) to test the impact of FBO influence on member risk and care behaviors, embedding it in the Theory of Planned Behavior. Qualitative interviews and quantitative surveys were collected from five FBOs (Christian and Muslim) in Malawi and analyzed using mixed methods. Contrary to Garner, we found that the level of power and influence of the FBO had no significant impact on the risk-taking behaviors of members; however, leaders' HIV knowledge predicted members' behaviors. Stigmatizing attitudes of leaders significantly decreased members' care behaviors, but FBO hierarchy tended to increase members' care behaviors. The power of local church and mosque leaders to influence behavior could be exploited more effectively by nurses by providing support, knowledge, and encouragement to churches and mosques. Copyright © 2013 Association of Nurses in AIDS Care. Published by Elsevier Inc. All rights reserved.

Quantum-chemical studies on hexaazaisowurtzitanes.

PubMed

Ghule, V D; Jadhav, P M; Patil, R S; Radhakrishnan, S; Soman, T

2010-01-14

Highly nitrated cage molecules constitute a new class of energetic materials that have received a substantial amount of interest. Among them 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (CL-20) is a powerful explosive with poor impact and friction characteristics. In the present study we aim to design novel energetic materials by tailoring the molecular structure of CL-20. Important characteristics such as the heat of formation and density have been predicted using density functional theory and packing calculations, respectively. Sensitivity correlations have been established for model compounds by analyzing the charge on the nitro groups. Molecules IDX1, IDX4, and IDX7 have been found to have comparable performance with better insensitivity characteristics and may be explored as CL-20 substitutes in defense applications.

Interaction Models for Functional Regression.

PubMed

Usset, Joseph; Staicu, Ana-Maria; Maity, Arnab

2016-02-01

A functional regression model with a scalar response and multiple functional predictors is proposed that accommodates two-way interactions in addition to their main effects. The proposed estimation procedure models the main effects using penalized regression splines, and the interaction effect by a tensor product basis. Extensions to generalized linear models and data observed on sparse grids or with measurement error are presented. A hypothesis testing procedure for the functional interaction effect is described. The proposed method can be easily implemented through existing software. Numerical studies show that fitting an additive model in the presence of interaction leads to both poor estimation performance and lost prediction power, while fitting an interaction model where there is in fact no interaction leads to negligible losses. The methodology is illustrated on the AneuRisk65 study data.

Young people’s differential vulnerability to criminogenic exposure: Bridging the gap between people- and place-oriented approaches in the study of crime causation

PubMed Central

Wikström, Per-Olof H; Mann, Richard P; Hardie, Beth

2018-01-01

The overall purpose of this study is to contribute to bridging the gap between people- and place-oriented approaches in the study of crime causation. To achieve this we will explore some core hypotheses derived from Situational Action Theory about what makes young people crime prone and makes places criminogenic, and about the interaction between crime propensity and criminogenic exposure predicting crime events. We will also calculate the expected reduction in aggregate levels of crime that will occur as a result of successful interventions targeting crime propensity and criminogenic exposure. To test the hypotheses we will utilize a unique set of space–time budget, small area community survey, land-use and interviewer-led questionnaire data from the prospective longitudinal Peterborough Adolescent and Young Adult Development Study (PADS+) and an artificial neural network approach to modelling. The results show that people’s crime propensity (based on their personal morals and abilities to exercise self-control) has the bulk of predictive power, but also that including criminogenic exposure (being unsupervised with peers and engaged in unstructured activities in residential areas of poor collective efficacy or commercial centres) demonstrates a substantial increase in predictive power (in addition to crime propensity). Moreover, the results show that the probability of crime is strongest when a crime-prone person is in a criminogenic setting and, crucially, that the higher a person’s crime propensity the more vulnerable he or she is to influences of criminogenic exposure. Finally, the findings suggest that a reduction in people’s crime propensity has a much bigger impact on their crime involvement than a reduction in their exposure to criminogenic settings. PMID:29416442

Comparative study of chaotic features in hourly wind speed using recurrence quantification analysis

NASA Astrophysics Data System (ADS)

Adeniji, A. E.; Olusola, O. I.; Njah, A. N.

2018-02-01

Due to the shortage in electricity supply in Nigeria, there is a need to improve the alternative power generation from wind energy by analysing the wind speed data available in some parts of the country, for a better understanding of its underlying dynamics for the purpose of good prediction and modelling. The wind speed data used in this study were collected over a period of two years by National Space Research and Development Agency (NASRDA) from five different stations in the tropics namely; Abuja (7050'02.09"N and 6004'29.97"E), Akungba (6059'05.40"N and 5035'52.23"E), Nsukka (6051'28.14"N and 7024'28.15"E), Port Harcourt (4047'05.41"N and 6059'30.62"E), and Yola (9017'33.58"N and 12023'26.69"E). In this paper, recurrence plot (RP) and recurrence quantification analysis (RQA) are applied to investigate a non-linear deterministic dynamical process and non-stationarity in hourly wind speed data from the study areas. Using RQA for each month of the two years, it is observed that wind speed data for the wet months exhibit higher chaoticity than that of the dry months for all the stations, due to strong and weak monsoonal effect during the wet and dry seasons respectively. The results show that recurrence techniques are able to identify areas and periods for which the harvest of wind energy for power generation is good (high predictability) and poor (low predictability) in the study areas. This work also validates the RQA measures (Lmax, DET and ENT) used and establishes that they are similar/related as they give similar results for the dynamical characterization of the wind speed data.

1 H MR spectroscopy in cervical carcinoma using external phase array body coil at 3.0 Tesla: Prediction of poor prognostic human papillomavirus genotypes.

PubMed

Lin, Gigin; Lai, Chyong-Huey; Tsai, Shang-Yueh; Lin, Yu-Chun; Huang, Yu-Ting; Wu, Ren-Chin; Yang, Lan-Yan; Lu, Hsin-Ying; Chao, Angel; Wang, Chiun-Chieh; Ng, Koon-Kwan; Ng, Shu-Hang; Chou, Hung-Hsueh; Yen, Tzu-Chen; Hung, Ji-Hong

2017-03-01

To assess the clinical value of proton ( 1 H) MR spectroscopy in cervical carcinomas, in the prediction of poor prognostic human papillomavirus (HPV) genotypes as well as persistent disease following concurrent chemoradiotherapy (CCRT). 1 H MR spectroscopy using external phase array coil was performed in 52 consecutive cervical cancer patients at 3 Tesla (T). Poor prognostic HPV genotypes (alpha-7 species or absence of HPV infection) and persistent cervical carcinoma after CCRT were recorded. Statistical significance was calculated with the Mann-Whitney two-sided nonparametric test and areas under the receiver operating characteristics curve (AUC) analysis. A 4.3-fold (P = 0.032) increased level of methyl resonance at 0.9 ppm was found in the poor prognostic HPV genotypes, mainly attributed to the presence of HPV18, with a sensitivity of 75%, a specificity of 81%, and an AUC of 0.76. Poor prognostic HPV genotypes were more frequently observed in patients with adeno-/adenosquamous carcinoma (Chi-square, P < 0.0001). In prediction of the four patients with persistent disease after CCRT, elevated methyl resonance demonstrated a sensitivity of 100%, a specificity of 74%, and an AUC of 0.82. 1 H MR spectroscopy at 3T can be used to depict the elevated lipid resonance levels in cervical carcinomas, as well as help to predict the poor prognostic HPV genotypes and persistent disease following CCRT. Further large studies with longer follow up times are warranted to validate our initial findings. 1 J. Magn. Reson. Imaging 2017;45:899-907. © 2016 International Society for Magnetic Resonance in Medicine.

Resting-state EEG, Impulsiveness, and Personality in Daily and Nondaily Smokers†

PubMed Central

Rass, Olga; Ahn, Woo-Young; O’Donnell, Brian F.

2015-01-01

Objectives Resting EEG is sensitive to transient, acute effects of nicotine administration and abstinence, but the chronic effects smoking on EEG are poorly characterized. This study measures the resting EEG profile of chronic smokers in a non-deprived, non-peak state to test whether differences in smoking behavior and personality traits affect pharmaco-EEG response. Methods Resting EEG, impulsiveness, and personality measures were collected from daily smokers (n=22), nondaily smokers (n=31), and non-smokers (n=30). Results Daily smokers had reduced resting delta and alpha EEG power and higher impulsiveness (Barratt Impulsiveness Scale) compared to nondaily smokers and non-smokers. Both daily and nondaily smokers discounted delayed rewards more steeply, reported lower conscientiousness (NEO-FFI) and reported greater disinhibition and experience seeking (Sensation Seeking Scale) than non-smokers. Nondaily smokers reported greater sensory hedonia than nonsmokers. Conclusions Altered resting EEG power in daily smokers demonstrates differences in neural signaling that correlated with greater smoking behavior and dependence. Although nondaily smokers share some characteristics with daily smokers that may predict smoking initiation and maintenance, they differ on measures of impulsiveness and resting EEG power. Significance Resting EEG in non-deprived chronic smokers provides a standard for comparison to peak and trough nicotine states and may serve as a biomarker for nicotine dependence, relapse risk, and recovery. PMID:26051750

PD-L1, Galectin-9 and CD8+ tumor-infiltrating lymphocytes are associated with survival in hepatocellular carcinoma.

PubMed

Sideras, Kostandinos; Biermann, Katharina; Verheij, Joanne; Takkenberg, Bart R; Mancham, Shanta; Hansen, Bettina E; Schutz, Hannah M; de Man, Robert A; Sprengers, Dave; Buschow, Sonja I; Verseput, Maddy C M; Boor, Patrick P C; Pan, Qiuwei; van Gulik, Thomas M; Terkivatan, Turkan; Ijzermans, Jan N M; Beuers, Ulrich H W; Sleijfer, Stefan; Bruno, Marco J; Kwekkeboom, Jaap

2017-01-01

Novel systemic treatments for hepatocellular carcinoma (HCC) are strongly needed. Immunotherapy is a promising strategy that can induce specific antitumor immune responses. Understanding the mechanisms of immune resistance by HCC is crucial for development of suitable immunotherapeutics. We used immunohistochemistry on tissue-microarrays to examine the co-expression of the immune inhibiting molecules PD-L1, Galectin-9, HVEM and IDO, as well as tumor CD8 + lymphocyte infiltration in HCC, in two independent cohorts of patients. We found that at least some expression in tumor cells was seen in 97% of cases for HVEM, 83% for PD-L1, 79% for Gal-9 and 66% for IDO. In the discovery cohort (n = 94), we found that lack of, or low, tumor expression of PD-L1 ( p < 0.001), Galectin-9 ( p < 0.001) and HVEM ( p < 0.001), and low CD8 + TIL count ( p = 0.016), were associated with poor HCC-specific survival. PD-L1, Galectin-9 and CD8 + TIL count were predictive of HCC-specific survival independent of baseline clinicopathologic characteristics and the combination of these markers was a powerful predictor of HCC-specific survival (HR 0.29; p <0.001). These results were confirmed in the validation cohort (n = 60). We show that low expression levels of PD-L1 and Gal-9 in combination with low CD8 + TIL count predict extremely poor HCC-specific survival and it requires a change in two of these parameters to significantly improve prognosis. In conclusion, intra-tumoral expression of these immune inhibiting molecules was observed in the majority of HCC patients. Low expression of PD-L1 and Galectin-9 and low CD8 + TIL count are associated with poor HCC-specific survival. Combining immune biomarkers leads to superior predictors of HCC mortality.

Changes in the level of cardiac troponine and disorders in pulmonary gas exchange as predictors of short- and long-term outcomes of patients with aneurysm subarachnoid haemorrhage.

PubMed

Burzyńska, Małgorzata; Uryga, Agnieszka; Kasprowicz, Magdalena; Kędziora, Jarosław; Szewczyk, Ewa; Woźniak, Jowita; Jarmundowicz, Włodzimierz; Kübler, Andrzej

2017-12-01

Cardiopulmonary abnormalities are common after aneurysmal subarachnoid haemorrhage (aSAH). However, the relationship between short- and long-term outcome is poorly understood. In this paper, we present how cardiac troponine elevations (cTnI) and pulmonary disorders are associated with short- and long-term outcomes assessed by the Glasgow Outcome Scale (GOS) and Extended Glasgow Outcome Scale (GOSE). A total of 104 patients diagnosed with aSAH were analysed in the study. The non-parametric U Mann-Whitney test was used to evaluate the difference between good (GOS IV-V, GOSE V-VIII) and poor (GOS I-III, GOSE I-IV) outcomes in relation to cTnI elevation and pulmonary disorders. Outcome was assessed at discharge from the hospital, and then followed up 6 and 12 months later. Pulmonary disorders were determined by the PaO 2 /FiO 2 ratio and radiography. The areas under the ROC curves (AUCs) were used to determine the predictive power of these factors. In the group with good short-term outcomes cTnI elevation on the second day after aSAH was significantly lower (p = .00007) than in patients with poor short-term outcomes. The same trend was observed after 6 months, although there were different results 12 months from the onset (p = .024 and n.s., respectively). A higher peak of cTnI was observed in the group with a pathological X-ray (p = .008) and pathological PaO 2 /FiO 2 ratio (p ≪ .001). cTnI was an accurate predictor of short-term outcomes (AUC = 0.741, p ≪ .001) and the outcome after 6 months (AUC = 0.688, p = .015). The results showed that cardiopulmonary abnormalities perform well as predictive factors for short- and long-term outcomes after aSAH.

The prediction of disability by self-reported physical frailty components of the Tilburg Frailty Indicator (TFI).

PubMed

Gobbens, R J J; van Assen, M A L M; Schalk, M J D

2014-01-01

Disability is an important health outcome for older persons; it is associated with impaired quality of life, future hospitalization, and mortality. Disability also places a high burden on health care professionals and health care systems. Disability is regarded as an adverse outcome of physical frailty. The main objective of this study was to assess the predictive validity of the eight individual self-reported components of the physical frailty subscale of the TFI for activities of daily living (ADL) and instrumental activities of daily living (IADL) disability. This longitudinal study was carried out with a sample of Dutch citizens. At baseline the sample consisted at 429 people aged 65 years and older and a subset of all respondents participated again two and a half years later (N=355, 83% response rate). The respondents completed a web-based questionnaire comprising the TFI and the Groningen Activity Restriction Scale (GARS) for measuring disability. Five components together (unintentional weakness, weakness, poor endurance, slowness, low physical activity), referring to the phenotype of Fried et al., predicted disability, even after controlling for previous disability and other background characteristics. The other three components of the physical frailty subscale of the TFI (poor balance, poor hearing, poor vision) together did not predict disability. Low physical activity predicted both total and ADL disability, and slowness both total and IADL disability. In conclusion, self-report assessment using the physical subscale of the TFI aids the prediction of future ADL and IADL disability in older persons two and a half years later. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Development and design of photovoltaic power prediction system

NASA Astrophysics Data System (ADS)

Wang, Zhijia; Zhou, Hai; Cheng, Xu

2018-02-01

In order to reduce the impact of power grid safety caused by volatility and randomness of the energy produced in photovoltaic power plants, this paper puts forward a construction scheme on photovoltaic power generation prediction system, introducing the technical requirements, system configuration and function of each module, and discussing the main technical features of the platform software development. The scheme has been applied in many PV power plants in the northwest of China. It shows that the system can produce reasonable prediction results, providing a right guidance for dispatching and efficient running for PV power plant.

Photovoltaics: A Solar Technology for Powering Tomorrow.

ERIC Educational Resources Information Center

Flavin, Christopher

1983-01-01

Photovoltaics, the technology that converts sunlight directly into electricity, may soon be a reliable power source for the world's poor. The one major challenge is cost reduction. Many topics are discussed, including solar powering the Third World, designing the solar building, investing in the sun, and the future of photovoltaics. (NW)

Power-poor nation taps jungle river for energy

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

Not Available

1979-12-13

The Paute River 1,690-MW hydroelectric power project near Cuenca will triple the power generating capacity of Ecuador. Progress on this practically inaccessible site is reported. The centerpiece will be the 560-ft-high Amaluza Dam. The underground powerhouse is slated to come on line in 1982.

How PowerPoint Is Killing Education

ERIC Educational Resources Information Center

Isseks, Marc

2011-01-01

Although it is essential to incorporate new technologies into the classroom, says Isseks, one trend has negatively affected instruction--the misuse of PowerPoint presentations. The author describes how poorly designed PowerPoint presentations reduce complex thoughts to bullet points and reduce the act of learning to transferring text from slide to…

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

Comparisons with observational and experimental manipulation data imply needed conceptual changes to ESM land models

NASA Astrophysics Data System (ADS)

Riley, W. J.; Zhu, Q.; Tang, J.

2016-12-01

The land models integrated in Earth System Models (ESMs) are critical components necessary to predict soil carbon dynamics and carbon-climate interactions under a changing climate. Yet, these models have been shown to have poor predictive power when compared with observations and ignore many processes known to the observational communities to influence above and belowground carbon dynamics. Here I will report work to tightly couple observations and perturbation experiment results with development of an ESM land model (ALM), focusing on nutrient constraints of the terrestrial C cycle. Using high-frequency flux tower observations and short-term nitrogen and phosphorus perturbation experiments, we show that conceptualizing plant and soil microbe interactions as a multi-substrate, multi-competitor kinetic network allows for accurate prediction of nutrient acquisition. Next, using multiple-year FACE and fertilization response observations at many forest sites, we show that capturing the observed responses requires representation of dynamic allocation to respond to the resulting stresses. Integrating the mechanisms implied by these observations into ALM leads to much lower observational bias and to very different predictions of long-term soil and aboveground C stocks and dynamics, and therefore C-climate feedbacks. I describe how these types of observational constraints are being integrated into the open-source International Land Model Benchmarking (ILAMB) package, and end with the argument that consolidating as many observations of all sorts for easy use by modelers is an important goal to improve C-climate feedback predictions.

Automated use of mutagenesis data in structure prediction.

PubMed

Nanda, Vikas; DeGrado, William F

2005-05-15

In the absence of experimental structural determination, numerous methods are available to indirectly predict or probe the structure of a target molecule. Genetic modification of a protein sequence is a powerful tool for identifying key residues involved in binding reactions or protein stability. Mutagenesis data is usually incorporated into the modeling process either through manual inspection of model compatibility with empirical data, or through the generation of geometric constraints linking sensitive residues to a binding interface. We present an approach derived from statistical studies of lattice models for introducing mutation information directly into the fitness score. The approach takes into account the phenotype of mutation (neutral or disruptive) and calculates the energy for a given structure over an ensemble of sequences. The structure prediction procedure searches for the optimal conformation where neutral sequences either have no impact or improve stability and disruptive sequences reduce stability relative to wild type. We examine three types of sequence ensembles: information from saturation mutagenesis, scanning mutagenesis, and homologous proteins. Incorporating multiple sequences into a statistical ensemble serves to energetically separate the native state and misfolded structures. As a result, the prediction of structure with a poor force field is sufficiently enhanced by mutational information to improve accuracy. Furthermore, by separating misfolded conformations from the target score, the ensemble energy serves to speed up conformational search algorithms such as Monte Carlo-based methods. Copyright 2005 Wiley-Liss, Inc.

Prediction of passive blood-brain partitioning: straightforward and effective classification models based on in silico derived physicochemical descriptors

PubMed Central

Vilar, Santiago; Chakrabarti, Mayukh; Costanzi, Stefano

2010-01-01

The distribution of compounds between blood and brain is a very important consideration for new candidate drug molecules. In this paper, we describe the derivation of two linear discriminant analysis (LDA) models for the prediction of passive blood-brain partitioning, expressed in terms of log BB values. The models are based on computationally derived physicochemical descriptors, namely the octanol/water partition coefficient (log P), the topological polar surface area (TPSA) and the total number of acidic and basic atoms, and were obtained using a homogeneous training set of 307 compounds, for all of which the published experimental log BB data had been determined in vivo. In particular, since molecules with log BB > 0.3 cross the blood-brain barrier (BBB) readily while molecules with log BB < −1 are poorly distributed to the brain, on the basis of these thresholds we derived two distinct models, both of which show a percentage of good classification of about 80%. Notably, the predictive power of our models was confirmed by the analysis of a large external dataset of compounds with reported activity on the central nervous system (CNS) or lack thereof. The calculation of straightforward physicochemical descriptors is the only requirement for the prediction of the log BB of novel compounds through our models, which can be conveniently applied in conjunction with drug design and virtual screenings. PMID:20427217

Prediction of passive blood-brain partitioning: straightforward and effective classification models based on in silico derived physicochemical descriptors.

PubMed

Vilar, Santiago; Chakrabarti, Mayukh; Costanzi, Stefano

2010-06-01

The distribution of compounds between blood and brain is a very important consideration for new candidate drug molecules. In this paper, we describe the derivation of two linear discriminant analysis (LDA) models for the prediction of passive blood-brain partitioning, expressed in terms of logBB values. The models are based on computationally derived physicochemical descriptors, namely the octanol/water partition coefficient (logP), the topological polar surface area (TPSA) and the total number of acidic and basic atoms, and were obtained using a homogeneous training set of 307 compounds, for all of which the published experimental logBB data had been determined in vivo. In particular, since molecules with logBB>0.3 cross the blood-brain barrier (BBB) readily while molecules with logBB<-1 are poorly distributed to the brain, on the basis of these thresholds we derived two distinct models, both of which show a percentage of good classification of about 80%. Notably, the predictive power of our models was confirmed by the analysis of a large external dataset of compounds with reported activity on the central nervous system (CNS) or lack thereof. The calculation of straightforward physicochemical descriptors is the only requirement for the prediction of the logBB of novel compounds through our models, which can be conveniently applied in conjunction with drug design and virtual screenings. Published by Elsevier Inc.

Blend sign predicts poor outcome in patients with intracerebral hemorrhage

PubMed Central

Cao, Du; Zhu, Dan; Lv, Fa-Jin; Liu, Yang; Yuan, Liang; Zhang, Gang; Xiong, Xin; Li, Rui; Hu, Yun-Xin; Qin, Xin-Yue; Xie, Peng

2017-01-01

Introduction Blend sign has been recently described as a novel imaging marker that predicts hematoma expansion. The purpose of our study was to investigate the prognostic value of CT blend sign in patients with ICH. Objectives and methods Patients with intracerebral hemorrhage who underwent baseline CT scan within 6 hours were included. The presence of blend sign on admission nonenhanced CT was independently assessed by two readers. The functional outcome was assessed by using the modified Rankin Scale (mRS) at 90 days. Results Blend sign was identified in 40 of 238 (16.8%) patients on admission CT scan. The proportion of patients with a poor functional outcome was significantly higher in patients with blend sign than those without blend sign (75.0% versus 47.5%, P = 0.001). The multivariate logistic regression analysis demonstrated that age, intraventricular hemorrhage, admission GCS score, baseline hematoma volume and presence of blend sign on baseline CT independently predict poor functional outcome at 90 days. The CT blend sign independently predicts poor outcome in patients with ICH (odds ratio 3.61, 95% confidence interval [1.47–8.89];p = 0.005). Conclusions Early identification of blend sign is useful in prognostic stratification and may serve as a potential therapeutic target for prospective interventional studies. PMID:28829797

Predicting contraceptive vigilance in adolescent females: a projective method for assessing ego development.

PubMed

Speier, P L; Mélèse-D'Hospital, I A; Tschann, J M; Moore, P J; Adler, N E

1997-01-01

To test the hypothesis that ego development would predict contraceptive use. Problems in ego development were defined in terms of three factors: (1) realism, (2) complexity, and (3) discontinuity. Forty-one respondents aged 14-17 years were selected from a group of 233 adolescents who were administered a projective pregnancy scenario and participated in a 12-month follow-up. Twenty of these adolescents were randomly selected from the group determined to be effective contraceptive users, while 21 were randomly selected from the group of poor contraceptors. Chi-square test revealed a significant association (p < .0005) between the composite ego maturity (EM) measure and contraceptive outcome (chi 2 = 13.82, with df-1). Low scores on the ego maturity measure predicted poor contraceptive use. EM was unrelated to age but was associated with race (chi 2 = 7.535, .025 < p < .05). However, EM predicted contraceptive use when controlling for the effects of race. A simple, time-efficient projective pregnancy scenario is an effective way of determining adolescent females at risk for poor contraceptive effectiveness and, therefore, untimely pregnancy. These stories are analyzed using factors related to the ego development of the adolescent. Subjects who scored lower on this measure have poor contraceptive effectiveness while subjects with higher levels demonstrated effective contraception use, at 1-year follow-up.

Managing PV Power on Mars - MER Rovers

NASA Technical Reports Server (NTRS)

Stella, Paul M.; Chin, Keith; Wood, Eric; Herman, Jennifer; Ewell, Richard

2009-01-01

The MER Rovers have recently completed over 5 years of operation! This is a remarkable demonstration of the capabilities of PV power on the Martian surface. The extended mission required the development of an efficient process to predict the power available to the rovers on a day-to-day basis. The performance of the MER solar arrays is quite unlike that of any other Space array and perhaps more akin to Terrestrial PV operation, although even severe by that comparison. The impact of unpredictable factors, such as atmospheric conditions and dust accumulation (and removal) on the panels limits the accurate prediction of array power to short time spans. Based on the above, it is clear that long term power predictions are not sufficiently accurate to allow for detailed long term planning. Instead, the power assessment is essentially a daily activity, effectively resetting the boundary points for the overall predictive power model. A typical analysis begins with the importing of the telemetry from each rover's previous day's power subsystem activities. This includes the array power generated, battery state-of-charge, rover power loads, and rover orientation, all as functions of time. The predicted performance for that day is compared to the actual performance to identify the extent of any differences. The model is then corrected for these changes. Details of JPL's MER power analysis procedure are presented, including the description of steps needed to provide the final prediction for the mission planners. A dust cleaning event of the solar array is also highlighted to illustrate the impact of Martian weather on solar array performance

Glasgow prognostic score is superior to other inflammation-based scores in predicting survival of diffuse large B-cell lymphoma

PubMed Central

Wei, Xiaolei; Zhou, Lizhi; Wei, Qi; Zhang, Yuankun; Huang, Weimin; Feng, Ru

2017-01-01

Inflammation-based prognostic scores, such as the glasgow prognostic score (GPS), prognostic index (PI), prognostic nutritional index (PNI), neutrophil lymphocyte ratio (NLR) and platelet lymphocyte ratio (PLR) were related to survival in many solid tumors. Recent study showed that GPS can be used to predict outcome in diffuse large B-cell lymphoma (DLBCL). However, other inflammation related scores had not been reported and it also remained unknown which of them was the most useful to evaluate the survival in DLBCLs. In this retrospective study, a number of 252 newly diagnosed and histologically proven DLBCLs from January 2003 to December 2014 were included. The high GPS, high PI, high NLR, high PLR and low PNI were all associated with poor overall survival (p < 0.05) and event-free survival (p < 0.05) in univariate analysis. Multivariate analysis indicated that GPS (HR = 1.781, 95% CI = 1.065–2.979, p = 0.028) remained an independent prognostic predictor in DLBCL. The c-index of GPS (0.735, 95% CI = 0.645–0.824) was greater than that of PI (0.710, 95% CI = 0.621–0.799, p = 0.602), PNI (0.600, 95% CI = 0.517–0.683, p = 0.001), PLR (0.599, 95% CI = 0.510–0.689, p = 0.029) and NLR (0.572, 95% CI = 0.503–0.642, p = 0.005) by Harrell's concordance index. Especially in DLBCLs treated with R-CHOP, GPS still remained the most powerful prognostic score when comparing with others (p = 0.001 and p < 0.001, respectively for OS and EFS). In conclusion, it is indicated that inflammation-based prognostic scores such as GPS, PI, NLR, PNI and PLR all could be used to predict the outcome of DLBCLs. Among them, GPS is the most powerful indicator in predicting survival in DLBCLs, even in the rituximab era. PMID:29100345

A Comparison of Systemic Inflammation-Based Prognostic Scores in Patients on Regular Hemodialysis

PubMed Central

Kato, Akihiko; Tsuji, Takayuki; Sakao, Yukitoshi; Ohashi, Naro; Yasuda, Hideo; Fujimoto, Taiki; Takita, Takako; Furuhashi, Mitsuyoshi; Kumagai, Hiromichi

2013-01-01

Background/Aims Systemic inflammation-based prognostic scores have prognostic power in patients with cancer, independently of tumor stage and site. Although inflammatory status is associated with mortality in hemodialysis (HD) patients, it remains to be determined as to whether these composite scores are useful in predicting clinical outcomes. Methods We calculated the 6 prognostic scores [Glasgow prognostic score (GPS), modified GPS (mGPS), neutrophil-lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), prognostic index (PI) and prognostic nutritional index (PNI), which have been established as a useful scoring system in cancer patients. We enrolled 339 patients on regular HD (age: 64 ± 13 years; time on HD: 129 ± 114 months; males/females = 253/85) and followed them for 42 months. The area under the receiver-operating characteristics curve was used to determine which scoring system was more predictive of mortality. Results Elevated GPS, mGPS, NLR, PLR, PI and PNI were all associated with total mortality, independent of covariates. If GPS was raised, mGPS, NLR, PLR and PI were also predictive of all-cause mortality and/or hospitalization. GPS and PNI were associated with poor nutritional status. Using overall mortality as an endpoint, the area under the curve (AUC) was significant for a GPS of 0.701 (95% CI: 0.637-0.765; p < 0.01) and for a PNI of 0.616 (95% CI: 0.553-0.768; p = 0.01). However, AUC for hypoalbuminemia (<3.5 g/dl) was comparable to that of GPS (0.695, 95% CI: 0.632-0.759; p < 0.01). Conclusion GPS, based on serum albumin and highly sensitive C-reactive protein, has the most prognostic power for mortality prediction among the prognostic scores in HD patients. However, as the determination of serum albumin reflects mortality similarly to GPS, other composite combinations are needed to provide additional clinical utility beyond that of albumin alone in HD patients. PMID:24403910

Variable Selection for Regression Models of Percentile Flows

NASA Astrophysics Data System (ADS)

Fouad, G.

2017-12-01

Percentile flows describe the flow magnitude equaled or exceeded for a given percent of time, and are widely used in water resource management. However, these statistics are normally unavailable since most basins are ungauged. Percentile flows of ungauged basins are often predicted using regression models based on readily observable basin characteristics, such as mean elevation. The number of these independent variables is too large to evaluate all possible models. A subset of models is typically evaluated using automatic procedures, like stepwise regression. This ignores a large variety of methods from the field of feature (variable) selection and physical understanding of percentile flows. A study of 918 basins in the United States was conducted to compare an automatic regression procedure to the following variable selection methods: (1) principal component analysis, (2) correlation analysis, (3) random forests, (4) genetic programming, (5) Bayesian networks, and (6) physical understanding. The automatic regression procedure only performed better than principal component analysis. Poor performance of the regression procedure was due to a commonly used filter for multicollinearity, which rejected the strongest models because they had cross-correlated independent variables. Multicollinearity did not decrease model performance in validation because of a representative set of calibration basins. Variable selection methods based strictly on predictive power (numbers 2-5 from above) performed similarly, likely indicating a limit to the predictive power of the variables. Similar performance was also reached using variables selected based on physical understanding, a finding that substantiates recent calls to emphasize physical understanding in modeling for predictions in ungauged basins. The strongest variables highlighted the importance of geology and land cover, whereas widely used topographic variables were the weakest predictors. Variables suffered from a high degree of multicollinearity, possibly illustrating the co-evolution of climatic and physiographic conditions. Given the ineffectiveness of many variables used here, future work should develop new variables that target specific processes associated with percentile flows.

NASA's Prediction Of Worldwide Energy Resource (POWER) Project Unveils a New Geospatial Data Portal

Atmospheric Science Data Center

2018-03-16

NASA's Prediction Of Worldwide Energy Resource (POWER) Project Unveils a New Geospatial Data Portal ... current POWER home page. The new POWER will include improved solar and meteorological data with all parameters available on a 0.5-degree ...

Barkhausen noise in FeCoB amorphous alloys (abstract)

NASA Astrophysics Data System (ADS)

Durin, G.; Bertotti, G.

1996-04-01

In recent years, the Barkhausen effect has been indicated as a promising tool to investigate and verify the ideas about the self-organization of physical complex systems displaying power law distributions and 1/f noise. When measured at low magnetization rates, the Barkhausen signal displays 1/fα-type spectra (with α=1.5÷2) and power law distributions of duration and size of the Barkhausen jumps. These experimental data are quite well described by the model of Alessandro et al. which is based on a stochastic description of the domain wall dynamics over a pinning field with brownian properties. Yet, this model always predicts a 1/f 2 spectrum, and, at the moment, it is not clear if it can take into account possible effects of self-organization of the magnetization process. In order to improve the power of the model and clarify this problem, we have performed a thorough investigation of the noise spectra and the amplitude distributions of a wide set of FeCoB amorphous alloys. The stationary amplitude distribution of the signal is very well fitted by the gamma distribution P(ν)=νc-1 exp(-ν)/Γ(c), where ν is proportional to the domain wall velocity, and c is a dimensionless parameter. As predicted in Ref. , this parameter is found to have a parabolic dependence on the magnetization rate. In particular, the linear coefficient is related to the amplitude of the fluctuations of the pinning field, a parameter which can be measured directly from the power spectra. In all measured cases, the power spectra show α exponents less than 2, and thus poorly fitted by the model. Actually, the absolute value of the high frequency spectral density is not consistent with the c parameter determined from the amplitude distribution data. This discrepancy requires to introduce effects not taken into account in the model, as the propagation of the jumps along the domain wall. This highly enhances the fit of the data and indicates effects of propagation on the scale of a few millimeters. These results are analyzed in terms of new descriptions of the statistical properties of the pinning field based on fractional brownian processes.

Communal and Agentic Interpersonal and Intergroup Motives Predict Preferences for Status Versus Power.

PubMed

Locke, Kenneth D; Heller, Sonja

2017-01-01

Seven studies involving 1,343 participants showed how circumplex models of social motives can help explain individual differences in preferences for status (having others' admiration) versus power (controlling valuable resources). Studies 1 to 3 and 7 concerned interpersonal motives in workplace contexts, and found that stronger communal motives (to have mutual trust, support, and cooperation) predicted being more attracted to status (but not power) and achieving more workplace status, while stronger agentic motives (to be firm, decisive, and influential) predicted being more attracted to and achieving more workplace power, and experiencing a stronger connection between workplace power and job satisfaction. Studies 4 to 6 found similar effects for intergroup motives: Stronger communal motives predicted wanting one's ingroup (e.g., country) to have status-but not power-relative to other groups. Finally, most people preferred status over power, and this was especially true for women, which was partially explained by women having stronger communal motives.

Factors associated with poor sleep during menopause: results from the Midlife Women's Health Study.

PubMed

Smith, Rebecca L; Flaws, Jodi A; Mahoney, Megan M

2018-05-01

Poor sleep is one of the most common problems reported during menopause, and is known to vary throughout the menopause transition. The objective of this study was to describe the dynamics of poor sleep among participants of the Midlife Women's Health Study and to identify risk factors associated with poor sleep during the menopausal transition. Annual responses to surveys that included questions about the frequency of sleep disturbances and insomnia were analyzed to determine the likelihood of persistent poor sleep throughout the menopausal transition and the correlation of responses to the different sleep-related questions, including frequency of restless sleep during the first year of the study. Responses to questions about a large number of potential risk factors were used to identify risk factors for poor sleep. Poor sleep in premenopause was not predictive of poor sleep in perimenopause, and poor sleep in perimenopause was not predictive of poor sleep in postmenopause. Frequencies of each of the measures of poor sleep were highly correlated. For all sleep outcomes, high frequency of depression was related to a high frequency of poor sleep. Vasomotor symptoms were also significantly related with a higher frequency of all poor sleep outcomes. A history of smoking was also associated with higher frequencies of insomnia and sleep disturbances. The risk factors identified for poor sleep, depression and vasomotor symptoms, were consistently associated with poor sleep throughout the menopausal transition. The likelihood of these risk factors changed from premenopause, through perimenopause, and into postmenopause, however, which could explain changes in sleep difficulties across the menopausal transition. Treatment of these risk factors should be considered when addressing sleep difficulties in menopausal women. Copyright © 2018 Elsevier B.V. All rights reserved.

The predictive power of local properties of financial networks

NASA Astrophysics Data System (ADS)

Caraiani, Petre

2017-01-01

The literature on analyzing the dynamics of financial networks has focused so far on the predictive power of global measures of networks like entropy or index cohesive force. In this paper, I show that the local network properties have similar predictive power. I focus on key network measures like average path length, average degree or cluster coefficient, and also consider the diameter and the s-metric. Using Granger causality tests, I show that some of these measures have statistically significant prediction power with respect to the dynamics of aggregate stock market. Average path length is most robust relative to the frequency of data used or specification (index or growth rate). Most measures are found to have predictive power only for monthly frequency. Further evidences that support this view are provided through a simple regression model.

Interactive contributions of self-regulation deficits and social motivation to psychopathology: Unraveling divergent pathways to aggressive behavior and depressive symptoms

PubMed Central

RUDOLPH, KAREN D.; TROOP-GORDON, WENDY; LLEWELLYN, NICOLE

2015-01-01

Poor self-regulation has been implicated as a significant risk factor for the development of multiple forms of psychopathology. This research examined the proposition that self-regulation deficits differentially predict aggressive behavior and depressive symptoms, depending on children’s social approach versus avoidance motivation. A prospective, multiple-informant approach was used to test this hypothesis in 419 children (M age = 8.92, SD = 0.36). Parents rated children’s inhibitory control. Children completed measures of social approach–avoidance motivation and depressive symptoms. Teachers rated children’s aggressive behavior. As anticipated, poor inhibitory control predicted aggressive behavior in boys with high but not low approach motivation and low but not high avoidance motivation, whereas poor inhibitory control predicted depressive symptoms in girls with high but not low avoidance motivation. This research supports several complementary theoretical models of psychopathology and provides insight into the differential contributions of poor self-regulation to maladaptive developmental outcomes. The findings suggest the need for targeted intervention programs that consider heterogeneity among children with self-regulatory deficits. PMID:23627953

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.

Magnetic resonance spectroscopy metabolite profiles predict survival in paediatric brain tumours.

PubMed

Wilson, Martin; Cummins, Carole L; Macpherson, Lesley; Sun, Yu; Natarajan, Kal; Grundy, Richard G; Arvanitis, Theodoros N; Kauppinen, Risto A; Peet, Andrew C

2013-01-01

Brain tumours cause the highest mortality and morbidity rate of all childhood tumour groups and new methods are required to improve clinical management. (1)H magnetic resonance spectroscopy (MRS) allows non-invasive concentration measurements of small molecules present in tumour tissue, providing clinically useful imaging biomarkers. The primary aim of this study was to investigate whether MRS detectable molecules can predict the survival of paediatric brain tumour patients. Short echo time (30ms) single voxel (1)H MRS was performed on children attending Birmingham Children's Hospital with a suspected brain tumour and 115 patients were included in the survival analysis. Patients were followed-up for a median period of 35 months and Cox-Regression was used to establish the prognostic value of individual MRS detectable molecules. A multivariate model of survival was also investigated to improve prognostic power. Lipids and scyllo-inositol predicted poor survival whilst glutamine and N-acetyl aspartate predicted improved survival (p<0.05). A multivariate model of survival based on three MRS biomarkers predicted survival with a similar accuracy to histologic grading (p<5e-5). A negative correlation between lipids and glutamine was found, suggesting a functional link between these molecules. MRS detectable biomolecules have been identified that predict survival of paediatric brain tumour patients across a range of tumour types. The evaluation of these biomarkers in large prospective studies of specific tumour types should be undertaken. The correlation between lipids and glutamine provides new insight into paediatric brain tumour metabolism that may present novel targets for therapy. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

PubMed

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

2009-02-01

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

Living in contained environments: Research implications from undersea habitats. [undersea habitats

NASA Technical Reports Server (NTRS)

Helmreich, Robert L.

1986-01-01

A cost-reward model is used to frame a discussion of differences in observed behavior of individuals and groups in confined environments. It has been observed that the high cost of functioning in a stressful environment is likely to produce poor performance when anticipated rewards are low but that participants can manage the stress and achieve high performance if they anticipate high rewards. The high-reward environment is exemplified by early undersea habitats such as Sealab and Tektite and by early space missions. Other aspects of behavior occur in all confined environments and point to an important area for future research. Of particular interest are intergroup conflicts arising between the confined group and its external control. Also, individual differences in personality seem always to have an impact in confined environments. Recent research has focused on: (1) predicting performance and adjustment based on instrumental and expressive aspects of the self; (2) the differential predictive power of achievement striving and irritation/irritability in Type A personalities; and (3) the nature and role of leadership in small, isolated groups.

Perspectives on Molecular Biomarkers of Oxidative Stress and Antioxidant Strategies in Traumatic Brain Injury

PubMed Central

Mendes Arent, André; de Souza, Luiz Felipe; Walz, Roger; Dafre, Alcir Luiz

2014-01-01

Traumatic brain injury (TBI) is frequently associated with abnormal blood-brain barrier function, resulting in the release of factors that can be used as molecular biomarkers of TBI, among them GFAP, UCH-L1, S100B, and NSE. Although many experimental studies have been conducted, clinical consolidation of these biomarkers is still needed to increase the predictive power and reduce the poor outcome of TBI. Interestingly, several of these TBI biomarkers are oxidatively modified to carbonyl groups, indicating that markers of oxidative stress could be of predictive value for the selection of therapeutic strategies. Some drugs such as corticosteroids and progesterone have already been investigated in TBI neuroprotection but failed to demonstrate clinical applicability in advanced phases of the studies. Dietary antioxidants, such as curcumin, resveratrol, and sulforaphane, have been shown to attenuate TBI-induced damage in preclinical studies. These dietary antioxidants can increase antioxidant defenses via transcriptional activation of NRF2 and are also known as carbonyl scavengers, two potential mechanisms for neuroprotection. This paper reviews the relevance of redox biology in TBI, highlighting perspectives for future studies. PMID:24689052

Quality of life of French Canadian parents raising a child with autism spectrum disorder and effects of psychosocial factors.

PubMed

Cappe, Émilie; Poirier, Nathalie; Sankey, Carol; Belzil, Andréa; Dionne, Carmen

2018-04-01

This study aimed to investigate the quality of life of parents of a child with autism spectrum disorder in Quebec. Seventy-seven participants completed a questionnaire with socio-biographic information and five self-assessed scales, to measure perceived stress, social support and control, coping strategies, and quality of life. Perception of their child's autonomy level, of the severity of the disorder, of the family's income, as well as changes in their professional or familial organization influenced parents' quality of life. Perceiving their situation as a threat predicted poor quality of life, whereas satisfaction of social support predicted good quality of life. In addition, parents who used problem solving and support-seeking coping strategies had a better relationship with their child, whereas those who used more emotion-centered coping strategies struggled. Lastly, parents who felt they had the power to contribute to their child's development were more satisfied and less disturbed. Beyond the parents' actual situation, our results underscore the importance of paying attention to their own perception of the situation in order to provide them with appropriate support.

Silicon Heat Pipe Array

NASA Technical Reports Server (NTRS)

Yee, Karl Y.; Ganapathi, Gani B.; Sunada, Eric T.; Bae, Youngsam; Miller, Jennifer R.; Beinsford, Daniel F.

2013-01-01

Improved methods of heat dissipation are required for modern, high-power density electronic systems. As increased functionality is progressively compacted into decreasing volumes, this need will be exacerbated. High-performance chip power is predicted to increase monotonically and rapidly with time. Systems utilizing these chips are currently reliant upon decades of old cooling technology. Heat pipes offer a solution to this problem. Heat pipes are passive, self-contained, two-phase heat dissipation devices. Heat conducted into the device through a wick structure converts the working fluid into a vapor, which then releases the heat via condensation after being transported away from the heat source. Heat pipes have high thermal conductivities, are inexpensive, and have been utilized in previous space missions. However, the cylindrical geometry of commercial heat pipes is a poor fit to the planar geometries of microelectronic assemblies, the copper that commercial heat pipes are typically constructed of is a poor CTE (coefficient of thermal expansion) match to the semiconductor die utilized in these assemblies, and the functionality and reliability of heat pipes in general is strongly dependent on the orientation of the assembly with respect to the gravity vector. What is needed is a planar, semiconductor-based heat pipe array that can be used for cooling of generic MCM (multichip module) assemblies that can also function in all orientations. Such a structure would not only have applications in the cooling of space electronics, but would have commercial applications as well (e.g. cooling of microprocessors and high-power laser diodes). This technology is an improvement over existing heat pipe designs due to the finer porosity of the wick, which enhances capillary pumping pressure, resulting in greater effective thermal conductivity and performance in any orientation with respect to the gravity vector. In addition, it is constructed of silicon, and thus is better suited for the cooling of semiconductor devices.

Conditional power and predictive power based on right censored data with supplementary auxiliary information.

PubMed

Sun, Libo; Wan, Ying

2018-04-22

Conditional power and predictive power provide estimates of the probability of success at the end of the trial based on the information from the interim analysis. The observed value of the time to event endpoint at the interim analysis could be biased for the true treatment effect due to early censoring, leading to a biased estimate of conditional power and predictive power. In such cases, the estimates and inference for this right censored primary endpoint are enhanced by incorporating a fully observed auxiliary variable. We assume a bivariate normal distribution of the transformed primary variable and a correlated auxiliary variable. Simulation studies are conducted that not only shows enhanced conditional power and predictive power but also can provide the framework for a more efficient futility interim analysis in terms of an improved accuracy in estimator, a smaller inflation in type II error and an optimal timing for such analysis. We also illustrated the new approach by a real clinical trial example. Copyright © 2018 John Wiley & Sons, Ltd.

The predictive power of Japanese candlestick charting in Chinese stock market

NASA Astrophysics Data System (ADS)

Chen, Shi; Bao, Si; Zhou, Yu

2016-09-01

This paper studies the predictive power of 4 popular pairs of two-day bullish and bearish Japanese candlestick patterns in Chinese stock market. Based on Morris' study, we give the quantitative details of definition of long candlestick, which is important in two-day candlestick pattern recognition but ignored by several previous researches, and we further give the quantitative definitions of these four pairs of two-day candlestick patterns. To test the predictive power of candlestick patterns on short-term price movement, we propose the definition of daily average return to alleviate the impact of correlation among stocks' overlap-time returns in statistical tests. To show the robustness of our result, two methods of trend definition are used for both the medium-market-value and large-market-value sample sets. We use Step-SPA test to correct for data snooping bias. Statistical results show that the predictive power differs from pattern to pattern, three of the eight patterns provide both short-term and relatively long-term prediction, another one pair only provide significant forecasting power within very short-term period, while the rest three patterns present contradictory results for different market value groups. For all the four pairs, the predictive power drops as predicting time increases, and forecasting power is stronger for stocks with medium market value than those with large market value.

The prediction of the impact of climatic factors on short-term electric power load based on the big data of smart city

NASA Astrophysics Data System (ADS)

Qiu, Yunfei; Li, Xizhong; Zheng, Wei; Hu, Qinghe; Wei, Zhanmeng; Yue, Yaqin

2017-08-01

The climate changes have great impact on the residents’ electricity consumption, so the study on the impact of climatic factors on electric power load is of significance. In this paper, the effects of the data of temperature, rainfall and wind of smart city on short-term power load is studied to predict power load. The authors studied the relation between power load and daily temperature, rainfall and wind in the 31 days of January of one year. In the research, the authors used the Matlab neural network toolbox to establish the combinational forecasting model. The authors trained the original input data continuously to get the internal rules inside the data and used the rules to predict the daily power load in the next January. The prediction method relies on the accuracy of weather forecasting. If the weather forecasting is different from the actual weather, we need to correct the climatic factors to ensure accurate prediction.

Evaluating Upper-Body Strength and Power From a Single Test: The Ballistic Push-up.

PubMed

Wang, Ran; Hoffman, Jay R; Sadres, Eliahu; Bartolomei, Sandro; Muddle, Tyler W D; Fukuda, David H; Stout, Jeffrey R

2017-05-01

Wang, R, Hoffman, JR, Sadres, E, Bartolomei, S, Muddle, TWD, Fukuda, DH, and Stout, JR. Evaluating upper-body strength and power from a single test: the ballistic push-up. J Strength Cond Res 31(5): 1338-1345, 2017-The purpose of this study was to examine the reliability of the ballistic push-up (BPU) exercise and to develop a prediction model for both maximal strength (1 repetition maximum [1RM]) in the bench press exercise and upper-body power. Sixty recreationally active men completed a 1RM bench press and 2 BPU assessments in 3 separate testing sessions. Peak and mean force, peak and mean rate of force development, net impulse, peak velocity, flight time, and peak and mean power were determined. Intraclass correlation coefficients were used to examine the reliability of the BPU. Stepwise linear regression was used to develop 1RM bench press and power prediction equations. Intraclass correlation coefficient's ranged from 0.849 to 0.971 for the BPU measurements. Multiple regression analysis provided the following 1RM bench press prediction equation: 1RM = 0.31 × Mean Force - 1.64 × Body Mass + 0.70 (R = 0.837, standard error of the estimate [SEE] = 11 kg); time-based power prediction equation: Peak Power = 11.0 × Body Mass + 2012.3 × Flight Time - 338.0 (R = 0.658, SEE = 150 W), Mean Power = 6.7 × Body Mass + 1004.4 × Flight Time - 224.6 (R = 0.664, SEE = 82 W); and velocity-based power prediction equation: Peak Power = 8.1 × Body Mass + 818.6 × Peak Velocity - 762.0 (R = 0.797, SEE = 115 W); Mean Power = 5.2 × Body Mass + 435.9 × Peak Velocity - 467.7 (R = 0.838, SEE = 57 W). The BPU is a reliable test for both upper-body strength and power. Results indicate that the mean force generated from the BPU can be used to predict 1RM bench press, whereas peak velocity and flight time measured during the BPU can be used to predict upper-body power. These findings support the potential use of the BPU as a valid method to evaluate upper-body strength and power.

The GRB-SLSN connection: misaligned magnetars, weak jet emergence, and observational signatures

NASA Astrophysics Data System (ADS)

Margalit, Ben; Metzger, Brian D.; Thompson, Todd A.; Nicholl, Matt; Sukhbold, Tuguldur

2018-04-01

Multiple lines of evidence support a connection between hydrogen-poor superluminous supernovae (SLSNe) and long-duration gamma-ray bursts (GRBs). Both classes of events require a powerful central energy source, usually attributed to a millisecond magnetar or an accreting black hole. The GRB-SLSN link raises several theoretical questions: What distinguishes the engines responsible for these different phenomena? Can a single engine power both a GRB and a luminous SN in the same event? We propose a unifying model for magnetar thermalization and jet formation: misalignment between the rotation (Ω) and magnetic dipole (μ) axes dissipates a fraction of the spin-down power by reconnection in the striped equatorial wind, providing a guaranteed source of `thermal' emission to power the supernova. The remaining unthermalized power energizes a relativistic jet. We show that even weak relativistic jets of luminosity ˜1046 erg s-1 can escape the expanding SN ejecta implying that escaping relativistic jets may accompany many SLSNe. We calculate the observational signature of these jets. We show that they may produce transient ultraviolet (UV) cocoon emission lasting a few hours when the jet breaks out of the ejecta surface. A longer lived optical/UV signal may originate from a mildly relativistic wind driven from the interface between the jet and the ejecta walls, which could explain the secondary early-time maximum observed in some SLSNe light curves, such as LSQ14bdq. Our scenario predicts a population of GRB from on-axis jets with extremely long durations, potentially similar to the population of `jetted-tidal disruption events', in coincidence with a small subset of SLSNe.

EEG power as a biomarker to predict the outcome after cardiac arrest and cardiopulmonary resuscitation induced global ischemia.

PubMed

Weitzel, Lindsay-Rae; Sampath, Dayalan; Shimizu, Kaori; White, Andrew M; Herson, Paco S; Raol, Yogendra H

2016-11-15

Cardiac arrest (CA) is a major cause of mortality and survivors often develop neurologic deficits. The objective of this study was to determine the effect of CA and cardiopulmonary resuscitation (CPR) in mice on the EEG and neurologic outcomes, and identify biomarkers that can prognosticate poor outcomes. Video-EEG records were obtained at various periods following CA-CPR and examined manually to determine the presence of spikes and sharp-waves, and seizures. EEG power was calculated using a fast Fourier transform (FFT) algorithm. Fifty percent mice died within 72h following CA and successful CPR. Universal suppression of the background EEG was observed in all mice following CA-CPR, however, a more severe and sustained reduction in EEG power occurred in the mice that did not survive beyond 72h than those that survived until sacrificed. Spikes and sharp wave activity appeared in the cortex and hippocampus of all mice, but only one out of eight mice developed a purely electrographic seizure in the acute period after CA-CPR. Interestingly, none of the mice that died experienced any acute seizures. At 10days after the CA-CPR, 25% of the mice developed spontaneous convulsive and nonconvulsive seizures that remained restricted to the hippocampus. The frequency of nonconvulsive seizures was higher than that of convulsive seizures. A strong association between changes in EEG power and mortality following CA-CPR were observed in our study. Therefore, we suggest that the EEG power can be used to prognosticate mortality following CA-CPR induced global ischemia. Copyright © 2016 Elsevier Inc. All rights reserved.

Forest soil chemistry and terrain attributes in a Catskills watershed

USGS Publications Warehouse

Johnson, C.E.; Ruiz-Mendez, J. J.; Lawrence, G.B.

2000-01-01

Knowledge of soil chemistry is useful in assessing the sensitivity of forested areas to natural and anthropogenic disturbances, but characterizing large areas is expensive because of the large sample numbers required and the cost of soil chemical analyses. We collected and chemically analyzed soil samples from 72 sites within a 214-ha watershed in the Catskill Mountains of New York to evaluate factors that influence soil chemistry and whether terrain features could be used to predict soil chemical properties. Using geographic information system (GIS) techniques, we determined five terrain attributes at each sampling location: (i) slope, (ii) aspect, (iii) elevation, (iv) topographic index, and (v) flow accumulation. These attributes were ineffective in predicting the chemical properties of organic and mineral soil samples; together they explained only 4 to 25% of the variance in pH(w), effective cation-exchange capacity (CEC(e)), exchangeable bases, exchangeable acidity, total C, total N, and C/N ratio. Regressions among soil properties were much better; total C and pH(w) together explained 33 to 66% of the variation in exchangeable bases and CEC(e). Total C was positively correlated with N (r = 0.91 and 0.96 in Oa horizons and mineral soil, respectively), exchangeable bases (r = 0.65, 0.76), and CEC(e) (r = 0.54, 0.44), indicating the importance of organic matter to the chemistry of these acidic soils. The fraction of CEC(e) occupied by H explained 44% of the variation in pH(w). Soil chemical properties at this site vary on spatial scales finer than typical GIS analyses, resulting in relationships with poor predictive power. Thus, interrelationships among soil properties are more reliable for prediction.Knowledge of soil chemistry is useful in assessing the sensitivity of forested areas to natural and anthropogenic disturbances, but characterizing large areas is expensive because of the large sample numbers required and the cost of soil chemical analyses. We collected and chemically analyzed soil samples from 72 sites within a 214-ha watershed in the Catskill Mountains of New York to evaluate factors that influence soil chemistry and whether terrain features could be used to predict soil chemical properties. Using geographic information system (GIS) techniques, we determined five terrain attributes at each sampling location: (i) slope, (ii) aspect, (iii) elevation, (iv) topographic index, and (v) flow accumulation. These attributes were ineffective in predicting the chemical properties of organic and mineral soil samples; together they explained only 4 to 25% of the variance in pHw, effective cation-exchange capacity (CECe), exchangeable bases, exchangeable acidity, total C, total N, and C/N ratio. Regressions among soil properties were much better; total C and pHw together explained 33 to 66% of the variation in exchangeable bases and CECe. Total C was positively correlated with N (r = 0.91 and 0.96 in Oa horizons and mineral soil, respectively), exchangeable bases (r = 0.65, 0.76), and CECe (r = 0.54, 0.44), indicating the importance of organic matter to the chemistry of these acidic soils. The fraction of CECe occupied by H explained 44% of the variation in pHw. Soil chemical properties at this site vary on spatial scales finer than typical GIS analyses, resulting in relationships with poor predictive power. Thus, interrelationships among soil properties are more reliable for prediction.

Poor People, Black Faces: The Portrayal of Poverty in Economics Textbooks.

ERIC Educational Resources Information Center

Clawson, Rosalee A.

2002-01-01

Examined the portrayal of poverty in economics textbooks, investigating whether poverty would be predicted as a black problem. Results found evidence that black faces were overwhelmingly portrayed among the contemporary poor, yet Blacks were not portrayed among the Great Depression era poor and nor were they used to illustrate the popular Social…

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

Thermal niche estimators and the capability of poor dispersal species to cope with climate change

NASA Astrophysics Data System (ADS)

Sánchez-Fernández, David; Rizzo, Valeria; Cieslak, Alexandra; Faille, Arnaud; Fresneda, Javier; Ribera, Ignacio

2016-03-01

For management strategies in the context of global warming, accurate predictions of species response are mandatory. However, to date most predictions are based on niche (bioclimatic) models that usually overlook biotic interactions, behavioral adjustments or adaptive evolution, and assume that species can disperse freely without constraints. The deep subterranean environment minimises these uncertainties, as it is simple, homogeneous and with constant environmental conditions. It is thus an ideal model system to study the effect of global change in species with poor dispersal capabilities. We assess the potential fate of a lineage of troglobitic beetles under global change predictions using different approaches to estimate their thermal niche: bioclimatic models, rates of thermal niche change estimated from a molecular phylogeny, and data from physiological studies. Using bioclimatic models, at most 60% of the species were predicted to have suitable conditions in 2080. Considering the rates of thermal niche change did not improve this prediction. However, physiological data suggest that subterranean species have a broad thermal tolerance, allowing them to stand temperatures never experienced through their evolutionary history. These results stress the need of experimental approaches to assess the capability of poor dispersal species to cope with temperatures outside those they currently experience.

Cardiovascular Risk Stratification in Patients with Metabolic Syndrome Without Diabetes or Cardiovascular Disease: Usefulness of Metabolic Syndrome Severity Score.

PubMed

Masson, Walter; Epstein, Teo; Huerín, Melina; Lobo, Lorenzo Martín; Molinero, Graciela; Angel, Adriana; Masson, Gerardo; Millán, Diana; De Francesca, Salvador; Vitagliano, Laura; Cafferata, Alberto; Losada, Pablo

2017-09-01

The estimated cardiovascular risk determined by the different risk scores, could be heterogeneous in patients with metabolic syndrome without diabetes or vascular disease. This risk stratification could be improved by detecting subclinical carotid atheromatosis. To estimate the cardiovascular risk measured by different scores in patients with metabolic syndrome and analyze its association with the presence of carotid plaque. Non-diabetic patients with metabolic syndrome (Adult Treatment Panel III definition) without cardiovascular disease were enrolled. The Framingham score, the Reynolds score, the new score proposed by the 2013 ACC/AHA Guidelines and the Metabolic Syndrome Severity Calculator were calculated. Prevalence of carotid plaque was determined by ultrasound examination. A Receiver Operating Characteristic analysis was performed. A total of 238 patients were enrolled. Most patients were stratified as "low risk" by Framingham score (64%) and Reynolds score (70.1%). Using the 2013 ACC/AHA score, 45.3% of the population had a risk ≥7.5%. A significant correlation was found between classic scores but the agreement (concordance) was moderate. The correlation between classical scores and the Metabolic Syndrome Severity Calculator was poor. Overall, the prevalence of carotid plaque was 28.2%. The continuous metabolic syndrome score used in our study showed a good predictive power to detect carotid plaque (area under the curve 0.752). In this population, the calculated cardiovascular risk was heterogenic. The prevalence of carotid plaque was high. The Metabolic Syndrome Severity Calculator showed a good predictive power to detect carotid plaque.

Good phonetic errors in poor spellers are associated with right-handedness and possible weak utilisation of visuospatial abilities.

PubMed

Eglinton, Elizabeth; Annett, Marian

2008-06-01

Poor spellers in normal schools, who were not poor readers, were studied for handedness, visuospatial and other cognitive abilities in order to explore contrasts between poor spellers with and without good phonology. It was predicted by the right shift (RS) theory of handedness and cerebral dominance that those with good phonology would have strong bias to dextrality and relative weakness of the right hemisphere, while those without good phonology would have reduced bias to dextrality and relative weakness of the left hemisphere. Poor spellers with good phonetic equivalent spelling errors (GFEs) included fewer left-handers (2.4%) than poor spellers without GFEs (24.4%). Differences for hand skill were as predicted. Tests of visuospatial processing found no differences between the groups in levels of ability, but there was a marked difference in pattern of correlations between visuospatial test scores and homophonic word discrimination. Whereas good spellers (GS) and poor spellers without GFEs showed positive correlations between word discrimination and visuospatial ability, there were no significant correlations for poor spellers with GFEs. The differences for handedness and possibly for the utilisation of visuospatial skills suggest that surface dyslexics differ from phonological dyslexics in cerebral specialisation and perhaps in the quality of inter-hemispheric relations.

Formulation of poorly water-soluble Gemfibrozil applying power ultrasound.

PubMed

Ambrus, R; Naghipour Amirzadi, N; Aigner, Z; Szabó-Révész, P

2012-03-01

The dissolution properties of a drug and its release from the dosage form have a basic impact on its bioavailability. Solubility problems are a major challenge for the pharmaceutical industry as concerns the development of new pharmaceutical products. Formulation problems may possibly be overcome by modification of particle size and morphology. The application of power ultrasound is a novel possibility in drug formulation. This article reports on solvent diffusion and melt emulsification, as new methods supplemented with drying in the field of sonocrystallization of poorly water-soluble Gemfibrozil. During thermoanalytical characterization, a modified structure was detected. The specific surface area of the drug was increased following particle size reduction and the poor wettability properties could also be improved. The dissolution rate was therefore significantly increased. Copyright © 2011 Elsevier B.V. All rights reserved.

Action Imitation at 1.5 Years Is Better than Pointing Gesture in Predicting Late Development of Language Production at 3 Years of Age

ERIC Educational Resources Information Center

Zambrana, Imac M.; Ystrom, Eivind; Schjolberg, Synnve; Pons, Francisco

2013-01-01

This study examined whether poor pointing gestures and imitative actions at 18 months of age uniquely predicted late language production at 36 months, beyond the role of poor language at 18 months of age. Data from the Norwegian Mother and Child Cohort Study were utilized. Maternal reports of the children's nonverbal skills and language were…

Utilization of Model Predictive Control to Balance Power Absorption Against Load Accumulation

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

Abbas, Nikhar; Tom, Nathan M

2017-06-03

Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalmanmore » filter and autoregressive model to evaluate model predictive control performance.« less

Utilization of Model Predictive Control to Balance Power Absorption Against Load Accumulation: Preprint

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

Abbas, Nikhar; Tom, Nathan

Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalmanmore » filter and autoregressive model to evaluate model predictive control performance.« less

Relationship between catheter contact force and radiofrequency lesion size and incidence of steam pop in the beating canine heart: electrogram amplitude, impedance, and electrode temperature are poor predictors of electrode-tissue contact force and lesion size.

PubMed

Ikeda, Atsushi; Nakagawa, Hiroshi; Lambert, Hendrik; Shah, Dipen C; Fonck, Edouard; Yulzari, Aude; Sharma, Tushar; Pitha, Jan V; Lazzara, Ralph; Jackman, Warren M

2014-12-01

Electrode-tissue contact force (CF) is believed to be a major factor in radiofrequency lesion size. The purpose of this study was to determine, in the beating canine heart, the relationship between CF and radiofrequency lesion size and the accuracy of predicting CF and lesion size by measuring electrogram amplitude, impedance, and electrode temperature. Eight dogs were studied closed chest. Using a 7F catheter with a 3.5 mm irrigated electrode and CF sensor (TactiCath, St. Jude Medical), radiofrequency applications were delivered to 3 separate sites in the right ventricle (30 W, 60 seconds, 17 mL/min irrigation) and 3 sites in the left ventricle (40 W, 60 seconds, 30 mL/min irrigation) at (1) low CF (median 8 g); (2) moderate CF (median 21 g); and (3) high CF (median 60 g). Dogs were euthanized and lesion size was measured. At constant radiofrequency and time, lesion size increased significantly with increasing CF (P<0.01). The incidence of a steam pop increased with both increasing CF and higher power. Peak electrode temperature correlated poorly with lesion size. The decrease in impedance during the radiofrequency application correlated well with lesion size for lesions in the left ventricle but less well for lesions in the right ventricle. There was a poor relationship between CF and the amplitude of the bipolar or unipolar ventricular electrogram, unipolar injury current, and impedance. Radiofrequencylesion size and the incidence of steam pop increase strikingly with increasing CF. Electrogram parameters and initial impedance are poor predictors of CF for radiofrequency ablation. © 2014 American Heart Association, Inc.

Jet Velocity Profile Effects on Spray Characteristics of Impinging Jets at High Reynolds and Weber Numbers

NASA Astrophysics Data System (ADS)

Rodrigues, Neil S.; Kulkarni, Varun; Sojka, Paul E.

2014-11-01

While like-on-like doublet impinging jet atomization has been extensively studied in the literature, there is poor agreement between experimentally observed spray characteristics and theoretical predictions (Ryan et al. 1995, Anderson et al. 2006). Recent works (Bremond and Villermaux 2006, Choo and Kang 2007) have introduced a non-uniform jet velocity profile, which lead to a deviation from the standard assumptions for the sheet velocity and the sheet thickness parameter. These works have assumed a parabolic profile to serve as another limit to the traditional uniform jet velocity profile assumption. Incorporating a non-uniform jet velocity profile results in the sheet velocity and the sheet thickness parameter depending on the sheet azimuthal angle. In this work, the 1/7th power-law turbulent velocity profile is assumed to provide a closer match to the flow behavior of jets at high Reynolds and Weber numbers, which correspond to the impact wave regime. Predictions for the maximum wavelength, sheet breakup length, ligament diameter, and drop diameter are compared with experimental observations. The results demonstrate better agreement between experimentally measured values and predictions, compared to previous models. U.S. Army Research Office under the Multi-University Research Initiative Grant Number W911NF-08-1-0171.

Pump-probe imaging of pigmented cutaneous melanoma primary lesions gives insight into metastatic potential

PubMed Central

Robles, Francisco E.; Deb, Sanghamitra; Wilson, Jesse W.; Gainey, Christina S.; Selim, M. Angelica; Mosca, Paul J.; Tyler, Douglas S.; Fischer, Martin C.; Warren, Warren S.

2015-01-01

Metastatic melanoma is associated with a poor prognosis, but no method reliably predicts which melanomas of a given stage will ultimately metastasize and which will not. While sentinel lymph node biopsy (SLNB) has emerged as the most powerful predictor of metastatic disease, the majority of people dying from metastatic melanoma still have a negative SLNB. Here we analyze pump-probe microscopy images of thin biopsy slides of primary melanomas to assess their metastatic potential. Pump-probe microscopy reveals detailed chemical information of melanin with subcellular spatial resolution. Quantification of the molecular signatures without reference standards is achieved using a geometrical representation of principal component analysis. Melanin structure is analyzed in unison with the chemical information by applying principles of mathematical morphology. Results show that melanin in metastatic primary lesions has lower chemical diversity than non-metastatic primary lesions, and contains two distinct phenotypes that are indicative of aggressive disease. Further, the mathematical morphology analysis reveals melanin in metastatic primary lesions has a distinct “dusty” quality. Finally, a statistical analysis shows that the combination of the chemical information with spatial structures predicts metastatic potential with much better sensitivity than SLNB and high specificity, suggesting pump-probe microscopy can be an important tool to help predict the metastatic potential of melanomas. PMID:26417529

Model of the transient neurovascular response based on prompt arterial dilation

PubMed Central

Kim, Jung Hwan; Khan, Reswanul; Thompson, Jeffrey K; Ress, David

2013-01-01

Brief neural stimulation results in a stereotypical pattern of vascular and metabolic response that is the basis for popular brain-imaging methods such as functional magnetic resonance imagine. However, the mechanisms of transient oxygen transport and its coupling to cerebral blood flow (CBF) and oxygen metabolism (CMRO2) are poorly understood. Recent experiments show that brief stimulation produces prompt arterial vasodilation rather than venous vasodilation. This work provides a neurovascular response model for brief stimulation based on transient arterial effects using one-dimensional convection–diffusion transport. Hemoglobin oxygen dissociation is included to enable predictions of absolute oxygen concentrations. Arterial CBF response is modeled using a lumped linear flow model, and CMRO2 response is modeled using a gamma function. Using six parameters, the model successfully fit 161/166 measured extravascular oxygen time courses obtained for brief visual stimulation in cat cerebral cortex. Results show how CBF and CMRO2 responses compete to produce the observed features of the hemodynamic response: initial dip, hyperoxic peak, undershoot, and ringing. Predicted CBF and CMRO2 response amplitudes are consistent with experimental measurements. This model provides a powerful framework to quantitatively interpret oxygen transport in the brain; in particular, its intravascular oxygen concentration predictions provide a new model for fMRI responses. PMID:23756690

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.

Bimanual coordination positively predicts episodic memory: A combined behavioral and MRI investigation.

PubMed

Lyle, Keith B; Dombroski, Brynn A; Faul, Leonard; Hopkins, Robin F; Naaz, Farah; Switala, Andrew E; Depue, Brendan E

2017-11-01

Some people remember events more completely and accurately than other people, but the origins of individual differences in episodic memory are poorly understood. One way to advance understanding is by identifying characteristics of individuals that reliably covary with memory performance. Recent research suggests motor behavior is related to memory performance, with individuals who consistently use a single preferred hand for unimanual actions performing worse than individuals who make greater use of both hands. This research has relied on self-reports of behavior. It is unknown whether objective measures of motor behavior also predict memory performance. Here, we tested the predictive power of bimanual coordination, an important form of manual dexterity. Bimanual coordination, as measured objectively on the Purdue Pegboard Test, was positively related to correct recall on the California Verbal Learning Test-II and negatively related to false recall. Furthermore, MRI data revealed that cortical surface area in right lateral prefrontal regions was positively related to correct recall. In one of these regions, cortical thickness was negatively related to bimanual coordination. These results suggest that individual differences in episodic memory may partially reflect morphological variation in right lateral prefrontal cortex and suggest a relationship between neural correlates of episodic memory and motor behavior. Copyright © 2017 Elsevier Inc. All rights reserved.

Brief report: Poor self-regulation as a predictor of individual differences in adaptive functioning in young children with autism spectrum disorder.

PubMed

Uljarević, Mirko; Hedley, Darren; Nevill, Rose; Evans, David W; Cai, Ru Ying; Butter, Eric; Mulick, James A

2018-04-06

The present study examined the link between poor self-regulation (measured by the child behavior checklist dysregulated profile [DP]) and core autism symptoms, as well as with developmental level, in a sample of 107 children with autism spectrum disorder (ASD) aged 19-46 months. We further examined the utility of DP in predicting individual differences in adaptive functioning, relative to the influence of ASD severity, chronological age (CA), and developmental level. Poor self-regulation was unrelated to CA, developmental level, and severity of ADOS-2 restricted and repetitive behaviors, but was associated with lower ADOS-2 social affect severity. Hierarchical regression identified poor self-regulation as a unique independent predictor of adaptive behavior, with more severe dysregulation predicting poorer adaptive functioning. Results highlight the importance of early identification of deficits in self-regulation, and more specifically, of the utility of DP, when designing individually tailored treatments for young children with ASD. Autism Res 2018. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. This study explored the relationship between poor self-regulation and age, verbal and non-verbal developmental level, severity of autism symptoms and adaptive functioning in 107 children with autism under 4 years of age. Poor self-regulation was unrelated to age, developmental level, and severity of restricted and repetitive behaviors but was associated with lower social affect severity. Importantly, more severe self-regulation deficits predicted poorer adaptive functioning. © 2018 International Society for Autism Research, Wiley Periodicals, Inc.

How well do parental and peer relationships in adolescence predict health in adulthood?

PubMed

Landstedt, Evelina; Hammarström, Anne; Winefield, Helen

2015-07-01

Although health effects of social relationships are well-researched, long-term health consequences of adolescent family as well as peer relationships are poorly understood. The aim of the study was to explore the prospective importance of parental and peer social relationships in adolescence on internalising and functional somatic symptoms in adulthood. Data were drawn from four waves of the Northern Swedish Cohort Study, response rate 94.3%, N=1001. Outcome variables were internalising and functional somatic symptoms at the ages of 21, 30 and 42. Relationship variables at age 16 were poor parental contact and three indicators of poor peer relationships. Associations were assessed in multivariate ordinal logistic regressions with adjustment for confounders and baseline health. Results show that the main relationships-related predictors of adult internalising symptoms were self-rated poor peer relationships in terms of spending time alone during after-school hours and poor parental relationship. Functional somatic symptoms on the other hand were most strongly associated with poor parental contact and not being happy with classmates at age 16. The quality of parental and peer relationships in adolescence predicts adult mental and functional somatic health as much as 26 years later, even when accounting for confounders and adolescent symptomatology. This study extends past research by exploring how both adolescent parental and peer relationships (self-reported as well as teacher reported) predict adult self-reported health. © 2015 the Nordic Societies of Public Health.

Ultra-Short-Term Wind Power Prediction Using a Hybrid Model

NASA Astrophysics Data System (ADS)

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

2017-05-01

This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.

Physical health, self-reliance, and emotional control as moderators of the relationship between locus of control and mental health among men treated for prostate cancer.

PubMed

Burns, Shaun Michael; Mahalik, James R

2006-12-01

This investigation examined the moderating effects of physical health and scripts for masculinity (i.e., self-reliance and emotional control) on the relationship between powerful other people locus of control and mental health for 230 men treated for prostate cancer. Regression analyses indicated that physical health and masculine gender scripts moderated the association between powerful other people locus of control and mental health. Specifically, men with poor physical health evinced negative mental health when they endorsed masculine gender scripts and believed powerful other people (i.e., family, friends, or peers) were influential in controlling their cancer. By comparison, men reporting poor physical health, strong beliefs that powerful other people controlled their cancer, and less adherence to masculine scripts experienced positive mental health. The authors discuss future research directions and potential mental health implications for men treated for prostate cancer.

Experimental validation of boundary element methods for noise prediction

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Oswald, Fred B.

1992-01-01

Experimental validation of methods to predict radiated noise is presented. A combined finite element and boundary element model was used to predict the vibration and noise of a rectangular box excited by a mechanical shaker. The predicted noise was compared to sound power measured by the acoustic intensity method. Inaccuracies in the finite element model shifted the resonance frequencies by about 5 percent. The predicted and measured sound power levels agree within about 2.5 dB. In a second experiment, measured vibration data was used with a boundary element model to predict noise radiation from the top of an operating gearbox. The predicted and measured sound power for the gearbox agree within about 3 dB.

Temperament and impulsivity predictors of smoking cessation outcomes.

PubMed

López-Torrecillas, Francisca; Perales, José C; Nieto-Ruiz, Ana; Verdejo-García, Antonio

2014-01-01

Temperament and impulsivity are powerful predictors of addiction treatment outcomes. However, a comprehensive assessment of these features has not been examined in relation to smoking cessation outcomes. Naturalistic prospective study. Treatment-seeking smokers (n = 140) were recruited as they engaged in an occupational health clinic providing smoking cessation treatment between 2009 and 2013. Participants were assessed at baseline with measures of temperament (Temperament and Character Inventory), trait impulsivity (Barratt Impulsivity Scale), and cognitive impulsivity (Go/No Go, Delay Discounting and Iowa Gambling Task). The outcome measure was treatment status, coded as "dropout" versus "relapse" versus "abstinence" at 3, 6, and 12 months endpoints. Participants were telephonically contacted and reminded of follow-up face to face assessments at each endpoint. The participants that failed to answer the phone calls or self-reported discontinuation of treatment and failed to attend the upcoming follow-up session were coded as dropouts. The participants that self-reported continuing treatment, and successfully attended the upcoming follow-up session were coded as either "relapse" or "abstinence", based on the results of smoking behavior self-reports cross-validated with co-oximetry hemoglobin levels. Multinomial regression models were conducted to test whether temperament and impulsivity measures predicted dropout and relapse relative to abstinence outcomes. Higher scores on temperament dimensions of novelty seeking and reward dependence predicted poorer retention across endpoints, whereas only higher scores on persistence predicted greater relapse. Higher scores on the trait dimension of non-planning impulsivity but not performance on cognitive impulsivity predicted poorer retention. Higher non-planning impulsivity and poorer performance in the Iowa Gambling Task predicted greater relapse at 3 and 6 months and 6 months respectively. Temperament measures, and specifically novelty seeking and reward dependence, predict smoking cessation treatment retention, whereas persistence, non-planning impulsivity and poor decision-making predict smoking relapse.

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

Dynamic Modeling and Very Short-term Prediction of Wind Power Output Using Box-Cox Transformation

NASA Astrophysics Data System (ADS)

Urata, Kengo; Inoue, Masaki; Murayama, Dai; Adachi, Shuichi

2016-09-01

We propose a statistical modeling method of wind power output for very short-term prediction. The modeling method with a nonlinear model has cascade structure composed of two parts. One is a linear dynamic part that is driven by a Gaussian white noise and described by an autoregressive model. The other is a nonlinear static part that is driven by the output of the linear part. This nonlinear part is designed for output distribution matching: we shape the distribution of the model output to match with that of the wind power output. The constructed model is utilized for one-step ahead prediction of the wind power output. Furthermore, we study the relation between the prediction accuracy and the prediction horizon.

Social motives and cognitive power-sex associations: predictors of aggressive sexual behavior.

PubMed

Zurbriggen, E L

2000-03-01

The present study investigated whether implicit social motives and cognitive power-sex associations would predict self-reports of aggressive sexual behavior. Participants wrote stories in response to Thematic Apperception Test pictures, which were scored for power and affiliation-intimacy motives. They also completed a lexical-decision priming task that provided an index of the strength of the cognitive association between the concepts of "power" and "sexuality." For men, high levels of power motivation and strong power-sex associations predicted more frequent aggression. There was also an interaction: Power motivation was unrelated to aggression for men with the weakest power-sex associations. For women, high levels of affiliation-intimacy motivation were associated with more frequent aggression. Strong power-sex associations were also predictive for women but only when affiliation-intimacy motivation was high.

Effects of controlled breathing, mental activity and mental stress with or without verbalization on heart rate variability.

PubMed

Bernardi, L; Wdowczyk-Szulc, J; Valenti, C; Castoldi, S; Passino, C; Spadacini, G; Sleight, P

2000-05-01

To assess whether talking or reading (silently or aloud) could affect heart rate variability (HRV) and to what extent these changes require a simultaneous recording of respiratory activity to be correctly interpreted. Sympathetic predominance in the power spectrum obtained from short- and long-term HRV recordings predicts a poor prognosis in a number of cardiac diseases. Heart rate variability is often recorded without measuring respiration; slow breaths might artefactually increase low frequency power in RR interval (RR) and falsely mimic sympathetic activation. In 12 healthy volunteers we evaluated the effect of free talking and reading, silently and aloud, on respiration, RR and blood pressure (BP). We also compared spontaneous breathing to controlled breathing and mental arithmetic, silent or aloud. The power in the so called low- (LF) and high-frequency (HF) bands in RR and BP was obtained from autoregressive power spectrum analysis. Compared with spontaneous breathing, reading silently increased the speed of breathing (p < 0.05), decreased mean RR and RR variability and increased BP. Reading aloud, free talking and mental arithmetic aloud shifted the respiratory frequency into the LF band, thus increasing LF% and decreasing HF% to a similar degree in both RR and respiration, with decrease in mean RR but with minor differences in crude RR variability. Simple mental and verbal activities markedly affect HRV through changes in respiratory frequency. This possibility should be taken into account when analyzing HRV without simultaneous acquisition and analysis of respiration.

Prediction of poor outcomes six months following total knee arthroplasty in patients awaiting surgery.

PubMed

Lungu, Eugen; Desmeules, François; Dionne, Clermont E; Belzile, Etienne L; Vendittoli, Pascal-André

2014-09-08

Identification of patients experiencing poor outcomes following total knee arthroplasty (TKA) before the intervention could allow better case selection, patient preparation and, likely, improved outcomes. The objective was to develop a preliminary prediction rule (PR) to identify patients enrolled on surgical wait lists who are at the greatest risk of poor outcomes 6 months after TKA. 141 patients scheduled for TKA were recruited prospectively from the wait lists of 3 hospitals in Quebec City, Canada. Knee pain, stiffness and function were measured 6 months after TKA with the Western Ontario and McMaster Osteoarthritis Index (WOMAC) and participants in the lowest quintile for the WOMAC total score were considered to have a poor outcome. Several variables measured at enrolment on the wait lists (baseline) were considered potential predictors: demographic, socioeconomic, psychosocial, and clinical factors including pain, stiffness and functional status measured with the WOMAC. The prediction rule was built with recursive partitioning. The best prediction was provided by 5 items of the baseline WOMAC. The rule had a sensitivity of 82.1% (95% CI: 66.7-95.8), a specificity of 71.7% (95% CI: 62.8-79.8), a positive predictive value of 41.8% (95% CI: 29.7-55.0), a negative predictive value of 94.2% (95% CI: 87.1-97.5) and positive and negative likelihood ratios of 2.9 (95% CI: 1.8-4.7) and 0.3 (95% CI: 0.1-0.6) respectively. The developed PR is a promising tool to identify patients at risk of worse outcomes 6 months after TKA as it could help improve the management of these patients. Further validation of this rule is however warranted before clinical use.

Exploring the resilience of Bt cotton's "pro-poor success story".

PubMed

Glover, Dominic

2010-01-01

Expectations play a powerful role in driving technological change. Expectations are often encapsulated in narratives of technological promise that emphasize potential benefits and downplay potential negative impacts. Genetically modified (GM, transgenic) crops have been framed by expectations that they would be an intrinsically "pro-poor" innovation that would contribute powerfully to international agricultural development. However, expectations typically have to be scaled back in the light of experience. Published reviews of the socio-economic impacts of GM crops among poor, small-scale farmers in the developing world indicate that these effects have been very mixed and contingent on the agronomic, socio-economic and institutional settings where the technology has been applied. These conclusions should modulate expectations about the pro-poor potential of GM crop technology and focus attention on the conditions under which it might deliver substantial and sustainable benefits for poor farmers. However, the idea of GM crop technology as an intrinsically pro-poor developmental success story has been sustained in academic, public and policy arenas. This narrative depends upon an analysis that disembeds the technology from the technical, social and institutional contexts in which it is applied. Agricultural development policy should be based on a more rigorous and dispassionate analysis, rather than optimistic expectations alone.

FINAL REPORT: Mechanistically-Base Field Scale Models of Uranium Biogeochemistry from Upscaling Pore-Scale Experiments and Models

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

Wood, Brian D.

2013-11-04

Biogeochemical reactive transport processes in the subsurface environment are important to many contemporary environmental issues of significance to DOE. Quantification of risks and impacts associated with environmental management options, and design of remediation systems where needed, require that we have at our disposal reliable predictive tools (usually in the form of numerical simulation models). However, it is well known that even the most sophisticated reactive transport models available today have poor predictive power, particularly when applied at the field scale. Although the lack of predictive ability is associated in part with our inability to characterize the subsurface and limitations inmore » computational power, significant advances have been made in both of these areas in recent decades and can be expected to continue. In this research, we examined the upscaling (pore to Darcy and Darcy to field) the problem of bioremediation via biofilms in porous media. The principle idea was to start with a conceptual description of the bioremediation process at the pore scale, and apply upscaling methods to formally develop the appropriate upscaled model at the so-called Darcy scale. The purpose was to determine (1) what forms the upscaled models would take, and (2) how one might parameterize such upscaled models for applications to bioremediation in the field. We were able to effectively upscale the bioremediation process to explain how the pore-scale phenomena were linked to the field scale. The end product of this research was to produce a set of upscaled models that could be used to help predict field-scale bioremediation. These models were mechanistic, in the sense that they directly incorporated pore-scale information, but upscaled so that only the essential features of the process were needed to predict the effective parameters that appear in the model. In this way, a direct link between the microscale and the field scale was made, but the upscaling process helped inform potential users of the model what kinds of information would be needed to accurately characterize the system.« less

Prediction of Response to Preoperative Chemoradiotherapy in Rectal Cancer by Multiplex Kinase Activity Profiling

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

Folkvord, Sigurd; Flatmark, Kjersti; Department of Cancer and Surgery, Norwegian Radium Hospital, Oslo University Hospital

2010-10-01

Purpose: Tumor response of rectal cancer to preoperative chemoradiotherapy (CRT) varies considerably. In experimental tumor models and clinical radiotherapy, activity of particular subsets of kinase signaling pathways seems to predict radiation response. This study aimed to determine whether tumor kinase activity profiles might predict tumor response to preoperative CRT in locally advanced rectal cancer (LARC). Methods and Materials: Sixty-seven LARC patients were treated with a CRT regimen consisting of radiotherapy, fluorouracil, and, where possible, oxaliplatin. Pretreatment tumor biopsy specimens were analyzed using microarrays with kinase substrates, and the resulting substrate phosphorylation patterns were correlated with tumor response to preoperative treatmentmore » as assessed by histomorphologic tumor regression grade (TRG). A predictive model for TRG scores from phosphosubstrate signatures was obtained by partial-least-squares discriminant analysis. Prediction performance was evaluated by leave-one-out cross-validation and use of an independent test set. Results: In the patient population, 73% and 15% were scored as good responders (TRG 1-2) or intermediate responders (TRG 3), whereas 12% were assessed as poor responders (TRG 4-5). In a subset of 7 poor responders and 12 good responders, treatment outcome was correctly predicted for 95%. Application of the prediction model on the remaining patient samples resulted in correct prediction for 85%. Phosphosubstrate signatures generated by poor-responding tumors indicated high kinase activity, which was inhibited by the kinase inhibitor sunitinib, and several discriminating phosphosubstrates represented proteins derived from signaling pathways implicated in radioresistance. Conclusions: Multiplex kinase activity profiling may identify functional biomarkers predictive of tumor response to preoperative CRT in LARC.« less

Comparison of Short-Wavelength Reduced-Illuminance and Conventional Autofluorescence Imaging in Stargardt Macular Dystrophy.

PubMed

Strauss, Rupert W; Muñoz, Beatriz; Jha, Anamika; Ho, Alexander; Cideciyan, Artur V; Kasilian, Melissa L; Wolfson, Yulia; Sadda, SriniVas; West, Sheila; Scholl, Hendrik P N; Michaelides, Michel

2016-08-01

To compare grading results between short-wavelength reduced-illuminance and conventional autofluorescence imaging in Stargardt macular dystrophy. Reliability study. setting: Moorfields Eye Hospital, London (United Kingdom). Eighteen patients (18 eyes) with Stargardt macular dystrophy. A series of 3 fundus autofluorescence images using 3 different acquisition parameters on a custom-patched device were obtained: (1) 25% laser power and total sensitivity 87; (2) 25% laser power and freely adjusted sensitivity; and (3) 100% laser power and freely adjusted total sensitivity (conventional). The total area of 2 hypoautofluorescent lesion types (definitely decreased autofluorescence and poorly demarcated questionably decreased autofluorescence) was measured. Agreement in grading between the 3 imaging methods was assessed by kappa coefficients (κ) and intraclass correlation coefficients. The mean ± standard deviation area for images acquired with 25% laser power and freely adjusted total sensitivity was 2.04 ± 1.87 mm(2) for definitely decreased autofluorescence (n = 15) and 1.86 ± 2.14 mm(2) for poorly demarcated questionably decreased autofluorescence (n = 12). The intraclass correlation coefficient (95% confidence interval) was 0.964 (0.929, 0.999) for definitely decreased autofluorescence and 0.268 (0.000, 0.730) for poorly demarcated questionably decreased autofluorescence. Short-wavelength reduced-illuminance and conventional fundus autofluorescence imaging showed good concordance in assessing areas of definitely decreased autofluorescence. However, there was significantly higher variability between imaging modalities for assessing areas of poorly demarcated questionably decreased autofluorescence. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Extending Theory-Based Quantitative Predictions to New Health Behaviors.

PubMed

Brick, Leslie Ann D; Velicer, Wayne F; Redding, Colleen A; Rossi, Joseph S; Prochaska, James O

2016-04-01

Traditional null hypothesis significance testing suffers many limitations and is poorly adapted to theory testing. A proposed alternative approach, called Testing Theory-based Quantitative Predictions, uses effect size estimates and confidence intervals to directly test predictions based on theory. This paper replicates findings from previous smoking studies and extends the approach to diet and sun protection behaviors using baseline data from a Transtheoretical Model behavioral intervention (N = 5407). Effect size predictions were developed using two methods: (1) applying refined effect size estimates from previous smoking research or (2) using predictions developed by an expert panel. Thirteen of 15 predictions were confirmed for smoking. For diet, 7 of 14 predictions were confirmed using smoking predictions and 6 of 16 using expert panel predictions. For sun protection, 3 of 11 predictions were confirmed using smoking predictions and 5 of 19 using expert panel predictions. Expert panel predictions and smoking-based predictions poorly predicted effect sizes for diet and sun protection constructs. Future studies should aim to use previous empirical data to generate predictions whenever possible. The best results occur when there have been several iterations of predictions for a behavior, such as with smoking, demonstrating that expected values begin to converge on the population effect size. Overall, the study supports necessity in strengthening and revising theory with empirical data.

Cellulose Crystal Dissolution in Imidazolium-Based Ionic Liquids: A Theoretical Study.

PubMed

Uto, Takuya; Yamamoto, Kazuya; Kadokawa, Jun-Ichi

2018-01-11

The highly crystalline nature of cellulose results in poor processability and solubility, necessitating the search for solvents that can efficiently dissolve this material. Thus, ionic liquids (ILs) have recently been shown to be well suited for this purpose, although the corresponding dissolution mechanism has not been studied in detail. Herein, we adopt a molecular dynamics (MD) approach to study the dissolution of model cellulose crystal structures in imidazolium-based ILs and gain deep mechanistic insights, demonstrating that dissolution involves IL penetration-induced cleavage of hydrogen bonds between cellulose molecular chains. Moreover, we reveal that in ILs with high cellulose dissolving power (powerful solvents, such as 1-allyl-3-methylimidazolium chloride and 1-ethyl-3-methylimidazolium chloride), the above molecular chains are peeled from the crystal phase and subsequently dispersed in the solvent, whereas no significant structural changes are observed in poor-dissolving-power solvents. Finally, we utilize MD trajectory analysis to show that the solubility of microcrystalline cellulose is well correlated with the number of intermolecular hydrogen bonds in cellulose crystals. The obtained results allow us to conclude that both anions and cations of high-dissolving-power ILs contribute to the stepwise breakage of hydrogen bonds between cellulose chains, whereas this breakage does not occur to a sufficient extent in poorly solubilizing ILs.

Limited change in dune mobility in response to a large decrease in wind power in semi-arid northern China since the 1970s

USGS Publications Warehouse

Mason, J.A.; Swinehart, J.B.; Lu, H.; Miao, X.; Cha, P.; Zhou, Y.

2008-01-01

The climatic controls on dune mobility, especially the relative importance of wind strength, remain incompletely understood. This is a key research problem in semi-arid northern China, both for interpreting past dune activity as evidence of paleoclimate and for predicting future environmental change. Potential eolian sand transport, which is approximately proportional to wind power above the threshold for sand entrainment, has decreased across much of northern China since the 1970s. Over the same period, effective moisture (ratio of precipitation to potential evapotranspiration) has not changed significantly. This "natural experiment" provides insight on the relative importance of wind power as a control on dune mobility in three dunefields of northern China (Mu Us, Otindag, and Horqin), although poorly understood and potentially large effects of human land use complicate interpretation. Dune forms in these three regions are consistent with sand transport vectors inferred from weather station data, suggesting that wind directions have remained stable and the stations adequately represent winds that shaped the dunes. The predicted effect of weaker winds since the 1970s would be dune stabilization, with lower sand transport rates allowing vegetation cover to expand. Large portions of all three dunefields remained stabilized by vegetation in the 1970s despite high wind power. Since the 1970s, trends in remotely sensed vegetation greenness and change in mobile dune area inferred from sequential Landsat images do indicate widespread dune stabilization in the eastern Mu Us region. On the other hand, expansion of active dunes took place farther west in the Mu Us dunefield and especially in the central Otindag dunefield, with little overall change in two parts of the Horqin dunes. Better ground truth is needed to validate the remote sensing analyses, but results presented here place limits on the relative importance of wind strength as a control on dune mobility in the study areas. High wind power alone does not completely destabilize these dunes. A large decrease in wind power either has little short-term effect on the dunes, or more likely its effect is sufficiently small that it is obscured by human impacts on dune stability in many parts of the study areas. ?? 2008 Elsevier B.V. All rights reserved.

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

Newman, Jennifer F.; Clifton, Andrew

Currently, cup anemometers on meteorological towers are used to measure wind speeds and turbulence intensity to make decisions about wind turbine class and site suitability; however, as modern turbine hub heights increase and wind energy expands to complex and remote sites, it becomes more difficult and costly to install meteorological towers at potential sites. As a result, remote-sensing devices (e.g., lidars) are now commonly used by wind farm managers and researchers to estimate the flow field at heights spanned by a turbine. Although lidars can accurately estimate mean wind speeds and wind directions, there is still a large amount ofmore » uncertainty surrounding the measurement of turbulence using these devices. Errors in lidar turbulence estimates are caused by a variety of factors, including instrument noise, volume averaging, and variance contamination, in which the magnitude of these factors is highly dependent on measurement height and atmospheric stability. As turbulence has a large impact on wind power production, errors in turbulence measurements will translate into errors in wind power prediction. The impact of using lidars rather than cup anemometers for wind power prediction must be understood if lidars are to be considered a viable alternative to cup anemometers.In this poster, the sensitivity of power prediction error to typical lidar turbulence measurement errors is assessed. Turbulence estimates from a vertically profiling WINDCUBE v2 lidar are compared to high-resolution sonic anemometer measurements at field sites in Oklahoma and Colorado to determine the degree of lidar turbulence error that can be expected under different atmospheric conditions. These errors are then incorporated into a power prediction model to estimate the sensitivity of power prediction error to turbulence measurement error. Power prediction models, including the standard binning method and a random forest method, were developed using data from the aeroelastic simulator FAST for a 1.5 MW turbine. The impact of lidar turbulence error on the predicted power from these different models is examined to determine the degree of turbulence measurement accuracy needed for accurate power prediction.« less

POWER Web Access Data

Atmospheric Science Data Center

2018-05-27

Description:  Obtain Prediction of Worldwide Energy Resource (POWER) data The Prediction of Worldwide Energy ... (POWER) project was initiated to improve upon the current renewable energy data set and to create new data sets from new satellite ...

1. Photocopy of sketch showing water power drive mechanism for ...

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

1. Photocopy of sketch showing water power drive mechanism for up-and-down saw mill; delineated by Charles G. Poor, Bob Levy and Janet Hochuli, 1977. - Grant's Grist & Saw Mill, Wrentham Road, Cumberland, Providence County, RI

Can paediatric early warning scores (PEWS) be used to guide the need for hospital admission and predict significant illness in children presenting to the emergency department? An assessment of PEWS diagnostic accuracy using sensitivity and specificity.

PubMed

Lillitos, Peter J; Hadley, Graeme; Maconochie, Ian

2016-05-01

Designed to detect early deterioration of the hospitalised child, paediatric early warning scores (PEWS) validity in the emergency department (ED) is less validated. We aimed to evaluate sensitivity and specificity of two commonly used PEWS (Brighton and COAST) in predicting hospital admission and, for the first time, significant illness. Retrospective analysis of PEWS data for paediatric ED attendances at St Mary's Hospital, London, UK, in November 2012. Patients with missing data were excluded. Diagnoses were grouped: medical and surgical. To classify diagnoses as significant, established guidelines were used and, where not available, common agreement between three acute paediatricians. 1921 patients were analysed. There were 211 admissions (11%). 1630 attendances were medical (86%) and 273 (14%) surgical. Brighton and COAST PEWS performed similarly. hospital admission: PEWS of ≥3 was specific (93%) but poorly sensitive (32%). The area under the receiver operating curve (AUC) was low at 0.690. Significant illness: for medical illness, PEWS ≥3 was highly specific (96%) but poorly sensitive (44%). The AUC was 0.754 and 0.755 for Brighton and COAST PEWS, respectively. Both scores performed poorly for predicting significant surgical illness (AUC 0.642). PEWS ≥3 performed well in predicting significant respiratory illness: sensitivity 75%, specificity 91%. Both Brighton and COAST PEWS scores performed similarly. A score of ≥3 has good specificity but poor sensitivity for predicting hospital admission and significant illness. Therefore, a high PEWS should be taken seriously but a low score is poor at ruling out the requirement for admission or serious underlying illness. PEWS was better at detecting significant medical illness compared with detecting the need for admission. PEWS performed poorly in detecting significant surgical illness. PEWS may be particularly useful in evaluating respiratory illness in a paediatric ED. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Hyperkinetic Impulse Disorder in Children's Behavior Problems

ERIC Educational Resources Information Center

Laufer, Maurice W.; Denhoff, Eric; Solomons, Gerald

2011-01-01

A very common cause of children's behavior disorder disturbance is an entity described as the hyperkinetic impulse disorder. This is characterized by hyperactivity, short attention span and poor powers of concentration, irritability, impulsiveness, variability, and poor schoolwork. The existence of this complexity may lead to many psychological…

Impact of the revised International Prognostic Scoring System, cytogenetics and monosomal karyotype on outcome after allogeneic stem cell transplantation for myelodysplastic syndromes and secondary acute myeloid leukemia evolving from myelodysplastic syndromes: a retrospective multicenter study of the European Society of Blood and Marrow Transplantation

PubMed Central

Koenecke, Christian; Göhring, Gudrun; de Wreede, Liesbeth C.; van Biezen, Anja; Scheid, Christof; Volin, Liisa; Maertens, Johan; Finke, Jürgen; Schaap, Nicolaas; Robin, Marie; Passweg, Jakob; Cornelissen, Jan; Beelen, Dietrich; Heuser, Michael; de Witte, Theo; Kröger, Nicolaus

2015-01-01

The aim of this study was to determine the impact of the revised 5-group International Prognostic Scoring System cytogenetic classification on outcome after allogeneic stem cell transplantation in patients with myelodysplastic syndromes or secondary acute myeloid leukemia who were reported to the European Society for Blood and Marrow Transplantation database. A total of 903 patients had sufficient cytogenetic information available at stem cell transplantation to be classified according to the 5-group classification. Poor and very poor risk according to this classification was an independent predictor of shorter relapse-free survival (hazard ratio 1.40 and 2.14), overall survival (hazard ratio 1.38 and 2.14), and significantly higher cumulative incidence of relapse (hazard ratio 1.64 and 2.76), compared to patients with very good, good or intermediate risk. When comparing the predictive performance of a series of Cox models both for relapse-free survival and for overall survival, a model with simplified 5-group cytogenetics (merging very good, good and intermediate cytogenetics) performed best. Furthermore, monosomal karyotype is an additional negative predictor for outcome within patients of the poor, but not the very poor risk group of the 5-group classification. The revised International Prognostic Scoring System cytogenetic classification allows patients with myelodysplastic syndromes to be separated into three groups with clearly different outcomes after stem cell transplantation. Poor and very poor risk cytogenetics were strong predictors of poor patient outcome. The new cytogenetic classification added value to prediction of patient outcome compared to prediction models using only traditional risk factors or the 3-group International Prognostic Scoring System cytogenetic classification. PMID:25552702

Anion gap as a prognostic tool for risk stratification in critically ill patients - a systematic review and meta-analysis.

PubMed

Glasmacher, Stella Andrea; Stones, William

2016-08-30

Lactate concentration is a robust predictor of mortality but in many low resource settings facilities for its analysis are not available. Anion gap (AG), calculated from clinical chemistry results, is a marker of metabolic acidosis and may be more easily obtained in such settings. In this systematic review and meta-analysis we investigated whether the AG predicts mortality in adult patients admitted to critical care settings. We searched Medline, Embase, Web of Science, Scopus, The Cochrane Library and regional electronic databases from inception until May 2016. Studies conducted in any clinical setting that related AG to in-hospital mortality, in-intensive care unit mortality, 31-day mortality or comparable outcome measures were eligible for inclusion. Methodological quality of included studies was assessed using the Quality in Prognostic Studies tool. Descriptive meta-analysis was performed and the I(2) test was used to quantify heterogeneity. Subgroup analysis was undertaken to identify potential sources of heterogeneity between studies. Nineteen studies reporting findings in 12,497 patients were included. Overall, quality of studies was poor and most studies were rated as being at moderate or high risk of attrition bias and confounding. There was substantial diversity between studies with regards to clinical setting, age and mortality rates of patient cohorts. High statistical heterogeneity was found in the meta-analyses of area under the ROC curve (I(2) = 99 %) and mean difference (I(2) = 97 %) for the observed AG. Three studies reported good discriminatory power of the AG to predict mortality and were responsible for a large proportion of statistical heterogeneity. The remaining 16 studies reported poor to moderate ability of the AG to predict mortality. Subgroup analysis suggested that intravenous fluids affect the ability of the AG to predict mortality. Based on the limited quality of available evidence, a single AG measurement cannot be recommended for risk stratification in critically ill patients. The probable influence of intravenous fluids on AG levels renders the AG an impractical tool in clinical practice. Future research should focus on increasing the availability of lactate monitoring in low resource settings. CRD42015015249 . Registered on 4th February 2015.

Estrogen receptor and progesterone receptor as predictive biomarkers of response to endocrine therapy: a prospectively powered pathology study in the Tamoxifen and Exemestane Adjuvant Multinational trial.

PubMed

Bartlett, John M S; Brookes, Cassandra L; Robson, Tammy; van de Velde, Cornelis J H; Billingham, Lucinda J; Campbell, Fiona M; Grant, Margaret; Hasenburg, Annette; Hille, Elysée T M; Kay, Charlene; Kieback, Dirk G; Putter, Hein; Markopoulos, Christos; Kranenbarg, Elma Meershoek-Klein; Mallon, Elizabeth A; Dirix, Luc; Seynaeve, Caroline; Rea, Daniel

2011-04-20

The Tamoxifen and Exemestane Adjuvant Multinational (TEAM) trial included a prospectively planned pathology substudy testing the predictive value of progesterone receptor (PgR) expression for outcome of estrogen receptor-positive (ER-positive) early breast cancer treated with exemestane versus tamoxifen. Pathology blocks from 4,781 TEAM patients randomly assigned to exemestane versus tamoxifen followed by exemestane for 5 years of total therapy were collected centrally, and tissue microarrays were constructed from samples from 4,598 patients. Quantitative analysis of hormone receptors (ER and PgR) was performed by using image analysis and immunohistochemistry, and the results were linked to outcome data from the main TEAM trial and analyzed relative to disease-free survival and treatment. Of 4,325 eligible ER-positive patients, 23% were PgR-poor (Allred < 4) and 77% were PgR- rich (Allred ≥ 5). No treatment-by-marker effect for PgR was observed for exemestane versus tamoxifen (PgR-rich hazard ratio [HR], 0.83; 95% CI, 0.65 to 1.05; PgR-poor HR, 0.85; 95% CI, 0.61 to 1.19; P = .88 for interaction). Both PgR and ER expression were associated with patient prognosis in univariate (PgR HR, 0.53; 95% CI, 0.43 to 0.65; P < .001; ER HR, 0.66; 95% CI, 0.51 to 0.86; P = .002), and multivariate analyses (P < .001 and P = .001, respectively). A trend toward a treatment-by-marker effect for ER-rich patients was observed. Preferential exemestane versus tamoxifen treatment benefit was not predicted by PgR expression; conversely, patients with ER-rich tumors may derive additional benefit from exemestane. Quantitative analysis of ER and PgR expression provides highly significant information on risk of early relapse (within 1 to 3 years) during treatment.

Estrogen Receptor and Progesterone Receptor As Predictive Biomarkers of Response to Endocrine Therapy: A Prospectively Powered Pathology Study in the Tamoxifen and Exemestane Adjuvant Multinational Trial

PubMed Central

Bartlett, John M.S.; Brookes, Cassandra L.; Robson, Tammy; van de Velde, Cornelis J.H.; Billingham, Lucinda J.; Campbell, Fiona M.; Grant, Margaret; Hasenburg, Annette; Hille, Elysée T.M.; Kay, Charlene; Kieback, Dirk G.; Putter, Hein; Markopoulos, Christos; Kranenbarg, Elma Meershoek-Klein; Mallon, Elizabeth A.; Dirix, Luc; Seynaeve, Caroline; Rea, Daniel

2011-01-01

Purpose The Tamoxifen and Exemestane Adjuvant Multinational (TEAM) trial included a prospectively planned pathology substudy testing the predictive value of progesterone receptor (PgR) expression for outcome of estrogen receptor–positive (ER-positive) early breast cancer treated with exemestane versus tamoxifen. Patients and Methods Pathology blocks from 4,781 TEAM patients randomly assigned to exemestane versus tamoxifen followed by exemestane for 5 years of total therapy were collected centrally, and tissue microarrays were constructed from samples from 4,598 patients. Quantitative analysis of hormone receptors (ER and PgR) was performed by using image analysis and immunohistochemistry, and the results were linked to outcome data from the main TEAM trial and analyzed relative to disease-free survival and treatment. Results Of 4,325 eligible ER-positive patients, 23% were PgR-poor (Allred < 4) and 77% were PgR- rich (Allred ≥ 5). No treatment-by-marker effect for PgR was observed for exemestane versus tamoxifen (PgR-rich hazard ratio [HR], 0.83; 95% CI, 0.65 to 1.05; PgR-poor HR, 0.85; 95% CI, 0.61 to 1.19; P = .88 for interaction). Both PgR and ER expression were associated with patient prognosis in univariate (PgR HR, 0.53; 95% CI, 0.43 to 0.65; P < .001; ER HR, 0.66; 95% CI, 0.51 to 0.86; P = .002), and multivariate analyses (P < .001 and P = .001, respectively). A trend toward a treatment-by-marker effect for ER-rich patients was observed. Conclusion Preferential exemestane versus tamoxifen treatment benefit was not predicted by PgR expression; conversely, patients with ER-rich tumors may derive additional benefit from exemestane. Quantitative analysis of ER and PgR expression provides highly significant information on risk of early relapse (within 1 to 3 years) during treatment. PMID:21422407

Systematic Evaluation of Wajima Superposition (Steady-State Concentration to Mean Residence Time) in the Estimation of Human Intravenous Pharmacokinetic Profile.

PubMed

Lombardo, Franco; Berellini, Giuliano; Labonte, Laura R; Liang, Guiqing; Kim, Sean

2016-03-01

We present a systematic evaluation of the Wajima superpositioning method to estimate the human intravenous (i.v.) pharmacokinetic (PK) profile based on a set of 54 marketed drugs with diverse structure and range of physicochemical properties. We illustrate the use of average of "best methods" for the prediction of clearance (CL) and volume of distribution at steady state (VDss) as described in our earlier work (Lombardo F, Waters NJ, Argikar UA, et al. J Clin Pharmacol. 2013;53(2):178-191; Lombardo F, Waters NJ, Argikar UA, et al. J Clin Pharmacol. 2013;53(2):167-177). These methods provided much more accurate prediction of human PK parameters, yielding 88% and 70% of the prediction within 2-fold error for VDss and CL, respectively. The prediction of human i.v. profile using Wajima superpositioning of rat, dog, and monkey time-concentration profiles was tested against the observed human i.v. PK using fold error statistics. The results showed that 63% of the compounds yielded a geometric mean of fold error below 2-fold, and an additional 19% yielded a geometric mean of fold error between 2- and 3-fold, leaving only 18% of the compounds with a relatively poor prediction. Our results showed that good superposition was observed in any case, demonstrating the predictive value of the Wajima approach, and that the cause of poor prediction of human i.v. profile was mainly due to the poorly predicted CL value, while VDss prediction had a minor impact on the accuracy of human i.v. profile prediction. Copyright © 2016. Published by Elsevier Inc.

A hybrid localization technique for patient tracking.

PubMed

Rodionov, Denis; Kolev, George; Bushminkin, Kirill

2013-01-01

Nowadays numerous technologies are employed for tracking patients and assets in hospitals or nursing homes. Each of them has advantages and drawbacks. For example, WiFi localization has relatively good accuracy but cannot be used in case of power outage or in the areas with poor WiFi coverage. Magnetometer positioning or cellular network does not have such problems but they are not as accurate as localization with WiFi. This paper describes technique that simultaneously employs different localization technologies for enhancing stability and average accuracy of localization. The proposed algorithm is based on fingerprinting method paired with data fusion and prediction algorithms for estimating the object location. The core idea of the algorithm is technology fusion using error estimation methods. For testing accuracy and performance of the algorithm testing simulation environment has been implemented. Significant accuracy improvement was showed in practical scenarios.

Wildfire simulation using LES with synthetic-velocity SGS models

NASA Astrophysics Data System (ADS)

McDonough, J. M.; Tang, Tingting

2016-11-01

Wildland fires are becoming more prevalent and intense worldwide as climate change leads to warmer, drier conditions; and large-eddy simulation (LES) is receiving increasing attention for fire spread predictions as computing power continues to improve (see, e.g.,). We report results from wildfire simulations over general terrain employing implicit LES for solution of the incompressible Navier-Stokes (N.-S.) and thermal energy equations with Boussinesq approximation, altered with Darcy, Forchheimer and Brinkman extensions, to represent forested regions as porous media with varying (in both space and time) porosity and permeability. We focus on subgrid-scale (SGS) behaviors computed with a synthetic-velocity model, a discrete dynamical system, based on the poor man's N.-S. equations and investigate the ability of this model to produce fire whirls (tornadoes of fire) at the (unresolved) SGS level. Professor, Mechanical Engineering and Mathematics.

Flow-Boiling Critical Heat Flux Experiments Performed in Reduced Gravity

NASA Technical Reports Server (NTRS)

Hasan, Mohammad M.; Mudawar, Issam

2005-01-01

Poor understanding of flow boiling in microgravity has recently emerged as a key obstacle to the development of many types of power generation and advanced life support systems intended for space exploration. The critical heat flux (CHF) is perhaps the most important thermal design parameter for boiling systems involving both heatflux-controlled devices and intense heat removal. Exceeding the CHF limit can lead to permanent damage, including physical burnout of the heat-dissipating device. The importance of the CHF limit creates an urgent need to develop predictive design tools to ensure both the safe and reliable operation of a two-phase thermal management system under the reduced-gravity (like that on the Moon and Mars) and microgravity environments of space. At present, very limited information is available on flow-boiling heat transfer and the CHF under these conditions.

Core solidification and dynamo evolution in a mantle-stripped planetesimal

NASA Astrophysics Data System (ADS)

Scheinberg, A.; Elkins-Tanton, L. T.; Schubert, G.; Bercovici, D.

2016-01-01

The physical processes active during the crystallization of a low-pressure, low-gravity planetesimal core are poorly understood but have implications for asteroidal magnetic fields and large-scale asteroidal structure. We consider a core with only a thin silicate shell, which could be analogous to some M-type asteroids including Psyche, and use a parameterized thermal model to predict a solidification timeline and the resulting chemical profile upon complete solidification. We then explore the potential strength and longevity of a dynamo in the planetesimal's early history. We find that cumulate inner core solidification would be capable of sustaining a dynamo during solidification, but less power would be available for a dynamo in an inward dendritic solidification scenario. We also model and suggest limits on crystal settling and compaction of a possible cumulate inner core.

Fixing the War Powers

DTIC Science & Technology

1992-04-01

strength and unity. Third, such a divided arrangement comported with the perceived need to resurrect balanced government where neither branch could...Either way, King’s statement comports with the framers’ view of the President’s war powers. Despite the poor record, one may fairly conclude that this...the model for the war powers comports with the framers’ intellectual foundations. They divided the powers between two coordinate branches to prevent

POWER/SSE Web Access Data

Atmospheric Science Data Center

2018-06-25

Description:  Obtain Prediction of Worldwide Energy Resource (POWER) data The Prediction of Worldwide Energy ... (POWER) project was initiated to improve upon the current renewable energy data set and to create new data sets from new satellite ...

Research on prediction of agricultural machinery total power based on grey model optimized by genetic algorithm

NASA Astrophysics Data System (ADS)

Xie, Yan; Li, Mu; Zhou, Jin; Zheng, Chang-zheng

2009-07-01

Agricultural machinery total power is an important index to reflex and evaluate the level of agricultural mechanization. It is the power source of agricultural production, and is the main factors to enhance the comprehensive agricultural production capacity expand production scale and increase the income of the farmers. Its demand is affected by natural, economic, technological and social and other "grey" factors. Therefore, grey system theory can be used to analyze the development of agricultural machinery total power. A method based on genetic algorithm optimizing grey modeling process is introduced in this paper. This method makes full use of the advantages of the grey prediction model and characteristics of genetic algorithm to find global optimization. So the prediction model is more accurate. According to data from a province, the GM (1, 1) model for predicting agricultural machinery total power was given based on the grey system theories and genetic algorithm. The result indicates that the model can be used as agricultural machinery total power an effective tool for prediction.

Artificial neural network classifier predicts neuroblastoma patients' outcome.

PubMed

Cangelosi, Davide; Pelassa, Simone; Morini, Martina; Conte, Massimo; Bosco, Maria Carla; Eva, Alessandra; Sementa, Angela Rita; Varesio, Luigi

2016-11-08

More than fifty percent of neuroblastoma (NB) patients with adverse prognosis do not benefit from treatment making the identification of new potential targets mandatory. Hypoxia is a condition of low oxygen tension, occurring in poorly vascularized tissues, which activates specific genes and contributes to the acquisition of the tumor aggressive phenotype. We defined a gene expression signature (NB-hypo), which measures the hypoxic status of the neuroblastoma tumor. We aimed at developing a classifier predicting neuroblastoma patients' outcome based on the assessment of the adverse effects of tumor hypoxia on the progression of the disease. Multi-layer perceptron (MLP) was trained on the expression values of the 62 probe sets constituting NB-hypo signature to develop a predictive model for neuroblastoma patients' outcome. We utilized the expression data of 100 tumors in a leave-one-out analysis to select and construct the classifier and the expression data of the remaining 82 tumors to test the classifier performance in an external dataset. We utilized the Gene set enrichment analysis (GSEA) to evaluate the enrichment of hypoxia related gene sets in patients predicted with "Poor" or "Good" outcome. We utilized the expression of the 62 probe sets of the NB-Hypo signature in 182 neuroblastoma tumors to develop a MLP classifier predicting patients' outcome (NB-hypo classifier). We trained and validated the classifier in a leave-one-out cross-validation analysis on 100 tumor gene expression profiles. We externally tested the resulting NB-hypo classifier on an independent 82 tumors' set. The NB-hypo classifier predicted the patients' outcome with the remarkable accuracy of 87 %. NB-hypo classifier prediction resulted in 2 % classification error when applied to clinically defined low-intermediate risk neuroblastoma patients. The prediction was 100 % accurate in assessing the death of five low/intermediated risk patients. GSEA of tumor gene expression profile demonstrated the hypoxic status of the tumor in patients with poor prognosis. We developed a robust classifier predicting neuroblastoma patients' outcome with a very low error rate and we provided independent evidence that the poor outcome patients had hypoxic tumors, supporting the potential of using hypoxia as target for neuroblastoma treatment.

Predictors of poor adherence to treatment in inpatients with bipolar and psychotic spectrum disorders.

PubMed

Niolu, Cinzia; Barone, Ylenia; Bianciardi, Emanuela; Ribolsi, Michele; Marchetta, Claudia; Robone, Camilla; Ambrosio, Antonio; Sarchiola, Luca; Reggiardo, Giorgio; Lorenzo, Giorgio Di; Siracusano, Alberto

2015-01-01

The aim of this study was to assess possible predictors of poor adherence in patients with a diagnosis of schizophrenia-spectrum disorders (SD) or bipolar disorder (BD) and to evaluate the roles of attachment style and caregivers as predictive factors of adherence. The sample was composed of 178 voluntarily hospitalized inpatients: 89 diagnosed with BD (I, II), 89 with SD and other schizophrenia-spectrum disorders. All patients enrolled in the study were assessed for adherence, psychopathology, attachment style, presence of caregiver, subjective well-being during pharmacological treatment with neuroleptics, side effects following therapy, subjective attitude towards drugs, global functioning and quality of life. In patients with SD, non-adherence was associated with the absence of a caregiver, fewer years of treatment, poor insight and attitude towards drugs and fearful dimensions of attachment. In patients with BD, poor insight, anxious and social avoidant temperament traits, together with a high sense of self efficacy, were related to non-adherence. Diagnosis, type of medication and side effects were not predictive factors of adherence in either group. Interestingly, some temperament traits and dimensions of attachment predict non-adherence, indicating differences between patients with SD and BD. Considering these predictors of non-adherence and assessing adherence at the time of admission for relapse could be useful to plan an early and tailored “treatment adherence”, along with other therapeutic strategies, for patients using these predictive factors. The role of caregiver proved particularly important in relation to the therapeutic alliance. Attachment style may play a key role in predicting adherence through the therapeutic alliance with both patients and caregivers.

Phasic dopamine release in the rat nucleus accumbens predicts approach and avoidance performance

PubMed Central

Gentry, Ronny N.; Lee, Brian; Roesch, Matthew R.

2016-01-01

Dopamine (DA) is critical for reward processing, but significantly less is known about its role in punishment avoidance. Using a combined approach-avoidance task, we measured phasic DA release in the nucleus accumbens (NAc) of rats during presentation of cues that predicted reward, punishment or neutral outcomes and investigated individual differences based on avoidance performance. Here we show that DA release within a single microenvironment is higher for reward and avoidance cues compared with neutral cues and positively correlated with poor avoidance behaviour. We found that DA release delineates trial-type during sessions with good avoidance but is non-selective during poor avoidance, with high release correlating with poor performance. These data demonstrate that phasic DA is released during cued approach and avoidance within the same microenvironment and abnormal processing of value signals is correlated with poor performance. PMID:27786172

Defining Social Class Across Time and Between Groups.

PubMed

Cohen, Dov; Shin, Faith; Liu, Xi; Ondish, Peter; Kraus, Michael W

2017-11-01

We examined changes over four decades and between ethnic groups in how people define their social class. Changes included the increasing importance of income, decreasing importance of occupational prestige, and the demise of the "Victorian bargain," in which poor people who subscribed to conservative sexual and religious norms could think of themselves as middle class. The period also saw changes (among Whites) and continuity (among Black Americans) in subjective status perceptions. For Whites (and particularly poor Whites), their perceptions of enhanced social class were greatly reduced. Poor Whites now view their social class as slightly but significantly lower than their poor Black and Latino counterparts. For Black respondents, a caste-like understanding of social class persisted, as they continued to view their class standing as relatively independent of their achieved education, income, and occupation. Such achievement indicators, however, predicted Black respondents' self-esteem more than they predicted self-esteem for any other group.

Higher leukocyte count predicts 3-month poor outcome of ruptured cerebral aneurysms.

PubMed

Yao, Pei-Sen; Chen, Guo-Rong; Xie, Xue-Ling; Shang-Guan, Huang-Cheng; Gao, Jin-Zhen; Lin, Yuan-Xiang; Zheng, Shu-Fa; Lin, Zhang-Ya; Kang, De-Zhi

2018-04-11

It is not fully established whether leukocyte can predict the poor outcome for ruptured cerebral aneurysms (CA) or not. Here, we retrospectively analyzed the clinical data of 428 patients with ruptured CA between 2010 and 2015. Patients' demographic data, including gender, age, history of smoking, alcohol, hypertension, diabetes and hypercholesterolemia, Hunt-Hess and Fisher grade, occurrence of hydrocephalus, aneurysm location, time to surgery, delayed ischemic neurological deficit (DIND) and peak leukocyte of blood test from day 1 to 3 after aneurysmal rupture were recorded and analyzed. In the multivariable analysis model, gender, Fisher grade, time to surgery and hydrocephalus were not relevant to poor outcome. However, Hunt-Hess grade, DIND and preoperative leukocyte count (>13.84 × 10 9 /L) were significantly associated with adverse outcome. The respective increased risks were 5.2- (OR5.24, 95% CI 1.67-16.50, p = 0.005), 6.2-(OR 6.24, 95% CI 3.55-10.99, p < 0.001) and 10.9-fold (OR 9.35, 95% CI 5.98-19.97, p < 0.001). The study revealed that Hunt-Hess grade, DIND and preoperative leukocyte count (>13.84 × 10 9 /L) were independent risk factors for poor outcome of ruptured CA at 3 months. Higher leukocyte count is a convenient and useful marker to predict 3-month poor outcome for ruptured CA.

Poor fluorinated graphene sheets carboxymethylcellulose polymer composite mode locker for erbium doped fiber laser

NASA Astrophysics Data System (ADS)

Mou, Chengbo; Arif, Raz; Lobach, Anatoly S.; Khudyakov, Dmitry V.; Spitsina, Nataliya G.; Kazakov, Valery A.; Turitsyn, Sergei; Rozhin, Aleksey

2015-02-01

We report poor fluorinated graphene sheets produced by thermal exfoliation embedding in carboxymethylcellulose polymer composite (GCMC) as an efficient mode locker for erbium doped fiber laser. Two GCMC mode lockers with different concentration have been fabricated. The GCMC based mode locked fiber laser shows stable soliton output pulse shaping with repetition rate of 28.5 MHz and output power of 5.5 mW was achieved with the high concentration GCMC, while a slightly higher output power of 6.9 mW was obtained using the low concentration GCMC mode locker.

Poor fluorinated graphene sheets carboxymethylcellulose polymer composite mode locker for erbium doped fiber laser

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

Mou, Chengbo, E-mail: mouc1@aston.ac.uk, E-mail: a.rozhin@aston.ac.uk; Turitsyn, Sergei; Rozhin, Aleksey, E-mail: mouc1@aston.ac.uk, E-mail: a.rozhin@aston.ac.uk

We report poor fluorinated graphene sheets produced by thermal exfoliation embedding in carboxymethylcellulose polymer composite (GCMC) as an efficient mode locker for erbium doped fiber laser. Two GCMC mode lockers with different concentration have been fabricated. The GCMC based mode locked fiber laser shows stable soliton output pulse shaping with repetition rate of 28.5 MHz and output power of 5.5 mW was achieved with the high concentration GCMC, while a slightly higher output power of 6.9 mW was obtained using the low concentration GCMC mode locker.

Integrated Wind Power Planning Tool

NASA Astrophysics Data System (ADS)

Rosgaard, Martin; Giebel, Gregor; Skov Nielsen, Torben; Hahmann, Andrea; Sørensen, Poul; Madsen, Henrik

2013-04-01

This poster presents the current state of the public service obligation (PSO) funded project PSO 10464, with the title "Integrated Wind Power Planning Tool". The goal is to integrate a mesoscale numerical weather prediction (NWP) model with purely statistical tools in order to assess wind power fluctuations, with focus on long term power system planning for future wind farms as well as short term forecasting for existing wind farms. Currently, wind power fluctuation models are either purely statistical or integrated with NWP models of limited resolution. Using the state-of-the-art mesoscale NWP model Weather Research & Forecasting model (WRF) the forecast error is sought quantified in dependence of the time scale involved. This task constitutes a preparative study for later implementation of features accounting for NWP forecast errors in the DTU Wind Energy maintained Corwind code - a long term wind power planning tool. Within the framework of PSO 10464 research related to operational short term wind power prediction will be carried out, including a comparison of forecast quality at different mesoscale NWP model resolutions and development of a statistical wind power prediction tool taking input from WRF. The short term prediction part of the project is carried out in collaboration with ENFOR A/S; a Danish company that specialises in forecasting and optimisation for the energy sector. The integrated prediction model will allow for the description of the expected variability in wind power production in the coming hours to days, accounting for its spatio-temporal dependencies, and depending on the prevailing weather conditions defined by the WRF output. The output from the integrated short term prediction tool constitutes scenario forecasts for the coming period, which can then be fed into any type of system model or decision making problem to be solved. The high resolution of the WRF results loaded into the integrated prediction model will ensure a high accuracy data basis is available for use in the decision making process of the Danish transmission system operator. The need for high accuracy predictions will only increase over the next decade as Denmark approaches the goal of 50% wind power based electricity in 2025 from the current 20%.

Method for predicting water demand for crop uses in New Jersey in 1990, 2000, 2010, and 2020, and for estimating water use for livestock and selected sectors of the food-processing industry in New Jersey in 1987

USGS Publications Warehouse

Clawges, R.M.; Titus, E.O.

1993-01-01

A method was developed to predict water demand for crop uses in New Jersey. A separate method was developed to estimate water use for livestock and selected sectors of the food-processing industry in 1987. Predictions of water demand for field- grown crops in New Jersey were made for 1990, 2000, 2010, and 2020 under three climatological scenarios: (1) wet year, (2) average year, and (3) drought year. These estimates ranged from 4.10 times 10 to the 9th power to 16.82 times 10 to the 9th power gal (gallons). Irrigation amounts calculated for the three climatological scenarios by using a daily water-balance model were multiplied by predicted numbers of irrigated acreage. Irrigated acreage was predicted from historical crop-irrigation data and from predictions of harvested acreage produced by using a statistical model relating population to harvested acreage. Predictions of water demand for cranberries and container-grown nursery crops also were made for 1990, 2000, 2010, and 2020. Predictions of water demand under the three climatological scenarios were made for container- grown nursery crops, but not for cranberries, because water demand for cranberries varies little in response to climatological factors. Water demand for cranberries was predicted to remain constant at 4.43 times 10 to the 9th power gal through the year 2020. Predictions of water demand for container-grown nursery crops ranged from 1.89 times 10 to the 9th power to 3.63 times 10 to the 9th power gal. Water-use for livestock in 1987 was estimated to be 0.78 times 10 to the 9th power gal, and water use for selected sectors of the food-processing industry was estimated to be 3.75 times 10 to the 9th power gal.

Predictive factors for poor prognosis febrile neutropenia.

PubMed

Ahn, Shin; Lee, Yoon-Seon

2012-07-01

Most patients with chemotherapy-induced febrile neutropenia recover rapidly without serious complications. However, it still remains a life-threatening treatment-related toxicity, and is associated with dose reductions and delays of chemotherapeutic agents that may compromise treatment outcomes. Recent developments of risk stratification enabled early discharge with oral antibiotics for low-risk patients. However, even in low-risk patients, medical complications including bacteremia could happen. The authors reviewed recent literature to provide an update on research regarding predictive factors for poor prognosis in patients with febrile neutropenia. Various prognostic factors have been suggested with controversies. Hematological parameters, prophylactic measurements and patient-specific risk factors showed inconsistent results. MASCC risk-index score, which was originally developed to identify low-risk patients, in turn showed that the lower the MASCC score, the poorer the prognosis of febrile neutropenia, with very low levels (<15), the rate of complications was high. Patients with severe sepsis and septic shock commonly had procalcitonin concentration above 2.0 ng/ml, and this level should be considered at high risk of poor prognosis. Lower MASCC score and higher procalcitonin concentration can predict poor outcomes in febrile neutropenia. More research is required with regard to the other factors showing controversies.

Predicting when biliary excretion of parent drug is a major route of elimination in humans.

PubMed

Hosey, Chelsea M; Broccatelli, Fabio; Benet, Leslie Z

2014-09-01

Biliary excretion is an important route of elimination for many drugs, yet measuring the extent of biliary elimination is difficult, invasive, and variable. Biliary elimination has been quantified for few drugs with a limited number of subjects, who are often diseased patients. An accurate prediction of which drugs or new molecular entities are significantly eliminated in the bile may predict potential drug-drug interactions, pharmacokinetics, and toxicities. The Biopharmaceutics Drug Disposition Classification System (BDDCS) characterizes significant routes of drug elimination, identifies potential transporter effects, and is useful in understanding drug-drug interactions. Class 1 and 2 drugs are primarily eliminated in humans via metabolism and will not exhibit significant biliary excretion of parent compound. In contrast, class 3 and 4 drugs are primarily excreted unchanged in the urine or bile. Here, we characterize the significant elimination route of 105 orally administered class 3 and 4 drugs. We introduce and validate a novel model, predicting significant biliary elimination using a simple classification scheme. The model is accurate for 83% of 30 drugs collected after model development. The model corroborates the observation that biliarily eliminated drugs have high molecular weights, while demonstrating the necessity of considering route of administration and extent of metabolism when predicting biliary excretion. Interestingly, a predictor of potential metabolism significantly improves predictions of major elimination routes of poorly metabolized drugs. This model successfully predicts the major elimination route for poorly permeable/poorly metabolized drugs and may be applied prior to human dosing.

Magnetic resonance imaging-detected tumor response for locally advanced rectal cancer predicts survival outcomes: MERCURY experience.

PubMed

Patel, Uday B; Taylor, Fiona; Blomqvist, Lennart; George, Christopher; Evans, Hywel; Tekkis, Paris; Quirke, Philip; Sebag-Montefiore, David; Moran, Brendan; Heald, Richard; Guthrie, Ashley; Bees, Nicola; Swift, Ian; Pennert, Kjell; Brown, Gina

2011-10-01

To assess magnetic resonance imaging (MRI) and pathologic staging after neoadjuvant therapy for rectal cancer in a prospectively enrolled, multicenter study. In a prospective cohort study, 111 patients who had rectal cancer treated by neoadjuvant therapy were assessed for response by MRI and pathology staging by T, N and circumferential resection margin (CRM) status. Tumor regression grade (TRG) was also assessed by MRI. Overall survival (OS) was estimated by using the Kaplan-Meier product-limit method, and Cox proportional hazards models were used to determine associations between staging of good and poor responders on MRI or pathology and survival outcomes after controlling for patient characteristics. On multivariate analysis, the MRI-assessed TRG (mrTRG) hazard ratios (HRs) were independently significant for survival (HR, 4.40; 95% CI, 1.65 to 11.7) and disease-free survival (DFS; HR, 3.28; 95% CI, 1.22 to 8.80). Five-year survival for poor mrTRG was 27% versus 72% (P = .001), and DFS for poor mrTRG was 31% versus 64% (P = .007). Preoperative MRI-predicted CRM independently predicted local recurrence (LR; HR, 4.25; 95% CI, 1.45 to 12.51). Five-year survival for poor post-treatment pathologic T stage (ypT) was 39% versus 76% (P = .001); DFS for the same was 38% versus 84% (P = .001); and LR for the same was 27% versus 6% (P = .018). The 5-year survival for involved pCRM was 30% versus 59% (P = .001); DFS, 28 versus 62% (P = .02); and LR, 56% versus 10% (P = .001). Pathology node status did not predict outcomes. MRI assessment of TRG and CRM are imaging markers that predict survival outcomes for good and poor responders and provide an opportunity for the multidisciplinary team to offer additional treatment options before planning definitive surgery. Postoperative histopathology assessment of ypT and CRM but not post-treatment N status were important postsurgical predictors of outcome.

Usefulness of Midregional Proadrenomedullin to Predict Poor Outcome in Patients with Community Acquired Pneumonia

PubMed Central

Gordo-Remartínez, Susana; Sevillano-Fernández, José A.; Álvarez-Sala, Luis A.; Andueza-Lillo, Juan A.; de Miguel-Yanes, José M.

2015-01-01

Background midregional proadrenomedullin (MR-proADM) is a prognostic biomarker in patients with community-acquired pneumonia (CAP). We sought to confirm whether MR-proADM added to Pneumonia Severity Index (PSI) improves the potential prognostic value of PSI alone, and tested to what extent this combination could be useful in predicting poor outcome of patients with CAP in an Emergency Department (ED). Methods Consecutive patients diagnosed with CAP were enrolled in this prospective, single-centre, observational study. We analyzed the ability of MR-proADM added to PSI to predict poor outcome using receiver operating characteristic (ROC) curves, logistic regression and risk reclassification and comparing it with the ability of PSI alone. The primary outcome was “poor outcome”, defined as the incidence of an adverse event (ICU admission, hospital readmission, or mortality at 30 days after CAP diagnosis). Results 226 patients were included; 33 patients (14.6%) reached primary outcome. To predict primary outcome the highest area under curve (AUC) was found for PSI (0.74 [0.64-0.85]), which was not significantly higher than for MR-proADM (AUC 0.72 [0.63-0.81, p > 0.05]). The combination of PSI and MR-proADM failed to improve the predictive potential of PSI alone (AUC 0.75 [0.65-0.85, p=0.56]). Ten patients were appropriately reclassified when the combined PSI and MR-proADM model was used as compared with the model of PSI alone. Net reclassification improvement (NRI) index was statistically significant (7.69%, p = 0.03) with an improvement percentage of 3.03% (p = 0.32) for adverse event, and 4.66% (P = 0.02) for no adverse event. Conclusion MR-proADM in combination with PSI may be helpful in individual risk stratification for short-term poor outcome of CAP patients, allowing a better reclassification of patients compared with PSI alone. PMID:26030588

Post-anoxic quantitative MRI changes may predict emergence from coma and functional outcomes at discharge.

PubMed

Reynolds, Alexandra S; Guo, Xiaotao; Matthews, Elizabeth; Brodie, Daniel; Rabbani, Leroy E; Roh, David J; Park, Soojin; Claassen, Jan; Elkind, Mitchell S V; Zhao, Binsheng; Agarwal, Sachin

2017-08-01

Traditional predictors of neurological prognosis after cardiac arrest are unreliable after targeted temperature management. Absence of pupillary reflexes remains a reliable predictor of poor outcome. Diffusion-weighted imaging has emerged as a potential predictor of recovery, and here we compare imaging characteristics to pupillary exam. We identified 69 patients who had MRIs within seven days of arrest and used a semi-automated algorithm to perform quantitative volumetric analysis of apparent diffusion coefficient (ADC) sequences at various thresholds. Area under receiver operating characteristic curves (ROC-AUC) were estimated to compare predictive values of quantitative MRI with pupillary exam at days 3, 5 and 7 post-arrest, for persistence of coma and functional outcomes at discharge. Cerebral Performance Category scores of 3-4 were considered poor outcome. Excluding patients where life support was withdrawn, ≥2.8% diffusion restriction of the entire brain at an ADC of ≤650×10 -6 m 2 /s was 100% specific and 68% sensitive for failure to wake up from coma before discharge. The ROC-AUC of ADC changes at ≤450×10 -6 mm 2 /s and ≤650×10 -6 mm 2 /s were significantly superior in predicting failure to wake up from coma compared to bilateral absence of pupillary reflexes. Among survivors, >0.01% of diffusion restriction of the entire brain at an ADC ≤450×10 -6 m 2 /s was 100% specific and 46% sensitive for poor functional outcome at discharge. The ROC curve predicting poor functional outcome at ADC ≤450×10 -6 mm 2 /s had an AUC of 0.737 (0.574-0.899, p=0.04). Post-anoxic diffusion changes using quantitative brain MRI may aid in predicting persistent coma and poor functional outcomes at hospital discharge. Copyright © 2017 Elsevier B.V. All rights reserved.

Predicting Financial Distress and Closure in Rural Hospitals.

PubMed

Holmes, George M; Kaufman, Brystana G; Pink, George H

2017-06-01

Annual rates of rural hospital closure have been increasing since 2010, and hospitals that close have poor financial performance relative to those that remain open. This study develops and validates a latent index of financial distress to forecast the probability of financial distress and closure within 2 years for rural hospitals. Hospital and community characteristics are used to predict the risk of financial distress 2 years in the future. Financial and community data were drawn for 2,466 rural hospitals from 2000 through 2013. We tested and validated a model predicting a latent index of financial distress (FDI), measured by unprofitability, equity decline, insolvency, and closure. Using the predicted FDI score, hospitals are assigned to high, medium-high, medium-low, and low risk of financial distress for use by practitioners. The FDI forecasts 8.01% of rural hospitals to be at high risk of financial distress in 2015, 16.3% as mid-high, 46.8% as mid-low, and 28.9% as low risk. The rate of closure for hospitals in the high-risk category is 4 times the rate in the mid-high category and 28 times that in the mid-low category. The ability of the FDI to discriminate hospitals experiencing financial distress is supported by a c-statistic of .74 in a validation sample. This methodology offers improved specificity and predictive power relative to existing measures of financial distress applied to rural hospitals. This risk assessment tool may inform programs at the federal, state, and local levels that provide funding or support to rural hospitals. © 2016 National Rural Health Association.

Thermal niche estimators and the capability of poor dispersal species to cope with climate change

PubMed Central

Sánchez-Fernández, David; Rizzo, Valeria; Cieslak, Alexandra; Faille, Arnaud; Fresneda, Javier; Ribera, Ignacio

2016-01-01

For management strategies in the context of global warming, accurate predictions of species response are mandatory. However, to date most predictions are based on niche (bioclimatic) models that usually overlook biotic interactions, behavioral adjustments or adaptive evolution, and assume that species can disperse freely without constraints. The deep subterranean environment minimises these uncertainties, as it is simple, homogeneous and with constant environmental conditions. It is thus an ideal model system to study the effect of global change in species with poor dispersal capabilities. We assess the potential fate of a lineage of troglobitic beetles under global change predictions using different approaches to estimate their thermal niche: bioclimatic models, rates of thermal niche change estimated from a molecular phylogeny, and data from physiological studies. Using bioclimatic models, at most 60% of the species were predicted to have suitable conditions in 2080. Considering the rates of thermal niche change did not improve this prediction. However, physiological data suggest that subterranean species have a broad thermal tolerance, allowing them to stand temperatures never experienced through their evolutionary history. These results stress the need of experimental approaches to assess the capability of poor dispersal species to cope with temperatures outside those they currently experience. PMID:26983802

Prediction of Outcome From Adult Bacterial Meningitis in a High-HIV-Seroprevalence, Resource-Poor Setting Using the Malawi Adult Meningitis Score (MAMS).

PubMed

Wall, Emma C; Mukaka, Mavuto; Scarborough, Matthew; Ajdukiewicz, Katherine M A; Cartwright, Katharine E; Nyirenda, Mulinda; Denis, Brigitte; Allain, Theresa J; Faragher, Brian; Lalloo, David G; Heyderman, Robert S

2017-02-15

Acute bacterial meningitis (ABM) in adults residing in resource-poor countries is associated with mortality rates >50%. To improve outcome, interventional trials and standardized clinical algorithms are urgently required. To optimize these processes, we developed and validated an outcome prediction tool to identify ABM patients at greatest risk of death. We derived a nomogram using mortality predictors derived from a logistic regression model of a discovery database of adult Malawian patients with ABM (n = 523 [65%] cerebrospinal fluid [CSF] culture positive). We validated the nomogram internally using a bootstrap procedure and subsequently used the nomogram scores to further interpret the effects of adjunctive dexamethasone and glycerol using clinical trial data from Malawi. ABM mortality at 6-week follow-up was 54%. Five of 15 variables tested were strongly associated with poor outcome (CSF culture positivity, CSF white blood cell count, hemoglobin, Glasgow Coma Scale, and pulse rate), and were used in the derivation of the Malawi Adult Meningitis Score (MAMS) nomogram. The C-index (area under the curve) was 0.76 (95% confidence interval, .71-.80) and calibration was good (Hosmer-Lemeshow C-statistic = 5.48, df = 8, P = .705). Harmful effects of adjunctive glycerol were observed in groups with relatively low predicted risk of poor outcome (25%-50% risk): Case Fatality Rate of 21% in the placebo group and 52% in the glycerol group (P < .001). This effect was not seen with adjunctive dexamethasone. MAMS provides a novel tool for predicting prognosis and improving interpretation of ABM clinical trials by risk stratification in resource-poor settings. Whether MAMS can be applied to non-HIV-endemic countries requires further evaluation. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America.

Cross-sectional analysis of food choice frequency, sleep confounding beverages, and psychological distress predictors of sleep quality.

PubMed

Knowlden, Adam P; Burns, Maranda; Harcrow, Andy; Shewmake, Meghan E

2016-03-16

Poor sleep quality is a significant public health problem. The role of nutrition in predicting sleep quality is a relatively unexplored area of inquiry. The purpose of this study was to evaluate the capacity of 10 food choice categories, sleep confounding beverages, and psychological distress to predict the sleep quality of college students. A logistic regression model comprising 10 food choice variables (healthy proteins, unhealthy proteins, healthy dairy, unhealthy dairy, healthy grains, unhealthy grains, healthy fruits and vegetables, unhealthy empty calories, healthy beverages, unhealthy beverages), sleep confounding beverages (caffeinated/alcoholic beverages), as well as psychological distress (low, moderate, serious distress) was computed to determine the capacity of the variables to predict sleep quality (good/poor). The odds of poor sleep quality were 32.4% lower for each unit of increased frequency of healthy proteins consumed (p<0.001; OR=0.676), 14.1% lower for each unit of increased frequency of healthy dairy food choices consumed (p=0.024; OR=0.859), 13.1% higher for each unit of increased frequency of empty calorie food choices consumed (p=0.003; OR=1.131), and 107.3% higher for those classified in the moderate psychological distress (p=0.016; OR=2.073). Collectively, healthy proteins, healthy dairy, unhealthy empty calories, and moderate psychological distress were moderately predictive of sleep quality in the sample (Nagelkerke R2=23.8%). Results of the study suggested higher frequency of consumption of healthy protein and healthy dairy food choices reduced the odds of poor sleep quality, while higher consumption of empty calories and moderate psychological distress increased the odds of poor sleep quality.

Application of clustering analysis in the prediction of photovoltaic power generation based on neural network

NASA Astrophysics Data System (ADS)

Cheng, K.; Guo, L. M.; Wang, Y. K.; Zafar, M. T.

2017-11-01

In order to select effective samples in the large number of data of PV power generation years and improve the accuracy of PV power generation forecasting model, this paper studies the application of clustering analysis in this field and establishes forecasting model based on neural network. Based on three different types of weather on sunny, cloudy and rainy days, this research screens samples of historical data by the clustering analysis method. After screening, it establishes BP neural network prediction models using screened data as training data. Then, compare the six types of photovoltaic power generation prediction models before and after the data screening. Results show that the prediction model combining with clustering analysis and BP neural networks is an effective method to improve the precision of photovoltaic power generation.

Gbm.auto: A software tool to simplify spatial modelling and Marine Protected Area planning

PubMed Central

Officer, Rick; Clarke, Maurice; Reid, David G.; Brophy, Deirdre

2017-01-01

Boosted Regression Trees. Excellent for data-poor spatial management but hard to use Marine resource managers and scientists often advocate spatial approaches to manage data-poor species. Existing spatial prediction and management techniques are either insufficiently robust, struggle with sparse input data, or make suboptimal use of multiple explanatory variables. Boosted Regression Trees feature excellent performance and are well suited to modelling the distribution of data-limited species, but are extremely complicated and time-consuming to learn and use, hindering access for a wide potential user base and therefore limiting uptake and usage. BRTs automated and simplified for accessible general use with rich feature set We have built a software suite in R which integrates pre-existing functions with new tailor-made functions to automate the processing and predictive mapping of species abundance data: by automating and greatly simplifying Boosted Regression Tree spatial modelling, the gbm.auto R package suite makes this powerful statistical modelling technique more accessible to potential users in the ecological and modelling communities. The package and its documentation allow the user to generate maps of predicted abundance, visualise the representativeness of those abundance maps and to plot the relative influence of explanatory variables and their relationship to the response variables. Databases of the processed model objects and a report explaining all the steps taken within the model are also generated. The package includes a previously unavailable Decision Support Tool which combines estimated escapement biomass (the percentage of an exploited population which must be retained each year to conserve it) with the predicted abundance maps to generate maps showing the location and size of habitat that should be protected to conserve the target stocks (candidate MPAs), based on stakeholder priorities, such as the minimisation of fishing effort displacement. Gbm.auto for management in various settings By bridging the gap between advanced statistical methods for species distribution modelling and conservation science, management and policy, these tools can allow improved spatial abundance predictions, and therefore better management, decision-making, and conservation. Although this package was built to support spatial management of a data-limited marine elasmobranch fishery, it should be equally applicable to spatial abundance modelling, area protection, and stakeholder engagement in various scenarios. PMID:29216310

Child maltreatment, parent alcohol and drug-related problems, polydrug problems, and parenting practices: a test of gender differences and four theoretical perspectives.

PubMed

Locke, Thomas F; Newcomb, Michael

2004-03-01

The authors tested how adverse childhood experiences (child maltreatment and parent alcohol- and drug-related problems) and adult polydrug use (as a mediator) predict poor parenting in a community sample (237 mothers and 81 fathers). These relationships were framed within several theoretical perspectives, including observational learning, impaired functioning, self-medication, and parentification-pseudomaturity. Structural models revealed that child maltreatment predicted poor parenting practices among mothers. Parent alcohol- and drug-related problems had an indirect detrimental influence on mothers' parenting and practices through self-drug problems. Among fathers, emotional neglect experienced as a child predicted lack of parental warmth more parental neglect, and sexual abuse experienced as a child predicted a rejecting style of parenting.

Integrated modelling of H-mode pedestal and confinement in JET-ILW

NASA Astrophysics Data System (ADS)

Saarelma, S.; Challis, C. D.; Garzotti, L.; Frassinetti, L.; Maggi, C. F.; Romanelli, M.; Stokes, C.; Contributors, JET

2018-01-01

A pedestal prediction model Europed is built on the existing EPED1 model by coupling it with core transport simulation using a Bohm-gyroBohm transport model to self-consistently predict JET-ILW power scan for hybrid plasmas that display weaker power degradation than the IPB98(y, 2) scaling of the energy confinement time. The weak power degradation is reproduced in the coupled core-pedestal simulation. The coupled core-pedestal model is further tested for a 3.0 MA plasma with the highest stored energy achieved in JET-ILW so far, giving a prediction of the stored plasma energy within the error margins of the measured experimental value. A pedestal density prediction model based on the neutral penetration is tested on a JET-ILW database giving a prediction with an average error of 17% from the experimental data when a parameter taking into account the fuelling rate is added into the model. However the model fails to reproduce the power dependence of the pedestal density implying missing transport physics in the model. The future JET-ILW deuterium campaign with increased heating power is predicted to reach plasma energy of 11 MJ, which would correspond to 11-13 MW of fusion power in equivalent deuterium-tritium plasma but with isotope effects on pedestal stability and core transport ignored.

Prediction of High-Lift Flows using Turbulent Closure Models

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.; Gatski, Thomas B.; Ying, Susan X.; Bertelrud, Arild

1997-01-01

The flow over two different multi-element airfoil configurations is computed using linear eddy viscosity turbulence models and a nonlinear explicit algebraic stress model. A subset of recently-measured transition locations using hot film on a McDonnell Douglas configuration is presented, and the effect of transition location on the computed solutions is explored. Deficiencies in wake profile computations are found to be attributable in large part to poor boundary layer prediction on the generating element, and not necessarily inadequate turbulence modeling in the wake. Using measured transition locations for the main element improves the prediction of its boundary layer thickness, skin friction, and wake profile shape. However, using measured transition locations on the slat still yields poor slat wake predictions. The computation of the slat flow field represents a key roadblock to successful predictions of multi-element flows. In general, the nonlinear explicit algebraic stress turbulence model gives very similar results to the linear eddy viscosity models.

Millisecond Magnetar Birth Connects FRB 121102 to Superluminous Supernovae and Long-duration Gamma-Ray Bursts

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

Metzger, Brian D.; Margalit, Ben; Berger, Edo

Subarcsecond localization of the repeating fast radio burst FRB 121102 revealed its coincidence with a dwarf host galaxy and a steady (“quiescent”) nonthermal radio source. We show that the properties of the host galaxy are consistent with those of long-duration gamma-ray bursts (LGRB) and hydrogen-poor superluminous supernovae (SLSNe-I). Both LGRBs and SLSNe-I were previously hypothesized to be powered by the electromagnetic spin-down of newly formed, strongly magnetized neutron stars with millisecond birth rotation periods (“millisecond magnetars”). This motivates considering a scenario whereby the repeated bursts from FRB 121102 originate from a young magnetar remnant embedded within a young hydrogen-poor supernovamore » (SN) remnant. Requirements on the gigahertz free–free optical depth through the expanding SN ejecta (accounting for photoionization by the rotationally powered magnetar nebula), energetic constraints on the bursts, and constraints on the size of the quiescent source all point to an age of less than a few decades. The quiescent radio source can be attributed to synchrotron emission from the shock interaction between the fast outer layer of the supernova ejecta with the surrounding wind of the progenitor star, or the radio source can from deeper within the magnetar wind nebula as outlined in Metzger et al. Alternatively, the radio emission could be an orphan afterglow from an initially off-axis LGRB jet, though this might require the source to be too young. The young age of the source can be tested by searching for a time derivative of the dispersion measure and the predicted fading of the quiescent radio source. We propose future tests of the SLSNe-I/LGRB/FRB connection, such as searches for FRBs from nearby SLSNe-I/LGRBs on timescales of decades after their explosions.« less

Ultraviolet spectra of extreme nearby star-forming regions - approaching a local reference sample for JWST

NASA Astrophysics Data System (ADS)

Senchyna, Peter; Stark, Daniel P.; Vidal-García, Alba; Chevallard, Jacopo; Charlot, Stéphane; Mainali, Ramesh; Jones, Tucker; Wofford, Aida; Feltre, Anna; Gutkin, Julia

2017-12-01

Nearby dwarf galaxies provide a unique laboratory in which to test stellar population models below Z⊙/2. Such tests are particularly important for interpreting the surprising high-ionization ultraviolet (UV) line emission detected at z > 6 in recent years. We present HST/COS UV spectra of 10 nearby metal-poor star-forming galaxies selected to show He II emission in SDSS optical spectra. The targets span nearly a dex in gas-phase oxygen abundance (7.8 < 12 + log O/H < 8.5) and present uniformly large specific star formation rates (sSFR ∼102 Gyr-1). The UV spectra confirm that metal-poor stellar populations can power extreme nebular emission in high-ionization UV lines, reaching C III] equivalent widths comparable to those seen in systems at z ∼ 6-7. Our data reveal a marked transition in UV spectral properties with decreasing metallicity, with systems below 12 + log O/H ≲ 8.0 (Z/Z⊙ ≲ 1/5) presenting minimal stellar wind features and prominent nebular emission in He II and C IV. This is consistent with nearly an order of magnitude increase in ionizing photon production beyond the He+-ionizing edge relative to H-ionizing flux as metallicity decreases below a fifth solar, well in excess of standard stellar population synthesis predictions. Our results suggest that often-neglected sources of energetic radiation such as stripped binary products and very massive O-stars produce a sharper change in the ionizing spectrum with decreasing metallicity than expected. Consequently, nebular emission in C IV and He II powered by these stars may provide useful metallicity constraints in the reionization era.

Maximum predictive power and the superposition principle

NASA Technical Reports Server (NTRS)

Summhammer, Johann

1994-01-01

In quantum physics the direct observables are probabilities of events. We ask how observed probabilities must be combined to achieve what we call maximum predictive power. According to this concept the accuracy of a prediction must only depend on the number of runs whose data serve as input for the prediction. We transform each probability to an associated variable whose uncertainty interval depends only on the amount of data and strictly decreases with it. We find that for a probability which is a function of two other probabilities maximum predictive power is achieved when linearly summing their associated variables and transforming back to a probability. This recovers the quantum mechanical superposition principle.

Resting-state EEG, impulsiveness, and personality in daily and nondaily smokers.

PubMed

Rass, Olga; Ahn, Woo-Young; O'Donnell, Brian F

2016-01-01

Resting EEG is sensitive to transient, acute effects of nicotine administration and abstinence, but the chronic effects of smoking on EEG are poorly characterized. This study measures the resting EEG profile of chronic smokers in a non-deprived, non-peak state to test whether differences in smoking behavior and personality traits affect pharmaco-EEG response. Resting EEG, impulsiveness, and personality measures were collected from daily smokers (n=22), nondaily smokers (n=31), and non-smokers (n=30). Daily smokers had reduced resting delta and alpha EEG power and higher impulsiveness (Barratt Impulsiveness Scale) compared to nondaily smokers and non-smokers. Both daily and nondaily smokers discounted delayed rewards more steeply, reported lower conscientiousness (NEO-FFI), and reported greater disinhibition and experience seeking (Sensation Seeking Scale) than non-smokers. Nondaily smokers reported greater sensory hedonia than nonsmokers. Altered resting EEG power in daily smokers demonstrates differences in neural signaling that correlated with greater smoking behavior and dependence. Although nondaily smokers share some characteristics with daily smokers that may predict smoking initiation and maintenance, they differ on measures of impulsiveness and resting EEG power. Resting EEG in non-deprived chronic smokers provides a standard for comparison to peak and trough nicotine states and may serve as a biomarker for nicotine dependence, relapse risk, and recovery. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Improving consensus contact prediction via server correlation reduction.

PubMed

Gao, Xin; Bu, Dongbo; Xu, Jinbo; Li, Ming

2009-05-06

Protein inter-residue contacts play a crucial role in the determination and prediction of protein structures. Previous studies on contact prediction indicate that although template-based consensus methods outperform sequence-based methods on targets with typical templates, such consensus methods perform poorly on new fold targets. However, we find out that even for new fold targets, the models generated by threading programs can contain many true contacts. The challenge is how to identify them. In this paper, we develop an integer linear programming model for consensus contact prediction. In contrast to the simple majority voting method assuming that all the individual servers are equally important and independent, the newly developed method evaluates their correlation by using maximum likelihood estimation and extracts independent latent servers from them by using principal component analysis. An integer linear programming method is then applied to assign a weight to each latent server to maximize the difference between true contacts and false ones. The proposed method is tested on the CASP7 data set. If the top L/5 predicted contacts are evaluated where L is the protein size, the average accuracy is 73%, which is much higher than that of any previously reported study. Moreover, if only the 15 new fold CASP7 targets are considered, our method achieves an average accuracy of 37%, which is much better than that of the majority voting method, SVM-LOMETS, SVM-SEQ, and SAM-T06. These methods demonstrate an average accuracy of 13.0%, 10.8%, 25.8% and 21.2%, respectively. Reducing server correlation and optimally combining independent latent servers show a significant improvement over the traditional consensus methods. This approach can hopefully provide a powerful tool for protein structure refinement and prediction use.

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

PubMed Central

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

2009-01-01

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

Predictors of maternal health services utilization by poor, rural women: a comparative study in Indian States of Gujarat and Tamil Nadu.

PubMed

Vora, Kranti Suresh; Koblinsky, Sally A; Koblinsky, Marge A

2015-07-31

India leads all nations in numbers of maternal deaths, with poor, rural women contributing disproportionately to the high maternal mortality ratio. In 2005, India launched the world's largest conditional cash transfer scheme, Janani Suraksha Yojana (JSY), to increase poor women's access to institutional delivery, anticipating that facility-based birthing would decrease deaths. Indian states have taken different approaches to implementing JSY. Tamil Nadu adopted JSY with a reorganization of its public health system, and Gujarat augmented JSY with the state-funded Chiranjeevi Yojana (CY) scheme, contracting with private physicians for delivery services. Given scarce evidence of the outcomes of these approaches, especially in states with more optimal health indicators, this cross-sectional study examined the role of JSY/CY and other healthcare system and social factors in predicting poor, rural women's use of maternal health services in Gujarat and Tamil Nadu. Using the District Level Household Survey (DLHS)-3, the sample included 1584 Gujarati and 601 Tamil rural women in the lowest two wealth quintiles. Multivariate logistic regression analyses examined associations between JSY/CY and other salient health system, socio-demographic, and obstetric factors with three outcomes: adequate antenatal care, institutional delivery, and Cesarean-section. Tamil women reported greater use of maternal healthcare services than Gujarati women. JSY/CY participation predicted institutional delivery in Gujarat (AOR = 3.9), but JSY assistance failed to predict institutional delivery in Tamil Nadu, where mothers received some cash for home births under another scheme. JSY/CY assistance failed to predict adequate antenatal care, which was not incentivized. All-weather road access predicted institutional delivery in both Tamil Nadu (AOR = 3.4) and Gujarat (AOR = 1.4). Women's education predicted institutional delivery and Cesarean-section in Tamil Nadu, while husbands' education predicted institutional delivery in Gujarat. Overall, assistance from health financing schemes, good road access to health facilities, and socio-demographic and obstetric factors were associated with differential use of maternity health services by poor, rural women in the two states. Policymakers and practitioners should promote financing schemes to increase access, including consideration of incentives for antenatal care, and address health system and social factors in designing state-level interventions to promote safe motherhood.

In silico prediction of novel therapeutic targets using gene-disease association data.

PubMed

Ferrero, Enrico; Dunham, Ian; Sanseau, Philippe

2017-08-29

Target identification and validation is a pressing challenge in the pharmaceutical industry, with many of the programmes that fail for efficacy reasons showing poor association between the drug target and the disease. Computational prediction of successful targets could have a considerable impact on attrition rates in the drug discovery pipeline by significantly reducing the initial search space. Here, we explore whether gene-disease association data from the Open Targets platform is sufficient to predict therapeutic targets that are actively being pursued by pharmaceutical companies or are already on the market. To test our hypothesis, we train four different classifiers (a random forest, a support vector machine, a neural network and a gradient boosting machine) on partially labelled data and evaluate their performance using nested cross-validation and testing on an independent set. We then select the best performing model and use it to make predictions on more than 15,000 genes. Finally, we validate our predictions by mining the scientific literature for proposed therapeutic targets. We observe that the data types with the best predictive power are animal models showing a disease-relevant phenotype, differential expression in diseased tissue and genetic association with the disease under investigation. On a test set, the neural network classifier achieves over 71% accuracy with an AUC of 0.76 when predicting therapeutic targets in a semi-supervised learning setting. We use this model to gain insights into current and failed programmes and to predict 1431 novel targets, of which a highly significant proportion has been independently proposed in the literature. Our in silico approach shows that data linking genes and diseases is sufficient to predict novel therapeutic targets effectively and confirms that this type of evidence is essential for formulating or strengthening hypotheses in the target discovery process. Ultimately, more rapid and automated target prioritisation holds the potential to reduce both the costs and the development times associated with bringing new medicines to patients.

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.

Charting the Parameter Space of the 21-cm Power Spectrum

NASA Astrophysics Data System (ADS)

Cohen, Aviad; Fialkov, Anastasia; Barkana, Rennan

2018-05-01

The high-redshift 21-cm signal of neutral hydrogen is expected to be observed within the next decade and will reveal epochs of cosmic evolution that have been previously inaccessible. Due to the lack of observations, many of the astrophysical processes that took place at early times are poorly constrained. In recent work we explored the astrophysical parameter space and the resulting large variety of possible global (sky-averaged) 21-cm signals. Here we extend our analysis to the fluctuations in the 21-cm signal, accounting for those introduced by density and velocity, Lyα radiation, X-ray heating, and ionization. While the radiation sources are usually highlighted, we find that in many cases the density fluctuations play a significant role at intermediate redshifts. Using both the power spectrum and its slope, we show that properties of high-redshift sources can be extracted from the observable features of the fluctuation pattern. For instance, the peak amplitude of ionization fluctuations can be used to estimate whether heating occurred early or late and, in the early case, to also deduce the cosmic mean ionized fraction at that time. The slope of the power spectrum has a more universal redshift evolution than the power spectrum itself and can thus be used more easily as a tracer of high-redshift astrophysics. Its peaks can be used, for example, to estimate the redshift of the Lyα coupling transition and the redshift of the heating transition (and the mean gas temperature at that time). We also show that a tight correlation is predicted between features of the power spectrum and of the global signal, potentially yielding important consistency checks.

Impacts of Extreme Space Weather Events on Power Grid Infrastructure: Physics-Based Modelling of Geomagnetically-Induced Currents (GICs) During Carrington-Class Geomagnetic Storms

NASA Astrophysics Data System (ADS)

Henderson, M. G.; Bent, R.; Chen, Y.; Delzanno, G. L.; Jeffery, C. A.; Jordanova, V. K.; Morley, S.; Rivera, M. K.; Toth, G.; Welling, D. T.; Woodroffe, J. R.; Engel, M.

2017-12-01

Large geomagnetic storms can have devastating effects on power grids. The largest geomagnetic storm ever recorded - called the Carrington Event - occurred in 1859 and produced Geomagnetically Induced Currents (GICs) strong enough to set fires in telegraph offices. It has been estimated that if such a storm occurred today, it would have devastating, long-lasting effects on the North American power transmission infrastructure. Acutely aware of this imminent threat, the North American Electric Reliability Corporation (NERC) was recently instructed to establish requirements for transmission system performance during geomagnetic disturbance (GMD) events and, although the benchmarks adopted were based on the best available data at the time, they suffer from a severely limited physical understanding of the behavior of GMDs and the resulting GICs for strong events. To rectify these deficiencies, we are developing a first-of-its-kind data-informed modelling capability that will provide transformational understanding of the underlying physical mechanisms responsible for the most harmful intense localized GMDs and their impacts on real power transmission networks. This work is being conducted in two separate modes of operation: (1) using historical, well-observed large storm intervals for which robust data-assimilation can be performed, and (2) extending the modelling into a predictive realm in order to assess impacts of poorly and/or never-before observed Carrington-class events. Results of this work are expected to include a potential replacement for the current NERC benchmarking methodology and the development of mitigation strategies in real power grid networks. We report on progress to date and show some preliminary results of modeling large (but not yet extreme) events.

Marital Processes, Neuroticism, and Stress as Risk Factors for Internalizing Symptoms

PubMed Central

Brock, Rebecca L.; Lawrence, Erika

2013-01-01

Objective Marital discord has a robust association with depression, yet it is rarely considered within broader etiological frameworks of psychopathology. Further, little is known about the particular aspects of relationships that have the greatest impact on psychopathology. The purpose of the present study was to test a novel conceptual framework including neuroticism, specific relationship processes (conflict management, partner support, emotional intimacy, and distribution of power and control), and stress as predictors of internalizing symptoms (depression and anxiety). Method Questionnaire and interview data were collected from 103 husbands and wives 5 times over the first 7 years of marriage. Results Results suggest that neuroticism (an expression of the underlying vulnerability for internalizing disorders) contributes to symptoms primarily through high levels of non-marital stress, an imbalance of power/control in one’s marriage, and poor partner support for husbands, and through greater emotional disengagement for wives. Conclusions Marital processes, neuroticism, and stress work together to significantly predict internalizing symptoms, demonstrating the need to routinely consider dyadic processes in etiological models of individual psychopathology. Specific recommendations for adapting and implementing couple interventions to prevent and treat individual psychopathology are discussed. PMID:24818069

Mechanics of torque generation in the bacterial flagellar motor

PubMed Central

Mandadapu, Kranthi K.; Nirody, Jasmine A.; Berry, Richard M.; Oster, George

2015-01-01

The bacterial flagellar motor (BFM) is responsible for driving bacterial locomotion and chemotaxis, fundamental processes in pathogenesis and biofilm formation. In the BFM, torque is generated at the interface between transmembrane proteins (stators) and a rotor. It is well established that the passage of ions down a transmembrane gradient through the stator complex provides the energy for torque generation. However, the physics involved in this energy conversion remain poorly understood. Here we propose a mechanically specific model for torque generation in the BFM. In particular, we identify roles for two fundamental forces involved in torque generation: electrostatic and steric. We propose that electrostatic forces serve to position the stator, whereas steric forces comprise the actual “power stroke.” Specifically, we propose that ion-induced conformational changes about a proline “hinge” residue in a stator α-helix are directly responsible for generating the power stroke. Our model predictions fit well with recent experiments on a single-stator motor. The proposed model provides a mechanical explanation for several fundamental properties of the flagellar motor, including torque–speed and speed–ion motive force relationships, backstepping, variation in step sizes, and the effects of key mutations in the stator. PMID:26216959

Short Range Photoassociation of Rb2 by a high power fiber laser

NASA Astrophysics Data System (ADS)

Passagem, Henry; Rodriguez, Ricardo; Ventura, Paulo; Bouloufa, Nadia; Dulieu, Olivier; Marcassa, Luis

2016-05-01

Photoassociation has been studied using cold trapped atomic samples for the last 20 years. Due to poor Franck-Condon overlap, a free-to-bound transition followed by spontaneous decay results in a small production of electronic ground state molecules. If the photoassociation is done at short range, deeply bound ground state molecules can be formed. Optical pumping schemes can be used to populate a single state. In our experiment, we have performed trap loss spectroscopy on trapped 85 Rb atoms in a MOT using a high power fiber laser. Our single mode fiber laser (linewidth < 1 MHz) produces about 50 W, which can be tuned in the 1060-1070 nm range. Two vibrational bound states of the 0u+ potential were observed (ν = 137 and 138). The frequency positions as well as the rotational constants of these states are in good agreement with theoretical predictions. We have also measured the lifetime of a crossed optical dipole trap using such fiber laser. The lifetime on resonance is shorter than off resonance as expected. A simple theoretical model indicates that the molecules decay to deeply bound vibrational levels in the ground state. This work was supported by Fapesp and INCT-IQ.

Mechanics of torque generation in the bacterial flagellar motor.

PubMed

Mandadapu, Kranthi K; Nirody, Jasmine A; Berry, Richard M; Oster, George

2015-08-11

The bacterial flagellar motor (BFM) is responsible for driving bacterial locomotion and chemotaxis, fundamental processes in pathogenesis and biofilm formation. In the BFM, torque is generated at the interface between transmembrane proteins (stators) and a rotor. It is well established that the passage of ions down a transmembrane gradient through the stator complex provides the energy for torque generation. However, the physics involved in this energy conversion remain poorly understood. Here we propose a mechanically specific model for torque generation in the BFM. In particular, we identify roles for two fundamental forces involved in torque generation: electrostatic and steric. We propose that electrostatic forces serve to position the stator, whereas steric forces comprise the actual "power stroke." Specifically, we propose that ion-induced conformational changes about a proline "hinge" residue in a stator α-helix are directly responsible for generating the power stroke. Our model predictions fit well with recent experiments on a single-stator motor. The proposed model provides a mechanical explanation for several fundamental properties of the flagellar motor, including torque-speed and speed-ion motive force relationships, backstepping, variation in step sizes, and the effects of key mutations in the stator.

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

PubMed

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

2017-10-01

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

Lack of Early Improvement Predicts Poor Outcome Following Acute Intracerebral Hemorrhage.

PubMed

Yogendrakumar, Vignan; Smith, Eric E; Demchuk, Andrew M; Aviv, Richard I; Rodriguez-Luna, David; Molina, Carlos A; Silva Blas, Yolanda; Dzialowski, Imanuel; Kobayashi, Adam; Boulanger, Jean-Martin; Lum, Cheemun; Gubitz, Gord; Padma, Vasantha; Roy, Jayanta; Kase, Carlos S; Bhatia, Rohit; Ali, Myzoon; Lyden, Patrick; Hill, Michael D; Dowlatshahi, Dar

2018-04-01

There are limited data as to what degree of early neurologic change best relates to outcome in acute intracerebral hemorrhage. We aimed to derive and validate a threshold for early postintracerebral hemorrhage change that best predicts 90-day outcomes. Derivation: retrospective analysis of collated clinical stroke trial data (Virtual International Stroke Trials Archive). retrospective analysis of a prospective multicenter cohort study (Prediction of haematoma growth and outcome in patients with intracerebral haemorrhage using the CT-angiography spot sign [PREDICT]). Neurocritical and ICUs. Patients with acute intracerebral hemorrhage presenting less than 6 hours. Derivation: 552 patients; validation: 275 patients. None. We generated a receiver operating characteristic curve for the association between 24-hour National Institutes of Health Stroke Scale change and clinical outcome. The primary outcome was a modified Rankin Scale score of 4-6 at 90 days; secondary outcomes were other modified Rankin Scale score ranges (modified Rankin Scale, 2-6, 3-6, 5-6, 6). We employed Youden's J Index to select optimal cut points and calculated sensitivity, specificity, and predictive values. We determined independent predictors via multivariable logistic regression. The derived definitions were validated in the PREDICT cohort. Twenty-four-hour National Institutes of Health Stroke Scale change was strongly associated with 90-day outcome with an area under the receiver operating characteristic curve of 0.75. Youden's method showed an optimum cut point at -0.5, corresponding to National Institutes of Health Stroke Scale change of greater than or equal to 0 (a lack of clinical improvement), which was seen in 46%. Early neurologic change accurately predicted poor outcome when defined as greater than or equal to 0 (sensitivity, 65%; specificity, 73%; positive predictive value, 70%; adjusted odds ratio, 5.05 [CI, 3.25-7.85]) or greater than or equal to 4 (sensitivity, 19%; specificity, 98%; positive predictive value, 91%; adjusted odds ratio, 12.24 [CI, 4.08-36.66]). All definitions reproduced well in the validation cohort. Lack of clinical improvement at 24 hours robustly predicted poor outcome and showed good discrimination for individual patients who would do poorly. These findings are useful for prognostication and may also present as a potential early surrogate outcome for future intracerebral hemorrhage treatment trials.

Electric Power Engineering Cost Predicting Model Based on the PCA-GA-BP

NASA Astrophysics Data System (ADS)

Wen, Lei; Yu, Jiake; Zhao, Xin

2017-10-01

In this paper a hybrid prediction algorithm: PCA-GA-BP model is proposed. PCA algorithm is established to reduce the correlation between indicators of original data and decrease difficulty of BP neural network in complex dimensional calculation. The BP neural network is established to estimate the cost of power transmission project. The results show that PCA-GA-BP algorithm can improve result of prediction of electric power engineering cost.

Evaluation of Data-Driven Models for Predicting Solar Photovoltaics Power Output

DOE PAGES

Moslehi, Salim; Reddy, T. Agami; Katipamula, Srinivas

2017-09-10

This research was undertaken to evaluate different inverse models for predicting power output of solar photovoltaic (PV) systems under different practical scenarios. In particular, we have investigated whether PV power output prediction accuracy can be improved if module/cell temperature was measured in addition to climatic variables, and also the extent to which prediction accuracy degrades if solar irradiation is not measured on the plane of array but only on a horizontal surface. We have also investigated the significance of different independent or regressor variables, such as wind velocity and incident angle modifier in predicting PV power output and cell temperature.more » The inverse regression model forms have been evaluated both in terms of their goodness-of-fit, and their accuracy and robustness in terms of their predictive performance. Given the accuracy of the measurements, expected CV-RMSE of hourly power output prediction over the year varies between 3.2% and 8.6% when only climatic data are used. Depending on what type of measured climatic and PV performance data is available, different scenarios have been identified and the corresponding appropriate modeling pathways have been proposed. The corresponding models are to be implemented on a controller platform for optimum operational planning of microgrids and integrated energy systems.« less

Improved techniques for predicting spacecraft power

NASA Technical Reports Server (NTRS)

Chmielewski, A. B.

1987-01-01

Radioisotope Thermoelectric Generators (RTGs) are going to supply power for the NASA Galileo and Ulysses spacecraft now scheduled to be launched in 1989 and 1990. The duration of the Galileo mission is expected to be over 8 years. This brings the total RTG lifetime to 13 years. In 13 years, the RTG power drops more than 20 percent leaving a very small power margin over what is consumed by the spacecraft. Thus it is very important to accurately predict the RTG performance and be able to assess the magnitude of errors involved. The paper lists all the error sources involved in the RTG power predictions and describes a statistical method for calculating the tolerance.

ESB-based Sensor Web integration for the prediction of electric power supply system vulnerability.

PubMed

Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

2013-08-15

Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application.

ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability

PubMed Central

Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

2013-01-01

Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application. PMID:23955435

Interoception in anxiety and depression

PubMed Central

Stein, Murray B.

2010-01-01

We review the literature on interoception as it relates to depression and anxiety, with a focus on belief, and alliesthesia. The connection between increased but noisy afferent interoceptive input, self-referential and belief-based states, and top-down modulation of poorly predictive signals is integrated into a neuroanatomical and processing model for depression and anxiety. The advantage of this conceptualization is the ability to specifically examine the interface between basic interoception, self-referential belief-based states, and enhanced top-down modulation to attenuate poor predictability. We conclude that depression and anxiety are not simply interoceptive disorders but are altered interoceptive states as a consequence of noisily amplified self-referential interoceptive predictive belief states. PMID:20490545

Power quality analysis based on spatial correlation

NASA Astrophysics Data System (ADS)

Li, Jiangtao; Zhao, Gang; Liu, Haibo; Li, Fenghou; Liu, Xiaoli

2018-03-01

With the industrialization and urbanization, the status of electricity in the production and life is getting higher and higher. So the prediction of power quality is the more potential significance. Traditional power quality analysis methods include: power quality data compression, disturbance event pattern classification, disturbance parameter calculation. Under certain conditions, these methods can predict power quality. This paper analyses the temporal variation of power quality of one provincial power grid in China from time angle. The distribution of power quality was analyzed based on spatial autocorrelation. This paper tries to prove that the research idea of geography is effective for mining the potential information of power quality.

Poor Self-Control and Harsh Punishment in Childhood Prospectively Predict Borderline Personality Symptoms in Adolescent Girls

PubMed Central

Hallquist, Michael N.; Hipwell, Alison E.; Stepp, Stephanie D.

2015-01-01

Developmental theories of borderline personality disorder (BPD) propose that harsh, invalidating parenting of a child with poor self-control and heightened negative emotionality often leads to a coercive cycle of parent-child transactions that increase risk for BPD symptoms such as emotion dysregulation. Although parenting practices and child temperament have previously been linked with BPD, less is known about the prospective influences of caregiver and child characteristics. Using annual longitudinal data from the Pittsburgh Girls Study (n = 2450), our study examined how reciprocal influences among harsh parenting, self-control, and negative emotionality between ages 5 and 14 predicted the development of BPD symptoms in adolescent girls ages 14 to 17. Consistent with developmental theories, we found that harsh punishment, poor self-control, and negative emotionality predicted BPD symptom severity at age 14. Only worsening self-control between ages 12 and 14, however, predicted growth in BPD symptoms from 14 to 17. Furthermore, the effects of harsh punishment and poor self-control on age 14 BPD symptoms were partially mediated by their earlier reciprocal effects on each other between ages 5 and 14. Our findings underscore the need to address both child and parental contributions to dysfunctional transactions in order to stem the development of BPD symptoms. Moreover, problems with self-regulation in early adolescence may indicate heightened risk for subsequent BPD. Altogether, these results increase our understanding of developmental trajectories associated with BPD symptoms in adolescent girls. PMID:25961815

Poor self-control and harsh punishment in childhood prospectively predict borderline personality symptoms in adolescent girls.

PubMed

Hallquist, Michael N; Hipwell, Alison E; Stepp, Stephanie D

2015-08-01

Developmental theories of borderline personality disorder (BPD) propose that harsh, invalidating parenting of a child with poor self-control and heightened negative emotionality often leads to a coercive cycle of parent-child transactions that increase risk for BPD symptoms such as emotion dysregulation. Although parenting practices and child temperament have previously been linked with BPD, less is known about the prospective influences of caregiver and child characteristics. Using annual longitudinal data from the Pittsburgh Girls Study (n = 2,450), our study examined how reciprocal influences among harsh parenting, self-control, and negative emotionality between ages 5 and 14 predicted the development of BPD symptoms in adolescent girls ages 14 to 17. Consistent with developmental theories, we found that harsh punishment, poor self-control, and negative emotionality predicted BPD symptom severity at age 14. Only worsening self-control between ages 12 and 14, however, predicted growth in BPD symptoms from 14 to 17. Furthermore, the effects of harsh punishment and poor self-control on age 14 BPD symptoms were partially mediated by their earlier reciprocal effects on each other between ages 5 and 14. Our findings underscore the need to address both child and parental contributions to dysfunctional transactions in order to stem the development of BPD symptoms. Moreover, problems with self-regulation in early adolescence may indicate heightened risk for subsequent BPD. Altogether, these results increase our understanding of developmental trajectories associated with BPD symptoms in adolescent girls. (c) 2015 APA, all rights reserved).

A Valuable Tool in Predicting Poor Outcome due to Sepsis in Pediatric Intensive Care Unit: Tp-e/QT Ratio.

PubMed

Ozdemir, Rahmi; Isguder, Rana; Kucuk, Mehmet; Karadeniz, Cem; Ceylan, Gokhan; Katipoglu, Nagehan; Yilmazer, Murat Muhtar; Yozgat, Yilmaz; Mese, Timur; Agin, Hasan

2016-10-01

To assess the feasibility of 12-lead electrocardiographic (ECG) measures such as P wave dispersion (PWd), QT interval, QT dispersion (QTd), Tp-e interval, Tp-e/QT and Tp-e/QTc ratio in predicting poor outcome in patients diagnosed with sepsis in pediatric intensive care unit (PICU). Ninety-three patients diagnosed with sepsis, severe sepsis or septic shock and 103 age- and sex-matched healthy children were enrolled into the study. PWd, QT interval, QTd, Tp-e interval and Tp-e/QT, Tp-e/QTc ratios were obtained from a 12-lead electrocardiogram. PWd, QTd, Tp-e interval and Tp-e/QT, Tp-e/QTc ratios were significantly higher in septic patients compared with the controls. During the study period, 41 patients had died. In multivariate logistic regression analyses, only Tp-e/QT ratio was found to be an independent predictor of mortality. The ECG measurements can predict the poor outcome in patients with sepsis. The Tp-e/QT ratio may be a valuable tool in predicting mortality for patients with sepsis in the PICU. © The Author [2016]. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

How can community health programmes build enabling environments for transformative communication? Experiences from India and South Africa.

PubMed

Campbell, Catherine; Cornish, Flora

2012-05-01

Much research has examined how to empower the poor to articulate demands for health-enabling living conditions. Less is known about creating receptive social environments where the powerful heed the voices of the poor. We explore the potential for 'transformative communication' between the poor and the powerful, through comparing two well-documented case studies of HIV/AIDS management. The Entabeni Project in South Africa sought to empower impoverished women to deliver home-based nursing to people with AIDS. It successfully provided short-term welfare, but did not achieve local leadership or sustainability. The Sonagachi Project in India, an HIV-prevention programme targeting female sex workers, became locally led and sustainable. We highlight the strategies through which Sonagachi, but not Entabeni, altered the material, symbolic and relational contexts of participants' lives, enabling transformative communication and opportunities for sexual health-enabling social change.

Predicting power-optimal kinematics of avian wings

PubMed Central

Parslew, Ben

2015-01-01

A theoretical model of avian flight is developed which simulates wing motion through a class of methods known as predictive simulation. This approach uses numerical optimization to predict power-optimal kinematics of avian wings in hover, cruise, climb and descent. The wing dynamics capture both aerodynamic and inertial loads. The model is used to simulate the flight of the pigeon, Columba livia, and the results are compared with previous experimental measurements. In cruise, the model unearths a vast range of kinematic modes that are capable of generating the required forces for flight. The most efficient mode uses a near-vertical stroke–plane and a flexed-wing upstroke, similar to kinematics recorded experimentally. In hover, the model predicts that the power-optimal mode uses an extended-wing upstroke, similar to hummingbirds. In flexing their wings, pigeons are predicted to consume 20% more power than if they kept their wings full extended, implying that the typical kinematics used by pigeons in hover are suboptimal. Predictions of climbing flight suggest that the most energy-efficient way to reach a given altitude is to climb as steeply as possible, subjected to the availability of power. PMID:25392398

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.

Early predicted time to normalization of tumor markers predicts outcome in poor-prognosis nonseminomatous germ cell tumors.

PubMed

Fizazi, Karim; Culine, Stéphane; Kramar, Andrew; Amato, Robert J; Bouzy, Jeannine; Chen, Isan; Droz, Jean-Pierre; Logothetis, Christopher J

2004-10-01

The prognostic relevance of the rate of decline of serum alpha-fetoprotein (AFP) and human chorionic gonadotropin (HCG) during the first 3 weeks of chemotherapy for nonseminomatous germ cell tumors (NSGCT) was studied in the context of the International Germ Cell Cancer Collaborative Group (IGCCCG) classification. Data from 653 patients prospectively recruited in clinical trials were studied. Tumor markers were obtained before chemotherapy and 3 weeks later. Decline rates were calculated using a logarithmic formula and expressed as a predicted time to normalization (TTN). A favorable TTN was defined when both AFP and HCG had a favorable decline rate, including cases with normal values. The median follow-up was 50 months (range, 2 to 151 months). Tumor decline rate expressed as a predicted TTN was associated with both progression-free survival (PFS; P <.0001) and overall survival (OS; P <.0001). The 4-year PFS rates were 64% and 38% in patients from the poor-prognosis group who had a favorable and an unfavorable TTN, respectively. The 4-year OS rates were 83% and 58%, respectively. This effect was independent from the initial tumor marker values, the primary tumor site, and the presence of nonpulmonary visceral metastases: tumor marker decline rate remained a strong predictor for both PFS (hazard ratio = 2.5; P =.01) and OS (hazard ratio = 4.6; P =.002) in patients from the IGCCCG poor-prognosis group in multivariate analysis. Early predicted time to tumor marker normalization is an independent prognostic factor in patients with poor-prognosis NSGCT and may be a useful tool in the therapeutic management of these patients.

Black Hole Sign Predicts Poor Outcome in Patients with Intracerebral Hemorrhage.

PubMed

Li, Qi; Yang, Wen-Song; Chen, Sheng-Li; Lv, Fu-Rong; Lv, Fa-Jin; Hu, Xi; Zhu, Dan; Cao, Du; Wang, Xing-Chen; Li, Rui; Yuan, Liang; Qin, Xin-Yue; Xie, Peng

2018-01-01

In spontaneous intracerebral hemorrhage (ICH), black hole sign has been proposed as a promising imaging marker that predicts hematoma expansion in patients with ICH. The aim of our study was to investigate whether admission CT black hole sign predicts hematoma growth in patients with ICH. From July 2011 till February 2016, patients with spontaneous ICH who underwent baseline CT scan within 6 h of symptoms onset and follow-up CT scan were recruited into the study. The presence of black hole sign on admission non-enhanced CT was independently assessed by 2 readers. The functional outcome was assessed using the modified Rankin Scale (mRS) at 90 days. Univariate and multivariable logistic regression analyses were performed to assess the association between the presence of the black hole sign and functional outcome. A total of 225 patients (67.6% male, mean age 60.3 years) were included in our study. Black hole sign was identified in 32 of 225 (14.2%) patients on admission CT scan. The multivariate logistic regression analysis demonstrated that age, intraventricular hemorrhage, baseline ICH volume, admission Glasgow Coma Scale score, and presence of black hole sign on baseline CT independently predict poor functional outcome at 90 days. There are significantly more patients with a poor functional outcome (defined as mRS ≥4) among patients with black hole sign than those without (84.4 vs. 32.1%, p < 0.001; OR 8.19, p = 0.001). The CT black hole sign independently predicts poor outcome in patients with ICH. Early identification of black hole sign is useful in prognostic stratification and may serve as a potential therapeutic target for anti-expansion clinical trials. © 2018 S. Karger AG, Basel.

Prediction of light aircraft interior sound pressure level using the room equation

NASA Technical Reports Server (NTRS)

Atwal, M.; Bernhard, R.

1984-01-01

The room equation is investigated for predicting interior sound level. The method makes use of an acoustic power balance, by equating net power flow into the cabin volume to power dissipated within the cabin using the room equation. The sound power level transmitted through the panels was calculated by multiplying the measured space averaged transmitted intensity for each panel by its surface area. The sound pressure level was obtained by summing the mean square sound pressures radiated from each panel. The data obtained supported the room equation model in predicting the cabin interior sound pressure level.

Multi-Temporal Decomposed Wind and Load Power Models for Electric Energy Systems

NASA Astrophysics Data System (ADS)

Abdel-Karim, Noha

This thesis is motivated by the recognition that sources of uncertainties in electric power systems are multifold and may have potentially far-reaching effects. In the past, only system load forecast was considered to be the main challenge. More recently, however, the uncertain price of electricity and hard-to-predict power produced by renewable resources, such as wind and solar, are making the operating and planning environment much more challenging. The near-real-time power imbalances are compensated by means of frequency regulation and generally require fast-responding costly resources. Because of this, a more accurate forecast and look-ahead scheduling would result in a reduced need for expensive power balancing. Similarly, long-term planning and seasonal maintenance need to take into account long-term demand forecast as well as how the short-term generation scheduling is done. The better the demand forecast, the more efficient planning will be as well. Moreover, computer algorithms for scheduling and planning are essential in helping the system operators decide what to schedule and planners what to build. This is needed given the overall complexity created by different abilities to adjust the power output of generation technologies, demand uncertainties and by the network delivery constraints. Given the growing presence of major uncertainties, it is likely that the main control applications will use more probabilistic approaches. Today's predominantly deterministic methods will be replaced by methods which account for key uncertainties as decisions are made. It is well-understood that although demand and wind power cannot be predicted at very high accuracy, taking into consideration predictions and scheduling in a look-ahead way over several time horizons generally results in more efficient and reliable utilization, than when decisions are made assuming deterministic, often worst-case scenarios. This change is in approach is going to ultimately require new electricity market rules capable of providing the right incentives to manage uncertainties and of differentiating various technologies according to the rate at which they can respond to ever changing conditions. Given the overall need for modeling uncertainties in electric energy systems, we consider in this thesis the problem of multi-temporal modeling of wind and demand power, in particular. Historic data is used to derive prediction models for several future time horizons. Short-term prediction models derived can be used for look-ahead economic dispatch and unit commitment, while the long-term annual predictive models can be used for investment planning. As expected, the accuracy of such predictive models depends on the time horizons over which the predictions are made, as well as on the nature of uncertain signals. It is shown that predictive models obtained using the same general modeling approaches result in different accuracy for wind than for demand power. In what follows, we introduce several models which have qualitatively different patterns, ranging from hourly to annual. We first transform historic time-stamped data into the Fourier Transform (Fr) representation. The frequency domain data representation is used to decompose the wind and load power signals and to derive predictive models relevant for short-term and long-term predictions using extracted spectral techniques. The short-term results are interpreted next as a Linear Prediction Coding Model (LPC) and its accuracy is analyzed. Next, a new Markov-Based Sensitivity Model (MBSM) for short term prediction has been proposed and the dispatched costs of uncertainties for different predictive models with comparisons have been developed. Moreover, the Discrete Markov Process (DMP) representation is applied to help assess probabilities of most likely short-, medium- and long-term states and the related multi-temporal risks. In addition, this thesis discusses operational impacts of wind power integration in different scenario levels by performing more than 9,000 AC Optimal Power Flow runs. The effects of both wind and load variations on system constraints and costs are presented. The limitations of DC Optimal Power Flow (DCOPF) vs. ACOPF are emphasized by means of system convergence problems due to the effect of wind power on changing line flows and net power injections. By studying the effect of having wind power on line flows, we found that the divergence problem applies in areas with high wind and hydro generation capacity share (cheap generations). (Abstract shortened by UMI.).

Transcranial Duplex Sonography Predicts Outcome following an Intracerebral Hemorrhage.

PubMed

Camps-Renom, P; Méndez, J; Granell, E; Casoni, F; Prats-Sánchez, L; Martínez-Domeño, A; Guisado-Alonso, D; Martí-Fàbregas, J; Delgado-Mederos, R

2017-08-01

Several radiologic features such as hematoma volume are related to poor outcome following an intracerebral hemorrhage and can be measured with transcranial duplex sonography. We sought to determine the prognostic value of transcranial duplex sonography in patients with intracerebral hemorrhage. We conducted a prospective study of patients diagnosed with spontaneous intracerebral hemorrhage. Transcranial duplex sonography examinations were performed within 2 hours of baseline CT, and we recorded the following variables: hematoma volume, midline shift, third ventricle and lateral ventricle diameters, and the pulsatility index in both MCAs. We correlated these data with the CT scans and assessed the prognostic value of the transcranial duplex sonography measurements. We assessed early neurologic deterioration during hospitalization and mortality at 1-month follow-up. We included 35 patients with a mean age of 72.2 ± 12.8 years. Median baseline hematoma volume was 9.85 mL (interquartile range, 2.74-68.29 mL). We found good agreement and excellent correlation between transcranial duplex sonography and CT when measuring hematoma volume ( r = 0.791; P < .001) and midline shift ( r = 0.827; P < .001). The logistic regression analysis with transcranial duplex sonography measurements showed that hematoma volume was an independent predictor of early neurologic deterioration (OR, 1.078; 95% CI, 1.023-1.135) and mortality (OR, 1.089; 95% CI, 1.020-1.160). A second regression analysis with CT variables also demonstrated that hematoma volume was associated with early neurologic deterioration and mortality. When we compared the rating operation curves of both models, their predictive power was similar. Transcranial duplex sonography showed an excellent correlation with CT in assessing hematoma volume and midline shift in patients with intracerebral hemorrhage. Hematoma volume measured with transcranial duplex sonography was an independent predictor of poor outcome. © 2017 by American Journal of Neuroradiology.

Serum Hepatocyte Growth Factor Is Probably Associated With 3-Month Prognosis of Acute Ischemic Stroke.

PubMed

Zhu, Zhengbao; Xu, Tan; Guo, Daoxia; Huangfu, Xinfeng; Zhong, Chongke; Yang, Jingyuan; Wang, Aili; Chen, Chung-Shiuan; Peng, Yanbo; Xu, Tian; Wang, Jinchao; Sun, Yingxian; Peng, Hao; Li, Qunwei; Ju, Zhong; Geng, Deqin; Chen, Jing; Zhang, Yonghong; He, Jiang

2018-02-01

Serum hepatocyte growth factor (HGF) is positively associated with poor prognosis of heart failure and myocardial infarction, and it can also predict the risk of ischemic stroke in population. The goal of this study was to investigate the association between serum HGF and prognosis of ischemic stroke. A total of 3027 acute ischemic stroke patients were included in this post hoc analysis of the CATIS (China Antihypertensive Trial in Acute Ischemic Stroke). The primary outcome was composite outcome of death or major disability (modified Rankin Scale score ≥3) within 3 months. After multivariate adjustment, elevated HGF levels were associated with an increased risk of primary outcome (odds ratio, 1.50; 95% confidence interval, 1.10-2.03; P trend =0.015) when 2 extreme quartiles were compared. Each SD increase of log-transformed HGF was associated with 14% (95% confidence interval, 2%-27%) increased risk of primary outcome. Adding HGF quartiles to a model containing conventional risk factors improved the predictive power for primary outcome (net reclassification improvement: 17.50%, P <0.001; integrated discrimination index: 0.23%, P =0.022). The association between serum HGF and primary outcome could be modified by heparin pre-treatment ( P interaction =0.001), and a positive linear dose-response relationship between HGF and primary outcome was observed in patients without heparin pre-treatment ( P linearity <0.001) but not in those with heparin pre-treatment. Serum HGF levels were higher in the more severe stroke at baseline, and elevated HGF levels were probably associated with 3-month poor prognosis independently of stroke severity among ischemic stroke patients, especially in those without heparin pre-treatment. Further studies from other samples of ischemic stroke patients are needed to validate our findings. © 2018 American Heart Association, Inc.

A baseline metabolomic signature is associated with immunological CD4+ T-cell recovery after 36 months of antiretroviral therapy in HIV-infected patients.

PubMed

Rodríguez-Gallego, Esther; Gómez, Josep; Pacheco, Yolanda M; Peraire, Joaquim; Viladés, Consuelo; Beltrán-Debón, Raúl; Mallol, Roger; López-Dupla, Miguel; Veloso, Sergi; Alba, Verónica; Blanco, Julià; Cañellas, Nicolau; Rull, Anna; Leal, Manuel; Correig, Xavier; Domingo, Pere; Vidal, Francesc

2018-03-13

Poor immunological recovery in treated HIV-infected patients is associated with greater morbidity and mortality. To date, predictive biomarkers of this incomplete immune reconstitution have not been established. We aimed to identify a baseline metabolomic signature associated with a poor immunological recovery after antiretroviral therapy (ART) to envisage the underlying mechanistic pathways that influence the treatment response. This was a multicentre, prospective cohort study in ART-naive and a pre-ART low nadir (<200 cells/μl) HIV-infected patients (n = 64). We obtained clinical data and metabolomic profiles for each individual, in which low molecular weight metabolites, lipids and lipoproteins (including particle concentrations and sizes) were measured by NMR spectroscopy. Immunological recovery was defined as reaching CD4 T-cell count at least 250 cells/μl after 36 months of virologically successful ART. We used univariate comparisons, Random Forest test and receiver-operating characteristic curves to identify and evaluate the predictive factors of immunological recovery after treatment. HIV-infected patients with a baseline metabolic pattern characterized by high levels of large high density lipoprotein (HDL) particles, HDL cholesterol and larger sizes of low density lipoprotein particles had a better immunological recovery after treatment. Conversely, patients with high ratios of non-HDL lipoprotein particles did not experience this full recovery. Medium very-low-density lipoprotein particles and glucose increased the classification power of the multivariate model despite not showing any significant differences between the two groups. In HIV-infected patients, a baseline healthier metabolomic profile is related to a better response to ART where the lipoprotein profile, mainly large HDL particles, may play a key role.

Validation of SAPS3 admission score and its customization for use in Korean intensive care unit patients: a prospective multicentre study.

PubMed

Lim, So Yeon; Koh, Shin Ok; Jeon, Kyeongman; Na, Sungwon; Lim, Chae-Man; Choi, Won-Il; Lee, Young-Joo; Kim, Seok Chan; Chon, Gyu Rak; Kim, Je Hyeong; Kim, Jae Yeol; Lim, Jaemin; Rhee, Chin Kook; Park, Sunghoon; Kim, Ho Cheol; Lee, Jin Hwa; Lee, Ji Hyun; Park, Jisook; Koh, Younsuck; Suh, Gee Young

2013-08-01

To externally validate the simplified acute physiology score 3 (SAPS3) and to customize it for use in Korean intensive care unit (ICU) patients. This is a prospective multicentre cohort study involving 22 ICUs from 15 centres throughout Korea. The study population comprised patients who were consecutively admitted to participating ICUs from 1 July 2010 to 31 January 2011. A total of 4617 patients were enrolled. ICU mortality was 14.3%, and hospital mortality was 20.6%. The patients were randomly assigned into one of two cohorts: a development (n = 2309) or validation (n = 2308) cohort. In the development cohort, the general SAPS3 had good discrimination (area under the receiver operating characteristics curve = 0.829), but poor calibration (Hosmer-Lemeshow goodness-of-fit test H = 123.06, P < 0.001, C = 118.45, P < 0.001). The Australasia SAPS3 did not improve calibration (H = 73.53, P < 0.001, C = 70.52, P < 0.001). Customization was achieved by altering the logit of the original SAPS3 equation. The new equation for Korean ICU patients was validated in the validation cohort, and demonstrated both good discrimination (area under the receiver operating characteristics curve = 0.835) and good calibration (H = 4.61, P = 0.799, C = 5.67, P = 0.684). General and regional Australasia SAPS3 admission scores showed poor calibration for use in Korean ICU patients, but the prognostic power of the SAPS3 was significantly improved by customization. Prediction models should be customized before being used to predict mortality in different regions of the world. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.

The effects of load on system and lower-body joint kinetics during jump squats.

PubMed

Moir, Gavin L; Gollie, Jared M; Davis, Shala E; Guers, John J; Witmer, Chad A

2012-11-01

To investigate the effects of different loads on system and lower-body kinetics during jump squats, 12 resistance-trained men performed jumps under different loading conditions: 0%, 12%, 27%, 42%, 56%, 71%, and 85% of 1-repetition maximum (1-RM). System power output was calculated as the product of the vertical component of the ground reaction force and the vertical velocity of the bar during its ascent. Joint power output was calculated during bar ascent for the hip, knee, and ankle joints, and was also summed across the joints. System power output and joint power at knee and ankle joints were maximized at 0% 1-RM (p < 0.001) and followed the linear trends (p < 0.001) caused by power output decreasing as the load increased. Power output at the hip was maximized at 42% 1-RM (p = 0.016) and followed a quadratic trend (p = 0.030). Summed joint power could be predicted from system power (p < 0.05), while system power could predict power at the knee and ankle joints under some of the loading conditions. Power at the hip could not be predicted from system power. System power during loaded jumps reflects the power at the knee and ankle, while power at the hip does not correspond to system power.

Prolonged self-paced exercise in the heat – environmental factors affecting performance

PubMed Central

Junge, Nicklas; Jørgensen, Rasmus; Flouris, Andreas D.; Nybo, Lars

2016-01-01

ABSTRACT In this review we examine how self-paced performance is affected by environmental heat stress factors during cycling time trial performance as well as considering the effects of exercise mode and heat acclimatization. Mean power output during prolonged cycling time trials in the heat (≥30°C) was on average reduced by 15% in the 14 studies that fulfilled the inclusion criteria. Ambient temperature per se was a poor predictor of the integrated environmental heat stress and 2 of the prevailing heat stress indices (WBGT and UTCI) failed to predict the environmental influence on performance. The weighing of wind speed appears to be too low for predicting the effect for cycling in trained acclimatized subjects, where performance may be maintained in outdoor time trials at ambient temperatures as high as 36°C (36°C UTCI; 28°C WBGT). Power output during indoor trials may also be maintained with temperatures up to at least 27°C when humidity is modest and wind speed matches the movement speed generated during outdoor cycling, whereas marked reductions are observed when air movement is minimal. For running, representing an exercise mode with lower movement speed and higher heat production for a given metabolic rate, it appears that endurance is affected even at much lower ambient temperatures. On this basis we conclude that environmental heat stress impacts self-paced endurance performance. However, the effect is markedly modified by acclimatization status and exercise mode, as the wind generated by the exercise (movement speed) or the environment (natural or fan air movement) exerts a strong influence. PMID:28090557

Using Brain Oscillations and Corticospinal Excitability to Understand and Predict Post-Stroke Motor Function

PubMed Central

Thibaut, Aurore; Simis, Marcel; Battistella, Linamara Rizzo; Fanciullacci, Chiara; Bertolucci, Federica; Huerta-Gutierrez, Rodrigo; Chisari, Carmelo; Fregni, Felipe

2017-01-01

What determines motor recovery in stroke is still unknown and finding markers that could predict and improve stroke recovery is a challenge. In this study, we aimed at understanding the neural mechanisms of motor function recovery after stroke using neurophysiological markers by means of cortical excitability (transcranial magnetic stimulation—TMS) and brain oscillations (electroencephalography—EEG). In this cross-sectional study, 55 subjects with chronic stroke (62 ± 14 yo, 17 women, 32 ± 42 months post-stroke) were recruited in two sites. We analyzed TMS measures (i.e., motor threshold—MT—of the affected and unaffected sides) and EEG variables (i.e., power spectrum in different frequency bands and different brain regions of the affected and unaffected hemispheres) and their correlation with motor impairment as measured by Fugl-Meyer. Multiple univariate and multivariate linear regression analyses were performed to identify the predictors of good motor function. A significant interaction effect of MT in the affected hemisphere and power in beta bandwidth over the central region for both affected and unaffected hemispheres was found. We identified that motor function positively correlates with beta rhythm over the central region of the unaffected hemisphere, while it negatively correlates with beta rhythm in the affected hemisphere. Our results suggest that cortical activity in the affected and unaffected hemisphere measured by EEG provides new insights on the association between high-frequency rhythms and motor impairment, highlighting the role of an excess of beta in the affected central cortical region in poor motor function in stroke recovery. PMID:28539912

Resting Heart Rate Is Not a Good Predictor of a Clustered Cardiovascular Risk Score in Adolescents: The HELENA Study

PubMed Central

de Moraes, Augusto César Ferreira; Cassenote, Alex Jones Flores; Leclercq, Catherine; Dallongeville, Jean; Androutsos, Odysseas; Török, Katalin; González-Gross, Marcela; Widhalm, Kurt; Kafatos, Anthony; Carvalho, Heráclito Barbosa; Moreno, Luis Alberto

2015-01-01

Background Resting heart rate (RHR) reflects sympathetic nerve activity a significant association between RHR and all-cause and cardiovascular mortality has been reported in some epidemiologic studies. Methods To analyze the predictive power and accuracy of RHR as a screening measure for individual and clustered cardiovascular risk in adolescents. The study comprised 769 European adolescents (376 boys) participating in the HELENA cross-sectional study (2006–2008) were included in this study. Measurements on systolic blood pressure, HOMA index, triglycerides, TC/HDL-c, VO2máx and the sum of four skinfolds were obtained, and a clustered cardiovascular disease (CVD) risk index was computed. The receiver operating characteristics curve was applied to calculate the power and accuracy of RHR to predict individual and clustered CVD risk factors. Results RHR showed low accuracy for screening CVD risk factors in both sexes (range 38.5%–54.4% in boys and 45.5%–54.3% in girls). Low specificity’s (15.6%–19.7% in boys; 18.1%–20.0% in girls) were also found. Nevertheless, the sensitivities were moderate-to-high (61.4%–89.1% in boys; 72.9%–90.3% in girls). Conclusion RHR is a poor predictor of individual CVD risk factors and of clustered CVD and the estimates based on RHR are not accurate. The use of RHR as an indicator of CVD risk in adolescents may produce a biased screening of cardiovascular health in both sexes. PMID:26010248

Inductive Electron Heating Revisited

NASA Astrophysics Data System (ADS)

Tuszewski, M.

1996-11-01

Inductively Coupled Plasmas (ICPs) have been studied for over a century. Recently, ICPs have been rediscovered by the multi-billion dollar semiconductor industry as an important class of high-density, low-pressure plasma sources suitable for the manufacture of next-generation integrated circuits. Present low-pressure ICP development is among the most active areas of plasma research. However, this development remains largely empirical, a prohibitively expensive approach for upcoming 300-mm diameter wafers. Hence, there is an urgent need for basic ICP plasma physics research, including experimental characterization and predictive numerical modeling. Inductive radio frequency (rf) power absorption is fundamental to the ICP electron heating and the resulting plasma transport but remains poorly understood. For example, recent experimental measurements and supporting fluid calculationsfootnote M. Tuszewski, Phys. Rev. Lett. 77 in press (1996) on a commercial deposition tool prototype show that the induced rf magnetic fields in the source can cause an order of magnitude reduction in plasma conductivity and in electron heating power density. In some cases, the rf fields penetrate through the entire volume of the ICP discharges while existing models that neglect the induced rf magnetic fields predict rf absorption in a thin skin layer near the plasma surface. The rf magnetic fields also cause more subtle changes in the plasma density and in the electron temperature spatial distributions. These data will be presented and the role of basic research in the applied world of semiconductor manufacturing will be discussed. ^*This research was conducted under the auspices of the U.S. DOE, supported by funds provided by the University of California for discretionary research by Los Alamos National Laboratory.

Using Brain Oscillations and Corticospinal Excitability to Understand and Predict Post-Stroke Motor Function.

PubMed

Thibaut, Aurore; Simis, Marcel; Battistella, Linamara Rizzo; Fanciullacci, Chiara; Bertolucci, Federica; Huerta-Gutierrez, Rodrigo; Chisari, Carmelo; Fregni, Felipe

2017-01-01

What determines motor recovery in stroke is still unknown and finding markers that could predict and improve stroke recovery is a challenge. In this study, we aimed at understanding the neural mechanisms of motor function recovery after stroke using neurophysiological markers by means of cortical excitability (transcranial magnetic stimulation-TMS) and brain oscillations (electroencephalography-EEG). In this cross-sectional study, 55 subjects with chronic stroke (62 ± 14 yo, 17 women, 32 ± 42 months post-stroke) were recruited in two sites. We analyzed TMS measures (i.e., motor threshold-MT-of the affected and unaffected sides) and EEG variables (i.e., power spectrum in different frequency bands and different brain regions of the affected and unaffected hemispheres) and their correlation with motor impairment as measured by Fugl-Meyer. Multiple univariate and multivariate linear regression analyses were performed to identify the predictors of good motor function. A significant interaction effect of MT in the affected hemisphere and power in beta bandwidth over the central region for both affected and unaffected hemispheres was found. We identified that motor function positively correlates with beta rhythm over the central region of the unaffected hemisphere, while it negatively correlates with beta rhythm in the affected hemisphere. Our results suggest that cortical activity in the affected and unaffected hemisphere measured by EEG provides new insights on the association between high-frequency rhythms and motor impairment, highlighting the role of an excess of beta in the affected central cortical region in poor motor function in stroke recovery.

Wind farms production: Control and prediction

NASA Astrophysics Data System (ADS)

El-Fouly, Tarek Hussein Mostafa

Wind energy resources, unlike dispatchable central station generation, produce power dependable on external irregular source and that is the incident wind speed which does not always blow when electricity is needed. This results in the variability, unpredictability, and uncertainty of wind resources. Therefore, the integration of wind facilities to utility electrical grid presents a major challenge to power system operator. Such integration has significant impact on the optimum power flow, transmission congestion, power quality issues, system stability, load dispatch, and economic analysis. Due to the irregular nature of wind power production, accurate prediction represents the major challenge to power system operators. Therefore, in this thesis two novel models are proposed for wind speed and wind power prediction. One proposed model is dedicated to short-term prediction (one-hour ahead) and the other involves medium term prediction (one-day ahead). The accuracy of the proposed models is revealed by comparing their results with the corresponding values of a reference prediction model referred to as the persistent model. Utility grid operation is not only impacted by the uncertainty of the future production of wind farms, but also by the variability of their current production and how the active and reactive power exchange with the grid is controlled. To address this particular task, a control technique for wind turbines, driven by doubly-fed induction generators (DFIGs), is developed to regulate the terminal voltage by equally sharing the generated/absorbed reactive power between the rotor-side and the gridside converters. To highlight the impact of the new developed technique in reducing the power loss in the generator set, an economic analysis is carried out. Moreover, a new aggregated model for wind farms is proposed that accounts for the irregularity of the incident wind distribution throughout the farm layout. Specifically, this model includes the wake effect and the time delay of the incident wind speed of the different turbines on the farm, and to simulate the fluctuation in the generated power more accurately and more closer to real-time operation. Recently, wind farms with considerable output power ratings have been installed. Their integrating into the utility grid will substantially affect the electricity markets. This thesis investigates the possible impact of wind power variability, wind farm control strategy, wind energy penetration level, wind farm location, and wind power prediction accuracy on the total generation costs and close to real time electricity market prices. These issues are addressed by developing a single auction market model for determining the real-time electricity market prices.

Quality of life before hyperhidrosis treatment as a predictive factor for oxybutynin treatment outcomes in palmar and axillary hyperhidrosis.

PubMed

Wolosker, Nelson; Krutman, Mariana; Teivelis, Marcelo P; Campbell, Taiz P D A; Kauffman, Paulo; de Campos, José Ribas M; Puech-Leão, Pedro

2014-05-01

Studies have suggested that quality of life (QOL) evaluation before video-assisted thoracoscopic sympathectomy for patients with hyperhidrosis may serve as a predictive factor for positive postoperative outcomes. Our study aims to analyze if this tendency is also observed in patients treated with oxybutynin for palmar and axillary hyperhidrosis. Five hundred sixty-five patients who submitted to a protocol treatment with oxybutynin were retrospectively analyzed between January 2007 and January 2012 and were divided into 2 groups according to QOL assessment before treatment. The groups consisted of 176 patients with "poor" and 389 patients with "very poor" QOL evaluation before oxybutynin treatment. Outcomes involving improvements in QOL and clinical progression of hyperhidrosis were evaluated using a validated clinical questionnaire that was specifically designed to assess satisfaction in patients with excessive sweating. Improvements in hyperhidrosis after oxybutynin were observed in 65.5% of patients with very poor pretreatment QOL scores and in 75% of patients with poor pretreatment QOL scores, and the only adverse event associated with oxybutynin treatment was dry mouth, which was observed with greater intensity in patients with very poor initial QOL evaluation. Improvements in hyperhidrosis after oxybutynin treatment were similar in both groups, suggesting that QOL before treatment is not a predictive factor for clinical outcomes, contrasting with surgical results that disclose significantly better results in patients with initially poorer QOL analysis. Copyright © 2014 Elsevier Inc. All rights reserved.

Efffect of Aeroallergen Sensitization on Asthma Control in African-American Teens with Persistent Asthma

EPA Science Inventory

In African-American adolescents with persistent asthma, allergic profile predicted the likelihood of having poorly controlled asthma despite guidelines-directed therapies. Our results suggest that tree and weed pollen sensitization are independent risk factors for poorly controll...

Replacement of SSE (Release 6) with NASA's Prediction of Worldwide Energy Resource (POWER) Project GIS-enabled Web Data Portal:

Atmospheric Science Data Center

2018-03-15

... effort has been developed under the Prediction Of Worldwide Energy Resource (POWER) Project funded largely by NASA Earth Applied Sciences ... to NASA's satellite and modeling analysis for Renewable Energy, Sustainable Buildings and Agroclimatology applications.  A new POWER ...

POWER/SSE

Atmospheric Science Data Center

2018-06-15

... The Prediction of Worldwide Energy Resource (POWER) project was initiated to improve upon the current SSE ... continue to be focussed on the solar and wind Renewable Energy industry. New data sets will target Sustainable Buildings ... The Prediction of Worldwide Energy Resource (POWER) project was initiated to improve upon the current SSE ...

Prediction of Recovery from Coma After CPR

MedlinePlus

... to pain. There is good evidence* that myoclonus status epilepticus within the first day after CPR accurately predicts poor recovery from coma. Myoclonus status epilepticus is a constant twitching of muscles, including the ...

Mental health, sleep quality, drinking motives, and alcohol-related consequences: a path-analytic model.

PubMed

Kenney, Shannon R; Lac, Andrew; Labrie, Joseph W; Hummer, Justin F; Pham, Andy

2013-11-01

Poor mental health, sleep problems, drinking motivations, and high-risk drinking are prevalent among college students. However, research designed to explicate the interrelationships among these health risk behaviors is lacking. This study was designed to assess the direct and indirect influences of poor mental health (a latent factor consisting of depression, anxiety, and stress) to alcohol use and alcohol-related consequences through the mediators of global sleep quality and drinking motives in a comprehensive model. Participants were 1,044 heavy-drinking college students (66.3% female) who completed online surveys. A hybrid structural equation model tested hypotheses involving relations leading from poor mental health to drinking motives and poorer global sleep quality to drinking outcomes. Results showed that poor mental health significantly predicted all four subscales of drinking motivations (social, coping, conformity, and enhancement) as well as poor sleep. Most of the drinking motives and poor sleep were found to explain alcohol use and negative alcohol consequences. Poor sleep predicted alcohol consequences, even after controlling for all other variables in the model. The hypothesized mediational pathways were examined with tests of indirect effects. This is the first study to assess concomitantly the relationships among three vital health-related domains (mental health, sleep behavior, and alcohol risk) in college students. Findings offer important implications for college personnel and interventionists interested in reducing alcohol risk by focusing on alleviating mental health problems and poor sleep quality.

Proton MRS in acute traumatic brain injury: role for glutamate/glutamine and choline for outcome prediction.

PubMed

Shutter, Lori; Tong, Karen A; Holshouser, Barbara A

2004-12-01

Proton magnetic resonance spectroscopy (MRS) is being used to evaluate individuals with acute traumatic brain injury and several studies have shown that changes in certain brain metabolites (N-acetylaspartate, choline) are associated with poor neurologic outcomes. The majority of previous MRS studies have been obtained relatively late after injury and none have examined the role of glutamate/ glutamine (Glx). We conducted a prospective MRS study of 42 severely injured adults to measure quantitative metabolite changes early (7 days) after injury in normal appearing brain. We used these findings to predict long-term neurologic outcome and to determine if MRS data alone or in combination with clinical outcome variables provided better prediction of long-term outcomes. We found that glutamate/glutamine (Glx) and choline (Cho) were significantly elevated in occipital gray and parietal white matter early after injury in patients with poor long-term (6-12-month) outcomes. Glx and Cho ratios predicted long-term outcome with 94% accuracy and when combined with the motor Glasgow Coma Scale score provided the highest predictive accuracy (97%). Somatosensory evoked potentials were not as accurate as MRS data in predicting outcome. Elevated Glx and Cho are more sensitive indicators of injury and predictors of poor outcome when spectroscopy is done early after injury. This may be a reflection of early excitotoxic injury (i.e., elevated Glx) and of injury associated with membrane disruption (i.e., increased Cho) secondary to diffuse axonal injury.

EEG, evoked potentials and pulsed Doppler in asphyxiated term infants.

PubMed

Julkunen, Mia K; Himanen, Sari-Leena; Eriksson, Kai; Janas, Martti; Luukkaala, Tiina; Tammela, Outi

2014-09-01

To evaluate electroencephalograms (EEG), evoked potentials (EPs) and Doppler findings in the cerebral arteries as predictors of a 1-year outcome in asphyxiated newborn infants. EEG and EPs (brain stem auditory (BAEP), somatosensory (SEP), visual (VEP) evoked potentials) were assessed in 30 asphyxiated and 30 healthy term infants during the first days (range 1-8). Cerebral blood flow velocities (CBFV) were measured from the cerebral arteries using pulsed Doppler at ∼24h of age. EEG, EPs, Doppler findings, symptoms of hypoxic ischemic encephalopathy (HIE) and their combination were evaluated in predicting a 1-year outcome. An abnormal EEG background predicted poor outcome in the asphyxia group with a sensitivity of 67% and 81% specificity, and an abnormal SEP with 75% and 79%, respectively. Combining increased systolic CBFV (mean+3SD) with abnormal EEG or SEP improved the specificity, but not the sensitivity. The predictive values of abnormal BAEP and VEP were poor. Normal EEG and SEP predicted good outcome in the asphyxia group with sensitivities from 79% to 81%. The combination of normal EEG, normal SEP and systolic CBFV<3SD predicted good outcome with a sensitivity of 74% and 100% specificity. Combining abnormal EEG or EPs findings with increased systolic CBFV did not improve prediction of a poor 1-year outcome of asphyxiated infants. Normal EEG and normal SEP combined with systolic CBFV<3SD at about 24 h can be valuable in the prediction of normal 1-year outcome. Combining systolic CBFV at 24 h with EEG and SEP examinations can be of use in the prediction of normal 1-year outcome among asphyxiated infants. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Breaking through barriers: using technology to address executive function weaknesses and improve student achievement.

PubMed

Schwartz, David M

2014-01-01

Assistive technologies provide significant capabilities for improving student achievement. Improved accessibility, cost, and diversity of applications make integration of technology a powerful tool to compensate for executive function weaknesses and deficits and their impact on student performance, learning, and achievement. These tools can be used to compensate for decreased working memory, poor time management, poor planning and organization, poor initiation, and decreased memory. Assistive technology provides mechanisms to assist students with diverse strengths and weaknesses in mastering core curricular concepts.

Comparative systems biology across an evolutionary gradient within the Shewanella genus.

PubMed

Konstantinidis, Konstantinos T; Serres, Margrethe H; Romine, Margaret F; Rodrigues, Jorge L M; Auchtung, Jennifer; McCue, Lee-Ann; Lipton, Mary S; Obraztsova, Anna; Giometti, Carol S; Nealson, Kenneth H; Fredrickson, James K; Tiedje, James M

2009-09-15

To what extent genotypic differences translate to phenotypic variation remains a poorly understood issue of paramount importance for several cornerstone concepts of microbiology including the species definition. Here, we take advantage of the completed genomic sequences, expressed proteomic profiles, and physiological studies of 10 closely related Shewanella strains and species to provide quantitative insights into this issue. Our analyses revealed that, despite extensive horizontal gene transfer within these genomes, the genotypic and phenotypic similarities among the organisms were generally predictable from their evolutionary relatedness. The power of the predictions depended on the degree of ecological specialization of the organisms evaluated. Using the gradient of evolutionary relatedness formed by these genomes, we were able to partly isolate the effect of ecology from that of evolutionary divergence and to rank the different cellular functions in terms of their rates of evolution. Our ranking also revealed that whole-cell protein expression differences among these organisms, when the organisms were grown under identical conditions, were relatively larger than differences at the genome level, suggesting that similarity in gene regulation and expression should constitute another important parameter for (new) species description. Collectively, our results provide important new information toward beginning a systems-level understanding of bacterial species and genera.

The impact of environmental and climatic variation on the spatiotemporal trends of hospitalized pediatric diarrhea in Ho Chi Minh City, Vietnam.

PubMed

Thompson, Corinne N; Zelner, Jonathan L; Nhu, Tran Do Hoang; Phan, My Vt; Hoang Le, Phuc; Nguyen Thanh, Hung; Vu Thuy, Duong; Minh Nguyen, Ngoc; Ha Manh, Tuan; Van Hoang Minh, Tu; Lu Lan, Vi; Nguyen Van Vinh, Chau; Tran Tinh, Hien; von Clemm, Emmiliese; Storch, Harry; Thwaites, Guy; Grenfell, Bryan T; Baker, Stephen

2015-09-01

It is predicted that the integration of climate-based early warning systems into existing action plans will facilitate the timely provision of interventions to diarrheal disease epidemics in resource-poor settings. Diarrhea remains a considerable public health problem in Ho Chi Minh City (HCMC), Vietnam and we aimed to quantify variation in the impact of environmental conditions on diarrheal disease risk across the city. Using all inpatient diarrheal admissions data from three large hospitals within HCMC, we developed a mixed effects regression model to differentiate district-level variation in risk due to environmental conditions from the overarching seasonality of diarrheal disease hospitalization in HCMC. We identified considerable spatial heterogeneity in the risk of all-cause diarrhea across districts of HCMC with low elevation and differential responses to flooding, air temperature, and humidity driving further spatial heterogeneity in diarrheal disease risk. The incorporation of these results into predictive forecasting algorithms will provide a powerful resource to aid diarrheal disease prevention and control practices in HCMC and other similar settings. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Quantitative theory of driven nonlinear brain dynamics.

PubMed

Roberts, J A; Robinson, P A

2012-09-01

Strong periodic stimuli such as bright flashing lights evoke nonlinear responses in the brain and interact nonlinearly with ongoing cortical activity, but the underlying mechanisms for these phenomena are poorly understood at present. The dominant features of these experimentally observed dynamics are reproduced by the dynamics of a quantitative neural field model subject to periodic drive. Model power spectra over a range of drive frequencies show agreement with multiple features of experimental measurements, exhibiting nonlinear effects including entrainment over a range of frequencies around the natural alpha frequency f(α), subharmonic entrainment near 2f(α), and harmonic generation. Further analysis of the driven dynamics as a function of the drive parameters reveals rich nonlinear dynamics that is predicted to be observable in future experiments at high drive amplitude, including period doubling, bistable phase-locking, hysteresis, wave mixing, and chaos indicated by positive Lyapunov exponents. Moreover, photosensitive seizures are predicted for physiologically realistic model parameters yielding bistability between healthy and seizure dynamics. These results demonstrate the applicability of neural field models to the new regime of periodically driven nonlinear dynamics, enabling interpretation of experimental data in terms of specific generating mechanisms and providing new tests of the theory. Copyright © 2012 Elsevier Inc. All rights reserved.

An Empirically Calibrated Model of Cell Fate Decision Following Viral Infection

NASA Astrophysics Data System (ADS)

Coleman, Seth; Igoshin, Oleg; Golding, Ido

The life cycle of the virus (phage) lambda is an established paradigm for the way genetic networks drive cell fate decisions. But despite decades of interrogation, we are still unable to theoretically predict whether the infection of a given cell will result in cell death or viral dormancy. The poor predictive power of current models reflects the absence of quantitative experimental data describing the regulatory interactions between different lambda genes. To address this gap, we are constructing a theoretical model that captures the known interactions in the lambda network. Model assumptions and parameters are calibrated using new single-cell data from our lab, describing the activity of lambda genes at single-molecule resolution. We began with a mean-field model, aimed at exploring the population averaged gene-expression trajectories under different initial conditions. Next, we will develop a stochastic formulation, to capture the differences between individual cells within the population. The eventual goal is to identify how the post-infection decision is driven by the interplay between network topology, initial conditions, and stochastic effects. The insights gained here will inform our understanding of cell fate choices in more complex cellular systems.

Measurements and empirical model of the acoustic properties of reticulated vitreous carbon.

PubMed

Muehleisena, Ralph T; Beamer, C Walter; Tinianov, Brandon D

2005-02-01

Reticulated vitreous carbon (RVC) is a highly porous, rigid, open cell carbon foam structure with a high melting point, good chemical inertness, and low bulk thermal conductivity. For the proper design of acoustic devices such as acoustic absorbers and thermoacoustic stacks and regenerators utilizing RVC, the acoustic properties of RVC must be known. From knowledge of the complex characteristic impedance and wave number most other acoustic properties can be computed. In this investigation, the four-microphone transfer matrix measurement method is used to measure the complex characteristic impedance and wave number for 60 to 300 pore-per-inch RVC foams with flow resistivities from 1759 to 10,782 Pa s m(-2) in the frequency range of 330 Hz-2 kHz. The data are found to be poorly predicted by the fibrous material empirical model developed by Delany and Bazley, the open cell plastic foam empirical model developed by Qunli, or the Johnson-Allard microstructural model. A new empirical power law model is developed and is shown to provide good predictions of the acoustic properties over the frequency range of measurement. Uncertainty estimates for the constants of the model are also computed.

Measurements and empirical model of the acoustic properties of reticulated vitreous carbon

NASA Astrophysics Data System (ADS)

Muehleisen, Ralph T.; Beamer, C. Walter; Tinianov, Brandon D.

2005-02-01

Reticulated vitreous carbon (RVC) is a highly porous, rigid, open cell carbon foam structure with a high melting point, good chemical inertness, and low bulk thermal conductivity. For the proper design of acoustic devices such as acoustic absorbers and thermoacoustic stacks and regenerators utilizing RVC, the acoustic properties of RVC must be known. From knowledge of the complex characteristic impedance and wave number most other acoustic properties can be computed. In this investigation, the four-microphone transfer matrix measurement method is used to measure the complex characteristic impedance and wave number for 60 to 300 pore-per-inch RVC foams with flow resistivities from 1759 to 10 782 Pa s m-2 in the frequency range of 330 Hz-2 kHz. The data are found to be poorly predicted by the fibrous material empirical model developed by Delany and Bazley, the open cell plastic foam empirical model developed by Qunli, or the Johnson-Allard microstructural model. A new empirical power law model is developed and is shown to provide good predictions of the acoustic properties over the frequency range of measurement. Uncertainty estimates for the constants of the model are also computed. .

Intelligent Prediction of Fan Rotation Stall in Power Plants Based on Pressure Sensor Data Measured In-Situ

PubMed Central

Xu, Xiaogang; Wang, Songling; Liu, Jinlian; Liu, Xinyu

2014-01-01

Blower and exhaust fans consume over 30% of electricity in a thermal power plant, and faults of these fans due to rotation stalls are one of the most frequent reasons for power plant outage failures. To accurately predict the occurrence of fan rotation stalls, we propose a support vector regression machine (SVRM) model that predicts the fan internal pressures during operation, leaving ample time for rotation stall detection. We train the SVRM model using experimental data samples, and perform pressure data prediction using the trained SVRM model. To prove the feasibility of using the SVRM model for rotation stall prediction, we further process the predicted pressure data via wavelet-transform-based stall detection. By comparison of the detection results from the predicted and measured pressure data, we demonstrate that the SVRM model can accurately predict the fan pressure and guarantee reliable stall detection with a time advance of up to 0.0625 s. This superior pressure data prediction capability leaves significant time for effective control and prevention of fan rotation stall faults. This model has great potential for use in intelligent fan systems with stall prevention capability, which will ensure safe operation and improve the energy efficiency of power plants. PMID:24854057

Physical performance and clinical outcomes in dialysis patients: a secondary analysis of the EXCITE trial.

PubMed

Torino, Claudia; Manfredini, Fabio; Bolignano, Davide; Aucella, Filippo; Baggetta, Rossella; Barillà, Antonio; Battaglia, Yuri; Bertoli, Silvio; Bonanno, Graziella; Castellino, Pietro; Ciurlino, Daniele; Cupisti, Adamasco; D'Arrigo, Graziella; De Paola, Luciano; Fabrizi, Fabrizio; Fatuzzo, Pasquale; Fuiano, Giorgio; Lombardi, Luigi; Lucisano, Gaetano; Messa, Piergiorgio; Rapanà, Renato; Rapisarda, Francesco; Rastelli, Stefania; Rocca-Rey, Lisa; Summaria, Chiara; Zuccalà, Alessandro; Tripepi, Giovanni; Catizone, Luigi; Zoccali, Carmine; Mallamaci, Francesca

2014-01-01

Scarce physical activity predicts shorter survival in dialysis patients. However, the relationship between physical (motor) fitness and clinical outcomes has never been tested in these patients. We tested the predictive power of an established metric of motor fitness, the Six-Minute Walking Test (6MWT), for death, cardiovascular events and hospitalization in 296 dialysis patients who took part in the trial EXCITE (ClinicalTrials.gov Identifier: NCT01255969). During follow up 69 patients died, 90 had fatal and non-fatal cardiovascular events, 159 were hospitalized and 182 patients had the composite outcome. In multivariate Cox models - including the study allocation arm and classical and non-classical risk factors - an increase of 20 walked metres during the 6MWT was associated to a 6% reduction of the risk for the composite end-point (P=0.001) and a similar relationship existed between the 6MWT, mortality (P<0.001) and hospitalizations (P=0.03). A similar trend was observed for cardiovascular events but this relationship did not reach statistical significance (P=0.09). Poor physical performance predicts a high risk of mortality, cardiovascular events and hospitalizations in dialysis patients. Future studies, including phase-2 EXCITE, will assess whether improving motor fitness may translate into better clinical outcomes in this high risk population. © 2014 S. Karger AG, Basel.

Ultrasound disease activity of bilateral wrist and finger joints at three months reflects the clinical response at six months of patients with rheumatoid arthritis treated with biologic disease-modifying anti-rheumatic drugs.

PubMed

Kawashiri, Shin-Ya; Nishino, Ayako; Shimizu, Toshimasa; Umeda, Masataka; Fukui, Shoichi; Nakashima, Yoshikazu; Suzuki, Takahisa; Koga, Tomohiro; Iwamoto, Naoki; Ichinose, Kunihiro; Tamai, Mami; Nakamura, Hideki; Origuchi, Tomoki; Aoyagi, Kiyoshi; Kawakami, Atsushi

2017-03-01

We evaluated whether the early responsiveness of ultrasound synovitis can predict the clinical response in rheumatoid arthritis (RA) patients treated with biologic disease-modifying anti-rheumatic drugs (bDMARDs). Articular synovitis was assessed by ultrasound at 22 bilateral wrist and finger joints in 39 RA patients treated with bDMARDs. Each joint was assigned a gray-scale (GS) and power Doppler (PD) score from 0 to 3, and the sum of the GS or PD scores was considered to represent the ultrasound disease activity. We investigated the correlation of the change in ultrasound disease activity at three months with the EULAR response criteria at six months. GS and PD scores were significantly decreased at three months (p < 0.0001). The % changes of the GS and PD scores at three months were significantly higher at six months in moderate and good responders compared with non-responders (p < 0.05). These tendencies were numerically more prominent if clinical response was set as good responder or Disease Activity Score 28 remission. Poor improvement of ultrasound synovitis scores had good predictive value for non-responders at six months. The responsiveness of ultrasound disease activity is considered to predict further clinical response in RA patients treated with bDMARDs.

Nucleation, growth and localisation of microcracks: implications for predictability of rock failure

NASA Astrophysics Data System (ADS)

Main, I. G.; Kun, F.; Pál, G.; Jánosi, Z.

2016-12-01

The spontaneous emergence of localized co-operative deformation is an important phenomenon in the development of shear faults in porous media. It can be studied by empirical observation, by laboratory experiment or by numerical simulation. Here we investigate the evolution of damage and fragmentation leading up to and including system-sized failure in a numerical model of a porous rock, using discrete element simulations of the strain-controlled uniaxial compression of cylindrical samples of different finite size. As the system approaches macroscopic failure the number of fractures and the energy release rate both increase as a time-reversed Omori law, with scaling constants for the frequency-size distribution and the inter-event time, including their temporal evolution, that closely resemble those of natural experiments. The damage progressively localizes in a narrow shear band, ultimately a fault 'gouge' containing a large number of poorly-sorted non-cohesive fragments on a broad bandwidth of scales, with properties similar to those of natural and experimental faults. We determine the position and orientation of the central fault plane, the width of the deformation band and the spatial and mass distribution of fragments. The relative width of the deformation band decreases as a power law of the system size and the probability distribution of the angle of the damage plane converges to around 30 degrees, representing an emergent internal coefficient of friction of 0.7 or so. The mass of fragments is power law distributed, with an exponent that does not depend on scale, and is near that inferred for experimental and natural fault gouges. The fragments are in general angular, with a clear self-affine geometry. The consistency of this model with experimental and field results confirms the critical roles of pre-existing heterogeneity, elastic interactions, and finite system size to grain size ratio on the development of faults, and ultimately to assessing the predictive power of forecasts of failure time in such media.

Effect of the equivalent refractive index on intraocular lens power prediction with ray tracing after myopic laser in situ keratomileusis.

PubMed

Canovas, Carmen; van der Mooren, Marrie; Rosén, Robert; Piers, Patricia A; Wang, Li; Koch, Douglas D; Artal, Pablo

2015-05-01

To determine the impact of the equivalent refractive index (ERI) on intraocular lens (IOL) power prediction for eyes with previous myopic laser in situ keratomileusis (LASIK) using custom ray tracing. AMO B.V., Groningen, the Netherlands, and the Department of Ophthalmology, Baylor College of Medicine, Houston, Texas, USA. Retrospective data analysis. The ERI was calculated individually from the post-LASIK total corneal power. Two methods to account for the posterior corneal surface were tested; that is, calculation from pre-LASIK data or from post-LASIK data only. Four IOL power predictions were generated using a computer-based ray-tracing technique, including individual ERI results from both calculation methods, a mean ERI over the whole population, and the ERI for normal patients. For each patient, IOL power results calculated from the four predictions as well as those obtained with the Haigis-L were compared with the optimum IOL power calculated after cataract surgery. The study evaluated 25 patients. The mean and range of ERI values determined using post-LASIK data were similar to those determined from pre-LASIK data. Introducing individual or an average ERI in the ray-tracing IOL power calculation procedure resulted in mean IOL power errors that were not significantly different from zero. The ray-tracing procedure that includes an average ERI gave a greater percentage of eyes with an IOL power prediction error within ±0.5 diopter than the Haigis-L (84% versus 52%). For IOL power determination in post-LASIK patients, custom ray tracing including a modified ERI was an accurate procedure that exceeded the current standards for normal eyes. Copyright © 2015 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

Impact of charge transport on current–voltage characteristics and power-conversion efficiency of organic solar cells

PubMed Central

Würfel, Uli; Neher, Dieter; Spies, Annika; Albrecht, Steve

2015-01-01

This work elucidates the impact of charge transport on the photovoltaic properties of organic solar cells. Here we show that the analysis of current–voltage curves of organic solar cells under illumination with the Shockley equation results in values for ideality factor, photocurrent and parallel resistance, which lack physical meaning. Drift-diffusion simulations for a wide range of charge-carrier mobilities and illumination intensities reveal significant carrier accumulation caused by poor transport properties, which is not included in the Shockley equation. As a consequence, the separation of the quasi Fermi levels in the organic photoactive layer (internal voltage) differs substantially from the external voltage for almost all conditions. We present a new analytical model, which considers carrier transport explicitly. The model shows excellent agreement with full drift-diffusion simulations over a wide range of mobilities and illumination intensities, making it suitable for realistic efficiency predictions for organic solar cells. PMID:25907581

Wire-bending test as a predictor of preclinical performance by dental students.

PubMed

Kao, E C; Ngan, P W; Wilson, S; Kunovich, R

1990-10-01

Traditional Dental Aptitude Test and academic grade point average have been shown to be poor predictors of clinical performance by dental students. To refine predictors of psychomotor skills, a wire-bending test was given to 105 freshmen at the beginning of their dental education. Grades from seven restorative preclinical courses in their freshman and sophomore years were compared to scores on wire bending and the three traditional predictors: GPA, academic aptitude, and perceptual aptitude scores. Wire-bending scores correlated significantly with six out of seven preclinical restorative courses. The predictive power for preclinical performance was doubled when wire bending was added to traditional predictors in stepwise multiple regression analysis. Wire-bending scores identified students of low performance. These preliminary results suggest that the wire-bending test shows some potential as a screening test for identifying students who may hae psychomotor difficulties, early in their dental education.

U.S. military enlisted accession mental health screening: history and current practice.

PubMed

Cardona, Robert Andrew; Ritchie, Elspeth Cameron

2007-01-01

Through the stimulus of war and concerns about neuropsychiatric disability, the U.S. military developed methods to rapidly screen the mental health of World War I and II draftees. Intelligence testing and brief psychiatric screening expanded the accession physical examination and underwent revision to identify only gross mental health disability. Supplemental psychiatric evaluations and written psychological screening tools were abandoned after postwar assessments; they demonstrated poor predictive power in evaluating recruit service capacity for combat environments. Currently, only three mental health accession tools are used to screen applicants before their entrance into military service, namely, educational achievement, cognitive testing, and a cursory psychiatric evaluation. The Navy and Air Force use a fourth screening measure during entry-level training. Educational attainment with high school graduation has been the strongest predictor of finishing a service term. The purpose of this article is to provide both a historical review and a review of testing efforts.

Image statistics underlying natural texture selectivity of neurons in macaque V4

PubMed Central

Okazawa, Gouki; Tajima, Satohiro; Komatsu, Hidehiko

2015-01-01

Our daily visual experiences are inevitably linked to recognizing the rich variety of textures. However, how the brain encodes and differentiates a plethora of natural textures remains poorly understood. Here, we show that many neurons in macaque V4 selectively encode sparse combinations of higher-order image statistics to represent natural textures. We systematically explored neural selectivity in a high-dimensional texture space by combining texture synthesis and efficient-sampling techniques. This yielded parameterized models for individual texture-selective neurons. The models provided parsimonious but powerful predictors for each neuron’s preferred textures using a sparse combination of image statistics. As a whole population, the neuronal tuning was distributed in a way suitable for categorizing textures and quantitatively predicts human ability to discriminate textures. Together, we suggest that the collective representation of visual image statistics in V4 plays a key role in organizing the natural texture perception. PMID:25535362

Dynamics of Single-Photon Emission from Electrically Pumped Color Centers

NASA Astrophysics Data System (ADS)

Khramtsov, Igor A.; Agio, Mario; Fedyanin, Dmitry Yu.

2017-08-01

Low-power, high-speed, and bright electrically driven true single-photon sources, which are able to operate at room temperature, are vital for the practical realization of quantum-communication networks and optical quantum computations. Color centers in semiconductors are currently the best candidates; however, in spite of their intensive study in the past decade, the behavior of color centers in electrically controlled systems is poorly understood. Here we present a physical model and establish a theoretical approach to address single-photon emission dynamics of electrically pumped color centers, which interprets experimental results. We support our analysis with self-consistent numerical simulations of a single-photon emitting diode based on a single nitrogen-vacancy center in diamond and predict the second-order autocorrelation function and other emission characteristics. Our theoretical findings demonstrate remarkable agreement with the experimental results and pave the way to the understanding of single-electron and single-photon processes in semiconductors.

Effect of protein properties on display efficiency using the M13 phage display system.

PubMed

Imai, S; Mukai, Y; Takeda, T; Abe, Y; Nagano, K; Kamada, H; Nakagawa, S; Tsunoda, S; Tsutsumi, Y

2008-10-01

The M13 phage display system is a powerful technology for engineering proteins such as functional mutant proteins and peptides. In this system, it is necessary that the protein is displayed on the phage surface. Therefore, its application is often limited when a protein is poorly displayed. In this study, we attempted to understand the relationship between a protein's properties and its display efficiency using the well-known pIII and pVIII type phage display system. The display of positively charged SV40 NLS and HIV-1 Tat peptides on pill was less efficient than that of the neutrally charged RGDS peptide. When different molecular weight proteins (1.5-58 kDa) were displayed on pIII and pVIII, their display efficiencies were directly influenced by their molecular weights. These results indicate the usefulness in predicting a desired protein's compatibility with protein and peptide engineering using the phage display system.

Adult attachment style and childhood interpersonal trauma in non-epileptic attack disorder.

PubMed

Holman, Natalie; Kirkby, Antonia; Duncan, Susan; Brown, Richard J

2008-03-01

Non-epileptic attack disorder (NEAD) poses a significant clinical problem but is poorly understood. Attachment theory provides a framework for understanding the development and maintenance of NEAD and the contribution of childhood abuse and neglect to these processes. A cross-sectional design was used to study attachment style and early traumatic experiences in individuals with NEAD (N=17) compared to those with epilepsy (N=26). A significant difference in predominant attachment style between the two groups was found, with fearful attachment occurring more frequently in the NEAD group. Abuse and neglect were also significantly more common in the NEAD patients. Both early traumatic experiences and fearful attachment added significantly to the predictive power of a logistic regression equation after controlling for anxiety and dysthymia. The findings suggest a link between disturbed attachment and NEAD and have clinical implications for therapeutic intervention with this group.

Traditional and emerging molecular markers in neuroblastoma prognosis: the good, the bad and the ugly.

PubMed

Poremba, C; Hero, B; Goertz, H G; Scheel, C; Wai, D; Schaefer, K L; Christiansen, H; Berthold, F; Juergens, H; Boecker, W; Dockhorn-Dworniczak, B

2001-01-01

Neuroblastomas (NB) are a heterogeneous group of childhood tumours with a wide range of likelihood for tumour progression. As traditional parameters do not ensure completely accurate prognostic grouping, new molecular markers are needed for assessing the individual patient's prognosis more precisely. 133 NB of all stages were analysed in blind-trial fashion for telomerase activity (TA), expression of surviving, and MYCN status. These data were correlated with other traditional prognostic indicators and disease outcome. TA is a powerful independent prognostic marker for all stages and is capable of differentiating between good and poor outcome in putative "favourable" clinical or biological subgroups of NB patients. High surviving expression is associated with an adverse outcome, but is more difficult to interprete than TA because survivin expression needs to be accurately quantified to be of predictive value. We propose an extended progression model for NB including emerging prognostic markers, with emphasis on telomerase activity.

Modelling tooth–prey interactions in sharks: the importance of dynamic testing

PubMed Central

Farina, Stacy C.; Brash, Jeffrey; Summers, Adam P.

2016-01-01

The shape of shark teeth varies among species, but traditional testing protocols have revealed no predictive relationship between shark tooth morphology and performance. We developed a dynamic testing device to quantify cutting performance of teeth. We mimicked head-shaking behaviour in feeding large sharks by attaching teeth to the blade of a reciprocating power saw fixed in a custom-built frame. We tested three tooth types at biologically relevant speeds and found differences in tooth cutting ability and wear. Teeth from the bluntnose sixgill (Hexanchus griseus) showed poor cutting ability compared with tiger (Galeocerdo cuvier), sandbar (Carcharhinus plumbeus) and silky (C. falciformis) sharks, but they also showed no wear with repeated use. Some shark teeth are very sharp at the expense of quickly dulling, while others are less sharp but dull more slowly. This demonstrates that dynamic testing is vital to understanding the performance of shark teeth. PMID:27853592

Forecasting Electric Power Generation of Photovoltaic Power System for Energy Network

NASA Astrophysics Data System (ADS)

Kudo, Mitsuru; Takeuchi, Akira; Nozaki, Yousuke; Endo, Hisahito; Sumita, Jiro

Recently, there has been an increase in concern about the global environment. Interest is growing in developing an energy network by which new energy systems such as photovoltaic and fuel cells generate power locally and electric power and heat are controlled with a communications network. We developed the power generation forecast method for photovoltaic power systems in an energy network. The method makes use of weather information and regression analysis. We carried out forecasting power output of the photovoltaic power system installed in Expo 2005, Aichi Japan. As a result of comparing measurements with a prediction values, the average prediction error per day was about 26% of the measured power.

Emotional Disturbance and Chronic Low Back Pain.

ERIC Educational Resources Information Center

McCreary, Charles P.; And Others

1980-01-01

Patients high in alientation and distrust may be poor compliers. Because only the somatic concern dimension predicted outcome, a single scale that measures this characteristic may be sufficient for effective identification of the potential good v poor responders to conservative treatment of low back pain. (Author)

Using Reanalysis Data for the Prediction of Seasonal Wind Turbine Power Losses Due to Icing

NASA Astrophysics Data System (ADS)

Burtch, D.; Mullendore, G. L.; Delene, D. J.; Storm, B.

2013-12-01

The Northern Plains region of the United States is home to a significant amount of potential wind energy. However, in winter months capturing this potential power is severely impacted by the meteorological conditions, in the form of icing. Predicting the expected loss in power production due to icing is a valuable parameter that can be used in wind turbine operations, determination of wind turbine site locations and long-term energy estimates which are used for financing purposes. Currently, losses due to icing must be estimated when developing predictions for turbine feasibility and financing studies, while icing maps, a tool commonly used in Europe, are lacking in the United States. This study uses the Modern-Era Retrospective Analysis for Research and Applications (MERRA) dataset in conjunction with turbine production data to investigate various methods of predicting seasonal losses (October-March) due to icing at two wind turbine sites located 121 km apart in North Dakota. The prediction of icing losses is based on temperature and relative humidity thresholds and is accomplished using three methods. For each of the three methods, the required atmospheric variables are determined in one of two ways: using industry-specific software to correlate anemometer data in conjunction with the MERRA dataset and using only the MERRA dataset for all variables. For each season, a percentage of the total expected generated power lost due to icing is determined and compared to observed losses from the production data. An optimization is performed in order to determine the relative humidity threshold that minimizes the difference between the predicted and observed values. Eight seasons of data are used to determine an optimal relative humidity threshold, and a further three seasons of data are used to test this threshold. Preliminary results have shown that the optimized relative humidity threshold for the northern turbine is higher than the southern turbine for all methods. For the three test seasons, the optimized thresholds tend to under-predict the icing losses. However, the threshold determined using boundary layer similarity theory most closely predicts the power losses due to icing versus the other methods. For the northern turbine, the average predicted power loss over the three seasons is 4.65 % while the observed power loss is 6.22 % (average difference of 1.57 %). For the southern turbine, the average predicted power loss and observed power loss over the same time period are 4.43 % and 6.16 %, respectively (average difference of 1.73 %). The three-year average, however, does not clearly capture the variability that exists season-to-season. On examination of each of the test seasons individually, the optimized relative humidity threshold methodology performs better than fixed power loss estimates commonly used in the wind energy industry.

Improved accuracy of intraocular lens power calculation with the Zeiss IOLMaster.

PubMed

Olsen, Thomas

2007-02-01

This study aimed to demonstrate how the level of accuracy in intraocular lens (IOL) power calculation can be improved with optical biometry using partial optical coherence interferometry (PCI) (Zeiss IOLMaster) and current anterior chamber depth (ACD) prediction algorithms. Intraocular lens power in 461 consecutive cataract operations was calculated using both PCI and ultrasound and the accuracy of the results of each technique were compared. To illustrate the importance of ACD prediction per se, predictions were calculated using both a recently published 5-variable method and the Haigis 2-variable method and the results compared. All calculations were optimized in retrospect to account for systematic errors, including IOL constants and other off-set errors. The average absolute IOL prediction error (observed minus expected refraction) was 0.65 dioptres with ultrasound and 0.43 D with PCI using the 5-variable ACD prediction method (p < 0.00001). The number of predictions within +/- 0.5 D, +/- 1.0 D and +/- 2.0 D of the expected outcome was 62.5%, 92.4% and 99.9% with PCI, compared with 45.5%, 77.3% and 98.4% with ultrasound, respectively (p < 0.00001). The 2-variable ACD method resulted in an average error in PCI predictions of 0.46 D, which was significantly higher than the error in the 5-variable method (p < 0.001). The accuracy of IOL power calculation can be significantly improved using calibrated axial length readings obtained with PCI and modern IOL power calculation formulas incorporating the latest generation ACD prediction algorithms.

Using a Guided Machine Learning Ensemble Model to Predict Discharge Disposition following Meningioma Resection.

PubMed

Muhlestein, Whitney E; Akagi, Dallin S; Kallos, Justiss A; Morone, Peter J; Weaver, Kyle D; Thompson, Reid C; Chambless, Lola B

2018-04-01

Objective  Machine learning (ML) algorithms are powerful tools for predicting patient outcomes. This study pilots a novel approach to algorithm selection and model creation using prediction of discharge disposition following meningioma resection as a proof of concept. Materials and Methods  A diversity of ML algorithms were trained on a single-institution database of meningioma patients to predict discharge disposition. Algorithms were ranked by predictive power and top performers were combined to create an ensemble model. The final ensemble was internally validated on never-before-seen data to demonstrate generalizability. The predictive power of the ensemble was compared with a logistic regression. Further analyses were performed to identify how important variables impact the ensemble. Results  Our ensemble model predicted disposition significantly better than a logistic regression (area under the curve of 0.78 and 0.71, respectively, p  = 0.01). Tumor size, presentation at the emergency department, body mass index, convexity location, and preoperative motor deficit most strongly influence the model, though the independent impact of individual variables is nuanced. Conclusion  Using a novel ML technique, we built a guided ML ensemble model that predicts discharge destination following meningioma resection with greater predictive power than a logistic regression, and that provides greater clinical insight than a univariate analysis. These techniques can be extended to predict many other patient outcomes of interest.

Hybrid robust predictive optimization method of power system dispatch

DOEpatents

Chandra, Ramu Sharat [Niskayuna, NY; Liu, Yan [Ballston Lake, NY; Bose, Sumit [Niskayuna, NY; de Bedout, Juan Manuel [West Glenville, NY

2011-08-02

A method of power system dispatch control solves power system dispatch problems by integrating a larger variety of generation, load and storage assets, including without limitation, combined heat and power (CHP) units, renewable generation with forecasting, controllable loads, electric, thermal and water energy storage. The method employs a predictive algorithm to dynamically schedule different assets in order to achieve global optimization and maintain the system normal operation.

Power capability evaluation for lithium iron phosphate batteries based on multi-parameter constraints estimation

NASA Astrophysics Data System (ADS)

Wang, Yujie; Pan, Rui; Liu, Chang; Chen, Zonghai; Ling, Qiang

2018-01-01

The battery power capability is intimately correlated with the climbing, braking and accelerating performance of the electric vehicles. Accurate power capability prediction can not only guarantee the safety but also regulate driving behavior and optimize battery energy usage. However, the nonlinearity of the battery model is very complex especially for the lithium iron phosphate batteries. Besides, the hysteresis loop in the open-circuit voltage curve is easy to cause large error in model prediction. In this work, a multi-parameter constraints dynamic estimation method is proposed to predict the battery continuous period power capability. A high-fidelity battery model which considers the battery polarization and hysteresis phenomenon is presented to approximate the high nonlinearity of the lithium iron phosphate battery. Explicit analyses of power capability with multiple constraints are elaborated, specifically the state-of-energy is considered in power capability assessment. Furthermore, to solve the problem of nonlinear system state estimation, and suppress noise interference, the UKF based state observer is employed for power capability prediction. The performance of the proposed methodology is demonstrated by experiments under different dynamic characterization schedules. The charge and discharge power capabilities of the lithium iron phosphate batteries are quantitatively assessed under different time scales and temperatures.

Derivation of Tissue-specific Functional Gene Sets to Aid Transcriptomic Analysis of Chemical Impacts on the Teleost Reproductive Axis.

EPA Science Inventory

Oligonucleotide microarrays are a powerful tool for unsupervised analysis of chemical impacts on biological systems. However, the lack of well annotated biological pathways for many aquatic organisms, including fish, and the poor power of microarray-based analyses to detect diffe...

Balancing computation and communication power in power constrained clusters

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

Piga, Leonardo; Paul, Indrani; Huang, Wei

Systems, apparatuses, and methods for balancing computation and communication power in power constrained environments. A data processing cluster with a plurality of compute nodes may perform parallel processing of a workload in a power constrained environment. Nodes that finish tasks early may be power-gated based on one or more conditions. In some scenarios, a node may predict a wait duration and go into a reduced power consumption state if the wait duration is predicted to be greater than a threshold. The power saved by power-gating one or more nodes may be reassigned for use by other nodes. A cluster agentmore » may be configured to reassign the unused power to the active nodes to expedite workload processing.« less

Modeling of a resonant heat engine

NASA Astrophysics Data System (ADS)

Preetham, B. S.; Anderson, M.; Richards, C.

2012-12-01

A resonant heat engine in which the piston assembly is replaced by a sealed elastic cavity is modeled and analyzed. A nondimensional lumped-parameter model is derived and used to investigate the factors that control the performance of the engine. The thermal efficiency predicted by the model agrees with that predicted from the relation for the Otto cycle based on compression ratio. The predictions show that for a fixed mechanical load, increasing the heat input results in increased efficiency. The output power and power density are shown to depend on the loading for a given heat input. The loading condition for maximum output power is different from that required for maximum power density.

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

NASA Astrophysics Data System (ADS)

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

2013-05-01

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

Prediction of the effects of propeller operation on the static longitudinal stability of single-engine tractor monoplanes with flaps retracted

NASA Technical Reports Server (NTRS)

Weil, Joseph; Sleeman, William C , Jr

1949-01-01

The effects of propeller operation on the static longitudinal stability of single-engine tractor monoplanes are analyzed, and a simple method is presented for computing power-on pitching-moment curves for flap-retracted flight conditions. The methods evolved are based on the results of powered-model wind-tunnel investigations of 28 model configurations. Correlation curves are presented from which the effects of power on the downwash over the tail and the stabilizer effectiveness can be rapidly predicted. The procedures developed enable prediction of power-on longitudinal stability characteristics that are generally in very good agreement with experiment.

An Operating Method Using Prediction of Photovoltaic Power for a Photovoltaic-Diesel Hybrid Power Generation System

NASA Astrophysics Data System (ADS)

Yamamoto, Shigehiro; Sumi, Kazuyoshi; Nishikawa, Eiichi; Hashimoto, Takeshi

This paper describes a novel operating method using prediction of photovoltaic (PV) power for a photovoltaic-diesel hybrid power generation system. The system is composed of a PV array, a storage battery, a bi-directional inverter and a diesel engine generator (DG). The proposed method enables the system to save fuel consumption by using PV energy effectively, reducing charge and discharge energy of the storage battery, and avoiding low-load operation of the DG. The PV power is simply predicted from a theoretical equation of solar radiation and the observed PV energy for a constant time before the prediction. The amount of fuel consumption of the proposed method is compared with that of other methods by a simulation based on measurement data of the PV power at an actual PV generation system for one year. The simulation results indicate that the amount of fuel consumption of the proposed method is smaller than that of any other methods, and is close to that of the ideal operation of the DG.

A Comparison between Bench Press Throw and Ballistic Push-Up tests to assess upper-body power in trained individuals.

PubMed

Bartolomei, Sandro; Nigro, Federico; Ruggeri, Sandro; Lanzoni, Ivan Malagoli; Ciacci, Simone; Merni, Franco; Sadres, Eliahu; Hoffman, Jay R; Semprini, Gabriele

2018-03-06

The purpose of the present study was to validate the ballistic push-up test performed with hands on a force plate (BPU) as a method to measure upper-body power. Twenty-eight experienced resistance trained men (age = 25.4 ± 5.2 y; body mass = 78.5 ± 9.0 kg; body height = 179.6 ± 7.8 cm) performed, two days apart, a bench press 1RM test and upper-body power tests. Mean power and peak power were assessed using the bench press throw test (BT) and the BPU test performed in randomized order. The area under the force/power curve (AUC) obtained at BT was also calculated. Power expressed at BPU was estimated using a time-based prediction equation. Mean force and the participant's body weight were used to predict the bench press 1RM. Pearson product moment correlations were used to examine relationships between the power assessment methods and between the predicted 1RM bench and the actual value. Large correlations (0.79; p < 0.001) were found between AUC and mean power expressed at BPU. Large correlations were also detected between mean power and peak power expressed at BT and BPU (0.75; p < 0.001 and 0.74; p < 0.001, respectively). Very large correlations (0.87; p < 0.001) were found between the 1RM bench and the 1RM predicted by the BPU. Results of the present study indicate that BPU represents a valid and reliable method to estimate the upper-body power in resistance-trained individuals.

Foliar pH as a new plant trait: can it explain variation in foliar chemistry and carbon cycling processes among subarctic plant species and types?

PubMed

Cornelissen, J H C; Quested, H M; van Logtestijn, R S P; Pérez-Harguindeguy, N; Gwynn-Jones, D; Díaz, S; Callaghan, T V; Press, M C; Aerts, R

2006-03-01

Plant traits have become popular as predictors of interspecific variation in important ecosystem properties and processes. Here we introduce foliar pH as a possible new plant trait, and tested whether (1) green leaf pH or leaf litter pH correlates with biochemical and structural foliar traits that are linked to biogeochemical cycling; (2) there is consistent variation in green leaf pH or leaf litter pH among plant types as defined by nutrient uptake mode and higher taxonomy; (3) green leaf pH can predict a significant proportion of variation in leaf digestibility among plant species and types; (4) leaf litter pH can predict a significant proportion of variation in leaf litter decomposability among plant species and types. We found some evidence in support of all four hypotheses for a wide range of species in a subarctic flora, although cryptogams (fern allies and a moss) tended to weaken the patterns by showing relatively poor leaf digestibility or litter decomposability at a given pH. Among seed plant species, green leaf pH itself explained only up to a third of the interspecific variation in leaf digestibility and leaf litter up to a quarter of the interspecific variation in leaf litter decomposability. However, foliar pH substantially improved the power of foliar lignin and/or cellulose concentrations as predictors of these processes when added to regression models as a second variable. When species were aggregated into plant types as defined by higher taxonomy and nutrient uptake mode, green-specific leaf area was a more powerful predictor of digestibility or decomposability than any of the biochemical traits including pH. The usefulness of foliar pH as a new predictive trait, whether or not in combination with other traits, remains to be tested across more plant species, types and biomes, and also in relation to other plant or ecosystem traits and processes.

Studying the Power of the Integrative Weaning Index in Predicting the Success Rate of the Spontaneous Breathing Trial in Patients under Mechanical Ventilation.

PubMed

Ebrahimabadi, Sahar; Moghadam, Ahmad Bagheri; Vakili, Mohammadali; Modanloo, Mahnaz; Khoddam, Homeira

2017-08-01

The use of weaning predictive indicators can avoid early extubation and wrongful prolonged mechanical ventilation. This study aimed to determine the power of the integrative weaning index (IWI) in predicting the success rate of the spontaneous breathing trial (SBT) in patients under mechanical ventilation. In this prospective study, 105 patients undergoing mechanical ventilation for over 48 h were enrolled. Before weaning initiation, the IWI was calculated and based on the defined cutoff point (≥25), the success rate of the SBT was predicted. In case of weaning from the device, 2-h SBT was performed and the physiologic and respiratory indices were continuously studied while being intubated. If they were in the normal range besides the patient's tolerance, the test was considered as a success. The result was then compared with the IWI and further analyzed. The SBT was successful in 90 (85.7%) and unsuccessful in 15 (14.3%) cases. The difference between the true patient outcome after SBT, and the IWI prediction was 0.143 according to the Kappa agreement coefficient ( P < 0.001). Moreover, regarding the predictive power, IWI had high sensitivity (95.6%), specificity (40%), positive and negative predictive values (90.5% and 60), positive and negative likelihood ratios (1.59 and 0.11), and accuracy (86.7%). The IWI as a more objective indicator has acceptable accuracy and power for predicting the 2-h SBT result. Therefore, in addition to the reliable prediction of the final weaning outcome, it has favorable power to predict if the patient is ready to breathe spontaneously as the first step to weaning.

Studying the Power of the Integrative Weaning Index in Predicting the Success Rate of the Spontaneous Breathing Trial in Patients under Mechanical Ventilation

PubMed Central

Ebrahimabadi, Sahar; Moghadam, Ahmad Bagheri; Vakili, Mohammadali; Modanloo, Mahnaz; Khoddam, Homeira

2017-01-01

Background and Aims: The use of weaning predictive indicators can avoid early extubation and wrongful prolonged mechanical ventilation. This study aimed to determine the power of the integrative weaning index (IWI) in predicting the success rate of the spontaneous breathing trial (SBT) in patients under mechanical ventilation. Materials and Methods: In this prospective study, 105 patients undergoing mechanical ventilation for over 48 h were enrolled. Before weaning initiation, the IWI was calculated and based on the defined cutoff point (≥25), the success rate of the SBT was predicted. In case of weaning from the device, 2-h SBT was performed and the physiologic and respiratory indices were continuously studied while being intubated. If they were in the normal range besides the patient's tolerance, the test was considered as a success. The result was then compared with the IWI and further analyzed. Results: The SBT was successful in 90 (85.7%) and unsuccessful in 15 (14.3%) cases. The difference between the true patient outcome after SBT, and the IWI prediction was 0.143 according to the Kappa agreement coefficient (P < 0.001). Moreover, regarding the predictive power, IWI had high sensitivity (95.6%), specificity (40%), positive and negative predictive values (90.5% and 60), positive and negative likelihood ratios (1.59 and 0.11), and accuracy (86.7%). Conclusion: The IWI as a more objective indicator has acceptable accuracy and power for predicting the 2-h SBT result. Therefore, in addition to the reliable prediction of the final weaning outcome, it has favorable power to predict if the patient is ready to breathe spontaneously as the first step to weaning. PMID:28904477

Electronic stopping powers for heavy ions in SiC and SiO{sub 2}

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

Jin, K.; Xue, H.; Zhang, Y., E-mail: Zhangy1@ornl.gov

2014-01-28

Accurate information on electronic stopping power is fundamental for broad advances in materials science, electronic industry, space exploration, and sustainable energy technologies. In the case of slow heavy ions in light targets, current codes and models provide significantly inconsistent predictions, among which the Stopping and Range of Ions in Matter (SRIM) code is the most commonly used one. Experimental evidence, however, has demonstrated considerable errors in the predicted ion and damage profiles based on SRIM stopping powers. In this work, electronic stopping powers for Cl, Br, I, and Au ions are experimentally determined in two important functional materials, SiC andmore » SiO{sub 2}, based on a single ion technique, and new electronic stopping power values are derived over the energy regime from 0 to 15 MeV, where large deviations from the SRIM predictions are observed. As an experimental validation, Rutherford backscattering spectrometry (RBS) and secondary ion mass spectrometry (SIMS) are utilized to measure the depth profiles of implanted Au ions in SiC for energies from 700 keV to 15 MeV. The measured ion distributions by both RBS and SIMS are considerably deeper than the SRIM predictions, but agree well with predictions based on our derived stopping powers.« less

Electronic Stopping Powers For Heavy Ions In SiC And SiO2

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

Jin, Ke; Zhang, Y.; Zhu, Zihua

2014-01-24

Accurate information on electronic stopping power is fundamental for broad advances in materials science, electronic industry, space exploration, and sustainable energy technologies. In the case of slow heavy ions in light targets, current codes and models provide significantly inconsistent predictions, among which the Stopping and Range of Ions in Matter (SRIM) code is the most commonly used one. Experimental evidence, however, has demonstrated considerable errors in the predicted ion and damage profiles based on SRIM stopping powers. In this work, electronic stopping powers for Cl, Br, I, and Au ions are experimentally determined in two important functional materials, SiC andmore » SiO2, based on a single ion technique, and new electronic stopping power values are derived over the energy regime from 0 to 15 MeV, where large deviations from the SRIM predictions are observed. As an experimental validation, Rutherford backscattering spectrometry (RBS) and secondary ion mass spectrometry (SIMS) are utilized to measure the depth profiles of implanted Au ions in SiC for energies from 700 keV to 15MeV. The measured ion distributions by both RBS and SIMS are considerably deeper than the SRIM predictions, but agree well with predictions based on our derived stopping powers.« less

Comparison and validation of statistical methods for predicting power outage durations in the event of hurricanes.

PubMed

Nateghi, Roshanak; Guikema, Seth D; Quiring, Steven M

2011-12-01

This article compares statistical methods for modeling power outage durations during hurricanes and examines the predictive accuracy of these methods. Being able to make accurate predictions of power outage durations is valuable because the information can be used by utility companies to plan their restoration efforts more efficiently. This information can also help inform customers and public agencies of the expected outage times, enabling better collective response planning, and coordination of restoration efforts for other critical infrastructures that depend on electricity. In the long run, outage duration estimates for future storm scenarios may help utilities and public agencies better allocate risk management resources to balance the disruption from hurricanes with the cost of hardening power systems. We compare the out-of-sample predictive accuracy of five distinct statistical models for estimating power outage duration times caused by Hurricane Ivan in 2004. The methods compared include both regression models (accelerated failure time (AFT) and Cox proportional hazard models (Cox PH)) and data mining techniques (regression trees, Bayesian additive regression trees (BART), and multivariate additive regression splines). We then validate our models against two other hurricanes. Our results indicate that BART yields the best prediction accuracy and that it is possible to predict outage durations with reasonable accuracy. © 2011 Society for Risk Analysis.

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

Off-Ice Anaerobic Power Does Not Predict On-Ice Repeated Shift Performance in Hockey.

PubMed

Peterson, Ben J; Fitzgerald, John S; Dietz, Calvin C; Ziegler, Kevin S; Baker, Sarah E; Snyder, Eric M

2016-09-01

Peterson, BJ, Fitzgerald, JS, Dietz, CC, Ziegler, KS, Baker, SE, and Snyder, EM. Off-ice anaerobic power does not predict on-ice repeated shift performance in hockey. J Strength Cond Res 30(9): 2375-2381, 2016-Anaerobic power is a significant predictor of acceleration and top speed in team sport athletes. Historically, these findings have been applied to ice hockey although recent research has brought their validity for this sport into question. As ice hockey emphasizes the ability to repeatedly produce power, single bout anaerobic power tests should be examined to determine their ability to predict on-ice performance. We tested whether conventional off-ice anaerobic power tests could predict on-ice acceleration, top speed, and repeated shift performance. Forty-five hockey players, aged 18-24 years, completed anthropometric, off-ice, and on-ice tests. Anthropometric and off-ice testing included height, weight, body composition, vertical jump, and Wingate tests. On-ice testing consisted of acceleration, top speed, and repeated shift fatigue tests. Vertical jump (VJ) (r = -0.42; r = -0.58), Wingate relative peak power (WRPP) (r = -0.32; r = -0.43), and relative mean power (WRMP) (r = -0.34; r = -0.48) were significantly correlated (p ≤ 0.05) to on-ice acceleration and top speed, respectively. Conversely, none of the off-ice tests correlated with on-ice repeated shift performance, as measured by first gate, second gate, or total course fatigue; VJ (r = 0.06; r = 0.13; r = 0.09), WRPP (r = 0.06; r = 0.14; r = 0.10), or WRMP (r = -0.10; r = -0.01; r = -0.01). Although conventional off-ice anaerobic power tests predict single bout on-ice acceleration and top speed, they neither predict the repeated shift ability of the player, nor are good markers for performance in ice hockey.

Psychosocial mechanisms linking the social environment to mental health in African Americans

USDA-ARS?s Scientific Manuscript database

Resource-poor social environments predict poor health, but the mechanisms and processes linking the social environment to psychological health and well-being remain unclear. This study explored psychosocial mediators of the association between the social environment and mental health in African Amer...

Measured and predicted rotor performance for the SERI advanced wind turbine blades

NASA Astrophysics Data System (ADS)

Tangler, J.; Smith, B.; Kelley, N.; Jager, D.

1992-02-01

Measured and predicted rotor performance for the Solar Energy Research Institute (SERI) advanced wind turbine blades were compared to assess the accuracy of predictions and to identify the sources of error affecting both predictions and measurements. An awareness of these sources of error contributes to improved prediction and measurement methods that will ultimately benefit future rotor design efforts. Propeller/vane anemometers were found to underestimate the wind speed in turbulent environments such as the San Gorgonio Pass wind farm area. Using sonic or cup anemometers, good agreement was achieved between predicted and measured power output for wind speeds up to 8 m/sec. At higher wind speeds an optimistic predicted power output and the occurrence of peak power at wind speeds lower than measurements resulted from the omission of turbulence and yaw error. In addition, accurate two-dimensional (2-D) airfoil data prior to stall and a post stall airfoil data synthesization method that reflects three-dimensional (3-D) effects were found to be essential for accurate performance prediction.

NASA Lewis Stirling engine computer code evaluation

NASA Technical Reports Server (NTRS)

Sullivan, Timothy J.

1989-01-01

In support of the U.S. Department of Energy's Stirling Engine Highway Vehicle Systems program, the NASA Lewis Stirling engine performance code was evaluated by comparing code predictions without engine-specific calibration factors to GPU-3, P-40, and RE-1000 Stirling engine test data. The error in predicting power output was -11 percent for the P-40 and 12 percent for the Re-1000 at design conditions and 16 percent for the GPU-3 at near-design conditions (2000 rpm engine speed versus 3000 rpm at design). The efficiency and heat input predictions showed better agreement with engine test data than did the power predictions. Concerning all data points, the error in predicting the GPU-3 brake power was significantly larger than for the other engines and was mainly a result of inaccuracy in predicting the pressure phase angle. Analysis into this pressure phase angle prediction error suggested that improvements to the cylinder hysteresis loss model could have a significant effect on overall Stirling engine performance predictions.

Magnetic storm effects in electric power systems and prediction needs

NASA Technical Reports Server (NTRS)

Albertson, V. D.; Kappenman, J. G.

1979-01-01

Geomagnetic field fluctuations produce spurious currents in electric power systems. These currents enter and exit through points remote from each other. The fundamental period of these currents is on the order of several minutes which is quasi-dc compared to the normal 60 Hz or 50 Hz power system frequency. Nearly all of the power systems problems caused by the geomagnetically induced currents result from the half-cycle saturation of power transformers due to simultaneous ac and dc excitation. The effects produced in power systems are presented, current research activity is discussed, and magnetic storm prediction needs of the power industry are listed.

A variable capacitance based modeling and power capability predicting method for ultracapacitor

NASA Astrophysics Data System (ADS)

Liu, Chang; Wang, Yujie; Chen, Zonghai; Ling, Qiang

2018-01-01

Methods of accurate modeling and power capability predicting for ultracapacitors are of great significance in management and application of lithium-ion battery/ultracapacitor hybrid energy storage system. To overcome the simulation error coming from constant capacitance model, an improved ultracapacitor model based on variable capacitance is proposed, where the main capacitance varies with voltage according to a piecewise linear function. A novel state-of-charge calculation approach is developed accordingly. After that, a multi-constraint power capability prediction is developed for ultracapacitor, in which a Kalman-filter-based state observer is designed for tracking ultracapacitor's real-time behavior. Finally, experimental results verify the proposed methods. The accuracy of the proposed model is verified by terminal voltage simulating results under different temperatures, and the effectiveness of the designed observer is proved by various test conditions. Additionally, the power capability prediction results of different time scales and temperatures are compared, to study their effects on ultracapacitor's power capability.

The aerodynamic cost of flight in bats--comparing theory with measurement

NASA Astrophysics Data System (ADS)

von Busse, Rhea; Waldman, Rye M.; Swartz, Sharon M.; Breuer, Kenneth S.

2012-11-01

Aerodynamic theory has long been used to predict the aerodynamic power required for animal flight. However, even though the actuator disk model does not account for the flapping motion of a wing, it is used for lack of any better model. The question remains: how close are these predictions to reality? We designed a study to compare predicted aerodynamic power to measured power from the kinetic energy contained in the wake shed behind a bat flying in a wind tunnel. A high-accuracy displaced light-sheet stereo PIV system was used in the Trefftz plane to capture the wake behind four bats flown over a range of flight speeds (1-6m/s). The total power in the wake was computed from the wake vorticity and these estimates were compared with the power predicted using Pennycuick's model for bird flight as well as estimates derived from measurements of the metabolic cost of flight, previously acquired from the same individuals.

Esophageal Dysmotility in Patients following Total Laryngectomy.

PubMed

Zhang, Teng; Maclean, Julia; Szczesniak, Michal; Bertrand, Paul P; Quon, Harry; Tsang, Raymond K; Wu, Peter I; Graham, Peter; Cook, Ian J

2018-02-01

Objectives Dysphagia is common in total laryngectomees, with some symptoms suggesting esophageal dysmotility. Tracheoesophageal (TE) phonation requires effective esophagopharyngeal air passage. Hence, esophageal dysmotility may affect deglutition or TE phonation. This study aimed to determine (1) the characteristics of esophageal dysmotility in laryngectomees, (2) whether clinical history is sensitive in detecting esophageal dysmotility, and (3) the relationship between esophageal dysmotility and TE prosthesis dysfunction. Study Design Multidisciplinary cross-sectional study. Setting Tertiary academic hospital. Subjects and Methods For 31 participants undergone total laryngectomy 1 to 12 years prior, clinical histories were taken by a gastroenterologist and a speech pathologist experienced in managing dysphagia. Esophageal high-resolution manometry was performed and analyzed using Chicago Classification v3.0. Results Interpretable manometric studies were obtained in 23 (1 normal manometry). Esophageal dysmotility patterns included achalasia, esophagogastric junction outflow obstruction, diffuse esophageal spasm, and other major (30%) and minor (50%) peristaltic disorders. The sensitivity of predicting any esophageal dysmotility was 28%, but it is noteworthy that patients with achalasia and diffuse esophageal spasm (DES) were predicted. Two of 4 participants with TE puncture leakage had poor esophageal clearance. Of 20 TE speakers, 12 had voice problems, no correlation between poor voice, and any dysmotility pattern. Conclusions Peristaltic and lower esophageal sphincter dysfunction are common in laryngectomees. Clinical history, while not predictive of minor motor abnormalities, predicted correctly cases with treatable spastic motor disorders. Dysmotility was not associated with poor phonation, although TE puncture leakage might be linked to poor esophageal clearance. Esophageal dysmotility should be considered in the laryngectomees with persisting dysphagia or leaking TE puncture.

A new method of power load prediction in electrification railway

NASA Astrophysics Data System (ADS)

Dun, Xiaohong

2018-04-01

Aiming at the character of electrification railway, the paper mainly studies the problem of load prediction in electrification railway. After the preprocessing of data, and the similar days are separated on the basis of its statistical characteristics. Meanwhile the accuracy of different methods is analyzed. The paper provides a new thought of prediction and a new method of accuracy of judgment for the load prediction of power system.

A 3-Protein Expression Signature of Neuroblastoma for Outcome Prediction.

PubMed

Xie, Yi; Xu, Hua; Fang, Fang; Li, Zhiheng; Zhou, Huiting; Pan, Jian; Guo, Wanliang; Zhu, Xueming; Wang, Jian; Wu, Yi

2018-05-22

Neuroblastoma (NB) is the most common extracranial solid tumor in children with contrasting outcomes. Precise risk assessment contributes to prognosis prediction, which is critical for treatment strategy decisions. In this study, we developed a 3-protein predictor model, including the neural stem cell marker Msi1, neural differentiation marker ID1, and proliferation marker proliferating cell nuclear antigen (PCNA), to improve clinical risk assessment of patients with NB. Kaplan-Meier analysis in the microarray data (GSE16476) revealed that low expression of ID1 and high expression of Msi1 and PCNA were associated with poor prognosis in NB patients. Combined application of these 3 markers to constitute a signature further stratified NB patients into different risk subgroups can help obtain more accurate prediction performance. Survival prognostic power of age and Msi1_ID1_PCNA signature by receiver operating characteristics analysis showed that this signature predicted more effectively and sensitively compared with classic risk stratification system, compensating for the deficiency of the prediction function of the age. Furthermore, we validated the expressions of these 3 proteins in neuroblastic tumor spectrum tissues by immunohistochemistry revealed that Msi1 and PCNA exhibited increased expression in NB compared with intermedial ganglioneuroblastoma and benign ganglioneuroma, whereas ID1 levels were reduced in NB. In conclusion, we established a robust risk assessment predictor model based on simple immunohistochemistry for therapeutic decisions of NB patients.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0/.

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.

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

Electrocardiography based prediction of hypertrophy pattern and fibrosis amount in hypertrophic cardiomyopathy: comparative study with cardiac magnetic resonance imaging.

PubMed

Park, Chul Hwan; Chung, Hyemoon; Kim, Yoonjung; Kim, Jong-Youn; Min, Pil-Ki; Lee, Kyung-A; Yoon, Young Won; Kim, Tae Hoon; Lee, Byoung Kwon; Hong, Bum-Kee; Rim, Se-Joong; Kwon, Hyuck Moon; Choi, Eui-Young

2018-05-04

Although, cardiac magnetic resonance imaging (CMR) is a gold standard for risk stratification of hypertrophic cardiomyopathy (HCM), is limited in some situations. We sought to evaluate the predictive power of quantitative electrocardiography in assessing hypertrophy pattern and fibrosis in HCM. Eighty-eight patients with HCM were studied. Voltage of R-S-T waves, number of fragmented QRS (fQRS) complexes, and T wave morphology were measured by 12-lead electrocardiography. Sixteen segmental thickness, late gadolinium enhancement (LGE), native T1, extracellular volume fraction (ECV), and T2, left ventricular (LV) mass and %LGE were measured by CMR. Patterns of LV hypertrophy were classified as pure apical, mixed, or asymmetrical septal hypertrophy. Positive and negative predictive values of biphasic T wave for pure apical type were 70.4 and 63.9%, and the predictive values of precordial negative T wave sums [Formula: see text] 12.5 mm were 69.2 and 79.6%. Precordial S waves, especially Cornell voltage index, were significantly correlated to LV mass index and maximal thickness (p [Formula: see text]0.001). The number of fQRS leads was significantly correlated to %LGE, average ECV, and T2 (all p [Formula: see text]0.001). More than one lead with fQRS could predict [Formula: see text]5% of LGE mass with 58% sensitivity and 63% specificity (p = 0.049, area under the curve = 0.627). However, degree of correlation between maximal thickness and precordial S was poor in cases with fQRS more two leads. T wave morphology and precordial S helps discriminate hypertrophy pattern and maximal hypertrophy, however, in cases with more than two leads of concomitant fQRS, CMR defines fibrosis amount and hypertrophy more accurately.

Predictive Models of Liver Cancer

EPA Science Inventory

Predictive models of chemical-induced liver cancer face the challenge of bridging causative molecular mechanisms to adverse clinical outcomes. The latent sequence of intervening events from chemical insult to toxicity are poorly understood because they span multiple levels of bio...

A neural network based computational model to predict the output power of different types of photovoltaic cells.

PubMed

Xiao, WenBo; Nazario, Gina; Wu, HuaMing; Zhang, HuaMing; Cheng, Feng

2017-01-01

In this article, we introduced an artificial neural network (ANN) based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-), multi-crystalline (multi-), and amorphous (amor-) crystalline. The prediction results are very close to the experimental data, and were also influenced by numbers of hidden neurons. The order of the solar generation power output influenced by the external conditions from smallest to biggest is: multi-, mono-, and amor- crystalline silicon cells. In addition, the dependences of power prediction on the number of hidden neurons were studied. For multi- and amorphous crystalline cell, three or four hidden layer units resulted in the high correlation coefficient and low MSEs. For mono-crystalline cell, the best results were achieved at the hidden layer unit of 8.

Poor sleep in relation to natural menopause: a population-based 14-year follow-up of midlife women.

PubMed

Freeman, Ellen W; Sammel, Mary D; Gross, Stephanie A; Pien, Grace W

2015-07-01

This study aims to estimate the prevalence and predictors of moderate/severe poor sleep in relation to the final menstrual period (FMP) in midlife women. Annual assessments were conducted in a population-based cohort of 255 women. All were premenopausal at cohort enrollment and reached natural menopause during the 16-year follow-up. The outcome measure was severity of poor sleep, as reported by participants in annual interviews for 16 years and as evaluated in relation to the FMP. The annual prevalence of moderate/severe poor sleep largely ranged from about 28% to 35%, with no significant differences in any year relative to the FMP for the sample overall. When sleep status was stratified at premenopausal baseline, premenopausal sleep status strongly predicted poor sleep around the FMP. Women with moderate/severe poor sleep in premenopause were approximately 3.5 times more likely to have moderate/severe poor sleep around menopause than those with no poor sleep at baseline in adjusted analysis (odds ratio, 3.58; 95% CI, 2.50-5.11; P < 0.0001), whereas mild poor sleepers in premenopause were approximately 1.5 times more likely to have moderate/severe poor sleep around menopause (odds ratio, 1.57; 95% CI, 0.99-2.47; P = 0.053). There was no significant association between poor sleep and time relative to the FMP among women who had no poor sleep at premenopausal baseline. Hot flashes were significantly associated with poor sleep (odds ratio, 1.79; 95% CI, 1.44-2.21; P < 0.0001 in adjusted analysis) but had no interaction with baseline sleep severity (interaction P = 0.25), indicating that hot flashes contributed to poor sleep regardless of baseline sleep status. Findings show a high prevalence of moderate/severe poor sleep in midlife women, with only a small "at-risk" subgroup having a significant increase in poor sleep in relation to the FMP. Sleep status at premenopausal baseline and concurrent hot flashes strongly and consistently predict poor sleep in the menopausal transition. Overall, poor sleep does not increase around the FMP and frequently occurs in the absence of hot flashes, indicating that sleep difficulties in the menopausal transition in generally healthy women are not simply associated with ovarian decline.

Poor Sleep in Relation to Natural Menopause: A Population-Based 14-Year Follow-up of Mid-Life Women

PubMed Central

Freeman, Ellen W.; Sammel, Mary D.; Gross, Stephanie A.; Pien, Grace W.

2014-01-01

Objective To estimate the prevalence and predictors of moderate/severe poor sleep in relation to the final menstrual period (FMP) of mid-life women. Methods Annual assessments were conducted in a population-based cohort of 255 women. All were premenopausal at cohort enrollment and reached natural menopause during the 16-year follow-up. The outcome measure was the severity of poor sleep, as reported by the participants in annual interviews for 16 years and evaluated in relation to the FMP. Results The annual prevalence of moderate/severe poor sleep largely ranged from about 28% to 35%, with no significant differences in any year relative to the FMP for the sample overall. When sleep status was stratified at the premenopausal baseline, the premenopausal sleep status strongly predicted poor sleep around the FMP. Women with moderate/severe poor sleep when premenopausal were approximately 3 ½ times more likely to have moderate/severe poor sleep around menopause compared to those with no poor sleep at baseline in adjusted analysis (OR 3.58, 95% CI: 2.50-5.11, P<0.0001), while mild poor sleepers premenopause were approximately 1 ½ times more likely to have moderate/severe poor sleep around menopause (OR 1.57, 95% CI: 0.99-2.47, P=0.053). There was no significant association between poor sleep and time relative to the FMP among women who had no poor sleep at the premenopausal baseline. Hot flashes were significantly associated with poor sleep (OR 1.79, 95% CI: 1.44-2.21, P<0.0001 in adjusted analysis), but had no interaction with baseline sleep severity (interaction P=0.25), indicating that hot flashes contributed to poor sleep regardless of baseline sleep status. Conclusion The findings showed a high prevalence of moderate/severe poor sleep in mid-life women, with only a small “at risk” subgroup having a significant increase in poor sleep in relation to the FMP. Sleep status at the premenopausal baseline and concurrent hot flashes strongly and consistently predicted poor sleep in the menopause transition. Overall, poor sleep did not increase around the FMP and frequently occurred in the absence of hot flashes, indicating that sleep difficulties in the menopause transition in generally healthy women were not simply associated with ovarian decline. PMID:25549066

Predicting Handwriting Difficulties through Spelling Processes

ERIC Educational Resources Information Center

Rodríguez, Cristina; Villarroel, Rebeca

2017-01-01

This study examined whether spelling tasks contribute to the prediction of the handwriting status of children with poor and good handwriting skills in a cross-sectional study with 276 Spanish children from Grades 1 and 3. The main hypothesis was that the spelling tasks would predict the handwriting status of the children, although this influence…

Chronic and Acute Stress, Gender, and Serotonin Transporter Gene-Environment Interactions Predicting Depression Symptoms in Youth

ERIC Educational Resources Information Center

Hammen, Constance; Brennan, Patricia A.; Keenan-Miller, Danielle; Hazel, Nicholas A.; Najman, Jake M.

2010-01-01

Background: Many recent studies of serotonin transporter gene by environment effects predicting depression have used stress assessments with undefined or poor psychometric methods, possibly contributing to wide variation in findings. The present study attempted to distinguish between effects of acute and chronic stress to predict depressive…

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

NASA Technical Reports Server (NTRS)

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

1979-01-01

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

Clinical Value of Dorsal Medulla Oblongata Involvement Detected with Conventional MRI for Prediction of Outcome in Children with Enterovirus 71-related Brainstem Encephalitis.

PubMed

Liu, Kun; Zhou, Yongjin; Cui, Shihan; Song, Jiawen; Ye, Peipei; Xiang, Wei; Huang, Xiaoyan; Chen, Yiping; Yan, Zhihan; Ye, Xinjian

2018-04-05

Brainstem encephalitis is the most common neurologic complication after enterovirus 71 infection. The involvement of brainstem, especially the dorsal medulla oblongata, can cause severe sequelae or death in children with enterovirus 71 infection. We aimed to determine the prevalence of dorsal medulla oblongata involvement in children with enterovirus 71-related brainstem encephalitis (EBE) by using conventional MRI and to evaluate the value of dorsal medulla oblongata involvement in outcome prediction. 46 children with EBE were enrolled in the study. All subjects underwent a 1.5 Tesla MR examination of the brain. The disease distribution and clinical data were collected. Dichotomized outcomes (good versus poor) at longer than 6 months were available for 28 patients. Logistic regression was used to determine whether the MRI-confirmed dorsal medulla oblongata involvement resulted in improved clinical outcome prediction when compared with other location involvement. Of the 46 patients, 35 had MRI evidence of dorsal medulla oblongata involvement, 32 had pons involvement, 10 had midbrain involvement, and 7 had dentate nuclei involvement. Patients with dorsal medulla oblongata involvement or multiple area involvement were significantly more often in the poor outcome group than in the good outcome group. Logistic regression analysis showed that dorsal medulla oblongata involvement was the most significant single variable in outcome prediction (predictive accuracy, 90.5%), followed by multiple area involvement, age, and initial glasgow coma scale score. Dorsal medulla oblongata involvement on conventional MRI correlated significantly with poor outcomes in EBE children, improved outcome prediction when compared with other clinical and disease location variables, and was most predictive when combined with multiple area involvement, glasgow coma scale score and age.

High serum uric acid concentration predicts poor survival in patients with breast cancer.

PubMed

Yue, Cai-Feng; Feng, Pin-Ning; Yao, Zhen-Rong; Yu, Xue-Gao; Lin, Wen-Bin; Qian, Yuan-Min; Guo, Yun-Miao; Li, Lai-Sheng; Liu, Min

2017-10-01

Uric acid is a product of purine metabolism. Recently, uric acid has gained much attraction in cancer. In this study, we aim to investigate the clinicopathological and prognostic significance of serum uric acid concentration in breast cancer patients. A total of 443 female patients with histopathologically diagnosed breast cancer were included. After a mean follow-up time of 56months, survival was analysed using the Kaplan-Meier method. To further evaluate the prognostic significance of uric acid concentrations, univariate and multivariate Cox regression analyses were applied. Of the clinicopathological parameters, uric acid concentration was associated with age, body mass index, ER status and PR status. Univariate analysis identified that patients with increased uric acid concentration had a significantly inferior overall survival (HR 2.13, 95% CI 1.15-3.94, p=0.016). In multivariate analysis, we found that high uric acid concentration is an independent prognostic factor predicting death, but insufficient to predict local relapse or distant metastasis. Kaplan-Meier analysis indicated that high uric acid concentration is related to the poor overall survival (p=0.013). High uric acid concentration predicts poor survival in patients with breast cancer, and might serve as a potential marker for appropriate management of breast cancer patients. Copyright © 2017 Elsevier B.V. All rights reserved.

Impaired Patient-Reported Outcomes Predict Poor School Functioning and Daytime Sleepiness: The PROMIS Pediatric Asthma Study.

PubMed

Jones, Conor M; DeWalt, Darren A; Huang, I-Chan

Poor asthma control in children is related to impaired patient-reported outcomes (PROs; eg, fatigue, depressive symptoms, anxiety), but less well studied is the effect of PROs on children's school performance and sleep outcomes. In this study we investigated whether the consistency status of PROs over time affected school functioning and daytime sleepiness in children with asthma. Of the 238 children with asthma enrolled in the Patient-Reported Outcomes Measurement Information System (PROMIS) Pediatric Asthma Study, 169 children who provided survey data for all 4 time points were used in the analysis. The child's PROs, school functioning, and daytime sleepiness were measured 4 times within a 15-month period. PRO domains included asthma impact, pain interference, fatigue, depressive symptoms, anxiety, and mobility. Each child was classified as having poor/fair versus good PROs per meaningful cut points. The consistency status of each domain was classified as consistently poor/fair if poor/fair status was present for at least 3 time points; otherwise, the status was classified as consistently good. Seemingly unrelated regression was performed to test if consistently poor/fair PROs predicted impaired school functioning and daytime sleepiness at the fourth time point. Consistently poor/fair in all PRO domains was significantly associated with impaired school functioning and excessive daytime sleepiness (Ps < .01) after controlling for the influence of the child's age, sex, and race/ethnicity. Children with asthma with consistently poor/fair PROs are at risk of poor school functioning and daytime sleepiness. Developing child-friendly PRO assessment systems to track PROs can inform potential problems in the school setting. Copyright © 2017 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

External validation of a prediction model for surgical site infection after thoracolumbar spine surgery in a Western European cohort.

PubMed

Janssen, Daniël M C; van Kuijk, Sander M J; d'Aumerie, Boudewijn B; Willems, Paul C

2018-05-16

A prediction model for surgical site infection (SSI) after spine surgery was developed in 2014 by Lee et al. This model was developed to compute an individual estimate of the probability of SSI after spine surgery based on the patient's comorbidity profile and invasiveness of surgery. Before any prediction model can be validly implemented in daily medical practice, it should be externally validated to assess how the prediction model performs in patients sampled independently from the derivation cohort. We included 898 consecutive patients who underwent instrumented thoracolumbar spine surgery. To quantify overall performance using Nagelkerke's R 2 statistic, the discriminative ability was quantified as the area under the receiver operating characteristic curve (AUC). We computed the calibration slope of the calibration plot, to judge prediction accuracy. Sixty patients developed an SSI. The overall performance of the prediction model in our population was poor: Nagelkerke's R 2 was 0.01. The AUC was 0.61 (95% confidence interval (CI) 0.54-0.68). The estimated slope of the calibration plot was 0.52. The previously published prediction model showed poor performance in our academic external validation cohort. To predict SSI after instrumented thoracolumbar spine surgery for the present population, a better fitting prediction model should be developed.

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.

Estimation of Power Consumption in the Circular Sawing of Stone Based on Tangential Force Distribution

NASA Astrophysics Data System (ADS)

Huang, Guoqin; Zhang, Meiqin; Huang, Hui; Guo, Hua; Xu, Xipeng

2018-04-01

Circular sawing is an important method for the processing of natural stone. The ability to predict sawing power is important in the optimisation, monitoring and control of the sawing process. In this paper, a predictive model (PFD) of sawing power, which is based on the tangential force distribution at the sawing contact zone, was proposed, experimentally validated and modified. With regard to the influence of sawing speed on tangential force distribution, the modified PFD (MPFD) performed with high predictive accuracy across a wide range of sawing parameters, including sawing speed. The mean maximum absolute error rate was within 6.78%, and the maximum absolute error rate was within 11.7%. The practicability of predicting sawing power by the MPFD with few initial experimental samples was proved in case studies. On the premise of high sample measurement accuracy, only two samples are required for a fixed sawing speed. The feasibility of applying the MPFD to optimise sawing parameters while lowering the energy consumption of the sawing system was validated. The case study shows that energy use was reduced 28% by optimising the sawing parameters. The MPFD model can be used to predict sawing power, optimise sawing parameters and control energy.

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.

How well does a single question about health predict the financial health of Medicare managed care plans?

PubMed

Bierman, A S; Bubolz, T A; Fisher, E S; Wasson, J H

1999-01-01

Responses to simple questions that predict subsequent health care utilization are of interest to both capitated health plans and the payer. To determine how responses to a single question about general health status predict subsequent health care expenditures. Participants in the 1992 Medicare Current Beneficiary Survey were asked the following question: "In general, compared to other people your age, would you say your health is: excellent, very good, good, fair or poor?" To obtain each participant's total Medicare expenditures and number of hospitalizations in the ensuing year, we linked the responses to this question with data from the 1993 Medicare Continuous History Survey. Nationally representative sample of 8775 noninstitutionalized Medicare beneficiaries 65 years of age and older. Annual age- and sex-adjusted Medicare expenditures and hospitalization rates. Eighteen percent of the beneficiaries rated their health as excellent, 56% rated it as very good or good, 17% rated it as fair, and 7% rated it as poor. Medicare expenditures had a marked inverse relation to self-assessed health ratings. In the year after assessment, age- and sex-adjusted annual expenditures varied fivefold, from $8743 for beneficiaries rating their health as poor to $1656 for beneficiaries rating their health as excellent. Hospitalization rates followed the same pattern: Respondents who rated their health as poor had 675 hospitalizations per 1000 beneficiaries per year compared with 136 per 1000 for those rating their health as excellent. The response to a single question about general health status strongly predicts subsequent health care utilization. Self-reports of fair or poor health identify a group of high-risk patients who may benefit from targeted interventions. Because the current Medicare capitation formula does not account for health status, health plans can maximize profits by disproportionately enrolling beneficiaries who judge their health to be good. However, they are at a competitive disadvantage if they enroll beneficiaries who view themselves as sick.

Principals' Perceptions of Barriers to Dismissal of Poor-Performing Teachers

ERIC Educational Resources Information Center

Dandoy, Jason R.

2012-01-01

The purpose of this study is to determine which factors influence items that school principals consider "barriers" to dismissal of "incompetent" or "poor performing" teachers. This study determines if specific characteristics of schools, principals, or a combination of the two can predict the specific barriers cited…

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

Jin, Ke; Zhang, Yanwen; Zhu, Zihua

Accurate information of electronic stopping power is fundamental for broad advances in electronic industry, space exploration, national security, and sustainable energy technologies. The Stopping and Range of Ions in Matter (SRIM) code has been widely applied to predict stopping powers and ion distributions for decades. Recent experimental results have, however, shown considerable errors in the SRIM predictions for stopping of heavy ions in compounds containing light elements, indicating an urgent need to improve current stopping power models. The electronic stopping powers of 35Cl, 80Br, 127I, and 197Au ions are experimentally determined in two important functional materials, SiC and SiO2, frommore » tens to hundreds keV/u based on a single ion technique. By combining with the reciprocity theory, new electronic stopping powers are suggested in a region from 0 to 15 MeV, where large deviations from SRIM predictions are observed. For independent experimental validation of the electronic stopping powers we determined, Rutherford backscattering spectrometry (RBS) and secondary ion mass spectrometry (SIMS) are utilized to measure the depth profiles of implanted Au ions in SiC with energies from 700 keV to 15 MeV. The measured ion distributions from both RBS and SIMS are considerably deeper (up to ~30%) than the predictions from the commercial SRIM code. In comparison, the new electronic stopping power values are utilized in a modified TRIM-85 (the original version of the SRIM) code, M-TRIM, to predict ion distributions, and the results are in good agreement with the experimentally measured ion distributions.« less

NASA's Prediction Of Worldwide Energy Resource (POWER) Project Unveils a New Geospatial Data Portal

Atmospheric Science Data Center

2018-03-01

The Prediction Of Worldwide Energy Resource (POWER) Project facilitates access to NASA's satellite and modeling analysis for Renewable Energy, Sustainable Buildings and Agroclimatology applications.  A   new ...

Beyond climate envelopes: effects of weather on regional population trends in butterflies.

PubMed

WallisDeVries, Michiel F; Baxter, Wendy; Van Vliet, Arnold J H

2011-10-01

Although the effects of climate change on biodiversity are increasingly evident by the shifts in species ranges across taxonomical groups, the underlying mechanisms affecting individual species are still poorly understood. The power of climate envelopes to predict future ranges has been seriously questioned in recent studies. Amongst others, an improved understanding of the effects of current weather on population trends is required. We analysed the relation between butterfly abundance and the weather experienced during the life cycle for successive years using data collected within the framework of the Dutch Butterfly Monitoring Scheme for 40 species over a 15-year period and corresponding climate data. Both average and extreme temperature and precipitation events were identified, and multiple regression was applied to explain annual changes in population indices. Significant weather effects were obtained for 39 species, with the most frequent effects associated with temperature. However, positive density-dependence suggested climatic independent trends in at least 12 species. Validation of the short-term predictions revealed a good potential for climate-based predictions of population trends in 20 species. Nevertheless, data from the warm and dry year of 2003 indicate that negative effects of climatic extremes are generally underestimated for habitat specialists in drought-susceptible habitats, whereas generalists remain unaffected. Further climatic warming is expected to influence the trends of 13 species, leading to an improvement for nine species, but a continued decline in the majority of species. Expectations from climate envelope models overestimate the positive effects of climate change in northwestern Europe. Our results underline the challenge to include population trends in predicting range shifts in response to climate change.

Prevalence and Predictive Factors of Chronic Postsurgical Pain and Poor Global Recovery 1 Year After Outpatient Surgery.

PubMed

Hoofwijk, Daisy M N; Fiddelers, Audrey A A; Peters, Madelon L; Stessel, Björn; Kessels, Alfons G H; Joosten, Elbert A; Gramke, Hans-Fritz; Marcus, Marco A E

2015-12-01

To prospectively describe the prevalence and predictive factors of chronic postsurgical pain (CPSP) and poor global recovery in a large outpatient population at a university hospital, 1 year after outpatient surgery. A prospective longitudinal cohort study was performed. During 18 months, patients presenting for preoperative assessment were invited to participate. Outcome parameters were measured by using questionnaires at 3 timepoints: 1 week preoperatively, 4 days postoperatively, and 1 year postoperatively. A value of >3 on an 11-point numeric rating scale was considered to indicate moderate to severe pain. A score of ≤80% on the Global Surgical Recovery Index was defined as poor global recovery. A total of 908 patients were included. The prevalence of moderate to severe preoperative pain was 37.7%, acute postsurgical pain 26.7%, and CPSP 15.3%. Risk factors for the development of CPSP were surgical specialty, preoperative pain, preoperative analgesic use, acute postoperative pain, surgical fear, lack of optimism, and poor preoperative quality of life. The prevalence of poor global recovery was 22.3%. Risk factors for poor global recovery were recurrent surgery because of the same pathology, preoperative pain, preoperative analgesic use, surgical fear, lack of optimism, poor preoperative and acute postoperative quality of life, and follow-up surgery during the first postoperative year. Moderate to severe CPSP after outpatient surgery is common, and should not be underestimated. Patients at risk for developing CPSP can be identified during the preoperative phase.

The self-serving function of hypochondriacal complaints: physical symptoms as self-handicapping strategies.

PubMed

Smith, T W; Snyder, C R; Perkins, S C

1983-04-01

The present experiment tested the hypothesis that hypochondriacal individuals commonly use reports of physical illness and symptoms as a strategy to control attributions made about their performances in evaluative settings (i.e., self-handicapping strategies). Specifically, it was predicted that hypochondriacal individuals would report more recent physical illness and complaints and more current physical symptoms in an evaluative setting in which poor health could serve as an alternative explanation for poor performance than would either individuals in an evaluative setting in which poor health was precluded as an excuse or individuals in a nonevaluative setting. As predicted, results supported this self-protective pattern of complaints in a hypochondriacal sample but not in a nonhypochondriacal group. The self-protective role of hypochondriacal behavior is discussed in relation to other theory and research on the nature and treatment of hypochondriasis.

Gastric biomarkers: a global review.

PubMed

Baniak, Nick; Senger, Jenna-Lynn; Ahmed, Shahid; Kanthan, S C; Kanthan, Rani

2016-08-11

Gastric cancer is an aggressive disease with a poor 5-year survival and large global burden of disease. The disease is biologically and genetically heterogeneous with a poorly understood carcinogenesis at the molecular level. Despite the many prognostic, predictive, and therapeutic biomarkers investigated to date, gastric cancer continues to be detected at an advanced stage with resultant poor clinical outcomes. This is a global review of gastric biomarkers with an emphasis on HER2, E-cadherin, fibroblast growth factor receptor, mammalian target of rapamycin, and hepatocyte growth factor receptor as well as sections on microRNAs, long noncoding RNAs, matrix metalloproteinases, PD-L1, TP53, and microsatellite instability. A deeper understanding of the pathogenesis and biological features of gastric cancer, including the identification and characterization of diagnostic, prognostic, predictive, and therapeutic biomarkers, hopefully will provide improved clinical outcomes.

Predictability of Brayton electric power system performance

NASA Technical Reports Server (NTRS)

Klann, J. L.; Hettel, H. J.

1972-01-01

Data from the first tests of the 2- to 15-kilowatt space power system in a vacuum chamber were compared with predictions of both a pretest analysis and a modified version of that analysis. The pretest analysis predicted test results with differences of no more than 9 percent of the largest measured value for each quantity. The modified analysis correlated measurements. Differences in conversion efficiency and power output were no greater than plus or minus 2.5 percent. This modified analysis was used to project space performance maps for the current test system.

Sleep Quality Prediction From Wearable Data Using Deep Learning.

PubMed

Sathyanarayana, Aarti; Joty, Shafiq; Fernandez-Luque, Luis; Ofli, Ferda; Srivastava, Jaideep; Elmagarmid, Ahmed; Arora, Teresa; Taheri, Shahrad

2016-11-04

The importance of sleep is paramount to health. Insufficient sleep can reduce physical, emotional, and mental well-being and can lead to a multitude of health complications among people with chronic conditions. Physical activity and sleep are highly interrelated health behaviors. Our physical activity during the day (ie, awake time) influences our quality of sleep, and vice versa. The current popularity of wearables for tracking physical activity and sleep, including actigraphy devices, can foster the development of new advanced data analytics. This can help to develop new electronic health (eHealth) applications and provide more insights into sleep science. The objective of this study was to evaluate the feasibility of predicting sleep quality (ie, poor or adequate sleep efficiency) given the physical activity wearable data during awake time. In this study, we focused on predicting good or poor sleep efficiency as an indicator of sleep quality. Actigraphy sensors are wearable medical devices used to study sleep and physical activity patterns. The dataset used in our experiments contained the complete actigraphy data from a subset of 92 adolescents over 1 full week. Physical activity data during awake time was used to create predictive models for sleep quality, in particular, poor or good sleep efficiency. The physical activity data from sleep time was used for the evaluation. We compared the predictive performance of traditional logistic regression with more advanced deep learning methods: multilayer perceptron (MLP), convolutional neural network (CNN), simple Elman-type recurrent neural network (RNN), long short-term memory (LSTM-RNN), and a time-batched version of LSTM-RNN (TB-LSTM). Deep learning models were able to predict the quality of sleep (ie, poor or good sleep efficiency) based on wearable data from awake periods. More specifically, the deep learning methods performed better than traditional logistic regression. “CNN had the highest specificity and sensitivity, and an overall area under the receiver operating characteristic (ROC) curve (AUC) of 0.9449, which was 46% better as compared with traditional logistic regression (0.6463). Deep learning methods can predict the quality of sleep based on actigraphy data from awake periods. These predictive models can be an important tool for sleep research and to improve eHealth solutions for sleep. ©Aarti Sathyanarayana, Shafiq Joty, Luis Fernandez-Luque, Ferda Ofli, Jaideep Srivastava, Ahmed Elmagarmid, Teresa Arora, Shahrad Taheri. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 04.11.2016.

Sleep Quality Prediction From Wearable Data Using Deep Learning

PubMed Central

Sathyanarayana, Aarti; Joty, Shafiq; Ofli, Ferda; Srivastava, Jaideep; Elmagarmid, Ahmed; Arora, Teresa; Taheri, Shahrad

2016-01-01

Background The importance of sleep is paramount to health. Insufficient sleep can reduce physical, emotional, and mental well-being and can lead to a multitude of health complications among people with chronic conditions. Physical activity and sleep are highly interrelated health behaviors. Our physical activity during the day (ie, awake time) influences our quality of sleep, and vice versa. The current popularity of wearables for tracking physical activity and sleep, including actigraphy devices, can foster the development of new advanced data analytics. This can help to develop new electronic health (eHealth) applications and provide more insights into sleep science. Objective The objective of this study was to evaluate the feasibility of predicting sleep quality (ie, poor or adequate sleep efficiency) given the physical activity wearable data during awake time. In this study, we focused on predicting good or poor sleep efficiency as an indicator of sleep quality. Methods Actigraphy sensors are wearable medical devices used to study sleep and physical activity patterns. The dataset used in our experiments contained the complete actigraphy data from a subset of 92 adolescents over 1 full week. Physical activity data during awake time was used to create predictive models for sleep quality, in particular, poor or good sleep efficiency. The physical activity data from sleep time was used for the evaluation. We compared the predictive performance of traditional logistic regression with more advanced deep learning methods: multilayer perceptron (MLP), convolutional neural network (CNN), simple Elman-type recurrent neural network (RNN), long short-term memory (LSTM-RNN), and a time-batched version of LSTM-RNN (TB-LSTM). Results Deep learning models were able to predict the quality of sleep (ie, poor or good sleep efficiency) based on wearable data from awake periods. More specifically, the deep learning methods performed better than traditional linear regression. CNN had the highest specificity and sensitivity, and an overall area under the receiver operating characteristic (ROC) curve (AUC) of 0.9449, which was 46% better as compared with traditional linear regression (0.6463). Conclusions Deep learning methods can predict the quality of sleep based on actigraphy data from awake periods. These predictive models can be an important tool for sleep research and to improve eHealth solutions for sleep. PMID:27815231

Improving promoter prediction for the NNPP2.2 algorithm: a case study using Escherichia coli DNA sequences.

PubMed

Burden, S; Lin, Y-X; Zhang, R

2005-03-01

Although a great deal of research has been undertaken in the area of promoter prediction, prediction techniques are still not fully developed. Many algorithms tend to exhibit poor specificity, generating many false positives, or poor sensitivity. The neural network prediction program NNPP2.2 is one such example. To improve the NNPP2.2 prediction technique, the distance between the transcription start site (TSS) associated with the promoter and the translation start site (TLS) of the subsequent gene coding region has been studied for Escherichia coli K12 bacteria. An empirical probability distribution that is consistent for all E.coli promoters has been established. This information is combined with the results from NNPP2.2 to create a new technique called TLS-NNPP, which improves the specificity of promoter prediction. The technique is shown to be effective using E.coli DNA sequences, however, it is applicable to any organism for which a set of promoters has been experimentally defined. The data used in this project and the prediction results for the tested sequences can be obtained from http://www.uow.edu.au/~yanxia/E_Coli_paper/SBurden_Results.xls alh98@uow.edu.au.

Early Attachment Organization Moderates the Parent-Child Mutually Coercive Pathway to Children's Antisocial Conduct

ERIC Educational Resources Information Center

Kochanska, Grazyna; Barry, Robin A.; Stellern, Sarah A.; O'Bleness, Jessica J.

2009-01-01

This multimethod study of 101 mothers, fathers, and children elucidates poorly understood role of children's attachment security as "moderating" a common maladaptive trajectory: from parental power assertion, to child resentful opposition, to child antisocial conduct. Children's security was assessed at 15 months, parents' power assertion observed…

Issues of Power, Masculinity, and Gender Justice: Sally's Story of Teaching Boys

ERIC Educational Resources Information Center

Keddie, Amanda

2007-01-01

Despite calls for a more nuanced approach to issues of gender and equity that recognizes how broader relations of gender and power continue to produce injustices for many females, essentialized accounts expressing concern about boys' poor educational performance remain the most common refrain in dominant equity discourses across Western contexts.…

A Graphical Systems Model and Tissue-specific Functional Gene Sets to Aid Transcriptomic Analysis of Chemical Impacts on the Female Teleost Reproductive Axis

EPA Science Inventory

Oligonucleotide microarrays and other ‘omics’ approaches are powerful tools for unsupervised analysis of chemical impacts on biological systems. However, the lack of well annotated biological pathways for many aquatic organisms, including fish, and the poor power of microarray-b...

Ubiquitous Presenter: A Tablet PC-Based System to Support Instructors and Students

ERIC Educational Resources Information Center

Price, Edward; Simon, Beth

2009-01-01

Digital lecturing systems (computer and projector, often with PowerPoint) offer physics instructors the ability to incorporate graphics and the power to share and reuse materials. But these systems do a poor job of supporting interaction in the classroom. For instance, with digital presentation systems, instructors have limited ability to…

Efficacy of Insecticide and Bioinsecticide Ground Sprays to Control Metisa plana Walker (Lepidoptera: Psychidae) in Oil Palm Plantations, Malaysia.

PubMed

Salim, Hasber; Rawi, Che Salmah Md; Ahmad, Abu Hassan; Al-Shami, Salman Abdo

2015-12-01

The effectiveness of the synthetic insecticides trichlorfon, lambda-cyhalothrin, cypermethrin emulsion concentrated (EC) and cypermethrin emulsion water based (EW) and a bio-insecticide, Bacillus thuringiensis subsp. kurstaki (Btk), was evaluated at 3, 7, 14 and 30 days after treatment (DAT) for the control of Metisa plana larvae in an oil palm (Elaeis guineensis) plantation in Malaysia. Although all synthetic insecticides effectively reduced the larval population of M. plana, trichlorfon, lambda-cyhalothrin and cypermethrin EC were the fastest-acting. The larval population dropped below the economic threshold level (ETL) 30 days after a single application of the synthetic insecticides. Application of Btk, however, gave poor results, with the larval population remaining above the ETL post treatment. In terms of operational productivity, ground spraying using power spray equipment was time-consuming and resulted in poor coverage. Power spraying may not be appropriate for controlling M. plana infestations in large fields. Using a power sprayer, one man could cover 2-3 ha per day. Hence, power spraying is recommended during outbreaks of infestation in areas smaller than 50 ha.

Efficacy of Insecticide and Bioinsecticide Ground Sprays to Control Metisa plana Walker (Lepidoptera: Psychidae) in Oil Palm Plantations, Malaysia

PubMed Central

Salim, Hasber; Rawi, Che Salmah Md.; Ahmad, Abu Hassan; Al-Shami, Salman Abdo

2015-01-01

The effectiveness of the synthetic insecticides trichlorfon, lambda-cyhalothrin, cypermethrin emulsion concentrated (EC) and cypermethrin emulsion water based (EW) and a bio-insecticide, Bacillus thuringiensis subsp. kurstaki (Btk), was evaluated at 3, 7, 14 and 30 days after treatment (DAT) for the control of Metisa plana larvae in an oil palm (Elaeis guineensis) plantation in Malaysia. Although all synthetic insecticides effectively reduced the larval population of M. plana, trichlorfon, lambda-cyhalothrin and cypermethrin EC were the fastest-acting. The larval population dropped below the economic threshold level (ETL) 30 days after a single application of the synthetic insecticides. Application of Btk, however, gave poor results, with the larval population remaining above the ETL post treatment. In terms of operational productivity, ground spraying using power spray equipment was time-consuming and resulted in poor coverage. Power spraying may not be appropriate for controlling M. plana infestations in large fields. Using a power sprayer, one man could cover 2–3 ha per day. Hence, power spraying is recommended during outbreaks of infestation in areas smaller than 50 ha. PMID:26868711

Contralateral Delay Activity Tracks Fluctuations in Working Memory Performance.

PubMed

Adam, Kirsten C S; Robison, Matthew K; Vogel, Edward K

2018-01-08

Neural measures of working memory storage, such as the contralateral delay activity (CDA), are powerful tools in working memory research. CDA amplitude is sensitive to working memory load, reaches an asymptote at known behavioral limits, and predicts individual differences in capacity. An open question, however, is whether neural measures of load also track trial-by-trial fluctuations in performance. Here, we used a whole-report working memory task to test the relationship between CDA amplitude and working memory performance. If working memory failures are due to decision-based errors and retrieval failures, CDA amplitude would not differentiate good and poor performance trials when load is held constant. If failures arise during storage, then CDA amplitude should track both working memory load and trial-by-trial performance. As expected, CDA amplitude tracked load (Experiment 1), reaching an asymptote at three items. In Experiment 2, we tracked fluctuations in trial-by-trial performance. CDA amplitude was larger (more negative) for high-performance trials compared with low-performance trials, suggesting that fluctuations in performance were related to the successful storage of items. During working memory failures, participants oriented their attention to the correct side of the screen (lateralized P1) and maintained covert attention to the correct side during the delay period (lateralized alpha power suppression). Despite the preservation of attentional orienting, we found impairments consistent with an executive attention theory of individual differences in working memory capacity; fluctuations in executive control (indexed by pretrial frontal theta power) may be to blame for storage failures.

Direct measurement of neon production rates by (α,n) reactions in minerals

NASA Astrophysics Data System (ADS)

Cox, Stephen E.; Farley, Kenneth A.; Cherniak, Daniele J.

2015-01-01

The production of nucleogenic neon from alpha particle capture by 18O and 19F offers a potential chronometer sensitive to temperatures higher than the more widely used (U-Th)/He chronometer. The accuracy depends on the cross sections and the calculated stopping power for alpha particles in the mineral being studied. Published 18O(α,n)21Ne production rates are in poor agreement and were calculated from contradictory cross sections, and therefore demand experimental verification. Similarly, the stopping powers for alpha particles are calculated from SRIM (Stopping Range of Ions in Matter software) based on a limited experimental dataset. To address these issues we used a particle accelerator to implant alpha particles at precisely known energies into slabs of synthetic quartz (SiO2) and barium tungstate (BaWO4) to measure 21Ne production from capture by 18O. Within experimental uncertainties the observed 21Ne production rates compare favorably to our predictions using published cross sections and stopping powers, indicating that ages calculated using these quantities are accurate at the ∼3% level. In addition, we measured the 22Ne/21Ne ratio and (U-Th)/He and (U-Th)/Ne ages of Durango fluorapatite, which is an important model system for this work because it contains both oxygen and fluorine. Finally, we present 21Ne/4He production rate ratios for a variety of minerals of geochemical interest along with software for calculating neon production rates and (U-Th)/Ne ages.

Numerical Predictions of Wind Turbine Power and Aerodynamic Loads for the NREL Phase II and IV Combined Experiment Rotor

NASA Technical Reports Server (NTRS)

Duque, Earl P. N.; Johnson, Wayne; vanDam, C. P.; Chao, David D.; Cortes, Regina; Yee, Karen

1999-01-01

Accurate, reliable and robust numerical predictions of wind turbine rotor power remain a challenge to the wind energy industry. The literature reports various methods that compare predictions to experiments. The methods vary from Blade Element Momentum Theory (BEM), Vortex Lattice (VL), to variants of Reynolds-averaged Navier-Stokes (RaNS). The BEM and VL methods consistently show discrepancies in predicting rotor power at higher wind speeds mainly due to inadequacies with inboard stall and stall delay models. The RaNS methodologies show promise in predicting blade stall. However, inaccurate rotor vortex wake convection, boundary layer turbulence modeling and grid resolution has limited their accuracy. In addition, the inherently unsteady stalled flow conditions become computationally expensive for even the best endowed research labs. Although numerical power predictions have been compared to experiment. The availability of good wind turbine data sufficient for code validation experimental data that has been extracted from the IEA Annex XIV download site for the NREL Combined Experiment phase II and phase IV rotor. In addition, the comparisons will show data that has been further reduced into steady wind and zero yaw conditions suitable for comparisons to "steady wind" rotor power predictions. In summary, the paper will present and discuss the capabilities and limitations of the three numerical methods and make available a database of experimental data suitable to help other numerical methods practitioners validate their own work.

Projected electric power demands for the Potomac Electric Power Company

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

Wilson, J.W.

1975-07-01

Included are chapters on the background of the Potomac Electric Power Company, forecasting future power demand, demand modeling, accuracy of market predictions, and total power system requirements. (DG)

Power law behavior of RR-interval variability in healthy middle-aged persons, patients with recent acute myocardial infarction, and patients with heart transplants

NASA Technical Reports Server (NTRS)

Bigger, J. T. Jr; Steinman, R. C.; Rolnitzky, L. M.; Fleiss, J. L.; Albrecht, P.; Cohen, R. J.

1996-01-01

BACKGROUND. The purposes of the present study were (1) to establish normal values for the regression of log(power) on log(frequency) for, RR-interval fluctuations in healthy middle-aged persons, (2) to determine the effects of myocardial infarction on the regression of log(power) on log(frequency), (3) to determine the effect of cardiac denervation on the regression of log(power) on log(frequency), and (4) to assess the ability of power law regression parameters to predict death after myocardial infarction. METHODS AND RESULTS. We studied three groups: (1) 715 patients with recent myocardial infarction; (2) 274 healthy persons age and sex matched to the infarct sample; and (3) 19 patients with heart transplants. Twenty-four-hour RR-interval power spectra were computed using fast Fourier transforms and log(power) was regressed on log(frequency) between 10(-4) and 10(-2) Hz. There was a power law relation between log(power) and log(frequency). That is, the function described a descending straight line that had a slope of approximately -1 in healthy subjects. For the myocardial infarction group, the regression line for log(power) on log(frequency) was shifted downward and had a steeper negative slope (-1.15). The transplant (denervated) group showed a larger downward shift in the regression line and a much steeper negative slope (-2.08). The correlation between traditional power spectral bands and slope was weak, and that with log(power) at 10(-4) Hz was only moderate. Slope and log(power) at 10(-4) Hz were used to predict mortality and were compared with the predictive value of traditional power spectral bands. Slope and log(power) at 10(-4) Hz were excellent predictors of all-cause mortality or arrhythmic death. To optimize the prediction of death, we calculated a log(power) intercept that was uncorrelated with the slope of the power law regression line. We found that the combination of slope and zero-correlation log(power) was an outstanding predictor, with a relative risk of > 10, and was better than any combination of the traditional power spectral bands. The combination of slope and log(power) at 10(-4) Hz also was an excellent predictor of death after myocardial infarction. CONCLUSIONS. Myocardial infarction or denervation of the heart causes a steeper slope and decreased height of the power law regression relation between log(power) and log(frequency) of RR-interval fluctuations. Individually and, especially, combined, the power law regression parameters are excellent predictors of death of any cause or arrhythmic death and predict these outcomes better than the traditional power spectral bands.

History, Structure and Agency in Global Health Governance Comment on "Global Health Governance Challenges 2016 - Are We Ready?"

PubMed

Gill, Stephen; Benatar, Solomon R

2016-08-29

Ilona Kickbusch's thought provoking editorial is criticized in this commentary, partly because she fails to refer to previous critical work on the global conditions and policies that sustain inequality, poverty, poor health and damage to the biosphere and, as a result, she misreads global power and elides consideration of the fundamental historical structures of political and material power that shape agency in global health governance. We also doubt that global health can be improved through structures and processes of multilateralism that are premised on the continued reproduction of the ecologically myopic and socially unsustainable market civilization model of capitalist development that currently prevails in the world economy. This model drives net financial flows from poor to rich countries and from the poor to the affluent and super wealthy individuals. By contrast, we suggest that significant progress in global health requires a profound and socially just restructuring of global power, greater global solidarity and the "development of sustainability." © 2017 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Experimental validation of finite element and boundary element methods for predicting structural vibration and radiated noise

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Wu, T. W.; Wu, X. F.

1994-01-01

This research report is presented in three parts. In the first part, acoustical analyses were performed on modes of vibration of the housing of a transmission of a gear test rig developed by NASA. The modes of vibration of the transmission housing were measured using experimental modal analysis. The boundary element method (BEM) was used to calculate the sound pressure and sound intensity on the surface of the housing and the radiation efficiency of each mode. The radiation efficiency of each of the transmission housing modes was then compared to theoretical results for a finite baffled plate. In the second part, 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 level radiated from the box. The FEM was used to predict the vibration, while the BEM was used to predict the sound intensity and total radiated sound power using surface vibration as the input data. Vibration predicted by the FEM model was validated by experimental modal analysis; noise predicted by the BEM was validated by measurements of sound intensity. Three types of results are presented for the total radiated sound power: sound power predicted by the BEM model using vibration data measured on the surface of the box; sound power predicted by the FEM/BEM model; and sound power measured by an acoustic intensity scan. In the third part, the structure used in part two was modified. A rib was attached to the top plate of the structure. The FEM and BEM were then used to predict structural vibration and radiated noise respectively. The predicted vibration and radiated noise were then validated through experimentation.