Improving Power Density of Free-Piston Stirling Engines

NASA Technical Reports Server (NTRS)

Briggs, Maxwell H.; Prahl, Joseph M.; Loparo, Kenneth A.

2016-01-01

Analyses and experiments demonstrate the potential benefits of optimizing piston and displacer motion in a free-piston Stirling Engine. Isothermal analysis shows the theoretical limits of power density improvement due to ideal motion in ideal Stirling engines. More realistic models based on nodal analysis show that ideal piston and displacer waveforms are not optimal, often producing less power than engines that use sinusoidal piston and displacer motion. Constrained optimization using nodal analysis predicts that Stirling engine power density can be increased by as much as 58 percent using optimized higher harmonic piston and displacer motion. An experiment is conducted in which an engine designed for sinusoidal motion is forced to operate with both second and third harmonics, resulting in a piston power increase of as much as 14 percent. Analytical predictions are compared to experimental data and show close agreement with indirect thermodynamic power calculations, but poor agreement with direct electrical power measurements.

Improving Power Density of Free-Piston Stirling Engines

NASA Technical Reports Server (NTRS)

Briggs, Maxwell H.; Prahl, Joseph; Loparo, Kenneth

2016-01-01

Analyses and experiments demonstrate the potential benefits of optimizing piston and displacer motion in a free piston Stirling Engine. Isothermal analysis shows the theoretical limits of power density improvement due to ideal motion in ideal Stirling engines. More realistic models based on nodal analysis show that ideal piston and displacer waveforms are not optimal, often producing less power than engines that use sinusoidal piston and displacer motion. Constrained optimization using nodal analysis predicts that Stirling engine power density can be increased by as much as 58 using optimized higher harmonic piston and displacer motion. An experiment is conducted in which an engine designed for sinusoidal motion is forced to operate with both second and third harmonics, resulting in a maximum piston power increase of 14. Analytical predictions are compared to experimental data showing close agreement with indirect thermodynamic power calculations, but poor agreement with direct electrical power measurements.

Improving Free-Piston Stirling Engine Power Density

NASA Technical Reports Server (NTRS)

Briggs, Maxwell H.

2016-01-01

Analyses and experiments demonstrate the potential benefits of optimizing piston and displacer motion in a free piston Stirling Engine. Isothermal analysis shows the theoretical limits of power density improvement due to ideal motion in ideal Stirling engines. More realistic models based on nodal analysis show that ideal piston and displacer waveforms are not optimal, often producing less power than engines that use sinusoidal piston and displacer motion. Constrained optimization using nodal analysis predicts that Stirling engine power density can be increased by as much as 58% using optimized higher harmonic piston and displacer motion. An experiment is conducted in which an engine designed for sinusoidal motion is forced to operate with both second and third harmonics, resulting in a maximum piston power increase of 14%. Analytical predictions are compared to experimental data showing close agreement with indirect thermodynamic power calculations, but poor agreement with direct electrical power measurements.

Exercise dependence and the drive for muscularity in male bodybuilders, power lifters, and fitness lifters.

PubMed

Hale, Bruce D; Roth, Andrew D; DeLong, Ryan E; Briggs, Michael S

2010-06-01

Researchers have hypothesized differences in exercise dependence and drive for muscularity between bodybuilders and power lifters, while others have not found the predicted differences. This study assessed 146 weight lifters (bodybuilders, n=59; power lifters, n=47; fitness lifters, n=40) on the Exercise Dependence Scale, Bodybuilding Dependence Scale, and the Drive for Muscularity Scale. Results showed that bodybuilders and power lifters were significantly higher than fitness lifters on EDS Total, 7 EDS scales, and the 3 BDS scales. In contrast, power lifters were found to be significantly higher on DMS Total and DMS Behavior scales than bodybuilders. The regression results suggest that exercise dependence may be directly related to the drive for muscularity. 2010 Elsevier Ltd. All rights reserved.

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.

A Comparative Study to Assess the Predictability of Different IOL Power Calculation Formulas in Eyes of Short and Long Axial Length.

PubMed

Doshi, Dharmil; Limdi, Purvi; Parekh, Nilesh; Gohil, Neepa

2017-01-01

Accurate Intraocular Lens (IOL) power calculation in cataract surgery is very important for providing postoperative precise vision. Selection of most appropriate formula is difficult in high myopic and hypermetropic patients. To investigate the predictability of different IOL (Intra Ocular Lens) power calculation formulae in eyes with short and long Axial Length (AL) and to find out most accurate IOL power calculation formula in both groups. A prospective study was conducted on 80 consecutive patients who underwent phacoemulsification with monofocal IOL implantation after obtaining an informed and written consent. Preoperative keratometry was done by IOL Master. Axial length and anterior chamber depth was measured using A-scan machine ECHORULE 2 (BIOMEDIX). Patients were divided into two groups based on AL. (40 in each group). Group A with AL<22 mm and Group B with AL>24.5 mm. The IOL power calculation in each group was done by Haigis, Hoffer Q, Holladay-I, SRK/T formulae using the software of ECHORULE 2. The actual postoperative Spherical Equivalent (SE), Estimation error (E) and Absolute Error (AE) were calculated at one and half months and were used in data analysis. The predictive accuracy of each formula in each group was analyzed by comparing the Absolute Error (AE). The Kruskal Wallis test was used to compare differences in the (AE) of the formulae. A statistically significant difference was defined as p-value<0.05. In Group A, Hoffer Q, Holladay 1 and SRK/T formulae were equally accurate in predicting the postoperative refraction after cataract surgery (IOL power calculation) in eyes with AL less than 22.0 mm and accuracy of these three formulae was significantly higher than Haigis formula. Whereas in Group B, Hoffer Q, Holladay 1, SRK/T and Haigis formulae were equally accurate in predicting the postoperative refraction after cataract surgery (IOL power calculation) in eyes with AL more than 24.5 mm. Hoffer Q, Holladay 1 and SRK/T formulae were showing significantly higher accuracy than Haigis formula in predicting the postoperative refraction after cataract surgery (IOL power calculation) in eyes with AL less than 22.0 mm. In eyes with AL more than 24.5 mm Hoffer Q, Holladay 1, SRK/T and Haigis formulae were equally accurate.

A Comparative Study to Assess the Predictability of Different IOL Power Calculation Formulas in Eyes of Short and Long Axial Length

PubMed Central

Limdi, Purvi; Parekh, Nilesh; Gohil, Neepa

2017-01-01

Introduction Accurate Intraocular Lens (IOL) power calculation in cataract surgery is very important for providing postoperative precise vision. Selection of most appropriate formula is difficult in high myopic and hypermetropic patients. Aim To investigate the predictability of different IOL (Intra Ocular Lens) power calculation formulae in eyes with short and long Axial Length (AL) and to find out most accurate IOL power calculation formula in both groups. Materials and Methods A prospective study was conducted on 80 consecutive patients who underwent phacoemulsification with monofocal IOL implantation after obtaining an informed and written consent. Preoperative keratometry was done by IOL Master. Axial length and anterior chamber depth was measured using A-scan machine ECHORULE 2 (BIOMEDIX). Patients were divided into two groups based on AL. (40 in each group). Group A with AL<22 mm and Group B with AL>24.5 mm. The IOL power calculation in each group was done by Haigis, Hoffer Q, Holladay-I, SRK/T formulae using the software of ECHORULE 2. The actual postoperative Spherical Equivalent (SE), Estimation error (E) and Absolute Error (AE) were calculated at one and half months and were used in data analysis. The predictive accuracy of each formula in each group was analyzed by comparing the Absolute Error (AE). The Kruskal Wallis test was used to compare differences in the (AE) of the formulae. A statistically significant difference was defined as p-value<0.05. Results In Group A, Hoffer Q, Holladay 1 and SRK/T formulae were equally accurate in predicting the postoperative refraction after cataract surgery (IOL power calculation) in eyes with AL less than 22.0 mm and accuracy of these three formulae was significantly higher than Haigis formula. Whereas in Group B, Hoffer Q, Holladay 1, SRK/T and Haigis formulae were equally accurate in predicting the postoperative refraction after cataract surgery (IOL power calculation) in eyes with AL more than 24.5 mm. Conclusion Hoffer Q, Holladay 1 and SRK/T formulae were showing significantly higher accuracy than Haigis formula in predicting the postoperative refraction after cataract surgery (IOL power calculation) in eyes with AL less than 22.0 mm. In eyes with AL more than 24.5 mm Hoffer Q, Holladay 1, SRK/T and Haigis formulae were equally accurate. PMID:28273986

Social goals, aggression, peer preference, and popularity: longitudinal links during middle school.

PubMed

Ojanen, Tiina; Findley-Van Nostrand, Danielle

2014-08-01

Social goals are associated with behaviors and adjustment among peers. However, it remains unclear whether goals predict adolescent social development. We examined prospective associations among goals, physical and relational aggression, social preference, and popularity during middle school (N = 384 participants, ages 12-14 years). Agentic (status, power) goals predicted increased relational aggression and communal (closeness) goals predicted decreased physical aggression. Popularity predicted increases and preference predicted decreases in both forms of aggression. Goals moderated longitudinal links between aggression and popularity: Aggression predicted increases in popularity and vice versa for youth with higher agentic goals, and popularity predicted increases in physical aggression for youth with higher agentic and lower communal goals. Implications for research on social goals, aggression, and popularity are discussed. PsycINFO Database Record (c) 2014 APA, all rights reserved.

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.

Prediction by data mining, of suicide attempts in Korean adolescents: a national study

PubMed Central

Bae, Sung Man; Lee, Seung A; Lee, Seung-Hwan

2015-01-01

Objective This study aimed to develop a prediction model for suicide attempts in Korean adolescents. Methods We conducted a decision tree analysis of 2,754 middle and high school students nationwide. We fixed suicide attempt as the dependent variable and eleven sociodemographic, intrapersonal, and extrapersonal variables as independent variables. Results The rate of suicide attempts of the total sample was 9.5%, and severity of depression was the strongest variable to predict suicide attempt. The rates of suicide attempts in the depression and potential depression groups were 5.4 and 2.8 times higher than that of the non-depression group. In the depression group, the most powerful factor to predict a suicide attempt was delinquency, and the rate of suicide attempts in those in the depression group with higher delinquency was two times higher than in those in the depression group with lower delinquency. Of special note, the rate of suicide attempts in the depressed females with higher delinquency was the highest. Interestingly, in the potential depression group, the most impactful factor to predict a suicide attempt was intimacy with family, and the rate of suicide attempts of those in the potential depression group with lower intimacy with family was 2.4 times higher than that of those in the potential depression group with higher intimacy with family. And, among the potential depression group, middle school students with lower intimacy with family had a 2.5-times higher rate of suicide attempts than high school students with lower intimacy with family. Finally, in the non-depression group, stress level was the most powerful factor to predict a suicide attempt. Among the non-depression group, students who reported high levels of stress showed an 8.3-times higher rate of suicide attempts than students who reported average levels of stress. Discussion Based on the results, we especially need to pay attention to depressed females with higher delinquency and those with potential depression with lower intimacy with family to prevent suicide attempts in teenagers. PMID:26396521

The spectrum of the geoid from altimeter data

NASA Technical Reports Server (NTRS)

Wagner, C. A.

1977-01-01

A variety of sources of detailed information has been analyzed to arrive at a geoid power spectrum from global altimeter data. Using the equivalent of only two revolutions of data (mostly from GEOS-3) from all the major oceans, the high frequency geoid power (rms) is estimated (most simply) to be 80.7 n to the minus 1.47th power meters, where n is in cycles/global revolutions. This law is valid for all frequencies above 19 cycles but includes sea state. The (simple) law has more power than predicted by Kaula's rule for the geopotential. However, the data shows significantly less power for frequencies below 100 cycles. A closer approximation to the altimetry accumulates 2.18m (rss) for all frequencies higher than 19 cycles/rev. (including sea state), somewhat less power than predicted by the rule. The data permits up to 1.25 (rms) non-gravitational departures from the high frequency marine geoid.

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.

47 CFR 76.55 - Definitions applicable to the must-carry rules.

Code of Federal Regulations, 2010 CFR

2010-10-01

... television station with five watts or higher power serving the franchise area, (ii) A full-service station or... the purposes of § 76.55(a), “serving the franchise area” will be based on the predicted protected... all obligations and requirements applicable to full power television broadcast stations under part 73...

Radar observations of density gradients, electric fields, and plasma irregularities near polar cap patches in the context of the gradient-drift instability

NASA Astrophysics Data System (ADS)

Lamarche, Leslie J.; Makarevich, Roman A.

2017-03-01

We present observations of plasma density gradients, electric fields, and small-scale plasma irregularities near a polar cap patch made by the Super Dual Auroral Radar Network radar at Rankin Inlet (RKN) and the northern face of Resolute Bay Incoherent Scatter Radar (RISR-N). RKN echo power and occurrence are analyzed in the context of gradient-drift instability (GDI) theory, with a particular focus on the previously uninvestigated 2-D dependencies on wave propagation, electric field, and gradient vectors, with the latter two quantities evaluated directly from RISR-N measurements. It is shown that higher gradient and electric field components along the wave vector generally lead to the higher observed echo occurrence, which is consistent with the expected higher GDI growth rate, but the relationship with echo power is far less straightforward. The RKN echo power increases monotonically as the predicted linear growth rate approaches zero from negative values but does not continue this trend into positive growth rate values, in contrast with GDI predictions. The observed greater consistency of echo occurrence with GDI predictions suggests that GDI operating in the linear regime can control basic plasma structuring, but measured echo strength may be affected by other processes and factors, such as multistep or nonlinear processes or a shear-driven instability.

Temperature Effects in Varactors and Multipliers

NASA Technical Reports Server (NTRS)

East, J.; Mehdi, Imran

2001-01-01

Varactor diode multipliers are a critical part of many THz measurement systems. The power and efficiencies of these devices limit the available power for THz sources. Varactor operation is determined by the physics of the varactor device and a careful doping profile design is needed to optimize the performance. Higher doped devices are limited by junction breakdown and lower doped structures are limited by current saturation. Higher doped structures typically have higher efficiencies and lower doped structures typically have higher powers at the same operating frequency and impedance level. However, the device material properties are also a function of the operating temperature. Recent experimental evidence has shown that the power output of a multiplier can be improved by cooling the device. We have used a particle Monte Carlo simulation to investigate the temperature dependent velocity vs. electric field in GaAs. This information was then included in a nonlinear device circuit simulator to predict multiplier performance for various temperatures and device designs. This paper will describe the results of this analysis of temperature dependent multiplier operation.

Predictive analysis of beer quality by correlating sensory evaluation with higher alcohol and ester production using multivariate statistics methods.

PubMed

Dong, Jian-Jun; Li, Qing-Liang; Yin, Hua; Zhong, Cheng; Hao, Jun-Guang; Yang, Pan-Fei; Tian, Yu-Hong; Jia, Shi-Ru

2014-10-15

Sensory evaluation is regarded as a necessary procedure to ensure a reproducible quality of beer. Meanwhile, high-throughput analytical methods provide a powerful tool to analyse various flavour compounds, such as higher alcohol and ester. In this study, the relationship between flavour compounds and sensory evaluation was established by non-linear models such as partial least squares (PLS), genetic algorithm back-propagation neural network (GA-BP), support vector machine (SVM). It was shown that SVM with a Radial Basis Function (RBF) had a better performance of prediction accuracy for both calibration set (94.3%) and validation set (96.2%) than other models. Relatively lower prediction abilities were observed for GA-BP (52.1%) and PLS (31.7%). In addition, the kernel function of SVM played an essential role of model training when the prediction accuracy of SVM with polynomial kernel function was 32.9%. As a powerful multivariate statistics method, SVM holds great potential to assess beer quality. Copyright © 2014 Elsevier Ltd. All rights reserved.

Why Linking Budgets to Plans Has Proven Difficult in Higher Education.

ERIC Educational Resources Information Center

Schmidtlein, Frank A.

1990-01-01

Conclusions from two studies (including a three-year nationwide study of higher education institutional planning) concern types of planning (strategic, program, facility, operational, budget, and issue-specific), and limitations (the limited powers of prediction and the political character of planning and budgeting). Types of budgeting processes…

Predicting outcome of Internet-based treatment for depressive symptoms.

PubMed

Warmerdam, Lisanne; Van Straten, Annemieke; Twisk, Jos; Cuijpers, Pim

2013-01-01

In this study we explored predictors and moderators of response to Internet-based cognitive behavioral therapy (CBT) and Internet-based problem-solving therapy (PST) for depressive symptoms. The sample consisted of 263 participants with moderate to severe depressive symptoms. Of those, 88 were randomized to CBT, 88 to PST and 87 to a waiting list control condition. Outcomes were improvement and clinically significant change in depressive symptoms after 8 weeks. Higher baseline depression and higher education predicted improvement, while higher education, less avoidance behavior and decreased rational problem-solving skills predicted clinically significant change across all groups. No variables were found that differentially predicted outcome between Internet-based CBT and Internet-based PST. More research is needed with sufficient power to investigate predictors and moderators of response to reveal for whom Internet-based therapy is best suited.

Identification of the Best Anthropometric Predictors of Serum High- and Low-Density Lipoproteins Using Machine Learning.

PubMed

Lee, Bum Ju; Kim, Jong Yeol

2015-09-01

Serum high-density lipoprotein (HDL) and low-density lipoprotein (LDL) cholesterol levels are associated with risk factors for various diseases and are related to anthropometric measures. However, controversy remains regarding the best anthropometric indicators of the HDL and LDL cholesterol levels. The objectives of this study were to identify the best predictors of HDL and LDL cholesterol using statistical analyses and two machine learning algorithms and to compare the predictive power of combined anthropometric measures in Korean adults. A total of 13,014 subjects participated in this study. The anthropometric measures were assessed with binary logistic regression (LR) to evaluate statistically significant differences between the subjects with normal and high LDL cholesterol levels and between the subjects with normal and low HDL cholesterol levels. LR and the naive Bayes algorithm (NB), which provides more reasonable and reliable results, were used in the analyses of the predictive power of individual and combined measures. The best predictor of HDL was the rib to hip ratio (p =< 0.0001; odds ratio (OR) = 1.895; area under curve (AUC) = 0.681) in women and the waist to hip ratio (WHR) (p =< 0.0001; OR = 1.624; AUC = 0.633) in men. In women, the strongest indicator of LDL was age (p =< 0.0001; OR = 1.662; AUC by NB = 0.653 ; AUC by LR = 0.636). Among the anthropometric measures, the body mass index (BMI), WHR, forehead to waist ratio, forehead to rib ratio, and forehead to chest ratio were the strongest predictors of LDL; these measures had similar predictive powers. The strongest predictor in men was BMI (p =< 0.0001; OR = 1.369; AUC by NB = 0.594; AUC by LR = 0.595 ). The predictive power of almost all individual anthropometric measures was higher for HDL than for LDL, and the predictive power for both HDL and LDL in women was higher than for men. A combination of anthropometric measures slightly improved the predictive power for both HDL and LDL cholesterol. The best indicator for HDL and LDL might differ according to the type of cholesterol and the gender. In women, but not men, age was the variable that strongly predicted HDL and LDL cholesterol levels. Our findings provide new information for the development of better initial screening tools for HDL and LDL cholesterol.

Relevance of genetic relationship in GWAS and genomic prediction.

PubMed

Pereira, Helcio Duarte; Soriano Viana, José Marcelo; Andrade, Andréa Carla Bastos; Fonseca E Silva, Fabyano; Paes, Geísa Pinheiro

2018-02-01

The objective of this study was to analyze the relevance of relationship information on the identification of low heritability quantitative trait loci (QTLs) from a genome-wide association study (GWAS) and on the genomic prediction of complex traits in human, animal and cross-pollinating populations. The simulation-based data sets included 50 samples of 1000 individuals of seven populations derived from a common population with linkage disequilibrium. The populations had non-inbred and inbred progeny structure (50 to 200) with varying number of members (5 to 20). The individuals were genotyped for 10,000 single nucleotide polymorphisms (SNPs) and phenotyped for a quantitative trait controlled by 10 QTLs and 90 minor genes showing dominance. The SNP density was 0.1 cM and the narrow sense heritability was 25%. The QTL heritabilities ranged from 1.1 to 2.9%. We applied mixed model approaches for both GWAS and genomic prediction using pedigree-based and genomic relationship matrices. For GWAS, the observed false discovery rate was kept below the significance level of 5%, the power of detection for the low heritability QTLs ranged from 14 to 50%, and the average bias between significant SNPs and a QTL ranged from less than 0.01 to 0.23 cM. The QTL detection power was consistently higher using genomic relationship matrix. Regardless of population and training set size, genomic prediction provided higher prediction accuracy of complex trait when compared to pedigree-based prediction. The accuracy of genomic prediction when there is relatedness between individuals in the training set and the reference population is much higher than the value for unrelated individuals.

Using Conversation Topics for Predicting Therapy Outcomes in Schizophrenia

PubMed Central

Howes, Christine; Purver, Matthew; McCabe, Rose

2013-01-01

Previous research shows that aspects of doctor-patient communication in therapy can predict patient symptoms, satisfaction and future adherence to treatment (a significant problem with conditions such as schizophrenia). However, automatic prediction has so far shown success only when based on low-level lexical features, and it is unclear how well these can generalize to new data, or whether their effectiveness is due to their capturing aspects of style, structure or content. Here, we examine the use of topic as a higher-level measure of content, more likely to generalize and to have more explanatory power. Investigations show that while topics predict some important factors such as patient satisfaction and ratings of therapy quality, they lack the full predictive power of lower-level features. For some factors, unsupervised methods produce models comparable to manual annotation. PMID:23943658

The complex contribution of sociodemographics to decision-making power in gay male couples

PubMed Central

Perry, Nicholas S.; Huebner, David M.; Baucom, Brian R. W.; Hoff, Colleen C.

2016-01-01

Relationship power is an important dyadic construct in close relationships that is associated with relationship health and partner’s individual health. Understanding what predicts power in heterosexual couples has proven difficult, and even less is known about gay couples. Resource models of power posit that demographic characteristics associated with social status (e.g., age, income) confer power within the relationship, which in turn shapes relationship outcomes. We tested this model in a sample of gay male couples (N=566 couples), and extended it by examining race and HIV status. Multilevel modeling was used to test associations between demographic bases of power and decision-making power. We also examined relative associations among demographic bases and decision-making power with relationship satisfaction, given the literature on power imbalances and overall relationship functioning. Results showed that individual income was positively associated with decision-making power, as was participant’s HIV status, with HIV-positive men reporting greater power. Age differences within the relationship interacted with relationship length to predict decision-making power, but not satisfaction. HIV-concordant positive couples were less satisfied than concordant negative couples. Higher power partners were less satisfied than lower power partners. Demographic factors contributing to decision-making power among same-sex male couples appear to share some similarities with heterosexual couples (e.g., income is associated with power), as well as have unique features (e.g., HIV status influences power). However, these same demographics did not reliably predict relationship satisfaction in the manner that existing power theories suggest. Findings indicate important considerations for theories of power among same-sex male couples. PMID:27606937

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

PubMed

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

2015-01-01

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

Prestimulus EEG Power Predicts Conscious Awareness But Not Objective Visual Performance

PubMed Central

Veniero, Domenica

2017-01-01

Abstract Prestimulus oscillatory neural activity has been linked to perceptual outcomes during performance of psychophysical detection and discrimination tasks. Specifically, the power and phase of low frequency oscillations have been found to predict whether an upcoming weak visual target will be detected or not. However, the mechanisms by which baseline oscillatory activity influences perception remain unclear. Recent studies suggest that the frequently reported negative relationship between α power and stimulus detection may be explained by changes in detection criterion (i.e., increased target present responses regardless of whether the target was present/absent) driven by the state of neural excitability, rather than changes in visual sensitivity (i.e., more veridical percepts). Here, we recorded EEG while human participants performed a luminance discrimination task on perithreshold stimuli in combination with single-trial ratings of perceptual awareness. Our aim was to investigate whether the power and/or phase of prestimulus oscillatory activity predict discrimination accuracy and/or perceptual awareness on a trial-by-trial basis. Prestimulus power (3–28 Hz) was inversely related to perceptual awareness ratings (i.e., higher ratings in states of low prestimulus power/high excitability) but did not predict discrimination accuracy. In contrast, prestimulus oscillatory phase did not predict awareness ratings or accuracy in any frequency band. These results provide evidence that prestimulus α power influences the level of subjective awareness of threshold visual stimuli but does not influence visual sensitivity when a decision has to be made regarding stimulus features. Hence, we find a clear dissociation between the influence of ongoing neural activity on conscious awareness and objective performance. PMID:29255794

Relationship Power, Sexual Decision Making, and HIV Risk Among Midlife and Older Women.

PubMed

Altschuler, Joanne; Rhee, Siyon

2015-01-01

The number of midlife and older women with HIV/AIDS is high and increasing, especially among women of color. This article addresses these demographic realities by reporting on findings about self-esteem, relationship power, and HIV risk from a pilot study of midlife and older women. A purposive sample (N = 110) of ethnically, economically, and educationally diverse women 40 years and older from the Greater Los Angeles Area was surveyed to determine their levels of self-esteem, general relationship power, sexual decision-making power, safer sex behaviors, and HIV knowledge. Women with higher levels of self-esteem exercised greater power in their relationships with their partner. Women with higher levels of general relationship power and self-esteem tend to exercise greater power in sexual decision making, such as having sex and choosing sexual acts. Income and sexual decision-making power were statistically significant in predicting the use of condoms. Implications and recommendations for future HIV/AIDS research and intervention targeting midlife and older women are presented.

The Predictive Effects of Motivation toward Learning Science on TIMSS Grade 8 Students' Science Achievement: A Comparative Study between Malaysia and Singapore

ERIC Educational Resources Information Center

Lay, Yoon Fah; Chandrasegaran, A. L.

2016-01-01

TIMSS routinely presents very powerful evidence showing that students with more positive motivation toward learning science have substantially higher achievement. The results from TIMSS 2011 are consistent with previous assessments. This study explored the predictive effects of motivation toward learning science on science achievement among…

A Model-Based Approach to Predicting Graduate-Level Performance Using Indicators of Undergraduate-Level Performance

ERIC Educational Resources Information Center

Zimmermann, Judith; Brodersen, Kay H.; Heinimann, Hans R.; Buhmann, Joachim M.

2015-01-01

The graduate admissions process is crucial for controlling the quality of higher education, yet, rules-of-thumb and domain-specific experiences often dominate evidence-based approaches. The goal of the present study is to dissect the predictive power of undergraduate performance indicators and their aggregates. We analyze 81 variables in 171…

Chronic pain and praying to a higher power: useful or useless?

PubMed

Andersson, Gerhard

2008-06-01

In the present study a Swedish sample of 118 persons with chronic pain completed online tests on two occasions in association with treatment trials. A three item subscale measuring praying as a coping strategy was derived from the Coping Strategies Questionnaire (CSQ), but adapted to refer to "a higher power" instead of "God". Measures of pain and anxiety/depression were also included. Results revealed significant associations between praying and pain interference and impairment. Praying was also associated with anxiety and depression scores. Results also showed that prayer predicted depression scores at follow-up, and that follow-up prayer was predicted by pain interference at first measurement occasion. Overall, if prayer had any relation with the other variables it was in the negative direction of more distress being associated with more praying both concurrently and prospectively.

Contributions of the stochastic shape wake model to predictions of aerodynamic loads and power under single wake conditions

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

Doubrawa, P.; Barthelmie, R. J.; Wang, H.

The contribution of wake meandering and shape asymmetry to load and power estimates is quantified by comparing aeroelastic simulations initialized with different inflow conditions: an axisymmetric base wake, an unsteady stochastic shape wake, and a large-eddy simulation with rotating actuator-line turbine representation. Time series of blade-root and tower base bending moments are analyzed. We find that meandering has a large contribution to the fluctuation of the loads. Moreover, considering the wake edge intermittence via the stochastic shape model improves the simulation of load and power fluctuations and of the fatigue damage equivalent loads. Furthermore, these results indicate that the stochasticmore » shape wake simulator is a valuable addition to simplified wake models when seeking to obtain higher-fidelity computationally inexpensive predictions of loads and power.« less

Contributions of the stochastic shape wake model to predictions of aerodynamic loads and power under single wake conditions

DOE PAGES

Doubrawa, P.; Barthelmie, R. J.; Wang, H.; ...

2016-10-03

The contribution of wake meandering and shape asymmetry to load and power estimates is quantified by comparing aeroelastic simulations initialized with different inflow conditions: an axisymmetric base wake, an unsteady stochastic shape wake, and a large-eddy simulation with rotating actuator-line turbine representation. Time series of blade-root and tower base bending moments are analyzed. We find that meandering has a large contribution to the fluctuation of the loads. Moreover, considering the wake edge intermittence via the stochastic shape model improves the simulation of load and power fluctuations and of the fatigue damage equivalent loads. Furthermore, these results indicate that the stochasticmore » shape wake simulator is a valuable addition to simplified wake models when seeking to obtain higher-fidelity computationally inexpensive predictions of loads and power.« less

The complex contribution of sociodemographics to decision-making power in gay male couples.

PubMed

Perry, Nicholas S; Huebner, David M; Baucom, Brian R W; Hoff, Colleen C

2016-12-01

Relationship power is an important dyadic construct in close relationships that is associated with relationship health and partner's individual health. Understanding what predicts power in heterosexual couples has proven difficult, and even less is known about gay couples. Resource models of power posit that demographic characteristics associated with social status (e.g., age, income) confer power within the relationship, which in turn shapes relationship outcomes. We tested this model in a sample of gay male couples (N = 566 couples) and extended it by examining race and HIV status. Multilevel modeling was used to test associations between demographic bases of power and decision-making power. We also examined relative associations among demographic bases and decision-making power with relationship satisfaction given the literature on power imbalances and overall relationship functioning. Results showed that individual income was positively associated with decision-making power, as was participant's HIV status, with HIV-positive men reporting greater power. Age differences within the relationship interacted with relationship length to predict decision-making power, but not satisfaction. HIV-concordant positive couples were less satisfied than concordant negative couples. Higher power partners were less satisfied than lower power partners. Demographic factors contributing to decision-making power among same-sex male couples appear to share some similarities with heterosexual couples (e.g., income is associated with power) and have unique features (e.g., HIV status influences power). However, these same demographics did not reliably predict relationship satisfaction in the manner that existing power theories suggest. Findings indicate important considerations for theories of power among same-sex male couples. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Department of Defense Space Science and Technology Strategy 2015

DTIC Science & Technology

2015-01-01

solar cells at 34% efficiency enabling higher power spacecraft capability. These solar cells developed by the Air Force Research Laboratory (AFRL...Reduce size, weight, power , cost, and improve thermal management for SATCOM terminals  Support intelligence surveillance and reconnaissance (ISR...Improve understanding and awareness of the Earth-to-Sun environment  Improve space environment forecast capabilities and tools to predict operational

Experimental study on thrust and power of flapping-wing system based on rack-pinion mechanism.

PubMed

Nguyen, Tuan Anh; Vu Phan, Hoang; Au, Thi Kim Loan; Park, Hoon Cheol

2016-06-20

This experimental study investigates the effect of three parameters: wing aspect ratio (AR), wing offset, and flapping frequency, on thrust generation and power consumption of a flapping-wing system based on a rack-pinion mechanism. The new flapping-wing system is simple but robust, and is able to create a large flapping amplitude. The thrust measured by a load cell reveals that for a given power, the flapping-wing system using a higher wing AR produces larger thrust and higher flapping frequency at the wing offset of 0.15[Formula: see text] or 0.20[Formula: see text] ([Formula: see text] is the mean chord) than other wing offsets. Of the three parameters, the flapping frequency plays a more significant role on thrust generation than either the wing AR or the wing offset. Based on the measured thrusts, an empirical equation for thrust prediction is suggested, as a function of wing area, flapping frequency, flapping angle, and wing AR. The difference between the predicted and measured thrusts was less than 7%, which proved that the empirical equation for thrust prediction is reasonable. On average, the measured power consumption to flap the wings shows that 46.5% of the input power is spent to produce aerodynamic forces, 14.0% to overcome inertia force, 9.5% to drive the rack-pinion-based flapping mechanism, and 30.0% is wasted as the power loss of the installed motor. From the power analysis, it is found that the wing with an AR of 2.25 using a wing offset of 0.20[Formula: see text] showed the optimal power loading in the flapping-wing system. In addition, the flapping frequency of 25 Hz is recommended as the optimal frequency of the current flapping-wing system for high efficiency, which was 48.3%, using a wing with an AR of 2.25 and a wing offset of 0.20[Formula: see text] in the proposed design.

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

Endocrine and aggressive responses to competition are moderated by contest outcome, gender, individual versus team competition, and implicit motives

PubMed Central

Oxford, Jon K.; Tiedtke, Johanna M.; Ossmann, Anna; Özbe, Dominik

2017-01-01

This study examined hormonal responses to competition in relation to gender, social context, and implicit motives. Participants (N = 326) were randomly assigned to win or lose in a 10-round, virtual face-to-face competition, in same-sex individual- and team-competition contexts. Saliva samples, taken before and twice after the competition, were assayed for testosterone (T), estradiol (E), progesterone (P), and cortisol (C). Implicit needs for power (nPower) and affiliation (nAffiliation) were assessed with a picture-story exercise before the competition. Aggression was measured via the volume at which participants set noise blasts for their opponents. Men competing individually and women competing as teams showed similar T increases after winning. C was differentially associated with outcome in the team matches, with higher post-match cortisol for winning women, and an opposite effect for male teams. Analyses including implicit motives indicated that situational variables interacted with motivational needs in shaping hormonal responses to competition: in naturally cycling women, nPower predicted T increases after winning and T and E decreases after losing. In men, nPower predicted T increases after losing and decreases after winning. In male teams, nPower predicted C increases after losing, but not after winning, whereas in individual competitions, nPower was a general negative predictor of C changes in women. nAffiliation predicted P increases for women competing as teams, and P decreases for women competing individually. Aggression was higher in men, losers, and teams than in women, winners, and individuals. High aggression was associated with high baseline C in women competing individually and with low baseline C and C decreases in women competing as teams and in men generally. Our findings suggest that while situational and gender factors play a role in hormonal responses to competition, they also depend on their interplay with motivational factors. They also suggest that while aggression is strongly affected by situational factors in the context of a competition, it has no direct association with motivational and hormonal correlates of dominance (nPower, T, E) and instead is associated with (mostly) low levels of C. PMID:28750061

Local Burn-Up Effects in the NBSR Fuel Element

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

Brown N. R.; Hanson A.; Diamond, D.

2013-01-31

This study addresses the over-prediction of local power when the burn-up distribution in each half-element of the NBSR is assumed to be uniform. A single-element model was utilized to quantify the impact of axial and plate-wise burn-up on the power distribution within the NBSR fuel elements for both high-enriched uranium (HEU) and low-enriched uranium (LEU) fuel. To validate this approach, key parameters in the single-element model were compared to parameters from an equilibrium core model, including neutron energy spectrum, power distribution, and integral U-235 vector. The power distribution changes significantly when incorporating local burn-up effects and has lower power peakingmore » relative to the uniform burn-up case. In the uniform burn-up case, the axial relative power peaking is over-predicted by as much as 59% in the HEU single-element and 46% in the LEU single-element with uniform burn-up. In the uniform burn-up case, the plate-wise power peaking is over-predicted by as much as 23% in the HEU single-element and 18% in the LEU single-element. The degree of over-prediction increases as a function of burn-up cycle, with the greatest over-prediction at the end of Cycle 8. The thermal flux peak is always in the mid-plane gap; this causes the local cumulative burn-up near the mid-plane gap to be significantly higher than the fuel element average. Uniform burn-up distribution throughout a half-element also causes a bias in fuel element reactivity worth, due primarily to the neutronic importance of the fissile inventory in the mid-plane gap region.« less

Heat pipe cooling of power processing magnetics

NASA Technical Reports Server (NTRS)

Hansen, I. G.; Chester, M. S.

1979-01-01

A heat pipe cooled transformer and input filter were developed for the 2.4 kW beam supply of a 30 cm ion thruster system. This development yielded a mass reduction of 40% (1.76 kg) and lower mean winding temperature (20 C lower). While these improvements are significant, preliminary designs predict even greater benefits to be realized at higher power. The design details are presented along with the results of thermal vacuum operation and the component performance in a 3 kW breadboard power processor.

Evaluation of WRF-Predicted Near-Hub-Height Winds and Ramp Events over a Pacific Northwest Site with Complex Terrain

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

Yang, Qing; Berg, Larry K.; Pekour, Mikhail

The WRF model version 3.3 is used to simulate near hub-height winds and power ramps utilizing three commonly used planetary boundary-layer (PBL) schemes: Mellor-Yamada-Janjic (MYJ), University of Washington (UW), and Yonsei University (YSU). The predicted winds have small mean biases compared with observations. Power ramps and step changes (changes within an hour) consistently show that the UW scheme performed better in predicting up ramps under stable conditions with higher prediction accuracy and capture rates. Both YSU and UW scheme show good performance predicting up- and down- ramps under unstable conditions with YSU being slightly better for ramp durations longer thanmore » an hour. MYJ is the most successful simulating down-ramps under stable conditions. The high wind speed and large shear associated with low-level jets are frequently associated with power ramps, and the biases in predicted low-level jet explain some of the shown differences in ramp predictions among different PBL schemes. Low-level jets were observed as low as ~200 m in altitude over the Columbia Basin Wind Energy Study (CBWES) site, located in an area of complex terrain. The shear, low-level peak wind speeds, as well as the height of maximum wind speed are not well predicted. Model simulations with 3 PBL schemes show the largest variability among them under stable conditions.« less

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

PubMed

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

2018-01-01

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

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

PubMed Central

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

2018-01-01

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

The cross-cultural generalizability of Axis-II constructs: an evaluation of two personality disorder assessment instruments in the People's Republic of China.

PubMed

Yang, J; McCrae, R R; Costa, P T; Yao, S; Dai, X; Cai, T; Gao, B

2000-01-01

We examined the reliability, cross-instrument validity, and factor structure of Chinese adaptations of the Personality Diagnostic Questionnaire (PDQ-4+; N = 1,926) and Personality Disorders Interview (PDI-IV; N = 525) in psychiatric patients. Comparisons with data from Western countries suggest that the psychometric properties of these two instruments are comparable across cultures. Low to modest agreement between the PDQ-4+ and PDI-IV was observed for both dimensional and categorical personality disorder evaluations. When the PDI-IV was used as the diagnostic standard, the PDQ-4+ showed higher sensitivity than specificity, and higher negative predictive power than positive predictive power. Factor analyses of both instruments replicated the four-factor structure O'Connor and Dyce (1998) found in Western samples. Results suggested that conceptions and measures of DSM-IV personality disorders are cross-culturally generalizable to Chinese psychiatric populations.

Research on power source structure optimization for East China Power Grid

NASA Astrophysics Data System (ADS)

Xu, Lingjun; Sang, Da; Zhang, Jianping; Tang, Chunyi; Xu, Da

2017-05-01

The structure of east china power grid is not reasonable for the coal power takes a much higher proportion than hydropower, at present the coal power takes charge of most peak load regulation, and the pressure of peak load regulation cannot be ignored. The nuclear power, wind power, photovoltaic, other clean energy and hydropower, coal power and wind power from outside will be actively developed in future, which increases the pressure of peak load regulation. According to development of economic and social, Load status and load prediction, status quo and planning of power source and the characteristics of power source, the peak load regulation balance is carried out and put forward a reasonable plan of power source allocation. The ultimate aim is to optimize the power source structure and to provide reference for power source allocation in east china.

Sexual relationship power and depression among HIV-infected women in Rural Uganda.

PubMed

Hatcher, Abigail M; Tsai, Alexander C; Kumbakumba, Elias; Dworkin, Shari L; Hunt, Peter W; Martin, Jeffrey N; Clark, Gina; Bangsberg, David R; Weiser, Sheri D

2012-01-01

Depression is associated with increased HIV transmission risk, increased morbidity, and higher risk of HIV-related death among HIV-infected women. Low sexual relationship power also contributes to HIV risk, but there is limited understanding of how it relates to mental health among HIV-infected women. Participants were 270 HIV-infected women from the Uganda AIDS Rural Treatment Outcomes study, a prospective cohort of individuals initiating antiretroviral therapy (ART) in Mbarara, Uganda. Our primary predictor was baseline sexual relationship power as measured by the Sexual Relationship Power Scale (SRPS). The primary outcome was depression severity, measured with the Hopkins Symptom Checklist (HSCL), and a secondary outcome was a functional scale for mental health status (MHS). Adjusted models controlled for socio-demographic factors, CD4 count, alcohol and tobacco use, baseline WHO stage 4 disease, social support, and duration of ART. The mean HSCL score was 1.34 and 23.7% of participants had HSCL scores consistent with probable depression (HSCL>1.75). Compared to participants with low SRPS scores, individuals with both moderate (coefficient b = -0.21; 95%CI, -0.36 to -0.07) and high power (b = -0.21; 95%CI, -0.36 to -0.06) reported decreased depressive symptomology. High SRPS scores halved the likelihood of women meeting criteria for probable depression (adjusted odds ratio = 0.44; 95%CI, 0.20 to 0.93). In lagged models, low SRPS predicted subsequent depression severity, but depression did not predict subsequent changes in SPRS. Results were similar for MHS, with lagged models showing SRPS predicts subsequent mental health, but not visa versa. Both Decision-Making Dominance and Relationship Control subscales of SRPS were associated with depression symptom severity. HIV-infected women with high sexual relationship power had lower depression and higher mental health status than women with low power. Interventions to improve equity in decision-making and control within dyadic partnerships are critical to prevent HIV transmission and to optimize mental health of HIV-infected women.

Engagement vs Performance: Using Electronic Portfolios to Predict First Semester Engineering Student Persistence

ERIC Educational Resources Information Center

Aguiar, Everaldo; Ambrose, G. Alex; Chawla, Nitesh V.; Goodrich, Victoria; Brockman, Jay

2014-01-01

As providers of higher education begin to harness the power of big data analytics, one very fitting application for these new techniques is that of predicting student attrition. The ability to pinpoint students who might soon decide to drop out, or who may be following a suboptimal path to success, allows those in charge not only to understand the…

Detecting determinism with improved sensitivity in time series: rank-based nonlinear predictability score.

PubMed

Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G

2014-09-01

The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

Detecting determinism with improved sensitivity in time series: Rank-based nonlinear predictability score

NASA Astrophysics Data System (ADS)

Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G.

2014-09-01

The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

A First Look at Electric Motor Noise For Future Propulsion Systems

NASA Technical Reports Server (NTRS)

Huff, Dennis L.; Henderson, Brenda S.; Envia, Edmane

2016-01-01

Motor tone predictions using a vibration analysis and input from design parameters for high power density motors show that the noise can be significantly higher or lower than the empirical correlations and exceeds the stated uncertainty.

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.

Low Power Operation of Temperature-Modulated Metal Oxide Semiconductor Gas Sensors.

PubMed

Burgués, Javier; Marco, Santiago

2018-01-25

Mobile applications based on gas sensing present new opportunities for low-cost air quality monitoring, safety, and healthcare. Metal oxide semiconductor (MOX) gas sensors represent the most prominent technology for integration into portable devices, such as smartphones and wearables. Traditionally, MOX sensors have been continuously powered to increase the stability of the sensing layer. However, continuous power is not feasible in many battery-operated applications due to power consumption limitations or the intended intermittent device operation. This work benchmarks two low-power, duty-cycling, and on-demand modes against the continuous power one. The duty-cycling mode periodically turns the sensors on and off and represents a trade-off between power consumption and stability. On-demand operation achieves the lowest power consumption by powering the sensors only while taking a measurement. Twelve thermally modulated SB-500-12 (FIS Inc. Jacksonville, FL, USA) sensors were exposed to low concentrations of carbon monoxide (0-9 ppm) with environmental conditions, such as ambient humidity (15-75% relative humidity) and temperature (21-27 °C), varying within the indicated ranges. Partial Least Squares (PLS) models were built using calibration data, and the prediction error in external validation samples was evaluated during the two weeks following calibration. We found that on-demand operation produced a deformation of the sensor conductance patterns, which led to an increase in the prediction error by almost a factor of 5 as compared to continuous operation (2.2 versus 0.45 ppm). Applying a 10% duty-cycling operation of 10-min periods reduced this prediction error to a factor of 2 (0.9 versus 0.45 ppm). The proposed duty-cycling powering scheme saved up to 90% energy as compared to the continuous operating mode. This low-power mode may be advantageous for applications that do not require continuous and periodic measurements, and which can tolerate slightly higher prediction errors.

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

PubMed

Kasof, Joseph

2009-05-01

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

Trait psychopathy, emotional intelligence, and criminal thinking: Predicting illegal behavior among college students.

PubMed

Fix, Rebecca L; Fix, Spencer T

2015-01-01

Research focusing on individuals high on trait psychopathy remains limited. Higher trait psychopathy is associated with lower levels of emotional intelligence and increased participation in illegal behavior. Additionally, research has confirmed significantly higher levels of criminal thinking and lower levels of empathy in the incarcerated psychopathic population. However, the relationships between trait psychopathy and criminal thinking have not been researched in the community or college population. To test for such differences, questionnaires containing relevant measures were administered to 111 college students. Results indicated that higher levels of trait psychopathy were significantly related to less caring for others, intrapersonal understanding, and general mood, and greater interpersonal functioning and stress management. Furthermore, trait psychopathy was a strong predictor of violent, property, drug, and status offenses. Power-oriented criminal thinking was also predictive of violent behaviors, and entitlement predicted property offending. Results suggest emotional intelligence is important for predicting psychopathy, and trait psychopathy is a strong predictor of all types of illegal behaviors among the non-incarcerated population. Published by Elsevier Ltd.

Development of Integrated Assessment System for Underground Power Cable Performance: A Case Study

NASA Astrophysics Data System (ADS)

Turan, Faiz Mohd; Johan, Kartina; Soliha Sahimi, Nur; Nor, Nik Hisyamudin Muhd

2017-08-01

The basic operation of any electrical machines that is catered to serve needs of civilization involves electrical power which is the main source to trigger the internal mechanism in the machines then transfer the power to other form of energy such as mechanical, light, sound and etc. The supplies of electrical does not happen just by providing the source itself, it has load carrying agent which in many cases, user would refer to it as cable. Specifically, it is the power cable which its ampacity depends significantly on the operation temperature and load stress on it. Apart from having to focus on providing improvement on improving efficiency on the source itself, power cable plays and important role because without it, current ranging from low to high could not be transmitted and hence a failure of the power system generally. Studies have conducted to discuss whether which factor contributes relatively more to the causes of power cable failure or breakdown. Such factors can be narrowed down to the three major causes which are over temperature, over voltage and stress caused by over current. Over current is one of the factor which is depends on the usage of the power system itself. The higher the usage of the power system, higher the chances of over current to take place. This will then produce load stress on the cable which eventually destroy the insulator of the cable and slowly reach the core of the cable. It is believed that an assessment method should be implemented in order to predict the performance and failure rate of the power cable and use this prediction as reference rather than just letting power failure to happen anytime unpredictable which cause huge inconvenience to users and industries. Not only do a method should be implemented, it should be as easy to be used and understood by large range of users and integrated by a graphical user interface to be used. Therefore, this research will further narrow down on the approaches to do so and the location of studies involve Company M which is an agriculture industries which has higher usage on their own underground power cable. Moreover, in the past history the company experienced electrical power failure and this studies and findings will definitely come in hand to provide them necessary help and benefits.

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.

Thunderstorms and ground-based radio noise as observed by radio astronomy Explorer 1

NASA Technical Reports Server (NTRS)

Caruso, J. A.; Herman, J. R.

1973-01-01

Radio Astronomy Explorer (RAE) data were analyzed to determine the frequency dependence of HF terrestrial radio noise power. RAE observations of individual thunderstorms, mid-ocean areas, and specific geographic regions for which concommitant ground based measurements are available indicate that noise power is a monotonically decreasing function of frequency which conforms to expectations over the geographic locations and time periods investigated. In all cases investigated, active thunderstorm regions emit slightly higher power as contrasted to RAE observations of the region during meteorologically quiet periods. Noise levels are some 15 db higher than predicted values over mid-ocean, while in locations where ground based measurements are available a maximum deviation of 5 db occurs. Worldwide contour mapping of the noise power at 6000 km for five individual months and four observing frequencies, examples of which are given, indicate high noise levels over continental land masses with corresponding lower levels over ocean regions.

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

NASA Glenn Research Center Program in High Power Density Motors for Aeropropulsion

NASA Technical Reports Server (NTRS)

Brown, Gerald V.; Kascak, Albert F.; Ebihara, Ben; Johnson, Dexter; Choi, Benjamin; Siebert, Mark; Buccieri, Carl

2005-01-01

Electric drive of transport-sized aircraft propulsors, with electric power generated by fuel cells or turbo-generators, will require electric motors with much higher power density than conventional room-temperature machines. Cryogenic cooling of the motor windings by the liquid hydrogen fuel offers a possible solution, enabling motors with higher power density than turbine engines. Some context on weights of various systems, which is required to assess the problem, is presented. This context includes a survey of turbine engine weights over a considerable size range, a correlation of gear box weights and some examples of conventional and advanced electric motor weights. The NASA Glenn Research Center program for high power density motors is outlined and some technical results to date are presented. These results include current densities of 5,000 A per square centimeter current density achieved in cryogenic coils, finite element predictions compared to measurements of torque production in a switched reluctance motor, and initial tests of a cryogenic switched reluctance motor.

Accurate Estimate of Some Propagation Characteristics for the First Higher Order Mode in Graded Index Fiber with Simple Analytic Chebyshev Method

NASA Astrophysics Data System (ADS)

Dutta, Ivy; Chowdhury, Anirban Roy; Kumbhakar, Dharmadas

2013-03-01

Using Chebyshev power series approach, accurate description for the first higher order (LP11) mode of graded index fibers having three different profile shape functions are presented in this paper and applied to predict their propagation characteristics. These characteristics include fractional power guided through the core, excitation efficiency and Petermann I and II spot sizes with their approximate analytic formulations. We have shown that where two and three Chebyshev points in LP11 mode approximation present fairly accurate results, the values based on our calculations involving four Chebyshev points match excellently with available exact numerical results.

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.

The stopping power and energy straggling of light ions in graphene oxide foils

NASA Astrophysics Data System (ADS)

Mikšová, R.; Macková, A.; Malinský, P.; Sofer, Z.

2017-09-01

Energy-loss and straggling experiments were performed using 2-4 MeV 1H+ and 7.4-9.0 MeV 4He2+ ions in graphene oxide foils by the transmission technique. The thickness of the graphene oxide foils was determined using a detailed image analysis of a graphene oxide cut, which was used to refine the graphene oxide density. The density was determined by the standard technique of micro-balance weighing. The stoichiometry of the graphene oxide foils before the irradiation was determined by Rutherford backscattering spectrometry (RBS) and elastic recoil detection analysis (ERDA) using 2 and 2.5 MeV 4He+. The measured energy stopping powers for hydrogen and helium ions in graphene oxide were compared with the predictions obtained from the SRIM-2013 code. The energy straggling was compared with that calculated using Bohr's, Bethe-Livingston and Yang predictions. The results show that the stopping power of graphene oxide foils irradiated by both ion species decreases with increasing energies, the differences between the measured and predicted values being below 3.8%. The energy straggling determined in our experiment is higher than Bohr's and Bethe-Livingston predicted values; the predictions by Yang are in better agreement with our experiment.

Idiopathic normal pressure hydrocephalus, quantitative EEG findings, and the cerebrospinal fluid tap test: a pilot study.

PubMed

Seo, Jong-Geun; Kang, Kyunghun; Jung, Ji-Young; Park, Sung-Pa; Lee, Maan-Gee; Lee, Ho-Won

2014-12-01

In this pilot study, we analyzed relationships between quantitative EEG measurements and clinical parameters in idiopathic normal pressure hydrocephalus patients, along with differences in these quantitative EEG markers between cerebrospinal fluid tap test responders and nonresponders. Twenty-six idiopathic normal pressure hydrocephalus patients (9 cerebrospinal fluid tap test responders and 17 cerebrospinal fluid tap test nonresponders) constituted the final group for analysis. The resting EEG was recorded and relative powers were computed for seven frequency bands. Cerebrospinal fluid tap test nonresponders, when compared with responders, showed a statistically significant increase in alpha2 band power at the right frontal and centrotemporal regions. Higher delta2 band powers in the frontal, central, parietal, and occipital regions and lower alpha1 band powers in the right temporal region significantly correlated with poorer cognitive performance. Higher theta1 band powers in the left parietal and occipital regions significantly correlated with gait dysfunction. And higher delta1 band powers in the right frontal regions significantly correlated with urinary disturbance. Our findings may encourage further research using quantitative EEG in patients with ventriculomegaly as a potential electrophysiological marker for predicting cerebrospinal fluid tap test responders. This study additionally suggests that the delta, theta, and alpha bands are statistically correlated with the severity of symptoms in idiopathic normal pressure hydrocephalus patients.

Predicting Firm Success From the Facial Appearance of Chief Executive Officers of Non-Profit Organizations.

PubMed

Re, Daniel E; Rule, Nicholas O

2016-10-01

Recent research has demonstrated that judgments of Chief Executive Officers' (CEOs') faces predict their firms' financial performance, finding that characteristics associated with higher power (e.g., dominance) predict greater profits. Most of these studies have focused on CEOs of profit-based businesses, where the main criterion for success is financial gain. Here, we examined whether facial appearance might predict measures of success in a sample of CEOs of non-profit organizations (NPOs). Indeed, contrary to findings for the CEOs of profit-based businesses, judgments of leadership and power from the faces of CEOs of NPOs negatively correlated with multiple measures of charitable success (Study 1). Moreover, CEOs of NPOs looked less powerful than the CEOs of profit-based businesses (Study 2) and leadership ratings positively associated with warmth-based traits and NPO success when participants knew the faces belonged to CEOs of NPOs (Study 3). CEOs who look less dominant may therefore achieve greater success in leading NPOs, opposite the relationship found for the CEOs of profit-based companies. Thus, the relationship between facial appearance and leadership success varies by organizational context. © The Author(s) 2016.

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

PubMed

Mirzaei, Masoud; Khajeh, Mohammad

2018-04-13

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

[Implementation results of emission standards of air pollutants for thermal power plants: a numerical simulation].

PubMed

Wang, Zhan-Shan; Pan, Li-Bo

2014-03-01

The emission inventory of air pollutants from the thermal power plants in the year of 2010 was set up. Based on the inventory, the air quality of the prediction scenarios by implementation of both 2003-version emission standard and the new emission standard were simulated using Models-3/CMAQ. The concentrations of NO2, SO2, and PM2.5, and the deposition of nitrogen and sulfur in the year of 2015 and 2020 were predicted to investigate the regional air quality improvement by the new emission standard. The results showed that the new emission standard could effectively improve the air quality in China. Compared with the implementation results of the 2003-version emission standard, by 2015 and 2020, the area with NO2 concentration higher than the emission standard would be reduced by 53.9% and 55.2%, the area with SO2 concentration higher than the emission standard would be reduced by 40.0%, the area with nitrogen deposition higher than 1.0 t x km(-2) would be reduced by 75.4% and 77.9%, and the area with sulfur deposition higher than 1.6 t x km(-2) would be reduced by 37.1% and 34.3%, respectively.

The impact of frequency on the performance of microwave ablation.

PubMed

Sawicki, James F; Shea, Jacob D; Behdad, Nader; Hagness, Susan C

2017-02-01

The use of higher frequencies in percutaneous microwave ablation (MWA) may offer compelling interstitial antenna design advantages over the 915 MHz and 2.45 GHz frequencies typically employed in current systems. To evaluate the impact of higher frequencies on ablation performance, we conducted a comprehensive computational and experimental study of microwave absorption and tissue heating as a function of frequency. We performed electromagnetic and thermal simulations of MWA in ex vivo and in vivo porcine muscle at discrete frequencies in the 1.9-26 GHz range. Ex vivo ablation experiments were performed in the 1.9-18 GHz range. We tracked the size of the ablation zone across frequency for constant input power and ablation duration. Further, we conducted simulations to investigate antenna feed line heating as a function of frequency, input power, and cable diameter. As the frequency was increased from 1.9 to 26 GHz the resulting ablation zone dimensions decreased in the longitudinal direction while remaining relatively constant in the radial direction; thus at higher frequencies the overall ablation zone was more spherical. However, cable heating at higher frequencies became more problematic for smaller diameter cables at constant input power. Comparably sized ablation zones are achievable well above 1.9 GHz, despite increasingly localised power absorption. Specific absorption rate alone does not accurately predict ablation performance, particularly at higher frequencies where thermal diffusion plays an important role. Cable heating due to ohmic losses at higher frequencies may be controlled through judicious choices of input power and cable diameter.

Advanced space power PEM fuel cell systems

NASA Technical Reports Server (NTRS)

Vanderborgh, N. E.; Hedstrom, J.; Huff, J. R.

1989-01-01

A model showing mass and heat transfer in proton exchange membrane (PEM) single cells is presented. For space applications, stack operation requiring combined water and thermal management is needed. Advanced hardware designs able to combine these two techniques are available. Test results are shown for membrane materials which can operate with sufficiently fast diffusive water transport to sustain current densities of 300 ma per square centimeter. Higher power density levels are predicted to require active water removal.

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

PubMed

So, Hon-Cheong; Sham, Pak C

2017-03-15

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

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

NASA Technical Reports Server (NTRS)

Ash, A. G.

1985-01-01

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

Sexual Relationship Power and Depression among HIV-Infected Women in Rural Uganda

PubMed Central

Hatcher, Abigail M.; Tsai, Alexander C.; Kumbakumba, Elias; Dworkin, Shari L.; Hunt, Peter W.; Martin, Jeffrey N.; Clark, Gina; Bangsberg, David R.; Weiser, Sheri D.

2012-01-01

Background Depression is associated with increased HIV transmission risk, increased morbidity, and higher risk of HIV-related death among HIV-infected women. Low sexual relationship power also contributes to HIV risk, but there is limited understanding of how it relates to mental health among HIV-infected women. Methods Participants were 270 HIV-infected women from the Uganda AIDS Rural Treatment Outcomes study, a prospective cohort of individuals initiating antiretroviral therapy (ART) in Mbarara, Uganda. Our primary predictor was baseline sexual relationship power as measured by the Sexual Relationship Power Scale (SRPS). The primary outcome was depression severity, measured with the Hopkins Symptom Checklist (HSCL), and a secondary outcome was a functional scale for mental health status (MHS). Adjusted models controlled for socio-demographic factors, CD4 count, alcohol and tobacco use, baseline WHO stage 4 disease, social support, and duration of ART. Results The mean HSCL score was 1.34 and 23.7% of participants had HSCL scores consistent with probable depression (HSCL>1.75). Compared to participants with low SRPS scores, individuals with both moderate (coefficient b = −0.21; 95%CI, −0.36 to −0.07) and high power (b = −0.21; 95%CI, −0.36 to −0.06) reported decreased depressive symptomology. High SRPS scores halved the likelihood of women meeting criteria for probable depression (adjusted odds ratio = 0.44; 95%CI, 0.20 to 0.93). In lagged models, low SRPS predicted subsequent depression severity, but depression did not predict subsequent changes in SPRS. Results were similar for MHS, with lagged models showing SRPS predicts subsequent mental health, but not visa versa. Both Decision-Making Dominance and Relationship Control subscales of SRPS were associated with depression symptom severity. Conclusions HIV-infected women with high sexual relationship power had lower depression and higher mental health status than women with low power. Interventions to improve equity in decision-making and control within dyadic partnerships are critical to prevent HIV transmission and to optimize mental health of HIV-infected women. PMID:23300519

Predictors of cultural capital on science academic achievement at the 8th grade level

NASA Astrophysics Data System (ADS)

Misner, Johnathan Scott

The purpose of the study was to determine if students' cultural capital is a significant predictor of 8th grade science achievement test scores in urban locales. Cultural capital refers to the knowledge used and gained by the dominant class, which allows social and economic mobility. Cultural capital variables include magazines at home and parental education level. Other variables analyzed include socioeconomic status (SES), gender, and English language learners (ELL). This non-experimental study analyzed the results of the 2011 Eighth Grade Science National Assessment of Educational Progress (NAEP). The researcher analyzed the data using a multivariate stepwise regression analysis. The researcher concluded that the addition of cultural capital factors significantly increased the predictive power of the model where magazines in home, gender, student classified as ELL, parental education level, and SES were the independent variables and science achievement was the dependent variable. For alpha=0.05, the overall test for the model produced a R2 value of 0.232; therefore the model predicted 23.2% of variance in science achievement results. Other major findings include: higher measures of home resources predicted higher 2011 NAEP eighth grade science achievement; males were predicted to have higher 2011 NAEP 8 th grade science achievement; classified ELL students were predicted to score lower on the NAEP eight grade science achievement; higher parent education predicted higher NAEP eighth grade science achievement; lower measures of SES predicted lower 2011 NAEP eighth grade science achievement. This study contributed to the research in this field by identifying cultural capital factors that have been found to have statistical significance on predicting eighth grade science achievement results, which can lead to strategies to help improve science academic achievement among underserved populations.

Design and aero-acoustic analysis of a counter-rotating wind turbine

NASA Astrophysics Data System (ADS)

Agrawal, Vineesh V.

Wind turbines have become an integral part of the energy business because they are one of the most economical and reliable sources of renewable energy. Conventional wind turbines are capable of capturing less than half of the energy present in the wind. Hence, to make the wind turbines more efficient, it is important to increase their performance. A horizontal axis wind turbine with multiple rotors is one concept that can achieve a higher power conversion rate. Also, a concern for wind energy is the noise generated by wind turbines. Hence, an investigation into the acoustic behavior of a multi-rotor horizontal axis wind turbine is required. In response to the need of a wind turbine design with higher power coefficient, a unique design of a counter-rotating horizontal axis wind turbine (CR-HAWT) is proposed. The Blade Element Momentum (BEM) theory is used to aerodynamically design the blades of the two rotors. Modifications are made to the BEM theory to accommodate the interaction of the two rotors. The tower effect on the noise generation of the downwind rotor is investigated. Predictions are made for the total noise generated by the wind turbine at its design operating conditions. A total power coefficient of 65.2% is predicted for the proposed CR-HAWT design. A low tip speed ratio is chosen to minimize the noise generation. The aeroacoustic analysis of the CR-HAWT shows that the noise generated at its design operating conditions is within an acceptable range. Thus, the CR-HAWT is predicted to be a quiet wind turbine with a high power coefficient, making it highly desirable for small wind turbine applications.

Frequency weighting derived from power absorption of fingers-hand-arm system under z(h)-axis vibration.

PubMed

Dong, Ren G; Welcome, Daniel E; McDowell, Thomas W; Wu, John Z; Schopper, Aaron W

2006-01-01

The objectives of this study are to derive the frequency weighting from three vibration power absorption (VPA) methods (finger VPA, palm VPA, and total or hand VPA), and to explore whether these energy methods are better than the currently accepted acceleration method. To calculate the VPA weightings, the mechanical impedance of eight subjects exposed to a broadband random vibration spectrum in the z(h)-axis using 18 combinations of hand couplings and applied forces was measured. The VPA weightings were compared with the frequency weighting specified in ISO 5349-1 [2001. Mechanical Vibration--Measurement and Evaluation of Human Exposure to Hand--Transmitted Vibration--Part 1: General Requirements. International Organization for Standardization, Geneva, Switzerland]. This study found that the hand and palm VPA weightings are very similar to the ISO weighting but the finger VPA weighting for the combined grip and push action is much higher than the ISO weighting at frequencies higher than 25 Hz. Therefore, this study predicted that the total power absorption of the entire hand-arm system is likely to be correlated with psychophysical response or subjective sensation. However, if the ISO weighting method cannot yield good predictions of the vibration-induced disorders in the fingers and hand, the hand and palm energy methods are unlikely to yield significantly better predictions. The finger VPA is a vibration measure between unweighted and ISO weighted accelerations. The palm VPA method may have some value for studying the disorders in the wrist-arm system.

Real Time Monitoring and Prediction of the Monsoon Intraseasonal Oscillations: An index based on Nonlinear Laplacian Spectral Analysis Technique

NASA Astrophysics Data System (ADS)

Cherumadanakadan Thelliyil, S.; Ravindran, A. M.; Giannakis, D.; Majda, A.

2016-12-01

An improved index for real time monitoring and forecast verification of monsoon intraseasonal oscillations (MISO) is introduced using the recently developed Nonlinear Laplacian Spectral Analysis (NLSA) algorithm. Previous studies has demonstrated the proficiency of NLSA in capturing low frequency variability and intermittency of a time series. Using NLSA a hierarchy of Laplace-Beltrami (LB) eigen functions are extracted from the unfiltered daily GPCP rainfall data over the south Asian monsoon region. Two modes representing the full life cycle of complex northeastward propagating boreal summer MISO are identified from the hierarchy of Laplace-Beltrami eigen functions. These two MISO modes have a number of advantages over the conventionally used Extended Empirical Orthogonal Function (EEOF) MISO modes including higher memory and better predictability, higher fractional variance over the western Pacific, Western Ghats and adjoining Arabian Sea regions and more realistic representation of regional heat sources associated with the MISO. The skill of NLSA based MISO indices in real time prediction of MISO is demonstrated using hindcasts of CFSv2 extended range prediction runs. It is shown that these indices yield a higher prediction skill than the other conventional indices supporting the use of NLSA in real time prediction of MISO. Real time monitoring and prediction of MISO finds its application in agriculture, construction and hydro-electric power sectors and hence an important component of monsoon prediction.

A digital prediction algorithm for a single-phase boost PFC

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Organisational Commitments and Teaching Styles among Academics in Mainland China

ERIC Educational Resources Information Center

Zhang, Li-Fang; Jing, Li-Zhen

2016-01-01

This research pioneered the investigation of the predictive power of organisational commitments for academics' teaching styles. Participants were 370 faculty members from 15 higher educational institutions in Beijing, the People's Republic of China. Results showed that academics' organisational commitments as measured by the Organisational…

Design of online monitoring and forecasting system for electrical equipment temperature of prefabricated substation based on WSN

NASA Astrophysics Data System (ADS)

Qi, Weiran; Miao, Hongxia; Miao, Xuejiao; Xiao, Xuanxuan; Yan, Kuo

2016-10-01

In order to ensure the safe and stable operation of the prefabricated substations, temperature sensing subsystem, temperature remote monitoring and management subsystem, forecast subsystem are designed in the paper. Wireless temperature sensing subsystem which consists of temperature sensor and MCU sends the electrical equipment temperature to the remote monitoring center by wireless sensor network. Remote monitoring center can realize the remote monitoring and prediction by monitoring and management subsystem and forecast subsystem. Real-time monitoring of power equipment temperature, history inquiry database, user management, password settings, etc., were achieved by monitoring and management subsystem. In temperature forecast subsystem, firstly, the chaos of the temperature data was verified and phase space is reconstructed. Then Support Vector Machine - Particle Swarm Optimization (SVM-PSO) was used to predict the temperature of the power equipment in prefabricated substations. The simulation results found that compared with the traditional methods SVM-PSO has higher prediction accuracy.

Anxious gambling: Anxiety is associated with higher frontal midline theta predicting less risky decisions.

PubMed

Schmidt, Barbara; Kanis, Hannah; Holroyd, Clay B; Miltner, Wolfgang H R; Hewig, Johannes

2018-06-20

In this study, we address the effect of anxiety measured with the State-Trait Anxiety Inventory (STAI) on EEG and risk decisions. We selected 20 high and 20 low anxious participants based on their STAI trait scores in the upper or lower quartile of the norm distribution and implemented a risk game developed in our laboratory. We investigate if high anxious individuals exert more cognitive control, reflected in higher frontal midline theta (FMT) power when they make a risky decision, and if they act less risky compared to low anxious individuals. Participants played a risk game while we recorded their brain responses via EEG. High anxious participants played less risky compared to low anxious participants. Further, high anxious participants showed higher FMT power immediately before they chose one of two risk options, suggesting higher cognitive control during the decision time compared to low anxious participants. Via a mediation analysis, we show that the effect of anxiety on risk behavior is fully mediated by FMT power. Further, questionnaire responses revealed that high anxious participants rated risk situations as riskier compared to low anxious participants. We conclude that anxious individuals perceive risky situations as riskier and thus exert more cognitive control during their risk choices, reflected in higher FMT power, which leads to less risky decisions. © 2018 Society for Psychophysiological Research.

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.

Applying multibeam sonar and mathematical modeling for mapping seabed substrate and biota of offshore shallows

NASA Astrophysics Data System (ADS)

Herkül, Kristjan; Peterson, Anneliis; Paekivi, Sander

2017-06-01

Both basic science and marine spatial planning are in a need of high resolution spatially continuous data on seabed habitats and biota. As conventional point-wise sampling is unable to cover large spatial extents in high detail, it must be supplemented with remote sensing and modeling in order to fulfill the scientific and management needs. The combined use of in situ sampling, sonar scanning, and mathematical modeling is becoming the main method for mapping both abiotic and biotic seabed features. Further development and testing of the methods in varying locations and environmental settings is essential for moving towards unified and generally accepted methodology. To fill the relevant research gap in the Baltic Sea, we used multibeam sonar and mathematical modeling methods - generalized additive models (GAM) and random forest (RF) - together with underwater video to map seabed substrate and epibenthos of offshore shallows. In addition to testing the general applicability of the proposed complex of techniques, the predictive power of different sonar-based variables and modeling algorithms were tested. Mean depth, followed by mean backscatter, were the most influential variables in most of the models. Generally, mean values of sonar-based variables had higher predictive power than their standard deviations. The predictive accuracy of RF was higher than that of GAM. To conclude, we found the method to be feasible and with predictive accuracy similar to previous studies of sonar-based mapping.

Optimal Battery Utilization Over Lifetime for Parallel Hybrid Electric Vehicle to Maximize Fuel Economy

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

Patil, Chinmaya; Naghshtabrizi, Payam; Verma, Rajeev

This paper presents a control strategy to maximize fuel economy of a parallel hybrid electric vehicle over a target life of the battery. Many approaches to maximizing fuel economy of parallel hybrid electric vehicle do not consider the effect of control strategy on the life of the battery. This leads to an oversized and underutilized battery. There is a trade-off between how aggressively to use and 'consume' the battery versus to use the engine and consume fuel. The proposed approach addresses this trade-off by exploiting the differences in the fast dynamics of vehicle power management and slow dynamics of batterymore » aging. The control strategy is separated into two parts, (1) Predictive Battery Management (PBM), and (2) Predictive Power Management (PPM). PBM is the higher level control with slow update rate, e.g. once per month, responsible for generating optimal set points for PPM. The considered set points in this paper are the battery power limits and State Of Charge (SOC). The problem of finding the optimal set points over the target battery life that minimize engine fuel consumption is solved using dynamic programming. PPM is the lower level control with high update rate, e.g. a second, responsible for generating the optimal HEV energy management controls and is implemented using model predictive control approach. The PPM objective is to find the engine and battery power commands to achieve the best fuel economy given the battery power and SOC constraints imposed by PBM. Simulation results with a medium duty commercial hybrid electric vehicle and the proposed two-level hierarchical control strategy show that the HEV fuel economy is maximized while meeting a specified target battery life. On the other hand, the optimal unconstrained control strategy achieves marginally higher fuel economy, but fails to meet the target battery life.« less

Short-term load and wind power forecasting using neural network-based prediction intervals.

PubMed

Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

2014-02-01

Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.

Novel high-frequency, high-power, pulsed oscillator based on a transmission line transformer.

PubMed

Burdt, R; Curry, R D

2007-07-01

Recent analysis and experiments have demonstrated the potential for transmission line transformers to be employed as compact, high-frequency, high-power, pulsed oscillators with variable rise time, high output impedance, and high operating efficiency. A prototype system was fabricated and tested that generates a damped sinusoidal wave form at a center frequency of 4 MHz into a 200 Omega load, with operating efficiency above 90% and peak power on the order of 10 MW. The initial rise time of the pulse is variable and two experiments were conducted to demonstrate initial rise times of 12 and 3 ns, corresponding to a spectral content from 4-30 and from 4-100 MHz, respectively. A SPICE model has been developed to accurately predict the circuit behavior and scaling laws have been identified to allow for circuit design at higher frequencies and higher peak power. The applications, circuit analysis, test stand, experimental results, circuit modeling, and design of future systems are all discussed.

The Increasing Effects of Computers on Education.

ERIC Educational Resources Information Center

Gannon, John F.

Predicting that the teaching-learning process in American higher education is about to change drastically because of continuing innovations in computer-assisted technology, this paper argues that this change will be driven by inexpensive but powerful computer technology, and that it will manifest itself by reducing the traditional timing of…

A simulation model for predicting the temperature during the application of MR-guided focused ultrasound for stroke treatment using pulsed ultrasound

NASA Astrophysics Data System (ADS)

Hadjisavvas, V.; Damianou, C.

2011-09-01

In this paper a simulation model for predicting the temperature during the application of MR-guided focused ultrasound for stroke treatment using pulsed ultrasound is presented. A single element spherically focused transducer of 5 cm diameter, focusing at 10 cm and operating at either 0.5 MHz or 1 MHz was considered. The power field was estimated using the KZK model. The temperature was estimated using the bioheat equation. The goal was to extract the acoustic parameters (power, pulse duration, duty factor and pulse repetition frequency) that maintain a temperature increase of less than 1 °C during the application of a pulse ultrasound protocol. It was found that the temperature change increases linearly with duty factor. The higher the power, the lower the duty factor needed to keep the temperature change to the safe limit of 1 °C. The higher the frequency the lower the duty factor needed to keep the temperature change to the safe limit of 1 °C. Finally, the deeper the target, the higher the duty factor needed to keep the temperature change to the safe limit of 1 °C. The simulation model was tested in brain tissue during the application of pulse ultrasound and the measured temperature was in close agreement with the simulated temperature. This simulation model is considered to be very useful tool for providing acoustic parameters (frequency, power, duty factor, pulse repetition frequency) during the application of pulsed ultrasound at various depths in tissue so that a safe temperature is maintained during the treatment. This model could be tested soon during stroke clinical trials.

A distributed big data storage and data mining framework for solar-generated electricity quantity forecasting

NASA Astrophysics Data System (ADS)

Wang, Jianzong; Chen, Yanjun; Hua, Rui; Wang, Peng; Fu, Jia

2012-02-01

Photovoltaic is a method of generating electrical power by converting solar radiation into direct current electricity using semiconductors that exhibit the photovoltaic effect. Photovoltaic power generation employs solar panels composed of a number of solar cells containing a photovoltaic material. Due to the growing demand for renewable energy sources, the manufacturing of solar cells and photovoltaic arrays has advanced considerably in recent years. Solar photovoltaics are growing rapidly, albeit from a small base, to a total global capacity of 40,000 MW at the end of 2010. More than 100 countries use solar photovoltaics. Driven by advances in technology and increases in manufacturing scale and sophistication, the cost of photovoltaic has declined steadily since the first solar cells were manufactured. Net metering and financial incentives, such as preferential feed-in tariffs for solar-generated electricity; have supported solar photovoltaics installations in many countries. However, the power that generated by solar photovoltaics is affected by the weather and other natural factors dramatically. To predict the photovoltaic energy accurately is of importance for the entire power intelligent dispatch in order to reduce the energy dissipation and maintain the security of power grid. In this paper, we have proposed a big data system--the Solar Photovoltaic Power Forecasting System, called SPPFS to calculate and predict the power according the real-time conditions. In this system, we utilized the distributed mixed database to speed up the rate of collecting, storing and analysis the meteorological data. In order to improve the accuracy of power prediction, the given neural network algorithm has been imported into SPPFS.By adopting abundant experiments, we shows that the framework can provide higher forecast accuracy-error rate less than 15% and obtain low latency of computing by deploying the mixed distributed database architecture for solar-generated electricity.

Prevalence of diseases and statistical power of the Japan Nurses' Health Study.

PubMed

Fujita, Toshiharu; Hayashi, Kunihiko; Katanoda, Kota; Matsumura, Yasuhiro; Lee, Jung Su; Takagi, Hirofumi; Suzuki, Shosuke; Mizunuma, Hideki; Aso, Takeshi

2007-10-01

The Japan Nurses' Health Study (JNHS) is a long-term, large-scale cohort study investigating the effects of various lifestyle factors and healthcare habits on the health of Japanese women. Based on currently limited statistical data regarding the incidence of disease among Japanese women, our initial sample size was tentatively set at 50,000 during the design phase. The actual number of women who agreed to participate in follow-up surveys was approximately 18,000. Taking into account the actual sample size and new information on disease frequency obtained during the baseline component, we established the prevalence of past diagnoses of target diseases, predicted their incidence, and calculated the statistical power for JNHS follow-up surveys. For all diseases except ovarian cancer, the prevalence of a past diagnosis increased markedly with age, and incidence rates could be predicted based on the degree of increase in prevalence between two adjacent 5-yr age groups. The predicted incidence rate for uterine myoma, hypercholesterolemia, and hypertension was > or =3.0 (per 1,000 women, per year), while the rate of thyroid disease, hepatitis, gallstone disease, and benign breast tumor was predicted to be > or =1.0. For these diseases, the statistical power to detect risk factors with a relative risk of 1.5 or more within ten years, was 70% or higher.

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.

Whose intentions predict? Power over condom use within heterosexual dyads.

PubMed

VanderDrift, Laura E; Agnew, Christopher R; Harvey, S Marie; Warren, Jocelyn T

2013-10-01

According to major theories of behavioral prediction, the most proximal psychological predictor of an individual's behavior is that individual's intention. With respect to interdependent behaviors such as condom use, however, relationship dynamics influence individuals' power to make decisions and to act. The current study examines how relationship dynamics impact 3 condom use relevant outcomes: (a) the individual forming his or her own intention to use condoms, (b) the couple forming their joint intention to use condoms, and (c) actual condom use behavior. We conducted a 2-wave longitudinal study of young heterosexual adult couples at high risk for HIV infection involving the collection of both individual- and couple-derived data. Results demonstrate the importance of both person (e.g., biological sex and dispositional dominance) and relational (e.g., relational power and amount of interest in the relationship, operationalized as commitment and perceived alternatives to the relationship) factors in predicting condom use intentions and behavior. Individuals who are lower in dispositional dominance are likely to incorporate their partner's intentions into their own individual intentions; the intentions of individuals who have less interest in the relationship are more highly predictive of the couple's joint intention; and the intentions of men and individuals higher in relationship power are more likely to exert a direct influence on condom use. These findings have implications for improving the health of high-risk individuals, including suggesting situations in which individuals are highly influenced by their partners' intentions. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Adjusted Clinical Groups: Predictive Accuracy for Medicaid Enrollees in Three States

PubMed Central

Adams, E. Kathleen; Bronstein, Janet M.; Raskind-Hood, Cheryl

2002-01-01

Actuarial split-sample methods were used to assess predictive accuracy of adjusted clinical groups (ACGs) for Medicaid enrollees in Georgia, Mississippi (lagging in managed care penetration), and California. Accuracy for two non-random groups—high-cost and located in urban poor areas—was assessed. Measures for random groups were derived with and without short-term enrollees to assess the effect of turnover on predictive accuracy. ACGs improved predictive accuracy for high-cost conditions in all States, but did so only for those in Georgia's poorest urban areas. Higher and more unpredictable expenses of short-term enrollees moderated the predictive power of ACGs. This limitation was significant in Mississippi due in part, to that State's very high proportion of short-term enrollees. PMID:12545598

A computational modeling approach of the jet-like acoustic streaming and heat generation induced by low frequency high power ultrasonic horn reactors.

PubMed

Trujillo, Francisco Javier; Knoerzer, Kai

2011-11-01

High power ultrasound reactors have gained a lot of interest in the food industry given the effects that can arise from ultrasonic-induced cavitation in liquid foods. However, most of the new food processing developments have been based on empirical approaches. Thus, there is a need for mathematical models which help to understand, optimize, and scale up ultrasonic reactors. In this work, a computational fluid dynamics (CFD) model was developed to predict the acoustic streaming and induced heat generated by an ultrasonic horn reactor. In the model it is assumed that the horn tip is a fluid inlet, where a turbulent jet flow is injected into the vessel. The hydrodynamic momentum rate of the incoming jet is assumed to be equal to the total acoustic momentum rate emitted by the acoustic power source. CFD velocity predictions show excellent agreement with the experimental data for power densities higher than W(0)/V ≥ 25kWm(-3). This model successfully describes hydrodynamic fields (streaming) generated by low-frequency-high-power ultrasound. Crown Copyright © 2011. Published by Elsevier B.V. All rights reserved.

Power, distress, and compassion: turning a blind eye to the suffering of others.

PubMed

van Kleef, Gerben A; Oveis, Christopher; van der Löwe, Ilmo; LuoKogan, Aleksandr; Goetz, Jennifer; Keltner, Dacher

2008-12-01

Responses to individuals who suffer are a foundation of cooperative communities. On the basis of the approach/inhibition theory of power (Keltner, Gruenfeld, & Anderson, 2003), we hypothesized that elevated social power is associated with diminished reciprocal emotional responses to another person's suffering (feeling distress at another person's distress) and with diminished complementary emotion (e.g., compassion). In face-to-face conversations, participants disclosed experiences that had caused them suffering. As predicted, participants with a higher sense of power experienced less distress and less compassion and exhibited greater autonomic emotion regulation when confronted with another participant's suffering. Additional analyses revealed that these findings could not be attributed to power-related differences in baseline emotion or decoding accuracy, but were likely shaped by power-related differences in the motivation to affiliate. Implications for theorizing about power and the social functions of emotions are discussed.

Active optimal control strategies for increasing the efficiency of photovoltaic cells

NASA Astrophysics Data System (ADS)

Aljoaba, Sharif Zidan Ahmad

Energy consumption has increased drastically during the last century. Currently, the worldwide energy consumption is about 17.4 TW and is predicted to reach 25 TW by 2035. Solar energy has emerged as one of the potential renewable energy sources. Since its first physical recognition in 1887 by Adams and Day till nowadays, research in solar energy is continuously developing. This has lead to many achievements and milestones that introduced it as one of the most reliable and sustainable energy sources. Recently, the International Energy Agency declared that solar energy is predicted to be one of the major electricity production energy sources by 2035. Enhancing the efficiency and lifecycle of photovoltaic (PV) modules leads to significant cost reduction. Reducing the temperature of the PV module improves its efficiency and enhances its lifecycle. To better understand the PV module performance, it is important to study the interaction between the output power and the temperature. A model that is capable of predicting the PV module temperature and its effects on the output power considering the individual contribution of the solar spectrum wavelengths significantly advances the PV module edsigns toward higher efficiency. In this work, a thermoelectrical model is developed to predict the effects of the solar spectrum wavelengths on the PV module performance. The model is characterized and validated under real meteorological conditions where experimental temperature and output power of the PV module measurements are shown to agree with the predicted results. The model is used to validate the concept of active optical filtering. Since this model is wavelength-based, it is used to design an active optical filter for PV applications. Applying this filter to the PV module is expected to increase the output power of the module by filtering the spectrum wavelengths. The active filter performance is optimized, where different cutoff wavelengths are used to maximize the module output power. It is predicted that if the optimized active optical filter is applied to the PV module, the module efficiency is predicted to increase by about 1%. Different technologies are considered for physical implementation of the active optical filter.

SRG110 Stirling Generator Dynamic Simulator Vibration Test Results and Analysis Correlation

NASA Technical Reports Server (NTRS)

Lewandowski, Edward J.; Suarez, Vicente J.; Goodnight, Thomas W.; Callahan, John

2007-01-01

The U.S. Department of Energy (DOE), Lockheed Martin (LM), and NASA Glenn Research Center (GRC) have been developing the Stirling Radioisotope Generator (SRG110) for use as a power system for space science missions. The launch environment enveloping potential missions results in a random input spectrum that is significantly higher than historical radioisotope power system (RPS) launch levels and is a challenge for designers. Analysis presented in prior work predicted that tailoring the compliance at the generator-spacecraft interface reduced the dynamic response of the system thereby allowing higher launch load input levels and expanding the range of potential generator missions. To confirm analytical predictions, a dynamic simulator representing the generator structure, Stirling convertors and heat sources were designed and built for testing with and without a compliant interface. Finite element analysis was performed to guide the generator simulator and compliant interface design so that test modes and frequencies were representative of the SRG110 generator. This paper presents the dynamic simulator design, the test setup and methodology, test article modes and frequencies and dynamic responses, and post-test analysis results. With the compliant interface, component responses to an input environment exceeding the SRG110 qualification level spectrum were all within design allowables. Post-test analysis included finite element model tuning to match test frequencies and random response analysis using the test input spectrum. Analytical results were in good overall agreement with the test results and confirmed previous predictions that the SRG110 power system may be considered for a broad range of potential missions, including those with demanding launch environments.

Population impact of familial and environmental risk factors for schizophrenia: a nationwide study.

PubMed

Sørensen, Holger J; Nielsen, Philip R; Pedersen, Carsten B; Benros, Michael E; Nordentoft, Merete; Mortensen, Preben B

2014-03-01

Although several studies have examined the relative contributions of familial and environmental risk factors for schizophrenia, few have additionally examined the predictive power on the individual level and simultaneously examined the population impact associated with a wide range of familial and environmental risk factors. The authors present rate ratios (IRR), population-attributable risks (PAR) and sex-specific cumulative incidences of the following risk factors: parental history of mental illness, urban place of birth, advanced paternal age, parental loss and immigration status. We established a population-based cohort of 2,486,646million persons born in Denmark between 1 January 1955 and 31 December 1993 using Danish registers. We found that PAR associated with urban birth was 11.73%; PAR associated with one, respectively 2, parent(s) with schizophrenia was 2.67% and 0.12%. PAR associated with second-generation immigration was 0.70%. Highest cumulative incidence (CI=20.23%; 95% CI=18.10-22.62) was found in male offspring of 2 parents with schizophrenia. Cumulative incidences for male offspring or female offspring of a parent with schizophrenia were 9.53% (95% CI=7.71-11.79), and 4.89%, (95% CI 4.50-5.31). The study showed that risk factors with highest predictive power on the individual level have a relatively low population impact. The challenge in future studies with direct genetic data is to examine gene-environmental interactions that can move research beyond current approaches and seek to achieve higher predictive power on the individual level and higher population impact. Copyright © 2014 Elsevier B.V. All rights reserved.

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

PubMed

Nemes, Szilard; Rolfson, Ola; Garellick, Göran

2018-02-01

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

Prediction of the far field noise from wind energy farms

NASA Technical Reports Server (NTRS)

Shepherd, K. P.; Hubbard, H. H.

1986-01-01

The basic physical factors involved in making predictions of wind turbine noise and an approach which allows for differences in the machines, the wind energy farm configurations and propagation conditions are reviewed. Example calculations to illustrate the sensitivity of the radiated noise to such variables as machine size, spacing and numbers, and such atmosphere variables as absorption and wind direction are presented. It is found that calculated far field distances to particular sound level contours are greater for lower values of atmospheric absorption, for a larger total number of machines, for additional rows of machines and for more powerful machines. At short and intermediate distances, higher sound pressure levels are calculated for closer machine spacings, for more powerful machines, for longer row lengths and for closer row spacings.

Life Ownership Orientation and Attitudes toward Abortion, Suicide, Doctor-Assisted Suicide, and Capital Punishment.

ERIC Educational Resources Information Center

Ross, Lisa Thomson; Kaplan, Kalman J.

1994-01-01

Examined life ownership orientation (extent to which one believes that God, individual, or society has power over one's life) among 117 college students who completed Life Ownership Orientation Questionnaire (LOOQ). Found LOOQ scores demonstrated higher predictive validity with regard to attitudes toward abortion, suicide, doctor-assisted suicide,…

Mining LMS Data to Develop an "Early Warning System" for Educators: A Proof of Concept

ERIC Educational Resources Information Center

Macfadyen, Leah P.; Dawson, Shane

2010-01-01

Earlier studies have suggested that higher education institutions could harness the predictive power of Learning Management System (LMS) data to develop reporting tools that identify at-risk students and allow for more timely pedagogical interventions. This paper confirms and extends this proposition by providing data from an international…

Global Contexts of Higher Education

ERIC Educational Resources Information Center

Lovett, Clara M.

2013-01-01

In his 2008 bestseller, "The Post-American World," Fareed Zakaria argued that the most significant development of the early 21st century is not, as others have predicted, the inevitable decline of the United States as the world's super-power but rather "the rise of the rest." In subsequent works, Zakaria and many others,…

VLSI design of lossless frame recompression using multi-orientation prediction

NASA Astrophysics Data System (ADS)

Lee, Yu-Hsuan; You, Yi-Lun; Chen, Yi-Guo

2016-01-01

Pursuing an experience of high-end visual quality drives human to demand a higher display resolution and a higher frame rate. Hence, a lot of powerful coding tools are aggregated together in emerging video coding standards to improve coding efficiency. This also makes video coding standards suffer from two design challenges: heavy computation and tremendous memory bandwidth. The first issue can be properly solved by a careful hardware architecture design with advanced semiconductor processes. Nevertheless, the second one becomes a critical design bottleneck for a modern video coding system. In this article, a lossless frame recompression using multi-orientation prediction technique is proposed to overcome this bottleneck. This work is realised into a silicon chip with the technology of TSMC 0.18 µm CMOS process. Its encoding capability can reach full-HD (1920 × 1080)@48 fps. The chip power consumption is 17.31 mW@100 MHz. Core area and chip area are 0.83 × 0.83 mm2 and 1.20 × 1.20 mm2, respectively. Experiment results demonstrate that this work exhibits an outstanding performance on lossless compression ratio with a competitive hardware performance.

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

PubMed

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

2017-11-21

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

Epaxial muscle fiber architecture favors enhanced excursion and power in the leaper Galago senegalensis

PubMed Central

Huq, Emranul; Wall, Christine E; Taylor, Andrea B

2015-01-01

Galago senegalensis is a habitual arboreal leaper that engages in rapid spinal extension during push-off. Large muscle excursions and high contraction velocities are important components of leaping, and experimental studies indicate that during leaping by G. senegalensis, peak power is facilitated by elastic storage of energy. To date, however, little is known about the functional relationship between epaxial muscle fiber architecture and locomotion in leaping primates. Here, fiber architecture of select epaxial muscles is compared between G. senegalensis (n = 4) and the slow arboreal quadruped, Nycticebus coucang (n = 4). The hypothesis is tested that G. senegalensis exhibits architectural features of the epaxial muscles that facilitate rapid and powerful spinal extension during the take-off phase of leaping. As predicted, G. senegalensis epaxial muscles have relatively longer, less pinnate fibers and higher ratios of tendon length-to-fiber length, indicating the capacity for generating relatively larger muscle excursions, higher whole-muscle contraction velocities, and a greater capacity for elastic energy storage. Thus, the relatively longer fibers and higher tendon length-to-fiber length ratios can be functionally linked to leaping performance in G. senegalensis. It is further predicted that G. senegalensis epaxial muscles have relatively smaller physiological cross-sectional areas (PCSAs) as a consequence of an architectural trade-off between fiber length (excursion) and PCSA (force). Contrary to this prediction, there are no species differences in relative PCSAs, but the smaller-bodied G. senegalensis trends towards relatively larger epaxial muscle mass. These findings suggest that relative increase in muscle mass in G. senegalensis is largely attributable to longer fibers. The relative increase in erector spinae muscle mass may facilitate sagittal flexibility during leaping. The similarity between species in relative PCSAs provides empirical support for previous work linking osteological features of the vertebral column in lorisids with axial stability and reduced muscular effort associated with slow, deliberate movements during anti-pronograde locomotion. PMID:26184388

Beams 92. Proceedings of the International Conference on High-Power Particle Beams (9th) held in Washington, DC on May 25-29 1992, Volume 3

DTIC Science & Technology

1992-05-29

measurement we measured an aXP = 0.7(±0.2) when the value predicted by a single particle theory is ath = 0.35. The physical mechanism which leads to higher ...theoretical possibility of higher harmonics generation in the presence of a reversed guide field is highlighted. Introduction High-current free electron...ACCELERATORS, M. Bums, P. Allison, J. Downing, D.C. Moir, G. Caporaso, Y.J. Chen ...................................................... 283 SLIA THEORY

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

PubMed

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

2014-03-01

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

Numerical simulation and comparison of conventional and sloped solar chimney power plants: the case for Lanzhou.

PubMed

Cao, Fei; Li, Huashan; Zhang, Yang; Zhao, Liang

2013-01-01

The solar chimney power plant (SCPP) generates updraft wind through the green house effect. In this paper, the performances of two SCPP styles, that is, the conventional solar chimney power plant (CSCPP) and the sloped solar chimney power plant (SSCPP), are compared through a numerical simulation. A simplified Computational Fluid Dynamics (CFD) model is built to predict the performances of the SCPP. The model is validated through a comparison with the reported results from the Manzanares prototype. The annual performances of the CSCPP and the SSCPP are compared by taking Lanzhou as a case study. Numerical results indicate that the SSCPP holds a higher efficiency and generates smoother power than those of the CSCPP, and the effective pressure in the SSCPP is relevant to both the chimney and the collector heights.

Numerical Simulation and Comparison of Conventional and Sloped Solar Chimney Power Plants: The Case for Lanzhou

PubMed Central

Zhang, Yang; Zhao, Liang

2013-01-01

The solar chimney power plant (SCPP) generates updraft wind through the green house effect. In this paper, the performances of two SCPP styles, that is, the conventional solar chimney power plant (CSCPP) and the sloped solar chimney power plant (SSCPP), are compared through a numerical simulation. A simplified Computational Fluid Dynamics (CFD) model is built to predict the performances of the SCPP. The model is validated through a comparison with the reported results from the Manzanares prototype. The annual performances of the CSCPP and the SSCPP are compared by taking Lanzhou as a case study. Numerical results indicate that the SSCPP holds a higher efficiency and generates smoother power than those of the CSCPP, and the effective pressure in the SSCPP is relevant to both the chimney and the collector heights. PMID:24489515

Predicting fatty acid profiles in blood based on food intake and the FADS1 rs174546 SNP.

PubMed

Hallmann, Jacqueline; Kolossa, Silvia; Gedrich, Kurt; Celis-Morales, Carlos; Forster, Hannah; O'Donovan, Clare B; Woolhead, Clara; Macready, Anna L; Fallaize, Rosalind; Marsaux, Cyril F M; Lambrinou, Christina-Paulina; Mavrogianni, Christina; Moschonis, George; Navas-Carretero, Santiago; San-Cristobal, Rodrigo; Godlewska, Magdalena; Surwiłło, Agnieszka; Mathers, John C; Gibney, Eileen R; Brennan, Lorraine; Walsh, Marianne C; Lovegrove, Julie A; Saris, Wim H M; Manios, Yannis; Martinez, Jose Alfredo; Traczyk, Iwona; Gibney, Michael J; Daniel, Hannelore

2015-12-01

A high intake of n-3 PUFA provides health benefits via changes in the n-6/n-3 ratio in blood. In addition to such dietary PUFAs, variants in the fatty acid desaturase 1 (FADS1) gene are also associated with altered PUFA profiles. We used mathematical modeling to predict levels of PUFA in whole blood, based on multiple hypothesis testing and bootstrapped LASSO selected food items, anthropometric and lifestyle factors, and the rs174546 genotypes in FADS1 from 1607 participants (Food4Me Study). The models were developed using data from the first reported time point (training set) and their predictive power was evaluated using data from the last reported time point (test set). Among other food items, fish, pizza, chicken, and cereals were identified as being associated with the PUFA profiles. Using these food items and the rs174546 genotypes as predictors, models explained 26-43% of the variability in PUFA concentrations in the training set and 22-33% in the test set. Selecting food items using multiple hypothesis testing is a valuable contribution to determine predictors, as our models' predictive power is higher compared to analogue studies. As unique feature, we additionally confirmed our models' power based on a test set. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification of Type 2 Diabetes Risk Factors Using Phenotypes Consisting of Anthropometry and Triglycerides based on Machine Learning.

PubMed

Lee, Bum Ju; Kim, Jong Yeol

2016-01-01

The hypertriglyceridemic waist (HW) phenotype is strongly associated with type 2 diabetes; however, to date, no study has assessed the predictive power of phenotypes based on individual anthropometric measurements and triglyceride (TG) levels. The aims of the present study were to assess the association between the HW phenotype and type 2 diabetes in Korean adults and to evaluate the predictive power of various phenotypes consisting of combinations of individual anthropometric measurements and TG levels. Between November 2006 and August 2013, 11,937 subjects participated in this retrospective cross-sectional study. We measured fasting plasma glucose and TG levels and performed anthropometric measurements. We employed binary logistic regression (LR) to examine statistically significant differences between normal subjects and those with type 2 diabetes using HW and individual anthropometric measurements. For more reliable prediction results, two machine learning algorithms, naive Bayes (NB) and LR, were used to evaluate the predictive power of various phenotypes. All prediction experiments were performed using a tenfold cross validation method. Among all of the variables, the presence of HW was most strongly associated with type 2 diabetes (p < 0.001, adjusted odds ratio (OR) = 2.07 [95% CI, 1.72-2.49] in men; p < 0.001, adjusted OR = 2.09 [1.79-2.45] in women). When comparing waist circumference (WC) and TG levels as components of the HW phenotype, the association between WC and type 2 diabetes was greater than the association between TG and type 2 diabetes. The phenotypes tended to have higher predictive power in women than in men. Among the phenotypes, the best predictors of type 2 diabetes were waist-to-hip ratio + TG in men (AUC by NB = 0.653, AUC by LR = 0.661) and rib-to-hip ratio + TG in women (AUC by NB = 0.73, AUC by LR = 0.735). Although the presence of HW demonstrated the strongest association with type 2 diabetes, the predictive power of the combined measurements of the actual WC and TG values may not be the best manner of predicting type 2 diabetes. Our findings may provide clinical information concerning the development of clinical decision support systems for the initial screening of type 2 diabetes.

Implementing effective policy in a national mental health re-engagement program for Veterans

PubMed Central

Smith, Shawna N.; Lai, Zongshan; Almirall, Daniel; Goodrich, David E.; Abraham, Kristen M.; Nord, Kristina M.; Kilbourne, Amy M.

2016-01-01

Policy is a powerful motivator of clinical change, but implementation success can depend on organizational characteristics. This paper used validated measures of organizational resources, culture and climate to predict uptake of a nationwide VA policy aimed at implementing Re-Engage, a brief care management program that re-establishes contact with Veterans with serious mental illness lost to care. Patient care databases were used to identify 2,738 Veterans lost to care. Local Recovery Coordinators (LRCs) were to update disposition for 2,738 Veterans at 158 VA facilities and, as appropriate, facilitate a return to care. Multivariable regression assessed organizational culture and climate as predictors of early policy compliance (via LRC presence) and uptake at six months. Higher composite climate and culture scores were associated with higher odds of having a designated LRC, but were not predictive of higher uptake. Sites with LRCs had significantly higher rates of updated documentation than sites without LRCs. PMID:27668352

Comparison of the economic impact of different wind power forecast systems for producers

NASA Astrophysics Data System (ADS)

Alessandrini, S.; Davò, F.; Sperati, S.; Benini, M.; Delle Monache, L.

2014-05-01

Deterministic forecasts of wind production for the next 72 h at a single wind farm or at the regional level are among the main end-users requirement. However, for an optimal management of wind power production and distribution it is important to provide, together with a deterministic prediction, a probabilistic one. A deterministic forecast consists of a single value for each time in the future for the variable to be predicted, while probabilistic forecasting informs on probabilities for potential future events. This means providing information about uncertainty (i.e. a forecast of the PDF of power) in addition to the commonly provided single-valued power prediction. A significant probabilistic application is related to the trading of energy in day-ahead electricity markets. It has been shown that, when trading future wind energy production, using probabilistic wind power predictions can lead to higher benefits than those obtained by using deterministic forecasts alone. In fact, by using probabilistic forecasting it is possible to solve economic model equations trying to optimize the revenue for the producer depending, for example, on the specific penalties for forecast errors valid in that market. In this work we have applied a probabilistic wind power forecast systems based on the "analog ensemble" method for bidding wind energy during the day-ahead market in the case of a wind farm located in Italy. The actual hourly income for the plant is computed considering the actual selling energy prices and penalties proportional to the unbalancing, defined as the difference between the day-ahead offered energy and the actual production. The economic benefit of using a probabilistic approach for the day-ahead energy bidding are evaluated, resulting in an increase of 23% of the annual income for a wind farm owner in the case of knowing "a priori" the future energy prices. The uncertainty on price forecasting partly reduces the economic benefit gained by using a probabilistic energy forecast system.

Identifying students with dyslexia in higher education.

PubMed

Tops, Wim; Callens, Maaike; Lammertyn, Jan; Van Hees, Valérie; Brysbaert, Marc

2012-10-01

An increasing number of students with dyslexia enter higher education. As a result, there is a growing need for standardized diagnosis. Previous research has suggested that a small number of tests may suffice to reliably assess students with dyslexia, but these studies were based on post hoc discriminant analysis, which tends to overestimate the percentage of systematic variance, and were limited to the English language (and the Anglo-Saxon education system). Therefore, we repeated the research in a non-English language (Dutch) and we selected variables on the basis of a prediction analysis. The results of our study confirm that it is not necessary to administer a wide range of tests to diagnose dyslexia in (young) adults. Three tests sufficed: word reading, word spelling and phonological awareness, in line with the proposal that higher education students with dyslexia continue to have specific problems with reading and writing. We also show that a traditional postdiction analysis selects more variables of importance than the prediction analysis. However, these extra variables explain study-specific variance and do not result in more predictive power of the model.

Flexural isostasy: Constraints from gravity and topography power spectra

NASA Astrophysics Data System (ADS)

Watts, Tony; Moore, James

2017-04-01

We have used the spherical harmonic coefficients that describe the EGM2008 gravity and topography model (Pavlis et al. 2010) to quantify the role of flexural isostasy in contributing to Earth's gravity and topography. Power spectra show that the gravity effect of the topography and its flexural compensation contributes significantly to the observed free-air gravity anomaly field for degree 33-180, which corresponds approximately to wavelengths of 220-1200 km. The best fit is for an elastic thickness of the lithosphere, Te, of 34.0±4.0 km. Smaller values of Te, under-predict while high values of Te, over-predict the observed gravity spectra. The best fit value is a global average and so it is reasonable to speculate that regions exist where Te is both lower and higher. This is confirmed in studies of selected regions such as the Hawaiian-Emperor seamount chain and the Ganges-Himalaya foreland fold and thrust belt where we show that flexural isostatic anomalies are near zero in regions where Te approaches 34 km (e.g. Hawaiian ridge) and of large amplitude in regions of lower (e.g. Emperor) and higher Te (e.g. Ganges-Himalaya). Plate flexure may be significant at higher (180-441) and lower (12-33) degrees, but topography appears either uncompensated or fully compensated at these degrees, irrespective of the actual Te. Nevertheless, all isostatic models under-predict the observed gravity spectra at degree <12 and so we interpret the low order Earth's gravity field as caused by non-isostatic processes due to dynamic motions such as those associated with mantle convection.

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.

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.

One-side forward-backward asymmetry in top quark pair production at the CERN Large Hadron Collider

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

Wang Youkai; Xiao Bo; Zhu Shouhua

2010-11-01

Both D0 and CDF at Tevatron reported the measurements of forward-backward asymmetry in top pair production, which showed possible deviation from the standard model QCD prediction. In this paper, we explore how to examine the same higher-order QCD effects at the more powerful Large Hadron Collider.

Promoting Teaching Excellence of Universities in Taiwan: Policy Analysis with a Special Reference to Educational Equality

ERIC Educational Resources Information Center

Yang, Cheng-Cheng; Huang, Yueh-Chun

2012-01-01

As some comparative educators predict, educational policies will move toward similar paths when globalization becomes more powerful. The global higher education expansion in the past decades is one example. The quest of establishing world class universities in the world is another case. The Taiwan government experiences challenges from expansion…

Internal mechanisms underlying anticipatory language processing: Evidence from event-related-potentials and neural oscillations.

PubMed

Li, Xiaoqing; Zhang, Yuping; Xia, Jinyan; Swaab, Tamara Y

2017-07-28

Although numerous studies have demonstrated that the language processing system can predict upcoming content during comprehension, there is still no clear picture of the anticipatory stage of predictive processing. This electroencephalograph study examined the cognitive and neural oscillatory mechanisms underlying anticipatory processing during language comprehension, and the consequences of this prediction for bottom-up processing of predicted/unpredicted content. Participants read Mandarin Chinese sentences that were either strongly or weakly constraining and that contained critical nouns that were congruent or incongruent with the sentence contexts. We examined the effects of semantic predictability on anticipatory processing prior to the onset of the critical nouns and on integration of the critical nouns. The results revealed that, at the integration stage, the strong-constraint condition (compared to the weak-constraint condition) elicited a reduced N400 and reduced theta activity (4-7Hz) for the congruent nouns, but induced beta (13-18Hz) and theta (4-7Hz) power decreases for the incongruent nouns, indicating benefits of confirmed predictions and potential costs of disconfirmed predictions. More importantly, at the anticipatory stage, the strongly constraining context elicited an enhanced sustained anterior negativity and beta power decrease (19-25Hz), which indicates that strong prediction places a higher processing load on the anticipatory stage of processing. The differences (in the ease of processing and the underlying neural oscillatory activities) between anticipatory and integration stages of lexical processing were discussed with regard to predictive processing models. Copyright © 2017 Elsevier Ltd. All rights reserved.

Image Feature Types and Their Predictions of Aesthetic Preference and Naturalness

PubMed Central

Ibarra, Frank F.; Kardan, Omid; Hunter, MaryCarol R.; Kotabe, Hiroki P.; Meyer, Francisco A. C.; Berman, Marc G.

2017-01-01

Previous research has investigated ways to quantify visual information of a scene in terms of a visual processing hierarchy, i.e., making sense of visual environment by segmentation and integration of elementary sensory input. Guided by this research, studies have developed categories for low-level visual features (e.g., edges, colors), high-level visual features (scene-level entities that convey semantic information such as objects), and how models of those features predict aesthetic preference and naturalness. For example, in Kardan et al. (2015a), 52 participants provided aesthetic preference and naturalness ratings, which are used in the current study, for 307 images of mixed natural and urban content. Kardan et al. (2015a) then developed a model using low-level features to predict aesthetic preference and naturalness and could do so with high accuracy. What has yet to be explored is the ability of higher-level visual features (e.g., horizon line position relative to viewer, geometry of building distribution relative to visual access) to predict aesthetic preference and naturalness of scenes, and whether higher-level features mediate some of the association between the low-level features and aesthetic preference or naturalness. In this study we investigated these relationships and found that low- and high- level features explain 68.4% of the variance in aesthetic preference ratings and 88.7% of the variance in naturalness ratings. Additionally, several high-level features mediated the relationship between the low-level visual features and aaesthetic preference. In a multiple mediation analysis, the high-level feature mediators accounted for over 50% of the variance in predicting aesthetic preference. These results show that high-level visual features play a prominent role predicting aesthetic preference, but do not completely eliminate the predictive power of the low-level visual features. These strong predictors provide powerful insights for future research relating to landscape and urban design with the aim of maximizing subjective well-being, which could lead to improved health outcomes on a larger scale. PMID:28503158

The Effect of Sex on Heart Rate Variability at High Altitude.

PubMed

Boos, Christopher John; Vincent, Emma; Mellor, Adrian; O'Hara, John; Newman, Caroline; Cruttenden, Richard; Scott, Phylip; Cooke, Mark; Matu, Jamie; Woods, David Richard

2017-12-01

There is evidence suggesting that high altitude (HA) exposure leads to a fall in heart rate variability (HRV) that is linked to the development of acute mountain sickness (AMS). The effects of sex on changes in HRV at HA and its relationship to AMS are unknown. HRV (5-min single-lead ECG) was measured in 63 healthy adults (41 men and 22 women) 18-56 yr of age at sea level (SL) and during a HA trek at 3619, 4600, and 5140 m, respectively. The main effects of altitude (SL, 3619 m, 4600 m, and 5140 m) and sex (men vs women) and their potential interaction were assessed using a factorial repeated-measures ANOVA. Logistic regression analyses were performed to assess the ability of HRV to predict AMS. Men and women were of similar age (31.2 ± 9.3 vs 31.7 ± 7.5 yr), ethnicity, and body and mass index. There was main effect for altitude on heart rate, SD of normal-to-normal (NN) intervals (SDNN), root mean square of successive differences (RMSSD), number of pairs of successive NN differing by >50 ms (NN50), NN50/total number of NN, very low-frequency power, low-frequency (LF) power, high-frequency (HF) power, and total power (TP). The most consistent effect on post hoc analysis was reduction in these HRV measures between 3619 and 5140 m at HA. Heart rate was significantly lower and SDNN, RMSSD, LF power, HF power, and TP were higher in men compared with women at HA. There was no interaction between sex and altitude for any of the HRV indices measured. HRV was not predictive of AMS development. Increasing HA leads to a reduction in HRV. Significant differences between men and women emerge at HA. HRV was not predictive of AMS.

Thermomechanical modelling of laser surface glazing for H13 tool steel

NASA Astrophysics Data System (ADS)

Kabir, I. R.; Yin, D.; Tamanna, N.; Naher, S.

2018-03-01

A two-dimensional thermomechanical finite element (FE) model of laser surface glazing (LSG) has been developed for H13 tool steel. The direct coupling technique of ANSYS 17.2 (APDL) has been utilised to solve the transient thermomechanical process. A H13 tool steel cylindrical cross-section has been modelled for laser power 200 W and 300 W at constant 0.2 mm beam width and 0.15 ms residence time. The model can predict temperature distribution, stress-strain increments in elastic and plastic region with time and space. The crack formation tendency also can be assumed by analysing the von Mises stress in the heat-concentrated zone. Isotropic and kinematic hardening models have been applied separately to predict the after-yield phenomena. At 200 W laser power, the peak surface temperature achieved is 1520 K which is below the melting point (1727 K) of H13 tool steel. For laser power 300 W, the peak surface temperature is 2523 K. Tensile residual stresses on surface have been found after cooling, which are in agreement with literature. Isotropic model shows higher residual stress that increases with laser power. Conversely, kinematic model gives lower residual stress which decreases with laser power. Therefore, both plasticity models could work in LSG for H13 tool steel.

Influence of polygenic risk scores on lipid levels and dyslipidemia in a psychiatric population receiving weight gain-inducing psychotropic drugs.

PubMed

Delacrétaz, Aurélie; Lagares Santos, Patricia; Saigi Morgui, Nuria; Vandenberghe, Frederik; Glatard, Anaïs; Gholam-Rezaee, Mehdi; von Gunten, Armin; Conus, Philippe; Eap, Chin B

2017-12-01

Dyslipidemia represents a major health issue in psychiatry. We determined whether weighted polygenic risk scores (wPRSs) combining multiple single-nucleotide polymorphisms (SNPs) associated with lipid levels in the general population are associated with lipid levels [high-density lipoprotein (HDL), low-density lipoprotein (LDL), total cholesterol (TC), and triglycerides] and/or dyslipidemia in patients receiving weight gain-inducing psychotropic drugs. We also determined whether genetics improve the predictive power of dyslipidemia. The influence of wPRS on lipid levels was firstly assessed in a discovery psychiatric sample (n=332) and was then tested for replication in an independent psychiatric sample (n=140). The contribution of genetic markers to predict dyslipidemia was evaluated in the combined psychiatric sample. wPRSs were significantly associated with the four lipid traits in the discovery (P≤0.02) and in the replication sample (P≤0.03). Patients whose wPRS was higher than the median wPRS had significantly higher LDL, TC, and triglyceride levels (0.20, 0.32 and 0.26 mmol/l, respectively; P≤0.004) and significantly lower HDL levels (0.13 mmol/l; P<0.0001) compared with others. Adding wPRS to clinical data significantly improved dyslipidemia prediction of HDL (P=0.03) and a trend for improvement was observed for the prediction of TC dyslipidemia (P=0.08). Population-based wPRSs have thus significant effects on lipid levels in the psychiatric population. As genetics improved the predictive power of dyslipidemia development, only 24 patients need to be genotyped to prevent the development of one case of HDL hypocholesterolemia. If confirmed by further prospective investigations, the present results could be used for individualizing psychotropic treatment.

A comparison of efficacy of six prediction models for intravenous immunoglobulin resistance in Kawasaki disease.

PubMed

Qian, Weiguo; Tang, Yunjia; Yan, Wenhua; Sun, Ling; Lv, Haitao

2018-03-09

Kawasaki disease (KD) is the most common pediatric vasculitis. Several models have been established to predict intravenous immunoglobulin (IVIG) resistance. The present study was aimed to evaluate the efficacy of prediction models using the medical data of KD patients. We collected the medical records of patients hospitalized in the Department of Cardiology in Children's Hospital of Soochow University with a diagnosis of KD from Jan 2015 to Dec 2016. IVIG resistance was defined as recrudescent or persistent fever ≥36 h after the end of their IVIG infusion. Patients with IVIG resistance tended to be younger, have higher occurrence of rash and changes of extremities. They had higher levels of c-reactive protein, aspartate aminotransferase, neutrophils proportion (N%), total bilirubin and lower level of albumin. Our prediction model had a sensitivity of 0.72 and a specificity of 0.75. Sensitivity of Kobayashi, Egami, Kawamura, Sano and Formosa were 0.72, 0.44, 0.48, 0.20, and 0.68, respectively. Specificity of these models were 0.62, 0.82, 0.66, 0.91, and 0.48, respectively. Our prediction model had a powerful predictive value in this area, followed by Kobayashi model while all the other prediction models had less excellent performances than ours.

[Studies of marker screening efficiency and corresponding influencing factors in QTL composite interval mapping].

PubMed

Gao, Yong-Ming; Wan, Ping

2002-06-01

Screening markers efficiently is the foundation of mapping QTLs by composite interval mapping. Main and interaction markers distinguished, besides using background control for genetic variation, could also be used to construct intervals of two-way searching for mapping QTLs with epistasis, which can save a lot of calculation time. Therefore, the efficiency of marker screening would affect power and precision of QTL mapping. A doubled haploid population with 200 individuals and 5 chromosomes was constructed, with 50 markers evenly distributed at 10 cM space. Among a total of 6 QTLs, one was placed on chromosome I, two linked on chromosome II, and the other three linked on chromosome IV. QTL setting included additive effects and epistatic effects of additive x additive, the corresponding QTL interaction effects were set if data were collected under multiple environments. The heritability was assumed to be 0.5 if no special declaration. The power of marker screening by stepwise regression, forward regression, and three methods for random effect prediction, e.g. best linear unbiased prediction (BLUP), linear unbiased prediction (LUP) and adjusted unbiased prediction (AUP), was studied and compared through 100 Monte Carlo simulations. The results indicated that the marker screening power by stepwise regression at 0.1, 0.05 and 0.01 significant level changed from 2% to 68%, the power changed from 2% to 72% by forward regression. The larger the QTL effects, the higher the marker screening power. While the power of marker screening by three random effect prediction was very low, the maximum was only 13%. That suggested that regression methods were much better than those by using the approaches of random effect prediction to identify efficient markers flanking QTLs, and forward selection method was more simple and efficient. The results of simulation study on heritability showed that heightening of both general heritability and interaction heritability of genotype x environments could enhance marker screening power, the former had a greater influence on QTLs with larger main and/or epistatic effects, while the later on QTLs with small main and/or epistatic effects. The simulation of 100 times was also conducted to study the influence of different marker number and density on marker screening power. It is indicated that the marker screening power would decrease if there were too many markers, especially with high density in a mapping population, which suggested that a mapping population with definite individuals could only hold limited markers. According to the simulation study, the reasonable number of markers should not be more than individuals. The simulation study of marker screening under multiple environments showed high total power of marker screening. In order to relieve the problem that marker screening power restricted the efficiency of QTL mapping, markers identified in multiple environments could be used to construct two search intervals.

Performance of U3Si2 Fuel in a Reactivity Insertion Accident

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

Cheng, Lap Y.; Cuadra, Arantxa; Todosow, Michael

In this study we examined the performance of the U3Si2 fuel cladded with Zircaloy (Zr) in a reactivity insertion accident (RIA) in a PWR core. The power excursion as a result of a $1 reactivity insertion was calculated by a TRACE PWR plant model using point-kinetics, for alternative cores with UO2 and U3Si2 fuel assemblies. The point-kinetics parameters (feedback coefficients, prompt-neutron lifetime and group constants for six delayed-neutron groups) were obtained from beginning-of-cycle equilibrium full core calculations with PARCS. In the PARCS core calculations, the few-group parameters were developed utilizing the TRITON/NEWT tools in the SCALE package. In order tomore » assess the fuel response in finer detail (e.g. the maximum fuel temperature) the power shape and thermal boundary conditions from the TRACE/PARCS calculations were used to drive a BISON model of a fuel pin with U3Si2 and UO2 respectively. For a $1 reactivity transient both TRACE and BISON predicted a higher maximum fuel temperature for the UO2 fuel than the U3Si2 fuel. Furthermore, BISON is noted to calculate a narrower gap and a higher gap heat transfer coefficient than TRACE. This resulted in BISON predicting consistently lower fuel temperatures than TRACE. This study also provides a systematic comparison between TRACE and BISON using consistent transient boundary conditions. The TRACE analysis of the RIA only reflects the core-wide response in power. A refinement to the analysis would be to predict the local peaking in a three-dimensional core as a result of control rod ejection.« less

High-Power Piezoelectric Acoustic-Electric Power Feedthru for Metal Walls

NASA Technical Reports Server (NTRS)

Bao, Xiaoqi; Biederman, Will; Sherrit, Stewart; Badescu, Mircea; Bar-Cohen, Yoseph; Jones, Christopher; Aldrich, Jack; Chang, Zensheu

2008-01-01

Piezoelectric acoustic-electric power feed-through devices transfer electric power wirelessly through a solid wall by using acoustic waves. This approach allows for the removal of holes through structures. The technology is applicable to power supply for electric equipment inside sealed containers, vacuum or pressure vessels, etc where the holes on the wall are prohibitive or result in significant performance degrade or complex designs. In the author's previous work, 100-W electric power was transferred through a metal wall by a small, simple-structure piezoelectric device. To meet requirements of higher power applications, the feasibility to transfer kilowatts level power was investigated. Pre-stressed longitudinal piezoelectric feedthru devices were analyzed by finite element model. An equivalent circuit model was developed to predict the power transfer characteristics to different electric loads. Based on the analysis results, a prototype device was designed, fabricated and a demonstration of the transmission of electric power up to 1-kW was successfully conducted. The methods to minimize the plate wave excitation on the wall were also analyzed. Both model analysis and experimental results are presented in detail in this presentation.

On- and off-eye spherical aberration of soft contact lenses and consequent changes of effective lens power.

PubMed

Dietze, Holger H; Cox, Michael J

2003-02-01

Soft contact lenses produce a significant level of spherical aberration affecting their power on-eye. A simple model assuming that a thin soft contact lens aligns to the cornea predicts that these effects are similar on-eye and off-eye. The wavefront aberration for 17 eyes and 33 soft contact lenses on-eye was measured with a Shack-Hartmann wavefront sensor. The Zernike coefficients describing the on-eye spherical aberration of the soft contact lens were compared with off-eye ray-tracing results. Paraxial and effective lens power changes were determined. The model predicts the on-eye spherical aberration of soft contact lenses closely. The resulting power change for a +/- 7.00 D spherical soft contact lens is +/- 0.5 D for a 6-mm pupil diameter and +/- 0.1 D for a 3-mm pupil diameter. Power change is negligible for soft contact lenses corrected for off-eye spherical aberration. For thin soft contact lenses, the level of spherical aberration and the consequent power change is similar on-eye and off-eye. Soft contact lenses corrected for spherical aberration in air will be expected to be aberration-free on-eye and produce only negligibly small power changes. For soft contact lenses without aberration correction, for higher levels of ametropia and large pupils, the soft contact lens power should be determined with trial lenses with their power and p value similar to the prescribed lens. The benefit of soft contact lenses corrected for spherical aberration depends on the level of ocular spherical aberration.

Heat pipe cooling of power processing magnetics

NASA Technical Reports Server (NTRS)

Hansen, I. G.; Chester, M.

1979-01-01

The constant demand for increased power and reduced mass has raised the internal temperature of conventionally cooled power magnetics toward the upper limit of acceptability. The conflicting demands of electrical isolation, mechanical integrity, and thermal conductivity preclude significant further advancements using conventional approaches. However, the size and mass of multikilowatt power processing systems may be further reduced by the incorporation of heat pipe cooling directly into the power magnetics. Additionally, by maintaining lower more constant temperatures, the life and reliability of the magnetic devices will be improved. A heat pipe cooled transformer and input filter have been developed for the 2.4 kW beam supply of a 30-cm ion thruster system. This development yielded a mass reduction of 40% (1.76 kg) and lower mean winding temperature (20 C lower). While these improvements are significant, preliminary designs predict even greater benefits to be realized at higher power. This paper presents the design details along with the results of thermal vacuum operation and the component performance in a 3 kW breadboard power processor.

Analysis of satellite measurements of terrestrial radio noise

NASA Technical Reports Server (NTRS)

Bakalyar, G.; Caruso, J. A.; Vargas-Vila, R.; Ziemba, E.

1974-01-01

Worldwide distributions of terrestrial radio noise as monitored by Radio Astronomy Explorer 1 (RAE 1) generated and compared with CCIR predictions. These contour maps show the global morphology of radio noise at 6.55 and 9.18 MHz for fall, winter, spring and summer during the local time blocks of 00-08 LT and 16-24 LT. These computer produced maps show general agreement with CCIR predictions over large land masses. The RAE and CCIR maps diverge at high latitudes over Asia and frequently over ocean regions. Higher noise levels observed by RAE at high latitudes are attributed to magnetospheric emission while higher noise levels observed by RAE over Asia are attributable to high power transmitters. Analysis of RAE noise observations in conjunction with various geophysical phenomena showed no obvious correlation.

Identification of Hemoglobin Levels Based on Anthropometric Indices in Elderly Koreans

PubMed Central

Kim, Jong Yeol

2016-01-01

Objectives Anemia is independently and strongly associated with an increased risk of mortality in older people and is also strongly associated with obesity. The objectives of the present study were to examine the associations between the hemoglobin level and various anthropometric indices, to predict low and normal hemoglobin levels using combined anthropometric indices, and to assess differences in the hemoglobin level and anthropometric indices between Korean men and women. Methods A total of 7,156 individuals ranging in age from 53–90 years participated in this retrospective cross-sectional study. Binary logistic regression (LR) and naïve Bayes (NB) models were used to identify significant differences in the anthropometric indices between subjects with low and normal hemoglobin levels and to assess the predictive power of these indices for the hemoglobin level. Results Among all of the variables, age displayed the strongest association with the hemoglobin level in both men (p < 0.0001, odds ratio [OR] = 0.487, area under the receiver operating characteristic curve based on the LR [LR-AUC] = 0.702, NB-AUC = 0.701) and women (p < 0.0001, OR = 0.636, LR-AUC = 0.625, NB-AUC = 0.624). Among the anthropometric indices, weight and body mass index (BMI) were the best predictors of the hemoglobin level. The predictive powers of all of the variables were higher in men than in women. The AUC values for the NB-Wrapper and LR-Wrapper predictive models generated using combined anthropometric indices were 0.734 and 0.723, respectively, for men and 0.649 and 0.652, respectively, for women. The use of combined anthropometric indices may improve the predictive power for the hemoglobin level. Discussion Among the various anthropometric indices, with the exception of age, we did not identify any indices that were better predictors than weight and BMI for low and normal hemoglobin levels. In addition, none of the ratios between pairs of indices were good indicators of the hemoglobin level. Finally, the Korean men tended to have higher associations between the anthropometric indices and anemia than the women. PMID:27812118

The predictive performance of a path-dependent exotic-option credit risk model in the emerging market

NASA Astrophysics Data System (ADS)

Chen, Dar-Hsin; Chou, Heng-Chih; Wang, David; Zaabar, Rim

2011-06-01

Most empirical research of the path-dependent, exotic-option credit risk model focuses on developed markets. Taking Taiwan as an example, this study investigates the bankruptcy prediction performance of the path-dependent, barrier option model in the emerging market. We adopt Duan's (1994) [11], (2000) [12] transformed-data maximum likelihood estimation (MLE) method to directly estimate the unobserved model parameters, and compare the predictive ability of the barrier option model to the commonly adopted credit risk model, Merton's model. Our empirical findings show that the barrier option model is more powerful than Merton's model in predicting bankruptcy in the emerging market. Moreover, we find that the barrier option model predicts bankruptcy much better for highly-leveraged firms. Finally, our findings indicate that the prediction accuracy of the credit risk model can be improved by higher asset liquidity and greater financial transparency.

Effects of turbulence in the atmosphere of Venus on Pioneer Venus radio, phase 1

NASA Technical Reports Server (NTRS)

Woo, R.; Kendall, W.; Ishimaru, A.; Berwin, R.

1973-01-01

The prediction of the turbulence effects in the Venus atmosphere on Pioneer Venus radio was investigated. A careful investigation based on a theoretical and experimental study of the power spectrum of the Mariner 5 amplitude fluctuations is carried out and the results contribute considerably to our scientific knowledge of turbulence in the atmosphere of Venus. Fully developed turbulence is seen to exist predominantly in the altitude range of 41 - 49 km. This result is consistent with the high wind shear and wind velocities observed by Venera 4 for altitudes higher than 40 km. The outer scale size of turbulence is on the order of 100 m, the structure constant for the dayside atmosphere 3.9 x 10 to the -7 power m to the -1/3rd power, and that for the nightside atmosphere 2.9 x 10 to the -7 power m to the -1/3rd power.

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.

Distinct plasma lipids profiles of recurrent ovarian cancer by liquid chromatography-mass spectrometry

PubMed Central

Li, Ang; Cheng, Jinlong; Yang, Kai; Wang, Jingtao; Wang, Wenjie; Zhang, Fan; Li, Zhenzi; Dhillon, Harman S.; Openkova, Margarita S; Zhou, Xiaohua; Li, Kang; Hou, Yan

2017-01-01

Epithelial ovarian cancer (EOC) is the most deadly gynecologic malignancy worldwide due to its high recurrence rate after surgery and chemotherapy. There is a critical need for discovery of novel biomarkers for EOC recurrence providing higher prediction power than that of the present ones. Lipids have been reported to associate with development and progression of cancer. In the current study, we aim to identify and validate the lipids which were relevant to the ovarian cancer recurrence based on plasma lipidomics performed by ultra-performance liquid chromatography coupled with mass spectrometry. In order to fulfill this objective, plasma from 70 EOC patients with follow up information was obtained. The results revealed that patients with and without recurrence could be clearly distinguished based on their lipid profiles. Thirty-one lipid metabolites were identified as potential biomarkers for EOC recurrence. The AUC value of these metabolite combinations for predicting EOC recurrence was 0.897. In terms of clinical applicability, LysoPG(20:5) arose as a potential EOC recurrence predictive biomarker to increase the predictive power of clinical predictors from AUC value 0.739 to 0.875. Additionally, we still found that individuals with early relapses (< 6 months) had a distinctive metabolomic pattern compared with late EOC and non-EOC recurrence subjects. Interestingly, decreased levels of triglycerides (TGs) were found to be a specific metabolic feature foreshadowing an early relapse. In conclusion, plasma lipidomics study could be used for predicting EOC recurrences, as well as early and late recurrent cases. The lipid biomarker research improves the predictive power of clinical predictors and the identified biomarkers are of great prognostic and therapeutic potential. PMID:27564116

Pneumococcal pneumonia - Are the new severity scores more accurate in predicting adverse outcomes?

PubMed

Ribeiro, C; Ladeira, I; Gaio, A R; Brito, M C

2013-01-01

The site-of-care decision is one of the most important factors in the management of patients with community-acquired pneumonia. The severity scores are validated prognostic tools for community-acquired pneumonia mortality and treatment site decision. The aim of this paper was to compare the discriminatory power of four scores - the classic PSI and CURB65 ant the most recent SCAP and SMART-COP - in predicting major adverse events: death, ICU admission, need for invasive mechanical ventilation or vasopressor support in patients admitted with pneumococcal pneumonia. A five year retrospective study of patients admitted for pneumococcal pneumonia. Patients were stratified based on admission data and assigned to low-, intermediate-, and high-risk classes for each score. Results were obtained comparing low versus non-low risk classes. We studied 142 episodes of hospitalization with 2 deaths and 10 patients needing mechanical ventilation and vasopressor support. The majority of patients were classified as low risk by all scores - we found high negative predictive values for all adverse events studied, the most negative value corresponding to the SCAP score. The more recent scores showed better accuracy for predicting ICU admission and need for ventilation or vasopressor support (mostly for the SCAP score with higher AUC values for all adverse events). The rate of all adverse outcomes increased directly with increasing risk class in all scores. The new gravity scores appear to have a higher discriminatory power in all adverse events in our study, particularly, the SCAP score. Copyright © 2012 Sociedade Portuguesa de Pneumologia. Published by Elsevier España. All rights reserved.

Lessons Learned from the Wide Field Camera 3 Flight Correlation

NASA Technical Reports Server (NTRS)

Peabody, Hume L.; Stavely, Richard A.; Townsend, Jackie; Abel, Josh; Mandi, Joe; Bast, William

2010-01-01

The Wide Field Camera 3 (WFC3) instrument was installed into the Hubble Space Telescope (HST) as part of the activities for STS (Space Transportation System)-125 (HST Servicing Mission 4). Initial model predictions for power and radiator temperature were not in good agreement with flight data during a relatively hot, stable period, with the flight power and temperatures being significantly higher than predictions. Significant efforts were undertaken to identify the causes of the discrepancies and to resolve the flight model correlation problems as the thermal vacuum test correlation indicated good agreement. The WFC3 thermal design performance has proven difficult to accurately predict, since the power dissipation on the radiator typically increases as the radiator temperature increases, due to a Thermo Electric Cooler (TEC) attached to the this radiator. This self beating continues until the radiative emissive capability is met for a given temperature, and only then does the system find a quasi-steady regime. Various other factors may also contribute to the radiator temperature, such as backloadlng from the observatory itself and the planet, local high-absorptivity regions near fasteners/holes, and temperature varying parasitic heat leaks from the instrument itself to the radiator. Each of these effects in turn may increase the radiator temperature, and furthermore the demand on the TEC.

Intestinal Fatty Acid Binding Protein as a Marker of Necrosis and Severity in Acute Pancreatitis.

PubMed

Kupčinskas, Juozas; Gedgaudas, Rolandas; Hartman, Hannes; Sippola, Tomi; Lindström, Outi; Johnson, Colin D; Regnér, Sara

2018-07-01

The aim of this study was to study intestinal fatty acid binding protein (i-FABP) as a potential biomarker in predicting severity of acute pancreatitis (AP). In a prospective multicenter cohort study, plasma levels of i-FABP were measured in 402 patients with AP. Severity of AP was determined based on the 1992 Atlanta Classification. Admission levels of plasma i-FABP were significantly higher in patients with pancreatic necrosis, in patients having systemic complications, in patients treated invasively, in patients treated in the intensive care unit, in patients with severe AP, and in deceased patients. Plasma i-FABP levels on admission yielded an area under curve (AUC) of 0.732 in discriminating patients with or without pancreatic necrosis and AUC of 0.669 in predicting severe AP. Combination of levels of i-FABP and venous lactate on the day of admission showed higher discriminative power in severe AP-AUC of 0.808. Higher i-FABP levels on admission were associated with pancreatic necrosis, systemic complications, and severe AP. Low levels of i-FABP had a high negative predictive value for pancreatic necrosis and severe AP. Combination of levels of i-FABP and venous lactates on admission were superior to either of markers used alone in predicting severe AP.

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

SU-F-J-218: Predicting Radiation-Induced Xerostomia by Dosimetrically Accounting for Daily Setup Uncertainty During Head and Neck IMRT

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

Park, S; Quon, H; McNutt, T

2016-06-15

Purpose: To determine if the accumulated parotid dosimetry using planning CT to daily CBCT deformation and dose re-calculation can predict for radiation-induced xerostomia. Methods: To track and dosimetrically account for the effects of anatomical changes on the parotid glands, we propagated physicians’ contours from planning CT to daily CBCT using a deformable registration with iterative CBCT intensity correction. A surface mesh for each OAR was created with the deformation applied to the mesh to obtain the deformed parotid volumes. Daily dose was computed on the deformed CT and accumulated to the last fraction. For both the accumulated and the plannedmore » parotid dosimetry, we tested the prediction power of different dosimetric parameters including D90, D50, D10, mean, standard deviation, min/max dose to the combined parotids and patient age to severe xerostomia (NCI-CTCAE grade≥2 at 6 mo follow-up). We also tested the dosimetry to parotid sub-volumes. Three classification algorithms, random tree, support vector machine, and logistic regression were tested to predict severe xerostomia using a leave-one-out validation approach. Results: We tested our prediction model on 35 HN IMRT cases. Parameters from the accumulated dosimetry model demonstrated an 89% accuracy for predicting severe xerostomia. Compared to the planning dosimetry, the accumulated dose consistently demonstrated higher prediction power with all three classification algorithms, including 11%, 5% and 30% higher accuracy, sensitivity and specificity, respectively. Geometric division of the combined parotid glands into superior-inferior regions demonstrated ∼5% increased accuracy than the whole volume. The most influential ranked features include age, mean accumulated dose of the submandibular glands and the accumulated D90 of the superior parotid glands. Conclusion: We demonstrated that the accumulated parotid dosimetry using CT-CBCT registration and dose re-calculation more accurately predicts for severe xerostomia and that the superior portion of the parotid glands may be particularly important in predicting for severe xerostomia. This work was supported in part by NIH/NCI under grant R42CA137886 and in part by Toshiba big data research project funds.« less

Comparison of Parallel and Series Hybrid Power Trains for Transit Bus Applications

DOE PAGES

Gao, Zhiming; Daw, C. Stuart; Smith, David E.; ...

2016-08-01

The fuel economy and emissions of conventional and hybrid buses equipped with emissions after treatment were evaluated via computational simulation for six representative city bus drive cycles. Both series and parallel configurations for the hybrid case were studied. The simulation results indicated that series hybrid buses have the greatest overall advantage in fuel economy. The series and parallel hybrid buses were predicted to produce similar carbon monoxide and hydrocarbon tailpipe emissions but were also predicted to have reduced tailpipe emissions of nitrogen oxides compared with the conventional bus in higher speed cycles. For the New York bus cycle, which hasmore » the lowest average speed among the cycles evaluated, the series bus tailpipe emissions were somewhat higher than they were for the conventional bus; the parallel hybrid bus had significantly lower tailpipe emissions. All three bus power trains were found to require periodic active diesel particulate filter regeneration to maintain control of particulate matter. Finally, plug-in operation of series hybrid buses appears to offer significant fuel economy benefits and is easily employed because of the relatively large battery capacity that is typical of the series hybrid configuration.« less

Comparison of Parallel and Series Hybrid Power Trains for Transit Bus Applications

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

Gao, Zhiming; Daw, C. Stuart; Smith, David E.

The fuel economy and emissions of conventional and hybrid buses equipped with emissions after treatment were evaluated via computational simulation for six representative city bus drive cycles. Both series and parallel configurations for the hybrid case were studied. The simulation results indicated that series hybrid buses have the greatest overall advantage in fuel economy. The series and parallel hybrid buses were predicted to produce similar carbon monoxide and hydrocarbon tailpipe emissions but were also predicted to have reduced tailpipe emissions of nitrogen oxides compared with the conventional bus in higher speed cycles. For the New York bus cycle, which hasmore » the lowest average speed among the cycles evaluated, the series bus tailpipe emissions were somewhat higher than they were for the conventional bus; the parallel hybrid bus had significantly lower tailpipe emissions. All three bus power trains were found to require periodic active diesel particulate filter regeneration to maintain control of particulate matter. Finally, plug-in operation of series hybrid buses appears to offer significant fuel economy benefits and is easily employed because of the relatively large battery capacity that is typical of the series hybrid configuration.« less

The Technology of Suppressing Harmonics with Complex Neural Network is Applied to Microgrid

NASA Astrophysics Data System (ADS)

Zhang, Jing; Li, Zhan-Ying; Wang, Yan-ping; Li, Yang; Zong, Ke-yong

2018-03-01

According to the traits of harmonics in microgrid, a new CANN controller which combines BP and RBF neural network is proposed to control APF to detect and suppress harmonics. This controller has the function of current prediction. By simulation in Matlab / Simulink, this design can shorten the delay time nearly 0.02s (a power supply current cycle) in comparison with the traditional controller based on ip-iq method. The new controller also has higher compensation accuracy and better dynamic tracking traits, it can greatly suppress the harmonics and improve the power quality.

Addition of 24-Hour Heart Rate Variability Parameters to the Cardiovascular Health Study Stroke Risk Score and Prediction of Incident Stroke: The Cardiovascular Health Study.

PubMed

Bodapati, Rohan K; Kizer, Jorge R; Kop, Willem J; Kamel, Hooman; Stein, Phyllis K

2017-07-21

Heart rate variability (HRV) characterizes cardiac autonomic functioning. The association of HRV with stroke is uncertain. We examined whether 24-hour HRV added predictive value to the Cardiovascular Health Study clinical stroke risk score (CHS-SCORE), previously developed at the baseline examination. N=884 stroke-free CHS participants (age 75.3±4.6), with 24-hour Holters adequate for HRV analysis at the 1994-1995 examination, had 68 strokes over ≤8 year follow-up (median 7.3 [interquartile range 7.1-7.6] years). The value of adding HRV to the CHS-SCORE was assessed with stepwise Cox regression analysis. The CHS-SCORE predicted incident stroke (HR=1.06 per unit increment, P =0.005). Two HRV parameters, decreased coefficient of variance of NN intervals (CV%, P =0.031) and decreased power law slope (SLOPE, P =0.033) also entered the model, but these did not significantly improve the c-statistic ( P =0.47). In a secondary analysis, dichotomization of CV% (LOWCV% ≤12.8%) was found to maximally stratify higher-risk participants after adjustment for CHS-SCORE. Similarly, dichotomizing SLOPE (LOWSLOPE <-1.4) maximally stratified higher-risk participants. When these HRV categories were combined (eg, HIGHCV% with HIGHSLOPE), the c-statistic for the model with the CHS-SCORE and combined HRV categories was 0.68, significantly higher than 0.61 for the CHS-SCORE alone ( P =0.02). In this sample of older adults, 2 HRV parameters, CV% and power law slope, emerged as significantly associated with incident stroke when added to a validated clinical risk score. After each parameter was dichotomized based on its optimal cut point in this sample, their composite significantly improved prediction of incident stroke during ≤8-year follow-up. These findings will require validation in separate, larger cohorts. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Effect of African- and European-American maternal attitudes and limit-setting strategies on children's self-regulation.

PubMed

LeCuyer, Elizabeth A; Swanson, Dena P; Cole, Robert; Kitzman, Harriet

2011-12-01

The effect of maternal attitudes and limit-setting strategies on children's self-regulation (measured as committed compliance) was compared in 151 African-American (AA) and 108 European-American (EA) mothers and their 3-year-old children. There were no ethnic differences in children's compliance, however ethnicity moderated the relationship between maternal authoritarian attitudes and children's compliance. Higher authoritarian attitudes predicted less children's compliance in the EA sample, but greater compliance in the AA sample. Observational limit-setting data revealed that in both ethnic groups, maternal authoritarian attitudes influenced children's self-regulation through maternal use of lower-power (gentle) verbal strategies, fewer physical strategies, and judicious use of higher-power verbal strategies. The findings indicate that the meaning and purpose of authoritarian attitudes varies across these mothers' socio-cultural contexts. Copyright © 2011 Wiley Periodicals, Inc.

Ionosphere/microwave beam interaction study

NASA Technical Reports Server (NTRS)

Gordon, W. E.; Duncan, L. M.

1978-01-01

The microwave beam of the Solar Power Satellite (SPS) is predicted to interact with the ionosphere producing thermal runaway up to an altitude of about 100 kilometers at a power density threshold of 12 mW/cm sq (within a factor of two). The operation of the SPS at two frequencies, 2450 and 5800 MHz, is compared. The ionosphere interaction is less at the higher frequency, but the tropospheric problem scattering from heavy rain and hail is worse at the higher frequency. Microwave signals from communication satellites were observed to scintillate, but there is some concern that the uplink pilot signal may be distorted by the SPS heated ionosphere. The microwave scintillations are only observed in the tropics in the early evenings near the equinoxes. Results indicate that large phase errors in the uplink pilot signal can be reduced.

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)

Spin Dependence of η Meson Production in Proton-Proton Collisions Close to Threshold.

PubMed

Adlarson, P; Augustyniak, W; Bardan, W; Bashkanov, M; Bass, S D; Bergmann, F S; Berłowski, M; Bondar, A; Büscher, M; Calén, H; Ciepał, I; Clement, H; Czerwiński, E; Demmich, K; Engels, R; Erven, A; Erven, W; Eyrich, W; Fedorets, P; Föhl, K; Fransson, K; Goldenbaum, F; Goswami, A; Grigoryev, K; Gullström, C-O; Heijkenskjöld, L; Hejny, V; Hüsken, N; Jarczyk, L; Johansson, T; Kamys, B; Kemmerling, G; Khatri, G; Khoukaz, A; Khreptak, O; Kirillov, D A; Kistryn, S; Kleines, H; Kłos, B; Krzemień, W; Kulessa, P; Kupść, A; Kuzmin, A; Lalwani, K; Lersch, D; Lorentz, B; Magiera, A; Maier, R; Marciniewski, P; Mariański, B; Morsch, H-P; Moskal, P; Ohm, H; Parol, W; Perez Del Rio, E; Piskunov, N M; Prasuhn, D; Pszczel, D; Pysz, K; Pyszniak, A; Ritman, J; Roy, A; Rudy, Z; Rundel, O; Sawant, S; Schadmand, S; Schätti-Ozerianska, I; Sefzick, T; Serdyuk, V; Shwartz, B; Sitterberg, K; Skorodko, T; Skurzok, M; Smyrski, J; Sopov, V; Stassen, R; Stepaniak, J; Stephan, E; Sterzenbach, G; Stockhorst, H; Ströher, H; Szczurek, A; Trzciński, A; Wolke, M; Wrońska, A; Wüstner, P; Yamamoto, A; Zabierowski, J; Zieliński, M J; Złomańczuk, J; Żuprański, P; Żurek, M

2018-01-12

Taking advantage of the high acceptance and axial symmetry of the WASA-at-COSY detector, and the high polarization degree of the proton beam of COSY, the reaction p[over →]p→ppη has been measured close to threshold to explore the analyzing power A_{y}. The angular distribution of A_{y} is determined with the precision improved by more than 1 order of magnitude with respect to previous results, allowing a first accurate comparison with theoretical predictions. The determined analyzing power is consistent with zero for an excess energy of Q=15  MeV, signaling s-wave production with no evidence for higher partial waves. At Q=72  MeV the data reveal strong interference of Ps and Pp partial waves and cancellation of (Pp)^{2} and Ss^{*}Sd contributions. These results rule out the presently available theoretical predictions for the production mechanism of the η meson.

Keep it simple? Predicting primary health care costs with clinical morbidity measures

PubMed Central

Brilleman, Samuel L.; Gravelle, Hugh; Hollinghurst, Sandra; Purdy, Sarah; Salisbury, Chris; Windmeijer, Frank

2014-01-01

Models of the determinants of individuals’ primary care costs can be used to set capitation payments to providers and to test for horizontal equity. We compare the ability of eight measures of patient morbidity and multimorbidity to predict future primary care costs and examine capitation payments based on them. The measures were derived from four morbidity descriptive systems: 17 chronic diseases in the Quality and Outcomes Framework (QOF); 17 chronic diseases in the Charlson scheme; 114 Expanded Diagnosis Clusters (EDCs); and 68 Adjusted Clinical Groups (ACGs). These were applied to patient records of 86,100 individuals in 174 English practices. For a given disease description system, counts of diseases and sets of disease dummy variables had similar explanatory power. The EDC measures performed best followed by the QOF and ACG measures. The Charlson measures had the worst performance but still improved markedly on models containing only age, gender, deprivation and practice effects. Comparisons of predictive power for different morbidity measures were similar for linear and exponential models, but the relative predictive power of the models varied with the morbidity measure. Capitation payments for an individual patient vary considerably with the different morbidity measures included in the cost model. Even for the best fitting model large differences between expected cost and capitation for some types of patient suggest incentives for patient selection. Models with any of the morbidity measures show higher cost for more deprived patients but the positive effect of deprivation on cost was smaller in better fitting models. PMID:24657375

Prediction of cold and heat patterns using anthropometric measures based on machine learning.

PubMed

Lee, Bum Ju; Lee, Jae Chul; Nam, Jiho; Kim, Jong Yeol

2018-01-01

To examine the association of body shape with cold and heat patterns, to determine which anthropometric measure is the best indicator for discriminating between the two patterns, and to investigate whether using a combination of measures can improve the predictive power to diagnose these patterns. Based on a total of 4,859 subjects (3,000 women and 1,859 men), statistical analyses using binary logistic regression were performed to assess the significance of the difference and the predictive power of each anthropometric measure, and binary logistic regression and Naive Bayes with the variable selection technique were used to assess the improvement in the predictive power of the patterns using the combined measures. In women, the strongest indicators for determining the cold and heat patterns among anthropometric measures were body mass index (BMI) and rib circumference; in men, the best indicator was BMI. In experiments using a combination of measures, the values of the area under the receiver operating characteristic curve in women were 0.776 by Naive Bayes and 0.772 by logistic regression, and the values in men were 0.788 by Naive Bayes and 0.779 by logistic regression. Individuals with a higher BMI have a tendency toward a heat pattern in both women and men. The use of a combination of anthropometric measures can slightly improve the diagnostic accuracy. Our findings can provide fundamental information for the diagnosis of cold and heat patterns based on body shape for personalized medicine.

Artificial neural network approach to predict surgical site infection after free-flap reconstruction in patients receiving surgery for head and neck cancer.

PubMed

Kuo, Pao-Jen; Wu, Shao-Chun; Chien, Peng-Chen; Chang, Shu-Shya; Rau, Cheng-Shyuan; Tai, Hsueh-Ling; Peng, Shu-Hui; Lin, Yi-Chun; Chen, Yi-Chun; Hsieh, Hsiao-Yun; Hsieh, Ching-Hua

2018-03-02

The aim of this study was to develop an effective surgical site infection (SSI) prediction model in patients receiving free-flap reconstruction after surgery for head and neck cancer using artificial neural network (ANN), and to compare its predictive power with that of conventional logistic regression (LR). There were 1,836 patients with 1,854 free-flap reconstructions and 438 postoperative SSIs in the dataset for analysis. They were randomly assigned tin ratio of 7:3 into a training set and a test set. Based on comprehensive characteristics of patients and diseases in the absence or presence of operative data, prediction of SSI was performed at two time points (pre-operatively and post-operatively) with a feed-forward ANN and the LR models. In addition to the calculated accuracy, sensitivity, and specificity, the predictive performance of ANN and LR were assessed based on area under the curve (AUC) measures of receiver operator characteristic curves and Brier score. ANN had a significantly higher AUC (0.892) of post-operative prediction and AUC (0.808) of pre-operative prediction than LR (both P <0.0001). In addition, there was significant higher AUC of post-operative prediction than pre-operative prediction by ANN (p<0.0001). With the highest AUC and the lowest Brier score (0.090), the post-operative prediction by ANN had the highest overall predictive performance. The post-operative prediction by ANN had the highest overall performance in predicting SSI after free-flap reconstruction in patients receiving surgery for head and neck cancer.

Can human experts predict solubility better than computers?

PubMed

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

2017-12-13

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

The Zeldovich & Adhesion approximations and applications to the local universe

NASA Astrophysics Data System (ADS)

Hidding, Johan; van de Weygaert, Rien; Shandarin, Sergei

2016-10-01

The Zeldovich approximation (ZA) predicts the formation of a web of singularities. While these singularities may only exist in the most formal interpretation of the ZA, they provide a powerful tool for the analysis of initial conditions. We present a novel method to find the skeleton of the resulting cosmic web based on singularities in the primordial deformation tensor and its higher order derivatives. We show that the A 3 lines predict the formation of filaments in a two-dimensional model. We continue with applications of the adhesion model to visualise structures in the local (z < 0.03) universe.

Coexistence of collapse and stable spatiotemporal solitons in multimode fibers

NASA Astrophysics Data System (ADS)

Shtyrina, Olga V.; Fedoruk, Mikhail P.; Kivshar, Yuri S.; Turitsyn, Sergei K.

2018-01-01

We analyze spatiotemporal solitons in multimode optical fibers and demonstrate the existence of stable solitons, in a sharp contrast to earlier predictions of collapse of multidimensional solitons in three-dimensional media. We discuss the coexistence of blow-up solutions and collapse stabilization by a low-dimensional external potential in graded-index media, and also predict the existence of stable higher-order nonlinear waves such as dipole-mode spatiotemporal solitons. To support the main conclusions of our numerical studies we employ a variational approach and derive analytically the stability criterion for input powers for the collapse stabilization.

Spin-lattice relaxation and the calculation of gain, pump power, and noise temperature in ruby

NASA Technical Reports Server (NTRS)

Lyons, J. R.

1989-01-01

The use of a quantitative analysis of the dominant source of relaxation in ruby spin systems to make predictions of key maser amplifier parameters is described. The spin-lattice Hamiltonian which describes the interaction of the electron spins with the thermal vibrations of the surrounding lattice is obtained from the literature. Taking into account the vibrational anisotropy of ruby, Fermi's rule is used to calculate the spin transition rates between the maser energy levels. The spin population rate equations are solved for the spin transition relaxation times, and a comparison with previous calculations is made. Predictions of ruby gain, inversion ratio, and noise temperature as a function of physical temperature are made for 8.4-GHz and 32-GHz maser pumping schemes. The theory predicts that ruby oriented at 90 deg will have approximately 50 percent higher gain in dB and slightly lower noise temperature than a 54.7-deg ruby at 32 GHz (assuming pump saturation). A specific calculation relating pump power to inversion ratio is given for a single channel of the 32-GHz reflected wave maser.

Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks

PubMed Central

Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E.; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A.; Kellis, Manolis

2012-01-01

Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein–protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level. PMID:22456606

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

Hoke, Anderson; Shirazi, Mariko; Chakraborty, Sudipta

As deployment of power electronic coupled generation such as photovoltaic (PV) systems increases, grid operators have shown increasing interest in calling on inverter-coupled generation to help mitigate frequency contingency events by rapidly surging active power into the grid. When responding to contingency events, the faster the active power is provided, the more effective it may be for arresting the frequency event. This paper proposes a predictive PV inverter control method for very fast and accurate control of active power. This rapid active power control method will increase the effectiveness of various higher-level controls designed to mitigate grid frequency contingency events,more » including fast power-frequency droop, inertia emulation, and fast frequency response, without the need for energy storage. The rapid active power control method, coupled with a maximum power point estimation method, is implemented in a prototype PV inverter connected to a PV array. The prototype inverter's response to various frequency events is experimentally confirmed to be fast (beginning within 2 line cycles and completing within 4.5 line cycles of a severe test event) and accurate (below 2% steady-state error).« less

Groundwater nitrate contamination: Factors and indicators

PubMed Central

Wick, Katharina; Heumesser, Christine; Schmid, Erwin

2012-01-01

Identifying significant determinants of groundwater nitrate contamination is critical in order to define sensible agri-environmental indicators that support the design, enforcement, and monitoring of regulatory policies. We use data from approximately 1200 Austrian municipalities to provide a detailed statistical analysis of (1) the factors influencing groundwater nitrate contamination and (2) the predictive capacity of the Gross Nitrogen Balance, one of the most commonly used agri-environmental indicators. We find that the percentage of cropland in a given region correlates positively with nitrate concentration in groundwater. Additionally, environmental characteristics such as temperature and precipitation are important co-factors. Higher average temperatures result in lower nitrate contamination of groundwater, possibly due to increased evapotranspiration. Higher average precipitation dilutes nitrates in the soil, further reducing groundwater nitrate concentration. Finally, we assess whether the Gross Nitrogen Balance is a valid predictor of groundwater nitrate contamination. Our regression analysis reveals that the Gross Nitrogen Balance is a statistically significant predictor for nitrate contamination. We also show that its predictive power can be improved if we account for average regional precipitation. The Gross Nitrogen Balance predicts nitrate contamination in groundwater more precisely in regions with higher average precipitation. PMID:22906701

Resting-state sensorimotor rhythm (SMR) power predicts the ability to up-regulate SMR in an EEG-instrumental conditioning paradigm.

PubMed

Reichert, Johanna Louise; Kober, Silvia Erika; Neuper, Christa; Wood, Guilherme

2015-11-01

Instrumental conditioning of EEG activity (EEG-IC) is a promising method for improvement and rehabilitation of cognitive functions. However, it has been found that even healthy adults are not always able to learn how to regulate their brain activity during EEG-IC. In the present study, the role of a neurophysiological predictor of EEG-IC learning performance, the resting-state power of sensorimotor rhythm (rs-SMR, 12-15Hz), was investigated. Eyes-open and eyes-closed rs-SMR power was assessed before N=28 healthy adults underwent 10 training sessions of instrumental SMR conditioning (ISC), in which participants should learn to voluntarily increase their SMR power by means of audio-visual feedback. A control group of N=19 participants received gamma (40-43Hz) or sham EEG-IC. N=19 of the ISC participants could be classified as "responders" as they were able to increase SMR power during training sessions, while N=9 participants ("non-responders") were not able to increase SMR power. Rs-SMR power in responders before start of ISC was higher in widespread parieto-occipital areas than in non-responders. A discriminant analysis indicated that eyes-open rs-SMR power in a central brain region specifically predicted later ISC performance, but not an increase of SMR in the control group. Together, these findings indicate that rs-SMR power is a specific and easy-to-measure predictor of later ISC learning performance. The assessment of factors that influence the ability to regulate brain activity is of high relevance, as it could be used to avoid potentially frustrating and expensive EEG-IC training sessions for participants who have a low chance of success. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

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.

Noninvasive prediction of shunt operation outcome in idiopathic normal pressure hydrocephalus

PubMed Central

Aoki, Yasunori; Kazui, Hiroaki; Tanaka, Toshihisa; Ishii, Ryouhei; Wada, Tamiki; Ikeda, Shunichiro; Hata, Masahiro; Canuet, Leonides; Katsimichas, Themistoklis; Musha, Toshimitsu; Matsuzaki, Haruyasu; Imajo, Kaoru; Kanemoto, Hideki; Yoshida, Tetsuhiko; Nomura, Keiko; Yoshiyama, Kenji; Iwase, Masao; Takeda, Masatoshi

2015-01-01

Idiopathic normal pressure hydrocephalus (iNPH) is a syndrome characterized by gait disturbance, cognitive deterioration and urinary incontinence in elderly individuals. These symptoms can be improved by shunt operation in some but not all patients. Therefore, discovering predictive factors for the surgical outcome is of great clinical importance. We used normalized power variance (NPV) of electroencephalography (EEG) waves, a sensitive measure of the instability of cortical electrical activity, and found significantly higher NPV in beta frequency band at the right fronto-temporo-occipital electrodes (Fp2, T4 and O2) in shunt responders compared to non-responders. By utilizing these differences, we were able to correctly identify responders and non-responders to shunt operation with a positive predictive value of 80% and a negative predictive value of 88%. Our findings indicate that NPV can be useful in noninvasively predicting the clinical outcome of shunt operation in patients with iNPH. PMID:25585705

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.

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

O'Driscoll, M.

Power capacity additions in Asia will at least triple by 2010, and Arthur D. Little Inc. predicts natural gas can pick up a good 15 percent of that market. The study predicts Asia potentially will need 720 gigawatts of new power generation by 2010, of which 15 percent may be gas-based. This represents a market three times the size of the US market in the same period, and would require more than $1 trillion in investment to finance the power generation projects alone. Six forces are driving new market opportunities for natural gas in Asia, and have set the stagemore » for major investments in Asian gas-based power generation. They are: New technologies; growing environmental pressures; privatization; alternative energy pricing; gas availability; and continued economic growth. Japan, South Korea and Taiwan already have large, well-established markets for both gas and power that provide minimal opportunities for foreign investment. But the rest of Asia - specifically, India, Pakistan, the Philippines, Vietnam, Indonesia, Malaysia, the People's Republic of China, Thailand, Bangladesh and Myanmar - is still relatively undeveloped, the study said, and gas is emerging as an energy import substitute or export earner. The study found those countries will turn increased environmental awareness and concern into legislation as their economic prosperity grows, leading to a higher future value for natural gas relative to other fuels. Stricter emissions standards will favor gas over diesel, fuel oil and coal.« less

A New Weighted Injury Severity Scoring System: Better Predictive Power for Pediatric Trauma Mortality.

PubMed

Shi, Junxin; Shen, Jiabin; Caupp, Sarah; Wang, Angela; Nuss, Kathryn E; Kenney, Brian; Wheeler, Krista K; Lu, Bo; Xiang, Henry

2018-05-02

An accurate injury severity measurement is essential for the evaluation of pediatric trauma care and outcome research. The traditional Injury Severity Score (ISS) does not consider the differential risks of the Abbreviated Injury Scale (AIS) from different body regions nor is it pediatric specific. The objective of this study was to develop a weighted injury severity scoring (wISS) system for pediatric blunt trauma patients with better predictive power than ISS. Based on the association between mortality and AIS from each of the six ISS body regions, we generated different weights for the component AIS scores used in the calculation of ISS. The weights and wISS were generated using the National Trauma Data Bank (NTDB). The Nationwide Emergency Department Sample (NEDS) was used to validate our main results. Pediatric blunt trauma patients less than 16 years were included, and mortality was the outcome. Discrimination (areas under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value, concordance) and calibration (Hosmer-Lemeshow statistic) were compared between the wISS and ISS. The areas under the receiver operating characteristic curves from the wISS and ISS are 0.88 vs. 0.86 in ISS=1-74 and 0.77 vs. 0.64 in ISS=25-74 (p<0.0001). The wISS showed higher specificity, positive predictive value, negative predictive value, and concordance when they were compared at similar levels of sensitivity. The wISS had better calibration (smaller Hosmer-Lemeshow statistic) than the ISS (11.6 versus 19.7 for ISS=1-74 and 10.9 versus 12.6 for ISS= 25-74). The wISS showed even better discrimination with the NEDS. By weighting the AIS from different body regions, the wISS had significantly better predictive power for mortality than the ISS, especially in critically injured children.Level of Evidence and study typeLevel IV Prognostic/Epidemiological.

Validation of Kinetic-Turbulent-Neoclassical Theory for Edge Intrinsic Rotation in DIII-D Plasmas

NASA Astrophysics Data System (ADS)

Ashourvan, Arash

2017-10-01

Recent experiments on DIII-D with low-torque neutral beam injection (NBI) have provided a validation of a new model of momentum generation in a wide range of conditions spanning L- and H-mode with direct ion and electron heating. A challenge in predicting the bulk rotation profile for ITER has been to capture the physics of momentum transport near the separatrix and steep gradient region. A recent theory has presented a model for edge momentum transport which predicts the value and direction of the main-ion intrinsic velocity at the pedestal-top, generated by the passing orbits in the inhomogeneous turbulent field. In this study, this model-predicted velocity is tested on DIII-D for a database of 44 low-torque NBI discharges comprised of bothL- and H-mode plasmas. For moderate NBI powers (PNBI<4 MW), model prediction agrees well with the experiments for both L- and H-mode. At higher NBI power the experimental rotation is observed to saturate and even degrade compared to theory. TRANSP-NUBEAM simulations performed for the database show that for discharges with nominally balanced - but high powered - NBI, the net injected torque through the edge can exceed 1 N.m in the counter-current direction. The theory model has been extended to compute the rotation degradation from this counter-current NBI torque by solving a reduced momentum evolution equation for the edge and found the revised velocity prediction to be in agreement with experiment. Projecting to the ITER baseline scenario, this model predicts a value for the pedestal-top rotation (ρ 0.9) comparable to 4 kRad/s. Using the theory modeled - and now tested - velocity to predict the bulk plasma rotation opens up a path to more confidently projecting the confinement and stability in ITER. Supported by the US DOE under DE-AC02-09CH11466 and DE-FC02-04ER54698.

Using the weighted area under the net benefit curve for decision curve analysis.

PubMed

Talluri, Rajesh; Shete, Sanjay

2016-07-18

Risk prediction models have been proposed for various diseases and are being improved as new predictors are identified. A major challenge is to determine whether the newly discovered predictors improve risk prediction. Decision curve analysis has been proposed as an alternative to the area under the curve and net reclassification index to evaluate the performance of prediction models in clinical scenarios. The decision curve computed using the net benefit can evaluate the predictive performance of risk models at a given or range of threshold probabilities. However, when the decision curves for 2 competing models cross in the range of interest, it is difficult to identify the best model as there is no readily available summary measure for evaluating the predictive performance. The key deterrent for using simple measures such as the area under the net benefit curve is the assumption that the threshold probabilities are uniformly distributed among patients. We propose a novel measure for performing decision curve analysis. The approach estimates the distribution of threshold probabilities without the need of additional data. Using the estimated distribution of threshold probabilities, the weighted area under the net benefit curve serves as the summary measure to compare risk prediction models in a range of interest. We compared 3 different approaches, the standard method, the area under the net benefit curve, and the weighted area under the net benefit curve. Type 1 error and power comparisons demonstrate that the weighted area under the net benefit curve has higher power compared to the other methods. Several simulation studies are presented to demonstrate the improvement in model comparison using the weighted area under the net benefit curve compared to the standard method. The proposed measure improves decision curve analysis by using the weighted area under the curve and thereby improves the power of the decision curve analysis to compare risk prediction models in a clinical scenario.

High-power piezoelectric acoustic-electric power feedthru for metal walls

NASA Astrophysics Data System (ADS)

Bao, Xiaoqi; Biederman, Will; Sherrit, Stewart; Badescu, Mircea; Bar-Cohen, Yoseph; Jones, Christopher; Aldrich, Jack; Chang, Zensheu

2008-03-01

Piezoelectric acoustic-electric power feed-through devices transfer electric power wirelessly through a solid wall using elastic waves. This approach allows for the elimination of the need for holes through structures for cabling or electrical feed-thrus . The technology supplies power to electric equipment inside sealed containers, vacuum or pressure vessels, etc where holes in the wall are prohibitive or may result in significant performance degradation or requires complex designs. In the our previous work, 100-W of electric power was transferred through a metal wall by a small, piezoelectric device with a simple-structure. To meet requirements of higher power applications, the feasibility to transfer kilowatts level power was investigated. Pre-stressed longitudinal piezoelectric feed-thru devices were analyzed by finite element modeling. An equivalent circuit model was developed to predict the characteristics of power transfer to different electric loads. Based on the analytical results, a prototype device was designed, fabricated and successfully demonstrated to transfer electric power at a level of 1-kW. Methods of minimizing plate wave excitation on the wall were also analyzed. Both model analysis and experimental results are presented in detail in this paper.

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

Small wind turbine performance evaluation using field test data and a coupled aero-electro-mechanical model

NASA Astrophysics Data System (ADS)

Wallace, Brian D.

A series of field tests and theoretical analyses were performed on various wind turbine rotor designs at two Penn State residential-scale wind-electric facilities. This work involved the prediction and experimental measurement of the electrical and aerodynamic performance of three wind turbines; a 3 kW rated Whisper 175, 2.4 kW rated Skystream 3.7, and the Penn State designed Carolus wind turbine. Both the Skystream and Whisper 175 wind turbines are OEM blades which were originally installed at the facilities. The Carolus rotor is a carbon-fiber composite 2-bladed machine, designed and assembled at Penn State, with the intent of replacing the Whisper 175 rotor at the off-grid system. Rotor aerodynamic performance is modeled using WT_Perf, a National Renewable Energy Laboratory developed Blade Element Momentum theory based performance prediction code. Steady-state power curves are predicted by coupling experimentally determined electrical characteristics with the aerodynamic performance of the rotor simulated with WT_Perf. A dynamometer test stand is used to establish the electromechanical efficiencies of the wind-electric system generator. Through the coupling of WT_Perf and dynamometer test results, an aero-electro-mechanical analysis procedure is developed and provides accurate predictions of wind system performance. The analysis of three different wind turbines gives a comprehensive assessment of the capability of the field test facilities and the accuracy of aero-electro-mechanical analysis procedures. Results from this study show that the Carolus and Whisper 175 rotors are running at higher tip-speed ratios than are optimum for power production. The aero-electro-mechanical analysis predicted the high operating tip-speed ratios of the rotors and was accurate at predicting output power for the systems. It is shown that the wind turbines operate at high tip-speeds because of a miss-match between the aerodynamic drive torque and the operating torque of the wind-system generator. Through the change of load impedance on the wind generator, the research facility has the ability to modify the rotational speed of the wind turbines, allowing the rotors to perform closer to their optimum tip-speed. Comparisons between field test data and performance predictions show that the aero-electro-mechanical analysis was able to predict differences in power production and rotational speed which result from changes in the system load impedance.

Implications of Atmospheric Test Fallout Data for Nuclear Winter.

NASA Astrophysics Data System (ADS)

Baker, George Harold, III

1987-09-01

Atmospheric test fallout data have been used to determine admissable dust particle size distributions for nuclear winter studies. The research was originally motivated by extreme differences noted in the magnitude and longevity of dust effects predicted by particle size distributions routinely used in fallout predictions versus those used for nuclear winter studies. Three different sets of historical data have been analyzed: (1) Stratospheric burden of Strontium -90 and Tungsten-185, 1954-1967 (92 contributing events); (2) Continental U.S. Strontium-90 fallout through 1958 (75 contributing events); (3) Local Fallout from selected Nevada tests (16 events). The contribution of dust to possible long term climate effects following a nuclear exchange depends strongly on the particle size distribution. The distribution affects both the atmospheric residence time and optical depth. One dimensional models of stratospheric/tropospheric fallout removal were developed and used to identify optimum particle distributions. Results indicate that particle distributions which properly predict bulk stratospheric activity transfer tend to be somewhat smaller than number size distributions used in initial nuclear winter studies. In addition, both ^{90}Sr and ^ {185}W fallout behavior is better predicted by the lognormal distribution function than the prevalent power law hybrid function. It is shown that the power law behavior of particle samples may well be an aberration of gravitational cloud stratification. Results support the possible existence of two independent particle size distributions in clouds generated by surface or near surface bursts. One distribution governs late time stratospheric fallout, the other governs early time fallout. A bimodal lognormal distribution is proposed to describe the cloud particle population. The distribution predicts higher initial sunlight attenuation and lower late time attenuation than the power law hybrid function used in initial nuclear winter studies.

Nitrogen oxides emissions from thermal power plants in china: current status and future predictions.

PubMed

Tian, Hezhong; Liu, Kaiyun; Hao, Jiming; Wang, Yan; Gao, Jiajia; Qiu, Peipei; Zhu, Chuanyong

2013-10-01

Increasing emissions of nitrogen oxides (NOx) over the Chinese mainland have been of great concern due to their adverse impacts on regional air quality and public health. To explore and obtain the temporal and spatial characteristics of NOx emissions from thermal power plants in China, a unit-based method is developed. The method assesses NOx emissions based on detailed information on unit capacity, boiler and burner patterns, feed fuel types, emission control technologies, and geographical locations. The national total NOx emissions in 2010 are estimated at 7801.6 kt, of which 5495.8 kt is released from coal-fired power plant units of considerable size between 300 and 1000 MW. The top provincial emitter is Shandong where plants are densely concentrated. The average NOx-intensity is estimated at 2.28 g/kWh, markedly higher than that of developed countries, mainly owing to the inadequate application of high-efficiency denitrification devices such as selective catalytic reduction (SCR). Future NOx emissions are predicted by applying scenario analysis, indicating that a reduction of about 40% by the year 2020 can be achieved compared with emissions in 2010. These results suggest that NOx emissions from Chinese thermal power plants could be substantially mitigated within 10 years if reasonable control measures were implemented effectively.

Environmental Loss Characterization of an Advanced Stirling Convertor (ASC-E2) Insulation Package Using a Mock Heater Head

NASA Technical Reports Server (NTRS)

Schifer, Nicholas A.; Briggs, Maxwell H.

2012-01-01

The U.S. Department of Energy (DOE) and Lockheed Martin Space Systems Company (LMSSC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. This generator would use two highefficiency Advanced Stirling Convertors (ASCs), developed by Sunpower Inc. and NASA Glenn Research Center (GRC). As part of ground testing of these ASCs, different operating conditions are used to simulate expected mission conditions. These conditions require achieving a specified electrical power output for a given net heat input. While electrical power output can be precisely quantified, thermal power input to the Stirling cycle cannot be directly measured. In an effort to improve net heat input predictions, the Mock Heater Head was developed with the same relative thermal paths as a convertor using a conducting rod to represent the Stirling cycle and tested to provide a direct comparison to numerical and empirical models used to predict convertor net heat input. The Mock Heater Head also served as the pathfinder for a higher fidelity version of validation test hardware, known as the Thermal Standard. This paper describes how the Mock Heater Head was tested and utilized to validate a process for the Thermal Standard.

Integrated CFD modeling of gas turbine combustors

NASA Technical Reports Server (NTRS)

Fuller, E. J.; Smith, C. E.

1993-01-01

3D, curvilinear, multi-domain CFD analysis is becoming a valuable tool in gas turbine combustor design. Used as a supplement to experimental testing. CFD analysis can provide improved understanding of combustor aerodynamics and used to qualitatively assess new combustor designs. This paper discusses recent advancements in CFD combustor methodology, including the timely integration of the design (i.e. CAD) and analysis (i.e. CFD) processes. Allied Signal's F124 combustor was analyzed at maximum power conditions. The assumption of turbulence levels at the nozzle/swirler inlet was shown to be very important in the prediction of combustor exit temperatures. Predicted exit temperatures were compared to experimental rake data, and good overall agreement was seen. Exit radial temperature profiles were well predicted, while the predicted pattern factor was 25 percent higher than the harmonic-averaged experimental pattern factor.

Effects of porous films on the light reflectivity of pigmentary titanium dioxide particles

NASA Astrophysics Data System (ADS)

Liang, Yong; Qiao, Bing; Wang, Tig-Jie; Gao, Han; Yu, Keyi

2016-11-01

The light reflectivity of the film-coated titanium dioxide particles (TiO2) as a function of the film refractive index was derived and calculated using a plane film model. For the refractive index in the range of 1.00-2.15, the lower the film refractive index is, the higher is the light reflectivity of the film. It is inferred that the lower apparent refractive index of the porous film resulted in the higher reflectivity of light, i.e., the higher hiding power of the titanium dioxide particles. A dense film coating on TiO2 particles with different types of oxides, i.e., SiO2, Al2O3, MgO, ZnO, ZrO2, TiO2, corresponding to different refractive indices of the film from 1.46 to 2.50, was achieved, and the effects of refractive index on the hiding power from the model prediction were confirmed. Porous film coating of TiO2 particles was achieved by adding the organic template agent triethanolamine (TEA). The hiding power of the coated TiO2 particles was increased from 88.3 to 90.8 by adding the TEA template to the film coating (5-20 wt%). In other words, the amount of titanium dioxide needed was reduced by approximately 10% without a change in the hiding power. It is concluded that the film structure coated on TiO2 particle surface affects the light reflectivity significantly, namely, the porous film exhibits excellent performance for pigmentary titanium dioxide particles with high hiding power.

RECONCILING AGN-STAR FORMATION, THE SOLTAN ARGUMENT, AND MEIER’S PARADOX

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

Garofalo, David; Kim, Matthew I.; Christian, Damian J.

2016-02-01

We provide a theoretical context for understanding the recent work of Kalfountzou et al. showing that star formation is enhanced at lower optical luminosity in radio-loud quasars. Our proposal for coupling the assumption of collimated FRII quasar-jet-induced star formation with lower accretion optical luminosity also explains the observed jet power peak in active galaxies at higher redshift compared to the peak in accretion power, doing so in a way that predicts the existence of a family of radio-quiet active galactic nuclei associated with rapidly spinning supermassive black holes at low redshift, as mounting observations suggest. The relevance of this work liesmore » in its promise to explain the observed cosmological evolution of accretion power, jet power, and star formation in a way that is both compatible with the Soltan argument and resolves the so-called “Meier Paradox.”.« less

The role of short-time intensity and envelope power for speech intelligibility and psychoacoustic masking.

PubMed

Biberger, Thomas; Ewert, Stephan D

2017-08-01

The generalized power spectrum model [GPSM; Biberger and Ewert (2016). J. Acoust. Soc. Am. 140, 1023-1038], combining the "classical" concept of the power-spectrum model (PSM) and the envelope power spectrum-model (EPSM), was demonstrated to account for several psychoacoustic and speech intelligibility (SI) experiments. The PSM path of the model uses long-time power signal-to-noise ratios (SNRs), while the EPSM path uses short-time envelope power SNRs. A systematic comparison of existing SI models for several spectro-temporal manipulations of speech maskers and gender combinations of target and masker speakers [Schubotz et al. (2016). J. Acoust. Soc. Am. 140, 524-540] showed the importance of short-time power features. Conversely, Jørgensen et al. [(2013). J. Acoust. Soc. Am. 134, 436-446] demonstrated a higher predictive power of short-time envelope power SNRs than power SNRs using reverberation and spectral subtraction. Here the GPSM was extended to utilize short-time power SNRs and was shown to account for all psychoacoustic and SI data of the three mentioned studies. The best processing strategy was to exclusively use either power or envelope-power SNRs, depending on the experimental task. By analyzing both domains, the suggested model might provide a useful tool for clarifying the contribution of amplitude modulation masking and energetic masking.

Analytical approach to the multi-state lasing phenomenon in quantum dot lasers

NASA Astrophysics Data System (ADS)

Korenev, V. V.; Savelyev, A. V.; Zhukov, A. E.; Omelchenko, A. V.; Maximov, M. V.

2013-03-01

We introduce an analytical approach to describe the multi-state lasing phenomenon in quantum dot lasers. We show that the key parameter is the hole-to-electron capture rate ratio. If it is lower than a certain critical value, the complete quenching of ground-state lasing takes place at high injection levels. At higher values of the ratio, the model predicts saturation of the ground-state power. This explains the diversity of experimental results and their contradiction to the conventional rate equation model. Recently found enhancement of ground-state lasing in p-doped samples and temperature dependence of the ground-state power are also discussed.

Enhanced power factor of higher manganese silicide via melt spin synthesis method

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

Shi, Xiaoya; Li, Qiang, E-mail: liqiang@bnl.gov; Shi, Xun

We report on the thermoelectric properties of the higher manganese silicide MnSi{sub 1.75} synthesized by means of a one-step non-equilibrium method. The ultrahigh cooling rate generated from the melt-spin technique is found to be effective in reducing second phases, which are inevitable during the traditional solid state diffusion processes. Aside from being detrimental to thermoelectric properties, second phases skew the revealing of the intrinsic properties of this class of materials, for example, the optimal level of carrier concentration. With this melt-spin sample, we are able to formulate a simple model based on a single parabolic band that can well describemore » the carrier concentration dependence of the Seebeck coefficient and power factor of the data reported in the literature. An optimal carrier concentration around 5 × 10{sup 20 }cm{sup −3} at 300 K is predicted according to this model. The phase-pure melt-spin sample shows the largest power factor at high temperature, resulting in the highest zT value among the three samples in this paper.« less

Improving accuracy and power with transfer learning using a meta-analytic database.

PubMed

Schwartz, Yannick; Varoquaux, Gaël; Pallier, Christophe; Pinel, Philippe; Poline, Jean-Baptiste; Thirion, Bertrand

2012-01-01

Typical cohorts in brain imaging studies are not large enough for systematic testing of all the information contained in the images. To build testable working hypotheses, investigators thus rely on analysis of previous work, sometimes formalized in a so-called meta-analysis. In brain imaging, this approach underlies the specification of regions of interest (ROIs) that are usually selected on the basis of the coordinates of previously detected effects. In this paper, we propose to use a database of images, rather than coordinates, and frame the problem as transfer learning: learning a discriminant model on a reference task to apply it to a different but related new task. To facilitate statistical analysis of small cohorts, we use a sparse discriminant model that selects predictive voxels on the reference task and thus provides a principled procedure to define ROIs. The benefits of our approach are twofold. First it uses the reference database for prediction, i.e., to provide potential biomarkers in a clinical setting. Second it increases statistical power on the new task. We demonstrate on a set of 18 pairs of functional MRI experimental conditions that our approach gives good prediction. In addition, on a specific transfer situation involving different scanners at different locations, we show that voxel selection based on transfer learning leads to higher detection power on small cohorts.

Migrants, health, and happiness: Evidence that health assessments travel with migrants and predict well-being.

PubMed

Ljunge, Martin

2016-09-01

Health assessments correlate with health outcomes and subjective well-being. Immigrants offer an opportunity to study persistent social influences on health where the social conditions are not endogenous to individual outcomes. This approach provides a clear direction of causality from social conditions to health, and in a second stage to well-being. Natives and immigrants from across the world residing in 30 European countries are studied using survey data. The paper applies within country analysis using both linear regressions and two stage least squares. Natives' and immigrants' individual characteristics have similar predictive power for health, except Muslim immigrants who experience a sizeable health penalty. Average health reports in the immigrant's birth country have a significant association with the immigrant's current health. Almost a quarter of the birth country health variation is brought by the immigrants, while conditioning on socioeconomic characteristics. There is no evidence of the birth country predictive power declining neither as the immigrant spends more time in the residence country nor over the life course. The second stage estimates indicate that a one standard deviation improvement in health predicts higher happiness by 1.72 point or 0.82 of a standard deviation, more than four times the happiness difference of changing employment status from unemployed to employed. Studying life satisfaction yields similar results. Health improvements predict substantial increases in individual happiness. Copyright © 2016 Elsevier B.V. All rights reserved.

Artificial neural network approach to predict surgical site infection after free-flap reconstruction in patients receiving surgery for head and neck cancer

PubMed Central

Kuo, Pao-Jen; Wu, Shao-Chun; Chien, Peng-Chen; Chang, Shu-Shya; Rau, Cheng-Shyuan; Tai, Hsueh-Ling; Peng, Shu-Hui; Lin, Yi-Chun; Chen, Yi-Chun; Hsieh, Hsiao-Yun; Hsieh, Ching-Hua

2018-01-01

Background The aim of this study was to develop an effective surgical site infection (SSI) prediction model in patients receiving free-flap reconstruction after surgery for head and neck cancer using artificial neural network (ANN), and to compare its predictive power with that of conventional logistic regression (LR). Materials and methods There were 1,836 patients with 1,854 free-flap reconstructions and 438 postoperative SSIs in the dataset for analysis. They were randomly assigned tin ratio of 7:3 into a training set and a test set. Based on comprehensive characteristics of patients and diseases in the absence or presence of operative data, prediction of SSI was performed at two time points (pre-operatively and post-operatively) with a feed-forward ANN and the LR models. In addition to the calculated accuracy, sensitivity, and specificity, the predictive performance of ANN and LR were assessed based on area under the curve (AUC) measures of receiver operator characteristic curves and Brier score. Results ANN had a significantly higher AUC (0.892) of post-operative prediction and AUC (0.808) of pre-operative prediction than LR (both P<0.0001). In addition, there was significant higher AUC of post-operative prediction than pre-operative prediction by ANN (p<0.0001). With the highest AUC and the lowest Brier score (0.090), the post-operative prediction by ANN had the highest overall predictive performance. Conclusion The post-operative prediction by ANN had the highest overall performance in predicting SSI after free-flap reconstruction in patients receiving surgery for head and neck cancer. PMID:29568393

Analysis of Factors Affecting the Performance of RLV Thrust Cell Liners

NASA Technical Reports Server (NTRS)

Arnold, Steven M. (Technical Monitor); Butler, Daniel T., Jr.; Pinders, Marek-Jerzy

2004-01-01

The reusable launch vehicle (RLV) thrust cell liner, or thrust chamber, is a critical component of the Space Shuttle Main Engine (SSME). It is designed to operate in some of the most severe conditions seen in engineering practice. This requirement, in conjunction with experimentally observed 'dog-house' failure modes characterized by bulging and thinning of the cooling channel wall, provides the motivation to study the factors that influence RLV thrust cell liner performance. Factors or parameters believed to be directly related to the observed characteristic deformation modes leading to failure under in-service loading conditions are identified, and subsequently investigated using the cylindrical version of the higher-order theory for functionally graded materials in conjunction with the Robinson's unified viscoplasticity theory and the power-law creep model for modeling the response of the liner s constituents. Configurations are analyzed in which specific modifications in cooling channel wall thickness or constituent materials are made to determine the influence of these parameters on the deformations resulting in the observed failure modes in the outer walls of the cooling channel. The application of thermal barrier coatings and functional grading are also investigated within this context. Comparison of the higher-order theory results based on the Robinson and power-law creep model predictions has demonstrated that, using the available material parameters, the power-law creep model predicts more precisely the experimentally observed deformation leading to the 'dog-house' failure mode for multiple short cycles, while also providing much improved computational efficiency. However, for a single long cycle, both models predict virtually identical deformations. Increasing the power-law creep model coefficients produces appreciable deformations after just one long cycle that would normally be obtained after multiple cycles, thereby enhancing the efficiency of the analysis. This provides a basis for the development of an accelerated modeling procedure to further characterize dog-house deformation modes in RLV thrust cell liners. Additionally, the results presented herein have demonstrated that the mechanism responsible for deformation leading to 'dog-house' failure modes is driven by pressure, creep/relaxation and geometric effects.

Sensitivity to Referential Ambiguity in Discourse: The Role of Attention, Working Memory, and Verbal Ability

PubMed Central

Boudewyn, Megan A.; Long, Debra L.; Traxler, Matthew J.; Lesh, Tyler A.; Dave, Shruti; Mangun, George R.; Carter, Cameron S.; Swaab, Tamara Y.

2016-01-01

The establishment of reference is essential to language comprehension. The goal of this study was to examine listeners’ sensitivity to referential ambiguity as a function of individual variation in attention, working memory capacity, and verbal ability. Participants listened to stories in which two entities were introduced that were either very similar (e.g., two oaks) or less similar (e.g., one oak and one elm). The manipulation rendered an anaphor in a subsequent sentence (e.g., oak) ambiguous or unambiguous. EEG was recorded as listeners comprehended the story, after which participants completed tasks to assess working memory, verbal ability, and the ability to use context in task performance. Power in the alpha and theta frequency bands when listeners received critical information about the discourse entities (e.g., oaks) was used to index attention and the involvement of the working memory system in processing the entities. These measures were then used to predict an ERP component that is sensitive to referential ambiguity, the Nref, which was recorded when listeners received the anaphor. Nref amplitude at the anaphor was predicted by alpha power during the earlier critical sentence: Individuals with increased alpha power in ambiguous compared with unambiguous stories were less sensitive to the anaphor's ambiguity. Verbal ability was also predictive of greater sensitivity to referential ambiguity. Finally, increased theta power in the ambiguous compared with unambiguous condition was associated with higher working-memory span. These results highlight the role of attention and working memory in referential processing during listening comprehension. PMID:26401815

Sensitivity to Referential Ambiguity in Discourse: The Role of Attention, Working Memory, and Verbal Ability.

PubMed

Boudewyn, Megan A; Long, Debra L; Traxler, Matthew J; Lesh, Tyler A; Dave, Shruti; Mangun, George R; Carter, Cameron S; Swaab, Tamara Y

2015-12-01

The establishment of reference is essential to language comprehension. The goal of this study was to examine listeners' sensitivity to referential ambiguity as a function of individual variation in attention, working memory capacity, and verbal ability. Participants listened to stories in which two entities were introduced that were either very similar (e.g., two oaks) or less similar (e.g., one oak and one elm). The manipulation rendered an anaphor in a subsequent sentence (e.g., oak) ambiguous or unambiguous. EEG was recorded as listeners comprehended the story, after which participants completed tasks to assess working memory, verbal ability, and the ability to use context in task performance. Power in the alpha and theta frequency bands when listeners received critical information about the discourse entities (e.g., oaks) was used to index attention and the involvement of the working memory system in processing the entities. These measures were then used to predict an ERP component that is sensitive to referential ambiguity, the Nref, which was recorded when listeners received the anaphor. Nref amplitude at the anaphor was predicted by alpha power during the earlier critical sentence: Individuals with increased alpha power in ambiguous compared with unambiguous stories were less sensitive to the anaphor's ambiguity. Verbal ability was also predictive of greater sensitivity to referential ambiguity. Finally, increased theta power in the ambiguous compared with unambiguous condition was associated with higher working-memory span. These results highlight the role of attention and working memory in referential processing during listening comprehension.

Predicting Increased Blood Pressure Using Machine Learning

PubMed Central

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

2014-01-01

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

Predicting increased blood pressure using machine learning.

PubMed

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

2014-01-01

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

Robust predictions for an oscillatory bispectrum in Planck 2015 data from transient reductions in the speed of sound of the inflaton

NASA Astrophysics Data System (ADS)

Torrado, Jesús; Hu, Bin; Achúcarro, Ana

2017-10-01

We update the search for features in the cosmic microwave background (CMB) power spectrum due to transient reductions in the speed of sound, using Planck 2015 CMB temperature and polarization data. We enlarge the parameter space to much higher oscillatory frequencies of the feature, and define a robust prior independent of the ansatz for the reduction, guaranteed to reproduce the assumptions of the theoretical model. This prior exhausts the regime in which features coming from a Gaussian reduction are easily distinguishable from the baseline cosmology. We find a fit to the ℓ≈20 - 40 minus /plus structure in Planck TT power spectrum, as well as features spanning along higher ℓ's (ℓ≈100 - 1500 ). None of those fits is statistically significant, either in terms of their improvement of the likelihood or in terms of the Bayes ratio. For the higher-ℓ ones, their oscillatory frequency (and their amplitude to a lesser extent) is tightly constrained, so they can be considered robust, falsifiable predictions for their correlated features in the CMB bispectrum. We compute said correlated features, and assess their signal to noise and correlation with the secondary bispectrum of the correlation between the gravitational lensing of the CMB and the integrated Sachs-Wolfe effect. We compare our findings to the shape-agnostic oscillatory template tested in Planck 2015, and we comment on some tantalizing coincidences with some of the traits described in Planck's 2015 bispectrum data.

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.

Forced Mixer Nozzle Optimization

NASA Technical Reports Server (NTRS)

Sheoran, Yogi; Hoover, Robert; Schuster, William; Anderson, Morris; Weir, Donald S.

1999-01-01

Computational fluid dynamic (CFD) and computational acoustic analyses (CAA) were performed for a TFE731-40 compound nozzle, a TFE731-60 mixer nozzle and an Energy Efficient Engine (E(sup 3)) mixer nozzle for comparison with available data. The CFD analyses were performed with a three dimensional, Navier-Stokes solution of the flowfield on an unstructured grid using the RAMPANT program. The CAA analyses were performed with the NASA Glenn MGB program using a structured grid. A successful aerodynamic solution for the TFE731-40 compound nozzle operating statically was obtained, simulating an engine operating on a test stand. Analysis of the CFD results of the TFE731-40 with the MGB program produced predicted sound power levels that agree quite well with the measured data front full-scale static engine tests. Comparison of the predicted sound pressure with the data show good agreement near the jet axis, but the noise levels are overpredicted at angles closer to the inlet. The predicted sound power level for the TFE731-60 did not agree as well with measured static engine data as the TFE731-40. Although a reduction in the predicted noise level due to the mixed flow was observed, the reduction was not as significant as the measured data. The analysis of the V2 mixer from the E(sup 3) study showed that peak temperatures predicted in the mixer exit flowfield were within 5 percent of the values measured by the exit probes. The noise predictions of the V2 mixer nozzle tended to be 3-5 dB higher in peak noise level than the measurements. In addition, the maximum frequency of the noise was also overpredicted. An analysis of the 3 candidate mixer nozzle configurations demonstrated the feasibility of using centerbody lobes and porosity to improve mixing efficiency. A final configuration was designed with a predicted thermal mixing efficiency that was 5 percent higher than the 3 candidate mixers. The results of the MGB noise calculations show that the final design will exceed the design goal of a 3 dB reduction in noise as compared to the baseline TFE731-40.

The influence of having a quit date on prediction of smoking cessation outcome.

PubMed

Balmford, James; Borland, Ron; Burney, Sue

2010-08-01

The aim of this study was to explore whether factors predicting making a quit attempt are uniform within the preparation stage of the transtheoretical model (TTM). Participants were 283 smokers, all planning to quit in the next 30 days (preparation stage), who used a computer-generated tailored advice programme. Evidence of differences in prediction of making a quit attempt was found between smokers with and without a quit date, with the predictive power of a multivariate model markedly higher among those with a set date. In particular, one aspect of pros of smoking (smoking helps you feel better when things are bad) was predictive of progression among those with a quit date, but not among those without. The results suggest that factors predicting stage progression are not uniform within the preparation stage. The results complement other recent research that has questioned the stage definitions used in the TTM and provide evidence in support of an alternative stage boundary defined by the commitment of setting a quit date.

EEG Beta Oscillations in the Temporoparietal Area Related to the Accuracy in Estimating Others' Preference

PubMed Central

Park, Jonghyeok; Kim, Hackjin; Sohn, Jeong-Woo; Choi, Jong-ryul; Kim, Sung-Phil

2018-01-01

Humans often attempt to predict what others prefer based on a narrow slice of experience, called thin-slicing. According to the theoretical bases for how humans can predict the preference of others, one tends to estimate the other's preference using a perceived difference between the other and self. Previous neuroimaging studies have revealed that the network of dorsal medial prefrontal cortex (dmPFC) and right temporoparietal junction (rTPJ) is related to the ability of predicting others' preference. However, it still remains unknown about the temporal patterns of neural activities for others' preference prediction through thin-slicing. To investigate such temporal aspects of neural activities, we investigated human electroencephalography (EEG) recorded during the task of predicting the preference of others while only a facial picture of others was provided. Twenty participants (all female, average age: 21.86) participated in the study. In each trial of the task, participants were shown a picture of either a target person or self for 3 s, followed by the presentation of a movie poster over which participants predicted the target person's preference as liking or disliking. The time-frequency EEG analysis was employed to analyze temporal changes in the amplitudes of brain oscillations. Participants could predict others' preference for movies with accuracy of 56.89 ± 3.16% and 10 out of 20 participants exhibited prediction accuracy higher than a chance level (95% interval). There was a significant difference in the power of the parietal alpha (10~13 Hz) oscillation 0.6~0.8 s after the onset of poster presentation between the cases when participants predicted others' preference and when they reported self-preference (p < 0.05). The power of brain oscillations at any frequency band and time period during the trial did not show a significant correlation with individual prediction accuracy. However, when we measured differences of the power between the trials of predicting other's preference and reporting self-preference, the right temporal beta oscillations 1.6~1.8 s after the onset of facial picture presentation exhibited a significant correlation with individual accuracy. Our results suggest that right temporoparietal beta oscillations may be correlated with one's ability to predict what others prefer with minimal information. PMID:29479312

EEG Beta Oscillations in the Temporoparietal Area Related to the Accuracy in Estimating Others' Preference.

PubMed

Park, Jonghyeok; Kim, Hackjin; Sohn, Jeong-Woo; Choi, Jong-Ryul; Kim, Sung-Phil

2018-01-01

Humans often attempt to predict what others prefer based on a narrow slice of experience, called thin-slicing. According to the theoretical bases for how humans can predict the preference of others, one tends to estimate the other's preference using a perceived difference between the other and self. Previous neuroimaging studies have revealed that the network of dorsal medial prefrontal cortex (dmPFC) and right temporoparietal junction (rTPJ) is related to the ability of predicting others' preference. However, it still remains unknown about the temporal patterns of neural activities for others' preference prediction through thin-slicing. To investigate such temporal aspects of neural activities, we investigated human electroencephalography (EEG) recorded during the task of predicting the preference of others while only a facial picture of others was provided. Twenty participants (all female, average age: 21.86) participated in the study. In each trial of the task, participants were shown a picture of either a target person or self for 3 s, followed by the presentation of a movie poster over which participants predicted the target person's preference as liking or disliking. The time-frequency EEG analysis was employed to analyze temporal changes in the amplitudes of brain oscillations. Participants could predict others' preference for movies with accuracy of 56.89 ± 3.16% and 10 out of 20 participants exhibited prediction accuracy higher than a chance level (95% interval). There was a significant difference in the power of the parietal alpha (10~13 Hz) oscillation 0.6~0.8 s after the onset of poster presentation between the cases when participants predicted others' preference and when they reported self-preference ( p < 0.05). The power of brain oscillations at any frequency band and time period during the trial did not show a significant correlation with individual prediction accuracy. However, when we measured differences of the power between the trials of predicting other's preference and reporting self-preference, the right temporal beta oscillations 1.6~1.8 s after the onset of facial picture presentation exhibited a significant correlation with individual accuracy. Our results suggest that right temporoparietal beta oscillations may be correlated with one's ability to predict what others prefer with minimal information.

Baseline predictors of persistence to first disease-modifying treatment in multiple sclerosis.

PubMed

Zettl, U K; Schreiber, H; Bauer-Steinhusen, U; Glaser, T; Hechenbichler, K; Hecker, M

2017-08-01

Patients with multiple sclerosis (MS) require lifelong therapy. However, success of disease-modifying therapies is dependent on patients' persistence and adherence to treatment schedules. In the setting of a large multicenter observational study, we aimed at assessing multiple parameters for their predictive power with respect to discontinuation of therapy. We analyzed 13 parameters to predict discontinuation of interferon beta-1b treatment during a 2-year follow-up period based on data from 395 patients with MS who were treatment-naïve at study onset. Besides clinical characteristics, patient-related psychosocial outcomes were assessed as well. Among patients without clinically relevant fatigue, males showed a higher persistence rate than females (80.3% vs 64.7%). Clinically relevant fatigue scores decreased the persistence rate in men and especially in women (71.4% and 51.2%). Besides gender and fatigue, univariable and multivariable analyses revealed further factors associated with interferon beta-1b therapy discontinuation, namely lower quality of life, depressiveness, and higher relapse rate before therapy initiation, while higher education, living without a partner, and higher age improved persistence. Patients with higher grades of fatigue and depressiveness are at higher risk to prematurely discontinue MS treatment; especially, women suffering from fatigue have an increased discontinuation rate. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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

Investigating market efficiency through a forecasting model based on differential equations

NASA Astrophysics Data System (ADS)

de Resende, Charlene C.; Pereira, Adriano C. M.; Cardoso, Rodrigo T. N.; de Magalhães, A. R. Bosco

2017-05-01

A new differential equation based model for stock price trend forecast is proposed as a tool to investigate efficiency in an emerging market. Its predictive power showed statistically to be higher than the one of a completely random model, signaling towards the presence of arbitrage opportunities. Conditions for accuracy to be enhanced are investigated, and application of the model as part of a trading strategy is discussed.

Robust regression on noisy data for fusion scaling laws

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

Verdoolaege, Geert, E-mail: geert.verdoolaege@ugent.be; Laboratoire de Physique des Plasmas de l'ERM - Laboratorium voor Plasmafysica van de KMS

2014-11-15

We introduce the method of geodesic least squares (GLS) regression for estimating fusion scaling laws. Based on straightforward principles, the method is easily implemented, yet it clearly outperforms established regression techniques, particularly in cases of significant uncertainty on both the response and predictor variables. We apply GLS for estimating the scaling of the L-H power threshold, resulting in estimates for ITER that are somewhat higher than predicted earlier.

Replacement Capability Options for the United States Space Shuttle

DTIC Science & Technology

2013-09-01

extended periods, and to expand our knowledge of solar astronomy well beyond Earth-based observations.” During the Skylab missions, both the man...determined Skylab’s orbit was no longer stable due to higher than predicted solar activity. Therefore, Skylab had to be de-orbited earlier than...Module houses the oxygen, life support, power, communications, thermal control, and propulsions systems. The solar arrays for the Soyuz are also

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.

An increasing electromechanical window is a predictive marker of ventricular fibrillation in anesthetized rabbit with ischemic heart.

PubMed

Limprasutr, Vudhiporn; Pirintr, Prapawadee; Kijtawornrat, Anusak; Hamlin, Robert L

2018-05-10

The QTc interval is widely used in Safety Pharmacological studies to predict arrhythmia risk, and the electromechanical window (EMW) and short-term variability of QT intervals (STV QT ) have been studied as new biomarkers for drug-induced Torsades de Pointes (TdP). However, the use of EMW and STV QT to predict ventricular fibrillation (VF) has not been elucidated. This study aimed to evaluate EMW and STV QT to predict VF in anesthetized rabbit model of VF. VF was induced by ligation of the left anterior descending and a descending branch of the left circumflex coronary arteries in a sample population of rabbits (n=18). VF was developed 55.6% (10/18). In rabbit with VF, the EMW was significantly higher than in rabbits without VF (96.3 ± 15.6 ms and 49.5 ± 5.6 ms, respectively, P<0.05). STV QT had significantly increased before the onset of VF in rabbits that experienced VF, but not in rabbits that did not experience VF (11.7 ± 1.8 ms and 3.7 ± 0.4 ms, respectively, P<0.05). The EMW and STV QT had better predictive power for VF with higher sensitivity and specificity than the QTc measure. The result suggested that the increasing of EMW, as well as the elevation of STV QT , can potentially be used as biomarkers for predicting of VF.

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

Versatility and addiction in gaming: the number of video-game genres played is associated with pathological gaming in male adolescents.

PubMed

Donati, Maria Anna; Chiesi, Francesca; Ammannato, Giulio; Primi, Caterina

2015-02-01

This study tested the predictive power of gaming versatility (i.e., the number of video game genres engaged in) on game addiction in male adolescents, controlling for time spent on gaming. Participants were 701 male adolescents attending high school (Mage=15.6 years). Analyses showed that pathological gaming was predicted not only by higher time spent on gaming, but also by participation in a greater number of video game genres. Specifically, the wider the array of video game genres played, the higher were the negative consequences caused by gaming. Findings show that versatility can be considered as one of the behavioral risk factors related to gaming addiction, which may be characterized by a composite and diversified experience with video games. This study suggests that educational efforts designed to prevent gaming addiction among youth may also be focused on adolescents' engagement in different video games.

Initial Assessment of the Risk Assessment and Prediction Tool in a Heterogeneous Neurosurgical Patient Population.

PubMed

Piazza, Matthew; Sharma, Nikhil; Osiemo, Benjamin; McClintock, Scott; Missimer, Emily; Gardiner, Diana; Maloney, Eileen; Callahan, Danielle; Smith, J Lachlan; Welch, William; Schuster, James; Grady, M Sean; Malhotra, Neil R

2018-05-21

Bundled care payments are increasingly being explored for neurosurgical interventions. In this setting, skilled nursing facility (SNF) is less desirable from a cost perspective than discharge to home, underscoring the need for better preoperative prediction of postoperative disposition. To assess the capability of the Risk Assessment and Prediction Tool (RAPT) and other preoperative variables to determine expected disposition prior to surgery in a heterogeneous neurosurgical cohort, through observational study. Patients aged 50 yr or more undergoing elective neurosurgery were enrolled from June 2016 to February 2017 (n = 623). Logistic regression was used to identify preoperative characteristics predictive of discharge disposition. Results from multivariate analysis were used to create novel grading scales for the prediction of discharge disposition that were subsequently compared to the RAPT Score using Receiver Operating Characteristic analysis. Higher RAPT Score significantly predicted home disposition (P < .001). Age 65 and greater, dichotomized RAPT walk score, and spinal surgery below L2 were independent predictors of SNF discharge in multivariate analysis. A grading scale utilizing these variables had superior discriminatory power between SNF and home/rehab discharge when compared with RAPT score alone (P = .004). Our analysis identified age, lower lumbar/lumbosacral surgery, and RAPT walk score as independent predictors of discharge to SNF, and demonstrated superior predictive power compared with the total RAPT Score when combined in a novel grading scale. These tools may identify patients who may benefit from expedited discharge to subacute care facilities and decrease inpatient hospital resource utilization following surgery.

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.

Usefulness of combining admission brain natriuretic peptide (BNP) plus hospital discharge bioelectrical impedance vector analysis (BIVA) in predicting 90 days cardiovascular mortality in patients with acute heart failure.

PubMed

Santarelli, Simona; Russo, Veronica; Lalle, Irene; De Berardinis, Benedetta; Navarin, Silvia; Magrini, Laura; Piccoli, Antonio; Codognotto, Marta; Castello, Luigi Maria; Avanzi, Gian Carlo; Villacorta, Humberto; Precht, Bernardo Luiz Campanário; de Araújo Porto, Pilar Barreto; Villacorta, Aline Sterque; Di Somma, Salvatore

2017-06-01

Heart failure is a disease characterized by high prevalence and mortality, and frequent rehospitalizations. The aim of this study is to investigate the prognostic power of combining brain natriuretic peptide (BNP) and congestion status detected by bioelectrical impedance vector analysis (BIVA) in acute heart failure patients. This is an observational, prospective, and a multicentre study. BNP assessment was measured upon hospital arrival, while BIVA analysis was obtained at the time of discharge. Cardiovascular deaths were evaluated at 90 days by a follow up phone call. 292 patients were enrolled. Compared to survivors, BNP was higher in the non-survivors group (mean value 838 vs 515 pg/ml, p < 0.001). At discharge, BIVA shows a statistically significant difference in hydration status between survivors and non-survivors [respectively, hydration index (HI) 85 vs 74, p < 0.001; reactance (Xc) 26.7 vs 37, p < 0.001; resistance (R) 445 vs 503, p < 0.01)]. Discharge BIVA shows a prognostic value in predicting cardiovascular death [HI: area under the curve (AUC) 0.715, 95% confidence interval (95% CI) 0.65-0.76; p < 0.004; Xc: AUC 0.712, 95% CI 0.655-0.76, p < 0.007; R: AUC 0.65, 95% CI 0.29-0.706, p < 0.0247]. The combination of BIVA with BNP gives a greater prognostic power for cardiovascular mortality [combined receiving operating characteristic (ROC): AUC 0.74; 95% CI 0.68-0.79; p < 0.001]. In acute heart failure patients, higher BNP levels upon hospital admission, and congestion detected by BIVA at discharge have a significant predictive value for 90 days cardiovascular mortality. The combined use of admission BNP and BIVA discharge seems to be a useful tool for increasing prognostic power in these patients.

Early changes of parotid density and volume predict modifications at the end of therapy and intensity of acute xerostomia.

PubMed

Belli, Maria Luisa; Scalco, Elisa; Sanguineti, Giuseppe; Fiorino, Claudio; Broggi, Sara; Dinapoli, Nicola; Ricchetti, Francesco; Valentini, Vincenzo; Rizzo, Giovanna; Cattaneo, Giovanni Mauro

2014-10-01

To quantitatively assess the predictive power of early variations of parotid gland volume and density on final changes at the end of therapy and, possibly, on acute xerostomia during IMRT for head-neck cancer. Data of 92 parotids (46 patients) were available. Kinetics of the changes during treatment were described by the daily rate of density (rΔρ) and volume (rΔvol) variation based on weekly diagnostic kVCT images. Correlation between early and final changes was investigated as well as the correlation with prospective toxicity data (CTCAEv3.0) collected weekly during treatment for 24/46 patients. A higher rΔρ was observed during the first compared to last week of treatment (-0,50 vs -0,05HU, p-value = 0.0001). Based on early variations, a good estimation of the final changes may be obtained (Δρ: AUC = 0.82, p = 0.0001; Δvol: AUC = 0.77, p = 0.0001). Both early rΔρ and rΔvol predict a higher "mean" acute xerostomia score (≥ median value, 1.57; p-value = 0.01). Median early density rate changes for patients with mean xerostomia score ≥ / < 1.57 were -0.98 vs -0.22 HU/day respectively (p = 0.05). Early density and volume variations accurately predict final changes of parotid glands. A higher longitudinally assessed score of acute xerostomia is well predicted by higher rΔρ and rΔvol in the first two weeks of treatment: best cut-off values were -0.50 HU/day and -380 mm(3)/day for rΔρ and rΔvol respectively. Further studies are necessary to definitively assess the potential of early density/volume changes in identifying more sensitive patients at higher risk of experiencing xerostomia.

Analysis of 2D Transport and Performance Characteristics for Lateral Power Devices Based on AlGaN Alloys

DOE PAGES

Coltrin, Michael E.; Baca, Albert G.; Kaplar, Robert J.

2017-10-26

In this paper, predicted lateral power device performance as a function of alloy composition is characterized by a standard lateral device figure-of-merit (LFOM) that depends on mobility, critical electric field, and sheet carrier density. The paper presents calculations of AlGaN electron mobility in lateral devices such as HEMTs across the entire alloy composition range. Alloy scattering and optical polar phonon scattering are the dominant mechanisms limiting carrier mobility. Due to the significant degradation of mobility from alloy scattering, at room temperature Al fractions greater than about 85% are required for improved LFOM relative to GaN using a conservative sheet chargemore » density of 1 × 10 13 cm –2. However, at higher temperatures at which AlGaN power devices are anticipated to operate, this “breakeven” composition decreases to about 65% at 500 K, for example. For high-frequency applications, the Johnson figure-of-merit (JFOM) is the relevant metric to compare potential device performance across materials platforms. At room temperature, the JFOM for AlGaN alloys is predicted to surpass that of GaN for Al fractions greater than about 40%.« less

Analysis of 2D Transport and Performance Characteristics for Lateral Power Devices Based on AlGaN Alloys

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

Coltrin, Michael E.; Baca, Albert G.; Kaplar, Robert J.

In this paper, predicted lateral power device performance as a function of alloy composition is characterized by a standard lateral device figure-of-merit (LFOM) that depends on mobility, critical electric field, and sheet carrier density. The paper presents calculations of AlGaN electron mobility in lateral devices such as HEMTs across the entire alloy composition range. Alloy scattering and optical polar phonon scattering are the dominant mechanisms limiting carrier mobility. Due to the significant degradation of mobility from alloy scattering, at room temperature Al fractions greater than about 85% are required for improved LFOM relative to GaN using a conservative sheet chargemore » density of 1 × 10 13 cm –2. However, at higher temperatures at which AlGaN power devices are anticipated to operate, this “breakeven” composition decreases to about 65% at 500 K, for example. For high-frequency applications, the Johnson figure-of-merit (JFOM) is the relevant metric to compare potential device performance across materials platforms. At room temperature, the JFOM for AlGaN alloys is predicted to surpass that of GaN for Al fractions greater than about 40%.« less

Culture and medical decision making: Healthcare consumer perspectives in Japan and the United States.

PubMed

Alden, Dana L; Friend, John M; Lee, Angela Y; de Vries, Marieke; Osawa, Ryosuke; Chen, Qimei

2015-12-01

Two studies identified core value influences on medical decision-making processes across and within cultures. In Study 1, Japanese and American adults reported desired levels of medical decision-making influence across conditions that varied in seriousness. Cultural antecedents (interdependence, independence, and power distance) were also measured. In Study 2, American adults reviewed a colorectal cancer screening decision aid. Decision preparedness was measured along with interdependence, independence, and desire for medical information. In Study 1, higher interdependence predicted stronger desire for decision-making information in both countries, but was significantly stronger in Japan. The path from information desire to decision-making influence desire was significant only in Japan. The independence path to desire for decision-making influence was significant only in the United States. Power distance effects negatively predicted desire for decision-making influence only in the United States. For Study 2, high (low) interdependents and women (men) in the United States felt that a colorectal cancer screening decision aid helped prepare them more (less) for a medical consultation. Low interdependent men were at significantly higher risk for low decision preparedness. Study 1 suggests that Japanese participants may tend to view medical decision-making influence as an interdependent, information sharing exchange, whereas American respondents may be more interested in power sharing that emphasizes greater independence. Study 2 demonstrates the need to assess value influences on medical decision-making processes within and across cultures and suggests that individually tailored versions of decision aids may optimize decision preparedness. (c) 2015 APA, all rights reserved).

Ultrasound-Assisted Extraction of Cannabinoids from Cannabis Sativa L. Optimized by Response Surface Methodology.

PubMed

Agarwal, Charu; Máthé, Katalin; Hofmann, Tamás; Csóka, Levente

2018-03-01

Ultrasonication was used to extract bioactive compounds from Cannabis sativa L. such as polyphenols, flavonoids, and cannabinoids. The influence of 3 independent factors (time, input power, and methanol concentration) was evaluated on the extraction of total phenols (TPC), flavonoids (TF), ferric reducing ability of plasma (FRAP) and the overall yield. A face-centered central composite design was used for statistical modelling of the response data, followed by regression and analysis of variance in order to determine the significance of the model and factors. Both the solvent composition and the time significantly affected the extraction while the sonication power had no significant impact on the responses. The response predictions obtained at optimum extraction conditions of 15 min time, 130 W power, and 80% methanol were 314.822 mg GAE/g DW of TPC, 28.173 mg QE/g DW of TF, 18.79 mM AAE/g DW of FRAP, and 10.86% of yield. A good correlation was observed between the predicted and experimental values of the responses, which validated the mathematical model. On comparing the ultrasonic process with the control extraction, noticeably higher values were obtained for each of the responses. Additionally, ultrasound considerably improved the extraction of cannabinoids present in Cannabis. Low frequency ultrasound was employed to extract bioactive compounds from the inflorescence part of Cannabis. The responses evaluated were-total phenols, flavonoids, ferric reducing assay and yield. The solvent composition and time significantly influenced the extraction process. Appreciably higher extraction of cannabinoids was achieved on sonication against control. © 2018 Institute of Food Technologists®.

Prediction of vertical jump height from anthropometric factors in male and female martial arts athletes.

PubMed

Abidin, Nahdiya Zainal; Adam, Mohd Bakri

2013-01-01

Vertical jump is an index representing leg/kick power. The explosive movement of the kick is the key to scoring in martial arts competitions. It is important to determine factors that influence the vertical jump to help athletes improve their leg power. The objective of the present study is to identify anthropometric factors that influence vertical jump height for male and female martial arts athletes. Twenty-nine male and 25 female athletes participated in this study. Participants were Malaysian undergraduate students whose ages ranged from 18 to 24 years old. Their heights were measured using a stadiometer. The subjects were weighted using digital scale. Body mass index was calculated by kg/m(2). Waist-hip ratio was measured from the ratio of waist to hip circumferences. Body fat % was obtained from the sum of four skinfold thickness using Harpenden callipers. The highest vertical jump from a stationary standing position was recorded. The maximum grip was recorded using a dynamometer. For standing back strength, the maximum pull upwards using a handle bar was recorded. Multiple linear regression was used to obtain the relationship between vertical jump height and explanatory variables with gender effect. Body fat % has a significant negative relationship with vertical jump height (P < 0.001). The effect of gender is significant (P < 0.001): on average, males jumped 26% higher than females did. Vertical jump height of martial arts athletes can be predicted by body fat %. The vertical jump for male is higher than for their female counterparts. Reducing body fat by proper dietary planning will help to improve leg power.

Effect of wake structure on blade-vortex interaction phenomena: Acoustic prediction and validation

NASA Technical Reports Server (NTRS)

Gallman, Judith M.; Tung, Chee; Schultz, Klaus J.; Splettstoesser, Wolf; Buchholz, Heino

1995-01-01

During the Higher Harmonic Control Aeroacoustic Rotor Test, extensive measurements of the rotor aerodynamics, the far-field acoustics, the wake geometry, and the blade motion for powered, descent, flight conditions were made. These measurements have been used to validate and improve the prediction of blade-vortex interaction (BVI) noise. The improvements made to the BVI modeling after the evaluation of the test data are discussed. The effects of these improvements on the acoustic-pressure predictions are shown. These improvements include restructuring the wake, modifying the core size, incorporating the measured blade motion into the calculations, and attempting to improve the dynamic blade response. A comparison of four different implementations of the Ffowcs Williams and Hawkings equation is presented. A common set of aerodynamic input has been used for this comparison.

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…

Modeling of static and flowing-gas diode pumped alkali lasers

NASA Astrophysics Data System (ADS)

Barmashenko, Boris D.; Auslender, Ilya; Yacoby, Eyal; Waichman, Karol; Sadot, Oren; Rosenwaks, Salman

2016-03-01

Modeling of static and flowing-gas subsonic, transonic and supersonic Cs and K Ti:Sapphire and diode pumped alkali lasers (DPALs) is reported. A simple optical model applied to the static K and Cs lasers shows good agreement between the calculated and measured dependence of the laser power on the incident pump power. The model reproduces the observed threshold pump power in K DPAL which is much higher than that predicted by standard models of the DPAL. Scaling up flowing-gas DPALs to megawatt class power is studied using accurate three-dimensional computational fluid dynamics model, taking into account the effects of temperature rise and losses of alkali atoms due to ionization. Both the maximum achievable power and laser beam quality are estimated for Cs and K lasers. The performance of subsonic and, in particular, supersonic DPALs is compared with that of transonic, where supersonic nozzle and diffuser are spared and high power mechanical pump (needed for recovery of the gas total pressure which strongly drops in the diffuser), is not required for continuous closed cycle operation. For pumping by beams of the same rectangular cross section, comparison between end-pumping and transverse-pumping shows that the output power is not affected by the pump geometry, however, the intensity of the output laser beam in the case of transverse-pumped DPALs is strongly non-uniform in the laser beam cross section resulting in higher brightness and better beam quality in the far field for the end-pumping geometry where the intensity of the output beam is uniform.

Effect of Voltage Level on Power System Design for Solar Electric Propulsion Missions

NASA Technical Reports Server (NTRS)

Kerslake, Thomas W.

2003-01-01

This paper presents study results quantifying the benefits of higher voltage, electric power system designs for a typical solar electric propulsion spacecraft Earth orbiting mission. A conceptual power system architecture was defined and design points were generated for system voltages of 28-V, 50-V, 120-V, and 300-V using state-of-the-art or advanced technologies. A 300-V 'direct-drive' architecture was also analyzed to assess the benefits of directly powering the electric thruster from the photovoltaic array without up-conversion. Fortran and spreadsheet computational models were exercised to predict the performance and size power system components to meet spacecraft mission requirements. Pertinent space environments, such as electron and proton radiation, were calculated along the spiral trajectory. In addition, a simplified electron current collection model was developed to estimate photovoltaic array losses for the orbital plasma environment and that created by the thruster plume. The secondary benefits of power system mass savings for spacecraft propulsion and attitude control systems were also quantified. Results indicate that considerable spacecraft wet mass savings were achieved by the 300-V and 300-V direct-drive architectures.

Spatiotemporal dynamics of auditory attention synchronize with speech

PubMed Central

Wöstmann, Malte; Herrmann, Björn; Maess, Burkhard

2016-01-01

Attention plays a fundamental role in selectively processing stimuli in our environment despite distraction. Spatial attention induces increasing and decreasing power of neural alpha oscillations (8–12 Hz) in brain regions ipsilateral and contralateral to the locus of attention, respectively. This study tested whether the hemispheric lateralization of alpha power codes not just the spatial location but also the temporal structure of the stimulus. Participants attended to spoken digits presented to one ear and ignored tightly synchronized distracting digits presented to the other ear. In the magnetoencephalogram, spatial attention induced lateralization of alpha power in parietal, but notably also in auditory cortical regions. This alpha power lateralization was not maintained steadily but fluctuated in synchrony with the speech rate and lagged the time course of low-frequency (1–5 Hz) sensory synchronization. Higher amplitude of alpha power modulation at the speech rate was predictive of a listener’s enhanced performance of stream-specific speech comprehension. Our findings demonstrate that alpha power lateralization is modulated in tune with the sensory input and acts as a spatiotemporal filter controlling the read-out of sensory content. PMID:27001861

Dynamical electrical conductivity of graphene.

PubMed

Rani, Luxmi; Singh, Navinder

2017-06-28

For graphene (a Dirac material) it has been theoretically predicted and experimentally observed that DC resistivity is proportional to T 4 when the temperature is much less than Bloch-Grüneisen temperature ([Formula: see text]) and T-linear in the opposite case ([Formula: see text]). Going beyond this case, we investigate the dynamical electrical conductivity in graphene using the powerful method of the memory function formalism. In the zero frequency regime, we obtain the above mentioned behavior which was previously obtained using the Bloch-Boltzmann kinetic equation. In the finite frequency regime, we obtain several new results: (1) the generalized Drude scattering rate, in the zero temperature limit, shows [Formula: see text] behavior at low frequencies ([Formula: see text]) and saturates at higher frequencies. We also observed the Holstein mechanism, however, with different power laws from that in the case of metals; (2) at higher frequencies, [Formula: see text], and higher temperatures [Formula: see text], we observed that the generalized Drude scattering rate is linear in temperature. In addition, several other results are also obtained. With the experimental advancement of this field, these results should be experimentally tested.

Monitoring of hot pipes at the power plant Neurath using guided waves

NASA Astrophysics Data System (ADS)

Weihnacht, Bianca; Klesse, Thomas; Neubeck, Robert; Schubert, Lars

2013-04-01

In order to reduce the CO2-emissions and to increase the energy efficiency, the operating temperatures of power plants will be increased up to 720°C. This demands for novel high-performance steels in the piping systems. Higher temperatures lead to a higher risk of damage and have a direct impact on the structure stability and the deposition structure. Adequately trusted results for the prediction of the residual service life of those high strength steels are not available so far. To overcome these problems the implementation of an online monitoring system in addition to periodic testing is needed. RWE operates the lignite power plant Neurath. All test and research activities have to be checked regarding their safety and have to be coordinated with the business operation of the plant. An extra bypass was established for this research and made the investigations independent from the power plant operating. In order to protect the actuators and sensors from the heat radiated from the pipe, waveguides were welded to the bypass. The data was evaluated regarding their dependencies on the environmental influences like temperature and correction algorithms were developed. Furthermore, damages were introduced into the pipe with diameters of 8 mm to 10 mm and successfully detected by the acoustic method.

High energy density propulsion systems and small engine dynamometer

NASA Astrophysics Data System (ADS)

Hays, Thomas

2009-07-01

Scope and Method of Study. This study investigates all possible methods of powering small unmanned vehicles, provides reasoning for the propulsion system down select, and covers in detail the design and production of a dynamometer to confirm theoretical energy density calculations for small engines. Initial energy density calculations are based upon manufacturer data, pressure vessel theory, and ideal thermodynamic cycle efficiencies. Engine tests are conducted with a braking type dynamometer for constant load energy density tests, and show true energy densities in excess of 1400 WH/lb of fuel. Findings and Conclusions. Theory predicts lithium polymer, the present unmanned system energy storage device of choice, to have much lower energy densities than other conversion energy sources. Small engines designed for efficiency, instead of maximum power, would provide the most advantageous method for powering small unmanned vehicles because these engines have widely variable power output, loss of mass during flight, and generate rotational power directly. Theoretical predictions for the energy density of small engines has been verified through testing. Tested values up to 1400 WH/lb can be seen under proper operating conditions. The implementation of such a high energy density system will require a significant amount of follow-on design work to enable the engines to tolerate the higher temperatures of lean operation. Suggestions are proposed to enable a reliable, small-engine propulsion system in future work. Performance calculations show that a mature system is capable of month long flight times, and unrefueled circumnavigation of the globe.

Testing predictive models of positive and negative affect with psychosocial, acculturation, and coping variables in a multiethnic undergraduate sample.

PubMed

Kuo, Ben Ch; Kwantes, Catherine T

2014-01-01

Despite the prevalence and popularity of research on positive and negative affect within the field of psychology, there is currently little research on affect involving the examination of cultural variables and with participants of diverse cultural and ethnic backgrounds. To the authors' knowledge, currently no empirical studies have comprehensively examined predictive models of positive and negative affect based specifically on multiple psychosocial, acculturation, and coping variables as predictors with any sample populations. Therefore, the purpose of the present study was to test the predictive power of perceived stress, social support, bidirectional acculturation (i.e., Canadian acculturation and heritage acculturation), religious coping and cultural coping (i.e., collective, avoidance, and engagement coping) in explaining positive and negative affect in a multiethnic sample of 301 undergraduate students in Canada. Two hierarchal multiple regressions were conducted, one for each affect as the dependent variable, with the above described predictors. The results supported the hypotheses and showed the two overall models to be significant in predicting affect of both kinds. Specifically, a higher level of positive affect was predicted by a lower level of perceived stress, less use of religious coping, and more use of engagement coping in dealing with stress by the participants. Higher level of negative affect, however, was predicted by a higher level of perceived stress and more use of avoidance coping in responding to stress. The current findings highlight the value and relevance of empirically examining the stress-coping-adaptation experiences of diverse populations from an affective conceptual framework, particularly with the inclusion of positive affect. Implications and recommendations for advancing future research and theoretical works in this area are considered and presented.

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

A Particle and Energy Balance Model of the Orificed Hollow Cathode

NASA Technical Reports Server (NTRS)

Domonkos, Matthew T.

2002-01-01

A particle and energy balance model of orificed hollow cathodes was developed to assist in cathode design. The model presented here is an ensemble of original work by the author and previous work by others. The processes in the orifice region are considered to be one of the primary drivers in determining cathode performance, since the current density was greatest in this volume (up to 1.6 x 10(exp 8) A/m2). The orifice model contains comparatively few free parameters, and its results are used to bound the free parameters for the insert model. Next, the insert region model is presented. The sensitivity of the results to the free parameters is assessed, and variation of the free parameters in the orifice dominates the calculated power consumption and plasma properties. The model predictions are compared to data from a low-current orificed hollow cathode. The predicted power consumption exceeds the experimental results. Estimates of the plasma properties in the insert region overlap Langmuir probe data, and the predicted orifice plasma suggests the presence of one or more double layers. Finally, the model is used to examine the operation of higher current cathodes.

Variability in Cadence During Forced Cycling Predicts Motor Improvement in Individuals With Parkinson’s Disease

PubMed Central

Ridgel, Angela L.; Abdar, Hassan Mohammadi; Alberts, Jay L.; Discenzo, Fred M.; Loparo, Kenneth A.

2014-01-01

Variability in severity and progression of Parkinson’s disease symptoms makes it challenging to design therapy interventions that provide maximal benefit. Previous studies showed that forced cycling, at greater pedaling rates, results in greater improvements in motor function than voluntary cycling. The precise mechanism for differences in function following exercise is unknown. We examined the complexity of biomechanical and physiological features of forced and voluntary cycling and correlated these features to improvements in motor function as measured by the Unified Parkinson’s Disease Rating Scale (UPDRS). Heart rate, cadence, and power were analyzed using entropy signal processing techniques. Pattern variability in heart rate and power were greater in the voluntary group when compared to forced group. In contrast, variability in cadence was higher during forced cycling. UPDRS Motor III scores predicted from the pattern variability data were highly correlated to measured scores in the forced group. This study shows how time series analysis methods of biomechanical and physiological parameters of exercise can be used to predict improvements in motor function. This knowledge will be important in the development of optimal exercise-based rehabilitation programs for Parkinson’s disease. PMID:23144045

Prediction of Radioactive Material Proliferation in Abukuma Basin using USLE

NASA Astrophysics Data System (ADS)

Yi, C. J.

2014-12-01

Due to the nuclear-power plant accident after the 2011 Great East Japan Earthquake and Tsunami, the residents who had resided within 20 km from the Daiichi Fukushima Nuclear Power Plant had forced to leave their hometown. The impacts by the radioactive contamination extended to numerous social elements, such as food, economy, civil engineering, community rebuilding, etc. Japanese government agencies have measured the level of radioactive contamination in urban, agricultural area, forest, riverine and ocean. The research found that the concentration level of cesium-137 (137Cs) is higher in the forest than an open area such as paddy field or rural town. Litter layers and surface layers, especially, are found to be significantly contaminated. The study calculated the estimation of contaminated soil erosion using the USLE which the idea is based on scenario that addresses a question, what if 137Cs would carry out from the forest after intensive rainfall. Predicting radioactively contaminated areas after intense rainfall is a critical matter for the future watershed risk management.

Differentiating psychotic patients from nonpsychotic patients with the MMPI-2 and Rorschach.

PubMed

Dao, Tam K; Prevatt, Frances; Horne, Heather Leveta

2008-01-01

The goal of this study was to examine the incremental validity and the clinical utility of the Minnesota Multiphasic Personality Inventory-2 (MMPI-2; (Butcher, Dahlstrom, Graham, Tellegen, & Kaemmer, 1989) and Rorschach (Rorschach, 1942) with regard to differential diagnosis in a sample of adult inpatients with a primary psychotic disorder or a primary mood disorder without psychotic features. Diagnostic efficiency statistics have suggested that the Rorschach Perceptual Thinking Index (PTI; Exner, 2000a, 2000b) was better than MMPI-2 scales in discriminating psychotic patients from nonpsychotic patients. We compared the 84% overall correct classification rate (OCC) for the PTI to an OCC of 70% for the MMPI-2 scales. Adding the MMPI-2 scales to the PTI resulted in a decrease in OCC of 1%, whereas adding the PTI to the MMPI-2 resulted in an increase in OCC of 14%. Sensitivity, specificity, positive predictive power, negative predictive power, and kappa were equal or higher with only the PTI in the model.

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.

SRG110 Stirling Generator Dynamic Simulator Vibration Test Results and Analysis Correlation

NASA Technical Reports Server (NTRS)

Suarez, Vicente J.; Lewandowski, Edward J.; Callahan, John

2006-01-01

The U.S. Department of Energy (DOE), Lockheed Martin (LM), and NASA Glenn Research Center (GRC) have been developing the Stirling Radioisotope Generator (SRG110) for use as a power system for space science missions. The launch environment enveloping potential missions results in a random input spectrum that is significantly higher than historical RPS launch levels and is a challenge for designers. Analysis presented in prior work predicted that tailoring the compliance at the generator-spacecraft interface reduced the dynamic response of the system thereby allowing higher launch load input levels and expanding the range of potential generator missions. To confirm analytical predictions, a dynamic simulator representing the generator structure, Stirling convertors and heat sources was designed and built for testing with and without a compliant interface. Finite element analysis was performed to guide the generator simulator and compliant interface design so that test modes and frequencies were representative of the SRG110 generator. This paper presents the dynamic simulator design, the test setup and methodology, test article modes and frequencies and dynamic responses, and post-test analysis results. With the compliant interface, component responses to an input environment exceeding the SRG110 qualification level spectrum were all within design allowables. Post-test analysis included finite element model tuning to match test frequencies and random response analysis using the test input spectrum. Analytical results were in good overall agreement with the test results and confirmed previous predictions that the SRG110 power system may be considered for a broad range of potential missions, including those with demanding launch environments.

Inequality matters: classroom status hierarchy and adolescents' bullying.

PubMed

Garandeau, Claire F; Lee, Ihno A; Salmivalli, Christina

2014-07-01

The natural emergence of status hierarchies in adolescent peer groups has long been assumed to help prevent future intragroup aggression. However, clear evidence of this beneficial influence is lacking. In fact, few studies have examined between-group differences in the degree of status hierarchy (defined as within-group variation in individual status) and how they are related to bullying, a widespread form of aggression in schools. Data from 11,296 eighth- and ninth-graders (mean age = 14.57, 50.6 % female) from 583 classes in 71 schools were used to determine the direction of the association between classroom degree of status hierarchy and bullying behaviors, and to investigate prospective relationships between these two variables over a 6-month period. Multilevel structural equation modeling analyses showed that higher levels of classroom status hierarchy were concurrently associated with higher levels of bullying at the end of the school year. Higher hierarchy in the middle of the school year predicted higher bullying later in the year. No evidence was found to indicate that initial bullying predicted future hierarchy. These findings highlight the importance of a shared balance of power in the classroom for the prevention of bullying among adolescents.

Ellipsoidal universe can solve the cosmic microwave background quadrupole problem.

PubMed

Campanelli, L; Cea, P; Tedesco, L

2006-09-29

The recent 3 yr Wilkinson Microwave Anisotropy Probe data have confirmed the anomaly concerning the low quadrupole amplitude compared to the best-fit Lambda-cold dark matter prediction. We show that by allowing the large-scale spatial geometry of our universe to be plane symmetric with eccentricity at decoupling or order 10(-2), the quadrupole amplitude can be drastically reduced without affecting higher multipoles of the angular power spectrum of the temperature anisotropy.

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.

Aerobic power and lean mass are indicators of competitive sprint performance among elite female cross-country skiers.

PubMed

Carlsson, Tomas; Tonkonogi, Michail; Carlsson, Magnus

2016-01-01

The purpose of this study was to establish the optimal allometric models to predict International Ski Federation's ski-ranking points for sprint competitions (FISsprint) among elite female cross-country skiers based on maximal oxygen uptake ( [Formula: see text]) and lean mass (LM). Ten elite female cross-country skiers (age: 24.5±2.8 years [mean ± SD]) completed a treadmill roller-skiing test to determine [Formula: see text] (ie, aerobic power) using the diagonal stride technique, whereas LM (ie, a surrogate indicator of anaerobic capacity) was determined by dual-emission X-ray anthropometry. The subjects' FISsprint were used as competitive performance measures. Power function modeling was used to predict the skiers' FISsprint based on [Formula: see text], LM, and body mass. The subjects' test and performance data were as follows: [Formula: see text], 4.0±0.3 L min -1 ; LM, 48.9±4.4 kg; body mass, 64.0±5.2 kg; and FISsprint, 116.4±59.6 points. The following power function models were established for the prediction of FISsprint: [Formula: see text] and 6.95 × 10 10 · LM -5.25 ; these models explained 66% ( P =0.0043) and 52% ( P =0.019), respectively, of the variance in the FISsprint. Body mass failed to contribute to both models; hence, the models are based on [Formula: see text] and LM expressed absolutely. The results demonstrate that the physiological variables that reflect aerobic power and anaerobic capacity are important indicators of competitive sprint performance among elite female skiers. To accurately indicate performance capability among elite female skiers, the presented power function models should be used. Skiers whose [Formula: see text] differs by 1% will differ in their FISsprint by 5.8%, whereas the corresponding 1% difference in LM is related to an FISsprint difference of 5.1%, where both differences are in favor of the skier with higher [Formula: see text] or LM. It is recommended that coaches use the absolute expression of these variables to monitor skiers' performance-related training adaptations linked to changes in aerobic power and anaerobic capacity.

High Fidelity, “Faster than Real-Time” Simulator for Predicting Power System Dynamic Behavior - Final Technical Report

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

Flueck, Alex

The “High Fidelity, Faster than Real­Time Simulator for Predicting Power System Dynamic Behavior” was designed and developed by Illinois Institute of Technology with critical contributions from Electrocon International, Argonne National Laboratory, Alstom Grid and McCoy Energy. Also essential to the project were our two utility partners: Commonwealth Edison and AltaLink. The project was a success due to several major breakthroughs in the area of large­scale power system dynamics simulation, including (1) a validated faster than real­ time simulation of both stable and unstable transient dynamics in a large­scale positive sequence transmission grid model, (2) a three­phase unbalanced simulation platform formore » modeling new grid devices, such as independently controlled single­phase static var compensators (SVCs), (3) the world’s first high fidelity three­phase unbalanced dynamics and protection simulator based on Electrocon’s CAPE program, and (4) a first­of­its­ kind implementation of a single­phase induction motor model with stall capability. The simulator results will aid power grid operators in their true time of need, when there is a significant risk of cascading outages. The simulator will accelerate performance and enhance accuracy of dynamics simulations, enabling operators to maintain reliability and steer clear of blackouts. In the long­term, the simulator will form the backbone of the newly conceived hybrid real­time protection and control architecture that will coordinate local controls, wide­area measurements, wide­area controls and advanced real­time prediction capabilities. The nation’s citizens will benefit in several ways, including (1) less down time from power outages due to the faster­than­real­time simulator’s predictive capability, (2) higher levels of reliability due to the detailed dynamics plus protection simulation capability, and (3) more resiliency due to the three­ phase unbalanced simulator’s ability to model three­phase and single­ phase networks and devices.« less

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

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

Zia, Jalal; Sevincer, Edip; Chen, Huijuan

2013-06-29

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

Thermal optimization of second harmonic generation at high pump powers.

PubMed

Sahm, Alexander; Uebernickel, Mirko; Paschke, Katrin; Erbert, Götz; Tränkle, Günther

2011-11-07

We measure the temperature distribution of a 3 cm long periodically poled LiNbO₃ crystal in a single-pass second harmonic generation (SHG) setup at 488 nm. By means of three resistance heaters and directly mounted Pt100 sensors the crystal is subdivided in three sections. 9.4 W infrared pump light and 1.3 W of SHG light cause a de-homogenized temperature distribution of 0.2 K between the middle and back section. A sectional offset heating is used to homogenize the temperature in those two sections and thus increasing the conversion efficiency. A 15% higher SHG output power matching the prediction of our theoretical model is achieved.

Effect of Tilt of the Propeller Axis on the Longitudinal-stability Characteristics of Single-Engine Airplanes

NASA Technical Reports Server (NTRS)

Goett, Harry J; Delaney, Noel K

1944-01-01

Report presents the results of tests of a model of a single-engine airplane with two different tilts of the propeller axis. The results indicate that on a typical design a 5 degree downward tilt of the propeller axis will considerably reduce the destabilization effects of power. A comparison of the experimental results with those computed by use of existing theory is included. A comparison of the experimental results with those computed by use of existing theory is included. It is shown that the results can be predicted with an accuracy acceptable for preliminary design purposes, particularly at the higher powers where the effects are of significant magnitude.

Differences in participation based on self-esteem in power and manual wheelchair users on a university campus: a pilot study.

PubMed

Rice, Ian M; Wong, Alex W K; Salentine, Benjamin A; Rice, Laura A

2015-03-01

To examine the relationship of self-esteem and wheelchair type with participation of young adult manual and power wheelchair users with diverse physical disabilities. Cross-sectional survey study. Large University Campus. A convenience sample of college students (N = 39) with self-reported physical disabilities who are full time wheelchair users (>40 per week) and are two or more years post illness or injury. Not applicable. The Rosenberg Self-Esteem Scale was used to measure self-esteem, and the Craig Handicap Assessment and Reporting Technique was used to measure participation. Self-esteem correlated highly with cognitive independence (CI) (r = 0.58), mobility (r = 0.67) and social integration (SI) (r = 0.52). Use of manual wheelchair was significantly related to higher levels of CI and mobility while longer use of any wheelchair (power or manual) was significantly associated with higher levels of mobility and SI. In addition higher self-esteem independently predicted a significant proportion of the variance in CI, mobility and SI, while type of wheelchair predicted a significant proportion of the variance in CI (p < 0.005). High self-esteem was found to be the strongest predictor of participation in a population of young adults with mobility limitations. Better understanding of the factors influencing participation may help to facilitate new interventions to minimize the disparities between persons with disabilities and their able bodied peers. Implication for Rehabilitation A total of 46.8% of wheelchair users report the desire for increased community participant but face significant barriers. The type of wheelchair has been identified as having a large impact on participation. This study found self-esteem to be the strongest predictor of participation, which is notable because self-esteem is a characteristic that is potentially modifiable with treatment.

CASCADE AND DAMPING OF ALFVEN-CYCLOTRON FLUCTUATIONS: APPLICATION TO SOLAR WIND TURBULENCE

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

Jiang Yanwei; Petrosian, Vahe; Liu Siming

2009-06-10

It is well recognized that the presence of magnetic fields will lead to anisotropic energy cascade and dissipation of astrophysical turbulence. With the diffusion approximation and linear dissipation rates, we study the cascade and damping of Alfven-cyclotron fluctuations in solar plasmas numerically for two diagonal diffusion tensors, one (isotropic) with identical components for the parallel and perpendicular directions (with respect to the magnetic field) and one with different components (nonisotropic). It is found that for the isotropic case the steady-state turbulence spectra are nearly isotropic in the inertial range and can be fitted by a single power-law function with amore » spectral index of -3/2, similar to the Iroshnikov-Kraichnan phenomenology, while for the nonisotropic case the spectra vary greatly with the direction of propagation. The energy fluxes in both cases are much higher in the perpendicular direction than in the parallel direction due to the angular dependence (or inhomogeneity) of the components. In addition, beyond the MHD regime the kinetic effects make the spectrum softer at higher wavenumbers. In the dissipation range the turbulence spectrum cuts off at the wavenumber, where the damping rate becomes comparable to the cascade rate, and the cutoff wavenumber changes with the wave propagation direction. The angle-averaged turbulence spectrum of the isotropic model resembles a broken power law, which cuts off at the maximum of the cutoff wavenumbers or the {sup 4}He cyclotron frequency. Taking into account the Doppler effects, the model naturally reproduces the broken power-law turbulence spectra observed in the solar wind and predicts that a higher break frequency always comes along with a softer dissipation range spectrum that may be caused by the increase of the turbulence intensity, the reciprocal of the plasma {beta}{sub p}, and/or the angle between the solar wind velocity and the mean magnetic field. These predictions can be tested by detailed comparisons with more accurate observations.« less

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

PubMed

Thé, Dwight J; Ploutz-Snyder, Lori

2003-07-01

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

Polygenic risk predicts obesity in both white and black young adults.

PubMed

Domingue, Benjamin W; Belsky, Daniel W; Harris, Kathleen Mullan; Smolen, Andrew; McQueen, Matthew B; Boardman, Jason D

2014-01-01

To test transethnic replication of a genetic risk score for obesity in white and black young adults using a national sample with longitudinal data. A prospective longitudinal study using the National Longitudinal Study of Adolescent Health Sibling Pairs (n = 1,303). Obesity phenotypes were measured from anthropometric assessments when study members were aged 18-26 and again when they were 24-32. Genetic risk scores were computed based on published genome-wide association study discoveries for obesity. Analyses tested genetic associations with body-mass index (BMI), waist-height ratio, obesity, and change in BMI over time. White and black young adults with higher genetic risk scores had higher BMI and waist-height ratio and were more likely to be obese compared to lower genetic risk age-peers. Sibling analyses revealed that the genetic risk score was predictive of BMI net of risk factors shared by siblings. In white young adults only, higher genetic risk predicted increased risk of becoming obese during the study period. In black young adults, genetic risk scores constructed using loci identified in European and African American samples had similar predictive power. Cumulative information across the human genome can be used to characterize individual level risk for obesity. Measured genetic risk accounts for only a small amount of total variation in BMI among white and black young adults. Future research is needed to identify modifiable environmental exposures that amplify or mitigate genetic risk for elevated BMI.

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.

Sound Shell Model for Acoustic Gravitational Wave Production at a First-Order Phase Transition in the Early Universe.

PubMed

Hindmarsh, Mark

2018-02-16

A model for the acoustic production of gravitational waves at a first-order phase transition is presented. The source of gravitational radiation is the sound waves generated by the explosive growth of bubbles of the stable phase. The model assumes that the sound waves are linear and that their power spectrum is determined by the characteristic form of the sound shell around the expanding bubble. The predicted power spectrum has two length scales, the average bubble separation and the sound shell width when the bubbles collide. The peak of the power spectrum is at wave numbers set by the sound shell width. For a higher wave number k, the power spectrum decreases to k^{-3}. At wave numbers below the inverse bubble separation, the power spectrum goes to k^{5}. For bubble wall speeds near the speed of sound where these two length scales are distinguished, there is an intermediate k^{1} power law. The detailed dependence of the power spectrum on the wall speed and the other parameters of the phase transition raises the possibility of their constraint or measurement at a future space-based gravitational wave observatory such as LISA.

Sound Shell Model for Acoustic Gravitational Wave Production at a First-Order Phase Transition in the Early Universe

NASA Astrophysics Data System (ADS)

Hindmarsh, Mark

2018-02-01

A model for the acoustic production of gravitational waves at a first-order phase transition is presented. The source of gravitational radiation is the sound waves generated by the explosive growth of bubbles of the stable phase. The model assumes that the sound waves are linear and that their power spectrum is determined by the characteristic form of the sound shell around the expanding bubble. The predicted power spectrum has two length scales, the average bubble separation and the sound shell width when the bubbles collide. The peak of the power spectrum is at wave numbers set by the sound shell width. For a higher wave number k , the power spectrum decreases to k-3. At wave numbers below the inverse bubble separation, the power spectrum goes to k5. For bubble wall speeds near the speed of sound where these two length scales are distinguished, there is an intermediate k1 power law. The detailed dependence of the power spectrum on the wall speed and the other parameters of the phase transition raises the possibility of their constraint or measurement at a future space-based gravitational wave observatory such as LISA.

Mitigation of Hot-Spots in Photovoltaic Systems Using Distributed Power Electronics

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

Olalla, Carlos; Hasan, Md. Nazmul; Deline, Chris

In the presence of partial shading and other mismatch factors, bypass diodes may not offer complete elimination of excessive power dissipation due to cell reverse biasing, commonly referred to as hot-spotting in photovoltaic (PV) systems. As a result, PV systems may experience higher failure rates and accelerated ageing. In this paper, a cell-level simulation model is used to assess occurrence of hot-spotting events in a representative residential rooftop system scenario featuring a moderate shading environment. The approach is further used to examine how well distributed power electronics converters mitigate the effects of partial shading and other sources of mismatch bymore » preventing activation of bypass diodes and thereby reducing the chances of heavy power dissipation and hot-spotting in mismatched cells. The simulation results confirm that the occurrence of heavy power dissipation is reduced in all distributed power electronics architectures, and that submodule-level converters offer nearly 100% mitigation of hot-spotting. In addition, the paper further elaborates on the possibility of hot-spot-induced permanent damage, predicting a lifetime energy loss above 15%. In conclusion, this energy loss is fully recoverable with submodule-level power converters that mitigate hot-spotting and prevent the damage.« less

Mitigation of Hot-Spots in Photovoltaic Systems Using Distributed Power Electronics

DOE PAGES

Olalla, Carlos; Hasan, Md. Nazmul; Deline, Chris; ...

2018-03-23

In the presence of partial shading and other mismatch factors, bypass diodes may not offer complete elimination of excessive power dissipation due to cell reverse biasing, commonly referred to as hot-spotting in photovoltaic (PV) systems. As a result, PV systems may experience higher failure rates and accelerated ageing. In this paper, a cell-level simulation model is used to assess occurrence of hot-spotting events in a representative residential rooftop system scenario featuring a moderate shading environment. The approach is further used to examine how well distributed power electronics converters mitigate the effects of partial shading and other sources of mismatch bymore » preventing activation of bypass diodes and thereby reducing the chances of heavy power dissipation and hot-spotting in mismatched cells. The simulation results confirm that the occurrence of heavy power dissipation is reduced in all distributed power electronics architectures, and that submodule-level converters offer nearly 100% mitigation of hot-spotting. In addition, the paper further elaborates on the possibility of hot-spot-induced permanent damage, predicting a lifetime energy loss above 15%. In conclusion, this energy loss is fully recoverable with submodule-level power converters that mitigate hot-spotting and prevent the damage.« less

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

PubMed

Minahan, C; Chia, M; Inbar, O

2007-10-01

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

Applying a new mammographic imaging marker to predict breast cancer risk

NASA Astrophysics Data System (ADS)

Aghaei, Faranak; Danala, Gopichandh; Hollingsworth, Alan B.; Stoug, Rebecca G.; Pearce, Melanie; Liu, Hong; Zheng, Bin

2018-02-01

Identifying and developing new mammographic imaging markers to assist prediction of breast cancer risk has been attracting extensive research interest recently. Although mammographic density is considered an important breast cancer risk, its discriminatory power is lower for predicting short-term breast cancer risk, which is a prerequisite to establish a more effective personalized breast cancer screening paradigm. In this study, we presented a new interactive computer-aided detection (CAD) scheme to generate a new quantitative mammographic imaging marker based on the bilateral mammographic tissue density asymmetry to predict risk of cancer detection in the next subsequent mammography screening. An image database involving 1,397 women was retrospectively assembled and tested. Each woman had two digital mammography screenings namely, the "current" and "prior" screenings with a time interval from 365 to 600 days. All "prior" images were originally interpreted negative. In "current" screenings, these cases were divided into 3 groups, which include 402 positive, 643 negative, and 352 biopsy-proved benign cases, respectively. There is no significant difference of BIRADS based mammographic density ratings between 3 case groups (p < 0.6). When applying the CAD-generated imaging marker or risk model to classify between 402 positive and 643 negative cases using "prior" negative mammograms, the area under a ROC curve is 0.70+/-0.02 and the adjusted odds ratios show an increasing trend from 1.0 to 8.13 to predict the risk of cancer detection in the "current" screening. Study demonstrated that this new imaging marker had potential to yield significantly higher discriminatory power to predict short-term breast cancer risk.

Remaining Useful Life Estimation of Insulated Gate Biploar Transistors (IGBTs) Based on a Novel Volterra k-Nearest Neighbor Optimally Pruned Extreme Learning Machine (VKOPP) Model Using Degradation Data

PubMed Central

Mei, Wenjuan; Zeng, Xianping; Yang, Chenglin; Zhou, Xiuyun

2017-01-01

The insulated gate bipolar transistor (IGBT) is a kind of excellent performance switching device used widely in power electronic systems. How to estimate the remaining useful life (RUL) of an IGBT to ensure the safety and reliability of the power electronics system is currently a challenging issue in the field of IGBT reliability. The aim of this paper is to develop a prognostic technique for estimating IGBTs’ RUL. There is a need for an efficient prognostic algorithm that is able to support in-situ decision-making. In this paper, a novel prediction model with a complete structure based on optimally pruned extreme learning machine (OPELM) and Volterra series is proposed to track the IGBT’s degradation trace and estimate its RUL; we refer to this model as Volterra k-nearest neighbor OPELM prediction (VKOPP) model. This model uses the minimum entropy rate method and Volterra series to reconstruct phase space for IGBTs’ ageing samples, and a new weight update algorithm, which can effectively reduce the influence of the outliers and noises, is utilized to establish the VKOPP network; then a combination of the k-nearest neighbor method (KNN) and least squares estimation (LSE) method is used to calculate the output weights of OPELM and predict the RUL of the IGBT. The prognostic results show that the proposed approach can predict the RUL of IGBT modules with small error and achieve higher prediction precision and lower time cost than some classic prediction approaches. PMID:29099811

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

The relationship between blood pressure and the structures of Pender's health promotion model in rural hypertensive patients.

PubMed

Kamran, Aziz; Azadbakht, Leila; Sharifirad, Gholamreza; Mahaki, Behzad; Mohebi, Siamak

2015-01-01

Perception is the most important predictor of behavior and there is a strong relation and correlation between behavior and believes. Thus, to improve self-care behaviors of patients, it is required to fully understand their perceptions about behavior. This paper aimed to assess the prediction power of health promotion model of systolic blood pressure (SBP) as the result of self-care behavior in rural hypertensive. This cross-sectional study has been carried out through random multistage sampling on 671 rural patients under the coverage of health center of Ardebil city in 2013. Data were collected through reliable and valid questionnaire based on the health promotion model in eight sectors. For data analysis, Pearson correlation statistical tests, multivariate linear regression, ANOVA and independent t-test were used and for confirmatory factor analysis, SPSS 18 and AMOS 18 (SPSS Inc., Chicago, IL, USA) were used. The results showed significant negative correlation between self-efficacy, perceived benefits, situational influences, affects related to behavior and commitment to action structures with SBP and showed a positive significant correlation between perceived barriers and SBP. Furthermore, age and body mass had direct significant relation with SBP. The age of patients showed inverse significant correlation with self-efficacy, perceived benefits, affects related to behavior, interpersonal influences and commitment and showed a direct significant correlation with perceived barriers, means that by increase of age, the perceived barriers also increased. The structures of health promotion model have in overall the prediction power of 71.4% of SBP changes. The diet perceptions of patients, the same as health promotion model, has good predictive power of SBP, especially the structures of perceived benefits and self-efficacy have inverse meaningful relation with systole blood pressure and predicted a higher percentage of this variable.

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 ...

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.

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.

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.

Plasma cytokines eotaxin, MIP-1α, MCP-4, and vascular endothelial growth factor in acute lower respiratory tract infection.

PubMed

Relster, Mette Marie; Holm, Anette; Pedersen, Court

2017-02-01

Major overlaps of clinical characteristics and the limitations of conventional diagnostic tests render the initial diagnosis and clinical management of pulmonary disorders difficult. In this pilot study, we analyzed the predictive value of eotaxin, macrophage inflammatory protein 1 alpha (MIP-1α), monocyte chemoattractant protein 4 (MCP-4), and vascular endothelial growth factor (VEGF) in 40 patients hospitalized with acute lower respiratory tract infections (LRTI). The cytokines contribute to the pathogenesis of several inflammatory respiratory diseases, indicating a potential as markers for LRTI. Patients were stratified according to etiology and severity of LRTI, based on baseline C-reactive protein and CURB-65 scores. Using a multiplex immunoassay of plasma, levels of eotaxin and MCP-4 were shown to increase from baseline until day 6 after admission to hospital. The four cytokines were unable to predict the etiology and severity. Eotaxin and MCP-4 were significantly lower in patients with C-reactive protein ≥100, and MIP-1α was significantly higher in the patients with CURB-65 > 3, but the predictive power was low. In conclusion, further evaluation, including more patients, is required to assess the full potential of eotaxin, MCP-4, MIP-1α, and VEGF as biomarkers for LRTI because of their low predictive power and a high interindividual variation of cytokine levels. © 2016 APMIS. Published by John Wiley & Sons Ltd.

Enhanced power factor of higher manganese silicide via melt spin synthesis method

DOE PAGES

Shi, Xiaoya; Shi, Xun; Li, Yulong; ...

2014-12-30

We report on the thermoelectric properties of the Higher Manganese Silicide MnSi₁.₇₅ (HMS) synthesized by means of a one-step non-equilibrium method. The ultrahigh cooling rate generated from the melt-spin technique is found to be effective in reducing second phases, which are inevitable during the traditional solid state diffusion processes. Aside from being detrimental to thermoelectric properties, second phases skew the revealing of the intrinsic properties of this class of materials, for example the optimal level of carrier concentration. With this melt-spin sample, we are able to formulate a simple model based on a single parabolic band that can well describemore » the carrier concentration dependence of the Seebeck coefficient and power factor of the data reported in the literature. An optimal carrier concentration around 5x10²⁰ cm⁻³ at 300 K is predicted according to this model. The phase-pure melt-spin sample shows the largest power factor at high temperature, resulting in the highest zT value among the three samples in this paper; the maximum value is superior to those reported in the literatures.« less

Enhanced power factor of higher manganese silicide via melt spin synthesis method

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

Shi, Xiaoya; Shi, Xun; Li, Yulong

We report on the thermoelectric properties of the Higher Manganese Silicide MnSi₁.₇₅ (HMS) synthesized by means of a one-step non-equilibrium method. The ultrahigh cooling rate generated from the melt-spin technique is found to be effective in reducing second phases, which are inevitable during the traditional solid state diffusion processes. Aside from being detrimental to thermoelectric properties, second phases skew the revealing of the intrinsic properties of this class of materials, for example the optimal level of carrier concentration. With this melt-spin sample, we are able to formulate a simple model based on a single parabolic band that can well describemore » the carrier concentration dependence of the Seebeck coefficient and power factor of the data reported in the literature. An optimal carrier concentration around 5x10²⁰ cm⁻³ at 300 K is predicted according to this model. The phase-pure melt-spin sample shows the largest power factor at high temperature, resulting in the highest zT value among the three samples in this paper; the maximum value is superior to those reported in the literatures.« less

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

PubMed

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

2014-08-01

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

Decision-making, sensitivity to reward, and attrition in weight-management

PubMed Central

Koritzky, Gilly; Dieterle, Camille; Rice, Chantelle; Jordan, Katie; Bechara, Antoine

2014-01-01

Objective Attrition is a common problem in weight-management. Understanding the risk factors for attrition should enhance professionals’ ability to increase completion rates and improve health outcomes for more individuals. We propose a model that draws upon neuropsychological knowledge on reward-sensitivity in obesity and overeating to predict attrition. Design & Methods 52 participants in a weight-management program completed a complex decision-making task.Decision-making characteristics – including sensitivity to reward – were further estimated using a quantitative model. Impulsivity and risk-taking measures were also administered. Results Consistent with the hypothesis that sensitivity to reward predicted attrition, program dropouts had higher sensitivity to reward than completers (p < 0.03). No differences were observed between completers and dropouts in initial BMI, age, employment status, or the number of prior weight-loss attempts (p ≥ 0.07). Completers had a slightly higher education level than dropouts, but its inclusion in the model did not increase predictive power. Impulsivity, delay of gratification, and risk-taking did not predict attrition, either. Conclusions Findings link attrition in weight-management to the neural mechanisms associated with reward-seeking and related influences on decision-making. Individual differences in the magnitude of response elicited by rewards may account for the relative difficulty experienced by dieters in adhering to treatment. PMID:24771588

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.

Optimal pitching axis location of flapping wings for efficient hovering flight.

PubMed

Wang, Q; Goosen, J F L; van Keulen, F

2017-09-01

Flapping wings can pitch passively about their pitching axes due to their flexibility, inertia, and aerodynamic loads. A shift in the pitching axis location can dynamically alter the aerodynamic loads, which in turn changes the passive pitching motion and the flight efficiency. Therefore, it is of great interest to investigate the optimal pitching axis for flapping wings to maximize the power efficiency during hovering flight. In this study, flapping wings are modeled as rigid plates with non-uniform mass distribution. The wing flexibility is represented by a linearly torsional spring at the wing root. A predictive quasi-steady aerodynamic model is used to evaluate the lift generated by such wings. Two extreme power consumption scenarios are modeled for hovering flight, i.e. the power consumed by a drive system with and without the capacity of kinetic energy recovery. For wings with different shapes, the optimal pitching axis location is found such that the cycle-averaged power consumption during hovering flight is minimized. Optimization results show that the optimal pitching axis is located between the leading edge and the mid-chord line, which shows close resemblance to insect wings. An optimal pitching axis can save up to 33% of power during hovering flight when compared to traditional wings used by most of flapping wing micro air vehicles (FWMAVs). Traditional wings typically use the straight leading edge as the pitching axis. With the optimized pitching axis, flapping wings show higher pitching amplitudes and start the pitching reversals in advance of the sweeping reversals. These phenomena lead to higher lift-to-drag ratios and, thus, explain the lower power consumption. In addition, the optimized pitching axis provides the drive system higher potential to recycle energy during the deceleration phases as compared to their counterparts. This observation underlines the particular importance of the wing pitching axis location for energy-efficient FWMAVs when using kinetic energy recovery drive systems.

Power-constrained supercomputing

NASA Astrophysics Data System (ADS)

Bailey, Peter E.

As we approach exascale systems, power is turning from an optimization goal to a critical operating constraint. With power bounds imposed by both stakeholders and the limitations of existing infrastructure, achieving practical exascale computing will therefore rely on optimizing performance subject to a power constraint. However, this requirement should not add to the burden of application developers; optimizing the runtime environment given restricted power will primarily be the job of high-performance system software. In this dissertation, we explore this area and develop new techniques that extract maximum performance subject to a particular power constraint. These techniques include a method to find theoretical optimal performance, a runtime system that shifts power in real time to improve performance, and a node-level prediction model for selecting power-efficient operating points. We use a linear programming (LP) formulation to optimize application schedules under various power constraints, where a schedule consists of a DVFS state and number of OpenMP threads for each section of computation between consecutive message passing events. We also provide a more flexible mixed integer-linear (ILP) formulation and show that the resulting schedules closely match schedules from the LP formulation. Across four applications, we use our LP-derived upper bounds to show that current approaches trail optimal, power-constrained performance by up to 41%. This demonstrates limitations of current systems, and our LP formulation provides future optimization approaches with a quantitative optimization target. We also introduce Conductor, a run-time system that intelligently distributes available power to nodes and cores to improve performance. The key techniques used are configuration space exploration and adaptive power balancing. Configuration exploration dynamically selects the optimal thread concurrency level and DVFS state subject to a hardware-enforced power bound. Adaptive power balancing efficiently predicts where critical paths are likely to occur and distributes power to those paths. Greater power, in turn, allows increased thread concurrency levels, CPU frequency/voltage, or both. We describe these techniques in detail and show that, compared to the state-of-the-art technique of using statically predetermined, per-node power caps, Conductor leads to a best-case performance improvement of up to 30%, and an average improvement of 19.1%. At the node level, an accurate power/performance model will aid in selecting the right configuration from a large set of available configurations. We present a novel approach to generate such a model offline using kernel clustering and multivariate linear regression. Our model requires only two iterations to select a configuration, which provides a significant advantage over exhaustive search-based strategies. We apply our model to predict power and performance for different applications using arbitrary configurations, and show that our model, when used with hardware frequency-limiting in a runtime system, selects configurations with significantly higher performance at a given power limit than those chosen by frequency-limiting alone. When applied to a set of 36 computational kernels from a range of applications, our model accurately predicts power and performance; our runtime system based on the model maintains 91% of optimal performance while meeting power constraints 88% of the time. When the runtime system violates a power constraint, it exceeds the constraint by only 6% in the average case, while simultaneously achieving 54% more performance than an oracle. Through the combination of the above contributions, we hope to provide guidance and inspiration to research practitioners working on runtime systems for power-constrained environments. We also hope this dissertation will draw attention to the need for software and runtime-controlled power management under power constraints at various levels, from the processor level to the cluster level.

Continuous glucose determination using fiber-based tunable mid-infrared laser spectroscopy

NASA Astrophysics Data System (ADS)

Yu, Songlin; Li, Dachao; Chong, Hao; Sun, Changyue; Xu, Kexin

2014-04-01

Wavelength-tunable laser spectroscopy in combination with a small-sized fiber-optic attenuated total reflection (ATR) sensor (fiber-based evanescent field analysis, FEFA) is reported for the continuous measurement of the glucose level. We propose a method of controlling and stabilizing the wavelength and power of laser emission and present a newly developed mid-infrared wavelength-tunable laser with a broad emission spectrum band of 9.19-9.77 μm (1024-1088 cm-1). The novel small-sized flow-through fiber-optic ATR sensor with long optical sensing length was used for glucose level determination. The experimental results indicate that the noise-equivalent concentration of this laser measurement system is as low as 3.8 mg/dL, which is among the most precise glucose measurements using mid-infrared spectroscopy. The sensitivity, which is three times that of conventional Fourier transform infrared spectrometer, was acquired because of the higher laser power and higher spectral resolution. The best prediction of the glucose concentration in phosphate buffered saline solution was achieved using the five-variable partial least-squares model, yielding a root-mean-square error of prediction as small as 3.5 mg/dL. The high sensitivity, multiple tunable wavelengths and small fiber-based sensor with long optical sensing length make glucose determination possible in blood or interstitial fluid in vivo.

Application of Landsat Thematic Mapper data for coastal thermal plume analysis at Diablo Canyon

NASA Technical Reports Server (NTRS)

Gibbons, D. E.; Wukelic, G. E.; Leighton, J. P.; Doyle, M. J.

1989-01-01

The possibility of using Landsat Thematic Mapper (TM) thermal data to derive absolute temperature distributions in coastal waters that receive cooling effluent from a power plant is demonstrated. Landsat TM band 6 (thermal) data acquired on June 18, 1986, for the Diablo Canyon power plant in California were compared to ground truth temperatures measured at the same time. Higher-resolution band 5 (reflectance) data were used to locate power plant discharge and intake positions and identify locations of thermal pixels containing only water, no land. Local radiosonde measurements, used in LOWTRAN 6 adjustments for atmospheric effects, produced corrected ocean surface radiances that, when converted to temperatures, gave values within approximately 0.6 C of ground truth. A contour plot was produced that compared power plant plume temperatures with those of the ocean and coastal environment. It is concluded that Landsat can provide good estimates of absolute temperatures of the coastal power plant thermal plume. Moreover, quantitative information on ambient ocean surface temperature conditions (e.g., upwelling) may enhance interpretation of numerical model prediction.

Condensed Matter Cluster Reactions in LENR Power Cells for a Radical New Type of Space Power Source

NASA Astrophysics Data System (ADS)

Yang, Xiaoling; Miley, George H.; Hora, Heinz

2009-03-01

This paper reviews previous theoretical and experimental study on the possibility of nuclear events in multilayer thin film electrodes (Lipson et al., 2004 and 2005; Miley et al., 2007), including the correlation between excess heat and transmutations (Miley and Shrestha, 2003) and the cluster theory that predicts it. As a result of this added understanding of cluster reactions, a new class of electrodes is under development at the University of Illinois. These electrodes are designed to enhance cluster formation and subsequent reactions. Two approaches are under development. The first employs improved loading-unloading techniques, intending to obtain a higher volumetric density of sites favoring cluster formation. The second is designed to create nanostructures on the electrode where the cluster state is formed by electroless deposition of palladium on nickel micro structures. Power units employing these electrodes should offer unique advantages for space applications. This is a fundamental new nuclear energy source that is environmentally compatible with a minimum of radiation involvement, high specific power, very long lifetime, and scalable from micro power to kilowatts.

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

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.

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.

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.

Prediction of Vertical Jump Height from Anthropometric Factors in Male and Female Martial Arts Athletes

PubMed Central

Abidin, Nahdiya Zainal; Adam, Mohd Bakri

2013-01-01

Background: Vertical jump is an index representing leg/kick power. The explosive movement of the kick is the key to scoring in martial arts competitions. It is important to determine factors that influence the vertical jump to help athletes improve their leg power. The objective of the present study is to identify anthropometric factors that influence vertical jump height for male and female martial arts athletes. Methods: Twenty-nine male and 25 female athletes participated in this study. Participants were Malaysian undergraduate students whose ages ranged from 18 to 24 years old. Their heights were measured using a stadiometer. The subjects were weighted using digital scale. Body mass index was calculated by kg/m2. Waist–hip ratio was measured from the ratio of waist to hip circumferences. Body fat % was obtained from the sum of four skinfold thickness using Harpenden callipers. The highest vertical jump from a stationary standing position was recorded. The maximum grip was recorded using a dynamometer. For standing back strength, the maximum pull upwards using a handle bar was recorded. Multiple linear regression was used to obtain the relationship between vertical jump height and explanatory variables with gender effect. Results: Body fat % has a significant negative relationship with vertical jump height (P < 0.001). The effect of gender is significant (P < 0.001): on average, males jumped 26% higher than females did. Conclusion: Vertical jump height of martial arts athletes can be predicted by body fat %. The vertical jump for male is higher than for their female counterparts. Reducing body fat by proper dietary planning will help to improve leg power. PMID:23785254

Ranking low, feeling high: How hierarchical position and experienced power promote prosocial behavior in response to procedural justice.

PubMed

van Dijke, Marius; De Cremer, David; Langendijk, Gerben; Anderson, Cameron

2018-02-01

Research shows that power can lead to prosocial behavior by facilitating the behavioral expression of dispositional prosocial motivation. However, it is not clear how power may facilitate responses to contextual factors that promote prosocial motivation. Integrating fairness heuristic theory and the situated focus theory of power, we argue that in particular, organization members in lower (vs. higher) hierarchical positions who simultaneously experience a high (vs. low) sense of power respond with prosocial behavior to 1 important antecedent of prosocial motivation, that is, the enactment of procedural justice. The results from a multisource survey among employees and their leaders from various organizations (Study 1) and an experiment using a public goods dilemma (Study 2) support this prediction. Three subsequent experiments (Studies 3-5) show that this effect is mediated by perceptions of authority trustworthiness. Taken together, this research (a) helps resolve the debate regarding whether power promotes or undermines prosocial behavior, (b) demonstrates that hierarchical position and the sense of power can have very different effects on processes that are vital to the functioning of an organization, and (c) helps solve ambiguity regarding the roles of hierarchical position and power in fairness heuristic theory. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Operation of a sub-terahertz CW gyrotron with an extremely low voltage

NASA Astrophysics Data System (ADS)

Bratman, V. L.; Fedotov, A. E.; Fokin, A. P.; Glyavin, M. Yu.; Manuilov, V. N.; Osharin, I. V.

2017-11-01

Decreasing the operating voltage for medium-power sub-terahertz gyrotrons aimed at industrial and scientific applications is highly attractive, since it allows size and cost reduction of the tubes and power supply units. In this paper, we examine such an opportunity both numerically and experimentally for the fundamental cyclotron resonance operation of an existing gyrotron initially designed for operation at the second cyclotron harmonic with a relatively high voltage. Simulations predict that output power higher than 10 W can be produced at the fundamental harmonic at voltages less than 2 kV. To form a low-voltage helical electron beam with a sufficiently large pitch-factor, a positive voltage was applied to the first anode of the gyrotron three-electrode magnetron-injection gun with a negative voltage at the cathode. CW gyrotron operation at voltages down to 1.5 kV has been demonstrated at a frequency about of 256 GHz.

Influences of Atmospheric Stability State on Wind Turbine Aerodynamic Loadings

NASA Astrophysics Data System (ADS)

Vijayakumar, Ganesh; Lavely, Adam; Brasseur, James; Paterson, Eric; Kinzel, Michael

2011-11-01

Wind turbine power and loadings are influenced by the structure of atmospheric turbulence and thus on the stability state of the atmosphere. Statistical differences in loadings with atmospheric stability could impact controls, blade design, etc. Large-eddy simulation (LES) of the neutral and moderately convective atmospheric boundary layer (NBL, MCBL) are used as inflow to the NREL FAST advanced blade-element momentum theory code to predict wind turbine rotor power, sectional lift and drag, blade bending moments and shaft torque. Using horizontal homogeneity, we combine time and ensemble averages to obtain converged statistics equivalent to ``infinite'' time averages over a single turbine. The MCBL required longer effective time periods to obtain converged statistics than the NBL. Variances and correlation coefficients among wind velocities, turbine power and blade loadings were higher in the MCBL than the NBL. We conclude that the stability state of the ABL strongly influences wind turbine performance. Supported by NSF and DOE.

Cosmological perturbation theory using the FFTLog: formalism and connection to QFT loop integrals

NASA Astrophysics Data System (ADS)

Simonović, Marko; Baldauf, Tobias; Zaldarriaga, Matias; Carrasco, John Joseph; Kollmeier, Juna A.

2018-04-01

We present a new method for calculating loops in cosmological perturbation theory. This method is based on approximating a ΛCDM-like cosmology as a finite sum of complex power-law universes. The decomposition is naturally achieved using an FFTLog algorithm. For power-law cosmologies, all loop integrals are formally equivalent to loop integrals of massless quantum field theory. These integrals have analytic solutions in terms of generalized hypergeometric functions. We provide explicit formulae for the one-loop and the two-loop power spectrum and the one-loop bispectrum. A chief advantage of our approach is that the difficult part of the calculation is cosmology independent, need be done only once, and can be recycled for any relevant predictions. Evaluation of standard loop diagrams then boils down to a simple matrix multiplication. We demonstrate the promise of this method for applications to higher multiplicity/loop correlation functions.

Outdoor Performance of a Thin-Film Gallium-Arsenide Photovoltaic Module

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

Silverman, T. J.; Deceglie, M. G.; Marion, B.

2013-06-01

We deployed a 855 cm2 thin-film, single-junction gallium arsenide (GaAs) photovoltaic (PV) module outdoors. Due to its fundamentally different cell technology compared to silicon (Si), the module responds differently to outdoor conditions. On average during the test, the GaAs module produced more power when its temperature was higher. We show that its maximum-power temperature coefficient, while actually negative, is several times smaller in magnitude than that of a Si module used for comparison. The positive correlation of power with temperature in GaAs is due to temperature-correlated changes in the incident spectrum. We show that a simple correction based on precipitablemore » water vapor (PWV) brings the photocurrent temperature coefficient into agreement with that measured by other methods and predicted by theory. The low operating temperature and small temperature coefficient of GaAs give it an energy production advantage in warm weather.« less

The Solar Array Photovoltaic Assembly for the INSAT 4CR Spacecraft Design, Development and In-Orbit Performance

NASA Astrophysics Data System (ADS)

Thomas, Joseph; Sudhakar, M.; Agarwal, Anil; Sankaran, M.; Mudramachary, P.

2008-09-01

The INSAT 4CR spacecraft, the third in the INSAT 4 series of Indian Space Research Organization (ISRO)'s Communication satellite program, is a high power communication satellite in Geo- stationary Earth Orbit (GEO), configured using the ISRO I2K bus. The primary power is provided by two-wing sun tracking, deployable solar array and the eclipse load requirement is supported by two 70 Ah nickel hydrogen batteries. The power output of the solar array is regulated by Sequential Switching Shunt Regulators to 42V±0.5V. The salient feature of the solar array design is that it uses the new generation multi junction solar cells for all the four panels of size 2.54m x 1.525m to meet the higher power requirement with the available array area. The solar panel fabrication process with the Advanced Triple Junction (ATJ) solar cells from M/s. EMCORE, USA, has been demonstrated for the GEO life cycle through qualification coupon fabrication and testing.This paper describes the INSAT 4CR solar array photovoltaic assemblies design, layout optimization and realization of the Flight Model (FM) panels. It focuses on the power generation prediction, electrical performance measurement under Large Area Pulsed Sun Simulator (LAPSS) and verification of the ground level test results. The indigenously built Geostationary Launch Vehicle (GSLV F04) has successfully launched the INSAT 4CR spacecraft into the orbit on September 2nd, 2007. This paper also presents the analysis of telemetry data to validate the initial phase in-orbit performance of the solar array with prediction.

Do Jews and Arabs Differ in Their Fear of Terrorism and Crime?

PubMed

Shechory Bitton, Mally; Silawi, Yousef

2016-10-01

The current study was carried out with the aim of supplementing the existing literature and broadening the understanding of the determinants of two powerful types of fear, fear of terrorism and fear of crime, by comparing their presence among Jews and Arabs in Israel. Based on an overview of factors influencing fear of victimization, the study focused on individual variables (ethnicity, sex, age, objective, and subjective exposure) as well as on neighborhood disorder and social integration. The sample consisted of 375 Israeli students (191 Jews and 184 Arabs). Predictions of fear of terrorism and crime were conducted with two multiple regressions. Fear of terrorism was significantly predicted by gender (women more than men), higher self exposure to terror, and higher neighborhood disorder. The only interaction found with regard to exposure to incidents showed that previous victimization predicts only fear of terrorism and only among Arabs who were themselves affected or exposed to the victimization of others. Fear of crime was predicted by sector (Jews more than Arabs), gender (women more than men), higher neighborhood disorder, and lower social integration. As far as known, this is the first attempt to examine differences between Jews and Arabs with regard to these two types of fear and to predict their causes. The findings help gain a better understanding as to how people perceive the threat of crime and terrorism, in general and in the Arab-Jewish context in particular. The findings also enable an understanding of the complexity of living under ongoing terrorism threats. The results are discussed in accordance with the literature, concluding with the need for further research that will take into account the wider cultural and social context.

Scaling of oxidative and glycolytic enzymes in mammals.

PubMed

Emmett, B; Hochachka, P W

1981-09-01

The catalytic activities of several oxidative and glycolytic enzymes were determined in the gastrocnemius muscle of 10 mammalian species differing in body weight by nearly 6 orders of magnitude. When expressed in terms of units gm-1, the activities of enzymes functioning in oxidative metabolism (citrate synthase, beta-hydroxybutyrylCoA dehydrogenase, and malate dehydrogenase) decrease as body weight increases. Log-log plots (activity gm-1 vs body mass) yield straight lines with negative slopes that are less than the allometric exponent (-0.25) typically observed for basal metabolic rates. Since the amount of power a muscle can generate depends upon the catalytic potential of its enzyme machinery (the higher the catalytic potential the higher the maximum rate of energy generation), these data predict that the scope for aerobic activity in large mammals should be greater than in small mammals if nothing else becomes limiting, a result in fact recently obtained by Taylor et al. (Respir. Physiol., 1981). In contrast to the scaling of oxidative enzymes, the activities of enzymes functioning in anaerobic glycogenolysis (glycogen phosphorylase, pyruvate kinase, and lactate dehydrogenase) increase as body size increases. Log-log plots (activity gm-1 vs body mass) display a positive slope indicating that the larger the animal the higher the glycolytic potential of its skeletal muscles. This unexpected result may indicate higher relative power costs for burst type locomotion in larger mammals, which is in fact observed in within-species studies of man. However, the scaling of anaerobic muscle power has not been closely assessed in between-species comparisons of mammals varying greatly in body size.

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 ...

Plasma superoxide dismutase-1 as a surrogate marker of vivax malaria severity.

PubMed

Andrade, Bruno B; Reis-Filho, Antonio; Souza-Neto, Sebastião Martins; Raffaele-Netto, Imbroinise; Camargo, Luis M A; Barral, Aldina; Barral-Netto, Manoel

2010-04-06

Severe outcomes have been described for both Plasmodium falciparum and P. vivax infections. The identification of sensitive and reliable markers of disease severity is fundamental to improving patient care. An intense pro-inflammatory response with oxidative stress and production of reactive oxygen species is present in malaria. Inflammatory cytokines such as tumor necrosis factor-alpha (TNF-alpha) and antioxidant agents such as superoxide dismutase-1 (SOD-1) are likely candidate biomarkers for disease severity. Here we tested whether plasma levels of SOD-1 could serve as a biomarker of severe vivax malaria. Plasma samples were obtained from residents of the Brazilian Amazon with a high risk for P. vivax transmission. Malaria diagnosis was made by both microscopy and nested PCR. A total of 219 individuals were enrolled: non-infected volunteers (n = 90) and individuals with vivax malaria: asymptomatic (n = 60), mild (n = 50) and severe infection (n = 19). SOD-1 was directly associated with parasitaemia, plasma creatinine and alanine amino-transaminase levels, while TNF-alpha correlated only with the later enzyme. The predictive power of SOD-1 and TNF-alpha levels was compared. SOD-1 protein levels were more effective at predicting vivax malaria severity than TNF-alpha. For discrimination of mild infection, elevated SOD-1 levels showed greater sensitivity than TNF-alpha (76% vs. 30% respectively; p<0.0001), with higher specificity (100% vs. 97%; p<0.0001). In predicting severe vivax malaria, SOD-1 levels exhibited higher sensitivity than TNF-alpha (80% vs. 56%, respectively; p<0.0001; likelihood ratio: 7.45 vs. 3.14; p<0.0001). Neither SOD-1 nor TNF-alpha could discriminate P. vivax infections from those caused by P. falciparum. SOD-1 is a powerful predictor of disease severity in individuals with different clinical presentations of vivax malaria.

Acceleration of low-energy ions at parallel shocks with a focused transport model

DOE PAGES

Zuo, Pingbing; Zhang, Ming; Rassoul, Hamid K.

2013-04-10

Here, we present a test particle simulation on the injection and acceleration of low-energy suprathermal particles by parallel shocks with a focused transport model. The focused transport equation contains all necessary physics of shock acceleration, but avoids the limitation of diffusive shock acceleration (DSA) that requires a small pitch angle anisotropy. This simulation verifies that the particles with speeds of a fraction of to a few times the shock speed can indeed be directly injected and accelerated into the DSA regime by parallel shocks. At higher energies starting from a few times the shock speed, the energy spectrum of acceleratedmore » particles is a power law with the same spectral index as the solution of standard DSA theory, although the particles are highly anisotropic in the upstream region. The intensity, however, is different from that predicted by DSA theory, indicating a different level of injection efficiency. It is found that the shock strength, the injection speed, and the intensity of an electric cross-shock potential (CSP) jump can affect the injection efficiency of the low-energy particles. A stronger shock has a higher injection efficiency. In addition, if the speed of injected particles is above a few times the shock speed, the produced power-law spectrum is consistent with the prediction of standard DSA theory in both its intensity and spectrum index with an injection efficiency of 1. CSP can increase the injection efficiency through direct particle reflection back upstream, but it has little effect on the energetic particle acceleration once the speed of injected particles is beyond a few times the shock speed. This test particle simulation proves that the focused transport theory is an extension of DSA theory with the capability of predicting the efficiency of particle injection.« less

Do resting brain dynamics predict oddball evoked-potential?

PubMed Central

2011-01-01

Background The oddball paradigm is widely applied to the investigation of cognitive function in neuroscience and in neuropsychiatry. Whether cortical oscillation in the resting state can predict the elicited oddball event-related potential (ERP) is still not clear. This study explored the relationship between resting electroencephalography (EEG) and oddball ERPs. The regional powers of 18 electrodes across delta, theta, alpha and beta frequencies were correlated with the amplitude and latency of N1, P2, N2 and P3 components of oddball ERPs. A multivariate analysis based on partial least squares (PLS) was applied to further examine the spatial pattern revealed by multiple correlations. Results Higher synchronization in the resting state, especially at the alpha spectrum, is associated with higher neural responsiveness and faster neural propagation, as indicated by the higher amplitude change of N1/N2 and shorter latency of P2. None of the resting quantitative EEG indices predict P3 latency and amplitude. The PLS analysis confirms that the resting cortical dynamics which explains N1/N2 amplitude and P2 latency does not show regional specificity, indicating a global property of the brain. Conclusions This study differs from previous approaches by relating dynamics in the resting state to neural responsiveness in the activation state. Our analyses suggest that the neural characteristics carried by resting brain dynamics modulate the earlier/automatic stage of target detection. PMID:22114868

Improving satellite-driven PM2.5 models with Moderate Resolution Imaging Spectroradiometer fire counts in the southeastern U.S.

PubMed

Hu, Xuefei; Waller, Lance A; Lyapustin, Alexei; Wang, Yujie; Liu, Yang

2014-10-16

Multiple studies have developed surface PM 2.5 (particle size less than 2.5 µm in aerodynamic diameter) prediction models using satellite-derived aerosol optical depth as the primary predictor and meteorological and land use variables as secondary variables. To our knowledge, satellite-retrieved fire information has not been used for PM 2.5 concentration prediction in statistical models. Fire data could be a useful predictor since fires are significant contributors of PM 2.5 . In this paper, we examined whether remotely sensed fire count data could improve PM 2.5 prediction accuracy in the southeastern U.S. in a spatial statistical model setting. A sensitivity analysis showed that when the radius of the buffer zone centered at each PM 2.5 monitoring site reached 75 km, fire count data generally have the greatest predictive power of PM 2.5 across the models considered. Cross validation (CV) generated an R 2 of 0.69, a mean prediction error of 2.75 µg/m 3 , and root-mean-square prediction errors (RMSPEs) of 4.29 µg/m 3 , indicating a good fit between the dependent and predictor variables. A comparison showed that the prediction accuracy was improved more substantially from the nonfire model to the fire model at sites with higher fire counts. With increasing fire counts, CV RMSPE decreased by values up to 1.5 µg/m 3 , exhibiting a maximum improvement of 13.4% in prediction accuracy. Fire count data were shown to have better performance in southern Georgia and in the spring season due to higher fire occurrence. Our findings indicate that fire count data provide a measurable improvement in PM 2.5 concentration estimation, especially in areas and seasons prone to fire events.

QSAR Modeling of Rat Acute Toxicity by Oral Exposure

PubMed Central

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

2009-01-01

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

Improving satellite-driven PM2.5 models with Moderate Resolution Imaging Spectroradiometer fire counts in the southeastern U.S

PubMed Central

Hu, Xuefei; Waller, Lance A.; Lyapustin, Alexei; Wang, Yujie; Liu, Yang

2017-01-01

Multiple studies have developed surface PM2.5 (particle size less than 2.5 µm in aerodynamic diameter) prediction models using satellite-derived aerosol optical depth as the primary predictor and meteorological and land use variables as secondary variables. To our knowledge, satellite-retrieved fire information has not been used for PM2.5 concentration prediction in statistical models. Fire data could be a useful predictor since fires are significant contributors of PM2.5. In this paper, we examined whether remotely sensed fire count data could improve PM2.5 prediction accuracy in the southeastern U.S. in a spatial statistical model setting. A sensitivity analysis showed that when the radius of the buffer zone centered at each PM2.5 monitoring site reached 75 km, fire count data generally have the greatest predictive power of PM2.5 across the models considered. Cross validation (CV) generated an R2 of 0.69, a mean prediction error of 2.75 µg/m3, and root-mean-square prediction errors (RMSPEs) of 4.29 µg/m3, indicating a good fit between the dependent and predictor variables. A comparison showed that the prediction accuracy was improved more substantially from the nonfire model to the fire model at sites with higher fire counts. With increasing fire counts, CV RMSPE decreased by values up to 1.5 µg/m3, exhibiting a maximum improvement of 13.4% in prediction accuracy. Fire count data were shown to have better performance in southern Georgia and in the spring season due to higher fire occurrence. Our findings indicate that fire count data provide a measurable improvement in PM2.5 concentration estimation, especially in areas and seasons prone to fire events. PMID:28967648

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

PubMed

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

2009-12-01

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

Building human capital to increase earning power among people living with mental illnesses.

PubMed

Gao, Ni; Schmidt, Lisa T; Gill, Kenneth J; Pratt, Carlos W

2011-01-01

Human Capital Theory, a well-established model from the field of economics, maintains that a person's lifetime earnings are affected by the amount of education and job training they receive. This study uses Human Capital Theory to predict wages and explain employment outcomes among individuals living with psychiatric illnesses. Hourly wages were examined between 100 individuals with mental illnesses and 100 matched comparisons who had no mental illnesses. The study found that participants with mental illnesses earned $12.19 an hour vs. $14.54 an hour earned by their counterparts without disability. The study also revealed that higher educational attainment and longer work history predicted higher wages among participants with mental illnesses. The severity of psychiatric symptoms and diagnosis, however, did not predict wages. These findings indicate that human capital variables are correlated with wages earned by persons living with mental illnesses. Findings also suggest that assisting mental health consumers in the pursuit of education and job training may increase earning potential which can lead to financial independence and community integration. This supports the value in developing and implementing Supported Education to assist consumers in acquiring education and job training.

INTER-GENERATIONAL RELATIONSHIPS BETWEEN WOMEN’S FERTILITY, ASPIRATIONS FOR THEIR CHILDREN’S EDUCATION AND SCHOOL COMPLETION IN THE PHILIPPINES

PubMed Central

GIPSON, JESSICA D.; HINDIN, MICHELLE J.

2015-01-01

Summary Women’s education is associated with positive social and health outcomes for women and their families, as well as greater opportunities and decision-making power for women. An extensive literature documents ways in which broader, societal changes have facilitated roles for women beyond reproduction, yet there is minimal exploration at the family level. This study used inter-generational cohort data from the Philippines to examine mothers’ aspirations for their children’s education, and how these aspirations predict children’s subsequent educational attainment. Mothers’ education, household wealth and a locally developed measure of women’s status were positively associated with higher educational aspirations for children; however, only mothers with the highest fertility were less likely to desire their children to attend college or higher. Mothers’ fertility and aspirations both significantly and independently predicted children’s school completion. Together, these findings indicate that increased opportunities for Filipina women beyond childbearing may not only positively benefit these women themselves, but also future generations. PMID:25488276

The role of imperfect surrogate endpoint information in drug approval and reimbursement decisions.

PubMed

Bognar, Katalin; Romley, John A; Bae, Jay P; Murray, James; Chou, Jacquelyn W; Lakdawalla, Darius N

2017-01-01

Approval of new drugs is increasingly reliant on "surrogate endpoints," which correlate with but imperfectly predict clinical benefits. Proponents argue surrogate endpoints allow for faster approval, but critics charge they provide inadequate evidence. We develop an economic framework that addresses the value of improvement in the predictive power, or "quality," of surrogate endpoints, and clarifies how quality can influence decisions by regulators, payers, and manufacturers. For example, the framework shows how lower-quality surrogates lead to greater misalignment of incentives between payers and regulators, resulting in more drugs that are approved for use but not covered by payers. Efficient price-negotiation in the marketplace can help align payer incentives for granting access based on surrogates. Higher-quality surrogates increase manufacturer profits and social surplus from early access to new drugs. Since the return on better quality is shared between manufacturers and payers, private incentives to invest in higher-quality surrogates are inefficiently low. Copyright © 2016 The Author(s). Published by Elsevier B.V. All rights reserved.

Dynamical electrical conductivity of graphene

NASA Astrophysics Data System (ADS)

Rani, Luxmi; Singh, Navinder

2017-06-01

For graphene (a Dirac material) it has been theoretically predicted and experimentally observed that DC resistivity is proportional to T 4 when the temperature is much less than Bloch-Grüneisen temperature ({{ \\Theta }\\text{BG}} ) and T-linear in the opposite case (T\\gg {{ \\Theta }\\text{BG}} ). Going beyond this case, we investigate the dynamical electrical conductivity in graphene using the powerful method of the memory function formalism. In the zero frequency regime, we obtain the above mentioned behavior which was previously obtained using the Bloch-Boltzmann kinetic equation. In the finite frequency regime, we obtain several new results: (1) the generalized Drude scattering rate, in the zero temperature limit, shows {ω4} behavior at low frequencies (ω \\ll {{k}\\text{B}}{{ \\Theta }\\text{BG}}/\\hbar ) and saturates at higher frequencies. We also observed the Holstein mechanism, however, with different power laws from that in the case of metals; (2) at higher frequencies, ω \\gg {{k}\\text{B}}{{ \\Theta }\\text{BG}}/\\hbar , and higher temperatures T\\gg {{ \\Theta }\\text{BG}} , we observed that the generalized Drude scattering rate is linear in temperature. In addition, several other results are also obtained. With the experimental advancement of this field, these results should be experimentally tested.

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.

Noninvasive Uterine Electromyography For Prediction of Preterm Delivery*

PubMed Central

UCOVNIK, Miha L; MANER, William L.; CHAMBLISS, Linda R.; BLUMRICK, Richard; BALDUCCI, James; NOVAK-ANTOLIC, Ziva; GARFIELD, Robert E.

2011-01-01

Objective Power spectrum (PS) of uterine electromyography (EMG) can identify true labor. EMG propagation velocity (PV) to diagnose labor has not been reported. The objective was to compare uterine EMG against current methods to predict preterm delivery. Study design EMG was recorded in 116 patients (preterm labor, n=20; preterm non-labor, n=68; term labor, n=22; term non-labor, n=6). Student’s t-test was used to compare EMG values for labor vs. non-labor (P<0.05 significant). Predictive values of EMG, Bishop-score, contractions on tocogram, and transvaginal cervical length were calculated using receiver-operator-characteristics analysis. Results PV was higher in preterm and term labor compared with non-labor (P<0.001). Combined PV and PS peak frequency predicted preterm delivery within 7 days with area-under-the-curve (AUC) = 0.96. Bishop score, contractions, and cervical length had AUC of 0.72, 0.67, and 0.54. Conclusions Uterine EMG PV and PS peak frequency more accurately identify true preterm labor than clinical methods. PMID:21145033

Prediction of Advisability of Returning Home Using the Home Care Score

PubMed Central

Matsugi, Akiyoshi; Tani, Keisuke; Tamaru, Yoshiki; Yoshioka, Nami; Yamashita, Akira; Mori, Nobuhiko; Oku, Kosuke; Ikeda, Masashi; Nagano, Kiyoshi

2015-01-01

Purpose. The aim of this study was to assess whether the home care score (HCS), which was developed by the Ministry of Health and Welfare in Japan in 1992, is useful for the prediction of advisability of home care. Methods. Subjects living at home and in assisted-living facilities were analyzed. Binominal logistic regression analyses, using age, sex, the functional independence measure score, and the HCS, along with receiver operating characteristic curve analyses, were conducted. Findings/Conclusions. Only HCS was selected for the regression equation. Receiver operating characteristic curve analysis revealed that the area under the curve (0.9), sensitivity (0.82), specificity (0.83), and positive predictive value (0.84) for HCS were higher than those for the functional independence measure, indicating that the HCS is a powerful predictor for advisability of home care. Clinical Relevance. Comprehensive measurements of the condition of provided care and the activities of daily living of the subjects, which are included in the HCS, are required for the prediction of advisability of home care. PMID:26491568

Prediction of Winter Storm Tracks and Intensities Using the GFDL fvGFS Model

NASA Astrophysics Data System (ADS)

Rees, S.; Boaggio, K.; Marchok, T.; Morin, M.; Lin, S. J.

2017-12-01

The GFDL Finite-Volume Cubed-Sphere Dynamical core (FV3) is coupled to a modified version of the Global Forecast System (GFS) physics and initial conditions, to form the fvGFS model. This model is similar to the one being implemented as the next-generation operational weather model for the NWS, which is also FV3-powered. Much work has been done to verify fvGFS tropical cyclone prediction, but little has been done to verify winter storm prediction. These costly and dangerous storms impact parts of the U.S. every year. To verify winter storms we ran the NCEP operational cyclone tracker, developed at GFDL, on semi-real-time 13 km horizontal resolution fvGFS forecasts. We have found that fvGFS compares well to the operational GFS in storm track and intensity, though often predicts slightly higher intensities. This presentation will show the track and intensity verification from the past two winter seasons and explore possible reasons for bias.

A nanoscale piezoelectric transformer for low-voltage transistors.

PubMed

Agarwal, Sapan; Yablonovitch, Eli

2014-11-12

A novel piezoelectric voltage transformer for low-voltage transistors is proposed. Placing a piezoelectric transformer on the gate of a field-effect transistor results in the piezoelectric transformer field-effect transistor that can switch at significantly lower voltages than a conventional transistor. The piezoelectric transformer operates by using one piezoelectric to squeeze another piezoelectric to generate a higher output voltage than the input voltage. Multiple piezoelectrics can be used to squeeze a single piezoelectric layer to generate an even higher voltage amplification. Coupled electrical and mechanical modeling in COMSOL predicts a 12.5× voltage amplification for a six-layer piezoelectric transformer. This would lead to more than a 150× reduction in the power needed for communications.

Displacement Damage Induced Catastrophic Second Breakdown in Silicon Carbide Schottky Power Diodes

NASA Technical Reports Server (NTRS)

Scheick, Leif; Selva, Luis; Selva, Luis

2004-01-01

A novel catastrophic breakdown mode in reversed biased Silicon carbide diodes has been seen for low LET particles. These particles are too low in LET to induce SEB, however SEB was seen from particles of higher LET. The low LET mechanism correlates with second breakdown in diodes due to increase leakage and assisted charge injection from incident particles. Percolation theory was used to predict some basic responses of the devices, but the inherent reliability issue with silicon carbide have proven challenging.

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.

The stopping power and energy straggling of the energetic C and O ions in polyimide

NASA Astrophysics Data System (ADS)

Mikšová, R.; Macková, A.; Slepička, P.

2016-03-01

The stopping power and energy straggling of 12Cn+ and 16On+ heavy ions in the energy range 5.3-8.0 MeV in 8 μm thick polyimide (PI) foil were measured by means of an indirect transmission method using a half-covered a PIPS detector. Ions scattered from thin gold layer, under the scattering angle 150° were detected and the spectrum of ions penetrating the PI foil and without foil was recorded. The values of the experimentally determined stopping powers were compared to the calculated data by SRIM-2013 and MSTAR codes. Measured data were in good agreement with data calculated by SRIM-2013, especially for C ions was observed better agreement than for O ions. The energy straggling was determined and compared to those calculated by using Bohr's, Bethe-Livingston and Yang models. The measured energy straggling values in the PI foil was corrected for foil roughness and thickness inhomogeneity determined from AFM. Bethe-Livingston predicting formula has been modified to make it appropriate for thicker targets. The energy straggling determined in our experiment was obtained higher than Bohr's predicted value; the predictions by Yang are in good agreement with our experiment. Bethe-Livingston formulation of the energy straggling shows better agreement with the experimental data after the modified formula implementation which assumes that the thick target was consisted to be composed of n-number of thin layers. Influence of the charge-exchange phenomena to the energy straggling of C and O ions in PI was discussed.

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

PubMed

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

2017-04-01

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

Artificial neural network optimization of Althaea rosea seeds polysaccharides and its antioxidant activity.

PubMed

Liu, Feng; Liu, Wenhui; Tian, Shuge

2014-09-01

A combination of an orthogonal L16(4)4 test design and a three-layer artificial neural network (ANN) model was applied to optimize polysaccharides from Althaea rosea seeds extracted by hot water method. The highest optimal experimental yield of A. rosea seed polysaccharides (ARSPs) of 59.85 mg/g was obtained using three extraction numbers, 113 min extraction time, 60.0% ethanol concentration, and 1:41 solid-liquid ratio. Under these optimized conditions, the ARSP experimental yield was very close to the predicted yield of 60.07 mg/g and was higher than the orthogonal test results (40.86 mg/g). Structural characterizations were conducted using physicochemical property and FTIR analysis. In addition, the study of ARSP antioxidant activity demonstrated that polysaccharides exhibited high superoxide dismutase activity, strong reducing power, and positive scavenging activity on superoxide anion, hydroxyl radical, 2,2-diphenyl-1-picrylhydrazyl, and reducing power. Our results indicated that ANNs were efficient quantitative tools for predicting the total ARSP content. Copyright © 2014 Elsevier B.V. All rights reserved.

Widely tunable optical parametric oscillation in a Kerr microresonator.

PubMed

Sayson, Noel Lito B; Webb, Karen E; Coen, Stéphane; Erkintalo, Miro; Murdoch, Stuart G

2017-12-15

We report on the first experimental demonstration of widely tunable parametric sideband generation in a Kerr microresonator. Specifically, by pumping a silica microsphere in the normal dispersion regime, we achieve the generation of phase-matched four-wave mixing sidebands at large frequency detunings from the pump. Thanks to the role of higher-order dispersion in enabling phase matching, small variations of the pump wavelength translate into very large and controllable changes in the wavelengths of the generated sidebands: we experimentally demonstrate over 720 nm of tunability using a low-power continuous-wave pump laser in the C-band. We also derive simple theoretical predictions for the phase-matched sideband frequencies and discuss the predictions in light of the discrete cavity resonance frequencies. Our experimentally measured sideband wavelengths are in very good agreement with theoretical predictions obtained from our simple phase-matching analysis.

Diagnostics of seeded RF plasmas: An experimental study related to the gaseous core reactor

NASA Technical Reports Server (NTRS)

Thompson, S. D.; Clement, J. D.; Williams, J. R.

1974-01-01

Measurements of the temperature profiles in an RF argon plasma were made over magnetic field intensities ranging from 20 amp turns/cm to 80 amp turns/cm. The results were compared with a one-dimensional numerical treatment of the governing equations and with an approximate closed form analytical solution that neglected radiation losses. The average measured temperatures in the plasma compared well with the numerical treatment, though the experimental profile showed less of an off center temperature peak than predicted by theory. This may be a result of the complex turbulent flow pattern present in the experimental torch and not modeled in the numerical treatment. The radiation term cannot be neglected for argon at the power levels investigated. The closed form analytical approximation that neglected radiation led to temperature predictions on the order of 1000 K to 2000 K higher than measured or predicted by the numerical treatment which considered radiation losses.

Thermal-structural modeling of polymer Bragg grating waveguides illuminated by a light emitting diode.

PubMed

Joon Kim, Kyoung; Bar-Cohen, Avram; Han, Bongtae

2012-02-20

This study reports both analytical and numerical thermal-structural models of polymer Bragg grating (PBG) waveguides illuminated by a light emitting diode (LED). A polymethyl methacrylate (PMMA) Bragg grating (BG) waveguide is chosen as an analysis vehicle to explore parametric effects of incident optical powers and substrate materials on the thermal-structural behavior of the BG. Analytical models are verified by comparing analytically predicted average excess temperatures, and thermally induced axial strains and stresses with numerical predictions. A parametric study demonstrates that the PMMA substrate induces more adverse effects, such as higher excess temperatures, complex axial temperature profiles, and greater and more complicated thermally induced strains in the BG compared with the Si substrate. © 2012 Optical Society of America

Respectful Modeling: Addressing Uncertainty in Dynamic System Models for Molecular Biology.

PubMed

Tsigkinopoulou, Areti; Baker, Syed Murtuza; Breitling, Rainer

2017-06-01

Although there is still some skepticism in the biological community regarding the value and significance of quantitative computational modeling, important steps are continually being taken to enhance its accessibility and predictive power. We view these developments as essential components of an emerging 'respectful modeling' framework which has two key aims: (i) respecting the models themselves and facilitating the reproduction and update of modeling results by other scientists, and (ii) respecting the predictions of the models and rigorously quantifying the confidence associated with the modeling results. This respectful attitude will guide the design of higher-quality models and facilitate the use of models in modern applications such as engineering and manipulating microbial metabolism by synthetic biology. Copyright © 2016 Elsevier Ltd. All rights reserved.

Stable plume rise in a shear layer.

PubMed

Overcamp, Thomas J

2007-03-01

Solutions are given for plume rise assuming a power-law wind speed profile in a stably stratified layer for point and finite sources with initial vertical momentum and buoyancy. For a constant wind speed, these solutions simplify to the conventional plume rise equations in a stable atmosphere. In a shear layer, the point of maximum rise occurs further downwind and is slightly lower compared with the plume rise with a constant wind speed equal to the wind speed at the top of the stack. If the predictions with shear are compared with predictions for an equivalent average wind speed over the depth of the plume, the plume rise with shear is higher than plume rise with an equivalent average wind speed.

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.

Automated prediction of protein function and detection of functional sites from structure.

PubMed

Pazos, Florencio; Sternberg, Michael J E

2004-10-12

Current structural genomics projects are yielding structures for proteins whose functions are unknown. Accordingly, there is a pressing requirement for computational methods for function prediction. Here we present PHUNCTIONER, an automatic method for structure-based function prediction using automatically extracted functional sites (residues associated to functions). The method relates proteins with the same function through structural alignments and extracts 3D profiles of conserved residues. Functional features to train the method are extracted from the Gene Ontology (GO) database. The method extracts these features from the entire GO hierarchy and hence is applicable across the whole range of function specificity. 3D profiles associated with 121 GO annotations were extracted. We tested the power of the method both for the prediction of function and for the extraction of functional sites. The success of function prediction by our method was compared with the standard homology-based method. In the zone of low sequence similarity (approximately 15%), our method assigns the correct GO annotation in 90% of the protein structures considered, approximately 20% higher than inheritance of function from the closest homologue.

Using timing of ice retreat to predict timing of fall freeze-up in the Arctic

NASA Astrophysics Data System (ADS)

Stroeve, Julienne C.; Crawford, Alex D.; Stammerjohn, Sharon

2016-06-01

Reliable forecasts of the timing of sea ice advance are needed in order to reduce risks associated with operating in the Arctic as well as planning of human and environmental emergencies. This study investigates the use of a simple statistical model relating the timing of ice retreat to the timing of ice advance, taking advantage of the inherent predictive power supplied by the seasonal ice-albedo feedback and ocean heat uptake. Results show that using the last retreat date to predict the first advance date is applicable in some regions, such as Baffin Bay and the Laptev and East Siberian seas, where a predictive skill is found even after accounting for the long-term trend in both variables. Elsewhere, in the Arctic, there is some predictive skills depending on the year (e.g., Kara and Beaufort seas), but none in regions such as the Barents and Bering seas or the Sea of Okhotsk. While there is some suggestion that the relationship is strengthening over time, this may reflect that higher correlations are expected during periods when the underlying trend is strong.

Prediction of Central Nervous System Side Effects Through Drug Permeability to Blood-Brain Barrier and Recommendation Algorithm.

PubMed

Fan, Jun; Yang, Jing; Jiang, Zhenran

2018-04-01

Drug side effects are one of the public health concerns. Using powerful machine-learning methods to predict potential side effects before the drugs reach the clinical stages is of great importance to reduce time consumption and protect the security of patients. Recently, researchers have proved that the central nervous system (CNS) side effects of a drug are closely related to its permeability to the blood-brain barrier (BBB). Inspired by this, we proposed an extended neighborhood-based recommendation method to predict CNS side effects using drug permeability to the BBB and other known features of drug. To the best of our knowledge, this is the first attempt to predict CNS side effects considering drug permeability to the BBB. Computational experiments demonstrated that drug permeability to the BBB is an important factor in CNS side effects prediction. Moreover, we built an ensemble recommendation model and obtained higher AUC score (area under the receiver operating characteristic curve) and AUPR score (area under the precision-recall curve) on the data set of CNS side effects by integrating various features of drug.

Geophysical Anomalies and Earthquake Prediction

NASA Astrophysics Data System (ADS)

Jackson, D. D.

2008-12-01

Finding anomalies is easy. Predicting earthquakes convincingly from such anomalies is far from easy. Why? Why have so many beautiful geophysical abnormalities not led to successful prediction strategies? What is earthquake prediction? By my definition it is convincing information that an earthquake of specified size is temporarily much more likely than usual in a specific region for a specified time interval. We know a lot about normal earthquake behavior, including locations where earthquake rates are higher than elsewhere, with estimable rates and size distributions. We know that earthquakes have power law size distributions over large areas, that they cluster in time and space, and that aftershocks follow with power-law dependence on time. These relationships justify prudent protective measures and scientific investigation. Earthquake prediction would justify exceptional temporary measures well beyond those normal prudent actions. Convincing earthquake prediction would result from methods that have demonstrated many successes with few false alarms. Predicting earthquakes convincingly is difficult for several profound reasons. First, earthquakes start in tiny volumes at inaccessible depth. The power law size dependence means that tiny unobservable ones are frequent almost everywhere and occasionally grow to larger size. Thus prediction of important earthquakes is not about nucleation, but about identifying the conditions for growth. Second, earthquakes are complex. They derive their energy from stress, which is perniciously hard to estimate or model because it is nearly singular at the margins of cracks and faults. Physical properties vary from place to place, so the preparatory processes certainly vary as well. Thus establishing the needed track record for validation is very difficult, especially for large events with immense interval times in any one location. Third, the anomalies are generally complex as well. Electromagnetic anomalies in particular require some understanding of their sources and the physical properties of the crust, which also vary from place to place and time to time. Anomalies are not necessarily due to stress or earthquake preparation, and separating the extraneous ones is a problem as daunting as understanding earthquake behavior itself. Fourth, the associations presented between anomalies and earthquakes are generally based on selected data. Validating a proposed association requires complete data on the earthquake record and the geophysical measurements over a large area and time, followed by prospective testing which allows no adjustment of parameters, criteria, etc. The Collaboratory for Study of Earthquake Predictability (CSEP) is dedicated to providing such prospective testing. Any serious proposal for prediction research should deal with the problems above, and anticipate the huge investment in time required to test hypotheses.

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.

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.

TiO2 dye sensitized solar cell (DSSC): linear relationship of maximum power point and anthocyanin concentration

NASA Astrophysics Data System (ADS)

Ahmadian, Radin

2010-09-01

This study investigated the relationship of anthocyanin concentration from different organic fruit species and output voltage and current in a TiO2 dye-sensitized solar cell (DSSC) and hypothesized that fruits with greater anthocyanin concentration produce higher maximum power point (MPP) which would lead to higher current and voltage. Anthocyanin dye solution was made with crushing of a group of fresh fruits with different anthocyanin content in 2 mL of de-ionized water and filtration. Using these test fruit dyes, multiple DSSCs were assembled such that light enters through the TiO2 side of the cell. The full current-voltage (I-V) co-variations were measured using a 500 Ω potentiometer as a variable load. Point-by point current and voltage data pairs were measured at various incremental resistance values. The maximum power point (MPP) generated by the solar cell was defined as a dependent variable and the anthocyanin concentration in the fruit used in the DSSC as the independent variable. A regression model was used to investigate the linear relationship between study variables. Regression analysis showed a significant linear relationship between MPP and anthocyanin concentration with a p-value of 0.007. Fruits like blueberry and black raspberry with the highest anthocyanin content generated higher MPP. In a DSSC, a linear model may predict MPP based on the anthocyanin concentration. This model is the first step to find organic anthocyanin sources in the nature with the highest dye concentration to generate energy.

Health care expenditure and life expectancy in Australia: how well do we perform?

PubMed

Taylor, R; Salkeld, G

1996-06-01

The Australian health care system consists of mixed public and private financing underpinned by Medicare, a universal government-run insurance scheme paid through taxation (and levy) on income. Australia has improved its ranking for life expectancy (at birth) since 1960, and in 1990 ranked ninth and seventh of 24 countries for females and males respectively; this is ahead of the United States and United Kingdom, and approximately equal to Canada. Australian hospital bed supply and utilisation are average, after deletion of day-only cases. The proportion of gross domestic product (GDP) spent on health, in relation to GDP per capita (adjusted for purchasing power), in Australia in 1990 was average, and the prices for health care from 1975 to 1990 did not increase when adjusted for inflation. Although 68 per cent of health expenditure emanates from public sources in Australia, this is lower than in the majority of European countries and Canada. Some countries are doing poorly (such as the United States, with lower than average life expectancy and higher than predicted health expenditure) and some countries are doing well (with higher than average life expectancy and lower than predicted health expenditure; for example, Japan). Australia has higher than average life expectancy and only slightly higher than predicted health expenditure per capita. Although the Australian system could be improved, there are no indications that radical changes are required. The relatively high life expectancy in Australia can be attributed to favourable social and economic conditions, successful public health programs, and the availability of universal quality health care.

Impact of Different Tidal Volume Levels at Low Mechanical Power on Ventilator-Induced Lung Injury in Rats.

PubMed

Moraes, Lillian; Silva, Pedro L; Thompson, Alessandra; Santos, Cintia L; Santos, Raquel S; Fernandes, Marcos V S; Morales, Marcelo M; Martins, Vanessa; Capelozzi, Vera L; de Abreu, Marcelo G; Pelosi, Paolo; Rocco, Patricia R M

2018-01-01

Tidal volume (V T ) has been considered the main determinant of ventilator-induced lung injury (VILI). Recently, experimental studies have suggested that mechanical power transferred from the ventilator to the lungs is the promoter of VILI. We hypothesized that, as long as mechanical power is kept below a safe threshold, high V T should not be injurious. The present study aimed to investigate the impact of different V T levels and respiratory rates (RR) on lung function, diffuse alveolar damage (DAD), alveolar ultrastructure, and expression of genes related to inflammation [interleukin (IL)-6], alveolar stretch (amphiregulin), epithelial [club cell secretory protein (CC)16] and endothelial [intercellular adhesion molecule (ICAM)-1] cell injury, and extracellular matrix damage [syndecan-1, decorin, and metalloproteinase (MMP)-9] in experimental acute respiratory distress syndrome (ARDS) under low-power mechanical ventilation. Twenty-eight Wistar rats received Escherichia coli lipopolysaccharide intratracheally. After 24 h, 21 animals were randomly assigned to ventilation (2 h) with low mechanical power at three different V T levels ( n = 7/group): (1) V T = 6 mL/kg and RR adjusted to normocapnia; (2) V T = 13 mL/kg; and 3) V T = 22 mL/kg. In the second and third groups, RR was adjusted to yield low mechanical power comparable to that of the first group. Mechanical power was calculated as [(Δ[Formula: see text]/Est, L )/2]× RR (ΔP, L = transpulmonary driving pressure, Est, L = static lung elastance). Seven rats were not mechanically ventilated (NV) and were used for molecular biology analysis. Mechanical power was comparable among groups, while V T gradually increased. ΔP, L and mechanical energy were higher in V T = 22 mL/kg than V T = 6 mL/kg and V T = 13 mL/kg ( p < 0.001 for both). Accordingly, DAD score increased in V T = 22 mL/kg compared to V T = 6 mL/kg and V T = 13 mL/kg [23(18.5-24.75) vs. 16(12-17.75) and 16(13.25-18), p < 0.05, respectively]. V T = 22 mL/kg was associated with higher IL-6, amphiregulin, CC16, MMP-9, and syndecan-1 mRNA expression and lower decorin expression than V T = 6 mL/kg. Multiple linear regression analyses indicated that V T was able to predict changes in IL-6 and CC16, whereas ΔP, L predicted pHa, oxygenation, amphiregulin, and syndecan-1 expression. In the model of ARDS used herein, even at low mechanical power, high V T resulted in VILI. V T control seems to be more important than RR control to mitigate VILI.

The Predictive Effects of Protection Motivation Theory on Intention and Behaviour of Physical Activity in Patients with Type 2 Diabetes.

PubMed

Ali Morowatisharifabad, Mohammad; Abdolkarimi, Mahdi; Asadpour, Mohammad; Fathollahi, Mahmood Sheikh; Balaee, Parisa

2018-04-15

Theory-based education tailored to target behaviour and group can be effective in promoting physical activity. The purpose of this study was to examine the predictive power of Protection Motivation Theory on intent and behaviour of Physical Activity in Patients with Type 2 Diabetes. This descriptive study was conducted on 250 patients in Rafsanjan, Iran. To examine the scores of protection motivation theory structures, a researcher-made questionnaire was used. Its validity and reliability were confirmed. The level of physical activity was also measured by the International Short - form Physical Activity Inventory. Its validity and reliability were also approved. Data were analysed by statistical tests including correlation coefficient, chi-square, logistic regression and linear regression. The results revealed that there was a significant correlation between all the protection motivation theory constructs and the intention to do physical activity. The results showed that the Theory structures were able to predict 60% of the variance of physical activity intention. The results of logistic regression demonstrated that increase in the score of physical activity intent and self - efficacy increased the chance of higher level of physical activity by 3.4 and 1.5 times, respectively OR = (3.39, 1.54). Considering the ability of protection motivation theory structures to explain the physical activity behaviour, interventional designs are suggested based on the structures of this theory, especially to improve self -efficacy as the most powerful factor in predicting physical activity intention and behaviour.

Examination of the Mild Brain Injury Atypical Symptom Scale and the Validity-10 Scale to detect symptom exaggeration in US military service members.

PubMed

Lange, Rael T; Brickell, Tracey A; French, Louis M

2015-01-01

The purpose of this study was to examine the clinical utility of two validity scales designed for use with the Neurobehavioral Symptom Inventory (NSI) and the PTSD Checklist-Civilian Version (PCL-C); the Mild Brain Injury Atypical Symptoms Scale (mBIAS) and Validity-10 scale. Participants were 63 U.S. military service members (age: M = 31.9 years, SD = 12.5; 90.5% male) who sustained a mild traumatic brain injury (MTBI) and were prospectively enrolled from Walter Reed National Military Medical Center. Participants were divided into two groups based on the validity scales of the Minnesota Multiphasic Personality Inventory-2 Restructured Form (MMPI-2-RF): (a) symptom validity test (SVT)-Fail (n = 24) and (b) SVT-Pass (n = 39). Participants were evaluated on average 19.4 months postinjury (SD = 27.6). Participants in the SVT-Fail group had significantly higher scores (p < .05) on the mBIAS (d = 0.85), Validity-10 (d = 1.89), NSI (d = 2.23), and PCL-C (d = 2.47), and the vast majority of the MMPI-2-RF scales (d = 0.69 to d = 2.47). Sensitivity, specificity, and predictive power values were calculated across the range of mBIAS and Validity-10 scores to determine the optimal cutoff to detect symptom exaggeration. For the mBIAS, a cutoff score of ≥8 was considered optimal, which resulted in low sensitivity (.17), high specificity (1.0), high positive predictive power (1.0), and moderate negative predictive power (.69). For the Validity-10 scale, a cutoff score of ≥13 was considered optimal, which resulted in moderate-high sensitivity (.63), high specificity (.97), and high positive (.93) and negative predictive power (.83). These findings provide strong support for the use of the Validity-10 as a tool to screen for symptom exaggeration when administering the NSI and PCL-C. The mBIAS, however, was not a reliable tool for this purpose and failed to identify the vast majority of people who exaggerated symptoms.

International migration patterns of physicians to the United States: a cross-national panel analysis.

PubMed

Hussey, Peter S

2007-12-01

To analyze the dynamics of physician international migration patterns and identify the countries deviating most from expected migration rates. A negative binomial log-linear model of physician migration to the United States from every other country was constructed using a panel of country-level data for years 1994-2000. The model was used to identify factors associated with physician migration and to identify countries with higher or lower rates of physician migration than expected. Physician migration varied with a country's GDP per capita in an inverse-U pattern, with highest migration rates from middle-income countries. The absence of medical schools, immigrant networks in the United States, medical instruction in English, proximity to the United States, and the lack of political and civil liberties were also associated with higher migration rates. Countries with higher-than-predicted migration rates included Iceland, Albania, Armenia, Dominica, Lebanon, Syria, the United Arab Emirates, and Bulgaria. Countries with lower-than-predicted migration rates included Mexico, Japan, Brazil, Zimbabwe, Mauritania, Portugal, Senegal, and France. This analysis shows that many of the most powerful factors associated with physician migration are difficult or impossible for countries to change through public policy. GDP per capita and proximity to the U.S. are two of the most powerful predictors of physician migration. Networks of immigrants in the U.S. and fewer political and civil liberties also put countries at higher risk for physician emigration. Several other factors that were associated with physician migration might be more easily amenable to policy intervention. These factors include the absence of a medical school and medical instruction in English. Policies addressing these factors would involve making several difficult tradeoffs, however. Other examples of policies that are effective in minimizing physician migration might be found by examining countries with lower-than-expected migration rates.

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.

The impact of lateral variations in lithospheric thickness on glacial isostatic adjustment in West Antarctica

NASA Astrophysics Data System (ADS)

Nield, Grace A.; Whitehouse, Pippa L.; van der Wal, Wouter; Blank, Bas; O'Donnell, John Paul; Stuart, Graham W.

2018-04-01

Differences in predictions of Glacial Isostatic Adjustment (GIA) for Antarctica persist due to uncertainties in deglacial history and Earth rheology. The Earth models adopted in many GIA studies are defined by parameters that vary in the radial direction only and represent a global average Earth structure (referred to as 1D Earth models). Over-simplifying actual Earth structure leads to bias in model predictions in regions where Earth parameters differ significantly from the global average, such as West Antarctica. We investigate the impact of lateral variations in lithospheric thickness on GIA in Antarctica by carrying out two experiments that use different rheological approaches to define 3D Earth models that include spatial variations in lithospheric thickness. The first experiment defines an elastic lithosphere with spatial variations in thickness inferred from seismic studies. We compare the results from this 3D model with results derived from a 1D Earth model that has a uniform lithospheric thickness defined as the average of the 3D lithospheric thickness. Irrespective of deglacial history and sub-lithospheric mantle viscosity, we find higher gradients of present-day uplift rates (i.e. higher amplitude and shorter wavelength) in West Antarctica when using the 3D models, due to the thinner-than-1D-average lithosphere prevalent in this region. The second experiment uses seismically-inferred temperature as input to a power-law rheology thereby allowing the lithosphere to have a viscosity structure. Modelling the lithosphere with a power-law rheology results in behaviour that is equivalent to a thinner-lithosphere model, and it leads to higher amplitude and shorter wavelength deformation compared with the first experiment. We conclude that neglecting spatial variations in lithospheric thickness in GIA models will result in predictions of peak uplift and subsidence that are biased low in West Antarctica. This has important implications for ice-sheet modelling studies as the steeper gradients of uplift predicted from the more realistic 3D model may promote stability in marine-grounded regions of West Antarctica. Including lateral variations in lithospheric thickness, at least to the level of considering West and East Antarctica separately, is important for capturing short wavelength deformation and it has the potential to provide a better fit to GPS observations as well as an improved GIA correction for GRACE data.

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

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

PubMed

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

2017-11-02

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

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

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.

Quantitative EEG and functional outcome following acute ischemic stroke.

PubMed

Bentes, Carla; Peralta, Ana Rita; Viana, Pedro; Martins, Hugo; Morgado, Carlos; Casimiro, Carlos; Franco, Ana Catarina; Fonseca, Ana Catarina; Geraldes, Ruth; Canhão, Patrícia; Pinho E Melo, Teresa; Paiva, Teresa; Ferro, José M

2018-06-18

To identify the most accurate quantitative electroencephalographic (qEEG) predictor(s) of unfavorable post-ischemic stroke outcome, and its discriminative capacity compared to already known demographic, clinical and imaging prognostic markers. Prospective cohort of 151 consecutive anterior circulation ischemic stroke patients followed for 12 months. EEG was recorded within 72 h and at discharge or 7 days post-stroke. QEEG (global band power, symmetry, affected/unaffected hemisphere and time changes) indices were calculated from mean Fast Fourier Transform and analyzed as predictors of unfavorable outcome (mRS ≥ 3), at discharge and 12 months poststroke, before and after adjustment for age, admission NIHSS and ASPECTS. Higher delta, lower alpha and beta relative powers (RP) predicted outcome. Indices with higher discriminative capacity were delta-theta to alpha-beta ratio (DTABR) and alpha RP. Outcome models including either of these and other clinical/imaging stroke outcome predictors were superior to models without qEEG data. In models with qEEG indices, infarct size was not a significant outcome predictor. DTAABR and alpha RP are the best qEEG indices and superior to ASPECTS in post-stroke outcome prediction. They improve the discriminative capacity of already known clinical and imaging stroke outcome predictors, both at discharge and 12 months after stroke. qEEG indices are independent predictors of stroke outcome. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

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.).

Bias in discriminating very mild dementia for older adults with different levels of education in Hong Kong.

PubMed

Chang, Jianfang; Tse, Chi-Shing; Leung, Grace Tak Yu; Fung, Ada Wai Tung; Hau, Kit-Tai; Chiu, Helen Fung Kum; Lam, Linda Chiu Wa

2014-06-01

Education has a profound effect on older adults' cognitive performance. In Hong Kong, some dementia screening tasks were originally designed for developed population with, on average, higher education. We compared the screening power of these tasks for Chinese older adults with different levels of education. Community-dwelling older adults who were healthy (N = 383) and with very mild dementia (N = 405) performed the following tasks: Mini-Mental State Examination, Alzheimer's Disease Assessment Scale-Cognitive subscales, Verbal Fluency, Abstract Thinking, and Visual/Digit Span. Logistic regression was used to examine the power of these tasks to predict Clinical Dementia Rating (CDR 0.5 vs. 0). Logistic regression analysis showed that while the screening power of the total scores in all tasks was similar for high and low education groups, there were education biases in some items of these tasks. The differential screening power in high and low education groups was not identical across items in some tasks. Thus, in cognitive assessments, we should exercise great caution when using these potentially biased items for older adults with limited education.

Multiple high-intensity focused ultrasound probes for kidney-tissue ablation.

PubMed

Häcker, Axel; Chauhan, Sunita; Peters, Kristina; Hildenbrand, Ralf; Marlinghaus, Ernst; Alken, Peter; Michel, Maurice Stephan

2005-10-01

To investigate kidney-tissue ablation by high-intensity focused ultrasound (HIFU) using multiple and single probes. Ultrasound beams (1.75 MHz) produced by a piezoceramic element (focal distance 80 mm) were focused at the center of renal parenchyma. One of the three probes (mounted on a jig) could also be used for comparison with a single probe at comparable power ratings. Lesion dimensions were examined in perfused and unperfused ex vivo porcine kidneys at different power levels (40, 60, and 80 W) and treatment times (4, 6, and 8 seconds). At identical power levels, the lesions induced by multiple probes were larger than those induced by a single probe. Lesion size increased with increasing pulse duration and generator power. The sizes and shapes of the lesions were predictably repeatable in all samples. Lesions in perfused kidneys were smaller than those in unperfused kidneys. Ex vivo, kidney-tissue ablation by means of multiple HIFU probes offers significant advantages over single HIFU probes in respect of lesion size and formation. These advantages need to be confirmed by tests in vivo at higher energy levels.

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.

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.

Progress and challenges in bipolar lead-acid battery development

NASA Astrophysics Data System (ADS)

Bullock, Kathryn R.

1995-05-01

Bipolar lead-acid batteries have higher power densities than any other aqueous battery system. Predicted specific powers based on models and prototypes range from 800 kW/kg for 100 ms discharge times to 1.6 kW/kg for 10 s. A 48 V automotive bipolar battery could have 2 1/2 times the cold cranking rate of a monopolar 12 V design in the same size. Problems which have precluded the development of commercial bipolar designs include the instability of substrate materials and enhanced side reactions. Design approaches include pseudo-bipolar configurations, as well as true bipolar designs in planar and tubular configurations. Substrate materials used include lead and lead alloys, carbons, conductive ceramics, and tin-oxide-coated glass fibers. These approaches are reviewed and evaluated.

Efficiency of bulk-heterojunction organic solar cells

PubMed Central

Scharber, M.C.; Sariciftci, N.S.

2013-01-01

During the last years the performance of bulk heterojunction solar cells has been improved significantly. For a large-scale application of this technology further improvements are required. This article reviews the basic working principles and the state of the art device design of bulk heterojunction solar cells. The importance of high power conversion efficiencies for the commercial exploitation is outlined and different efficiency models for bulk heterojunction solar cells are discussed. Assuming state of the art materials and device architectures several models predict power conversion efficiencies in the range of 10–15%. A more general approach assuming device operation close to the Shockley–Queisser-limit leads to even higher efficiencies. Bulk heterojunction devices exhibiting only radiative recombination of charge carriers could be as efficient as ideal inorganic photovoltaic devices. PMID:24302787

Application of the electroosmotic effect for thrust generation

NASA Astrophysics Data System (ADS)

Hansen, Thomas Edward

The present work focuses on demonstrating the capabilities of electroosmotic pumps, (EOP) to generate thrust. An underwater glider was successfully propelled by electroosmosis for the first time published - at 0.85 inches per second. Asymmetric AC voltage pulsing proved to produce higher flow rates then equivalent DC pumps for the same average voltage. Ultra-short pulsing proved 100 nanosecond rise times in EOP are possible, which surpassed published predictions by three orders of magnitude. Theories behind efficiency losses of high power EOP were investigated. Direct measurement of effective voltage at the face of a membrane is the most accurate way to determine voltage drop across the electrolyte of an EOP. Forced convection lowered efficiency of the EOP for low voltages by preventing capacitance charging, but proved to prolong pump life during high power application.

On the bispectra of very massive tracers in the Effective Field Theory of Large-Scale Structure

DOE PAGES

Nadler, Ethan O.; Perko, Ashley; Senatore, Leonardo

2018-02-01

The Effective Field Theory of Large-Scale Structure (EFTofLSS) provides a consistent perturbative framework for describing the statistical distribution of cosmological large-scale structure. In a previous EFTofLSS calculation that involved the one-loop power spectra and tree-level bispectra, it was shown that the k-reach of the prediction for biased tracers is comparable for all investigated masses if suitable higher-derivative biases, which are less suppressed for more massive tracers, are added. However, it is possible that the non-linear biases grow faster with tracer mass than the linear bias, implying that loop contributions could be the leading correction to the bispectra. To check this,more » we include the one-loop contributions in a fit to numerical data in the limit of strongly enhanced higher-order biases. Here, we show that the resulting one-loop power spectra and higher-derivative plus leading one-loop bispectra fit the two- and three-point functions respectively up to k≃0.19 h Mpc -1 and ksime 0.14 h Mpc -1 at the percent level. We find that the higher-order bias coefficients are not strongly enhanced, and we argue that the gain in perturbative reach due to the leading one-loop contributions to the bispectra is relatively small. Thus, we conclude that higher-derivative biases provide the leading correction to the bispectra for tracers of a very wide range of masses.« less

On the bispectra of very massive tracers in the Effective Field Theory of Large-Scale Structure

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

Nadler, Ethan O.; Perko, Ashley; Senatore, Leonardo

The Effective Field Theory of Large-Scale Structure (EFTofLSS) provides a consistent perturbative framework for describing the statistical distribution of cosmological large-scale structure. In a previous EFTofLSS calculation that involved the one-loop power spectra and tree-level bispectra, it was shown that the k-reach of the prediction for biased tracers is comparable for all investigated masses if suitable higher-derivative biases, which are less suppressed for more massive tracers, are added. However, it is possible that the non-linear biases grow faster with tracer mass than the linear bias, implying that loop contributions could be the leading correction to the bispectra. To check this,more » we include the one-loop contributions in a fit to numerical data in the limit of strongly enhanced higher-order biases. Here, we show that the resulting one-loop power spectra and higher-derivative plus leading one-loop bispectra fit the two- and three-point functions respectively up to k≃0.19 h Mpc -1 and ksime 0.14 h Mpc -1 at the percent level. We find that the higher-order bias coefficients are not strongly enhanced, and we argue that the gain in perturbative reach due to the leading one-loop contributions to the bispectra is relatively small. Thus, we conclude that higher-derivative biases provide the leading correction to the bispectra for tracers of a very wide range of masses.« less

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 ...

Osmotic indices and kidney concentrating activity: population-based data on correlates and prognostic power.

PubMed

Cirillo, Massimo; Bilancio, Giancarlo; Lombardi, Cinzia; Cavallo, Pierpaolo; Terradura Vagnarelli, Oscar; Zanchetti, Alberto; Laurenzi, Martino

2018-02-01

Research data are limited on indices of osmotic equilibrium and of kidney concentrating activity (KCA). This study investigated correlates and prognostic power of these indices in a sample of the general population. Urine osmolality (U-osm), plasma osmolality (P-osm), plasma creatinine and other variables were measured by the Gubbio Study for the 1988-92 exam (baseline). Plasma creatinine and other variables were re-measured in the 2001-07 exam (follow-up). KCA was assessed as the U-osm/P-osm ratio and kidney function as estimated glomerular filtration rate (eGFR). Baseline data were complete in 4220 adults, of whom 852 died before follow-up and 2795 participated in the follow-up. At baseline, the following independent cross-sectional associations were identified: female sex and higher urine flow with lower values of U-osm, P-osm and U-osm/P-osm ratio (P < 0.01); obesity with higher values of U-osm, P-osm and U-osm/P-osm ratio (P < 0.01); older age and lower eGFR with lower U-osm, lower U-osm/P-osm ratio and higher P-osm (P < 0.05); hypertension and smoking with lower U-osm and lower U-osm/P-osm ratio (P < 0.05) but not with P-osm. From baseline to follow-up, the annualized rate was 1.26% for mortality and -0.74 ± 0.76 mL/min × 1.73 m2 for eGFR change. Mortality was independently predicted by baseline U-osm and baseline U-osm/P-osm ratio (hazard ratio for one higher standard deviation was ≤0.91, 95% confidence interval was ≤0.97, P < 0.01), but not by baseline P-osm. The eGFR change was not independently predicted by baseline values of U-osm, P-osm and U-osm/P-osm ratio (P ≥ 0.4). Sex, age, obesity, eGFR, urine flow, hypertension and smoking independently associated with U-osm and KCA. U-osm and KCA independently predicted mortality, but not kidney function change over time. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

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

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.

Increase of EEG Spectral Theta Power Indicates Higher Risk of the Development of Severe Cognitive Decline in Parkinson’s Disease after 3 Years

PubMed Central

Cozac, Vitalii V.; Chaturvedi, Menorca; Hatz, Florian; Meyer, Antonia; Fuhr, Peter; Gschwandtner, Ute

2016-01-01

Objective: We investigated quantitative electroencephalography (qEEG) and clinical parameters as potential risk factors of severe cognitive decline in Parkinson’s disease. Methods: We prospectively investigated 37 patients with Parkinson’s disease at baseline and follow-up (after 3 years). Patients had no severe cognitive impairment at baseline. We used a summary score of cognitive tests as the outcome at follow-up. At baseline we assessed motor, cognitive, and psychiatric factors; qEEG variables [global relative median power (GRMP) spectra] were obtained by a fully automated processing of high-resolution EEG (256-channels). We used linear regression models with calculation of the explained variance to evaluate the relation of baseline parameters with cognitive deterioration. Results: The following baseline parameters significantly predicted severe cognitive decline: GRMP theta (4–8 Hz), cognitive task performance in executive functions and working memory. Conclusions: Combination of neurocognitive tests and qEEG improves identification of patients with higher risk of cognitive decline in PD. PMID:27965571

Persistence in the WFC3 IR Detector: Intrinsic Variability

NASA Astrophysics Data System (ADS)

Long, Knox S.; Baggett, Sylvia M.

2018-03-01

When the WFC3 IR detector is exposed to a bright source or sources, the sources can appear as afterimages in subsequent exposures, a phenomenon known as persistence. This can affect the science obtained with the IR channel. We have been involved in an effort to predict the brightness of the afterimages so that users can (at a minimum) flag the affected pixels and remove them from their analysis or (even better) subtract the afterimages from their science images to salvage the data. The ability of any model to remove afterimages depends on the degree to which persistence is the same for identical sets of exposures. We investigate possible time variability of persistence in the WFC3 detector using sets of (almost) identical visits comprised of single exposures of Omega Cen followed by a series of darks in which persistence is measured. We analyze 8 data sets, each consisting of two or three identical visits, with stimulus exposures between 49 and 1199 s, and find clear evidence of variability in several of the datasets in darks taken within 1000 s of the stimulus exposure. In most of the datasets, the difference in persistence for saturated pixels in the stimulus exposure is < 0.01 e-/s for darks taken 1000 s after the initial exposure. One of three 274-second visits has significantly more persistence than its two identical visits. Persistence in this visit was higher in all 4 detector quadrants. The persistence in all three visits is well modeled as a power law decay; the visit with higher persistence has a higher power law amplitude. There was nothing unusual about the observing conditions preceding and during each of these visits that can explain the discrepancy in persistence levels. Variation in persistence implies that: (1) Unless and until the source of the variability is understood, any persistence model for the WFC3 array will be limited in its ability to predict persistence in a single observation, and, (2) as a consequence, users should always carefully inspect the results of any attempt to subtract persistence from WFC3 IR data based on a model prediction.

Analytical and numerical prediction of harmonic sound power in the inlet of aero-engines with emphasis on transonic rotation speeds

NASA Astrophysics Data System (ADS)

Lewy, Serge; Polacsek, Cyril; Barrier, Raphael

2014-12-01

Tone noise radiated through the inlet of a turbofan is mainly due to rotor-stator interactions at subsonic regimes (approach flight), and to the shock waves attached to each blade at supersonic helical tip speeds (takeoff). The axial compressor of a helicopter turboshaft engine is transonic as well and can be studied like turbofans at takeoff. The objective of the paper is to predict the sound power at the inlet radiating into the free field, with a focus on transonic conditions because sound levels are much higher. Direct numerical computation of tone acoustic power is based on a RANS (Reynolds averaged Navier-Stokes) solver followed by an integration of acoustic intensity over specified inlet cross-sections, derived from Cantrell and Hart equations (valid in irrotational flows). In transonic regimes, sound power decreases along the intake because of nonlinear propagation, which must be discriminated from numerical dissipation. This is one of the reasons why an analytical approach is also suggested. It is based on three steps: (i) appraisal of the initial pressure jump of the shock waves; (ii) 2D nonlinear propagation model of Morfey and Fisher; (iii) calculation of the sound power of the 3D ducted acoustic field. In this model, all the blades are assumed to be identical such that only the blade passing frequency and its harmonics are predicted (like in the present numerical simulations). However, transfer from blade passing frequency to multiple pure tones can be evaluated in a fourth step through a statistical analysis of irregularities between blades. Interest of the analytical method is to provide a good estimate of nonlinear acoustic propagation in the upstream duct while being easy and fast to compute. The various methods are applied to two turbofan models, respectively in approach (subsonic) and takeoff (transonic) conditions, and to a Turbomeca turboshaft engine (transonic case). The analytical method in transonic appears to be quite reliable by comparison with the numerical solution and with available experimental data.

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.

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.

Preoperative Beta Cell Function Is Predictive of Diabetes Remission After Bariatric Surgery.

PubMed

Souteiro, Pedro; Belo, Sandra; Neves, João Sérgio; Magalhães, Daniela; Silva, Rita Bettencourt; Oliveira, Sofia Castro; Costa, Maria Manuel; Saavedra, Ana; Oliveira, Joana; Cunha, Filipe; Lau, Eva; Esteves, César; Freitas, Paula; Varela, Ana; Queirós, Joana; Carvalho, Davide

2017-02-01

Bariatric surgery can improve glucose metabolism in obese patients with diabetes, but the factors that can predict diabetes remission are still under discussion. The present study aims to examine the impact of preoperative beta cell function on diabetes remission following surgery. We investigated a cohort of 363 obese diabetic patients who underwent bariatric surgery. The impact of several preoperative beta cell function indexes on diabetes remission was explored through bivariate logistic regression models. Postoperative diabetes remission was achieved in 39.9 % of patients. Younger patients (p < 0.001) and those with lower HbA1c (p = 0.001) at the baseline evaluation had higher odds of diabetes remission. Use of oral anti-diabetics and insulin therapy did not reach statistical significance when they were adjusted for age and HbA1c. Among the evaluated indexes of beta cell function, higher values of insulinogenix index, Stumvoll first- and second-phase indexes, fasting C-peptide, C-peptide area under the curve (AUC), C-peptide/glucose AUC, ISR (insulin secretion rate) AUC, and ISR/glucose AUC predicted diabetes remission even after adjustment for age and HbA1c. Among them, C-peptide AUC had the higher discriminative power (AUC 0.76; p < 0.001). Patients' age and preoperative HbA1c can forecast diabetes remission following surgery. Unlike other studies, our group found that the use of oral anti-diabetics and insulin therapy were not independent predictors of postoperative diabetes status. Preoperative beta cell function, mainly C-peptide AUC, is useful in predicting diabetes remission, and it should be assessed in all obese diabetic patients before bariatric or metabolic surgery.

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

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.

Hyperextended Cosmological Perturbation Theory: Predicting Nonlinear Clustering Amplitudes

NASA Astrophysics Data System (ADS)

Scoccimarro, Román; Frieman, Joshua A.

1999-07-01

We consider the long-standing problem of predicting the hierarchical clustering amplitudes Sp in the strongly nonlinear regime of gravitational evolution. N-body results for the nonlinear evolution of the bispectrum (the Fourier transform of the three-point density correlation function) suggest a physically motivated Ansatz that yields the strongly nonlinear behavior of the skewness, S3, starting from leading-order perturbation theory. When generalized to higher order (p>3) polyspectra or correlation functions, this Ansatz leads to a good description of nonlinear amplitudes in the strongly nonlinear regime for both scale-free and cold dark matter models. Furthermore, these results allow us to provide a general fitting formula for the nonlinear evolution of the bispectrum that interpolates between the weakly and strongly nonlinear regimes, analogous to previous expressions for the power spectrum.

Relativistic high-current electron-beam stopping-power characterization in solids and plasmas: collisional versus resistive effects.

PubMed

Vauzour, B; Santos, J J; Debayle, A; Hulin, S; Schlenvoigt, H-P; Vaisseau, X; Batani, D; Baton, S D; Honrubia, J J; Nicolaï, Ph; Beg, F N; Benocci, R; Chawla, S; Coury, M; Dorchies, F; Fourment, C; d'Humières, E; Jarrot, L C; McKenna, P; Rhee, Y J; Tikhonchuk, V T; Volpe, L; Yahia, V

2012-12-21

We present experimental and numerical results on intense-laser-pulse-produced fast electron beams transport through aluminum samples, either solid or compressed and heated by laser-induced planar shock propagation. Thanks to absolute K(α) yield measurements and its very good agreement with results from numerical simulations, we quantify the collisional and resistive fast electron stopping powers: for electron current densities of ≈ 8 × 10(10) A/cm(2) they reach 1.5 keV/μm and 0.8 keV/μm, respectively. For higher current densities up to 10(12)A/cm(2), numerical simulations show resistive and collisional energy losses at comparable levels. Analytical estimations predict the resistive stopping power will be kept on the level of 1 keV/μm for electron current densities of 10(14)A/cm(2), representative of the full-scale conditions in the fast ignition of inertially confined fusion targets.

13.1 micrometers hard X-ray focusing by a new type monocapillary X-ray optic designed for common laboratory X-ray source

NASA Astrophysics Data System (ADS)

Sun, Xuepeng; zhang, Xiaoyun; Zhu, Yu; Wang, Yabing; Shang, Hongzhong; Zhang, Fengshou; Liu, Zhiguo; Sun, Tianxi

2018-04-01

A new type of monocapillary X-ray optic, called 'two bounces monocapillary X-ray optics' (TBMXO), is proposed for generating a small focal spot with high power-density gain for micro X-ray analysis, using a common laboratory X-ray source. TBMXO is consists of two parts: an ellipsoidal part and a tapered part. Before experimental testing, the TBMXO was simulated by the ray tracing method in MATLAB. The simulated results predicted that the proposed TBMXO would produce a smaller focal spot with higher power-density gain than the ellipsoidal monocapillary X-ray optic (EMXO). In the experiment, the TBMXO performance was tested by both an optical device and a Cu target X-ray tube with focal spot of 100 μm. The results indicated that the TBMXO had a slope error of 57.6 μrad and a 13.1 μm focal spot and a 1360 gain in power density were obtained.

Free triiodothyronine/free thyroxine ratio rather than thyrotropin is more associated with metabolic parameters in healthy euthyroid adult subjects.

PubMed

Park, So Young; Park, Se Eun; Jung, Sang Won; Jin, Hyun Seok; Park, Ie Byung; Ahn, Song Vogue; Lee, Sihoon

2017-07-01

The interrelation between TSH, thyroid hormones and metabolic parameters is complex and has not been confirmed. This study aimed to determine the association of TSH and thyroid hormones in euthyroid subjects and the relationship between thyroid function and metabolic risk factors. Furthermore, this study examined whether thyroid function has predictive power for metabolic syndrome. This is a cross-sectional study that included subjects in a medical health check-up programme at a single institution. The study included 132 346 participants (66 991 men and 65 355 women) aged over 18 years who had TSH, free T4 (FT4) and free T3 (FT3) levels within the institutional reference ranges. Thyrotropin, FT4, FT3 and metabolic parameters including height, weight, waist circumference, blood pressure, serum levels of total cholesterol, triglyceride, high-density lipoprotein cholesterol, insulin and glucose were measured. There was a positive association between FT3/FT4 ratio and TSH in both men and women after adjusting for age, body mass index, smoking status and menopausal status (in women). The FT3/FT4 ratio and TSH were positively associated with risk of metabolic syndrome parameters including insulin resistance. The FT3/FT4 ratio had a greater predictive power than TSH for metabolic syndrome in both men and women. Thyrotropin levels were positively associated with FT3/FT4 ratio within the euthyroid range. The higher FT3/FT4 ratio is associated with increased risk of metabolic syndrome parameters and insulin resistance. FT3/FT4 ratio has a better predictive power for metabolic syndrome than TSH. © 2017 John Wiley & Sons Ltd.

An analogue study of the influence of solidification on the advance and surface thermal signature of lava flows

NASA Astrophysics Data System (ADS)

Garel, F.; Kaminski, E.; Tait, S.; Limare, A.

2014-06-01

The prediction of lava flow advance and velocity is crucial during an effusive volcanic crisis. The effusion rate is a key control of lava dynamics, and proxies have been developed to estimate it in near real-time. The thermal proxy in predominant use links the satellite-measured thermal radiated power to the effusion rate. It lacks however a robust physical basis to allow time-dependent modeling. We investigate here through analogue experiments the coupling between the spreading of a solidifying flow and its surface thermal signal. We extract a first order behavior from experimental results obtained using polyethylene glycol (PEG) wax, that solidifies abruptly during cooling. We find that the flow advance is discontinuous, with relatively low supply rates yielding long stagnation phases and compound flows. Flows with higher supply rates are less sensitive to solidification and display a spreading behavior closer to that of purely viscous currents. The total power radiated from the upper surface also grows by stages, but the signal radiated by the hottest and liquid part of the flow reaches a quasi-steady state after some time. This plateau value scales around half of the theoretical prediction of a model developed previously for the spreading and cooling of isoviscous gravity currents. The corrected scaling yields satisfying estimates of the effusion rate from the total radiated power measured on a range of basaltic lava flows. We conclude that a gross estimate of the supply rate of solidifying flows can be retrieved from thermal remote-sensing, but the predictions of lava advance as a function of effusion rate appears a more difficult task due to chaotic emplacement of solidifying flows.

Sex-specific predictive power of 6-minute walk test in chronic heart failure is not enhanced using percent achieved of published reference equations.

PubMed

Frankenstein, Lutz; Zugck, Christian; Nelles, Manfred; Schellberg, Dieter; Katus, Hugo; Remppis, Andrew

2008-04-01

The 6-minute walk test (6MWT) is an established prognostic tool in chronic heart failure. The strong influence of height, weight, age, and sex on 6MWT distance may be accounted for by using percentage achieved of predicted value rather than uncorrected 6MWT values. The study included 1069 patients (862 men) with a mean age 55.2 +/- 11.7 years and mean left ventricular ejection fraction of 29% +/- 10%, attending the heart failure clinic of the University of Heidelberg between 1995 and 2005. The predictive power and accuracy of 6MWT and achieved percentage values according to all available published equations for mortality and mortality or transplant combined were tested separately for each sex. The percentage values varied largely between equations. For all equations, women in New York Heart Association (NYHA) functional class I had higher values than men. Although the 6MWT significantly discriminated all NYHA classes for both sexes, only 1 equation discriminated all NYHA classes. No significant differences in the area under the receiver operating-characteristic curve were noted between achieved percentage values and 6MWT. Despite strong univariate significance, achieved percentage values did not retain multivariate significance. The 6MWT was independent from N-terminal brain natriuretic propeptide, NYHA, left ventricular ejection fraction, and peak oxygen uptake. We confirmed 6MWT to be a strong and independent risk predictor for both sexes. Because the prognostic power of 6MWT is not enhanced using percentage achieved of published reference equations, we suggest recalibration of these reference values rather than discarding this approach.

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

Can insoluble polysaccharide concentration in dental plaque, sugar exposure and cariogenic microorganisms predict early childhood caries? A follow-up study.

PubMed

Parisotto, T M; Stipp, R; Rodrigues, L K A; Mattos-Graner, R O; Costa, L S; Nobre-Dos-Santos, M

2015-08-01

Insoluble polysaccharide (IP) has been associated with caries prevalence in young children. However, the power of IP to predict ECC needs to be demonstrated. To assess the relationships between early childhood caries (ECC) and extracellular insoluble polysaccharides (IP) in dental plaque, sugar exposure and cariogenic microorganisms. Visible plaque on maxillary incisors was recorded, followed by caries diagnosis in 65 preschoolers (3-4 years) at baseline and after 1 year. Plaque was collected for mutans streptococci (MS), total microorganism (TM) and lactobacilli (LB) enumerations in selective media, as well as for IP analysis, which was later assessed by colorimetry. Sugar/sucrose exposure was assessed by a diet chart. Positive correlations were found among the prevalence of caries and MS, TM, LB, solid sucrose and visible dental plaque. Additionally, children with IP concentrations in dental plaque higher than 2.36 μg/mg (odds ratio-OR=6.8), with visible plaque on maxillary incisors (OR=4.3), harbouring LB (OR=13) and exposed to solid sugar more than twice/day (OR=5) showed higher risk of developing caries (p<0.05). Extracellular insoluble polysaccharides, solid sugar/sucrose, visible dental plaque and cariogenic microorganisms could predict caries development, partially explaining the ECC pattern. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sex differences in personality traits and gender-related occupational preferences across 53 nations: testing evolutionary and social-environmental theories.

PubMed

Lippa, Richard A

2010-06-01

Using data from over 200,000 participants from 53 nations, I examined the cross-cultural consistency of sex differences for four traits: extraversion, agreeableness, neuroticism, and male-versus-female-typical occupational preferences. Across nations, men and women differed significantly on all four traits (mean ds = -.15, -.56, -.41, and 1.40, respectively, with negative values indicating women scoring higher). The strongest evidence for sex differences in SDs was for extraversion (women more variable) and for agreeableness (men more variable). United Nations indices of gender equality and economic development were associated with larger sex differences in agreeableness, but not with sex differences in other traits. Gender equality and economic development were negatively associated with mean national levels of neuroticism, suggesting that economic stress was associated with higher neuroticism. Regression analyses explored the power of sex, gender equality, and their interaction to predict men's and women's 106 national trait means for each of the four traits. Only sex predicted means for all four traits, and sex predicted trait means much more strongly than did gender equality or the interaction between sex and gender equality. These results suggest that biological factors may contribute to sex differences in personality and that culture plays a negligible to small role in moderating sex differences in personality.

Detection of regional infrasound signals using array data: Testing, tuning, and physical interpretation

DOE PAGES

Park, Junghyun; Stump, Brian W.; Hayward, Chris; ...

2016-07-14

This work quantifies the physical characteristics of infrasound signal and noise, assesses their temporal variations, and determines the degree to which these effects can be predicted by time-varying atmospheric models to estimate array and network performance. An automated detector that accounts for both correlated and uncorrelated noise is applied to infrasound data from three seismo-acoustic arrays in South Korea (BRDAR, CHNAR, and KSGAR), cooperatively operated by Korea Institute of Geoscience and Mineral Resources (KIGAM) and Southern Methodist University (SMU). Arrays located on an island and near the coast have higher noise power, consistent with both higher wind speeds and seasonablymore » variable ocean wave contributions. On the basis of the adaptive F-detector quantification of time variable environmental effects, the time-dependent scaling variable is shown to be dependent on both weather conditions and local site effects. Significant seasonal variations in infrasound detections including daily time of occurrence, detection numbers, and phase velocity/azimuth estimates are documented. These time-dependent effects are strongly correlated with atmospheric winds and temperatures and are predicted by available atmospheric specifications. As a result, this suggests that commonly available atmospheric specifications can be used to predict both station and network detection performance, and an appropriate forward model improves location capabilities as a function of time.« less

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

PubMed

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

2016-10-01

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

Detection of regional infrasound signals using array data: Testing, tuning, and physical interpretation.

PubMed

Park, Junghyun; Stump, Brian W; Hayward, Chris; Arrowsmith, Stephen J; Che, Il-Young; Drob, Douglas P

2016-07-01

This work quantifies the physical characteristics of infrasound signal and noise, assesses their temporal variations, and determines the degree to which these effects can be predicted by time-varying atmospheric models to estimate array and network performance. An automated detector that accounts for both correlated and uncorrelated noise is applied to infrasound data from three seismo-acoustic arrays in South Korea (BRDAR, CHNAR, and KSGAR), cooperatively operated by Korea Institute of Geoscience and Mineral Resources (KIGAM) and Southern Methodist University (SMU). Arrays located on an island and near the coast have higher noise power, consistent with both higher wind speeds and seasonably variable ocean wave contributions. On the basis of the adaptive F-detector quantification of time variable environmental effects, the time-dependent scaling variable is shown to be dependent on both weather conditions and local site effects. Significant seasonal variations in infrasound detections including daily time of occurrence, detection numbers, and phase velocity/azimuth estimates are documented. These time-dependent effects are strongly correlated with atmospheric winds and temperatures and are predicted by available atmospheric specifications. This suggests that commonly available atmospheric specifications can be used to predict both station and network detection performance, and an appropriate forward model improves location capabilities as a function of time.

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.

Potential role of liver enzymes levels as predictor markers of glucose metabolism disorders in Tunisian population.

PubMed

Bouhajja, Houda; Abdelhedi, Rania; Amouri, Ali; Hadj Kacem, Faten; Marrakchi, Rim; Safi, Wajdi; Mrabet, Houcem; Chtourou, Lassaad; Charfi, Nadia; Fourati, Mouna; Bensassi, Salwa; Jamoussi, Kamel; Abid, Mohamed; Ayadi, Hammadi; Feki, Mouna Mnif; Elleuch, Noura Bougacha

2018-03-10

The relationship between liver enzymes and type 2 diabetes (T2D) risk is inconclusive. We aimed to evaluate the association between liver markers and risk of carbohydrate metabolism disorders and their discriminatory power for T2D prediction. This cross-sectional study enrolled 216 participants classified as normoglycemic, prediabetes, newly-diagnosed diabetes and diagnosed diabetes. All participants underwent anthropometric and biochemical measurements. The relationship between hepatic enzymes and glucose metabolism markers was evaluated by ANCOVA analyses. The associations between liver enzymes and incident carbohydrate metabolism disorders were analyzed through logistic regression and their discriminatory capacity for T2D by receiver operating characteristic (ROC) analysis. High alkaline phosphatase (AP), alanine aminotransferase (ALT), γ-glutamyltransferase (γGT) and aspartate aminotrasferase (AST) levels were independently related to decreased insulin sensitivity. Interestingly, higher AP level was significantly associated with increased risk of prediabetes (p=0.017), newly-diagnosed diabetes (p=0.004) and T2D (p=0.007). Elevated γGT level was an independent risk factor for T2D (p=0.032) and undiagnosed-T2D (p=0.010) in prediabetic and normoglycemic subjects, respectively. In ROC analysis, AP was a powerful predictor of incident diabetes and significantly improved T2D prediction. Liver enzymes within normal range, specifically AP levels, are associated with increased risk of carbohydrate metabolism disorders and significantly improved T2D prediction.

Large eddy simulation for predicting turbulent heat transfer in gas turbines

PubMed Central

Tafti, Danesh K.; He, Long; Nagendra, K.

2014-01-01

Blade cooling technology will play a critical role in the next generation of propulsion and power generation gas turbines. Accurate prediction of blade metal temperature can avoid the use of excessive compressed bypass air and allow higher turbine inlet temperature, increasing fuel efficiency and decreasing emissions. Large eddy simulation (LES) has been established to predict heat transfer coefficients with good accuracy under various non-canonical flows, but is still limited to relatively simple geometries and low Reynolds numbers. It is envisioned that the projected increase in computational power combined with a drop in price-to-performance ratio will make system-level simulations using LES in complex blade geometries at engine conditions accessible to the design process in the coming one to two decades. In making this possible, two key challenges are addressed in this paper: working with complex intricate blade geometries and simulating high-Reynolds-number (Re) flows. It is proposed to use the immersed boundary method (IBM) combined with LES wall functions. A ribbed duct at Re=20 000 is simulated using the IBM, and a two-pass ribbed duct is simulated at Re=100 000 with and without rotation (rotation number Ro=0.2) using LES with wall functions. The results validate that the IBM is a viable alternative to body-conforming grids and that LES with wall functions reproduces experimental results at a much lower computational cost. PMID:25024418

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.

A prepositioned areal electrofishing apparatus for sampling stream habitats

USGS Publications Warehouse

Fisher, William L.; Brown, Marshall E.

1993-01-01

We describe the design, use, and sampling characteristics ofan electrofishing apparatus used to sample fish in stream habitats. The apparatus uses two prepositioned areal electrofishing devices (PAED) of different designs, a bottom parallel electrode PAED and a suspended dropper electrode PAED. To determine the effective immobilization ranges of the PAEDs, we evaluated intensities and shapes of the PAEDs' electrical fields, and the electroshock responses of fish in cages in concrete tanks and in four streams in Alabama with different water conductivities. Electroshock responses indicated that complete immobilization occurred at voltage gradients of 1.0 V/cm or higher (voltage drop, 400 V AC), as far as 35 cm from the PAED electrodes, although some fish were immobilized up to 65 cm away at 0.3 V/cm. We estimated the immobilization (stun) power density threshold to be about 10 μW/cm3. Stream evaluations of the PAEDs revealed that higher voltages were needed to immobilize fish at lower (35 μS/cm) and higher (120 and 125 μS/cm) water conductivities, whereas lower voltages were required at an intermediate conductivity (60 μS/cm). These results conformed with the predictions of power transfer theory and underscored the need to calibrate PAEDs to stream conductivities to standardize the effective sampling range.

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

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

PubMed

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

2017-09-01

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

Development and implementation of a dynamic TES dispatch control component in a PV-CSP techno-economic performance modelling tool

NASA Astrophysics Data System (ADS)

Hansson, Linus; Guédez, Rafael; Larchet, Kevin; Laumert, Bjorn

2017-06-01

The dispatchability offered by thermal energy storage (TES) in concentrated solar power (CSP) and solar hybrid plants based on such technology presents the most important difference compared to power generation based only on photovoltaics (PV). This has also been one reason for recent hybridization efforts of the two technologies and the creation of Power Purchase Agreement (PPA) payment schemes based on offering higher payment multiples during daily hours of higher (peak or priority) demand. Recent studies involving plant-level thermal energy storage control strategies are however to a large extent based on pre-determined approaches, thereby not taking into account the actual dynamics of thermal energy storage system operation. In this study, the implementation of a dynamic dispatch strategy in the form of a TRNSYS controller for hybrid PV-CSP plants in the power-plant modelling tool DYESOPT is presented. In doing this it was attempted to gauge the benefits of incorporating a day-ahead approach to dispatch control compared to a fully pre-determined approach determining hourly dispatch only once prior to annual simulation. By implementing a dynamic strategy, it was found possible to enhance technical and economic performance for CSP-only plants designed for peaking operation and featuring low values of the solar multiple. This was achieved by enhancing dispatch control, primarily by taking storage levels at the beginning of every simulation day into account. The sequential prediction of the TES level could therefore be improved, notably for evaluated plants without integrated PV, for which the predicted storage levels deviated less than when PV was present in the design. While also featuring dispatch performance gains, optimal plant configurations for hybrid PV-CSP was found to present a trade-off in economic performance in the form of an increase in break-even electricity price when using the dynamic strategy which was offset to some extent by a reduction in upfront investment cost. An increase in turbine starts for the implemented strategy however highlights that this is where further improvements can be made.

Finite coupling corrections to holographic predictions for hot QCD

DOE PAGES

Waeber, Sebastian; Schafer, Andreas; Vuorinen, Aleksi; ...

2015-11-13

Finite ’t Hooft coupling corrections to multiple physical observables in strongly coupled N=4 supersymmetric Yang-Mills plasma are examined, in an attempt to assess the stability of the expansion in inverse powers of the ’t Hooft coupling λ. Observables considered include thermodynamic quantities, transport coefficients, and quasinormal mode frequencies. Furthermore large λ expansions for quasinormal mode frequencies are notably less well behaved than the expansions of other quantities, we find that a partial resummation of higher order corrections can significantly reduce the sensitivity of the results to the value of λ.

Shadow image on the retina of a defocused eye

NASA Astrophysics Data System (ADS)

Lenskii, A. V.

1994-04-01

Some visual conditions for transparent objects positioned within and beyond the accommodation limits on the path of the light traveling from a remote source of a small angular size are theoretically considered for the naked eye with a strong ametropia. The resolving power and admissible angular size of the light source are evaluated. The predicted possibility of seeing sufficiently extended transparent gratings at such distances has found that the density of ruling of the grating-object is higher than the ultimate angular resolution of the normal eye.

Laser power beaming: an emerging technology for power transmission and propulsion in space

NASA Astrophysics Data System (ADS)

Bennett, Harold E.

1997-05-01

A ground based laser beam transmitted to space can be used as an electric utility for satellites. It can significantly increase the electric power available to operate a satellite or to transport it from low earth orbit (LEO) to mid earth or geosynchronous orbits. The increase in electrical power compared to that obtainable from the sun is as much as 1000% for the same size solar panels. An increase in satellite electric power is needed to meet the increasing demands for power caused by the advent of 'direct to home TV,' for increased telecommunications, or for other demands made by the burgeoning 'space highway.' Monetary savings as compared to putting up multiple satellites in the same 'slot' can be over half a billion dollars. To obtain propulsion, the laser power can be beamed through the atmosphere to an 'orbit transfer vehicle' (OTV) satellite which travels back and forth between LEO and higher earth orbits. The OTV will transport the satellite into orbit as does a rocket but does not require the heavy fuel load needed if rocket propulsion is used. Monetary savings of 300% or more in launch costs are predicted. Key elements in the proposed concept are a 100 to 200 kW free- electron laser operating at 0.84 m in the photographic infrared region of the spectrum and a novel adaptive optic telescope.

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.

Catalytic power of enzymes decreases with temperature: New insights for understanding soil C cycling and microbial ecology under warming.

PubMed

Alvarez, Gaël; Shahzad, Tanvir; Andanson, Laurence; Bahn, Michael; Wallenstein, Matthew D; Fontaine, Sébastien

2018-04-23

Most current models of soil C dynamics predict that climate warming will accelerate soil C mineralization, resulting in a long-term CO 2 release and positive feedback to global warming. However, ecosystem warming experiments show that CO 2 loss from warmed soils declines to control levels within a few years. Here, we explore the temperature dependence of enzymatic conversion of polymerized soil organic C (SOC) into assimilable compounds, which is presumed the rate-limiting step of SOC mineralization. Combining literature review, modelling and enzyme assays, we studied the effect of temperature on activity of enzymes considering their thermal inactivation and catalytic activity. We defined the catalytic power of enzymes (E power ) as the cumulative amount of degraded substrate by one unit of enzyme until its complete inactivation. We show a universal pattern of enzyme's thermodynamic properties: activation energy of catalytic activity (EA cat ) < activation energy of thermal inactivation (EA inact ). By investing in stable enzymes (high EA inact ) having high catalytic activity (low EA cat ), microorganisms may maximize the E power of their enzymes. The counterpart of such EAs' hierarchical pattern is the higher relative temperature sensitivity of enzyme inactivation than catalysis, resulting in a reduction in E power under warming. Our findings could explain the decrease with temperature in soil enzyme pools, microbial biomass (MB) and carbon use efficiency (CUE) reported in some warming experiments and studies monitoring the seasonal variation in soil enzymes. They also suggest that a decrease in soil enzyme pools due to their faster inactivation under warming contributes to the observed attenuation of warming effect on soil C mineralization. This testable theory predicts that the ultimate response of SOC degradation to warming can be positive or negative depending on the relative temperature response of E power and microbial production of enzymes. © 2018 John Wiley & Sons Ltd.

The Association Between CMV Viremia or Endoscopic Features and Histopathological Characteristics of CMV Colitis in Patients with Underlying Ulcerative Colitis.

PubMed

Yang, Hong; Zhou, Weixun; Lv, Hong; Wu, Dongsheng; Feng, Yunlu; Shu, Huijun; Jin, Meng; Hu, Lingling; Wang, Qiang; Wu, Dong; Chen, Jie; Qian, Jiaming

2017-05-01

Cytomegalovirus (CMV) infection has been shown to be related to severe or steroid-refractory ulcerative colitis (UC) flare-ups. The aim of this study was to evaluate the endoscopic and pathological characteristics of CMV colitis in patients with UC and to assess the predictive value of the endoscopic and pathological features of CMV colitis. A total of 50 consecutive UC patients with CMV infection who were admitted to Peking Union Medical College Hospital from 2010 to 2015 were enrolled in this study. Twenty-five UC patients with CMV infection (50.0%) had concurrent CMV colitis. When the cutoff value was set at 1150 copies, the sensitivity and specificity of blood CMV DNAq polymerase chain reaction for predicting CMV colitis were 44.4% and 78.9%, respectively. A higher proportion of endoscopic punched-out ulcers, irregular ulcers, and cobblestone-like appearance were observed among the patients in the CMV colitis group than those in the non-CMV colitis group (52.0% versus 20.0%, 60.0% versus 16.0%, and 20.0% versus 0%, respectively, P < 0.05). The number of CMV inclusion bodies per high-power field was significantly higher in those with punch-out ulcerations (25.7% versus 60.0%, P < 0.05). A higher grade of pathological inflammation was observed in the CMV colitis group than in the control group (68.0% versus 44.0%). Characteristic endoscopic features with punch-out ulcers and high CMV viremia load may be useful for predicting the presence of CMV colitis in histology. Punch-out ulcers were found to be associated with a higher number of inclusion bodies on histology, suggesting a role of targeted biopsy for endoscopist.

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.

Topography and Higher Order Corneal Aberrations of the Fellow Eye in Unilateral Keratoconus.

PubMed

Aksoy, Sibel; Akkaya, Sezen; Özkurt, Yelda; Kurna, Sevda; Açıkalın, Banu; Şengör, Tomris

2017-10-01

Comparison of topography and corneal higher order aberrations (HOA) data of fellow normal eyes of unilateral keratoconus patients with keratoconus eyes and control group. The records of 196 patients with keratoconus were reviewed. Twenty patients were identified as unilateral keratoconus. The best corrected visual acuity (BCVA), topography and aberration data of the unilateral keratoconus patients' normal eyes were compared with their contralateral keratoconus eyes and with control group eyes. For statistical analysis, flat and steep keratometry values, average corneal power, cylindrical power, surface regularity index (SRI), surface asymmetry index (SAI), inferior-superior ratio (I-S), keratoconus prediction index, and elevation-depression power (EDP) and diameter (EDD) topography indices were selected. Mean age of the unilateral keratoconus patients was 26.05±4.73 years and that of the control group was 23.6±8.53 years (p>0.05). There was no statistical difference in BCVA between normal and control eyes (p=0.108), whereas BCVA values were significantly lower in eyes with keratoconus (p=0.001). Comparison of quantitative topographic indices between the groups showed that all indices except the I-S ratio were significantly higher in the normal group than in the control group (p<0.05). The most obvious differences were in the SRI, SAI, EDP, and EDD values. All topographic indices were higher in the keratoconus eyes compared to the normal fellow eyes. There was no difference between normal eyes and the control group in terms of spherical aberration, while coma, trefoil, irregular astigmatism, and total HOA values were higher in the normal eyes of unilateral keratoconus patients (p<0.05). All HOA values were higher in keratoconus eyes than in the control group. According to our study, SRI, SAI, EDP, EDD values, and HOA other than spherical aberration were higher in the clinically and topographically normal fellow eyes of unilateral keratoconus patients when compared to a control group. This finding may be due to the mild asymmetric and morphologic changes in the subclinical stage of keratoconus leading to deterioration in the indicators of corneal irregularity and elevation changes. Therefore, these eyes may be exhibiting the early form of the disease.

Novel Approach to Classify Plants Based on Metabolite-Content Similarity.

PubMed

Liu, Kang; Abdullah, Azian Azamimi; Huang, Ming; Nishioka, Takaaki; Altaf-Ul-Amin, Md; Kanaya, Shigehiko

2017-01-01

Secondary metabolites are bioactive substances with diverse chemical structures. Depending on the ecological environment within which they are living, higher plants use different combinations of secondary metabolites for adaptation (e.g., defense against attacks by herbivores or pathogenic microbes). This suggests that the similarity in metabolite content is applicable to assess phylogenic similarity of higher plants. However, such a chemical taxonomic approach has limitations of incomplete metabolomics data. We propose an approach for successfully classifying 216 plants based on their known incomplete metabolite content. Structurally similar metabolites have been clustered using the network clustering algorithm DPClus. Plants have been represented as binary vectors, implying relations with structurally similar metabolite groups, and classified using Ward's method of hierarchical clustering. Despite incomplete data, the resulting plant clusters are consistent with the known evolutional relations of plants. This finding reveals the significance of metabolite content as a taxonomic marker. We also discuss the predictive power of metabolite content in exploring nutritional and medicinal properties in plants. As a byproduct of our analysis, we could predict some currently unknown species-metabolite relations.

Novel Approach to Classify Plants Based on Metabolite-Content Similarity

PubMed Central

Abdullah, Azian Azamimi; Huang, Ming; Nishioka, Takaaki

2017-01-01

Secondary metabolites are bioactive substances with diverse chemical structures. Depending on the ecological environment within which they are living, higher plants use different combinations of secondary metabolites for adaptation (e.g., defense against attacks by herbivores or pathogenic microbes). This suggests that the similarity in metabolite content is applicable to assess phylogenic similarity of higher plants. However, such a chemical taxonomic approach has limitations of incomplete metabolomics data. We propose an approach for successfully classifying 216 plants based on their known incomplete metabolite content. Structurally similar metabolites have been clustered using the network clustering algorithm DPClus. Plants have been represented as binary vectors, implying relations with structurally similar metabolite groups, and classified using Ward's method of hierarchical clustering. Despite incomplete data, the resulting plant clusters are consistent with the known evolutional relations of plants. This finding reveals the significance of metabolite content as a taxonomic marker. We also discuss the predictive power of metabolite content in exploring nutritional and medicinal properties in plants. As a byproduct of our analysis, we could predict some currently unknown species-metabolite relations. PMID:28164123

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.

Low-Cost CdTe/Silicon Tandem Solar Cells

DOE PAGES

Tamboli, Adele C.; Bobela, David C.; Kanevce, Ana; ...

2017-09-06

Achieving higher photovoltaic efficiency in single-junction devices is becoming increasingly difficult, but tandem modules offer the possibility of significant efficiency improvements. By device modeling we show that four-terminal CdTe/Si tandem solar modules offer the prospect of 25%-30% module efficiency, and technoeconomic analysis predicts that these efficiency gains can be realized at costs per Watt that are competitive with CdTe and Si single junction alternatives. The cost per Watt of the modeled tandems is lower than crystalline silicon, but slightly higher than CdTe alone. But, these higher power modules reduce area-related balance of system costs, providing increased value especially in area-constrainedmore » applications. This avenue for high-efficiency photovoltaics enables improved performance on a near-term timeframe, as well as a path to further reduced levelized cost of electricity as module and cell processes continue to advance.« less

Low-Cost CdTe/Silicon Tandem Solar Cells

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

Tamboli, Adele C.; Bobela, David C.; Kanevce, Ana

Achieving higher photovoltaic efficiency in single-junction devices is becoming increasingly difficult, but tandem modules offer the possibility of significant efficiency improvements. By device modeling we show that four-terminal CdTe/Si tandem solar modules offer the prospect of 25%-30% module efficiency, and technoeconomic analysis predicts that these efficiency gains can be realized at costs per Watt that are competitive with CdTe and Si single junction alternatives. The cost per Watt of the modeled tandems is lower than crystalline silicon, but slightly higher than CdTe alone. But, these higher power modules reduce area-related balance of system costs, providing increased value especially in area-constrainedmore » applications. This avenue for high-efficiency photovoltaics enables improved performance on a near-term timeframe, as well as a path to further reduced levelized cost of electricity as module and cell processes continue to advance.« less

An experimental study of dynamic characteristics of labyrinth seal

NASA Technical Reports Server (NTRS)

Iwatsubo, Takuzo; Fukumoto, Koji; Mochida, Hideyuki

1994-01-01

The fluid force due to labyrinth seal sometimes makes the turbomachineries unstable under higher rotating speed, higher pressure and higher power. Therefore, it is important to predict the magnitude and the direction of the fluid force and to evaluate the stability of the rotor system in design process. This paper shows the experimental results of the fluid force induced by a straight labyrinth seal and the rotordynamic coefficients calculated from the fluid force. Influences of the number of fins under the rotating speed, whirling speed, inlet pressure, and inlet tangential velocity are mainly investigated on a stability of the rotor system. The results show that increase of the number of fins makes the fluid force small and the rotor system stable, an increase of inlet pressure makes the fluid forces large and an increase of inlet tangential velocity makes the rotor system unstable.

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.

Identifying Effective Signals to Predict Deleted and Suspended Accounts on Twitter across Languages

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

Volkova, Svitlana; Bell, Eric B.

Social networks have an ephemerality to them where accounts and messages are constantly being edited, deleted, or marked as private. This continuous change comes from concerns around privacy, a potential desire for deception, and spam-like behavior. In this study we analyze multiple large datasets of thousands of active and deleted Twitter accounts to produce a series of predictive features for the removal or shutdown of an account. We have selected these accounts from speakers of three languages -- Russian, Spanish, and English to evaluate if speakers of various languages behave differently with regards to deleting accounts. We find that unlikemore » previously used profile and network features, the discourse of deleted vs. active accounts forms the basis for highly accurate account deletion prediction. More precisely, we observed that the presence of a certain set of terms in user tweets leads to a higher likelihood for that user's account deletion. We show that the predictive power of profile, language, affect, and network features is not consistent across speakers of the three evaluated languages.« less

A modification of Murray's law for shear-thinning rheology.

PubMed

McGah, Patrick M; Capobianchi, Massimo

2015-05-01

This study reformulates Murray's well-known principle of minimum work as applied to the cardiovascular system to include the effects of the shear-thinning rheology of blood. The viscous behavior is described using the extended modified power law (EMPL), which is a time-independent, but shear-thinning rheological constitutive equation. The resulting minimization problem is solved numerically for typical parameter ranges. The non-Newtonian analysis still predicts the classical cubic diameter dependence of the volume flow rate and the cubic branching law. The current analysis also predicts a constant wall shear stress throughout the vascular tree, albeit with a numerical value about 15-25% higher than the Newtonian analysis. Thus, experimentally observed deviations from the cubic branching law or the predicted constant wall shear stress in the vasculature cannot likely be attributed to blood's shear-thinning behavior. Further differences between the predictions of the non-Newtonian and the Newtonian analyses are highlighted, and the limitations of the Newtonian analysis are discussed. Finally, the range and limits of applicability of the current results as applied to the human arterial tree are also discussed.

The Predictive Effects of Protection Motivation Theory on Intention and Behaviour of Physical Activity in Patients with Type 2 Diabetes

PubMed Central

Ali Morowatisharifabad, Mohammad; Abdolkarimi, Mahdi; Asadpour, Mohammad; Fathollahi, Mahmood Sheikh; Balaee, Parisa

2018-01-01

INTRODUCTION: Theory-based education tailored to target behaviour and group can be effective in promoting physical activity. AIM: The purpose of this study was to examine the predictive power of Protection Motivation Theory on intent and behaviour of Physical Activity in Patients with Type 2 Diabetes. METHODS: This descriptive study was conducted on 250 patients in Rafsanjan, Iran. To examine the scores of protection motivation theory structures, a researcher-made questionnaire was used. Its validity and reliability were confirmed. The level of physical activity was also measured by the International Short - form Physical Activity Inventory. Its validity and reliability were also approved. Data were analysed by statistical tests including correlation coefficient, chi-square, logistic regression and linear regression. RESULTS: The results revealed that there was a significant correlation between all the protection motivation theory constructs and the intention to do physical activity. The results showed that the Theory structures were able to predict 60% of the variance of physical activity intention. The results of logistic regression demonstrated that increase in the score of physical activity intent and self - efficacy increased the chance of higher level of physical activity by 3.4 and 1.5 times, respectively OR = (3.39, 1.54). CONCLUSION: Considering the ability of protection motivation theory structures to explain the physical activity behaviour, interventional designs are suggested based on the structures of this theory, especially to improve self -efficacy as the most powerful factor in predicting physical activity intention and behaviour. PMID:29731945

Electroencephalographic identifiers of motor adaptation learning

NASA Astrophysics Data System (ADS)

Özdenizci, Ozan; Yalçın, Mustafa; Erdoğan, Ahmetcan; Patoğlu, Volkan; Grosse-Wentrup, Moritz; Çetin, Müjdat

2017-08-01

Objective. Recent brain-computer interface (BCI) assisted stroke rehabilitation protocols tend to focus on sensorimotor activity of the brain. Relying on evidence claiming that a variety of brain rhythms beyond sensorimotor areas are related to the extent of motor deficits, we propose to identify neural correlates of motor learning beyond sensorimotor areas spatially and spectrally for further use in novel BCI-assisted neurorehabilitation settings. Approach. Electroencephalographic (EEG) data were recorded from healthy subjects participating in a physical force-field adaptation task involving reaching movements through a robotic handle. EEG activity recorded during rest prior to the experiment and during pre-trial movement preparation was used as features to predict motor adaptation learning performance across subjects. Main results. Subjects learned to perform straight movements under the force-field at different adaptation rates. Both resting-state and pre-trial EEG features were predictive of individual adaptation rates with relevance of a broad network of beta activity. Beyond sensorimotor regions, a parieto-occipital cortical component observed across subjects was involved strongly in predictions and a fronto-parietal cortical component showed significant decrease in pre-trial beta-powers for users with higher adaptation rates and increase in pre-trial beta-powers for users with lower adaptation rates. Significance. Including sensorimotor areas, a large-scale network of beta activity is presented as predictive of motor learning. Strength of resting-state parieto-occipital beta activity or pre-trial fronto-parietal beta activity can be considered in BCI-assisted stroke rehabilitation protocols with neurofeedback training or volitional control of neural activity for brain-robot interfaces to induce plasticity.

Kinematic Mechanisms of How Power Training Improves Healthy Old Adults' Gait Velocity.

PubMed

Beijersbergen, Chantal M I; Granacher, Urs; Gäbler, Martijn; Devita, Paul; Hortobágyi, Tibor

2017-01-01

Slow gait predicts many adverse clinical outcomes in old adults, but the mechanisms of how power training can minimize the age-related loss of gait velocity is unclear. We examined the effects of 10 wk of lower extremity power training and detraining on healthy old adults' lower extremity muscle power and gait kinematics. As part of the Potsdam Gait Study, participants started with 10 wk of power training followed by 10 wk of detraining (n = 16), and participants started with a 10-wk control period followed by 10 wk of power training (n = 16). We measured gait kinematics (stride characteristic and joint kinematics) and isokinetic power of the ankle plantarflexor (20°·s, 40°·s, and 60°·s) and knee extensor and flexor (60°·s, 120°·s, and 180°·s) muscles at weeks 0, 10, and 20. Power training improved isokinetic muscle power by ~30% (P ≤ 0.001) and fast (5.9%, P < 0.05) but not habitual gait velocity. Ankle plantarflexor velocity measured during gait at fast pace decreased by 7.9% (P < 0.05). The changes isokinetic muscle power and joint kinematics did not correlate with increases in fast gait velocity. The mechanisms that increased fast gait velocity involved higher cadence (r = 0.86, P ≤ 0.001) rather than longer strides (r = 0.49, P = 0.066). Detraining did not reverse the training-induced increases in muscle power and fast gait velocity. Because increases in muscle power and modifications in joint kinematics did not correlate with increases in fast gait velocity, kinematic mechanisms seem to play a minor role in improving healthy old adults' fast gait velocity after power training.

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.

High Efficiency Microwave Power Amplifier: From the Lab to Industry

NASA Technical Reports Server (NTRS)

Sims, William Herbert, III; Bell, Joseph L. (Technical Monitor)

2001-01-01

Since the beginnings of space travel, various microwave power amplifier designs have been employed. These included Class-A, -B, and -C bias arrangements. However, shared limitation of these topologies is the inherent high total consumption of input power associated with the generation of radio frequency (RF)/microwave power. The power amplifier has always been the largest drain for the limited available power on the spacecraft. Typically, the conversion efficiency of a microwave power amplifier is 10 to 20%. For a typical microwave power amplifier of 20 watts, input DC power of at least 100 watts is required. Such a large demand for input power suggests that a better method of RF/microwave power generation is required. The price paid for using a linear amplifier where high linearity is unnecessary includes higher initial and operating costs, lower DC-to-RF conversion efficiency, high power consumption, higher power dissipation and the accompanying need for higher capacity heat removal means, and an amplifier that is more prone to parasitic oscillation. The first use of a higher efficiency mode of power generation was described by Baxandall in 1959. This higher efficiency mode, Class-D, is achieved through distinct switching techniques to reduce the power losses associated with switching, conduction, and gate drive losses of a given transistor.

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

A power-balance model for local helicity injection startup in a spherical tokamak

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

Barr, Jayson L.; Bongard, Michael W.; Burke, Marcus G.

A 0D circuit model for predicting I p( t) in Local Helicity Injection (LHI) discharges is developed. Analytic formulas for estimating the surface flux of finite-A plasmas developed are modified and expanded to treat highly shaped, ultralow-A tokamak geometry using a database of representative equilibria. Model predictions are compared to sample LHI discharges in the A ~ 1 Pegasus spherical tokamak, and are found to agree within 15% of experimental I p( t). High performance LHI discharges are found to follow the Taylor relaxation current limit for approximately the first half of the current ramp, or I p ≲ 75more » kA. The second half of the current ramp follows a limit imposed by power-balance as plasmas expand from high- A to ultralow- A. Here, this shape evolution generates a significant drop in external plasma inductance, effectively using the plasma’s initially high inductance to drive the current ramp and provide > 70% of the current drive V-s. Projections using this model indicate the relative influences of higher helicity input rate and injector current on the attainable total plasma current.« less

Mental Health Disorders, Psychological Distress, and Suicidality in a Diverse Sample of Lesbian, Gay, Bisexual, and Transgender Youths

PubMed Central

Garofalo, Robert; Emerson, Erin M.

2010-01-01

Objectives. We examined associations of race/ethnicity, gender, and sexual orientation with mental disorders among lesbian, gay, bisexual, and transgender (LGBT) youths. Methods. We assessed mental disorders by administering a structured diagnostic interview to a community sample of 246 LGBT youths aged 16 to 20 years. Participants also completed the Brief Symptom Inventory 18 (BSI 18). Results. One third of participants met criteria for any mental disorder, 17% for conduct disorder, 15% for major depression, and 9% for posttraumatic stress disorder. Anorexia and bulimia were rare. Lifetime suicide attempts were frequent (31%) but less so in the prior 12 months (7%). Few racial/ethnic and gender differences were statistically significant. Bisexually identified youths had lower prevalences of every diagnosis. The BSI 18 had high negative predictive power (90%) and low positive predictive power (25%) for major depression. Conclusions. LGBT youths had higher prevalences of mental disorder diagnoses than youths in national samples, but were similar to representative samples of urban, racial/ethnic minority youths. Suicide behaviors were similar to those among representative youth samples in the same geographic area. Questionnaires measuring psychological distress may overestimate depression prevalence among this population. PMID:20966378

Spectrotemporal dynamics of the EEG during working memory encoding and maintenance predicts individual behavioral capacity.

PubMed

Bashivan, Pouya; Bidelman, Gavin M; Yeasin, Mohammed

2014-12-01

We investigated the effect of memory load on encoding and maintenance of information in working memory. Electroencephalography (EEG) signals were recorded while participants performed a modified Sternberg visual memory task. Independent component analysis (ICA) was used to factorise the EEG signals into distinct temporal activations to perform spectrotemporal analysis and localisation of source activities. We found 'encoding' and 'maintenance' operations were correlated with negative and positive changes in α-band power, respectively. Transient activities were observed during encoding of information in the bilateral cuneus, precuneus, inferior parietal gyrus and fusiform gyrus, and a sustained activity in the inferior frontal gyrus. Strong correlations were also observed between changes in α-power and behavioral performance during both encoding and maintenance. Furthermore, it was also found that individuals with higher working memory capacity experienced stronger neural oscillatory responses during the encoding of visual objects into working memory. Our results suggest an interplay between two distinct neural pathways and different spatiotemporal operations during the encoding and maintenance of information which predict individual differences in working memory capacity observed at the behavioral level. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

A power-balance model for local helicity injection startup in a spherical tokamak

DOE PAGES

Barr, Jayson L.; Bongard, Michael W.; Burke, Marcus G.; ...

2018-05-15

A 0D circuit model for predicting I p( t) in Local Helicity Injection (LHI) discharges is developed. Analytic formulas for estimating the surface flux of finite-A plasmas developed are modified and expanded to treat highly shaped, ultralow-A tokamak geometry using a database of representative equilibria. Model predictions are compared to sample LHI discharges in the A ~ 1 Pegasus spherical tokamak, and are found to agree within 15% of experimental I p( t). High performance LHI discharges are found to follow the Taylor relaxation current limit for approximately the first half of the current ramp, or I p ≲ 75more » kA. The second half of the current ramp follows a limit imposed by power-balance as plasmas expand from high- A to ultralow- A. Here, this shape evolution generates a significant drop in external plasma inductance, effectively using the plasma’s initially high inductance to drive the current ramp and provide > 70% of the current drive V-s. Projections using this model indicate the relative influences of higher helicity input rate and injector current on the attainable total plasma current.« 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 ...

Predictors of stroke in patients with impaired glucose tolerance: results from the Nateglinide and Valsartan in Impaired Glucose Tolerance Outcomes Research trial.

PubMed

Preiss, David; Giles, Thomas D; Thomas, Laine E; Sun, Jie-Lena; Haffner, Steven M; Holman, Rury R; Standl, Eberhard; Mazzone, Theodore; Rutten, Guy E; Tognoni, Gianni; Chiang, Fu-Tien; McMurray, John J V; Califf, Robert M

2013-09-01

Risk factors for stroke are well-established in general populations but sparsely studied in individuals with impaired glucose tolerance. We identified predictors of stroke among participants with impaired glucose tolerance in the Nateglinide and Valsartan in Impaired Glucose Tolerance Outcomes Research (NAVIGATOR) trial. Cox proportional-hazard regression models were constructed using baseline variables, including the 2 medications studied, valsartan and nateglinide. Among 9306 participants, 237 experienced a stroke over 6.4 years. Predictors of stroke included classical risk factors such as existing cerebrovascular and coronary heart disease, higher pulse pressure, higher low-density lipoprotein cholesterol, older age, and atrial fibrillation. Other factors, including previous venous thromboembolism, higher waist circumference, lower estimated glomerular filtration rate, lower heart rate, and lower body mass index, provided additional important predictive information, yielding a C-index of 0.72. Glycemic measures were not predictive of stroke. Variables associated with stroke were similar in participants with no prior history of cerebrovascular disease at baseline. The most powerful predictors of stroke in patients with impaired glucose tolerance included a combination of established risk factors and novel variables, such as previous venous thromboembolism and elevated waist circumference, allowing moderately effective identification of high-risk individuals.

Isometric quadriceps strength determines sailing performance and neuromuscular fatigue during an upwind sailing emulation.

PubMed

Bourgois, Jan G; Callewaert, Margot; Celie, Bert; De Clercq, Dirk; Boone, Jan

2016-01-01

This study investigates the physiological responses to upwind sailing on a laser emulation ergometer and analyses the components of the physical profile that determine the physiological responses related to sailing level. Ten male high-level laser sailors performed an upwind sailing test, incremental cycling test and quadriceps strength test. During the upwind sailing test, heart rate (HR), oxygen uptake, ventilation, respiratory exchange ratio, rating of perceived exertion (RPE) and lactate concentration were measured, combined with near-infrared spectroscopy (NIRS) and electromyography (EMG) registration of the M. Vastus lateralis. Repeated measures ANOVA showed for the cardio-respiratory, metabolic and muscles responses (mean power frequency [MPF], root mean square [RMS], deoxy[Hb+Mb]) during the upwind sailing test an initial significant increase followed by a stabilisation, despite a constant increase in RPE. Stepwise regression analysis showed that better sailing level was for 46.5% predicted by lower MPF decrease. Lower MPF decrease was for 57.8% predicted by a higher maximal isometric quadriceps strength. In conclusion, this study indicates that higher sailing level was mainly determined by a lower rate of neuromuscular fatigue during the upwind sailing test (as indicated by MPF decrease). Additionally, the level of neuromuscular fatigue was mainly determined by higher maximal isometric quadriceps strength stressing the importance of resistance training in the planning of training.

Familial expressed emotion: outcome and course of Israeli patients with schizophrenia.

PubMed

Marom, Sofi; Munitz, Hanan; Jones, Peter B; Weizman, Abraham; Hermesh, Haggai

2002-01-01

We investigated the validity of expressed emotion (EE) in Israel. The study sample consisted of 108 patients with schizophrenia and 15 with schizoaffective disorder, and their key relatives. EE was rated with the Five Minute Speech Sample (FMSS). Patient households were categorized by EE and its two components: criticism and emotional overinvolvement. Patients were rated with the Brief Psychiatric Rating Scale (BPRS) at admission, at discharge, and 6 months after discharge. Readmissions were determined over a 9-month period. High EE and particularly high criticism were significantly associated with poorer outcome (higher rate of and earlier readmissions, and higher BPRS score at followup) and worse illness course (higher annual number of prior psychiatric hospital admissions). Odds ratios between high EE and high criticism and readmission were 2.6 and 3.5, respectively. The strongest predictor of earlier readmission was the interaction of high criticism x poor compliance with medication. The results converge to further confirm the notion that familial EE is a valid crosscultural predictor of the clinical course of schizophrenia. Moreover, EE has predictive power in very chronic samples. Criticism appears to be the crucial EE component linked with short-term outcome. Treatment aimed at reducing high criticism is warranted. The FMSS appears to have predictive validity.

Impact of higher order diagrams on phase equilibrium calculations for small molecules using lattice cluster theory

NASA Astrophysics Data System (ADS)

Zimmermann, Patrick; Walowski, Christoph; Enders, Sabine

2018-03-01

The Lattice Cluster Theory (LCT) provides a powerful tool to predict thermodynamic properties of large molecules (e.g., polymers) of different molecular architectures. When the pure-component parameters of a certain compound have been derived by adjustment to experimental data and the number of atoms is held constant within the molecule so that only the architecture is changed, the LCT is capable of predicting the properties of isomers without further parameter adjustment just based on the incorporation of molecular architecture. Trying to predict the thermodynamic properties of smaller molecules, one might face some challenges, which are addressed in this contribution. After factoring out the mean field term of the partition function, the LCT poses an expression that involves corrections to the mean field depending on molecular architecture, resulting in the free energy formally being expressed as a double series expansion in lattice coordination number z and interaction energy ɛ ˜ . In the process of deriving all contributing sub-structures within a molecule, some parts have been neglected to this point due to the double series expansion being truncated after the order ɛ˜ 2z-2. We consider the neglected parts that are of the order z-3 and reformulate the expression for the free energy within the LCT to achieve a higher predictive capability of the theory when it comes to small isomers and compressible systems. The modified version was successfully applied for phase equilibrium calculations of binary mixtures composed of linear and branched alkanes.

Mental health status, aggression, and poor driving distinguish traffic offenders from non-offenders but health status predicts driving behavior in both groups

PubMed Central

Abdoli, Nasrin; Farnia, Vahid; Delavar, Ali; Dortaj, Fariborz; Esmaeili, Alireza; Farrokhi, Noorali; Karami, Majid; Shakeri, Jalal; Holsboer-Trachsler, Edith; Brand, Serge

2015-01-01

Background In Iran, traffic accidents and deaths from traffic accidents are among the highest in the world, and generally, driver behavior rather than technical failures or environmental conditions are responsible for traffic accidents. In a previous study, we showed that among young Iranian male traffic offenders, poor mental health status, along with aggression, predicted poor driving behavior. The aims of the present study were twofold, to determine whether this pattern could be replicated among non-traffic offenders, and to compare the mental health status, aggression, and driving behavior of male traffic offenders and non-offenders. Methods A total of 850 male drivers (mean age =34.25 years, standard deviation =10.44) from Kermanshah (Iran) took part in the study. Of these, 443 were offenders (52.1%) and 407 (47.9%) were non-offenders with lowest driving penalty scores applying for attaining an international driving license. Participants completed a questionnaire booklet covering socio-demographic variables, traits of aggression, health status, and driving behavior. Results Compared to non-offenders, offenders reported higher aggression, poorer mental health status, and worse driving behavior. Among non-offenders, multiple regression indicated that poor health status, but not aggression, independently predicted poor driving behavior. Conclusion Compared to non-offenders, offenders reported higher aggression, poorer health status and driving behavior. Further, the predictive power of poorer mental health status, but not aggression, for driving behavior was replicated for male non-offenders. PMID:26300646

Optimization of multi-environment trials for genomic selection based on crop models.

PubMed

Rincent, R; Kuhn, E; Monod, H; Oury, F-X; Rousset, M; Allard, V; Le Gouis, J

2017-08-01

We propose a statistical criterion to optimize multi-environment trials to predict genotype × environment interactions more efficiently, by combining crop growth models and genomic selection models. Genotype × environment interactions (GEI) are common in plant multi-environment trials (METs). In this context, models developed for genomic selection (GS) that refers to the use of genome-wide information for predicting breeding values of selection candidates need to be adapted. One promising way to increase prediction accuracy in various environments is to combine ecophysiological and genetic modelling thanks to crop growth models (CGM) incorporating genetic parameters. The efficiency of this approach relies on the quality of the parameter estimates, which depends on the environments composing this MET used for calibration. The objective of this study was to determine a method to optimize the set of environments composing the MET for estimating genetic parameters in this context. A criterion called OptiMET was defined to this aim, and was evaluated on simulated and real data, with the example of wheat phenology. The MET defined with OptiMET allowed estimating the genetic parameters with lower error, leading to higher QTL detection power and higher prediction accuracies. MET defined with OptiMET was on average more efficient than random MET composed of twice as many environments, in terms of quality of the parameter estimates. OptiMET is thus a valuable tool to determine optimal experimental conditions to best exploit MET and the phenotyping tools that are currently developed.

Evaluation of half wave induction motor drive for use in passenger vehicles

NASA Technical Reports Server (NTRS)

Hoft, R. G.; Kawamura, A.; Goodarzi, A.; Yang, G. Q.; Erickson, C. L.

1985-01-01

Research performed at the University of Missouri-Columbia to devise and design a lower cost inverter induction motor drive for electrical propulsion of passenger vehicles is described. A two phase inverter motor system is recommended. The new design is predicted to provide comparable vehicle performance, improved reliability and a cost advantage for a high production vehicle, decreased total rating of the power semiconductor switches, and a somewhat simpler control hardware compared to the conventional three phase bridge inverter motor drive system. The major disadvantages of the two phase inverter motor drive are that it is larger and more expensive than a three phase machine, the design of snubbers for the power leakage inductances produce higher transient voltages, and the torque pulsations are relatively large because of the necessity to limit the inverter switching frequency to achieve high efficiency.

Advanced statistical energy analysis

NASA Astrophysics Data System (ADS)

Heron, K. H.

1994-09-01

A high-frequency theory (advanced statistical energy analysis (ASEA)) is developed which takes account of the mechanism of tunnelling and uses a ray theory approach to track the power flowing around a plate or a beam network and then uses statistical energy analysis (SEA) to take care of any residual power. ASEA divides the energy of each sub-system into energy that is freely available for transfer to other sub-systems and energy that is fixed within the sub-systems that are physically separate and can be interpreted as a series of mathematical models, the first of which is identical to standard SEA and subsequent higher order models are convergent on an accurate prediction. Using a structural assembly of six rods as an example, ASEA is shown to converge onto the exact results while SEA is shown to overpredict by up to 60 dB.

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.

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.

Yeast Prions and Human Prion-like Proteins: Sequence Features and Prediction Methods

PubMed Central

Cascarina, Sean; Ross, Eric D.

2014-01-01

Prions are self-propagating infectious protein isoforms. A growing number of prions have been identified in yeast, each resulting from the conversion of soluble proteins into an insoluble amyloid form. These yeast prions have served as a powerful model system for studying the causes and consequences of prion aggregation. Remarkably, a number of human proteins containing prion-like domains, defined as domains with compositional similarity to yeast prion domains, have recently been linked to various human degenerative diseases, including amyotrophic lateral sclerosis (ALS). This suggests that the lessons learned from yeast prions may help in understanding these human diseases. In this review, we examine what has been learned about the amino acid sequence basis for prion aggregation in yeast, and how this information has been used to develop methods to predict aggregation propensity. We then discuss how this information is being applied to understand human disease, and the challenges involved in applying yeast prediction methods to higher organisms. PMID:24390581

Yeast prions and human prion-like proteins: sequence features and prediction methods.

PubMed

Cascarina, Sean M; Ross, Eric D

2014-06-01

Prions are self-propagating infectious protein isoforms. A growing number of prions have been identified in yeast, each resulting from the conversion of soluble proteins into an insoluble amyloid form. These yeast prions have served as a powerful model system for studying the causes and consequences of prion aggregation. Remarkably, a number of human proteins containing prion-like domains, defined as domains with compositional similarity to yeast prion domains, have recently been linked to various human degenerative diseases, including amyotrophic lateral sclerosis. This suggests that the lessons learned from yeast prions may help in understanding these human diseases. In this review, we examine what has been learned about the amino acid sequence basis for prion aggregation in yeast, and how this information has been used to develop methods to predict aggregation propensity. We then discuss how this information is being applied to understand human disease, and the challenges involved in applying yeast prediction methods to higher organisms.

Structural kinematics based damage zone prediction in gradient structures using vibration database

NASA Astrophysics Data System (ADS)

Talha, Mohammad; Ashokkumar, Chimpalthradi R.

2014-05-01

To explore the applications of functionally graded materials (FGMs) in dynamic structures, structural kinematics based health monitoring technique becomes an important problem. Depending upon the displacements in three dimensions, the health of the material to withstand dynamic loads is inferred in this paper, which is based on the net compressive and tensile displacements that each structural degree of freedom takes. These net displacements at each finite element node predicts damage zones of the FGM where the material is likely to fail due to a vibration response which is categorized according to loading condition. The damage zone prediction of a dynamically active FGMs plate have been accomplished using Reddy's higher-order theory. The constituent material properties are assumed to vary in the thickness direction according to the power-law behavior. The proposed C0 finite element model (FEM) is applied to get net tensile and compressive displacement distributions across the structures. A plate made of Aluminum/Ziconia is considered to illustrate the concept of structural kinematics-based health monitoring aspects of FGMs.

Couples' cultural values, shared parenting, and family emotional climate within Mexican American families.

PubMed

Sotomayor-Peterson, Marcela; Figueredo, Aurelio J; Christensen, Donna H; Taylor, Angela R

2012-06-01

This study tested a model of shared parenting as its centerpiece that incorporates cultural values as predictors and family emotional climate as the outcome variable of interest. We aimed to assess the predictive power of the Mexican cultural values of familismo and simpatia over couples' shared parenting practices. We anticipated that higher levels of shared parenting would predict family emotional climate. The participants were 61 Mexican American, low income couples, with at least one child between 3 and 4 years of age, recruited from a home-based Head Start program. The predictive model demonstrated excellent goodness of fit, supporting the hypothesis that a positive emotional climate within the family is fostered when Mexican American couples practice a sufficient level of shared parenting. Empirical evidence was previously scarce on this proposition. The findings also provide evidence for the role of cultural values, highlighting the importance of family solidarity and avoidance of confrontation as a pathway to shared parenting within Mexican American couples. © FPI, Inc.

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

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

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

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

Genome-Wide Association Analysis of Adaptation Using Environmentally Predicted Traits.

PubMed

van Heerwaarden, Joost; van Zanten, Martijn; Kruijer, Willem

2015-10-01

Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation.

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.

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.

Program Predicts Nonlinear Inverter Performance

NASA Technical Reports Server (NTRS)

Al-Ayoubi, R. R.; Oepomo, T. S.

1985-01-01

Program developed for ac power distribution system on Shuttle orbiter predicts total load on inverters and node voltages at each of line replaceable units (LRU's). Mathematical model simulates inverter performance at each change of state in power distribution system.

A novel method for predicting the power outputs of wave energy converters

NASA Astrophysics Data System (ADS)

Wang, Yingguang

2018-03-01

This paper focuses on realistically predicting the power outputs of wave energy converters operating in shallow water nonlinear waves. A heaving two-body point absorber is utilized as a specific calculation example, and the generated power of the point absorber has been predicted by using a novel method (a nonlinear simulation method) that incorporates a second order random wave model into a nonlinear dynamic filter. It is demonstrated that the second order random wave model in this article can be utilized to generate irregular waves with realistic crest-trough asymmetries, and consequently, more accurate generated power can be predicted by subsequently solving the nonlinear dynamic filter equation with the nonlinearly simulated second order waves as inputs. The research findings demonstrate that the novel nonlinear simulation method in this article can be utilized as a robust tool for ocean engineers in their design, analysis and optimization of wave energy converters.

Mentoring Support and Power: A Three Year Predictive Field Study on Protege Networking and Career Success

ERIC Educational Resources Information Center

Blickle, Gerhard; Witzki, Alexander H.; Schneider, Paula B.

2009-01-01

Career success of early employees was analyzed from a power perspective and a developmental network perspective. In a predictive field study with 112 employees mentoring support and mentors' power were assessed in the first wave, employees' networking was assessed after two years, and career success (i.e. income and hierarchical position) and…

Placing your faith on the betting floor: Religiosity predicts disordered gambling via gambling fallacies.

PubMed

Kim, Hyoun S; Shifrin, Alexandra; Sztainert, Travis; Wohl, Michael J A

2018-04-12

Background and aims We examined the potential role religious beliefs may play in disordered gambling. Specifically, we tested the idea that religiosity primes people to place their faith in good fortune or a higher power. In the context of gambling, however, this may lead to gambling fallacies (e.g., erroneous beliefs that one has control over a random outcome). People who are high in religiosity may be more at risk of developing gambling fallacies, as they may believe that a higher power can influence a game of chance. Thus, this research investigated the relationship between religiosity and gambling problems and whether gambling fallacies mediated this relationship. Methods In Study 1, we recruited an online sample from Amazon's Mechanical Turk to complete measures that assessed the central constructs (religiosity, disordered gambling, and gambling fallacies). In Study 2, we conducted a secondary analysis of a large data set of representative adults (N = 4,121) from a Canadian province, which contained measures that assessed the constructs of interest. Results In Study 1, religiosity significantly predicted gambling problem. Conversely, there was no direct relationship between religiosity and gambling in Study 2. Importantly, a significant indirect effect of religiosity on disordered gambling severity through gambling fallacies was found in both studies, thus establishing mediation. The results remained the same when controlling for age, gender, ethnicity, and socioeconomic status for both studies. Discussion and conclusion These findings suggest religiosity and its propensity to be associated with gambling fallacies, which should be considered in the progression (and possibly treatment) of gambling.

Skill acquisition while operating in-vehicle information systems: interface design determines the level of safety-relevant distractions.

PubMed

Jahn, Georg; Krems, Josef F; Gelau, Christhard

2009-04-01

This study tested whether the ease of learning to use human-machine interfaces of in-vehicle information systems (IVIS) can be assessed at standstill. Assessing the attentional demand of IVIS should include an evaluation of ease of learning, because the use of IVIS at low skill levels may create safety-relevant distractions. Skill acquisition in operating IVIS was quantified by fitting the power law of practice to training data sets collected in a driving study and at standstill. Participants practiced manual destination entry with two route guidance systems differing in cognitive demand. In Experiment 1, a sample of middle-aged participants was trained while steering routes of varying driving demands. In Experiment 2, another sample of middle-aged participants was trained at standstill. In Experiment 1, display glance times were less affected by driving demands than by total task times and decreased at slightly higher speed-up rates (0.02 higher on average) than task times collected at standstill in Experiment 2. The system interface that minimized cognitive demand was operated more quickly and was easier to learn. Its system delays increased static task times, which still predicted 58% of variance in display glance times compared with even 76% for the second system. The ease of learning to use an IVIS interface and the decrease in attentional demand with training can be assessed at standstill. Fitting the power law of practice to static task times yields parameters that predict display glance times while driving, which makes it possible to compare interfaces with regard to ease of learning.

Scaling behavior of columnar structure during physical vapor deposition

NASA Astrophysics Data System (ADS)

Meese, W. J.; Lu, T.-M.

2018-02-01

The statistical effects of different conditions in physical vapor deposition, such as sputter deposition, have on thin film morphology has long been the subject of interest. One notable effect is that of column development due to differential chamber pressure in the well-known empirical model called the Thornton's Structure Zone Model. The model is qualitative in nature and theoretical understanding with quantitative predictions of the morphology is still lacking due, in part, to the absence of a quantitative description of the incident flux distribution on the growth front. In this work, we propose an incident Gaussian flux model developed from a series of binary hard-sphere collisions and simulate its effects using Monte Carlo methods and a solid-on-solid growth scheme. We also propose an approximate cosine-power distribution for faster Monte Carlo sampling. With this model, it is observed that higher chamber pressures widen the average deposition angle, and similarly increase the growth of column diameters (or lateral correlation length) and the column-to-column separation (film surface wavelength). We treat both the column diameter and the surface wavelength as power laws. It is seen that both the column diameter exponent and the wavelength exponent are very sensitive to changes in pressure for low pressures (0.13 Pa to 0.80 Pa); meanwhile, both exponents saturate for higher pressures (0.80 Pa to 6.7 Pa) around a value of 0.6. These predictions will serve as guides to future experiments for quantitative description of the film morphology under a wide range of vapor pressure.

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

PubMed

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

2016-10-01

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

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.

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

PubMed

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

2017-01-01

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

Modeling late rectal toxicities based on a parameterized representation of the 3D dose distribution

NASA Astrophysics Data System (ADS)

Buettner, Florian; Gulliford, Sarah L.; Webb, Steve; Partridge, Mike

2011-04-01

Many models exist for predicting toxicities based on dose-volume histograms (DVHs) or dose-surface histograms (DSHs). This approach has several drawbacks as firstly the reduction of the dose distribution to a histogram results in the loss of spatial information and secondly the bins of the histograms are highly correlated with each other. Furthermore, some of the complex nonlinear models proposed in the past lack a direct physical interpretation and the ability to predict probabilities rather than binary outcomes. We propose a parameterized representation of the 3D distribution of the dose to the rectal wall which explicitly includes geometrical information in the form of the eccentricity of the dose distribution as well as its lateral and longitudinal extent. We use a nonlinear kernel-based probabilistic model to predict late rectal toxicity based on the parameterized dose distribution and assessed its predictive power using data from the MRC RT01 trial (ISCTRN 47772397). The endpoints under consideration were rectal bleeding, loose stools, and a global toxicity score. We extract simple rules identifying 3D dose patterns related to a specifically low risk of complication. Normal tissue complication probability (NTCP) models based on parameterized representations of geometrical and volumetric measures resulted in areas under the curve (AUCs) of 0.66, 0.63 and 0.67 for predicting rectal bleeding, loose stools and global toxicity, respectively. In comparison, NTCP models based on standard DVHs performed worse and resulted in AUCs of 0.59 for all three endpoints. In conclusion, we have presented low-dimensional, interpretable and nonlinear NTCP models based on the parameterized representation of the dose to the rectal wall. These models had a higher predictive power than models based on standard DVHs and their low dimensionality allowed for the identification of 3D dose patterns related to a low risk of complication.

Body size, performance and fitness in galapagos marine iguanas.

PubMed

Wikelski, Martin; Romero, L Michael

2003-07-01

Complex organismal traits such as body size are influenced by innumerable selective pressures, making the prediction of evolutionary trajectories for those traits difficult. A potentially powerful way to predict fitness in natural systems is to study the composite response of individuals in terms of performance measures, such as foraging or reproductive performance. Once key performance measures are identified in this top-down approach, we can determine the underlying physiological mechanisms and gain predictive power over long-term evolutionary processes. Here we use marine iguanas as a model system where body size differs by more than one order of magnitude between island populations. We identified foraging efficiency as the main performance measure that constrains body size. Mechanistically, foraging performance is determined by food pasture height and the thermal environment, influencing intake and digestion. Stress hormones may be a flexible way of influencing an individual's response to low-food situations that may be caused by high population density, famines, or anthropogenic disturbances like oil spills. Reproductive performance, on the other hand, increases with body size and is mediated by higher survival of larger hatchlings from larger females and increased mating success of larger males. Reproductive performance of males may be adjusted via plastic hormonal feedback mechanisms that allow individuals to assess their social rank annually within the current population size structure. When integrated, these data suggest that reproductive performance favors increased body size (influenced by reproductive hormones), with an overall limit imposed by foraging performance (influenced by stress hormones). Based on our mechanistic understanding of individual performances we predicted an evolutionary increase in maximum body size caused by global warming trends. We support this prediction using specimens collected during 1905. We also show in a common-garden experiment that body size may have a genetic component in iguanids. This 'performance paradigm' allows predictions about adaptive evolution in natural populations.

Performance analysis of a potassium-base AMTEC cell

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

Huang, C.; Hendricks, T.J.; Hunt, T.K.

1998-07-01

Sodium-BASE Alkali-Metal-Thermal-to-Electric-Conversion (AMTEC) cells have been receiving increased attention and funding from the Department of Energy, NASA and the United States Air Force. Recently, sodium-BASE (Na-BASE) AMTEC cells were selected for the Advanced Radioisotope Power System (ARPS) program for the next generation of deep-space missions and spacecraft. Potassium-BASE (K-BASE) AMTEC cells have not received as much attention to date, even though the vapor pressure of potassium is higher than that of sodium at the same temperature. So that, K-BASE AMTEC cells with potentially higher open circuit voltage and higher power output than Na-BASE AMTEC cells are possible. Because the surfacemore » tension of potassium is about half of the surface tension of sodium at the same temperature, the artery and evaporator design in a potassium AMTEC cell has much more challenging pore size requirements than designs using sodium. This paper uses a flexible thermal/fluid/electrical model to predict the performance of a K-BASE AMTEC cell. Pore sizes in the artery of K-BASE AMTEC cells must be smaller by an order of magnitude than in Na-BASE AMTEC cells. The performance of a K-BASE AMTEC cell was higher than a Na-BASE AMTEC cell at low voltages/high currents. K-BASE AMTEC cells also have the potential of much better electrode performance, thereby creating another avenue for potentially better performance in K-BASE AMTEC cells.« less

Unpredicted Pitch Modulates Beta Oscillatory Power during Rhythmic Entrainment to a Tone Sequence.

PubMed

Chang, Andrew; Bosnyak, Dan J; Trainor, Laurel J

2016-01-01

Extracting temporal regularities in external stimuli in order to predict upcoming events is an essential aspect of perception. Fluctuations in induced power of beta band (15-25 Hz) oscillations in auditory cortex are involved in predictive timing during rhythmic entrainment, but whether such fluctuations are affected by prediction in the spectral (frequency/pitch) domain remains unclear. We tested whether unpredicted (i.e., unexpected) pitches in a rhythmic tone sequence modulate beta band activity by recording EEG while participants passively listened to isochronous auditory oddball sequences with occasional unpredicted deviant pitches at two different presentation rates. The results showed that the power in low-beta (15-20 Hz) was larger around 200-300 ms following deviant tones compared to standard tones, and this effect was larger when the deviant tones were less predicted. Our results suggest that the induced beta power activities in auditory cortex are consistent with a role in sensory prediction of both "when" (timing) upcoming sounds will occur as well as the prediction precision error of "what" (spectral content in this case). We suggest, further, that both timing and content predictions may co-modulate beta oscillations via attention. These findings extend earlier work on neural oscillations by investigating the functional significance of beta oscillations for sensory prediction. The findings help elucidate the functional significance of beta oscillations in perception.

Prediction and measurement of the electromagnetic environment of high-power medium-wave and short-wave broadcast antennas in far field.

PubMed

Tang, Zhanghong; Wang, Qun; Ji, Zhijiang; Shi, Meiwu; Hou, Guoyan; Tan, Danjun; Wang, Pengqi; Qiu, Xianbo

2014-12-01

With the increasing city size, high-power electromagnetic radiation devices such as high-power medium-wave (MW) and short-wave (SW) antennas have been inevitably getting closer and closer to buildings, which resulted in the pollution of indoor electromagnetic radiation becoming worsened. To avoid such radiation exceeding the exposure limits by national standards, it is necessary to predict and survey the electromagnetic radiation by MW and SW antennas before constructing the buildings. In this paper, a modified prediction method for the far-field electromagnetic radiation is proposed and successfully applied to predict the electromagnetic environment of an area close to a group of typical high-power MW and SW wave antennas. Different from currently used simplified prediction method defined in the Radiation Protection Management Guidelines (H J/T 10. 3-1996), the new method in this article makes use of more information such as antennas' patterns to predict the electromagnetic environment. Therefore, it improves the prediction accuracy significantly by the new feature of resolution at different directions. At the end of this article, a comparison between the prediction data and the measured results is given to demonstrate the effectiveness of the proposed new method. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Unpredicted Pitch Modulates Beta Oscillatory Power during Rhythmic Entrainment to a Tone Sequence

PubMed Central

Chang, Andrew; Bosnyak, Dan J.; Trainor, Laurel J.

2016-01-01

Extracting temporal regularities in external stimuli in order to predict upcoming events is an essential aspect of perception. Fluctuations in induced power of beta band (15–25 Hz) oscillations in auditory cortex are involved in predictive timing during rhythmic entrainment, but whether such fluctuations are affected by prediction in the spectral (frequency/pitch) domain remains unclear. We tested whether unpredicted (i.e., unexpected) pitches in a rhythmic tone sequence modulate beta band activity by recording EEG while participants passively listened to isochronous auditory oddball sequences with occasional unpredicted deviant pitches at two different presentation rates. The results showed that the power in low-beta (15–20 Hz) was larger around 200–300 ms following deviant tones compared to standard tones, and this effect was larger when the deviant tones were less predicted. Our results suggest that the induced beta power activities in auditory cortex are consistent with a role in sensory prediction of both “when” (timing) upcoming sounds will occur as well as the prediction precision error of “what” (spectral content in this case). We suggest, further, that both timing and content predictions may co-modulate beta oscillations via attention. These findings extend earlier work on neural oscillations by investigating the functional significance of beta oscillations for sensory prediction. The findings help elucidate the functional significance of beta oscillations in perception. PMID:27014138

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

Moslehi, Salim; Reddy, T. Agami; Katipamula, Srinivas

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

Desiccation resistance in tropical insects: causes and mechanisms underlying variability in a Panama ant community.

PubMed

Bujan, Jelena; Yanoviak, Stephen P; Kaspari, Michael

2016-09-01

Desiccation resistance, the ability of an organism to reduce water loss, is an essential trait in arid habitats. Drought frequency in tropical regions is predicted to increase with climate change, and small ectotherms are often under a strong desiccation risk. We tested hypotheses regarding the underexplored desiccation potential of tropical insects. We measured desiccation resistance in 82 ant species from a Panama rainforest by recording the time ants can survive desiccation stress. Species' desiccation resistance ranged from 0.7 h to 97.9 h. We tested the desiccation adaptation hypothesis, which predicts higher desiccation resistance in habitats with higher vapor pressure deficit (VPD) - the drying power of the air. In a Panama rainforest, canopy microclimates averaged a VPD of 0.43 kPa, compared to a VPD of 0.05 kPa in the understory. Canopy ants averaged desiccation resistances 2.8 times higher than the understory ants. We tested a number of mechanisms to account for desiccation resistance. Smaller insects should desiccate faster given their higher surface area to volume ratio. Desiccation resistance increased with ant mass, and canopy ants averaged 16% heavier than the understory ants. A second way to increase desiccation resistance is to carry more water. Water content was on average 2.5% higher in canopy ants, but total water content was not a good predictor of ant desiccation resistance or critical thermal maximum (CT max), a measure of an ant's thermal tolerance. In canopy ants, desiccation resistance and CT max were inversely related, suggesting a tradeoff, while the two were positively correlated in understory ants. This is the first community level test of desiccation adaptation hypothesis in tropical insects. Tropical forests do contain desiccation-resistant species, and while we cannot predict those simply based on their body size, high levels of desiccation resistance are always associated with the tropical canopy.

A large-eddy simulation based power estimation capability for wind farms over complex terrain

NASA Astrophysics Data System (ADS)

Senocak, I.; Sandusky, M.; Deleon, R.

2017-12-01

There has been an increasing interest in predicting wind fields over complex terrain at the micro-scale for resource assessment, turbine siting, and power forecasting. These capabilities are made possible by advancements in computational speed from a new generation of computing hardware, numerical methods and physics modelling. The micro-scale wind prediction model presented in this work is based on the large-eddy simulation paradigm with surface-stress parameterization. The complex terrain is represented using an immersed-boundary method that takes into account the parameterization of the surface stresses. Governing equations of incompressible fluid flow are solved using a projection method with second-order accurate schemes in space and time. We use actuator disk models with rotation to simulate the influence of turbines on the wind field. Data regarding power production from individual turbines are mostly restricted because of proprietary nature of the wind energy business. Most studies report percentage drop of power relative to power from the first row. There have been different approaches to predict power production. Some studies simply report available wind power in the upstream, some studies estimate power production using power curves available from turbine manufacturers, and some studies estimate power as torque multiplied by rotational speed. In the present work, we propose a black-box approach that considers a control volume around a turbine and estimate the power extracted from the turbine based on the conservation of energy principle. We applied our wind power prediction capability to wind farms over flat terrain such as the wind farm over Mower County, Minnesota and the Horns Rev offshore wind farm in Denmark. The results from these simulations are in good agreement with published data. We also estimate power production from a hypothetical wind farm in complex terrain region and identify potential zones suitable for wind power production.

A critical assessment of the Burning Index in Los Angeles County, California

USGS Publications Warehouse

Schoenberg, F.P.; Chang, H.-C.; Keeley, J.E.; Pompa, J.; Woods, J.; Xu, H.

2007-01-01

The Burning Index (BI) is commonly used as a predictor of wildfire activity. An examination of data on the BI and wildfires in Los Angeles County, California, from January 1976 to December 2000 reveals that although the BI is positively associated with wildfire occurrence, its predictive value is quite limited. Wind speed alone has a higher correlation with burn area than BI, for instance, and a simple alternative point process model using wind speed, relative humidity, precipitation and temperature well outperforms the BI in terms of predictive power. The BI is generally far too high in winter and too low in fall, and may exaggerate the impact of individual variables such as wind speed or temperature during times when other variables, such as precipitation or relative humidity, render the environment ill suited for wildfires. ?? IAWF 2007.

Physics-based model for predicting the performance of a miniature wind turbine

NASA Astrophysics Data System (ADS)

Xu, F. J.; Hu, J. Z.; Qiu, Y. P.; Yuan, F. G.

2011-04-01

A comprehensive physics-based model for predicting the performance of the miniature wind turbine (MWT) for power wireless sensor systems was proposed in this paper. An approximation of the power coefficient of the turbine rotor was made after the turbine rotor performance was measured. Incorporation of the approximation with the equivalent circuit model which was proposed according to the principles of the MWT, the overall system performance of the MWT was predicted. To demonstrate the prediction, the MWT system comprised of a 7.6 cm thorgren plastic propeller as turbine rotor and a DC motor as generator was designed and its performance was tested experimentally. The predicted output voltage, power and system efficiency are matched well with the tested results, which imply that this study holds promise in estimating and optimizing the performance of the MWT.

Modeling of indirect carbon fuel cell systems with steam and dry gasification

NASA Astrophysics Data System (ADS)

Ong, Katherine M.; Ghoniem, Ahmed F.

2016-05-01

An indirect carbon fuel cell (ICFC) system that couples coal gasification to a solid oxide fuel cell (SOFC) is a promising candidate for high efficiency stationary power. This study couples an equilibrium gasifier model to a detailed 1D MEA model to study the theoretical performance of an ICFC system run on steam or carbon dioxide. Results show that the fuel cell in the ICFC system is capable of power densities greater than 1.0 W cm-2 with H2O recycle, and power densities ranging from 0.2 to 0.4 W cm-2 with CO2 recycle. This result indicates that the ICFC system performs better with steam than with CO2 gasification as a result of the faster electro-oxidation kinetics of H2 relative to CO. The ICFC system is then shown to reach higher current densities and efficiencies than a thermally decoupled gasifier + fuel cell (G + FC) system because it does not include combustion losses associated with autothermal gasification. 55-60% efficiency is predicted for the ICFC system coupled to a bottoming cycle, making this technology competitive with other state-of-the-art stationary power candidates.

Thermal Stress Analysis of a Continuous and Pulsed End-Pumped Nd:YAG Rod Crystal Using Non-Classic Conduction Heat Transfer Theory

NASA Astrophysics Data System (ADS)

Mojahedi, Mahdi; Shekoohinejad, Hamidreza

2018-02-01

In this paper, temperature distribution in the continuous and pulsed end-pumped Nd:YAG rod crystal is determined using nonclassical and classical heat conduction theories. In order to find the temperature distribution in crystal, heat transfer differential equations of crystal with consideration of boundary conditions are derived based on non-Fourier's model and temperature distribution of the crystal is achieved by an analytical method. Then, by transferring non-Fourier differential equations to matrix equations, using finite element method, temperature and stress of every point of crystal are calculated in the time domain. According to the results, a comparison between classical and nonclassical theories is represented to investigate rupture power values. In continuous end pumping with equal input powers, non-Fourier theory predicts greater temperature and stress compared to Fourier theory. It also shows that with an increase in relaxation time, crystal rupture power decreases. Despite of these results, in single rectangular pulsed end-pumping condition, with an equal input power, Fourier theory indicates higher temperature and stress rather than non-Fourier theory. It is also observed that, when the relaxation time increases, maximum amounts of temperature and stress decrease.

Efficient 2-μm Tm:YAP Q-switched and CW lasers

NASA Astrophysics Data System (ADS)

Hays, A. D.; Cole, Brian; King, Vernon; Goldberg, Lew

2018-02-01

Highly efficient, diode pumped Tm:YAP lasers generating emission in the 1.85-1.94 μm range are demonstrated and characterized. Laser optical efficiencies of 51% and 45%, and electrical efficiencies of 31% and 25% are achieved under CW and Q-switched operation, respectively. Laser performance was characterized for maximum average powers up to 20W with various cavity configurations, all using an intra-cavity lens to compensate for thermal lensing in the Tm:YAP crystal. Q-switched lasers incorportating a Cr:ZnS saturable absorber (SA), resonant mechanical mirror scanner, or acousto-optic modulator were characterized. To enable higher average output powers, measurements of the thermal lens were conducted for the Tm:YAP crystal as a function of pump power and were compared to values predicted by a finiteelement- analysis (FEA) thermal-optical model of the Tm:YAP crystal. A resonator model is developed to incorporate this calculated thermal lens and its effect on laser performance. This paper will address approaches for improving the performance of Tm:YAP lasers, and means for achieving increased average output powers while maintaining high optical efficiency for both SA and mechanical Q-switching.

Modeling and validation of single-chamber microbial fuel cell cathode biofilm growth and response to oxidant gas composition

NASA Astrophysics Data System (ADS)

Ou, Shiqi; Zhao, Yi; Aaron, Douglas S.; Regan, John M.; Mench, Matthew M.

2016-10-01

This work describes experiments and computational simulations to analyze single-chamber, air-cathode microbial fuel cell (MFC) performance and cathodic limitations in terms of current generation, power output, mass transport, biomass competition, and biofilm growth. Steady-state and transient cathode models were developed and experimentally validated. Two cathode gas mixtures were used to explore oxygen transport in the cathode: the MFCs exposed to a helium-oxygen mixture (heliox) produced higher current and power output than the group of MFCs exposed to air or a nitrogen-oxygen mixture (nitrox), indicating a dependence on gas-phase transport in the cathode. Multi-substance transport, biological reactions, and electrochemical reactions in a multi-layer and multi-biomass cathode biofilm were also simulated in a transient model. The transient model described biofilm growth over 15 days while providing insight into mass transport and cathodic dissolved species concentration profiles during biofilm growth. Simulation results predict that the dissolved oxygen content and diffusion in the cathode are key parameters affecting the power output of the air-cathode MFC system, with greater oxygen content in the cathode resulting in increased power output and fully-matured biomass.

Study of the effect of loop inductance on the RF transmission line to cavity coupling coefficient

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

Lal, Shankar, E-mail: shankar@rrcat.gov.in; Pant, K. K.

2016-08-15

Coupling of RF power is an important aspect in the design and development of RF accelerating structures. RF power coupling employing coupler loops has the advantage of tunability of β, the transmission line to cavity coupling coefficient. Analytical expressions available in literature for determination of size of the coupler loop using Faraday’s law of induction show reasonably good agreement with experimentally measured values of β below critical coupling (β ≤ 1) but show large deviation with experimentally measured values and predictions by simulations for higher values of β. In actual accelerator application, many RF cavities need to be over-coupled withmore » β > 1 for reasons of beam loading compensation, reduction of cavity filling time, etc. This paper discusses a modified analytical formulation by including the effect of loop inductance in the determination of loop size for any desired coupling coefficient. The analytical formulation shows good agreement with 3D simulations and with experimentally measured values. It has been successfully qualified by the design and development of power coupler loops for two 476 MHz pre-buncher RF cavities, which have successfully been conditioned at rated power levels using these coupler loops.« less

Modeling and validation of single-chamber microbial fuel cell cathode biofilm growth and response to oxidant gas composition

DOE PAGES

Ou, Shiqi; Zhao, Yi; Aaron, Douglas S.; ...

2016-08-15

This work describes experiments and computational simulations to analyze single-chamber, air-cathode microbial fuel cell (MFC) performance and cathodic limitations in terms of current generation, power output, mass transport, biomass competition, and biofilm growth. Steady-state and transient cathode models were developed and experimentally validated. Two cathode gas mixtures were used to explore oxygen transport in the cathode: the MFCs exposed to a helium-oxygen mixture (heliox) produced higher current and power output than the group of MFCs exposed to air or a nitrogen-oxygen mixture (nitrox), indicating a dependence on gas-phase transport in the cathode. Multi-substance transport, biological reactions, and electrochemical reactions inmore » a multi-layer and multi-biomass cathode biofilm were also simulated in a transient model. The transient model described biofilm growth over 15 days while providing insight into mass transport and cathodic dissolved species concentration profiles during biofilm growth. Lastly, simulation results predict that the dissolved oxygen content and diffusion in the cathode are key parameters affecting the power output of the air-cathode MFC system, with greater oxygen content in the cathode resulting in increased power output and fully-matured biomass.« less

Study of the effect of loop inductance on the RF transmission line to cavity coupling coefficient

NASA Astrophysics Data System (ADS)

Lal, Shankar; Pant, K. K.

2016-08-01

Coupling of RF power is an important aspect in the design and development of RF accelerating structures. RF power coupling employing coupler loops has the advantage of tunability of β, the transmission line to cavity coupling coefficient. Analytical expressions available in literature for determination of size of the coupler loop using Faraday's law of induction show reasonably good agreement with experimentally measured values of β below critical coupling (β ≤ 1) but show large deviation with experimentally measured values and predictions by simulations for higher values of β. In actual accelerator application, many RF cavities need to be over-coupled with β > 1 for reasons of beam loading compensation, reduction of cavity filling time, etc. This paper discusses a modified analytical formulation by including the effect of loop inductance in the determination of loop size for any desired coupling coefficient. The analytical formulation shows good agreement with 3D simulations and with experimentally measured values. It has been successfully qualified by the design and development of power coupler loops for two 476 MHz pre-buncher RF cavities, which have successfully been conditioned at rated power levels using these coupler loops.

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

Nurten Vardar; Zehra Yumurtaci

The major gaseous emissions (e.g. sulfur dioxide, nitrogen oxides, carbon dioxide, and carbon monoxide), some various organic emissions (e.g. benzene, toluene and xylenes) and some trace metals (e.g. arsenic, cobalt, chromium, manganese and nickel) generated from lignite-fired power plants in Turkey are estimated. The estimations are made separately for each one of the thirteen plants that produced electricity in 2007, because the lignite-fired thermal plants in Turkey are installed near the regions where the lignite is mined, and characteristics and composition of lignite used in each power plant are quite different from a region to another. Emission factors methodology ismore » used for the estimations. The emission factors obtained from well-known literature are then modified depending on local moisture content of lignite. Emission rates and specific emissions (per MWh) of the pollutants from the plants without electrostatic precipitators and flue-gas desulfurization systems are found to be higher than emissions from the plants having electrostatic precipitators and flue -gas desulfurization systems. Finally a projection for the future emissions due to lignite-based power plants is given. Predicted demand for the increasing generation capacity based on the lignite-fired thermal power plant, from 2008 to 2017 is around 30%. 39 refs., 13 figs., 10 tabs.« less

Bioremediation for coal-fired power stations using macroalgae.

PubMed

Roberts, David A; Paul, Nicholas A; Bird, Michael I; de Nys, Rocky

2015-04-15

Macroalgae are a productive resource that can be cultured in metal-contaminated waste water for bioremediation but there have been no demonstrations of this biotechnology integrated with industry. Coal-fired power production is a water-limited industry that requires novel approaches to waste water treatment and recycling. In this study, a freshwater macroalga (genus Oedogonium) was cultivated in contaminated ash water amended with flue gas (containing 20% CO₂) at an Australian coal-fired power station. The continuous process of macroalgal growth and intracellular metal sequestration reduced the concentrations of all metals in the treated ash water. Predictive modelling shows that the power station could feasibly achieve zero discharge of most regulated metals (Al, As, Cd, Cr, Cu, Ni, and Zn) in waste water by using the ash water dam for bioremediation with algal cultivation ponds rather than storage of ash water. Slow pyrolysis of the cultivated algae immobilised the accumulated metals in a recalcitrant C-rich biochar. While the algal biochar had higher total metal concentrations than the algae feedstock, the biochar had very low concentrations of leachable metals and therefore has potential for use as an ameliorant for low-fertility soils. This study demonstrates a bioremediation technology at a large scale for a water-limited industry that could be implemented at new or existing power stations, or during the decommissioning of older power stations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Numerical calculations of non-inductive current driven by microwaves in JET

NASA Astrophysics Data System (ADS)

Kirov, K. K.; Baranov, Yu; Mailloux, J.; Nave, M. F. F.; Contributors, JET

2016-12-01

Recent studies at JET focus on analysis of the lower hybrid (LH) wave power absorption and current drive (CD) calculations by means of a new ray tracing (RT)/Fokker-Planck (FP) package. The RT code works in real 2D geometry accounting for the plasma boundary and the launcher shape. LH waves with different parallel refractive index, {{N}\\parallel} , spectra in poloidal direction can be launched thus simulating authentic antenna spectrum with rows fed by different combinations of klystrons. Various FP solvers were tested most advanced of which is a relativistic bounce averaged FP code. LH wave power deposition profiles from the new RT/FP code were compared to the experimental results from electron cyclotron emission (ECE) analysis of pulses at 3.4 T low and high density. This kind of direct comparison between power deposition profiles from experimental ECE data and numerical model were carried out for the first time for waves in the LH range of frequencies. The results were in a reasonable agreement with experimental data at lower density, line averaged values of {{n}\\text{e}}≈ 2.4× {{10}19} {{\\text{m}}-3} . At higher density, {{n}\\text{e}}≈ 3× {{10}19} {{\\text{m}}-3} , the code predicted larger on-axis LH power deposition, which is inconsistent with the experimental observations. Both calculations were unable to produce LH wave absorption at the plasma periphery, which contradicts to the analysis of the ECE data and possible sources of these discrepancies have been briefly discussed in the paper. The code was also used to calculate the LH power deposition and CD profiles for the low-density preheat phase of JET’s advanced tokamak (AT) scenario. It was found that as the density evolves from hollow to flat and then to a more peaked profile the LH power and driven current move inward i.e. towards the plasma axis. A total driven current of about 70 kA for 1 MW of launched LH power was predicted in these conditions.

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

PubMed

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

2018-06-02

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

Measurements and predictions of flyover and static noise of a TF30 afterburning turbofan engine

NASA Technical Reports Server (NTRS)

Burcham, F. W., Jr.; Lasagna, P. L.; Oas, S. C.

1978-01-01

The noise of the TF30 afterburning turbofan engine in an F-111 airplane was determined from static (ground) and flyover tests. A survey was made to measure the exhaust temperature and velocity profiles for a range of power settings. Comparisons were made between predicted and measured jet mixing, internal, and shock noise. It was found that the noise produced at static conditions was dominated by jet mixing noise, and was adequately predicted by current methods. The noise produced during flyovers exhibited large contributions from internally generated noise in the forward arc. For flyovers with the engine at nonafterburning power, the internal noise, shock noise, and jet mixing noise were accurately predicted. During flyovers with afterburning power settings, however, additional internal noise believed to be due to the afterburning process was evident; its level was as much as 8 decibels above the nonafterburning internal noise. Power settings that produced exhausts with inverted velocity profiles appeared to be slightly less noisy than power settings of equal thrust that produced uniform exhaust velocity profiles both in flight and in static testing.