Optimizing wind power generation while minimizing wildlife impacts in an urban area.

PubMed

Bohrer, Gil; Zhu, Kunpeng; Jones, Robert L; Curtis, Peter S

2013-01-01

The location of a wind turbine is critical to its power output, which is strongly affected by the local wind field. Turbine operators typically seek locations with the best wind at the lowest level above ground since turbine height affects installation costs. In many urban applications, such as small-scale turbines owned by local communities or organizations, turbine placement is challenging because of limited available space and because the turbine often must be added without removing existing infrastructure, including buildings and trees. The need to minimize turbine hazard to wildlife compounds the challenge. We used an exclusion zone approach for turbine-placement optimization that incorporates spatially detailed maps of wind distribution and wildlife densities with power output predictions for the Ohio State University campus. We processed public GIS records and airborne lidar point-cloud data to develop a 3D map of all campus buildings and trees. High resolution large-eddy simulations and long-term wind climatology were combined to provide land-surface-affected 3D wind fields and the corresponding wind-power generation potential. This power prediction map was then combined with bird survey data. Our assessment predicts that exclusion of areas where bird numbers are highest will have modest effects on the availability of locations for power generation. The exclusion zone approach allows the incorporation of wildlife hazard in wind turbine siting and power output considerations in complex urban environments even when the quantitative interaction between wildlife behavior and turbine activity is unknown.

On-line self-learning time forward voltage prognosis for lithium-ion batteries using adaptive neuro-fuzzy inference system

NASA Astrophysics Data System (ADS)

Fleischer, Christian; Waag, Wladislaw; Bai, Ziou; Sauer, Dirk Uwe

2013-12-01

The battery management system (BMS) of a battery-electric road vehicle must ensure an optimal operation of the electrochemical storage system to guarantee for durability and reliability. In particular, the BMS must provide precise information about the battery's state-of-functionality, i.e. how much dis-/charging power can the battery accept at current state and condition while at the same time preventing it from operating outside its safe operating area. These critical limits have to be calculated in a predictive manner, which serve as a significant input factor for the supervising vehicle energy management (VEM). The VEM must provide enough power to the vehicle's drivetrain for certain tasks and especially in critical driving situations. Therefore, this paper describes a new approach which can be used for state-of-available-power estimation with respect to lowest/highest cell voltage prediction using an adaptive neuro-fuzzy inference system (ANFIS). The estimated voltage for a given time frame in the future is directly compared with the actual voltage, verifying the effectiveness and accuracy of a relative voltage prediction error of less than 1%. Moreover, the real-time operating capability of the proposed algorithm was verified on a battery test bench while running on a real-time system performing voltage prediction.

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

Longitudinal aerodynamic performance of a series of power-law and minimum wave drag bodies at Mach 6 and several Reynolds numbers

NASA Technical Reports Server (NTRS)

Ashby, G. C., Jr.

1974-01-01

Experimental data have been obtained for two series of bodies at Mach 6 and Reynolds numbers, based on model length, from 1.4 million to 9.5 million. One series consisted of axisymmetric power-law bodies geometrically constrained for constant length and base diameter with values of the exponent n of 0.25, 0.5, 0.6, 0.667, 0.75, and 1.0. The other series consisted of positively and negatively cambered bodies of polygonal cross section, each having a constant longitudinal area distribution conforming to that required for minimizing zero-lift wave drag at hypersonic speeds under the geometric constraints of given length and volume. At the highest Reynolds number, the power-law body for minimum drag is blunter (exponent n lower) than predicted by inviscid theory (n approximately 0.6 instead of n = 0.667); however, the peak value of lift-drag ratio occurs at n = 0.667. Viscous effects were present on the bodies of polygonal cross section but were less pronounced than those on the power-law bodies. The trapezoidal bodies with maximum width at the bottom were found to have the highest maximum lift-drag ratio and the lowest mimimum drag.

Performance of Reclassification Statistics in Comparing Risk Prediction Models

PubMed Central

Paynter, Nina P.

2012-01-01

Concerns have been raised about the use of traditional measures of model fit in evaluating risk prediction models for clinical use, and reclassification tables have been suggested as an alternative means of assessing the clinical utility of a model. Several measures based on the table have been proposed, including the reclassification calibration (RC) statistic, the net reclassification improvement (NRI), and the integrated discrimination improvement (IDI), but the performance of these in practical settings has not been fully examined. We used simulations to estimate the type I error and power for these statistics in a number of scenarios, as well as the impact of the number and type of categories, when adding a new marker to an established or reference model. The type I error was found to be reasonable in most settings, and power was highest for the IDI, which was similar to the test of association. The relative power of the RC statistic, a test of calibration, and the NRI, a test of discrimination, varied depending on the model assumptions. These tools provide unique but complementary information. PMID:21294152

Improving prediction of fall risk among nursing home residents using electronic medical records.

PubMed

Marier, Allison; Olsho, Lauren E W; Rhodes, William; Spector, William D

2016-03-01

Falls are physically and financially costly, but may be preventable with targeted intervention. The Minimum Data Set (MDS) is one potential source of information on fall risk factors among nursing home residents, but its limited breadth and relatively infrequent updates may limit its practical utility. Richer, more frequently updated data from electronic medical records (EMRs) may improve ability to identify individuals at highest risk for falls. The authors applied a repeated events survival model to analyze MDS 3.0 and EMR data for 5129 residents in 13 nursing homes within a single large California chain that uses a centralized EMR system from a leading vendor. Estimated regression parameters were used to project resident fall probability. The authors examined the proportion of observed falls within each projected fall risk decile to assess improvements in predictive power from including EMR data. In a model incorporating fall risk factors from the MDS only, 28.6% of observed falls occurred among residents in the highest projected risk decile. In an alternative specification incorporating more frequently updated measures for the same risk factors from the EMR data, 32.3% of observed falls occurred among residents in the highest projected risk decile, a 13% increase over the base MDS-only specification. Incorporating EMR data improves ability to identify those at highest risk for falls relative to prediction using MDS data alone. These improvements stem chiefly from the greater frequency with which EMR data are updated, with minimal additional gains from availability of additional risk factor variables. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Bioinformatics analysis of single and multi-hybrid epitopes of GRA-1, GRA-4, GRA-6 and GRA-7 proteins to improve DNA vaccine design against Toxoplasma gondii.

PubMed

Shaddel, Minoo; Ebrahimi, Mansour; Tabandeh, Mohammad Reza

2018-06-01

Toxoplasma gondii , is a causative agent of morbidity and mortality in immunocompromised and congenitally-infected individuals. Attempts to construct DNA vaccines against T. gondii using surface proteins are increasing. The dense granule antigens are highly expressed in the acute and chronic phases of T. gondii infection and considered as suitable DNA vaccine candidates to control toxoplasmosis. In the present study, bioinformatics tools and online software were used to predict, analyze and compare the structural, physical and chemical characters and immunogenicity of the GRA-1, GRA-4, GRA-6 and GRA-7 proteins. Sequence alignment results indicated that the GRA-1, GRA-4, GRA-6 and GRA-7 proteins had low similarity. The secondary structure prediction demonstrated that among the four proteins, GRA-1 and GRA-6 had similar secondary structure except for a little discrepancy. Hydrophilicity/hydrophobicity analysis showed multiple hydrophilic regions and some classical high hydrophilic domains for each protein sequence. Immunogenic epitope prediction results demonstrated that the GRA-1 and GRA-4 epitopes were stable and GRA-4 showed the highest degree of antigenicity. Although the GRA-7 epitope had the highest score of immunogenicity, this epitope was instable and had the lowest degree of antigenicity and half-time in eukaryotic cell. Also, the results indicated that GRA4-GRA7 epitope and GRA6-GRA7 had the highest degree of antigenicity and immunogenicity among multi-hybrid epitopes, respectively. Totally, in the present study, single epitopes showed the highest degree of antigenicity compared with multi-hybrid epitopes. Given the results, it can be concluded that GRA-4 and GRA-7 can be powerful DNA vaccine candidates against T. gondii .

Classical Mathematical Models for Description and Prediction of Experimental Tumor Growth

PubMed Central

Benzekry, Sébastien; Lamont, Clare; Beheshti, Afshin; Tracz, Amanda; Ebos, John M. L.; Hlatky, Lynn; Hahnfeldt, Philip

2014-01-01

Despite internal complexity, tumor growth kinetics follow relatively simple laws that can be expressed as mathematical models. To explore this further, quantitative analysis of the most classical of these were performed. The models were assessed against data from two in vivo experimental systems: an ectopic syngeneic tumor (Lewis lung carcinoma) and an orthotopically xenografted human breast carcinoma. The goals were threefold: 1) to determine a statistical model for description of the measurement error, 2) to establish the descriptive power of each model, using several goodness-of-fit metrics and a study of parametric identifiability, and 3) to assess the models' ability to forecast future tumor growth. The models included in the study comprised the exponential, exponential-linear, power law, Gompertz, logistic, generalized logistic, von Bertalanffy and a model with dynamic carrying capacity. For the breast data, the dynamics were best captured by the Gompertz and exponential-linear models. The latter also exhibited the highest predictive power, with excellent prediction scores (≥80%) extending out as far as 12 days in the future. For the lung data, the Gompertz and power law models provided the most parsimonious and parametrically identifiable description. However, not one of the models was able to achieve a substantial prediction rate (≥70%) beyond the next day data point. In this context, adjunction of a priori information on the parameter distribution led to considerable improvement. For instance, forecast success rates went from 14.9% to 62.7% when using the power law model to predict the full future tumor growth curves, using just three data points. These results not only have important implications for biological theories of tumor growth and the use of mathematical modeling in preclinical anti-cancer drug investigations, but also may assist in defining how mathematical models could serve as potential prognostic tools in the clinic. PMID:25167199

Classical mathematical models for description and prediction of experimental tumor growth.

PubMed

Benzekry, Sébastien; Lamont, Clare; Beheshti, Afshin; Tracz, Amanda; Ebos, John M L; Hlatky, Lynn; Hahnfeldt, Philip

2014-08-01

Despite internal complexity, tumor growth kinetics follow relatively simple laws that can be expressed as mathematical models. To explore this further, quantitative analysis of the most classical of these were performed. The models were assessed against data from two in vivo experimental systems: an ectopic syngeneic tumor (Lewis lung carcinoma) and an orthotopically xenografted human breast carcinoma. The goals were threefold: 1) to determine a statistical model for description of the measurement error, 2) to establish the descriptive power of each model, using several goodness-of-fit metrics and a study of parametric identifiability, and 3) to assess the models' ability to forecast future tumor growth. The models included in the study comprised the exponential, exponential-linear, power law, Gompertz, logistic, generalized logistic, von Bertalanffy and a model with dynamic carrying capacity. For the breast data, the dynamics were best captured by the Gompertz and exponential-linear models. The latter also exhibited the highest predictive power, with excellent prediction scores (≥80%) extending out as far as 12 days in the future. For the lung data, the Gompertz and power law models provided the most parsimonious and parametrically identifiable description. However, not one of the models was able to achieve a substantial prediction rate (≥70%) beyond the next day data point. In this context, adjunction of a priori information on the parameter distribution led to considerable improvement. For instance, forecast success rates went from 14.9% to 62.7% when using the power law model to predict the full future tumor growth curves, using just three data points. These results not only have important implications for biological theories of tumor growth and the use of mathematical modeling in preclinical anti-cancer drug investigations, but also may assist in defining how mathematical models could serve as potential prognostic tools in the clinic.

The predictive power of physical function assessed by questionnaire and physical performance measures for subsequent disability.

PubMed

Hoshi, Masayuki; Hozawa, Atsushi; Kuriyama, Shinichi; Nakaya, Naoki; Ohmori-Matsuda, Kaori; Sone, Toshimasa; Kakizaki, Masako; Niu, Kaijun; Fujita, Kazuki; Ueki, Shouzoh; Haga, Hiroshi; Nagatomi, Ryoichi; Tsuji, Ichiro

2012-08-01

To compare the predictive power of physical function assessed by questionnaire and physical performance measures for subsequent disability in community-dwelling elderly persons. Prospective cohort study. Participants were 813 aged 70 years and older, elderly Japanese residing in the community, included in the Tsurugaya Project, who were not disabled at the baseline in 2003. Physical function was assessed by the questionnaire of "Motor Fitness Scale". Physical performance measures consisted of maximum walking velocity, timed up and go test (TUG), leg extension power, and functional reach test. The area under the curve (AUC) of the receiver operating characteristic curve for disability was used to compare screening accuracy between Motor Fitness Scale and physical performance measures. Incident disability, defined as certification for long-term care insurance, was used as the endpoint. We observed 135 cases of incident disability during follow-up. The third or fourth quartile for each measure was associated with a significantly increased risk of disability in comparison with the highest quartile. The AUC was 0.70, 0.72, 0.70, 0.68, 0.69 and 0.74, for Motor Fitness Scale, maxi- mum walking velocity, TUG, leg extension power, functional reach test, and total performance score, respectively. The predictive power of physical function assessed by the Motor Fitness Scale was equivalent to that assessed by physical performance measures. Since Motor Fitness Scale can evaluate physical function safely and simply in comparison with physical performance tests, it would be a practical tool for screening persons at high risk of disability.

The PREM score: a graphical tool for predicting survival in very preterm births.

PubMed

Cole, T J; Hey, E; Richmond, S

2010-01-01

To develop a tool for predicting survival to term in babies born more than 8 weeks early using only information available at or before birth. 1456 non-malformed very preterm babies of 22-31 weeks' gestation born in 2000-3 in the north of England and 3382 births of 23-31 weeks born in 2000-4 in Trent. Survival to term, predicted from information available at birth, and at the onset of labour or delivery. Development of a logistic regression model (the prematurity risk evaluation measure or PREM score) based on gestation, birth weight for gestation and base deficit from umbilical cord blood. Gestation was by far the most powerful predictor of survival to term, and as few as 5 extra days can double the chance of survival. Weight for gestation also had a powerful but non-linear effect on survival, with weight between the median and 85th centile predicting the highest survival. Using this information survival can be predicted almost as accurately before birth as after, although base deficit further improves the prediction. A simple graph is described that shows how the two main variables gestation and weight for gestation interact to predict the chance of survival. The PREM score can be used to predict the chance of survival at or before birth almost as accurately as existing measures influenced by post-delivery condition, to balance risk at entry into a controlled trial and to adjust for differences in "case mix" when assessing the quality of perinatal care.

Analysis of Particulate Composite Behavior Based on Nonlinear Elasticity and an Improved Mori-Tanaka Theory

DTIC Science & Technology

1998-09-01

to characterize the weakening constraint power of the matrix as opposed to earlier analyses that used an additional eigenstrain term. It also...matrix Poisson ratio was constant and the inclusions were rigid, he showed that the disturbed strain and the eigenstrain in the Eshelby method could...Eshelby, elastic properties, prediction, energy balance, mechanical behavior, eigenstrain , nonlinear dcd03e So7S&3 UNCLASSIFIED SECURITY CLASSIFICATION OF FORM (Highest classification of Title, Abstract, Keywords)

High N-Terminal Pro-B-Type Natriuretic Peptide Levels Are Associated with Reduced Heart Rate Variability in Acute Myocardial Infarction

PubMed Central

Lorgis, Luc; Moreau, Daniel; Mock, Laurent; Daumas, Bernadette; Potard, Daniel; Touzery, Claude; Cottin, Yves; Zeller, Marianne

2012-01-01

Aim We investigated the relationships between the autonomic nervous system, as assessed by heart rate variability (HRV) and levels of N-terminal Pro-B-type Natriuretic Peptide (Nt-proBNP) in patients with acute myocardial infarction (MI). Methods and Results The mean of standard deviation of RR intervals (SDNN), the percentage of RR intervals with >50 ms variation (pNN50), square root of mean squared differences of successive RR intervals (rMSSD), and frequency domain parameters (total power (TP), high frequency and low frequency power ratio (LF/HF)) were assessed by 24 h Holter ECG monitoring. 1018 consecutive patients admitted <24 h for an acute MI were included. Plasma Nt-proBNP (Elecsys, Roche) was measured from blood samples taken on admission. The median (IQR) Nt-proBNP level was 681(159–2432) pmol/L. Patients with the highest quartile of Nt-proBNP were older, with higher rate of risk factors and lower ejection fraction. The highest Nt-proBNP quartile group had the lowest SDNN, LF/HF and total power but similar pNN50 and rMSSD levels. Nt-proBNP levels correlated negatively with SDNN (r = −0.19, p<0.001), LF/HF (r = −0.37, p<0.001), and LF (r = −0.29, p<0.001) but not HF (r = −0.043, p = 0.172). Multiple regression analysis showed that plasma propeptide levels remained predictive of LF/HF (B(SE) = −0.065(0.015), p<0.001)), even after adjustment for confounders. Conclusions In conclusion, our population-based study highlights the importance of Nt-proBNP levels to predict decreased HRV after acute MI. PMID:23071500

Performance and driveline analyses of engine capacity in range extender engine hybrid vehicle

NASA Astrophysics Data System (ADS)

Praptijanto, Achmad; Santoso, Widodo Budi; Nur, Arifin; Wahono, Bambang; Putrasari, Yanuandri

2017-01-01

In this study, range extender engine designed should be able to meet the power needs of a power generator of hybrid electrical vehicle that has a minimum of 18 kW. Using this baseline model, the following range extenders will be compared between conventional SI piston engine (Baseline, BsL), engine capacity 1998 cm3, and efficiency-oriented SI piston with engine capacity 999 cm3 and 499 cm3 with 86 mm bore and stroke square gasoline engine in the performance, emission prediction of range extender engine, standard of charge by using engine and vehicle simulation software tools. In AVL Boost simulation software, range extender engine simulated from 1000 to 6000 rpm engine loads. The highest peak engine power brake reached up to 38 kW at 4500 rpm. On the other hand the highest torque achieved in 100 Nm at 3500 rpm. After that using AVL cruise simulation software, the model of range extended electric vehicle in series configuration with main components such as internal combustion engine, generator, electric motor, battery and the arthemis model rural road cycle was used to simulate the vehicle model. The simulation results show that engine with engine capacity 999 cm3 reported the economical performances of the engine and the emission and the control of engine cycle parameters.

Optimization of enzymes-microwave-ultrasound assisted extraction of Lentinus edodes polysaccharides and determination of its antioxidant activity.

PubMed

Yin, Chaomin; Fan, Xiuzhi; Fan, Zhe; Shi, Defang; Gao, Hong

2018-05-01

Enzymes-microwave-ultrasound assisted extraction (EMUE) method had been used to extract Lentinus edodes polysaccharides (LEPs). The enzymatic temperature, enzymatic pH, microwave power and microwave time were optimized by response surface methodology. The yields, properties and antioxidant activities of LEPs from EMUE and other extraction methods including hot-water extraction, enzymes-assisted extraction, microwave-assisted extraction and ultrasound-assisted extraction were evaluated. The results showed that the highest LEPs yield of 9.38% was achieved with enzymatic temperature of 48°C, enzymatic pH of 5.0, microwave power of 440W and microwave time of 10min, which correlated well with the predicted value of 9.79%. Additionally, LEPs from different extraction methods possessed typical absorption peak of polysaccharides, which meant different extraction methods had no significant effects on type of glycosidic bonds and sugar ring of LEPs. However, SEM images of LEPs from different extraction methods were significantly different. Moreover, the different LEPs all showed antioxidant activities, but LEPs from EMUE showed the highest reducing power when compared to other LEPs. The results indicated LEPs from EMUE can be used as natural antioxidant component in the pharmaceutical and functional food industries. Copyright © 2018 Elsevier B.V. All rights reserved.

Use of a Machine-learning Method for Predicting Highly Cited Articles Within General Radiology Journals.

PubMed

Rosenkrantz, Andrew B; Doshi, Ankur M; Ginocchio, Luke A; Aphinyanaphongs, Yindalon

2016-12-01

This study aimed to assess the performance of a text classification machine-learning model in predicting highly cited articles within the recent radiological literature and to identify the model's most influential article features. We downloaded from PubMed the title, abstract, and medical subject heading terms for 10,065 articles published in 25 general radiology journals in 2012 and 2013. Three machine-learning models were applied to predict the top 10% of included articles in terms of the number of citations to the article in 2014 (reflecting the 2-year time window in conventional impact factor calculations). The model having the highest area under the curve was selected to derive a list of article features (words) predicting high citation volume, which was iteratively reduced to identify the smallest possible core feature list maintaining predictive power. Overall themes were qualitatively assigned to the core features. The regularized logistic regression (Bayesian binary regression) model had highest performance, achieving an area under the curve of 0.814 in predicting articles in the top 10% of citation volume. We reduced the initial 14,083 features to 210 features that maintain predictivity. These features corresponded with topics relating to various imaging techniques (eg, diffusion-weighted magnetic resonance imaging, hyperpolarized magnetic resonance imaging, dual-energy computed tomography, computed tomography reconstruction algorithms, tomosynthesis, elastography, and computer-aided diagnosis), particular pathologies (prostate cancer; thyroid nodules; hepatic adenoma, hepatocellular carcinoma, non-alcoholic fatty liver disease), and other topics (radiation dose, electroporation, education, general oncology, gadolinium, statistics). Machine learning can be successfully applied to create specific feature-based models for predicting articles likely to achieve high influence within the radiological literature. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2014-06-01

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

An Optimal Current Observer for Predictive Current Controlled Buck DC-DC Converters

PubMed Central

Min, Run; Chen, Chen; Zhang, Xiaodong; Zou, Xuecheng; Tong, Qiaoling; Zhang, Qiao

2014-01-01

In digital current mode controlled DC-DC converters, conventional current sensors might not provide isolation at a minimized price, power loss and size. Therefore, a current observer which can be realized based on the digital circuit itself, is a possible substitute. However, the observed current may diverge due to the parasitic resistors and the forward conduction voltage of the diode. Moreover, the divergence of the observed current will cause steady state errors in the output voltage. In this paper, an optimal current observer is proposed. It achieves the highest observation accuracy by compensating for all the known parasitic parameters. By employing the optimal current observer-based predictive current controller, a buck converter is implemented. The converter has a convergently and accurately observed inductor current, and shows preferable transient response than the conventional voltage mode controlled converter. Besides, costs, power loss and size are minimized since the strategy requires no additional hardware for current sensing. The effectiveness of the proposed optimal current observer is demonstrated experimentally. PMID:24854061

Performance assessment of individual and ensemble data-mining techniques for gully erosion modeling.

PubMed

Pourghasemi, Hamid Reza; Yousefi, Saleh; Kornejady, Aiding; Cerdà, Artemi

2017-12-31

Gully erosion is identified as an important sediment source in a range of environments and plays a conclusive role in redistribution of eroded soils on a slope. Hence, addressing spatial occurrence pattern of this phenomenon is very important. Different ensemble models and their single counterparts, mostly data mining methods, have been used for gully erosion susceptibility mapping; however, their calibration and validation procedures need to be thoroughly addressed. The current study presents a series of individual and ensemble data mining methods including artificial neural network (ANN), support vector machine (SVM), maximum entropy (ME), ANN-SVM, ANN-ME, and SVM-ME to map gully erosion susceptibility in Aghemam watershed, Iran. To this aim, a gully inventory map along with sixteen gully conditioning factors was used. A 70:30% randomly partitioned sets were used to assess goodness-of-fit and prediction power of the models. The robustness, as the stability of models' performance in response to changes in the dataset, was assessed through three training/test replicates. As a result, conducted preliminary statistical tests showed that ANN has the highest concordance and spatial differentiation with a chi-square value of 36,656 at 95% confidence level, while the ME appeared to have the lowest concordance (1772). The ME model showed an impractical result where 45% of the study area was introduced as highly susceptible to gullying, in contrast, ANN-SVM indicated a practical result with focusing only on 34% of the study area. Through all three replicates, the ANN-SVM ensemble showed the highest goodness-of-fit and predictive power with a respective values of 0.897 (area under the success rate curve) and 0.879 (area under the prediction rate curve), on average, and correspondingly the highest robustness. This attests the important role of ensemble modeling in congruently building accurate and generalized models which emphasizes the necessity to examine different models integrations. The result of this study can prepare an outline for further biophysical designs on gullies scattered in the study area. Copyright © 2017 Elsevier B.V. All rights reserved.

Predicting punching acceleration from selected strength and power variables in elite karate athletes: a multiple regression analysis.

PubMed

Loturco, Irineu; Artioli, Guilherme Giannini; Kobal, Ronaldo; Gil, Saulo; Franchini, Emerson

2014-07-01

This study investigated the relationship between punching acceleration and selected strength and power variables in 19 professional karate athletes from the Brazilian National Team (9 men and 10 women; age, 23 ± 3 years; height, 1.71 ± 0.09 m; and body mass [BM], 67.34 ± 13.44 kg). Punching acceleration was assessed under 4 different conditions in a randomized order: (a) fixed distance aiming to attain maximum speed (FS), (b) fixed distance aiming to attain maximum impact (FI), (c) self-selected distance aiming to attain maximum speed, and (d) self-selected distance aiming to attain maximum impact. The selected strength and power variables were as follows: maximal dynamic strength in bench press and squat-machine, squat and countermovement jump height, mean propulsive power in bench throw and jump squat, and mean propulsive velocity in jump squat with 40% of BM. Upper- and lower-body power and maximal dynamic strength variables were positively correlated to punch acceleration in all conditions. Multiple regression analysis also revealed predictive variables: relative mean propulsive power in squat jump (W·kg-1), and maximal dynamic strength 1 repetition maximum in both bench press and squat-machine exercises. An impact-oriented instruction and a self-selected distance to start the movement seem to be crucial to reach the highest acceleration during punching execution. This investigation, while demonstrating strong correlations between punching acceleration and strength-power variables, also provides important information for coaches, especially for designing better training strategies to improve punching speed.

Chronic Obstructive Pulmonary Disease Assessment Test Can Predict Depression: A Prospective Multi-Center Study

PubMed Central

Lee, Young Seok; Park, Sunghoon; Oh, Yeon-Mok; Lee, Sang-Do; Park, Sung-Woo; Kim, Young Sam; In, Kwang Ho; Jung, Bock Hyun; Lee, Kwan Ho; Ra, Seung Won; Hwang, Yong Il; Park, Yong-Bum

2013-01-01

This study was conducted to investigate the association between the chronic obstructive pulmonary disease (COPD) assessment test (CAT) and depression in COPD patients. The Korean versions of the CAT and patient health questionnaire-9 (PHQ-9) were used to assess COPD symptoms and depressive disorder, respectively. In total, 803 patients with COPD were enrolled from 32 hospitals and the prevalence of depression was 23.8%. The CAT score correlated well with the PHQ-9 score (r=0.631; P<0.001) and was significantly associated with the presence of depression (β±standard error, 0.452±0.020; P<0.001). There was a tendency toward increasing severity of depression in patients with higher CAT scores. By assessment groups based on the 2011 Global Initiative for Chronic Obstructive Lung Disease guidelines, the prevalence of depression was affected more by current symptoms than by airway limitation. The area under the receiver operating characteristic curve for the CAT was 0.849 for predicting depression, and CAT scores ≥21 had the highest accuracy rate (80.6%). Among the eight CAT items, energy score showed the best correlation and highest power of discrimination. CAT scores are significantly associated with the presence of depression and have good performance for predicting depression in COPD patients. PMID:23853488

Neuromechanical sensor fusion yields highest accuracies in predicting ambulation mode transitions for trans-tibial amputees.

PubMed

Tkach, D C; Hargrove, L J

2013-01-01

Advances in battery and actuator technology have enabled clinical use of powered lower limb prostheses such as the BiOM Powered Ankle. To allow ambulation over various types of terrains, such devices rely on built-in mechanical sensors or manual actuation by the amputee to transition into an operational mode that is suitable for a given terrain. It is unclear if mechanical sensors alone can accurately modulate operational modes while voluntary actuation prevents seamless, naturalistic gait. Ensuring that the prosthesis is ready to accommodate new terrain types at first step is critical for user safety. EMG signals from patient's residual leg muscles may provide additional information to accurately choose the proper mode of prosthesis operation. Using a pattern recognition classifier we compared the accuracy of predicting 8 different mode transitions based on (1) prosthesis mechanical sensor output (2) EMG recorded from residual limb and (3) fusion of EMG and mechanical sensor data. Our findings indicate that the neuromechanical sensor fusion significantly decreases errors in predicting 10 mode transitions as compared to using either mechanical sensors or EMG alone (2.3±0.7% vs. 7.8±0.9% and 20.2±2.0% respectively).

Prediction and Characterization of NaGaS2, A High Thermal Conductivity Mid-Infrared Nonlinear Optical Material for High-Power Laser Frequency Conversion.

PubMed

Hou, Dianwei; Nissimagoudar, Arun S; Bian, Qiang; Wu, Kui; Pan, Shilie; Li, Wu; Yang, Zhihua

2018-06-15

Infrared nonlinear optical (IR NLO) crystals are the major materials to widen the output range of solid-state lasers to mid- or far-infrared regions. The IR NLO crystals used in the middle IR region are still inadequate for high-power laser applications because of deleterious thermal effects (lensing and expansion), low laser-induced damage threshold, and two-photon absorption. Herein, the unbiased global minimum search method was used for the first time to search for IR NLO optical materials and ultimately found a new IR NLO material NaGaS 2 . It meets the stringent demands for IR NLO materials pumped by high-power laser with the highest thermal conductivity among common IR NLO materials able to avoid two-photon absorption, a classic nonlinear coefficient, and wide infrared transparency.

Study of parametric instability in gravitational wave detectors with silicon test masses

NASA Astrophysics Data System (ADS)

Zhang, Jue; Zhao, Chunnong; Ju, Li; Blair, David

2017-03-01

Parametric instability is an intrinsic risk in high power laser interferometer gravitational wave detectors, in which the optical cavity modes interact with the acoustic modes of the mirrors, leading to exponential growth of the acoustic vibration. In this paper, we investigate the potential parametric instability for a proposed next generation gravitational wave detector, the LIGO Voyager blue design, with cooled silicon test masses of size 45 cm in diameter and 55 cm in thickness. It is shown that there would be about two unstable modes per test mass at an arm cavity power of 3 MW, with the highest parametric gain of  ∼76. While this is less than the predicted number of unstable modes for Advanced LIGO (∼40 modes with max gain of  ∼32 at the designed operating power of 830 kW), the importance of developing suitable instability suppression schemes is emphasized.

Splash dispersal of Phyllosticta citricarpa conidia from infected citrus fruit

PubMed Central

Perryman, S. A. M.; Clark, S. J.; West, J. S.

2014-01-01

Rain-splash dispersal of Phyllosticta citricarpa (syn. Guignardia citricarpa) conidia (pycnidiospores) from infected oranges was studied in still air and combined with wind. High power microscopy demonstrated the presence of conidia in splash droplets from diseased oranges, which exuded conidia for over one hour during repeated wetting. The largest (5 mm) incident drops produced the highest splashes (up to 41.0 cm). A linear-by-quadratic surface model predicted highest splashes to be 41.91 cm at a horizontal distance of 25.97 cm from the target orange. Large splash droplets contained most conidia (4–5.5 mm splashes averaged 308 conidia), but were splashed <30 cm horizontal distance. Most (80–90%) splashes were <1 mm diameter but carried only 0–4 conidia per droplet. In multiple splash experiments, splashes combined to reach higher maxima (up to 61.7 cm; linear-by-quadratic surface model prediction, 62.1 cm) than in the single splash experiments. In combination with wind, higher wind speeds carried an increasing proportion of splashes downwind travelling horizontally at least 8 m at the highest wind speed tested (7 m/s), due to a small proportion of droplets (<1 mm) being aerosolised. These experiments suggest that P. citricarpa conidia can be dispersed from infected oranges by splashes of water in rainfall events. PMID:25298272

Splash dispersal of Phyllosticta citricarpa conidia from infected citrus fruit.

PubMed

Perryman, S A M; Clark, S J; West, J S

2014-10-09

Rain-splash dispersal of Phyllosticta citricarpa (syn. Guignardia citricarpa) conidia (pycnidiospores) from infected oranges was studied in still air and combined with wind. High power microscopy demonstrated the presence of conidia in splash droplets from diseased oranges, which exuded conidia for over one hour during repeated wetting. The largest (5 mm) incident drops produced the highest splashes (up to 41.0 cm). A linear-by-quadratic surface model predicted highest splashes to be 41.91 cm at a horizontal distance of 25.97 cm from the target orange. Large splash droplets contained most conidia (4-5.5 mm splashes averaged 308 conidia), but were splashed <30 cm horizontal distance. Most (80-90%) splashes were <1 mm diameter but carried only 0-4 conidia per droplet. In multiple splash experiments, splashes combined to reach higher maxima (up to 61.7 cm; linear-by-quadratic surface model prediction, 62.1 cm) than in the single splash experiments. In combination with wind, higher wind speeds carried an increasing proportion of splashes downwind travelling horizontally at least 8 m at the highest wind speed tested (7 m/s), due to a small proportion of droplets (<1 mm) being aerosolised. These experiments suggest that P. citricarpa conidia can be dispersed from infected oranges by splashes of water in rainfall events.

SDP_mharwit_1: Demonstration of HIFI Linear Polarization Analysis of Spectral Features

NASA Astrophysics Data System (ADS)

Harwit, M.

2010-03-01

We propose to observe the polarization of the 621 GHz water vapor maser in VY Canis Majoris to demonstrate the capability of HIFI to make polarization observations of Far-Infrared/Submillimeter spectral lines. The proposed Demonstration Phase would: - Show that HIFI is capable of interesting linear polarization measurements of spectral lines; - Test out the highest spectral resolving power to sort out closely spaced Doppler components; - Determine whether the relative intensities predicted by Neufeld and Melnick are correct; - Record the degree and direction of linear polarization for the closely-Doppler shifted peaks.

Mitigation of multipacting, enhanced by gas condensation on the high power input coupler of a superconducting RF module, by comprehensive warm aging

NASA Astrophysics Data System (ADS)

Wang, Chaoen; Chang, Lung-Hai; Chang, Mei-Hsia; Chen, Ling-Jhen; Chung, Fu-Tsai; Lin, Ming-Chyuan; Liu, Zong-Kai; Lo, Chih-Hung; Tsai, Chi-Lin; Yeh, Meng-Shu; Yu, Tsung-Chi

2017-11-01

Excitation of multipacting, enhanced by gas condensation on cold surfaces of the high power input coupler in a SRF module poses the highest challenge for reliable SRF operation under high average RF power. This could prevent the light source SRF module from being operated with a desired high beam current. Off-line long-term reliability tests have been conducted for the newly constructed 500-MHz SRF KEKB type modules at an accelerating RF voltage of 1.6-MV to enable prediction of their operational reliability in the 3-GeV Taiwan Photon Source (TPS), since prediction from mere production performance by conventional horizontal test is presently unreliable. As expected, operational difficulties resulting from multipacting, enhanced by gas condensation, have been identified in the course of long-term reliability test. Our present hypothesis is that gas condensation can be slowed down by preserving the vacuum pressure at the power coupler close to that reached just after its cool down to liquid helium temperatures. This is achievable by reduction of the power coupler out-gassing rate through comprehensive warm aging. Its feasibility and effectiveness has been experimentally verified in a second long term reliability test. Our success opens the possibility to operate the SRF module free of multipacting trouble and opens a new direction to improve the operational performance of next generation SRF modules in light sources with high beam currents.

Earthquake prediction in California using regression algorithms and cloud-based big data infrastructure

NASA Astrophysics Data System (ADS)

Asencio-Cortés, G.; Morales-Esteban, A.; Shang, X.; Martínez-Álvarez, F.

2018-06-01

Earthquake magnitude prediction is a challenging problem that has been widely studied during the last decades. Statistical, geophysical and machine learning approaches can be found in literature, with no particularly satisfactory results. In recent years, powerful computational techniques to analyze big data have emerged, making possible the analysis of massive datasets. These new methods make use of physical resources like cloud based architectures. California is known for being one of the regions with highest seismic activity in the world and many data are available. In this work, the use of several regression algorithms combined with ensemble learning is explored in the context of big data (1 GB catalog is used), in order to predict earthquakes magnitude within the next seven days. Apache Spark framework, H2 O library in R language and Amazon cloud infrastructure were been used, reporting very promising results.

Relationship between TG/HDL-C ratio and metabolic syndrome risk factors with chronic kidney disease in healthy adult population.

PubMed

Ho, Chih-I; Chen, Jau-Yuan; Chen, Shou-Yen; Tsai, Yi-Wen; Weng, Yi-Ming; Tsao, Yu-Chung; Li, Wen-Cheng

2015-10-01

The triglycerides-to-high-density lipoprotein-cholesterol (TG/HDL-C) ratio has been identified as a biomarker of insulin resistance and a predictor for atherosclerosis. The objectives of this study were to investigate which the TG/HDL-C ratio is useful to detect metabolic syndrome (MS) risk factors and subclinical chronic kidney disease (CKD) in general population without known CKD or renal impairment and to compare predictive accuracy of MS risk factors. This was a cross-sectional study. A total 46,255 subjects aged ≥18 years undergoing health examination during 2010-2011 in Taiwan. The independent associations between TG/HDL-C ratio quartiles, waist circumstance (WC) waist-to-height ratio (WHtR), mean atrial pressure (MAP), and CKD prevalence was analyzed by using logistic regression models. Analyses of the areas under receiver operating characteristic (ROC) were performed to determine the accuracy of MS risk factors in predicting CKD. A dose-response manner was observed for the prevalence of CKD and measurements of MS risk factors, showing increases from the lowest to the highest quartile of the TG/HDL-C ratio. Males and females in the highest TG/HDL-C ratio quartile (>2.76) had a 1.4-fold and 1.74-fold greater risk of CKD than those in the lowest quartile (≤1.04), independent of confounding factors. Mean arterial pressure (MAP) had the highest AUC for predicting CKD among MS risk factors. The TG/HDL-C ratio was an independent risk factor for CKD, but it showed no superiority over MAP in predicting CKD. A TG/HDL-C ratio ≥2.76 may be useful in clinical practice to detect subjects with worsened cardiometabolic profile who need monitoring to prevent CKD. TG/HDL-C ratio is an independent risk factor for CKD in adults aged 18-50 years. MAP was the most powerful predictor over other MS risk factors in predicting CKD. However, longitudinal and comparative studies are required to demonstrate the predictive value of TG/HDL-C on the onset and progression of CKD over time. Copyright © 2014 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Mode perturbation method for optimal guided wave mode and frequency selection.

PubMed

Philtron, J H; Rose, J L

2014-09-01

With a thorough understanding of guided wave mechanics, researchers can predict which guided wave modes will have a high probability of success in a particular nondestructive evaluation application. However, work continues to find optimal mode and frequency selection for a given application. This "optimal" mode could give the highest sensitivity to defects or the greatest penetration power, increasing inspection efficiency. Since material properties used for modeling work may be estimates, in many cases guided wave mode and frequency selection can be adjusted for increased inspection efficiency in the field. In this paper, a novel mode and frequency perturbation method is described and used to identify optimal mode points based on quantifiable wave characteristics. The technique uses an ultrasonic phased array comb transducer to sweep in phase velocity and frequency space. It is demonstrated using guided interface waves for bond evaluation. After searching nearby mode points, an optimal mode and frequency can be selected which has the highest sensitivity to a defect, or gives the greatest penetration power. The optimal mode choice for a given application depends on the requirements of the inspection. Copyright © 2014 Elsevier B.V. All rights reserved.

A Numerical Simulation (Study) of a Strong West Coast December 2014 Winter Storm

NASA Astrophysics Data System (ADS)

Smelser, I.; Xu, L.; Amerault, C. M.; Baker, N. L.; Satterfield, E.; Chua, B.

2016-12-01

From December 10 through December 13, 2014, a powerful winter storm swept across the western US coastal states bringing widespread power outages, numerous downed trees and power lines, heavy rains, flooding and even a tornado in the Los Angeles basin. This windstorm was the strongest since October 2009, and was similar to classic wind storms such as the 1962 Columbus Day Storm (Read, 2015).The storm started developing over the Pacific Ocean north of Hawaii on Nov. 30, and formed an atmospheric river that eventually stretched from Hawaii to the west coast. The storm initially hit the Pacific Northwest on Dec. 9th and then split. The highest precipitation amounts started in British Colombia and moved south along the coast. By the Dec. 11th, the highest precipitation amounts were near San Francisco (CA). The peak wind gust (14.4 ms-1) for Monterey (CA) occurred at 1116Z on Dec. 11th while the heaviest 6-hr precipitation (42.9 mm) occurred between 18Z on Dec. 11th to 00Z on Dec. 12th. By Dec. 12th, the storm was centered over Southern California.This storm was poorly forecast by many operational NWP models even 2-3 days in advance (Mass, 2014). The NCEP Global Forecast System (GFS) showed considerably variability between successive model runs, and significant differences existed between Environment Canada, UK Met Office and ECMWF model forecasts. To study this extreme weather event, we used the Navy global (NAVGEM) and mesoscale (COAMPS®) NWP models, and compared the resulting forecasts to observations, satellite imagery and ECMWF (TIGGE) forecasts. NAVGEM, with Hybrid 4DVar, was run with a resolution of 31 km, and generated the boundary conditions for COAMPS® 4DVar and forecasts, that were run with triple-nested grids of 27, 9, and 3 km. The MesoWest data from the University of Utah were used for forecast verification, and to locate the times of highest precipitation and wind speed for different points along the coast. Both the online API and the python module were used to access and pull information from the data base. Overall, both NAVGEM and COAMPS® predicted the storm well. NAVGEM predicted the storm to be slower and more powerful than the analyses. The NAVGEM analysis and corresponding 5-day forecast accumulated 6-hr precipitation (Fig. 1) for Dec. 12th at 00Z agree well with the observed precipitation (4.29 cm) for Monterey (KMRY).

Qweak Data Analysis for Target Modeling Using Computational Fluid Dynamics

NASA Astrophysics Data System (ADS)

Moore, Michael; Covrig, Silviu

2015-04-01

The 2.5 kW liquid hydrogen (LH2) target used in the Qweak parity violation experiment is the highest power LH2 target in the world and the first to be designed with Computational Fluid Dynamics (CFD) at Jefferson Lab. The Qweak experiment determined the weak charge of the proton by measuring the parity-violating elastic scattering asymmetry of longitudinally polarized electrons from unpolarized liquid hydrogen at small momentum transfer (Q2 = 0 . 025 GeV2). This target met the design goals of < 1 % luminosity reduction and < 5 % contribution to the total asymmetry width (the Qweak target achieved 2 % or 55 ppm). State of the art time dependent CFD simulations are being developed to improve the predictions of target noise on the time scale of the electron beam helicity period. These predictions will be bench-marked with the Qweak target data. This work is an essential ingredient in future designs of very high power low noise targets like MOLLER (5 kW, target noise asymmetry contribution < 25 ppm) and MESA (4.5 kW).

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.

RS-25 Engines Powered to Highest Level Ever During Stennis Test

NASA Image and Video Library

2018-02-21

Operators powered NASA’s Space Launch System (SLS) engine to 113 percent thrust level, the highest RS-25 power level yet achieved, for 50 seconds of a 260-second test on February 21 at Stennis Space Center. This was the third full-duration test conducted on the A-1 Test Stand at Stennis this year.

RS-25 Engines Powered to Highest Level Ever during Stennis Test

NASA Image and Video Library

2018-02-21

Operators powered NASA’s Space Launch System (SLS) engine to 113 percent thrust level, the highest RS-25 power level yet achieved, for 50 seconds of a 260-second test on February 21 at Stennis Space Center. This was the third full-duration test conducted on the A-1 Test Stand at Stennis this year.

Investigation of bio polymer electrolyte based on cellulose acetate-ammonium nitrate for potential use in electrochemical devices.

PubMed

Monisha, S; Mathavan, T; Selvasekarapandian, S; Milton Franklin Benial, A; Aristatil, G; Mani, N; Premalatha, M; Vinoth Pandi, D

2017-02-10

Proton conducting materials create prime interest in electro chemical device development. Present work has been carried out to design environment friendly new biopolymer electrolytes (BPEs) using cellulose acetate (CA) complex with different concentrations of ammonium nitrate (NH 4 NO 3 ), which have been prepared as film and characterized. The 50mol% CA and 50mol% NH 4 NO 3 complex has highest ionic conductivity (1.02×10 -3 Scm -1 ). Differential scanning calorimetry shows the changes in glass transition temperature depends on salt concentration. Structural analysis indicates that the highest ionic conductivity complex exhibits more amorphous nature. Vibrational analysis confirms the complex formation, which has been validated theoretically by Gaussian 09 software. Conducting element in the BPEs has been predicted. Primary proton battery and proton exchange membrane fuel cell have been developed for highest ionic conductivity complex. Output voltage and power performance has been compared for single fuel cell application, which manifests the present BPE holds promise application in electrochemical devices. Copyright © 2016 Elsevier Ltd. All rights reserved.

Fully utilizing high power diode lasers by synergizing diode laser light sources and beam shaping micro-optics

NASA Astrophysics Data System (ADS)

Fan, Yingmin; Wang, Jingwei; Cai, Lei; Mitra, Thomas; Hauschild, Dirk; Zah, Chung-En; Liu, Xingsheng

2018-02-01

High power diode lasers (HPDLs) offer the highest wall-plug efficiency, highest specific power (power-to-weight ratio), arguably the lowest cost and highest reliability among all laser types. However, the poor beam quality of commercially HPDLs is the main bottleneck limiting their direct applications requiring high brightness at least in one dimension. In order to expand the applications of HPDLs, beam shaping and optical design are essential. In this work, we report the recent progresses on maximizing applications of HPDLs by synergizing diode laser light source and beam shaping micro-optics. Successful examples of matching of diode laser light sources and beam shaping micro-optics driving new applications are presented.

Assessment of Cable Aging Equipment, Status of Acquired Materials, and Experimental Matrix at the Pacific Northwest National Laboratory

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

Fifield, Leonard S.; Westman, Matthew P.; Zwoster, Andy

2015-03-30

The need for increased understanding of the aging and degradation behavior for polymer components of nuclear power plant electrical cables is described in this report. The highest priority materials for study and the resources available at PNNL for these studies are also described. The anticipated outcomes of the PNNL work described are : improved understanding of appropriate accelerated aging conditions, improved knowledge of correlation between observable aging indicators and cable condition in support of advanced non-destructive evaluation methods, and practical knowledge of condition-based cable lifetime prediction.

Maximization of the annual energy production of wind power plants by optimization of layout and yaw-based wake control: Maximization of wind plant AEP by optimization of layout and wake control

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

Gebraad, Pieter; Thomas, Jared J.; Ning, Andrew

This paper presents a wind plant modeling and optimization tool that enables the maximization of wind plant annual energy production (AEP) using yaw-based wake steering control and layout changes. The tool is an extension of a wake engineering model describing the steady-state effects of yaw on wake velocity profiles and power productions of wind turbines in a wind plant. To make predictions of a wind plant's AEP, necessary extensions of the original wake model include coupling it with a detailed rotor model and a control policy for turbine blade pitch and rotor speed. This enables the prediction of power productionmore » with wake effects throughout a range of wind speeds. We use the tool to perform an example optimization study on a wind plant based on the Princess Amalia Wind Park. In this case study, combined optimization of layout and wake steering control increases AEP by 5%. The power gains from wake steering control are highest for region 1.5 inflow wind speeds, and they continue to be present to some extent for the above-rated inflow wind speeds. The results show that layout optimization and wake steering are complementary because significant AEP improvements can be achieved with wake steering in a wind plant layout that is already optimized to reduce wake losses.« less

Early Oscillation Detection for DC/DC Converter Fault Diagnosis

NASA Technical Reports Server (NTRS)

Wang, Bright L.

2011-01-01

The electrical power system of a spacecraft plays a very critical role for space mission success. Such a modern power system may contain numerous hybrid DC/DC converters both inside the power system electronics (PSE) units and onboard most of the flight electronics modules. One of the faulty conditions for DC/DC converter that poses serious threats to mission safety is the random occurrence of oscillation related to inherent instability characteristics of the DC/DC converters and design deficiency of the power systems. To ensure the highest reliability of the power system, oscillations in any form shall be promptly detected during part level testing, system integration tests, flight health monitoring, and on-board fault diagnosis. The popular gain/phase margin analysis method is capable of predicting stability levels of DC/DC converters, but it is limited only to verification of designs and to part-level testing on some of the models. This method has to inject noise signals into the control loop circuitry as required, thus, interrupts the DC/DC converter's normal operation and increases risks of degrading and damaging the flight unit. A novel technique to detect oscillations at early stage for flight hybrid DC/DC converters was developed.

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.

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.

Learning the Relationship between Galaxy Spectra and Star Formation Histories

NASA Astrophysics Data System (ADS)

Lovell, Christopher; Acquaviva, Viviana; Iyer, Kartheik; Gawiser, Eric

2018-01-01

We explore novel approaches to the problem of predicting a galaxy’s star formation history (SFH) from its Spectral Energy Distribution (SED). Traditional approaches to SED template fitting use constant or exponentially declining SFHs, and are known to incur significant bias in the inferred SFHs, which are typically skewed toward younger stellar populations. Machine learning approaches, including tree ensemble methods and convolutional neural networks, would not be affected by the same bias, and may work well in recovering unbiased and multi-episodic star formation histories. We use a supervised approach whereby models are trained using synthetic spectra, generated from three state of the art hydrodynamical simulations, including nebular emission. We explore how SED feature maps can be used to highlight areas of the spectrum with the highest predictive power and discuss the limitations of the approach when applied to real data.

338-GHz Semiconductor Amplifier Module

NASA Technical Reports Server (NTRS)

Samoska, Lorene A.; Gaier, Todd C.; Soria, Mary M.; Fung, King Man; Rasisic, Vesna; Deal, William; Leong, Kevin; Mei, Xiao Bing; Yoshida, Wayne; Liu, Po-Hsin;

Prediction of beef carcass and meat quality traits from factors characterising the rearing management system applied during the whole life of heifers.

PubMed

Soulat, J; Picard, B; Léger, S; Monteils, V

2018-06-01

In this study, four prediction models were developed by logistic regression using individual data from 96 heifers. Carcass and sensory rectus abdominis quality clusters were identified then predicted using the rearing factors data. The obtained models from rearing factors applied during the fattening period were compared to those characterising the heifers' whole life. The highest prediction power of carcass and meat quality clusters were obtained from the models considering the whole life, with success rates of 62.8% and 54.9%, respectively. Rearing factors applied during both pre-weaning and fattening periods influenced carcass and meat quality. According to models, carcass traits were improved when heifer's mother was older for first calving, calves ingested concentrates during pasture preceding weaning and heifers were slaughtered older. Meat traits were improved by the genetic of heifers' parents (i.e., calving ease and early muscularity) and when heifers were slaughtered older. A management of carcass and meat quality traits is possible at different periods of the heifers' life. Copyright © 2018 Elsevier Ltd. All rights reserved.

Entropy production and optimization of geothermal power plants

NASA Astrophysics Data System (ADS)

Michaelides, Efstathios E.

2012-09-01

Geothermal power plants are currently producing reliable and low-cost, base load electricity. Three basic types of geothermal power plants are currently in operation: single-flashing, dual-flashing, and binary power plants. Typically, the single-flashing and dual-flashing geothermal power plants utilize geothermal water (brine) at temperatures in the range of 550-430 K. Binary units utilize geothermal resources at lower temperatures, typically 450-380 K. The entropy production in the various components of the three types of geothermal power plants determines the efficiency of the plants. It is axiomatic that a lower entropy production would improve significantly the energy utilization factor of the corresponding power plant. For this reason, the entropy production in the major components of the three types of geothermal power plants has been calculated. It was observed that binary power plants generate the lowest amount of entropy and, thus, convert the highest rate of geothermal energy into mechanical energy. The single-flashing units generate the highest amount of entropy, primarily because they re-inject fluid at relatively high temperature. The calculations for entropy production provide information on the equipment where the highest irreversibilities occur, and may be used to optimize the design of geothermal processes in future geothermal power plants and thermal cycles used for the harnessing of geothermal energy.

Prediction of attendance at fitness center: a comparison between the theory of planned behavior, the social cognitive theory, and the physical activity maintenance theory

PubMed Central

Jekauc, Darko; Völkle, Manuel; Wagner, Matthias O.; Mess, Filip; Reiner, Miriam; Renner, Britta

2015-01-01

In the processes of physical activity (PA) maintenance specific predictors are effective, which differ from other stages of PA development. Recently, Physical Activity Maintenance Theory (PAMT) was specifically developed for prediction of PA maintenance. The aim of the present study was to evaluate the predictability of the future behavior by the PAMT and compare it with the Theory of Planned Behavior (TPB) and Social Cognitive Theory (SCT). Participation rate in a fitness center was observed for 101 college students (53 female) aged between 19 and 32 years (M = 23.6; SD = 2.9) over 20 weeks using a magnetic card. In order to predict the pattern of participation TPB, SCT and PAMT were used. A latent class zero-inflated Poisson growth curve analysis identified two participation patterns: regular attenders and intermittent exercisers. SCT showed the highest predictive power followed by PAMT and TPB. Impeding aspects as life stress and barriers were the strongest predictors suggesting that overcoming barriers might be an important aspect for working out on a regular basis. Self-efficacy, perceived behavioral control, and social support could also significantly differentiate between the participation patterns. PMID:25717313

Effect of heteroscedasticity treatment in residual error models on model calibration and prediction uncertainty estimation

NASA Astrophysics Data System (ADS)

Sun, Ruochen; Yuan, Huiling; Liu, Xiaoli

2017-11-01

The heteroscedasticity treatment in residual error models directly impacts the model calibration and prediction uncertainty estimation. This study compares three methods to deal with the heteroscedasticity, including the explicit linear modeling (LM) method and nonlinear modeling (NL) method using hyperbolic tangent function, as well as the implicit Box-Cox transformation (BC). Then a combined approach (CA) combining the advantages of both LM and BC methods has been proposed. In conjunction with the first order autoregressive model and the skew exponential power (SEP) distribution, four residual error models are generated, namely LM-SEP, NL-SEP, BC-SEP and CA-SEP, and their corresponding likelihood functions are applied to the Variable Infiltration Capacity (VIC) hydrologic model over the Huaihe River basin, China. Results show that the LM-SEP yields the poorest streamflow predictions with the widest uncertainty band and unrealistic negative flows. The NL and BC methods can better deal with the heteroscedasticity and hence their corresponding predictive performances are improved, yet the negative flows cannot be avoided. The CA-SEP produces the most accurate predictions with the highest reliability and effectively avoids the negative flows, because the CA approach is capable of addressing the complicated heteroscedasticity over the study basin.

Geometrical analysis on cap-shaped coils for power optimization of the vibration-based electromagnetic harvesting system

NASA Astrophysics Data System (ADS)

Hasbullah Mohd Isa, Wan; Fikri Muhammad, Khairul; Mohd Khairuddin, Ismail; Ishak, Ismayuzri; Razlan Yusoff, Ahmad

2016-02-01

This paper presents the new form of coils for electromagnetic energy harvesting system based on topology optimization method which look-liked a cap to maximize the power output. It could increase the number of magnetic flux linkage interception of a cylindrical permanent magnet which in this case is of 10mm diameter. Several coils with different geometrical properties have been build and tested on a vibration generator with frequency of 100Hz. The results showed that the coil with lowest number of winding transduced highest power output of 680μW while the highest number of windings generated highest voltage output of 0.16V.

Analysis and design of high-power and efficient, millimeter-wave power amplifier systems using zero degree combiners

NASA Astrophysics Data System (ADS)

Tai, Wei; Abbasi, Mortez; Ricketts, David S.

2018-01-01

We present the analysis and design of high-power millimetre-wave power amplifier (PA) systems using zero-degree combiners (ZDCs). The methodology presented optimises the PA device sizing and the number of combined unit PAs based on device load pull simulations, driver power consumption analysis and loss analysis of the ZDC. Our analysis shows that an optimal number of N-way combined unit PAs leads to the highest power-added efficiency (PAE) for a given output power. To illustrate our design methodology, we designed a 1-W PA system at 45 GHz using a 45 nm silicon-on-insulator process and showed that an 8-way combined PA has the highest PAE that yields simulated output power of 30.6 dBm and 31% peak PAE.

Power of data mining methods to detect genetic associations and interactions.

PubMed

Molinaro, Annette M; Carriero, Nicholas; Bjornson, Robert; Hartge, Patricia; Rothman, Nathaniel; Chatterjee, Nilanjan

2011-01-01

Genetic association studies, thus far, have focused on the analysis of individual main effects of SNP markers. Nonetheless, there is a clear need for modeling epistasis or gene-gene interactions to better understand the biologic basis of existing associations. Tree-based methods have been widely studied as tools for building prediction models based on complex variable interactions. An understanding of the power of such methods for the discovery of genetic associations in the presence of complex interactions is of great importance. Here, we systematically evaluate the power of three leading algorithms: random forests (RF), Monte Carlo logic regression (MCLR), and multifactor dimensionality reduction (MDR). We use the algorithm-specific variable importance measures (VIMs) as statistics and employ permutation-based resampling to generate the null distribution and associated p values. The power of the three is assessed via simulation studies. Additionally, in a data analysis, we evaluate the associations between individual SNPs in pro-inflammatory and immunoregulatory genes and the risk of non-Hodgkin lymphoma. The power of RF is highest in all simulation models, that of MCLR is similar to RF in half, and that of MDR is consistently the lowest. Our study indicates that the power of RF VIMs is most reliable. However, in addition to tuning parameters, the power of RF is notably influenced by the type of variable (continuous vs. categorical) and the chosen VIM. Copyright © 2011 S. Karger AG, Basel.

Simple, empirical approach to predict neutron capture cross sections from nuclear masses

NASA Astrophysics Data System (ADS)

Couture, A.; Casten, R. F.; Cakirli, R. B.

2017-12-01

Background: Neutron capture cross sections are essential to understanding the astrophysical s and r processes, the modeling of nuclear reactor design and performance, and for a wide variety of nuclear forensics applications. Often, cross sections are needed for nuclei where experimental measurements are difficult. Enormous effort, over many decades, has gone into attempting to develop sophisticated statistical reaction models to predict these cross sections. Such work has met with some success but is often unable to reproduce measured cross sections to better than 40 % , and has limited predictive power, with predictions from different models rapidly differing by an order of magnitude a few nucleons from the last measurement. Purpose: To develop a new approach to predicting neutron capture cross sections over broad ranges of nuclei that accounts for their values where known and which has reliable predictive power with small uncertainties for many nuclei where they are unknown. Methods: Experimental neutron capture cross sections were compared to empirical mass observables in regions of similar structure. Results: We present an extremely simple method, based solely on empirical mass observables, that correlates neutron capture cross sections in the critical energy range from a few keV to a couple hundred keV. We show that regional cross sections are compactly correlated in medium and heavy mass nuclei with the two-neutron separation energy. These correlations are easily amenable to predict unknown cross sections, often converting the usual extrapolations to more reliable interpolations. It almost always reproduces existing data to within 25 % and estimated uncertainties are below about 40 % up to 10 nucleons beyond known data. Conclusions: Neutron capture cross sections display a surprisingly strong connection to the two-neutron separation energy, a nuclear structure property. The simple, empirical correlations uncovered provide model-independent predictions of neutron capture cross sections, extending far from stability, including for nuclei of the highest sensitivity to r -process nucleosynthesis.

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.

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.

Statistical modeling to support power system planning

NASA Astrophysics Data System (ADS)

Staid, Andrea

This dissertation focuses on data-analytic approaches that improve our understanding of power system applications to promote better decision-making. It tackles issues of risk analysis, uncertainty management, resource estimation, and the impacts of climate change. Tools of data mining and statistical modeling are used to bring new insight to a variety of complex problems facing today's power system. The overarching goal of this research is to improve the understanding of the power system risk environment for improved operation, investment, and planning decisions. The first chapter introduces some challenges faced in planning for a sustainable power system. Chapter 2 analyzes the driving factors behind the disparity in wind energy investments among states with a goal of determining the impact that state-level policies have on incentivizing wind energy. Findings show that policy differences do not explain the disparities; physical and geographical factors are more important. Chapter 3 extends conventional wind forecasting to a risk-based focus of predicting maximum wind speeds, which are dangerous for offshore operations. Statistical models are presented that issue probabilistic predictions for the highest wind speed expected in a three-hour interval. These models achieve a high degree of accuracy and their use can improve safety and reliability in practice. Chapter 4 examines the challenges of wind power estimation for onshore wind farms. Several methods for wind power resource assessment are compared, and the weaknesses of the Jensen model are demonstrated. For two onshore farms, statistical models outperform other methods, even when very little information is known about the wind farm. Lastly, chapter 5 focuses on the power system more broadly in the context of the risks expected from tropical cyclones in a changing climate. Risks to U.S. power system infrastructure are simulated under different scenarios of tropical cyclone behavior that may result from climate change. The scenario-based approach allows me to address the deep uncertainty present by quantifying the range of impacts, identifying the most critical parameters, and assessing the sensitivity of local areas to a changing risk. Overall, this body of work quantifies the uncertainties present in several operational and planning decisions for power system applications.

No added value of age at menopause and the lifetime cumulative number of menstrual cycles for cardiovascular risk prediction in postmenopausal women.

PubMed

Atsma, Femke; van der Schouw, Yvonne T; Grobbee, Diederick E; Hoes, Arno W; Bartelink, Marie-Louise E L

2008-11-12

The aim of the present study was to investigate the added value of age at menopause and the lifetime cumulative number of menstrual cycles in cardiovascular risk prediction in postmenopausal women. This study included 971 women. The ankle-arm index was used as a proxy for cardiovascular morbidity and mortality. The ankle-arm index was calculated for each leg by dividing the highest ankle systolic blood pressure by the highest brachial systolic blood pressure. A cut-off value of 0.95 was used to differentiate between low and high risk women. Three cardiovascular risk models were constructed. In the initial model all classical predictors for cardiovascular disease were investigated. This model was then extended by age at menopause or the lifetime cumulative number of menstrual cycles to test their added value for cardiovascular risk prediction. Differences in discriminative power between the models were investigated by comparing the area under the receiver operating characteristic (ROC) curves. The mean age was 66.0 (+/-5.6) years. The 6 independent predictors for cardiovascular disease were age, systolic blood pressure, total to HDL cholesterol ratio, current smoking, glucose level, and body mass index > or =30 kg/m(2). The ROC area was 0.69 (0.64-0.73) and did not change when age at menopause or the lifetime cumulative number of menstrual cycles was added. The findings in this study among postmenopausal women did not support the view that age at menopause or a refined estimation of lifetime endogenous estrogen exposure would improve cardiovascular risk prediction as approximated by the ankle-arm index.

Predicting the ultimate potential of natural gas SOFC power cycles with CO2 capture - Part A: Methodology and reference cases

NASA Astrophysics Data System (ADS)

Campanari, Stefano; Mastropasqua, Luca; Gazzani, Matteo; Chiesa, Paolo; Romano, Matteo C.

2016-08-01

Driven by the search for the highest theoretical efficiency, in the latest years several studies investigated the integration of high temperature fuel cells in natural gas fired power plants, where fuel cells are integrated with simple or modified Brayton cycles and/or with additional bottoming cycles, and CO2 can be separated via chemical or physical separation, oxy-combustion and cryogenic methods. Focusing on Solid Oxide Fuel Cells (SOFC) and following a comprehensive review and analysis of possible plant configurations, this work investigates their theoretical potential efficiency and proposes two ultra-high efficiency plant configurations based on advanced intermediate-temperature SOFCs integrated with a steam turbine or gas turbine cycle. The SOFC works at atmospheric or pressurized conditions and the resulting power plant exceeds 78% LHV efficiency without CO2 capture (as discussed in part A of the work) and 70% LHV efficiency with substantial CO2 capture (part B). The power plants are simulated at the 100 MW scale with a complete set of realistic assumptions about fuel cell (FC) performance, plant components and auxiliaries, presenting detailed energy and material balances together with a second law analysis.

Solving The Longstanding Problem Of Low-Energy Nuclear Reactions At the Highest Microscopic Level - Final Report

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

Quaglioni, S.

2016-09-22

A 2011 DOE-NP Early Career Award (ECA) under Field Work Proposal (FWP) SCW1158 supported the project “Solving the Long-Standing Problem of Low-Energy Nuclear Reactions at the Highest Microscopic Level” in the five-year period from June 15, 2011 to June 14, 2016. This project, led by PI S. Quaglioni, aimed at developing a comprehensive and computationally efficient framework to arrive at a unified description of structural properties and reactions of light nuclei in terms of constituent protons and neutrons interacting through nucleon-nucleon (NN) and three-nucleon (3N) forces. Specifically, the project had three main goals: 1) arriving at the accurate predictions formore » fusion reactions that power stars and Earth-based fusion facilities; 2) realizing a comprehensive description of clustering and continuum effects in exotic nuclei, including light Borromean systems; and 3) achieving fundamental understanding of the role of the 3N force in nuclear reactions and nuclei at the drip line.« less

Estimation of the residual bromine concentration after disinfection of cooling water by statistical evaluation.

PubMed

Megalopoulos, Fivos A; Ochsenkuehn-Petropoulou, Maria T

2015-01-01

A statistical model based on multiple linear regression is developed, to estimate the bromine residual that can be expected after the bromination of cooling water. Make-up water sampled from a power plant in the Greek territory was used for the creation of the various cooling water matrices under investigation. The amount of bromine fed to the circuit, as well as other important operational parameters such as concentration at the cooling tower, temperature, organic load and contact time are taken as the independent variables. It is found that the highest contribution to the model's predictive ability comes from cooling water's organic load concentration, followed by the amount of bromine fed to the circuit, the water's mean temperature, the duration of the bromination period and finally its conductivity. Comparison of the model results with the experimental data confirms its ability to predict residual bromine given specific bromination conditions.

Indicators of hypertriglyceridemia from anthropometric measures based on data mining.

PubMed

Lee, Bum Ju; Kim, Jong Yeol

2015-02-01

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

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

PubMed

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

2018-01-15

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

First and second generation antipsychotics influence hippocampal gamma oscillations by interactions with 5-HT3 and D3 receptors

PubMed Central

Schulz, Steffen B; Heidmann, Karin E; Mike, Arpad; Klaft, Zin-Juan; Heinemann, Uwe; Gerevich, Zoltan

2012-01-01

BACKGROUND AND PURPOSE Disturbed cortical gamma band oscillations (30–80 Hz) have been observed in schizophrenia: positive symptoms of the disease correlate with an increase in gamma oscillation power, whereas negative symptoms are associated with a decrease. EXPERIMENTAL APPROACH Here we investigated the effects of first and second generation antipsychotics (FGAs and SGAs, respectively) on gamma oscillations. The FGAs haloperidol, flupenthixol, chlorpromazine, chlorprothixene and the SGAs clozapine, risperidone, ziprasidone, amisulpride were applied on gamma oscillations induced by acetylcholine and physostigmine in the CA3 region of rat hippocampal slices. KEY RESULTS Antipsychotics inhibited the power of gamma oscillations and increased the bandwidth of the gamma band. Haloperidol and clozapine had the highest inhibitory effects. To determine which receptor is responsible for the alterations in gamma oscillations, the effects of the antipsychotics were plotted against their pKi values for 19 receptors and analysed for correlation. Our results indicated that 5-HT3 receptors have an enhancing effect on gamma oscillations whereas dopamine D3 receptors inhibit them. To test this prediction, m-chlorophenylbiguanide, PD 128907 and CP 809101, selective agonists at 5-HT3, D3 and 5-HT2C receptors were applied and revealed that 5-HT3 receptors indeed enhanced the gamma power whereas D3 receptors reduced it. As predicted, 5-HT2C receptors had no effects on gamma oscillations. CONCLUSION AND IMPLICATIONS Our data suggest that antipsychotics alter hippocampal gamma oscillations by interacting with 5-HT3 and dopamine D3 receptors. Moreover, a correlation of receptor affinities with the biological effects can be used to predict targets for the pharmacological effects of multi-target drugs. PMID:22817643

Green Power Markets

EPA Pesticide Factsheets

The U.S. EPA's Green Power Partnership defines Green power is a subset of renewable energy and represents those renewable energy resources and technologies that provide the highest environmental benefit.

Forecasting Strategies for Predicting Peak Electric Load Days

NASA Astrophysics Data System (ADS)

Saxena, Harshit

Academic institutions spend thousands of dollars every month on their electric power consumption. Some of these institutions follow a demand charges pricing structure; here the amount a customer pays to the utility is decided based on the total energy consumed during the month, with an additional charge based on the highest average power load required by the customer over a moving window of time as decided by the utility. Therefore, it is crucial for these institutions to minimize the time periods where a high amount of electric load is demanded over a short duration of time. In order to reduce the peak loads and have more uniform energy consumption, it is imperative to predict when these peaks occur, so that appropriate mitigation strategies can be developed. The research work presented in this thesis has been conducted for Rochester Institute of Technology (RIT), where the demand charges are decided based on a 15 minute sliding window panned over the entire month. This case study makes use of different statistical and machine learning algorithms to develop a forecasting strategy for predicting the peak electric load days of the month. The proposed strategy was tested for a whole year starting May 2015 to April 2016 during which a total of 57 peak days were observed. The model predicted a total of 74 peak days during this period, 40 of these cases were true positives, hence achieving an accuracy level of 70 percent. The results obtained with the proposed forecasting strategy are promising and demonstrate an annual savings potential worth about $80,000 for a single submeter of RIT.

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

Analysis of High Power IGBT Short Circuit Failures

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

Pappas, G.

2005-02-11

The Next Linear Collider (NLC) accelerator proposal at SLAC requires a highly efficient and reliable, low cost, pulsed-power modulator to drive the klystrons. A solid-state induction modulator has been developed at SLAC to power the klystrons; this modulator uses commercial high voltage and high current Insulated Gate Bipolar Transistor (IGBT) modules. Testing of these IGBT modules under pulsed conditions was very successful; however, the IGBTs failed when tests were performed into a low inductance short circuit. The internal electrical connections of a commercial IGBT module have been analyzed to extract self and mutual partial inductances for the main current pathsmore » as well as for the gate structure. The IGBT module, together with the partial inductances, has been modeled using PSpice. Predictions for electrical paths that carry the highest current correlate with the sites of failed die under short circuit tests. A similar analysis has been carried out for a SLAC proposal for an IGBT module layout. This paper discusses the mathematical model of the IGBT module geometry and presents simulation results.« less

AGR-5/6/7 Irradiation Test Predictions using PARFUME

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

Skerjanc, William F.

PARFUME, (PARticle FUel ModEl) a fuel performance modeling code used for high temperature gas-cooled reactors (HTGRs), was used to model the Advanced Gas Reactor (AGR)-5/6/7 irradiation test using predicted physics and thermal hydraulics data. The AGR-5/6/7 test consists of the combined fifth, sixth, and seventh planned irradiations of the AGR Fuel Development and Qualification Program. The AGR-5/6/7 test train is a multi-capsule, instrumented experiment that is designed for irradiation in the 133.4-mm diameter north east flux trap (NEFT) position of Advanced Test Reactor (ATR). Each capsule contains compacts filled with uranium oxycarbide (UCO) unaltered fuel particles. This report documents themore » calculations performed to predict the failure probability of tristructural isotropic (TRISO)-coated fuel particles during the AGR-5/6/7 experiment. In addition, this report documents the calculated source term from the driver fuel. The calculations include modeling of the AGR-5/6/7 irradiation that is scheduled to occur from October 2017 to April 2021 over a total of 13 ATR cycles, including nine normal cycles and four Power Axial Locator Mechanism (PALM) cycle for a total between 500 – 550 effective full power days (EFPD). The irradiation conditions and material properties of the AGR-5/6/7 test predicted zero fuel particle failures in Capsules 1, 2, and 4. Fuel particle failures were predicted in Capsule 3 due to internal particle pressure. These failures were predicted in the highest temperature compacts. Capsule 5 fuel particle failures were due to inner pyrolytic carbon (IPyC) cracking causing localized stresses concentrations in the SiC layer. This capsule predicted the highest particle failures due to the lower irradiation temperature. In addition, shrinkage of the buffer and IPyC layer during irradiation resulted in formation of a buffer-IPyC gap. The two capsules at the two ends of the test train, Capsules 1 and 5 experienced the smallest buffer-IPyC gap formation due to the lower irradiation fluences and temperatures. Capsule 3 experienced the largest buffer-IPyC gap formation of just under 24 µm. The release fraction of fission products Ag, Cs, and Sr silver (Ag), cesium (Cs), and strontium (Sr) vary depending on capsule location and irradiation temperature. The maximum release fraction of Ag occurs in Capsule 3, reaching up to 84.8% for the TRISO fuel particles. The release fraction of the other two fission products, Cs and Sr are much smaller and, in most cases, less than 1%. The notable exception is again in Capsule 3, where the release fraction for Cs and Sr reach up to 9.7% and 19.1%, respectively.« less

Comparison of the biometric formulas used for applanation A-scan ultrasound biometry.

PubMed

Özcura, Fatih; Aktaş, Serdar; Sağdık, Hacı Murat; Tetikoğlu, Mehmet

2016-10-01

The purpose of the study was to compare the accuracy of various biometric formulas for predicting postoperative refraction determined using applanation A-scan ultrasound. This retrospective comparative study included 485 eyes that underwent uneventful phacoemulsification with intraocular lens (IOL) implantation. Applanation A-scan ultrasound biometry and postoperative manifest refraction were obtained in all eyes. Biometric data were entered into each of the five IOL power calculation formulas: SRK-II, SRK/T, Holladay I, Hoffer Q, and Binkhorst II. All eyes were divided into three groups according to axial length: short (≤22.0 mm), average (22.0-25.0 mm), and long (≥25.0 mm) eyes. The postoperative spherical equivalent was calculated and compared with the predicted refractive error using each biometric formula. The results showed that all formulas had significantly lower mean absolute error (MAE) in comparison with Binkhorst II formula (P < 0.01). The lowest MAE was obtained with the SRK-II for average (0.49 ± 0.40 D) and short (0.67 ± 0.54 D) eyes and the SRK/T for long (0.61 ± 0.50 D) eyes. The highest postoperative hyperopic shift was seen with the SRK-II for average (46.8 %), short (28.1 %), and long (48.4 %) eyes. The highest postoperative myopic shift was seen with the Holladay I for average (66.4 %) and long (71.0 %) eyes and the SRK/T for short eyes (80.6 %). In conclusion, the SRK-II formula produced the lowest MAE in average and short eyes and the SRK/T formula produced the lowest MAE in long eyes. The SRK-II has the highest postoperative hyperopic shift in all eyes. The highest postoperative myopic shift is with the Holladay I for average and long eyes and SRK/T for short eyes.

What Is Green Power?

EPA Pesticide Factsheets

The U.S. EPA's Green Power Partnership defines Green power is a subset of renewable energy and represents those renewable energy resources and technologies that provide the highest environmental benefit.

Suitability of the HAM-Nat test and TMS module "basic medical-scientific understanding" for medical school selection

PubMed Central

Hissbach, Johanna; Feddersen, Lena; Sehner, Susanne; Hampe, Wolfgang

2012-01-01

Aims: Tests with natural-scientific content are predictive of the success in the first semesters of medical studies. Some universities in the German speaking countries use the ‘Test for medical studies’ (TMS) for student selection. One of its test modules, namely “medical and scientific comprehension”, measures the ability for deductive reasoning. In contrast, the Hamburg Assessment Test for Medicine, Natural Sciences (HAM-Nat) evaluates knowledge in natural sciences. In this study the predictive power of the HAM-Nat test will be compared to that of the NatDenk test, which is similar to the TMS module “medical and scientific comprehension” in content and structure. Methods: 162 medical school beginners volunteered to complete either the HAM-Nat (N=77) or the NatDenk test (N=85) in 2007. Until spring 2011, 84.2% of these successfully completed the first part of the medical state examination in Hamburg. Via different logistic regression models we tested the predictive power of high school grade point average (GPA or “Abiturnote”) and the test results (HAM-Nat and NatDenk) with regard to the study success criterion “first part of the medical state examination passed successfully up to the end of the 7th semester” (Success7Sem). The Odds Ratios (OR) for study success are reported. Results: For both test groups a significant correlation existed between test results and study success (HAM-Nat: OR=2.07; NatDenk: OR=2.58). If both admission criteria are estimated in one model, the main effects (GPA: OR=2.45; test: OR=2.32) and their interaction effect (OR=1.80) are significant in the HAM-Nat test group, whereas in the NatDenk test group only the test result (OR=2.21) significantly contributes to the variance explained. Conclusions: On their own both HAM-Nat and NatDenk have predictive power for study success, but only the HAM-Nat explains additional variance if combined with GPA. The selection according to HAM-Nat and GPA has under the current circumstances of medical school selection (many good applicants and only a limited number of available spaces) the highest predictive power of all models. PMID:23255967

Overview of Alcator C-Mod Research

NASA Astrophysics Data System (ADS)

White, A. E.

2017-10-01

Alcator C-Mod, a compact (R =0.68m, a =0.21m), high magnetic field, Bt <= 8T, tokamak accesses a variety of naturally ELM-suppressed high confinement regimes that feature extreme power density into the divertor, q|| <= 3 GW/m2, with SOL heat flux widths λq <0.5mm, exceeding conditions expected in ITER and approaching those foreseen in power plants. The unique parameter range provides much of the physics basis of a high-field, compact tokamak reactor. Research spans the topics of core transport and turbulence, RF heating and current drive, pedestal physics, scrape-off layer, divertor and plasma wall interactions. In the last experimental campaign, Super H-mode was explored and featured the highest pedestal pressures ever recorded, pped 90 kPa (90% of ITER target), consistent with EPED predictions. Optimization of naturally ELM-suppressed EDA H-modes accessed the highest volume averaged pressures ever achieved (〈p〉>2 atm), with pped 60 kPa. The SOL heat flux width has been measured at Bpol = 1.25T, confirming the Eich scaling over a broader poloidal field range than before. Multi-channel transport studies focus on the relationship between momentum transport and heat transport with perturbative experiments and new multi-scale gyrokinetic simulation validation techniques were developed. U.S. Department of Energy Grant No. DE-FC02-99ER54512.

High-power linearly polarized diode-side-pumped a-cut Nd:GdVO4 rod laser

NASA Astrophysics Data System (ADS)

Li, Xiaowen; Qian, Jianqiang; Zhang, Baitao

2017-03-01

An efficiently high-power diode-side-pumped Nd:GdVO4 rod laser system was successfully demonstrated, operating in continuous wave (CW) and acousto-optically (AO) Q-switched regime. With a 65 mm-long a-cut Nd:GdVO4 crystal, a maximum linearly polarized CW output power of 60 W at 1063.2 nm was obtained under an absorbed pump power of 180 W, corresponding to a slope efficiency of 50.6%. The output laser beam was linearly polarized with a degree of polarization of 98%. In AO Q-switched operation, the highest output power, minimum pulse width, and highest peak power were achieved to be 42 W, 36 ns, and 58 kW at the pulse repetition frequency of 20 kHz.

Test anxiety and academic performance in chiropractic students.

PubMed

Zhang, Niu; Henderson, Charles N R

2014-01-01

Objective : We assessed the level of students' test anxiety, and the relationship between test anxiety and academic performance. Methods : We recruited 166 third-quarter students. The Test Anxiety Inventory (TAI) was administered to all participants. Total scores from written examinations and objective structured clinical examinations (OSCEs) were used as response variables. Results : Multiple regression analysis shows that there was a modest, but statistically significant negative correlation between TAI scores and written exam scores, but not OSCE scores. Worry and emotionality were the best predictive models for written exam scores. Mean total anxiety and emotionality scores for females were significantly higher than those for males, but not worry scores. Conclusion : Moderate-to-high test anxiety was observed in 85% of the chiropractic students examined. However, total test anxiety, as measured by the TAI score, was a very weak predictive model for written exam performance. Multiple regression analysis demonstrated that replacing total anxiety (TAI) with worry and emotionality (TAI subscales) produces a much more effective predictive model of written exam performance. Sex, age, highest current academic degree, and ethnicity contributed little additional predictive power in either regression model. Moreover, TAI scores were not found to be statistically significant predictors of physical exam skill performance, as measured by OSCEs.

Frailty screening methods for predicting outcome of a comprehensive geriatric assessment in elderly patients with cancer: a systematic review.

PubMed

Hamaker, Marije E; Jonker, Judith M; de Rooij, Sophia E; Vos, Alinda G; Smorenburg, Carolien H; van Munster, Barbara C

2012-10-01

Comprehensive geriatric assessment (CGA) is done to detect vulnerability in elderly patients with cancer so that treatment can be adjusted accordingly; however, this process is time-consuming and pre-screening is often used to identify fit patients who are able to receive standard treatment versus those in whom a full CGA should be done. We aimed to assess which of the frailty screening methods available show the best sensitivity and specificity for predicting the presence of impairments on CGA in elderly patients with cancer. We did a systematic search of Medline and Embase, and a hand-search of conference abstracts, for studies on the association between frailty screening outcome and results of CGA in elderly patients with cancer. Our search identified 4440 reports, of which 22 publications from 14 studies, were included in this Review. Seven different frailty screening methods were assessed. The median sensitivity and specificity of each screening method for predicting frailty on CGA were as follows: Vulnerable Elders Survey-13 (VES-13), 68% and 78%; Geriatric 8 (G8), 87% and 61%; Triage Risk Screening Tool (TRST 1+; patient considered frail if one or more impairments present), 92% and 47%, Groningen Frailty Index (GFI) 57% and 86%, Fried frailty criteria 31% and 91%, Barber 59% and 79%, and abbreviated CGA (aCGA) 51% and 97%. However, even in case of the highest sensitivity, the negative predictive value was only roughly 60%. G8 and TRST 1+ had the highest sensitivity for frailty, but both had poor specificity and negative predictive value. These findings suggest that, for now, it might be beneficial for all elderly patients with cancer to receive a complete geriatric assessment, since available frailty screening methods have insufficient discriminative power to select patients for further assessment. Copyright © 2012 Elsevier Ltd. All rights reserved.

High-Power Growth-Robust InGaAs/InAlAs Terahertz Quantum Cascade Lasers

PubMed Central

2017-01-01

We report on high-power terahertz quantum cascade lasers based on low effective electron mass InGaAs/InAlAs semiconductor heterostructures with excellent reproducibility. Growth-related asymmetries in the form of interface roughness and dopant migration play a crucial role in this material system. These bias polarity dependent phenomena are studied using a nominally symmetric active region resulting in a preferential electron transport in the growth direction. A structure based on a three-well optical phonon depletion scheme was optimized for this bias direction. Depending on the sheet doping density, the performance of this structure shows a trade-off between high maximum operating temperature and high output power. While the highest operating temperature of 155 K is observed for a moderate sheet doping density of 2 × 1010 cm–2, the highest peak output power of 151 mW is found for 7.3 × 1010 cm–2. Furthermore, by abutting a hyperhemispherical GaAs lens to a device with the highest doping level a record output power of 587 mW is achieved for double-metal waveguide structures. PMID:28470028

High-Power Growth-Robust InGaAs/InAlAs Terahertz Quantum Cascade Lasers.

PubMed

Deutsch, Christoph; Kainz, Martin Alexander; Krall, Michael; Brandstetter, Martin; Bachmann, Dominic; Schönhuber, Sebastian; Detz, Hermann; Zederbauer, Tobias; MacFarland, Donald; Andrews, Aaron Maxwell; Schrenk, Werner; Beck, Mattias; Ohtani, Keita; Faist, Jérôme; Strasser, Gottfried; Unterrainer, Karl

2017-04-19

We report on high-power terahertz quantum cascade lasers based on low effective electron mass InGaAs/InAlAs semiconductor heterostructures with excellent reproducibility. Growth-related asymmetries in the form of interface roughness and dopant migration play a crucial role in this material system. These bias polarity dependent phenomena are studied using a nominally symmetric active region resulting in a preferential electron transport in the growth direction. A structure based on a three-well optical phonon depletion scheme was optimized for this bias direction. Depending on the sheet doping density, the performance of this structure shows a trade-off between high maximum operating temperature and high output power. While the highest operating temperature of 155 K is observed for a moderate sheet doping density of 2 × 10 10 cm -2 , the highest peak output power of 151 mW is found for 7.3 × 10 10 cm -2 . Furthermore, by abutting a hyperhemispherical GaAs lens to a device with the highest doping level a record output power of 587 mW is achieved for double-metal waveguide structures.

High-quality two-nucleon potentials up to fifth order of the chiral expansion

NASA Astrophysics Data System (ADS)

Entem, D. R.; Machleidt, R.; Nosyk, Y.

2017-08-01

We present NN potentials through five orders of chiral effective field theory ranging from leading order (LO) to next-to-next-to-next-to-next-to-leading order (N4LO ). The construction may be perceived as consistent in the sense that the same power counting scheme as well as the same cutoff procedures are applied in all orders. Moreover, the long-range parts of these potentials are fixed by the very accurate π N low-energy constants (LECs) as determined in the Roy-Steiner equations analysis by Hoferichter, Ruiz de Elvira, and coworkers. In fact, the uncertainties of these LECs are so small that a variation within the errors leads to effects that are essentially negligible, reducing the error budget of predictions considerably. The NN potentials are fit to the world NN data below the pion-production threshold of the year 2016. The potential of the highest order (N4LO ) reproduces the world NN data with the outstanding χ2/datum of 1.15, which is the highest precision ever accomplished for any chiral NN potential to date. The NN potentials presented may serve as a solid basis for systematic ab initio calculations of nuclear structure and reactions that allow for a comprehensive error analysis. In particular, the consistent order by order development of the potentials will make possible a reliable determination of the truncation error at each order. Our family of potentials is nonlocal and, generally, of soft character. This feature is reflected in the fact that the predictions for the triton binding energy (from two-body forces only) converges to about 8.1 MeV at the highest orders. This leaves room for three-nucleon-force contributions of moderate size.

Consistent, high-quality two-nucleon potentials up to fifth order of the chiral expansion

NASA Astrophysics Data System (ADS)

Machleidt, R.

2018-02-01

We present N N potentials through five orders of chiral effective field theory ranging from leading order (LO) to next-to-next-to-next-to-next-to-leading order (N4LO). The construction may be perceived as consistent in the sense that the same power counting scheme as well as the same cutoff procedures are applied in all orders. Moreover, the long-range parts of these potentials are fixed by the very accurate πN low-energy constants (LECs) as determined in the Roy-Steiner equations analysis by Hoferichter, Ruiz de Elvira and coworkers. In fact, the uncertainties of these LECs are so small that a variation within the errors leads to effects that are essentially negligible, reducing the error budget of predictions considerably. The N N potentials are fit to the world N N data below pion-production threshold of the year of 2016. The potential of the highest order (N4LO) reproduces the world N N data with the outstanding χ 2/datum of 1.15, which is the highest precision ever accomplished for any chiral N N potential to date. The N N potentials presented may serve as a solid basis for systematic ab initio calculations of nuclear structure and reactions that allow for a comprehensive error analysis. In particular, the consistent order by order development of the potentials will make possible a reliable determination of the truncation error at each order. Our family of potentials is non-local and, generally, of soft character. This feature is reflected in the fact that the predictions for the triton binding energy (from two-body forces only) converges to about 8.1 MeV at the highest orders. This leaves room for three-nucleon-force contributions of moderate size.

A lymphocyte spatial distribution graph-based method for automated classification of recurrence risk on lung cancer images

NASA Astrophysics Data System (ADS)

Garciá-Arteaga, Juan D.; Corredor, Germán.; Wang, Xiangxue; Velcheti, Vamsidhar; Madabhushi, Anant; Romero, Eduardo

2017-11-01

Tumor-infiltrating lymphocytes occurs when various classes of white blood cells migrate from the blood stream towards the tumor, infiltrating it. The presence of TIL is predictive of the response of the patient to therapy. In this paper, we show how the automatic detection of lymphocytes in digital H and E histopathological images and the quantitative evaluation of the global lymphocyte configuration, evaluated through global features extracted from non-parametric graphs, constructed from the lymphocytes' detected positions, can be correlated to the patient's outcome in early-stage non-small cell lung cancer (NSCLC). The method was assessed on a tissue microarray cohort composed of 63 NSCLC cases. From the evaluated graphs, minimum spanning trees and K-nn showed the highest predictive ability, yielding F1 Scores of 0.75 and 0.72 and accuracies of 0.67 and 0.69, respectively. The predictive power of the proposed methodology indicates that graphs may be used to develop objective measures of the infiltration grade of tumors, which can, in turn, be used by pathologists to improve the decision making and treatment planning processes.

Ion Engine Plume Interaction Calculations for Prototypical Prometheus 1

NASA Technical Reports Server (NTRS)

Mandell, Myron J.; Kuharski, Robert A.; Gardner, Barbara M.; Katz, Ira; Randolph, Tom; Dougherty, Ryan; Ferguson, Dale C.

2005-01-01

Prometheus 1 is a conceptual mission to demonstrate the use of atomic energy for distant space missions. The hypothetical spacecraft design considered in this paper calls for multiple ion thrusters, each with considerably higher beam energy and beam current than have previously flown in space. The engineering challenges posed by such powerful thrusters relate not only to the thrusters themselves, but also to designing the spacecraft to avoid potentially deleterious effects of the thruster plumes. Accommodation of these thrusters requires good prediction of the highest angle portions of the main beam, as well as knowledge of clastically scattered and charge exchange ions, predictions for grid erosion and contamination of surfaces by eroded grid material, and effects of the plasma plume on radio transmissions. Nonlinear interactions of multiple thrusters are also of concern. In this paper we describe two- and three-dimensional calculations for plume structure and effects of conceptual Prometheus 1 ion engines. Many of the techniques used have been validated by application to ground test data for the NSTAR and NEXT ion engines. Predictions for plume structure and possible sputtering and contamination effects will be presented.

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

PubMed

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

2015-01-01

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

160 W 800 fs Yb:YAG single crystal fiber amplifier without CPA.

PubMed

Markovic, Vesna; Rohrbacher, Andreas; Hofmann, Peter; Pallmann, Wolfgang; Pierrot, Simonette; Resan, Bojan

2015-10-05

We demonstrate a compact and simple two-stage Yb:YAG single crystal fiber amplifier which delivers 160 W average power, 800 fs pulses without chirped pulse amplification. This is the highest average power of femtosecond laser based on SCF. Additionally, we demonstrate the highest small signal gain of 32.5 dB from the SCF in the first stage and the highest extraction efficiency of 42% in the second stage. The excellent performance of the second stage was obtained using the bidirectional pumping scheme, which is applied to SCF for the first time.

The natural logarithm transforms the abbreviated injury scale and improves accuracy scoring.

PubMed

Wang, Xu; Gu, Xiaoming; Zhang, Zhiliang; Qiu, Fang; Zhang, Keming

2012-11-01

The Injury Severity Score (ISS) and the New Injury Severity Score (NISS) are widely used for anatomic severity assessments, but they do not display a linear relation to mortality. The mortality rates are significantly different between pairs of the Abbreviated Injury Scale (AIS) triplets that generate the same ISS/NISS total. The Logarithm Injury Severity Score (LISS) is defined as a change in AIS values by raising each AIS severity score (1-6) by taking the natural logarithm to a power of 5.53 multiplied by 1.7987 and then adding the three most severe injuries (i.e. highest AIS), regardless of body region. LISS values were calculated for every patient in three large independent data sets: 3,784, 4,436, and 4,018 patients treated over a six-year period at Class A tertiary comprehensive hospitals in China. The power of LISS to predict morality was then compared with previously calculated NISS values for the same patients in each of the three data sets. We found that LISS is more predictive of survival as well (Hangzhou: receiver operating characteristic (ROC): NISS=0.931, LISS=0.949, p=0.006; Similarly, Zhejiang and Shenyang: ROC NISS vs. LISS, p<0.05). Moreover, LISS provides a better fit throughout its entire range of predicting (Hosmer-Lemeshow statistic for Hangzhou NISS=15.76, p=0.027; LISS=13.79, p=0.055; Similarly, for Zhejiang and Shenyang). LISS should be used as the standard summary measure of human trauma.

An Assessment of Current Fan Noise Prediction Capability

NASA Technical Reports Server (NTRS)

Envia, Edmane; Woodward, Richard P.; Elliott, David M.; Fite, E. Brian; Hughes, Christopher E.; Podboy, Gary G.; Sutliff, Daniel L.

2008-01-01

In this paper, the results of an extensive assessment exercise carried out to establish the current state of the art for predicting fan noise at NASA are presented. Representative codes in the empirical, analytical, and computational categories were exercised and assessed against a set of benchmark acoustic data obtained from wind tunnel tests of three model scale fans. The chosen codes were ANOPP, representing an empirical capability, RSI, representing an analytical capability, and LINFLUX, representing a computational aeroacoustics capability. The selected benchmark fans cover a wide range of fan pressure ratios and fan tip speeds, and are representative of modern turbofan engine designs. The assessment results indicate that the ANOPP code can predict fan noise spectrum to within 4 dB of the measurement uncertainty band on a third-octave basis for the low and moderate tip speed fans except at extreme aft emission angles. The RSI code can predict fan broadband noise spectrum to within 1.5 dB of experimental uncertainty band provided the rotor-only contribution is taken into account. The LINFLUX code can predict interaction tone power levels to within experimental uncertainties at low and moderate fan tip speeds, but could deviate by as much as 6.5 dB outside the experimental uncertainty band at the highest tip speeds in some case.

Predicting Dishonorable Discharge Among Military Recruits

DTIC Science & Technology

2013-03-01

train its members to give them the highest chance possible at a successful career. Jacob Rodriquez’s study, “Predicting the Military Career Success of...society as a whole. To improve the enlistment process and attract recruits with the highest probability of future career success , based on our...00036840801964450 Rodriguez, John J. (2008, January 1). Predicting the career success of air force academy cadets (Paper AAI3309209). ETD collection for

Tidal Energy Resource Assessment for McMurdo Station, Antarctica

DTIC Science & Technology

2016-12-01

highest power coefficient possible, only to provide a high- fidelity data set for a simple geometry turbine model at reasonably high blade chord Reynolds...highest power coefficient possible, only to provide a high-fidelity data set for a simple geometry turbine model at reasonably high blade chord...Reynolds numbers. Tip speed ratio, , is defined as = where is the anglular velocity of the blade and is the

Combined application of mixture experimental design and artificial neural networks in the solid dispersion development.

PubMed

Medarević, Djordje P; Kleinebudde, Peter; Djuriš, Jelena; Djurić, Zorica; Ibrić, Svetlana

2016-01-01

This study for the first time demonstrates combined application of mixture experimental design and artificial neural networks (ANNs) in the solid dispersions (SDs) development. Ternary carbamazepine-Soluplus®-poloxamer 188 SDs were prepared by solvent casting method to improve carbamazepine dissolution rate. The influence of the composition of prepared SDs on carbamazepine dissolution rate was evaluated using d-optimal mixture experimental design and multilayer perceptron ANNs. Physicochemical characterization proved the presence of the most stable carbamazepine polymorph III within the SD matrix. Ternary carbamazepine-Soluplus®-poloxamer 188 SDs significantly improved carbamazepine dissolution rate compared to pure drug. Models developed by ANNs and mixture experimental design well described the relationship between proportions of SD components and percentage of carbamazepine released after 10 (Q10) and 20 (Q20) min, wherein ANN model exhibit better predictability on test data set. Proportions of carbamazepine and poloxamer 188 exhibited the highest influence on carbamazepine release rate. The highest carbamazepine release rate was observed for SDs with the lowest proportions of carbamazepine and the highest proportions of poloxamer 188. ANNs and mixture experimental design can be used as powerful data modeling tools in the systematic development of SDs. Taking into account advantages and disadvantages of both techniques, their combined application should be encouraged.

Alchemical and structural distribution based representation for universal quantum machine learning

NASA Astrophysics Data System (ADS)

Faber, Felix A.; Christensen, Anders S.; Huang, Bing; von Lilienfeld, O. Anatole

2018-06-01

We introduce a representation of any atom in any chemical environment for the automatized generation of universal kernel ridge regression-based quantum machine learning (QML) models of electronic properties, trained throughout chemical compound space. The representation is based on Gaussian distribution functions, scaled by power laws and explicitly accounting for structural as well as elemental degrees of freedom. The elemental components help us to lower the QML model's learning curve, and, through interpolation across the periodic table, even enable "alchemical extrapolation" to covalent bonding between elements not part of training. This point is demonstrated for the prediction of covalent binding in single, double, and triple bonds among main-group elements as well as for atomization energies in organic molecules. We present numerical evidence that resulting QML energy models, after training on a few thousand random training instances, reach chemical accuracy for out-of-sample compounds. Compound datasets studied include thousands of structurally and compositionally diverse organic molecules, non-covalently bonded protein side-chains, (H2O)40-clusters, and crystalline solids. Learning curves for QML models also indicate competitive predictive power for various other electronic ground state properties of organic molecules, calculated with hybrid density functional theory, including polarizability, heat-capacity, HOMO-LUMO eigenvalues and gap, zero point vibrational energy, dipole moment, and highest vibrational fundamental frequency.

Lactate Parameters Predict Clinical Outcomes in Patients with Nonvariceal Upper Gastrointestinal Bleeding.

PubMed

Lee, Seung Hoon; Min, Yang Won; Bae, Joohwan; Lee, Hyuk; Min, Byung Hoon; Lee, Jun Haeng; Rhee, Poong Lyul; Kim, Jae J

2017-11-01

The predictive role of lactate in patients with nonvariceal upper gastrointestinal bleeding (NVUGIB) has been suggested. This study evaluated several lactate parameters in terms of predicting outcomes of bleeding patients and sought to establish a new scoring model by combining lactate parameters and the AIMS65 score. A total of 114 patients with NVUGIB who underwent serum lactate level testing at least twice and endoscopic hemostasis within 24 hours after admission were retrospectively analyzed. The associations between five lactate parameters and clinical outcomes were evaluated and the predictive power of lactate parameter combined AIMS65s (L-AIMS65s) and AIMS56 scoring was compared. The most common cause of bleeding was gastric ulcer (48.2%). Lactate clearance rate (LCR) was associated with 30-day rebleeding (odds ratio [OR], 0.931; 95% confidence interval [CI], 0.872-0.994; P = 0.033). Initial lactate (OR, 1.313; 95% CI, 1.050-1.643; P = 0.017), maximal lactate (OR, 1.277; 95% CI, 1.037-1.573; P = 0.021), and average lactate (OR, 1.535; 95% CI, 1.137-2.072; P = 0.005) levels were associated with 30-day mortality. Initial lactate (OR, 1.213; 95% CI, 1.027-1.432; P = 0.023), maximal lactate (OR, 1.271; 95% CI, 1.074-1.504; P = 0.005), and average lactate (OR, 1.501; 95% CI, 1.150-1.959; P = 0.003) levels were associated with admission over 7 days. Although L-AIMS65s showed the highest area under the curve for prediction of each outcome, differences between L-AIMS65s and AIMS65 did not reach statistical significance. In conclusion, lactate parameters have a prognostic role in patients with NVUGIB. However, they do not increase the predictive power of AIMS65 when combined. © 2017 The Korean Academy of Medical Sciences.

14 CFR 29.1049 - Hovering cooling test procedures.

Code of Federal Regulations, 2010 CFR

2010-01-01

... minutes after the occurrence of the highest temperature recorded; and (b) With maximum continuous power... five minutes after the occurrence of the highest temperature recorded. Induction System ...

14 CFR 29.1049 - Hovering cooling test procedures.

Code of Federal Regulations, 2014 CFR

2014-01-01

... minutes after the occurrence of the highest temperature recorded; and (b) With maximum continuous power... five minutes after the occurrence of the highest temperature recorded. Induction System ...

14 CFR 29.1049 - Hovering cooling test procedures.

Code of Federal Regulations, 2012 CFR

2012-01-01

... minutes after the occurrence of the highest temperature recorded; and (b) With maximum continuous power... five minutes after the occurrence of the highest temperature recorded. Induction System ...

14 CFR 29.1049 - Hovering cooling test procedures.

Code of Federal Regulations, 2011 CFR

2011-01-01

... minutes after the occurrence of the highest temperature recorded; and (b) With maximum continuous power... five minutes after the occurrence of the highest temperature recorded. Induction System ...

14 CFR 29.1049 - Hovering cooling test procedures.

Code of Federal Regulations, 2013 CFR

2013-01-01

... minutes after the occurrence of the highest temperature recorded; and (b) With maximum continuous power... five minutes after the occurrence of the highest temperature recorded. Induction System ...

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.

Resonantly cladding-pumped Yb-free Er-doped LMA fiber laser with record high power and efficiency.

PubMed

Zhang, Jun; Fromzel, Viktor; Dubinskii, Mark

2011-03-14

We report the results of our power scaling experiments with resonantly cladding-pumped Er-doped eye-safe large mode area (LMA) fiber laser. While using commercial off-the-shelf LMA fiber we achieved over 88 W of continuous-wave (CW) single transverse mode power at ~1590 nm while pumping at 1532.5 nm. Maximum observed optical-to-optical efficiency was 69%. This result presents, to the best of our knowledge, the highest power reported from resonantly-pumped Yb-free Er-doped LMA fiber laser, as well as the highest efficiency ever reported for any cladding-pumped Er-doped laser, either Yb-co-doped or Yb-free.

Health and air quality benefits of policies to reduce coal-fired power plant emissions: a case study in North Carolina.

PubMed

Li, Ya-Ru; Gibson, Jacqueline MacDonald

2014-09-02

We analyzed sulfur dioxide (SO2) emissions and fine particulate sulfate (PM2.5 sulfate) concentrations in the southeastern United States during 2002-2012, in order to evaluate the health impacts in North Carolina (NC) of the NC Clean Smokestacks Act of 2002. This state law required progressive reductions (beyond those mandated by federal rules) in pollutant emissions from NC's coal-fired power plants. Although coal-fired power plants remain NC's leading SO2 source, a trend analysis shows significant declines in SO2 emissions (-20.3%/year) and PM2.5 sulfate concentrations (-8.7%/year) since passage of the act. Emissions reductions were significantly greater in NC than in neighboring states, and emissions and PM2.5 sulfate concentration reductions were highest in NC's piedmont region, where 9 of the state's 14 major coal-fired power plants are located. Our risk model estimates that these air quality improvements decreased the risk of premature death attributable to PM2.5 sulfate in NC by about 63%, resulting in an estimated 1700 (95% CI: 1500, 1800) deaths prevented in 2012. These findings lend support to recent studies predicting that implementing the proposed federal Cross-State Air Pollution Rule (recently upheld by the U.S. Supreme Court) could substantially decrease U.S. premature deaths attributable to coal-fired power plant emissions.

Testing Planetary Volcanism Models with Multi-Wavelength Near Infrared Observations of Kilauea Flows and Fountains

NASA Astrophysics Data System (ADS)

Howell, Robert R.; Radebaugh, Jani; M. C Lopes, Rosaly; Kerber, Laura; Solomonidou, Anezina; Watkins, Bryn

2017-10-01

Using remote sensing of planetary volcanism on objects such as Io to determine eruption conditions is challenging because the emitting region is typically not resolved and because exposed lava cools so quickly. A model of the cooling rate and eruption mechanism is typically used to predict the amount of surface area at different temperatures, then that areal distribution is convolved with a Planck blackbody emission curve, and the predicted spectra is compared with observation. Often the broad nature of the Planck curve makes interpretation non-unique. However different eruption mechanisms (for example cooling fire fountain droplets vs. cooling flows) have very different area vs. temperature distributions which can often be characterized by simple power laws. Furthermore different composition magmas have significantly different upper limit cutoff temperatures. In order to test these models in August 2016 and May 2017 we obtained spatially resolved observations of spreading Kilauea pahoehoe flows and fire fountains using a three-wavelength near-infrared prototype camera system. We have measured the area vs. temperature distribution for the flows and find that over a relatively broad temperature range the distribution does follow a power law matching the theoretical predictions. As one approaches the solidus temperature the observed area drops below the simple model predictions by an amount that seems to vary inversely with the vigor of the spreading rate. At these highest temperatures the simple models are probably inadequate. It appears necessary to model the visco-elastic stretching of the very thin crust which covers even the most recently formed surfaces. That deviation between observations and the simple models may be particularly important when using such remote sensing observations to determine magma eruption temperatures.

Relationship of physical fitness test results and hockey playing potential in elite-level ice hockey players.

PubMed

Burr, Jaime F; Jamnik, Roni K; Baker, Joseph; Macpherson, Alison; Gledhill, Norman; McGuire, E J

2008-09-01

The primary purpose of this study was to determine the fitness variables with the highest capability for predicting hockey playing potential at the elite level as determined by entry draft selection order. We also examined the differences associated with the predictive abilities of the test components among playing positions. The secondary purpose of this study was to update the physiological profile of contemporary hockey players including positional differences. Fitness test results conducted by our laboratory at the National Hockey League Entry Draft combine were compared with draft selection order on a total of 853 players. Regression models revealed peak anaerobic power output to be important for higher draft round selection in all positions; however, the degree of importance of this measurement varied with playing position. The body index, which is a composite score of height, lean mass, and muscular development, was similarly important in all models, with differing influence by position. Removal of the goalies' data increased predictive capacity, suggesting that talent identification using physical fitness testing of this sort may be more appropriate for skating players. Standing long jump was identified as a significant predictor variable for forwards and defense and could be a useful surrogate for assessing overall hockey potential. Significant differences exist between the physiological profiles of current players based on playing position. There are also positional differences in the relative importance of anthropometric and fitness measures of off-ice hockey tests in relation to draft order. Physical fitness measures and anthropometric data are valuable in helping predict hockey playing potential. Emphasis on anthropometry should be used when comparing elite-level forwards, whereas peak anaerobic power and fatigue rate are more useful for differentiating between defense.

Aging analysis of high performance FinFET flip-flop under Dynamic NBTI simulation configuration

NASA Astrophysics Data System (ADS)

Zainudin, M. F.; Hussin, H.; Halim, A. K.; Karim, J.

2018-03-01

A mechanism known as Negative-bias Temperature Instability (NBTI) degrades a main electrical parameters of a circuit especially in terms of performance. So far, the circuit design available at present are only focussed on high performance circuit without considering the circuit reliability and robustness. In this paper, the main circuit performances of high performance FinFET flip-flop such as delay time, and power were studied with the presence of the NBTI degradation. The aging analysis was verified using a 16nm High Performance Predictive Technology Model (PTM) based on different commands available at Synopsys HSPICE. The results shown that the circuit under the longer dynamic NBTI simulation produces the highest impact in the increasing of gate delay and decrease in the average power reduction from a fresh simulation until the aged stress time under a nominal condition. In addition, the circuit performance under a varied stress condition such as temperature and negative stress gate bias were also studied.

Heat profiling of phacoemulsification tip using a thermal scanning camera.

PubMed

Ngo, Wei Kiong; Lim, Louis W; Tan, Colin S H; Heng, Wee Jin

2013-12-01

An experimental study to measure the heat profile of the phacoemulsification (phaco) tip using standard continuous phaco and hyperpulse phaco with and without waveform power modulation in the Millennium Microsurgical System with Custom Control Software (CCS). The phaco tip was imaged in air using a thermal camera. The highest temperature was measured 15 s after application of phaco power. Continuous, hyperpulse and waveform power modulations of the Millennium Microsurgical System were used with different power settings (20, 50 and 100 %) and duty cycles (40, 60 and 90 %), with the irrigation turned on and off. Using continuous phaco with the irrigation on, the phaco tip temperature remains <28.0 °C. With irrigation off, the temperature is higher compared to irrigation on but still remains <45.0 °C. Comparing the temperatures for all three power modulations when irrigation is on, at each phaco power and duty cycle setting, the temperature of the phaco tip is highest with continuous phaco, followed by hyperpulse with rise time 1, then hyperpulse with rise time 2. When irrigation is off, the highest temperatures are recorded using the hyperpulse with rise time 2, followed by continuous phaco, then hyperpulse with rise time 1. Hyperpulse and waveform modulations reduce heat generation compared to the continuous mode when irrigation is turned on. Lower duty cycles and lower ultrasound power produce less heat at the phaco tip.

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

PubMed

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

2017-04-01

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

Distribution models for koalas in South Australia using citizen science-collected data

PubMed Central

Sequeira, Ana M M; Roetman, Philip E J; Daniels, Christopher B; Baker, Andrew K; Bradshaw, Corey J A

2014-01-01

The koala (Phascolarctos cinereus) occurs in the eucalypt forests of eastern and southern Australia and is currently threatened by habitat fragmentation, climate change, sexually transmitted diseases, and low genetic variability throughout most of its range. Using data collected during the Great Koala Count (a 1-day citizen science project in the state of South Australia), we developed generalized linear mixed-effects models to predict habitat suitability across South Australia accounting for potential errors associated with the dataset. We derived spatial environmental predictors for vegetation (based on dominant species of Eucalyptus or other vegetation), topographic water features, rain, elevation, and temperature range. We also included predictors accounting for human disturbance based on transport infrastructure (sealed and unsealed roads). We generated random pseudo-absences to account for the high prevalence bias typical of citizen-collected data. We accounted for biased sampling effort along sealed and unsealed roads by including an offset for distance to transport infrastructures. The model with the highest statistical support (wAICc ∼ 1) included all variables except rain, which was highly correlated with elevation. The same model also explained the highest deviance (61.6%), resulted in high R2(m) (76.4) and R2(c) (81.0), and had a good performance according to Cohen's κ (0.46). Cross-validation error was low (∼ 0.1). Temperature range, elevation, and rain were the best predictors of koala occurrence. Our models predict high habitat suitability in Kangaroo Island, along the Mount Lofty Ranges, and at the tips of the Eyre, Yorke and Fleurieu Peninsulas. In the highest-density region (5576 km2) of the Adelaide–Mount Lofty Ranges, a density–suitability relationship predicts a population of 113,704 (95% confidence interval: 27,685–199,723; average density = 5.0–35.8 km−2). We demonstrate the power of citizen science data for predicting species' distributions provided that the statistical approaches applied account for some uncertainties and potential biases. A future improvement to citizen science surveys to provide better data on search effort is that smartphone apps could be activated at the start of the search. The results of our models provide preliminary ranges of habitat suitability and population size for a species for which previous data have been difficult or impossible to gather otherwise. PMID:25360252

Distribution models for koalas in South Australia using citizen science-collected data.

PubMed

Sequeira, Ana M M; Roetman, Philip E J; Daniels, Christopher B; Baker, Andrew K; Bradshaw, Corey J A

2014-06-01

The koala (Phascolarctos cinereus) occurs in the eucalypt forests of eastern and southern Australia and is currently threatened by habitat fragmentation, climate change, sexually transmitted diseases, and low genetic variability throughout most of its range. Using data collected during the Great Koala Count (a 1-day citizen science project in the state of South Australia), we developed generalized linear mixed-effects models to predict habitat suitability across South Australia accounting for potential errors associated with the dataset. We derived spatial environmental predictors for vegetation (based on dominant species of Eucalyptus or other vegetation), topographic water features, rain, elevation, and temperature range. We also included predictors accounting for human disturbance based on transport infrastructure (sealed and unsealed roads). We generated random pseudo-absences to account for the high prevalence bias typical of citizen-collected data. We accounted for biased sampling effort along sealed and unsealed roads by including an offset for distance to transport infrastructures. The model with the highest statistical support (wAIC c ∼ 1) included all variables except rain, which was highly correlated with elevation. The same model also explained the highest deviance (61.6%), resulted in high R (2)(m) (76.4) and R (2)(c) (81.0), and had a good performance according to Cohen's κ (0.46). Cross-validation error was low (∼ 0.1). Temperature range, elevation, and rain were the best predictors of koala occurrence. Our models predict high habitat suitability in Kangaroo Island, along the Mount Lofty Ranges, and at the tips of the Eyre, Yorke and Fleurieu Peninsulas. In the highest-density region (5576 km(2)) of the Adelaide-Mount Lofty Ranges, a density-suitability relationship predicts a population of 113,704 (95% confidence interval: 27,685-199,723; average density = 5.0-35.8 km(-2)). We demonstrate the power of citizen science data for predicting species' distributions provided that the statistical approaches applied account for some uncertainties and potential biases. A future improvement to citizen science surveys to provide better data on search effort is that smartphone apps could be activated at the start of the search. The results of our models provide preliminary ranges of habitat suitability and population size for a species for which previous data have been difficult or impossible to gather otherwise.

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.

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

Design of a hybrid As₂S₃-Ti:LiNbO₃ optical waveguide for phase-matched difference frequency generation at mid-infrared.

PubMed

Wang, Xin; Madsen, Christi K

2014-11-03

Based on arsenic tri-sulfide films on titanium-diffused lithium niobate, we designed a hybrid optical waveguide for efficient mid-infrared emission by phase-matched difference frequency generation (DFG). The hybrid waveguide structure possesses a low-index magnesium fluoride buffer layer sandwiched between two high-index As(2)S(3) slabs, so that pump and signal waves are tightly confined by titanium-diffused waveguide while the DFG output idler wave at mid-infrared is confined by the whole hybrid waveguide structure. On a 1 mm-long hybrid waveguide pumped at 50 mW powers, a normalized power conversion efficiency of 20.52%W(-1)cm(-2) was theoretically predicted, which is the highest record for mid-infrared DFG waveguides based on lithium niobate crystal, to the best of our knowledge. Using a tunable near-infrared pump laser at 1.38-1.47 µm or a tunable signal laser at 1.95-2.15 µm, a broad mid-infrared tuning range from 4.0 µm to 4.9 µm can be achieved. Such hybrid optical waveguides are feasible for mid-infrared emission with mW powers and sub-nanometer linewidths.

Terra Flexible Blanket Solar Array Deployment, On-Orbit Performance and Future Applications

NASA Technical Reports Server (NTRS)

Kurland, Richard; Schurig, Hans; Rosenfeld, Mark; Herriage, Michael; Gaddy, Edward; Keys, Denney; Faust, Carl; Andiario, William; Kurtz, Michelle; Moyer, Eric;

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

Predictive power of the DASA-IV: Variations in rating method and timescales.

PubMed

Nqwaku, Mphindisi; Draycott, Simon; Aldridge-Waddon, Luke; Bush, Emma-Louise; Tsirimokou, Alexandra; Jones, Dominic; Puzzo, Ignazio

2018-05-10

This project evaluated the predictive validity of the Dynamic Appraisal of Situational Aggression - Inpatient Version (DASA-IV) in a high-secure psychiatric hospital in the UK over 24 hours and over a single nursing shift. DASA-IV scores from three sequential nursing shifts over a 24-hour period were compared with the mean (average of three scores across the 24-hour period) and peak (highest of the three scores across the 24-hour period) scores across these shifts. In addition, scores from a single nursing shift were used to predict aggressive incidents over each of the following three shifts. The DASA-IV was completed by nursing staff during handover meetings, rating 43 male psychiatric inpatients over a period of 6 months. Data were compared to incident reports recorded over the same period. Receiver operating characteristic (ROC) curves and generalized estimating equations assessed the predictive ability of various DASA-IV scores over 24-hour and single-shift timescales. Scores from the DASA-IV based on a single shift had moderate predictive ability for aggressive incidents occurring the next calendar day, whereas scores based on all three shifts had excellent predictive ability. DASA-IV scores from a single shift showed moderate predictive ability for each of the following three shifts. The DASA-IV has excellent predictive ability for aggressive incidents within a secure setting when data are summarized over a 24-hour period, as opposed to when a single rating is taken. In addition, it has moderate value for predicting incidents over even shorter timescales. © 2018 Australian College of Mental Health Nurses Inc.

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

Applying an intelligent model and sensitivity analysis to inspect mass transfer kinetics, shrinkage and crust color changes of deep-fat fried ostrich meat cubes.

PubMed

Amiryousefi, Mohammad Reza; Mohebbi, Mohebbat; Khodaiyan, Faramarz

2014-01-01

The objectives of this study were to use image analysis and artificial neural network (ANN) to predict mass transfer kinetics as well as color changes and shrinkage of deep-fat fried ostrich meat cubes. Two generalized feedforward networks were separately developed by using the operation conditions as inputs. Results based on the highest numerical quantities of the correlation coefficients between the experimental versus predicted values, showed proper fitting. Sensitivity analysis results of selected ANNs showed that among the input variables, frying temperature was the most sensitive to moisture content (MC) and fat content (FC) compared to other variables. Sensitivity analysis results of selected ANNs showed that MC and FC were the most sensitive to frying temperature compared to other input variables. Similarly, for the second ANN architecture, microwave power density was the most impressive variable having the maximum influence on both shrinkage percentage and color changes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Gut Microbiome Function Predicts Response to Anti-integrin Biologic Therapy in Inflammatory Bowel Diseases.

PubMed

Ananthakrishnan, Ashwin N; Luo, Chengwei; Yajnik, Vijay; Khalili, Hamed; Garber, John J; Stevens, Betsy W; Cleland, Thomas; Xavier, Ramnik J

2017-05-10

The gut microbiome plays a central role in inflammatory bowel diseases (IBDs) pathogenesis and propagation. To determine whether the gut microbiome may predict responses to IBD therapy, we conducted a prospective study with Crohn's disease (CD) or ulcerative colitis (UC) patients initiating anti-integrin therapy (vedolizumab). Disease activity and stool metagenomes at baseline, and weeks 14, 30, and 54 after therapy initiation were assessed. Community α-diversity was significantly higher, and Roseburia inulinivorans and a Burkholderiales species were more abundant at baseline among CD patients achieving week 14 remission. Several significant associations were identified with microbial function; 13 pathways including branched chain amino acid synthesis were significantly enriched in baseline samples from CD patients achieving remission. A neural network algorithm, vedoNet, incorporating microbiome and clinical data, provided highest classifying power for clinical remission. We hypothesize that the trajectory of early microbiome changes may be a marker of response to IBD treatment. Copyright © 2017 Elsevier Inc. All rights reserved.

Drift from the Use of Hand-Held Knapsack Pesticide Sprayers in Boyacá (Colombian Andes).

PubMed

García-Santos, Glenda; Feola, Giuseppe; Nuyttens, David; Diaz, Jaime

2016-05-25

Offsite pesticide losses in tropical mountainous regions have been little studied. One example is measuring pesticide drift soil deposition, which can support pesticide risk assessment for surface water, soil, bystanders, and off-target plants and fauna. This is considered a serious gap, given the evidence of pesticide-related poisoning in those regions. Empirical data of drift deposition of a pesticide surrogate, Uranine tracer, within one of the highest potato-producing regions in Colombia, characterized by small plots and mountain orography, is presented. High drift values encountered in this study reflect the actual spray conditions using hand-held knapsack sprayers. Comparison between measured and predicted drift values using three existing empirical equations showed important underestimation. However, after their optimization based on measured drift information, the equations showed a strong predictive power for this study area and the study conditions. The most suitable curve to assess mean relative drift was the IMAG calculator after optimization.

High Performance and Economic Supercapacitors for Energy Storage Based on Carbon Nanomaterials

NASA Astrophysics Data System (ADS)

Samuilov, Vladimir; Farshid, Behzad; Frenkel, Alexander; Sensor CAT at Stony Brook Team

2015-03-01

We designed and manufactured very inexpensive prototypes of supercapacitors for energy storage based on carbon nanomaterials comprised of: reduced graphene oxide (RGOs) and carbon nanotubes (CNTs) as electrodes filled with polymer gel electrolytes. The electrochemical properties of supercapacitors made using these materials were compared and analyzed. A significant tradeoff between the energy density and the power density was determined; RGO electrodes demonstrated the highest energy density, while composite RGO/CNT electrodes showed the highest power density. The thickness of the RGO electrode was varied to determine its effect on the power density of the supercapacitor and results showed that with decreasing electrode thickness power density would increase. The specific capacitances of over 600 F/g were observed.

Protection of Hardware: Powering Systems (Power Converter, Normal Conducting, and Superconducting Magnets)

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

Pfeffer, H.; Flora, B.; Wolff, D.

2016-01-01

Along with the protection of magnets and power converters, we have added a section on personnel protection because this is our highest priority in the design and operation of power systems. Thus, our topics are the protection of people, power converters, and magnet loads (protected from the powering equipment), including normal conducting magnets and superconducting magnets.

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

The capacity credit of grid-connected photovoltaic systems

NASA Astrophysics Data System (ADS)

Alsema, E. A.; van Wijk, A. J. M.; Turkenburg, W. C.

The capacity credit due photovoltaic (PV) power plants if integrated into the Netherlands grid was investigated, together with an estimate of the total allowable penetration. An hourly simulation was performed based on meteorological data from five stations and considering tilted surfaces, the current grid load pattern, and the load pattern after PV-power augmentation. The reliability of the grid was assessed in terms of a loss of load probability analysis, assuming power drops were limited to 1 GW. A projected tolerance for 2.5 GW of PV power was calculated. Peak demands were determined to be highest in winter, contrary to highest insolation levels; however, daily insolation levels coincided with daily peak demands. Combining the PV input with an equal amount of wind turbine power production was found to augment the capacity credit for both at aggregate outputs of 2-4 GW.

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.

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

PubMed

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

2017-01-01

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

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

PubMed Central

2017-01-01

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

Prediction of Human Performance Using Electroencephalography under Different Indoor Room Temperatures

PubMed Central

Zhang, Tinghe; Mao, Zijing; Xu, Xiaojing; Zhang, Lin; Pack, Daniel J.; Dong, Bing; Huang, Yufei

2018-01-01

Varying indoor environmental conditions is known to affect office worker’s performance; wherein past research studies have reported the effects of unfavorable indoor temperature and air quality causing sick building syndrome (SBS) among office workers. Thus, investigating factors that can predict performance in changing indoor environments have become a highly important research topic bearing significant impact in our society. While past research studies have attempted to determine predictors for performance, they do not provide satisfactory prediction ability. Therefore, in this preliminary study, we attempt to predict performance during office-work tasks triggered by different indoor room temperatures (22.2 °C and 30 °C) from human brain signals recorded using electroencephalography (EEG). Seven participants were recruited, from whom EEG, skin temperature, heart rate and thermal survey questionnaires were collected. Regression analyses were carried out to investigate the effectiveness of using EEG power spectral densities (PSD) as predictors of performance. Our results indicate EEG PSDs as predictors provide the highest R2 (> 0.70), that is 17 times higher than using other physiological signals as predictors and is more robust. Finally, the paper provides insight on the selected predictors based on brain activity patterns for low- and high-performance levels under different indoor-temperatures. PMID:29690601

Prediction of Human Performance Using Electroencephalography under Different Indoor Room Temperatures.

PubMed

Nayak, Tapsya; Zhang, Tinghe; Mao, Zijing; Xu, Xiaojing; Zhang, Lin; Pack, Daniel J; Dong, Bing; Huang, Yufei

2018-04-23

Varying indoor environmental conditions is known to affect office worker’s performance; wherein past research studies have reported the effects of unfavorable indoor temperature and air quality causing sick building syndrome (SBS) among office workers. Thus, investigating factors that can predict performance in changing indoor environments have become a highly important research topic bearing significant impact in our society. While past research studies have attempted to determine predictors for performance, they do not provide satisfactory prediction ability. Therefore, in this preliminary study, we attempt to predict performance during office-work tasks triggered by different indoor room temperatures (22.2 °C and 30 °C) from human brain signals recorded using electroencephalography (EEG). Seven participants were recruited, from whom EEG, skin temperature, heart rate and thermal survey questionnaires were collected. Regression analyses were carried out to investigate the effectiveness of using EEG power spectral densities (PSD) as predictors of performance. Our results indicate EEG PSDs as predictors provide the highest R ² (> 0.70), that is 17 times higher than using other physiological signals as predictors and is more robust. Finally, the paper provides insight on the selected predictors based on brain activity patterns for low- and high-performance levels under different indoor-temperatures.

Grid-Tied Photovoltaic Power System

NASA Technical Reports Server (NTRS)

Eichenberg, Dennis J.

2011-01-01

A grid-tied photovoltaic (PV) power system is connected directly to the utility distribution grid. Facility power can be obtained from the utility system as normal. The PV system is synchronized with the utility system to provide power for the facility, and excess power is provided to the utility. Operating costs of a PV power system are low compared to conventional power technologies. This method can displace the highest-cost electricity during times of peak demand in most climatic regions, and thus reduce grid loading. Net metering is often used, in which independent power producers such as PV power systems are connected to the utility grid via the customers main service panels and meters. When the PV power system is generating more power than required at that location, the excess power is provided to the utility grid. The customer pays the net of the power purchased when the on-site power demand is greater than the onsite power production, and the excess power is returned to the utility grid. Power generated by the PV system reduces utility demand, and the surplus power aids the community. Modern PV panels are readily available, reliable, efficient, and economical, with a life expectancy of at least 25 years. Modern electronics have been the enabling technology behind grid-tied power systems, making them safe, reliable, efficient, and economical with a life expectancy equal to the modern PV panels. The grid-tied PV power system was successfully designed and developed, and this served to validate the basic principles developed, and the theoretical work that was performed. Grid-tied PV power systems are reliable, maintenance- free, long-life power systems, and are of significant value to NASA and the community. Of particular value are the analytical tools and capabilities that have been successfully developed. Performance predictions can be made confidently for grid-tied PV systems of various scales. The work was done under the NASA Hybrid Power Management (HPM) Program, which is the integration of diverse power devices in an optimal configuration for space and terrestrial applications.

The exponential function transforms the Abbreviated Injury Scale, which both improves accuracy and simplifies scoring.

PubMed

Wang, M D; Fan, W H; Qiu, W S; Zhang, Z L; Mo, Y N; Qiu, F

2014-06-01

We present here the exponential function which transforms the Abbreviated Injury Scale (AIS). It is called the Exponential Injury Severity Score (EISS), and significantly outperforms the venerable but dated New Injury Severity Score (NISS) and Injury Severity Score (ISS) as a predictor of mortality. The EISS is defined as a change of AIS values by raising each AIS severity score (1-6) by 3 taking a power of AIS minus 2 and then summing the three most severe injuries (i.e., highest AIS), regardless of body regions. EISS values were calculated for every patient in two large independent data sets: 3,911 and 4,129 patients treated during a 6-year period at the Class A tertiary hospitals in China. The power of the EISS to predict mortality was then compared with previously calculated NISS values for the same patients in each of the two data sets. We found that the EISS is more predictive of survival [Zhejiang: area under the receiver operating characteristic curve (AUC): NISS = 0.932, EISS = 0.949, P = 0.0115; Liaoning: AUC: NISS = 0.924, EISS = 0.942, P = 0.0139]. Moreover, the EISS provides a better fit throughout its entire range of prediction (Hosmer-Lemeshow statistic for Zhejiang: NISS = 21.86, P = 0.0027, EISS = 13.52, P = 0.0604; Liaoning: NISS = 23.27, P = 0.0015, EISS = 15.55, P = 0.0164). The EISS may be used as the standard summary measure of human trauma.

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)

Predictive Modeling and Concentration of the Risk of Suicide: Implications for Preventive Interventions in the US Department of Veterans Affairs

PubMed Central

McCarthy, John F.; Katz, Ira R.; Thompson, Caitlin; Kemp, Janet; Hannemann, Claire M.; Nielson, Christopher; Schoenbaum, Michael

2015-01-01

Objectives. The Veterans Health Administration (VHA) evaluated the use of predictive modeling to identify patients at risk for suicide and to supplement ongoing care with risk-stratified interventions. Methods. Suicide data came from the National Death Index. Predictors were measures from VHA clinical records incorporating patient-months from October 1, 2008, to September 30, 2011, for all suicide decedents and 1% of living patients, divided randomly into development and validation samples. We used data on all patients alive on September 30, 2010, to evaluate predictions of suicide risk over 1 year. Results. Modeling demonstrated that suicide rates were 82 and 60 times greater than the rate in the overall sample in the highest 0.01% stratum for calculated risk for the development and validation samples, respectively; 39 and 30 times greater in the highest 0.10%; 14 and 12 times greater in the highest 1.00%; and 6.3 and 5.7 times greater in the highest 5.00%. Conclusions. Predictive modeling can identify high-risk patients who were not identified on clinical grounds. VHA is developing modeling to enhance clinical care and to guide the delivery of preventive interventions. PMID:26066914

Predictive Modeling and Concentration of the Risk of Suicide: Implications for Preventive Interventions in the US Department of Veterans Affairs.

PubMed

McCarthy, John F; Bossarte, Robert M; Katz, Ira R; Thompson, Caitlin; Kemp, Janet; Hannemann, Claire M; Nielson, Christopher; Schoenbaum, Michael

2015-09-01

The Veterans Health Administration (VHA) evaluated the use of predictive modeling to identify patients at risk for suicide and to supplement ongoing care with risk-stratified interventions. Suicide data came from the National Death Index. Predictors were measures from VHA clinical records incorporating patient-months from October 1, 2008, to September 30, 2011, for all suicide decedents and 1% of living patients, divided randomly into development and validation samples. We used data on all patients alive on September 30, 2010, to evaluate predictions of suicide risk over 1 year. Modeling demonstrated that suicide rates were 82 and 60 times greater than the rate in the overall sample in the highest 0.01% stratum for calculated risk for the development and validation samples, respectively; 39 and 30 times greater in the highest 0.10%; 14 and 12 times greater in the highest 1.00%; and 6.3 and 5.7 times greater in the highest 5.00%. Predictive modeling can identify high-risk patients who were not identified on clinical grounds. VHA is developing modeling to enhance clinical care and to guide the delivery of preventive interventions.

An evaluation of the effect of recent temperature variability on the prediction of coral bleaching events.

PubMed

Donner, Simon D

2011-07-01

Over the past 30 years, warm thermal disturbances have become commonplace on coral reefs worldwide. These periods of anomalous sea surface temperature (SST) can lead to coral bleaching, a breakdown of the symbiosis between the host coral and symbiotic dinoflagellates which reside in coral tissue. The onset of bleaching is typically predicted to occur when the SST exceeds a local climatological maximum by 1 degrees C for a month or more. However, recent evidence suggests that the threshold at which bleaching occurs may depend on thermal history. This study uses global SST data sets (HadISST and NOAA AVHRR) and mass coral bleaching reports (from Reefbase) to examine the effect of historical SST variability on the accuracy of bleaching prediction. Two variability-based bleaching prediction methods are developed from global analysis of seasonal and interannual SST variability. The first method employs a local bleaching threshold derived from the historical variability in maximum annual SST to account for spatial variability in past thermal disturbance frequency. The second method uses a different formula to estimate the local climatological maximum to account for the low seasonality of SST in the tropics. The new prediction methods are tested against the common globally fixed threshold method using the observed bleaching reports. The results find that estimating the bleaching threshold from local historical SST variability delivers the highest predictive power, but also a higher rate of Type I errors. The second method has the lowest predictive power globally, though regional analysis suggests that it may be applicable in equatorial regions. The historical data analysis suggests that the bleaching threshold may have appeared to be constant globally because the magnitude of interannual variability in maximum SST is similar for many of the world's coral reef ecosystems. For example, the results show that a SST anomaly of 1 degrees C is equivalent to 1.73-2.94 standard deviations of the maximum monthly SST for two-thirds of the world's coral reefs. Coral reefs in the few regions that experience anomalously high interannual SST variability like the equatorial Pacific could prove critical to understanding how coral communities acclimate or adapt to frequent and/or severe thermal disturbances.

The one-loop matter bispectrum in the Effective Field Theory of Large Scale Structures

DOE PAGES

Angulo, Raul E.; Foreman, Simon; Schmittfull, Marcel; ...

2015-10-14

With this study, given the importance of future large scale structure surveys for delivering new cosmological information, it is crucial to reliably predict their observables. The Effective Field Theory of Large Scale Structures (EFTofLSS) provides a manifestly convergent perturbative scheme to compute the clustering of dark matter in the weakly nonlinear regime in an expansion in k/k NL, where k is the wavenumber of interest and k NL is the wavenumber associated to the nonlinear scale. It has been recently shown that the EFTofLSS matches to 1% level the dark matter power spectrum at redshift zero up to k ≃more » 0.3 h Mpc –1 and k ≃ 0.6 h Mpc –1 at one and two loops respectively, using only one counterterm that is fit to data. Similar results have been obtained for the momentum power spectrum at one loop. This is a remarkable improvement with respect to former analytical techniques. Here we study the prediction for the equal-time dark matter bispectrum at one loop. We find that at this order it is sufficient to consider the same counterterm that was measured in the power spectrum. Without any remaining free parameter, and in a cosmology for which kNL is smaller than in the previously considered cases (σ 8=0.9), we find that the prediction from the EFTofLSS agrees very well with N-body simulations up to k ≃ 0.25 h Mpc –1, given the accuracy of the measurements, which is of order a few percent at the highest k's of interest. While the fit is very good on average up to k ≃ 0.25 h Mpc –1, the fit performs slightly worse on equilateral configurations, in agreement with expectations that for a given maximum k, equilateral triangles are the most nonlinear.« less

Traction Drive Inverter Cooling with Submerged Liquid Jet Impingement on Microfinned Enhanced Surfaces (Presentation)

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

Waye, S.; Narumanchi, S.; Moreno, G.

Jet impingement is one means to improve thermal management for power electronics in electric-drive traction vehicles. Jet impingement on microfin-enhanced surfaces further augments heat transfer and thermal performance. A channel flow heat exchanger from a commercial inverter was characterized as a baseline system for comparison with two new prototype designs using liquid jet impingement on plain and microfinned enhanced surfaces. The submerged jets can target areas with the highest heat flux to provide local cooling, such as areas under insulated-gate bipolar transistors and diode devices. Low power experiments, where four diodes were powered, dissipated 105 W of heat and weremore » used to validate computational fluid dynamics modeling of the baseline and prototype designs. Experiments and modeling used typical automotive flow rates using water-ethylene glycol as a coolant (50%-50% by volume). The computational fluid dynamics model was used to predict full inverter power heat dissipation. The channel flow and jet impingement configurations were tested at full inverter power of 40 to 100 kW (output power) on a dynamometer, translating to an approximate heat dissipation of 1 to 2 kW. With jet impingement, the cold plate material is not critical for the thermal pathway. A high-temperature plastic was used that could eventually be injection molded or formed, with the jets formed from a basic aluminum plate with orifices acting as nozzles. Long-term reliability of the jet nozzles and impingement on enhanced surfaces was examined. For jet impingement on microfinned surfaces, thermal performance increased 17%. Along with a weight reduction of approximately 3 kg, the specific power (kW/kg) increased by 36%, with an increase in power density (kW/L) of 12% compared with the baseline channel flow configuration.« less

Multivariate methods for evaluating the efficiency of electrodialytic removal of heavy metals from polluted harbour sediments.

PubMed

Pedersen, Kristine Bondo; Kirkelund, Gunvor M; Ottosen, Lisbeth M; Jensen, Pernille E; Lejon, Tore

2015-01-01

Chemometrics was used to develop a multivariate model based on 46 previously reported electrodialytic remediation experiments (EDR) of five different harbour sediments. The model predicted final concentrations of Cd, Cu, Pb and Zn as a function of current density, remediation time, stirring rate, dry/wet sediment, cell set-up as well as sediment properties. Evaluation of the model showed that remediation time and current density had the highest comparative influence on the clean-up levels. Individual models for each heavy metal showed variance in the variable importance, indicating that the targeted heavy metals were bound to different sediment fractions. Based on the results, a PLS model was used to design five new EDR experiments of a sixth sediment to achieve specified clean-up levels of Cu and Pb. The removal efficiencies were up to 82% for Cu and 87% for Pb and the targeted clean-up levels were met in four out of five experiments. The clean-up levels were better than predicted by the model, which could hence be used for predicting an approximate remediation strategy; the modelling power will however improve with more data included. Copyright © 2014 Elsevier B.V. All rights reserved.

Factors associated with diabetes mellitus prediction among pregnant Arab subjects with gestational diabetes.

PubMed

Aljohani, Naji; Al Serehi, Amal; Ahmed, Amjad M; Buhary, Badr Aldin M; Alzahrani, Saad; At-Taras, Eeman; Almujally, Najla; Alsharqi, Maha; Alqahtani, Mohammed; Almalki, Mussa

2015-01-01

There is scarcity of available information on the possible significant risk factors related to diabetes mellitus (DM) prediction among expectant Saudi mothers with gestational diabetes mellitus (GDM). The present study is the first to identify such risk factors in the Arab cohort. A total of 300 pregnant subjects (mean age 33.45 ± 6.5 years) were randomly selected from all the deliveries registered at the Obstetrics Department of King Fahad Medical City, Riyadh Saudi Arabia from April 2011 to March 2013. Demographic and baseline glycemic information were collected. A total of 7 highly significant and independent risk factors were identified: age, obesity, and family history of DM, GDM < 20 weeks, macrosomia, insulin therapy and recurrent GDM. Among these factors, subjects who had insulin therapy use are 5 times more likely to develop DMT2 (p-value 3.94 × 10(-14)) followed by recurrent GDM [odds-ratio 4.69 (Confidence Interval 2.34-4.84); P = 1.24 × 10(-13)). The identification of the risk factors mentioned with their respective predictive powers in the detection of DMT2 needs to be taken seriously in the post-partum assessment of Saudi pregnant patients at highest risk.

Power System Mass Analysis for Hydrogen Reduction Oxygen Production on the Lunar Surface

NASA Technical Reports Server (NTRS)

Colozza, Anthony J.

2009-01-01

The production of oxygen from the lunar regolith requires both thermal and electrical power in roughly similar proportions. This unique power requirement is unlike most applications on the lunar surface. To efficiently meet these requirements, both solar PV array and solar concentrator systems were evaluated. The mass of various types of photovoltaic and concentrator based systems were calculated to determine the type of power system that provided the highest specific power. These were compared over a range of oxygen production rates. Also a hybrid type power system was also considered. This system utilized a photovoltaic array to produce the electrical power and a concentrator to provide the thermal power. For a single source system the three systems with the highest specific power were a flexible concentrator/Stirling engine system, a rigid concentrator/Stirling engine system and a tracking triple junction solar array system. These systems had specific power values of 43, 34, and 33 W/kg, respectively. The hybrid power system provided much higher specific power values then the single source systems. The best hybrid combinations were the triple junction solar array with the flexible concentrator and the rigid concentrator. These systems had a specific power of 81 and 68 W/kg, respectively.

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

PubMed

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

2016-12-01

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

Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques.

PubMed

Illias, Hazlee Azil; Chai, Xin Rui; Abu Bakar, Ab Halim; Mokhlis, Hazlie

2015-01-01

It is important to predict the incipient fault in transformer oil accurately so that the maintenance of transformer oil can be performed correctly, reducing the cost of maintenance and minimise the error. Dissolved gas analysis (DGA) has been widely used to predict the incipient fault in power transformers. However, sometimes the existing DGA methods yield inaccurate prediction of the incipient fault in transformer oil because each method is only suitable for certain conditions. Many previous works have reported on the use of intelligence methods to predict the transformer faults. However, it is believed that the accuracy of the previously proposed methods can still be improved. Since artificial neural network (ANN) and particle swarm optimisation (PSO) techniques have never been used in the previously reported work, this work proposes a combination of ANN and various PSO techniques to predict the transformer incipient fault. The advantages of PSO are simplicity and easy implementation. The effectiveness of various PSO techniques in combination with ANN is validated by comparison with the results from the actual fault diagnosis, an existing diagnosis method and ANN alone. Comparison of the results from the proposed methods with the previously reported work was also performed to show the improvement of the proposed methods. It was found that the proposed ANN-Evolutionary PSO method yields the highest percentage of correct identification for transformer fault type than the existing diagnosis method and previously reported works.

Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques

PubMed Central

2015-01-01

It is important to predict the incipient fault in transformer oil accurately so that the maintenance of transformer oil can be performed correctly, reducing the cost of maintenance and minimise the error. Dissolved gas analysis (DGA) has been widely used to predict the incipient fault in power transformers. However, sometimes the existing DGA methods yield inaccurate prediction of the incipient fault in transformer oil because each method is only suitable for certain conditions. Many previous works have reported on the use of intelligence methods to predict the transformer faults. However, it is believed that the accuracy of the previously proposed methods can still be improved. Since artificial neural network (ANN) and particle swarm optimisation (PSO) techniques have never been used in the previously reported work, this work proposes a combination of ANN and various PSO techniques to predict the transformer incipient fault. The advantages of PSO are simplicity and easy implementation. The effectiveness of various PSO techniques in combination with ANN is validated by comparison with the results from the actual fault diagnosis, an existing diagnosis method and ANN alone. Comparison of the results from the proposed methods with the previously reported work was also performed to show the improvement of the proposed methods. It was found that the proposed ANN-Evolutionary PSO method yields the highest percentage of correct identification for transformer fault type than the existing diagnosis method and previously reported works. PMID:26103634

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.

An assessment of renewable energy in Southern Africa: Wind, solar, hydro

NASA Astrophysics Data System (ADS)

Fant, Charles William, IV

While electricity demand is rising quickly in the Southern African Power Pool (SAPP), the nations involved struggle to build the necessary infrastructure to meet the demand. In addition, the principal member---the Republic of South Africa---has made ambitious targets to reduce emissions via renewable energy technology. In this dissertation, three stand-alone studies on this subject are presented that address the future reliability of renewable energy in southern Africa, considering climate variability as well as long-term trends caused by climate change. In the first study, a suite of models are used to assess the vulnerability of the countries dependent on resources from the Zambezi River Basin to changes in climate. The study finds that the sectors most vulnerable to climate change are: hydropower in Zambia, irrigation in Zimbabwe and Mozambique, and flooding in Mozambique. In the second study, hourly reanalysis data is used to characterize wind power intermittency and assess the value of interconnection in southern Africa. The study finds that wind potential is high in Kenya, central Tanzania, and southern South Africa. With a closer look, wind power resource in South Africa is unreliable (i.e. intermittent) and is weak when power demand is highest on all relevant time-scales. In the third study, presented in Chapter 4, we develop a risk profile for changes in the long-term mean of wind and solar power sources. To do this, we use a statistical relationship between global mean temperature and each local gridded wind speed and solar radiation from the GCMs. We find that only small changes in wind speed and solar radiation are predicted in the median of the distributions projected to 2050. Furthermore, at the extremes of the distribution, relatively significant changes are predicted in some parts of southern Africa, and are associated with low probability. Finally, in the conclusion chapter, limitations and assumptions are listed for each of the three studies, South Africa's options for reducing emissions are revisited, power trade and interconnection are discussed broadly, and future research is suggested.

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.

Conflict and expectancies interact to predict sexual behavior under the influence among gay and bisexual men

PubMed Central

Wells, Brooke E; Starks, Tyrel J; Parsons, Jeffrey T; Golub, Sarit

2013-01-01

As the mechanisms of the associations between substance use and risky sex remain unclear, this study investigates the interactive roles of conflicts about casual sex and condom use and expectancies of the sexual effects of substances in those associations among gay men. Conflict interacted with expectancies to predict sexual behavior under the influence; low casual sex conflict coupled with high expectancies predicted the highest number of casual partners, and high condom use conflict and high expectancies predicted the highest number of unprotected sex acts. Results have implications for intervention efforts that aim to improve sexual decision-making and reduce sexual expectancies. PMID:23584507

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.

In silico designing of power conversion efficient organic lead dyes for solar cells using todays innovative approaches to assure renewable energy for future

NASA Astrophysics Data System (ADS)

Kar, Supratik; Roy, Juganta K.; Leszczynski, Jerzy

2017-06-01

Advances in solar cell technology require designing of new organic dye sensitizers for dye-sensitized solar cells with high power conversion efficiency to circumvent the disadvantages of silicon-based solar cells. In silico studies including quantitative structure-property relationship analysis combined with quantum chemical analysis were employed to understand the primary electron transfer mechanism and photo-physical properties of 273 arylamine organic dyes from 11 diverse chemical families explicit to iodine electrolyte. The direct quantitative structure-property relationship models enable identification of the essential electronic and structural attributes necessary for quantifying the molecular prerequisites of 11 classes of arylamine organic dyes, responsible for high power conversion efficiency of dye-sensitized solar cells. Tetrahydroquinoline, N,N'-dialkylaniline and indoline have been least explored classes under arylamine organic dyes for dye-sensitized solar cells. Therefore, the identified properties from the corresponding quantitative structure-property relationship models of the mentioned classes were employed in designing of "lead dyes". Followed by, a series of electrochemical and photo-physical parameters were computed for designed dyes to check the required variables for electron flow of dye-sensitized solar cells. The combined computational techniques yielded seven promising lead dyes each for all three chemical classes considered. Significant (130, 183, and 46%) increment in predicted %power conversion efficiency was observed comparing with the existing dye with highest experimental %power conversion efficiency value for tetrahydroquinoline, N,N'-dialkylaniline and indoline, respectively maintaining required electrochemical parameters.

Power Amplifier Module with 734-mW Continuous Wave Output Power

NASA Technical Reports Server (NTRS)

Fung, King Man; Samoska, Lorene A.; Kangaslahti, Pekka P.; Lamgrigtsen, Bjorn H.; Goldsmith, Paul F.; Lin, Robert H.; Soria, Mary M.; Cooperrider, Joelle T.; Micovic, Moroslav; Kurdoghlian, Ara

2010-01-01

Research findings were reported from an investigation of new gallium nitride (GaN) monolithic millimeter-wave integrated circuit (MMIC) power amplifiers (PAs) targeting the highest output power and the highest efficiency for class-A operation in W-band (75-110 GHz). W-band PAs are a major component of many frequency multiplied submillimeter-wave LO signal sources. For spectrometer arrays, substantial W-band power is required due to the passive lossy frequency multipliers-to generate higher frequency signals in nonlinear Schottky diode-based LO sources. By advancing PA technology, the LO system performance can be increased with possible cost reductions compared to current GaAs PAs. High-power, high-efficiency GaN PAs are cross-cutting and can enable more efficient local oscillator distribution systems for new astrophysics and planetary receivers and heterodyne array instruments. It can also allow for a new, electronically scannable solid-state array technology for future Earth science radar instruments and communications platforms.

[Ability of procalcitonin to predict bacteremia in patients with community acquired pneumonia].

PubMed

Julián-Jiménez, Agustín; Timón Zapata, Jesús; Laserna Mendieta, Emilio José; Parejo Miguez, Raquel; Flores Chacartegui, Manuel; Gallardo Schall, Pablo

2014-04-07

To analyze the usefulness and ability of procalcitonin (PCT) to predict the presence of bacteremia in patients with community-acquired pneumonia (CAP) caused by Streptococcus pneumoniae (S. pneumoniae) or other bacteria. This is an observational, prospective and descriptive study involving patients who were diagnosed with CAP in our Emergency Department. Data collected included socio-demographic and comorbidity variables, Charlson index, stage in the Pneumonia Severity Index and criteria of severe NAC, microbiologic studies and biomarker determinations (PCT and C reactive protein). The follow-up was carried out during 30 days to calculate the predictive power and the diagnostic performance for bacteremia caused or not by S. pneumoniae. Four hundred and seventy-four patients were finally included in the study. Blood cultures were positive in 85 individuals (17.9%) and S. pneumoniae was identified as the responsible pathogen in 75 of them (88.4%) (in 5 cases together with another agent). The area under the Receiver Operating Characteristic curve for PCT to predict bacteremia (caused by S. pneumoniae or not) was 0.988 (95% confidence interval 0.908-0.995; P<.001) and, considering a cut-off value≥0.95ng/mL, the negative predictive value and the positive likelihood ratio were>98% and>10, respectively. The most frequently isolated serotypes of S. pneumoniae were 19A, 7F, 1 and 3. The highest mean levels of PCT were found in serotypes 7F, 19A, 3 and 1, which showed statistically significant differences with regard to the others serotypes considered (P=.008). Serotypes associated with the highest percentage of severe sepsis-septic shock, 30-days mortality and multi-lobe or bilateral affection were 3, 1 and 19A; 1, 3 and 19A; and 3, 19A and 6A, respectively. PCT had a remarkable diagnostic ability to discard or suspect bacteremia and to guide the etiology of CAP caused by S. pneumoniae. Serotypes 1, 3, 19A and 7F showed greater frequency, systemic inflammatory response and clinical severity. Copyright © 2013 Elsevier España, S.L. All rights reserved.

Wet snow hazard for power lines: a forecast and alert system applied in Italy

NASA Astrophysics Data System (ADS)

Bonelli, P.; Lacavalla, M.; Marcacci, P.; Mariani, G.; Stella, G.

2011-09-01

Wet snow icing accretion on power lines is a real problem in Italy, causing failures on high and medium voltage power supplies during the cold season. The phenomenon is a process in which many large and local scale variables contribute in a complex way and not completely understood. A numerical weather forecast can be used to select areas where wet snow accretion has an high probability of occurring, but a specific accretion model must also be used to estimate the load of an ice sleeve and its hazard. All the information must be carefully selected and shown to the electric grid operator in order to warn him promptly. The authors describe a prototype of forecast and alert system, WOLF (Wet snow Overload aLert and Forecast), developed and applied in Italy. The prototype elaborates the output of a numerical weather prediction model, as temperature, precipitation, wind intensity and direction, to determine the areas of potential risk for the power lines. Then an accretion model computes the ice sleeves' load for different conductor diameters. The highest values are selected and displayed on a WEB-GIS application principally devoted to the electric operator, but also to more expert users. Some experimental field campaigns have been conducted to better parameterize the accretion model. Comparisons between real accidents and forecasted icing conditions are presented and discussed.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

Antioxidant and antibacterial activity of six edible wild plants (Sonchus spp.) in China.

PubMed

Xia, Dao-Zong; Yu, Xin-Fen; Zhu, Zhuo-Ying; Zou, Zhuang-Dan

2011-12-01

The total phenolic and flavonoid, antioxidant and antibacterial activities of six Sonchus wild vegetables (Sonchus oleraceus L., Sonchus arvensis L., Sonchus asper (L.) Hill., Sonchus uliginosus M.B., Sonchus brachyotus DC. and Sonchus lingianus Shih) in China were investigated. The results revealed that S. arvensis extract and S. oleraceus extract contained the highest amount of phenolic and flavonoid, respectively. Among the methanol extracts of six Sonchus species, S. arvensis extract exhibited the highest radical (DPPH and ABTS+ scavenging power and lipid peroxidation inhibitory power. It also exhibited the highest reducing power at 500 µg mL⁻¹ by A (700) = 0.80. The results of antibacterial test indicated that the S. oleraceus extract showed higher activity than the other five Sonchus wild vegetables extracts, both in Gram-negative bacteria (Escherichia coli, Salmonella enterica and Vibrio parahaemolyticus) and in a Gram-positive bacterium (Staphylococcus aureus). These results indicate that Sonchus wild food plants might be applicable in natural medicine and healthy food.

Au generation centres doped n+-Si: hole-injection adjustable anode for efficient organic light emission

NASA Astrophysics Data System (ADS)

Li, Y. Z.; Ran, G. Z.; Zhao, W. Q.; Qin, G. G.

2008-08-01

An organic light-emitting diode (OLED) with an n-Si-anode usually has an efficiency evidently lower than the OLED with the same structure with a p-Si-anode due to insufficient hole injection from the n-Si anode compared with the p-Si-anode. In this study, we find that introducing Au as generation centres with a suitable concentration into the n+-Si anode can enhance hole injection to match electron injection and then considerably promote the power efficiency. With optimizing Au generation centre concentration in the n+-Si anode, the OLED with a structure of n+-Si: Au/NPB/AlQ/Sm/Au reaches a highest power efficiency of 1.0 lm W-1, evidently higher than the reported highest power efficiency of 0.2 lm W-1 for its p-Si-anode counterpart. Furthermore, when the electron injection is enhanced by adopting BPhen:Cs2CO3 partly instead of AlQ as the electron transport material, and the Au generation centre concentration in the n+-Si anode is promoted correspondingly, then a highest power efficiency of 1.8 lm W-1 is reached. The role of Au generation centres in the n+-Si anode is discussed.

Family-Based Benchmarking of Copy Number Variation Detection Software.

PubMed

Nutsua, Marcel Elie; Fischer, Annegret; Nebel, Almut; Hofmann, Sylvia; Schreiber, Stefan; Krawczak, Michael; Nothnagel, Michael

2015-01-01

The analysis of structural variants, in particular of copy-number variations (CNVs), has proven valuable in unraveling the genetic basis of human diseases. Hence, a large number of algorithms have been developed for the detection of CNVs in SNP array signal intensity data. Using the European and African HapMap trio data, we undertook a comparative evaluation of six commonly used CNV detection software tools, namely Affymetrix Power Tools (APT), QuantiSNP, PennCNV, GLAD, R-gada and VEGA, and assessed their level of pair-wise prediction concordance. The tool-specific CNV prediction accuracy was assessed in silico by way of intra-familial validation. Software tools differed greatly in terms of the number and length of the CNVs predicted as well as the number of markers included in a CNV. All software tools predicted substantially more deletions than duplications. Intra-familial validation revealed consistently low levels of prediction accuracy as measured by the proportion of validated CNVs (34-60%). Moreover, up to 20% of apparent family-based validations were found to be due to chance alone. Software using Hidden Markov models (HMM) showed a trend to predict fewer CNVs than segmentation-based algorithms albeit with greater validity. PennCNV yielded the highest prediction accuracy (60.9%). Finally, the pairwise concordance of CNV prediction was found to vary widely with the software tools involved. We recommend HMM-based software, in particular PennCNV, rather than segmentation-based algorithms when validity is the primary concern of CNV detection. QuantiSNP may be used as an additional tool to detect sets of CNVs not detectable by the other tools. Our study also reemphasizes the need for laboratory-based validation, such as qPCR, of CNVs predicted in silico.

Risk terrain modeling predicts child maltreatment.

PubMed

Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye

2016-12-01

As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Competition and Cooperation of Distributed Generation and Power System

NASA Astrophysics Data System (ADS)

Miyake, Masatoshi; Nanahara, Toshiya

Advances in distributed generation technologies together with the deregulation of an electric power industry can lead to a massive introduction of distributed generation. Since most of distributed generation will be interconnected to a power system, coordination and competition between distributed generators and large-scale power sources would be a vital issue in realizing a more desirable energy system in the future. This paper analyzes competitions between electric utilities and cogenerators from the viewpoints of economic and energy efficiency based on the simulation results on an energy system including a cogeneration system. First, we examine best response correspondence of an electric utility and a cogenerator with a noncooperative game approach: we obtain a Nash equilibrium point. Secondly, we examine the optimum strategy that attains the highest social surplus and the highest energy efficiency through global optimization.

Innovative open air brayton combined cycle systems for the next generation nuclear power plants

NASA Astrophysics Data System (ADS)

Zohuri, Bahman

The purpose of this research was to model and analyze a nuclear heated multi-turbine power conversion system operating with atmospheric air as the working fluid. The air is heated by a molten salt, or liquid metal, to gas heat exchanger reaching a peak temperature of 660 0C. The effects of adding a recuperator or a bottoming steam cycle have been addressed. The calculated results are intended to identify paths for future work on the next generation nuclear power plant (GEN-IV). This document describes the proposed system in sufficient detail to communicate a good understanding of the overall system, its components, and intended uses. The architecture is described at the conceptual level, and does not replace a detailed design document. The main part of the study focused on a Brayton --- Rankine Combined Cycle system and a Recuperated Brayton Cycle since they offer the highest overall efficiencies. Open Air Brayton power cycles also require low cooling water flows relative to other power cycles. Although the Recuperated Brayton Cycle achieves an overall efficiency slightly less that the Brayton --- Rankine Combined Cycle, it is completely free of a circulating water system and can be used in a desert climate. Detailed results of modeling a combined cycle Brayton-Rankine power conversion system are presented. The Rankine bottoming cycle appears to offer a slight efficiency advantage over the recuperated Brayton cycle. Both offer very significant advantages over current generation Light Water Reactor steam cycles. The combined cycle was optimized as a unit and lower pressure Rankine systems seem to be more efficient. The combined cycle requires a lot less circulating water than current power plants. The open-air Brayton systems appear to be worth investigating, if the higher temperatures predicted for the Next Generation Nuclear Plant do materialize.

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

Social and physical aggression trajectories from childhood through late adolescence: Predictors of psychosocial maladjustment at age 18.

PubMed

Ehrenreich, Samuel E; Beron, Kurt J; Underwood, Marion K

2016-03-01

This research examined whether following social and physical aggression trajectories across Grades 3-12 predicted psychological maladjustment. Teachers rated participants' (n = 287, 138 boys) aggressive behavior at the end of each school year. Following the 12th grade, psychosocial outcomes were measured: rule-breaking behaviors, internalizing symptoms, and narcissistic and borderline personality features. Following the highest social aggression trajectory predicted rule-breaking behavior; the medium social aggression trajectory was not a significant predictor of any outcome. Following the highest physical aggression trajectory predicted rule-breaking, internalizing symptoms, and narcissism, whereas the medium physical aggression trajectory predicted rule-breaking and internalizing symptoms. (c) 2016 APA, all rights reserved).

Social and physical aggression trajectories from childhood through late adolescence: Predictors of psychosocial maladjustment at age 18

PubMed Central

Ehrenreich, Samuel E.; Beron, Kurt J.; Underwood, Marion K.

2016-01-01

This research examined whether following social and physical aggression trajectories across grades 3–12 predicted psychological maladjustment. Teachers rated participants’ (n=287, 138 boys) aggressive behavior at the end of each school year. Following the 12th grade, psychosocial outcomes were measured: rule-breaking behaviors, internalizing symptoms, and narcissistic and borderline personality features. Following the highest social aggression trajectory predicted rule-breaking behavior; the medium social aggression trajectory was not a significant predictor of any outcome. Following the highest physical aggression trajectory predicted rule-breaking, internalizing symptoms and narcissism, whereas the medium physical aggression trajectory predicted rule-breaking and internalizing symptoms. PMID:26891018

Conflict and expectancies interact to predict sexual behavior under the influence among gay and bisexual men.

PubMed

Wells, Brooke E; Starks, Tyrel J; Parsons, Jeffrey T; Golub, Sarit

2014-07-01

As the mechanisms of the associations between substance use and risky sex remain unclear, this study investigates the interactive roles of conflicts about casual sex and condom use and expectancies of the sexual effects of substances in those associations among gay men. Conflict interacted with expectancies to predict sexual behavior under the influence; low casual sex conflict coupled with high expectancies predicted the highest number of casual partners, and high condom use conflict and high expectancies predicted the highest number of unprotected sex acts. Results have implications for intervention efforts that aim to improve sexual decision-making and reduce sexual expectancies. © The Author(s) 2013.

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

Open data mining for Taiwan's dengue epidemic.

PubMed

Wu, ChienHsing; Kao, Shu-Chen; Shih, Chia-Hung; Kan, Meng-Hsuan

2018-07-01

By using a quantitative approach, this study examines the applicability of data mining technique to discover knowledge from open data related to Taiwan's dengue epidemic. We compare results when Google trend data are included or excluded. Data sources are government open data, climate data, and Google trend data. Research findings from analysis of 70,914 cases are obtained. Location and time (month) in open data show the highest classification power followed by climate variables (temperature and humidity), whereas gender and age show the lowest values. Both prediction accuracy and simplicity decrease when Google trends are considered (respectively 0.94 and 0.37, compared to 0.96 and 0.46). The article demonstrates the value of open data mining in the context of public health care. Copyright © 2018 Elsevier B.V. All rights reserved.

Prediction of Wind Energy Resources (PoWER) Users Guide

DTIC Science & Technology

2016-01-01

ARL-TR-7573● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER) User’s Guide by David P Sauter...not return it to the originator. ARL-TR-7573 ● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER...2016 2. REPORT TYPE Final 3. DATES COVERED (From - To) 09/2015–11/2015 4. TITLE AND SUBTITLE Prediction of Wind Energy Resources (PoWER) User’s

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

PubMed

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

2012-02-01

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

Structural principles and thermoelectric properties of polytypic group 14 clathrate-II frameworks.

PubMed

Karttunen, Antti J; Fässler, Thomas F

2013-06-24

We have investigated the structural principles and thermoelectric properties of polytypic group 14 clathrate-II frameworks using quantum chemical methods. The experimentally known cubic 3C polytype was found to be the energetically most favorable framework, but the studied hexagonal polytypes (2 H, 4 H, 6 H, 8 H, 10 H) lie energetically close to it. In the case of germanium, the energy difference between the 3C and 6H clathrate-II polytypes is ten times smaller than the difference between the experimentally known 3C-Ge (α-Ge) and 4H-Ge polytypes. The thermoelectric properties of guest-occupied clathrate-II structures were investigated for compositions Na-Rb-Ga-Ge and Ge-As-I. The clathrate-II structures show promising thermoelectric properties and the highest Seebeck coefficients and thermoelectric power factors were predicted for the 3C polytype. The structural anisotropy of the largest studied hexagonal polytypes affects their thermoelectric power factors by over a factor of two. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Polarization effects associated with thermal processing of HY-80 structural steel using high-power laser diode array

NASA Astrophysics Data System (ADS)

Wu, Sheldon S. Q.; Baker, Bradford W.; Rotter, Mark D.; Rubenchik, Alexander M.; Wiechec, Maxwell E.; Brown, Zachary M.; Beach, Raymond J.; Matthews, Manyalibo J.

2017-12-01

Localized heating of roughened steel surfaces using highly divergent laser light emitted from high-power laser diode arrays was experimentally demonstrated and compared with theoretical predictions. Polarization dependence was analyzed using Fresnel coefficients to understand the laser-induced temperature rise of HY-80 steel plates under 383- to 612-W laser irradiation. Laser-induced, transient temperature distributions were directly measured using bulk thermocouple probes and thermal imaging. Finite-element analysis yielded quantitative assessment of energy deposition and heat transport in HY-80 steel using absorptivity as a tuning parameter. The extracted absorptivity values ranged from 0.62 to 0.75 for S-polarized and 0.63 to 0.85 for P-polarized light, in agreement with partially oxidized iron surfaces. Microstructural analysis using electron backscatter diffraction revealed a heat affected zone for the highest temperature conditions (612 W, P-polarized) as evidence of rapid quenching and an austenite to martensite transformation. The efficient use of diode arrays for laser-assisted advanced manufacturing technologies, such as hybrid friction stir welding, is discussed.

α-Oscillations in the monkey sensorimotor network influence discrimination performance by rhythmical inhibition of neuronal spiking.

PubMed

Haegens, Saskia; Nácher, Verónica; Luna, Rogelio; Romo, Ranulfo; Jensen, Ole

2011-11-29

Extensive work in humans using magneto- and electroencephalography strongly suggests that decreased oscillatory α-activity (8-14 Hz) facilitates processing in a given region, whereas increased α-activity serves to actively suppress irrelevant or interfering processing. However, little work has been done to understand how α-activity is linked to neuronal firing. Here, we simultaneously recorded local field potentials and spikes from somatosensory, premotor, and motor regions while a trained monkey performed a vibrotactile discrimination task. In the local field potentials we observed strong activity in the α-band, which decreased in the sensorimotor regions during the discrimination task. This α-power decrease predicted better discrimination performance. Furthermore, the α-oscillations demonstrated a rhythmic relation with the spiking, such that firing was highest at the trough of the α-cycle. Firing rates increased with a decrease in α-power. These findings suggest that α-oscillations exercise a strong inhibitory influence on both spike timing and firing rate. Thus, the pulsed inhibition by α-oscillations plays an important functional role in the extended sensorimotor system.

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.

Emergency preparedness for the accidental release of radionuclides from the Uljin Nuclear Power Plant in Korea.

PubMed

Park, Soon-Ung; Lee, In-Hye; Joo, Seung Jin; Ju, Jae-Won

2017-12-01

Site specific radionuclide dispersion databases were archived for the emergency response to the hypothetical releases of 137 Cs from the Uljin nuclear power plant in Korea. These databases were obtained with the horizontal resolution of 1.5 km in the local domain centered the power plant site by simulations of the Lagrangian Particle Dispersion Model (LPDM) with the Unified Model (UM)-Local Data Assimilation Prediction System (LDAPS). The Eulerian Dispersion Model-East Asia (EDM-EA) with the UM-Global Data Assimilation Prediction System (UM-GDAPS) meteorological models was used to get dispersion databases in the regional domain. The LPDM model was performed for a year with a 5-day interval yielding 72 synoptic time-scale cases in a year. For each case hourly mean near surface concentrations, hourly mean column integrated concentrations, hourly total depositions for 5 consecutive days were archived by the LPDM model in the local domain and by the EDM-EA model in the regional domain of Asia. Among 72 synoptic cases in a year the worst synoptic case that showed the highest mean surface concentration averaged for 5 days in the LPDM model domain was chosen to illustrate the emergency preparedness to the hypothetical accident at the site. The simulated results by the LPDM model with the 137 Cs emission rate of the Fukushima nuclear power plant accident for the first 5-day period were found to be able to provide prerequisite information for the emergency response to the early phase of the accident whereas those of the EDM-EA model could provide information required for the environmental impact assessment of the accident in the regional domain. The archived site-specific database of 72 synoptic cases in a year could have a great potential to be used as a prognostic information on the emergency preparedness for the early phase of accident. Copyright © 2017 Elsevier Ltd. All rights reserved.

Automation in the Space Station module power management and distribution Breadboard

NASA Technical Reports Server (NTRS)

Walls, Bryan; Lollar, Louis F.

1990-01-01

The Space Station Module Power Management and Distribution (SSM/PMAD) Breadboard, located at NASA's Marshall Space Flight Center (MSFC) in Huntsville, Alabama, models the power distribution within a Space Station Freedom Habitation or Laboratory module. Originally designed for 20 kHz ac power, the system is now being converted to high voltage dc power with power levels on a par with those expected for a space station module. In addition to the power distribution hardware, the system includes computer control through a hierarchy of processes. The lowest level process consists of fast, simple (from a computing standpoint) switchgear, capable of quickly safing the system. The next level consists of local load center processors called Lowest Level Processors (LLP's). These LLP's execute load scheduling, perform redundant switching, and shed loads which use more than scheduled power. The level above the LLP's contains a Communication and Algorithmic Controller (CAC) which coordinates communications with the highest level. Finally, at this highest level, three cooperating Artificial Intelligence (AI) systems manage load prioritization, load scheduling, load shedding, and fault recovery and management. The system provides an excellent venue for developing and examining advanced automation techniques. The current system and the plans for its future are examined.

Terra Flexible Blanket Solar Array Deployment, On-Orbit Performance and Future Applications

NASA Technical Reports Server (NTRS)

Kurland, Richard; Schurig, Hans; Rosenfeld, Mark; Herriage, Michael; Gaddy, Edward; Keys, Denney; Faust, Carl; Andiario, William; Kurtz, Michelle; Moyer, Eric;

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

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

NASA Astrophysics Data System (ADS)

Woodland, Brandon Jay

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

Carbon fiber internal pressure vessels

NASA Technical Reports Server (NTRS)

Simon, R. A.

1973-01-01

Internal pressure vessels were designed; the filament was wound of carbon fibers and epoxy resin and tested to burst. The fibers used were Thornel 400, Thornel 75, and Hercules HTS. Additional vessels with type A fiber were made. Polymeric linears were used, and all burst testing was done at room temperature. The objective was to produce vessels with the highest attainable PbV/W efficiencies. The type A vessels showed the highest average efficiency: 2.56 x 10 to the 6th power cm. Next highest efficiency was with Thornel 400 vessels: 2.21 x 10 to the 6th power cm. These values compare favorably with efficiency values from good quality S-glass vessels, but strains averaged 0.97% or less, which is less than 1/3 the strain of S-glass vessels.

Development of machine learning models for diagnosis of glaucoma.

PubMed

Kim, Seong Jae; Cho, Kyong Jin; Oh, Sejong

2017-01-01

The study aimed to develop machine learning models that have strong prediction power and interpretability for diagnosis of glaucoma based on retinal nerve fiber layer (RNFL) thickness and visual field (VF). We collected various candidate features from the examination of retinal nerve fiber layer (RNFL) thickness and visual field (VF). We also developed synthesized features from original features. We then selected the best features proper for classification (diagnosis) through feature evaluation. We used 100 cases of data as a test dataset and 399 cases of data as a training and validation dataset. To develop the glaucoma prediction model, we considered four machine learning algorithms: C5.0, random forest (RF), support vector machine (SVM), and k-nearest neighbor (KNN). We repeatedly composed a learning model using the training dataset and evaluated it by using the validation dataset. Finally, we got the best learning model that produces the highest validation accuracy. We analyzed quality of the models using several measures. The random forest model shows best performance and C5.0, SVM, and KNN models show similar accuracy. In the random forest model, the classification accuracy is 0.98, sensitivity is 0.983, specificity is 0.975, and AUC is 0.979. The developed prediction models show high accuracy, sensitivity, specificity, and AUC in classifying among glaucoma and healthy eyes. It will be used for predicting glaucoma against unknown examination records. Clinicians may reference the prediction results and be able to make better decisions. We may combine multiple learning models to increase prediction accuracy. The C5.0 model includes decision rules for prediction. It can be used to explain the reasons for specific predictions.

High-frequency predictions for number counts and spectral properties of extragalactic radio sources. New evidence of a break at mm wavelengths in spectra of bright blazar sources

NASA Astrophysics Data System (ADS)

Tucci, M.; Toffolatti, L.; de Zotti, G.; Martínez-González, E.

2011-09-01

We present models to predict high-frequency counts of extragalactic radio sources using physically grounded recipes to describe the complex spectral behaviour of blazars that dominate the mm-wave counts at bright flux densities. We show that simple power-law spectra are ruled out by high-frequency (ν ≥ 100 GHz) data. These data also strongly constrain models featuring the spectral breaks predicted by classical physical models for the synchrotron emission produced in jets of blazars. A model dealing with blazars as a single population is, at best, only marginally consistent with data coming from current surveys at high radio frequencies. Our most successful model assumes different distributions of break frequencies, νM, for BL Lacs and flat-spectrum radio quasars (FSRQs). The former objects have substantially higher values of νM, implying that the synchrotron emission comes from more compact regions; therefore, a substantial increase of the BL Lac fraction at high radio frequencies and at bright flux densities is predicted. Remarkably, our best model is able to give a very good fit to all the observed data on number counts and on distributions of spectral indices of extragalactic radio sources at frequencies above 5 and up to 220 GHz. Predictions for the forthcoming sub-mm blazar counts from Planck, at the highest HFI frequencies, and from Herschel surveys are also presented. Appendices are available in electronic form at http://www.aanda.org

Determinants of work ability and its predictive value for disability.

PubMed

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

2009-01-01

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

CAN STABILITY REALLY PREDICT AN IMPENDING SLIP-RELATED FALL AMONG OLDER ADULTS?

PubMed Central

Yang, Feng; Pai, Yi-Chung

2015-01-01

The primary purpose of this study was to systematically evaluate and compare the predictive power of falls for a battery of stability indices, obtained during normal walking among community-dwelling older adults. One hundred and eighty seven community-dwelling older adults participated in the study. After walking regularly for 20 strides on a walkway, participants were subjected to an unannounced slip during gait under the protection of a safety harness. Full body kinematics and kinetics were monitored during walking using a motion capture system synchronized with force plates. Stability variables, including feasible-stability-region measurement, margin of stability, the maximum Floquet multiplier, the Lyapunov exponents (short- and long-term), and the variability of gait parameters (including the step length, step width, and step time) were calculated for each subject. Accuracy of predicting slip outcome (fall vs. recovery) was examined for each stability variable using logistic regression. Results showed that the feasible-stability-region measurement predicted fall incidence among these subjects with the highest accuracy (68.4%). Except for the step width (with an accuracy of 60.2%), no other stability variables could differentiate fallers from those who did not fall for the sample studied in this study. The findings from the present study could provide guidance to identify individuals at increased risk of falling using the feasible-stability-region measurement or variability of the step width. PMID:25458148

Generation of switchable domain wall and Cubic-Quintic nonlinear Schrödinger equation dark pulse

NASA Astrophysics Data System (ADS)

Tiu, Z. C.; Suthaskumar, M.; Zarei, A.; Tan, S. J.; Ahmad, H.; Harun, S. W.

2015-10-01

A switchable domain-wall (DW) and Cubic-Quintic nonlinear Schrödinger equation (CQNLSE) dark soliton pulse generation are demonstrated in Erbium-doped fiber laser (EDFL) for the first time. The DW pulse train operates at 1575 nm with a fundamental repetition rate of 1.52 MHz and pulse width of 203 ns as the pump power is increased above the threshold pump power of 80 mW. The highest pulse energy of 2.24 nJ is obtained at the maximum pump power of 140 mW. CQNLSE pulse can also be realized from the same cavity by adjusting the polarization state but at a higher threshold pump power of 104 mW. The repetition rate and pulse width of the CQNLSE dark pulses are obtained at 1.52 MHz and 219 ns, respectively. The highest energy of 0.58 nJ is obtained for the CQNLSE pulse at pump power of 140 mW.

Precipitation Cluster Distributions: Current Climate Storm Statistics and Projected Changes Under Global Warming

NASA Astrophysics Data System (ADS)

Quinn, Kevin Martin

The total amount of precipitation integrated across a precipitation cluster (contiguous precipitating grid cells exceeding a minimum rain rate) is a useful measure of the aggregate size of the disturbance, expressed as the rate of water mass lost or latent heat released, i.e. the power of the disturbance. Probability distributions of cluster power are examined during boreal summer (May-September) and winter (January-March) using satellite-retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) 3B42 and Special Sensor Microwave Imager and Sounder (SSM/I and SSMIS) programs, model output from the High Resolution Atmospheric Model (HIRAM, roughly 0.25-0.5 0 resolution), seven 1-2° resolution members of the Coupled Model Intercomparison Project Phase 5 (CMIP5) experiment, and National Center for Atmospheric Research Large Ensemble (NCAR LENS). Spatial distributions of precipitation-weighted centroids are also investigated in observations (TRMM-3B42) and climate models during winter as a metric for changes in mid-latitude storm tracks. Observed probability distributions for both seasons are scale-free from the smallest clusters up to a cutoff scale at high cluster power, after which the probability density drops rapidly. When low rain rates are excluded by choosing a minimum rain rate threshold in defining clusters, the models accurately reproduce observed cluster power statistics and winter storm tracks. Changes in behavior in the tail of the distribution, above the cutoff, are important for impacts since these quantify the frequency of the most powerful storms. End-of-century cluster power distributions and storm track locations are investigated in these models under a "business as usual" global warming scenario. The probability of high cluster power events increases by end-of-century across all models, by up to an order of magnitude for the highest-power events for which statistics can be computed. For the three models in the suite with continuous time series of high resolution output, there is substantial variability on when these probability increases for the most powerful precipitation clusters become detectable, ranging from detectable within the observational period to statistically significant trends emerging only after 2050. A similar analysis of National Centers for Environmental Prediction (NCEP) Reanalysis 2 and SSM/I-SSMIS rain rate retrievals in the recent observational record does not yield reliable evidence of trends in high-power cluster probabilities at this time. Large impacts to mid-latitude storm tracks are projected over the West Coast and eastern North America, with no less than 8 of the 9 models examined showing large increases by end-of-century in the probability density of the most powerful storms, ranging up to a factor of 6.5 in the highest range bin for which historical statistics are computed. However, within these regional domains, there is considerable variation among models in pinpointing exactly where the largest increases will occur.

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…

High-efficiency, 154  W CW, diode-pumped Raman fiber laser with brightness enhancement.

PubMed

Glick, Yaakov; Fromzel, Viktor; Zhang, Jun; Ter-Gabrielyan, Nikolay; Dubinskii, Mark

2017-01-20

We demonstrate a high-power, high-efficiency Raman fiber laser pumped directly by laser diode modules at 978 nm. 154 W of CW power were obtained at a wavelength of 1023 nm with an optical to optical efficiency of 65%. A commercial graded-index (GRIN) core fiber acts as the Raman fiber in a power oscillator configuration, which includes spectral selection to prevent generation of the second Stokes. In addition, brightness enhancement of the pump beam by a factor of 8.4 is attained due to the Raman gain distribution profile in the GRIN fiber. To the best of our knowledge this is the highest power and highest efficiency Raman fiber laser demonstrated in any configuration allowing brightness enhancement (i.e., in either cladding-pumped configuration or with GRIN fibers, excluding step-index core pumped), regardless of pumping scheme (i.e., either diode pumped or fiber laser pumped).

High power eye-safe Er3+:YVO4 laser diode-pumped at 976 nm and emitting at 1603 nm

NASA Astrophysics Data System (ADS)

Newburgh, G. A.; Dubinskii, M.

2016-02-01

We report on the performance of an eye-safe laser based on a Er:YVO4 single crystal, diode-pumped at 976 nm (4I15/2-->4I11/2 transition) and operating at 1603 nm (4I13/2-->4I15/2 transition) with good beam quality. A 10 mm long Er3+:YVO4 slab, cut with its c-axis perpendicular to the laser cavity axis, was pumped in σ-polarization and lased in π-polarization. The laser operated in a quasi-continuous wave (Q-CW) regime with nearly 9 W output power, and with a slope efficiency of about 39% with respect to absorbed power. This is believed to be the highest efficiency and highest power achieved from an Er3+:YVO4 laser pumped in the 970-980 nm absorption band.

Characterization Report on Fuels for NEAMS Model Validation

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

Gofryk, Krzysztof

Nearly 20% of the world’s electricity today is generated by nuclear energy from uranium dioxide (UO 2) fuel. The thermal conductivity of UO 2 governs the conversion of heat produced from fission events into electricity and it is an important parameter in reactor design and safety. While nuclear fuel operates at high to very high temperatures, thermal conductivity and other materials properties lack sensitivity to temperature variations and to material variations at reactor temperatures. As a result, both the uncertainties in laboratory measurements at high temperatures and the small differences in properties of different materials inevitably lead to large uncertaintiesmore » in models and little predictive power. Conversely, properties measured at low to moderate temperatures have more sensitivity, less uncertainty, and have larger differences in properties for different materials. These variations need to be characterized as they will afford the highest predictive capability in modeling and offer best assurances for validation and verification at all temperatures. This is well emphasized in the temperature variation of the thermal conductivity of UO 2.« less

A Low-Cost Method for Multiple Disease Prediction.

PubMed

Bayati, Mohsen; Bhaskar, Sonia; Montanari, Andrea

Recently, in response to the rising costs of healthcare services, employers that are financially responsible for the healthcare costs of their workforce have been investing in health improvement programs for their employees. A main objective of these so called "wellness programs" is to reduce the incidence of chronic illnesses such as cardiovascular disease, cancer, diabetes, and obesity, with the goal of reducing future medical costs. The majority of these wellness programs include an annual screening to detect individuals with the highest risk of developing chronic disease. Once these individuals are identified, the company can invest in interventions to reduce the risk of those individuals. However, capturing many biomarkers per employee creates a costly screening procedure. We propose a statistical data-driven method to address this challenge by minimizing the number of biomarkers in the screening procedure while maximizing the predictive power over a broad spectrum of diseases. Our solution uses multi-task learning and group dimensionality reduction from machine learning and statistics. We provide empirical validation of the proposed solution using data from two different electronic medical records systems, with comparisons to a statistical benchmark.

Application of the NEXT Ion Thruster Lifetime Assessment to Thruster Throttling

NASA Technical Reports Server (NTRS)

VanNoord, Jonathan L.; Herman, Daniel A.

2010-01-01

Ion thrusters are low thrust, high specific impulse devices with typical operational lifetimes of 10,000 to 30,000 hr over a range of throttling conditions. The NEXT ion thruster is the latest generation of ion thrusters under development. The NEXT ion thruster currently has a qualification level propellant throughput requirement of 450 kg of xenon, which corresponds to roughly 22,000 hr of operation at the highest input power throttling point. This paper will provide a brief review the previous life assessment predictions for various throttling conditions. A further assessment will be presented examining the anticipated accelerator grid hole wall erosion and related electron backstreaming limit. The continued assessment of the NEXT ion thruster indicates that the first failure mode across the throttling range is expected to be in excess of 36,000 hr of operation from charge exchange induced groove erosion. It is at this duration that the groove is predicted to penetrate the accelerator grid possibly resulting in structural failure. Based on these lifetime and mission assessments, a throttling approach is presented for the Long Duration Test to demonstrate NEXT thruster lifetime and validate modeling.

Prediction of protein subcellular locations by GO-FunD-PseAA predictor.

PubMed

Chou, Kuo-Chen; Cai, Yu-Dong

2004-08-06

The localization of a protein in a cell is closely correlated with its biological function. With the explosion of protein sequences entering into DataBanks, it is highly desired to develop an automated method that can fast identify their subcellular location. This will expedite the annotation process, providing timely useful information for both basic research and industrial application. In view of this, a powerful predictor has been developed by hybridizing the gene ontology approach [Nat. Genet. 25 (2000) 25], functional domain composition approach [J. Biol. Chem. 277 (2002) 45765], and the pseudo-amino acid composition approach [Proteins Struct. Funct. Genet. 43 (2001) 246; Erratum: ibid. 44 (2001) 60]. As a showcase, the recently constructed dataset [Bioinformatics 19 (2003) 1656] was used for demonstration. The dataset contains 7589 proteins classified into 12 subcellular locations: chloroplast, cytoplasmic, cytoskeleton, endoplasmic reticulum, extracellular, Golgi apparatus, lysosomal, mitochondrial, nuclear, peroxisomal, plasma membrane, and vacuolar. The overall success rate of prediction obtained by the jackknife cross-validation was 92%. This is so far the highest success rate performed on this dataset by following an objective and rigorous cross-validation procedure.

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

PubMed

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

2013-01-01

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

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.

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

PubMed

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

2012-01-01

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

Comparative study of plasma-deposited fluorocarbon coatings on different substrates

NASA Astrophysics Data System (ADS)

Farsari, E.; Kostopoulou, M.; Amanatides, E.; Mataras, D.; Rapakoulias, D. E.

2011-05-01

The deposition of hydrophobic fluorocarbon coatings from C2F6 and C2F6-H2 rf discharges on different substrates was examined. Polyester textile, glass and two different ceramic compounds were used as substrates. The effect of the total gas pressure, the rf power dissipation and the deposition time on the hydrophobic character of the samples was investigated. Films deposited on polyester textiles at low pressure (0.03 mbar) and power consumption (16 mW cm-2) using pure C2F6 presented the highest water contact angles (~150°). On the other hand, the addition of hydrogen was necessary in order to deposit stable hydrophobic coatings on glass and ceramic substrates. Coatings deposited on glass at intermediate deposition rates (~100 Å min-1) and pressures presented the highest angles (~105°). Concerning the heavy clay ceramics, samples treated in low-pressure (0.05 mbar) and low-power (16 mW cm-2) discharges showed the highest contact angles. The deposition time was found to play an important role in the hydrophobicity and long-term behaviour of porous and rough substrates.

Steady-State Thermal-Hydraulics Analyses for the Conversion of BR2 to Low Enriched Uranium Fuel

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

Licht, J.; Bergeron, A.; Dionne, B.

The code PLTEMP/ANL version 4.2 was used to perform the steady-state thermal-hydraulic analyses of the BR2 research reactor for conversion from Highly-Enriched to Low Enriched Uranium fuel (HEU and LEU, respectively). Calculations were performed to evaluate different fuel assemblies with respect to the onset of nucleate boiling (ONB), flow instability (FI), critical heat flux (CHF) and fuel temperature at beginning of cycle conditions. The fuel assemblies were characteristic of fresh fuel (0% burnup), highest heat flux (16% burnup), highest power (32% burnup) and highest burnup (46% burnup). Results show that the high heat flux fuel element is limiting for ONB,more » FI, and CHF, for both HEU and LEU fuel, but that the high power fuel element produces similar margin in a few cases. The maximum fuel temperature similarly occurs in both the high heat flux and high power fuel assemblies for both HEU and LEU fuel. A sensitivity study was also performed to evaluate the variation in fuel temperature due to uncertainties in the thermal conductivity degradation associated with burnup.« less

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.

Prediction of Potential Hit Song and Musical Genre Using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Monterola, Christopher; Abundo, Cheryl; Tugaff, Jeric; Venturina, Lorcel Ericka

Accurately quantifying the goodness of music based on the seemingly subjective taste of the public is a multi-million industry. Recording companies can make sound decisions on which songs or artists to prioritize if accurate forecasting is achieved. We extract 56 single-valued musical features (e.g. pitch and tempo) from 380 Original Pilipino Music (OPM) songs (190 are hit songs) released from 2004 to 2006. Based on an effect size criterion which measures a variable's discriminating power, the 20 highest ranked features are fed to a classifier tasked to predict hit songs. We show that regardless of musical genre, a trained feed-forward neural network (NN) can predict potential hit songs with an average accuracy of ΦNN = 81%. The accuracy is about +20% higher than those of standard classifiers such as linear discriminant analysis (LDA, ΦLDA = 61%) and classification and regression trees (CART, ΦCART = 57%). Both LDA and CART are above the proportional chance criterion (PCC, ΦPCC = 50%) but are slightly below the suggested acceptable classifier requirement of 1.25*ΦPCC = 63%. Utilizing a similar procedure, we demonstrate that different genres (ballad, alternative rock or rock) of OPM songs can be automatically classified with near perfect accuracy using LDA or NN but only around 77% using CART.

Association of increased total antioxidant capacity and anovulation in nonobese infertile patients with clomiphene citrate-resistant polycystic ovary syndrome.

PubMed

Verit, Fatma Ferda; Erel, Ozcan; Kocyigit, Abdurrahim

2007-08-01

To investigate whether total antioxidant capacity (TAC) could predict the response to ovulation induction to clomiphene citrate (CC) in nonobese women with polycystic ovary syndrome. Prospective longitudinal follow-up study. Academic hospital. Fifty-five nonobese, oligomenorrheic women with polycystic ovary syndrome and normal indices of insulin sensitivity. None. Standard clinical examinations and ultrasonographic and endocrine screening, including FSH, LH, E(2), P, total T, sex hormone-binding globulin, DHEAS, and TAC were performed before initiation of CC medication. Within the total group, 27 (49%) of the patients did not ovulate at the end of follow-up. TAC, free androgen index, and ovarian volume were all significantly different in CC nonresponders from those in responders. Total antioxidant capacity was found to be the best predictor in univariate analysis (odds ratio, 171.55; 95% confidence interval, 10.61-2,772.93), and it had the highest area in the receiver operating characteristics analysis (0.91). In a multivariate prediction model, TAC, free androgen index, and ovarian volume showed good predictive power, with Hosmer-Lemeshow goodness of fit test of 0.80. Total antioxidant capacity was the strongest predictor of ovarian response during CC induction of ovulation in these patients. It can be concluded that TAC can be used as a routine screening test.

49 CFR 250.5 - General instructions.

Code of Federal Regulations, 2010 CFR

2010-10-01

... to the effect that he is familiar with the corporate powers of the carrier applicant and the orders... obligations of the Trustee will be treated as an expense of administration and receive the highest lien on the... be treated as an expense of administration and receive the highest lien on the railroad's property...

Associations Between Balance and Muscle Strength, Power Performance in Male Youth Athletes of Different Maturity Status.

PubMed

Hammami, Raouf; Chaouachi, Anis; Makhlouf, Issam; Granacher, Urs; Behm, David G

2016-11-01

Balance, strength and power relationships may contain important information at various maturational stages to determine training priorities. The objective was to examine maturity-specific relationships of static/dynamic balance with strength and power measures in young male athletes. Soccer players (N = 130) aged 10-16 were assessed with the Stork and Y balance (YBT) tests. Strength/power measures included back extensor muscle strength, standing long jump (SLJ), countermovement jump (CMJ), and 3-hop jump tests. Associations between balance with strength/power variables were calculated according to peak-height-velocity (PHV). There were significant medium-large sized correlations between all balance measures with back extensor strength (r = .486-.791) and large associations with power (r = .511-.827). These correlation coefficients were significantly different between pre-PHV and circa PHV as well as pre-PHV and post-PHV with larger associations in the more mature groups. Irrespective of maturity-status, SLJ was the best strength/power predictor with the highest proportion of variance (12-47%) for balance (i.e., Stork eyes opened) and the YBT was the best balance predictor with the highest proportion of variance (43-78%) for all strength/power variables. The associations between balance and muscle strength/power measures in youth athletes that increase with maturity may imply transfer effects from balance to strength/power training and vice versa in youth athletes.

Differences in the associations of anthropometric measures with insulin resistance and type 2 diabetes mellitus between Korean and US populations: Comparisons of representative nationwide sample data.

PubMed

Yoon, Yeong Sook; Choi, Han Seok; Kim, Jin Kuk; Kim, Yu Il; Oh, Sang Woo

Variation among ethnic groups in the association between obesity and insulin resistance (IR)/diabetes has been suggested, but studies reported inconsistent results. We evaluated ethnic differences in the association between obesity and insulin resistance (IR)/diabetes. We conducted a cross-sectional analysis using Korea (n=18,845) and the USA (n=4657) National Health and Nutrition Examination Survey(NHANES) 2007-2010. We performed statistical comparisons of AUC-ROC (area under the curve in a receiver operating characteristic curve) values for body mass index (BMI), waist circumference (WC) and homeostasis model assessment of insulin resistance (HOMA-IR) to predict IR or diabetes among different ethnic groups. AUC-ROC values for BMI and WC for predicting IR were highest in Whites (0.8324 and 0.8468) and lowest in Koreans (0.7422 and 0.7367). Whites showed the highest AUC-ROC values for BMI (0.6869) and WC (0.7421) for predicting diabetes, while the AUC-ROC for HOMA-IR was highest in Koreans (0.8861). Linear regression showed significant interactions between ethnicity and the main effects (all P<0.0001). Increases in BMI were associated with a larger increase in HOMA-IR in Whites (β=0.0719) and WC in Hispanics (β=0.0324), while BMI was associated with a larger increase in fasting glucose in Koreans (β=0.8279) and WC in Blacks (β=0.4037). In addition, the slope for fasting glucose with increasing HOMA-IR was steeper in Koreans (β=16.5952, P<0.001) than in other groups. The ability of BMI and WC to predict IR and diabetes was highest in Whites, while the ability of HOMA-IR to predict diabetes was highest in Koreans. Copyright © 2015 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

Discussions On Worst-Case Test Condition For Single Event Burnout

NASA Astrophysics Data System (ADS)

Liu, Sandra; Zafrani, Max; Sherman, Phillip

2011-10-01

This paper discusses the failure characteristics of single- event burnout (SEB) on power MOSFETs based on analyzing the quasi-stationary avalanche simulation curves. The analyses show the worst-case test condition for SEB would be using the ion that has the highest mass that would result in the highest transient current due to charge deposition and displacement damage. The analyses also show it is possible to build power MOSFETs that will not exhibit SEB even when tested with the heaviest ion, which have been verified by heavy ion test data on SEB sensitive and SEB immune devices.

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.

Study on Safety Monitoring System for Submarine Power Cable on the Basis of AIS and Radar Technology

NASA Astrophysics Data System (ADS)

Jie, Wang; Yao-Tian, Fan

Through analyzing the risks of submarine power cable, the highest risk to damage the cable identified is from ship. Based on concept of Vessel Traffic Management Information Systems, the three core sub-systems of safety monitoring system for submarine power cable were studied and described, also some suggestions were given.

High-Power Hall Thruster Technology Evaluated for Primary Propulsion Applications

NASA Technical Reports Server (NTRS)

Manzella, David H.; Jankovsky, Robert S.; Hofer, Richard R.

2003-01-01

High-power electric propulsion systems have been shown to be enabling for a number of NASA concepts, including piloted missions to Mars and Earth-orbiting solar electric power generation for terrestrial use (refs. 1 and 2). These types of missions require moderate transfer times and sizable thrust levels, resulting in an optimized propulsion system with greater specific impulse than conventional chemical systems and greater thrust than ion thruster systems. Hall thruster technology will offer a favorable combination of performance, reliability, and lifetime for such applications if input power can be scaled by more than an order of magnitude from the kilowatt level of the current state-of-the-art systems. As a result, the NASA Glenn Research Center conducted strategic technology research and development into high-power Hall thruster technology. During program year 2002, an in-house fabricated thruster, designated the NASA-457M, was experimentally evaluated at input powers up to 72 kW. These tests demonstrated the efficacy of scaling Hall thrusters to high power suitable for a range of future missions. Thrust up to nearly 3 N was measured. Discharge specific impulses ranged from 1750 to 3250 sec, with discharge efficiencies between 46 and 65 percent. This thruster is the highest power, highest thrust Hall thruster ever tested.

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

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.

A Model Parameter Extraction Method for Dielectric Barrier Discharge Ozone Chamber using Differential Evolution

NASA Astrophysics Data System (ADS)

Amjad, M.; Salam, Z.; Ishaque, K.

2014-04-01

In order to design an efficient resonant power supply for ozone gas generator, it is necessary to accurately determine the parameters of the ozone chamber. In the conventional method, the information from Lissajous plot is used to estimate the values of these parameters. However, the experimental setup for this purpose can only predict the parameters at one operating frequency and there is no guarantee that it results in the highest ozone gas yield. This paper proposes a new approach to determine the parameters using a search and optimization technique known as Differential Evolution (DE). The desired objective function of DE is set at the resonance condition and the chamber parameter values can be searched regardless of experimental constraints. The chamber parameters obtained from the DE technique are validated by experiment.

Wave energy absorption by a submerged air bag connected to a rigid float.

PubMed

Kurniawan, A; Chaplin, J R; Hann, M R; Greaves, D M; Farley, F J M

2017-04-01

A new wave energy device features a submerged ballasted air bag connected at the top to a rigid float. Under wave action, the bag expands and contracts, creating a reciprocating air flow through a turbine between the bag and another volume housed within the float. Laboratory measurements are generally in good agreement with numerical predictions. Both show that the trajectory of possible combinations of pressure and elevation at which the device is in static equilibrium takes the shape of an S. This means that statically the device can have three different draughts, and correspondingly three different bag shapes, for the same pressure. The behaviour in waves depends on where the mean pressure-elevation condition is on the static trajectory. The captured power is highest for a mean condition on the middle section.

Wave energy absorption by a submerged air bag connected to a rigid float

PubMed Central

Chaplin, J. R.; Hann, M. R.; Greaves, D. M.; Farley, F. J. M.

2017-01-01

A new wave energy device features a submerged ballasted air bag connected at the top to a rigid float. Under wave action, the bag expands and contracts, creating a reciprocating air flow through a turbine between the bag and another volume housed within the float. Laboratory measurements are generally in good agreement with numerical predictions. Both show that the trajectory of possible combinations of pressure and elevation at which the device is in static equilibrium takes the shape of an S. This means that statically the device can have three different draughts, and correspondingly three different bag shapes, for the same pressure. The behaviour in waves depends on where the mean pressure-elevation condition is on the static trajectory. The captured power is highest for a mean condition on the middle section. PMID:28484330

Wave energy absorption by a submerged air bag connected to a rigid float

NASA Astrophysics Data System (ADS)

Kurniawan, A.; Chaplin, J. R.; Hann, M. R.; Greaves, D. M.; Farley, F. J. M.

2017-04-01

A new wave energy device features a submerged ballasted air bag connected at the top to a rigid float. Under wave action, the bag expands and contracts, creating a reciprocating air flow through a turbine between the bag and another volume housed within the float. Laboratory measurements are generally in good agreement with numerical predictions. Both show that the trajectory of possible combinations of pressure and elevation at which the device is in static equilibrium takes the shape of an S. This means that statically the device can have three different draughts, and correspondingly three different bag shapes, for the same pressure. The behaviour in waves depends on where the mean pressure-elevation condition is on the static trajectory. The captured power is highest for a mean condition on the middle section.

Validity, accuracy, and predictive value of urinary tract infection signs and symptoms in individuals with spinal cord injury on intermittent catheterization.

PubMed

Massa, Luiz M; Hoffman, Jeanne M; Cardenas, Diana D

2009-01-01

To determine the validity, accuracy, and predictive value of the signs and symptoms of urinary tract infection (UTI) for individuals with spinal cord injury (SCI) using intermittent catheterization (IC) and the accuracy of individuals with SCI on IC at predicting their own UTI. Prospective cohort based on data from the first 3 months of a 1-year randomized controlled trial to evaluate UTI prevention effectiveness of hydrophilic and standard catheters. Fifty-six community-based individuals on IC. Presence of UTI as defined as bacteriuria with a colony count of at least 10(5) colony-forming units/mL and at least 1 sign or symptom of UTI. Analysis of monthly urine culture and urinalysis data combined with analysis of monthly data collected using a questionnaire that asked subjects to self-report on UTI signs and symptoms and whether or not they felt they had a UTI. Overall, "cloudy urine" had the highest accuracy (83.1%), and "leukocytes in the urine" had the highest sensitivity (82.8%). The highest specificity was for "fever" (99.0%); however, it had a very low sensitivity (6.9%). Subjects were able to predict their own UTI with an accuracy of 66.2%, and the negative predictive value (82.8%) was substantially higher than the positive predictive value (32.6%). The UTI signs and symptoms can predict a UTI more accurately than individual subjects can by using subjective impressions of their own signs and symptoms. Subjects were better at predicting when they did not have a UTI than when they did have a UTI.

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.

NEXT Long-Duration Test Plume and Wear Characteristics after 16,550 h of Operation and 337 kg of Xenon Processed

NASA Technical Reports Server (NTRS)

Herman, Daniel A.; Soulas, George C.; Patterson, Michael J.

2009-01-01

The NASA s Evolutionary Xenon Thruster (NEXT) program is developing the next-generation ion propulsion system with significant enhancements beyond the state-of-the-art. The NEXT ion propulsion system provides improved mission capabilities for future NASA science missions to enhance and enable Discovery, New Frontiers, and Flagship-type NASA missions. As part of a comprehensive thruster service life assessment utilizing both testing and analyses, a Long-Duration Test (LDT) was initiated to validate and qualify the NEXT propellant throughput capability to a qualification-level of 450 kg, 1.5 times the mission-derived throughput requirement of 300 kg. This wear test is being conducted with a modified, flight-representative NEXT engineering model ion thruster, designated EM3. As of June 25, 2008, the thruster has accumulated 16,550 h of operation: the first 13,042 h at the thruster full-input-power of 6.9 kW with 3.52 A beam current and 1800 V beam power supply voltage. Operation since 13,042 h, i.e., the most recent 3,508 h, has been at an input power of 4.7 kW with 3.52 A beam current and 1180 V beam power supply voltage. The thruster has processed 337 kg of xenon (Xe) surpassing the NSTAR propellant throughput demonstrated during the extended life testing of the Deep Space 1 flight spare. The NEXT LDT has demonstrated a total impulse of 13.3 106 N s; the highest total impulse ever demonstrated by an ion thruster. Thruster plume diagnostics and erosion measurements are obtained periodically over the entire NEXT throttle table with input power ranging 0.5 to 6.9 kW. Observed thruster component erosion rates are consistent with predictions and the thruster service life assessment. There have not been any observed anomalous erosion and all erosion estimates indicate a thruster throughput capability that exceeds 750 kg of Xe, an equivalent of 36,500 h of continuous operation at the full-power operating condition. This paper presents the erosion measurements and plume diagnostic results for the NEXT LDT to date with emphasis on the change in thruster operating condition and resulting impact on wear characteristics. Ion optics grid-gap data, both cold and operating, are presented. Performance and wear predictions for the LDT throttle profile are presented.

Polygenic hazard scores in preclinical Alzheimer disease.

PubMed

Tan, Chin Hong; Hyman, Bradley T; Tan, Jacinth J X; Hess, Christopher P; Dillon, William P; Schellenberg, Gerard D; Besser, Lilah M; Kukull, Walter A; Kauppi, Karolina; McEvoy, Linda K; Andreassen, Ole A; Dale, Anders M; Fan, Chun Chieh; Desikan, Rahul S

2017-09-01

Identifying asymptomatic older individuals at elevated risk for developing Alzheimer disease (AD) is of clinical importance. Among 1,081 asymptomatic older adults, a recently validated polygenic hazard score (PHS) significantly predicted time to AD dementia and steeper longitudinal cognitive decline, even after controlling for APOE ɛ4 carrier status. Older individuals in the highest PHS percentiles showed the highest AD incidence rates. PHS predicted longitudinal clinical decline among older individuals with moderate to high Consortium to Establish a Registry for Alzheimer's Disease (amyloid) and Braak (tau) scores at autopsy, even among APOE ɛ4 noncarriers. Beyond APOE, PHS may help identify asymptomatic individuals at highest risk for developing Alzheimer neurodegeneration. Ann Neurol 2017;82:484-488. © 2017 American Neurological Association.

Children's externalizing and internalizing symptoms over time: the role of individual differences in patterns of RSA responding.

PubMed

Hinnant, James Benjamin; El-Sheikh, Mona

2009-11-01

We examined associations between basal respiratory sinus arrhythmia (RSA) in conjunction with RSA regulation with the hypothesis that their interaction would explain unique variability in children's prospective adjustment 2 years later. Participants were 176 children (98 girls; 78 boys) in middle childhood. RSA regulation was assessed through social and problem-solving challenges. Parents reported on children's internalizing and externalizing symptoms. Interactions between RSA baseline and regulation to the social stressor predicted children's later internalizing symptoms. Interactions between RSA baseline and responding to the problem-solving stressor predicted children's externalizing symptoms. The highest levels of internalizing symptoms were predicted for children with both lower basal RSA and higher RSA suppression. The highest levels of externalizing symptoms were predicted for children who demonstrated lower basal RSA in conjunction with RSA augmentation. Findings highlight the importance of the contemporaneous consideration of basal RSA and RSA regulation in the prediction of developmental psychopathology symptomology.

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.

A comparison of pairs figure skaters in repeated jumps.

PubMed

Sands, William A; Kimmel, Wendy L; McNeal, Jeni R; Murray, Steven Ross; Stone, Michael H

2012-01-01

Trends in pairs figure skating have shown that increasingly difficult jumps have become an essential aspect of high-level performance, especially in the latter part of a competitive program. We compared a repeated jump power index in a 60 s repeated jump test to determine the relationship of repeated jump test to competitive rank and to measure 2D hip, knee, and ankle angles and angular velocities at 0, 20, 40, and 60 s. Eighteen National Team Pairs Figure Skaters performed a 60 s repeated jump test on a large switch-mat with timing of flight and ground durations and digital video recording. Each 60-s period was divided into 6, 10-s intervals, with power indexes (W/kg) calculated for each 10-s interval. Power index by 10-s interval repeated measures ANOVAs (RMANOVA) showed that males exceeded females at all intervals, and the highest power index interval was during 10 to 20 s for both sexes. RMANOVAs of angles and angular velocities showed main effects for time only. Power index and jumping techniques among figure skaters showed rapid and steady declines over the test duration. Power index can predict approximately 50% of competitive rank variance, and sex differences in jumping technique were rare. Key pointsThe repeated jumps test can account for about 50% of the variance in pairs ranks.Changes in technique are largely due to fatigue, but the athletes were able to maintain a maximum flexion knee angle very close to the desired 90 degrees. Changes in angular velocity and jump heights occurred as expected, again probably due to fatigue.As expected from metabolic information, the athletes' power indexes peak around 20s and decline thereafter. Coaches should be aware of this time as a boundary beyond which fatigue becomes more manifest, and use careful choreographic choices to provide rest periods that are disguised as less demanding skating elements to afford recovery.The repeated jumps test may be a helpful off-ice test of power-endurance for figure skaters.

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.

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

Conversion of municipal solid wastes to carboxylic acids by thermophilic fermentation.

PubMed

Chan, Wen Ning; Holtzapple, Mark T

2003-11-01

The purpose of this research is to generate carboxylic acids from the biodegradable fraction of municipal solid wastes (MSW) and municipal sewage sludge (MSS) by using a thermophilic (55 degrees C), anaerobic, high-solid fermentation. With terrestrial inocula, the highest total carboxylic acid concentration achieved was 20.5 g/L, the highest conversion obtained was 69%, and the highest acetic acid selectivity was 86.4%. Marine inocula were also used to compare against terrestrial sources. Continuum particle distribution modeling (CPDM) was used to predict the final acid product concentrations and substrate conversions at a wide range of liquid residence times (LRT) and volatile solid loading rates (VSLR). "Maps" showing the product concentration and conversion for various LRT and VSLR were generated from CPDM. The predictions were compared to the experimental results. On average, the difference between the predicted and experimental values were 13% for acid concentration and 10% for conversion. CPDM "maps" show that marine inocula produce higher concentrations than terrestrial inocula.

Cadmium recovery by coupling double microbial fuel cells.

PubMed

Choi, Chansoo; Hu, Naixu; Lim, Bongsu

2014-10-01

Cr(VI)-MFC of the double microbial fuel cell (d-MFC) arrangement could successfully complement the insufficient voltage and power needed to recover cadmium metal from Cd(II)-MFC, which operated as a redox-flow battery. It was also possible to drain electrical energy from the d-MFC by an additional passage. The highest maximum utilization power density (22.5Wm(-2)) of Cr(VI)-MFC, with the cathode optimized with sulfate buffer, was 11.3times higher than the highest power density directly supplied to Cd(II)-MFC (2.0Wm(-2)). Cr(VI)-MFC could generate 3times higher power with the additional passage than without it; and the current density for the former was 4.2times higher than the latter at the same maximum power point (38.0Am(-2) vs. 9.0Am(-2)). This boosting phenomenon could be explained by the Le Chatelier's principle, which addresses the rate of electron-hole pair formation that can be accelerated by quickly removing electrons generated by microorganisms. Copyright © 2014 Elsevier Ltd. All rights reserved.

Medium power amplifiers covering 90 - 130 GHz for telescope local oscillators

NASA Technical Reports Server (NTRS)

Samoska, Lorene A.; Bryerton, Eric; Pukala, David; Peralta, Alejandro; Hu, Ming; Schmitz, Adele

2005-01-01

This paper describes a set of power amplifier (PA) modules containing InP High Electron Mobility Transistor (HEMT) Monolithic Millimeter-wave Integrated Circuit (MMIC) chips. The chips were designed and optimized for local oscillator sources in the 90-130 GHz band for the Atacama Large Millimeter Array telescope. The modules feature 20-45 mW of output power, to date the highest power from solid state HEMT MMIC modules above 110 GHz.

Magnetic Resonance Imaging of Intracranial Hypotension: Diagnostic Value of Combined Qualitative Signs and Quantitative Metrics.

PubMed

Aslan, Kerim; Gunbey, Hediye Pinar; Tomak, Leman; Ozmen, Zafer; Incesu, Lutfi

The aim of this study was to investigate whether the use of combination quantitative metrics (mamillopontine distance [MPD], pontomesencephalic angle, and mesencephalon anterior-posterior/medial-lateral diameter ratios) with qualitative signs (dural enhancement, subdural collections/hematoma, venous engorgement, pituitary gland enlargements, and tonsillar herniations) provides a more accurate diagnosis of intracranial hypotension (IH). The quantitative metrics and qualitative signs of 34 patients and 34 control subjects were assessed by 2 independent observers. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of quantitative metrics and qualitative signs, and for the diagnosis of IH, optimum cutoff values of quantitative metrics were found with ROC analysis. Combined ROC curve was measured for the quantitative metrics, and qualitative signs combinations in determining diagnostic accuracy and sensitivity, specificity, and positive and negative predictive values were found, and the best model combination was formed. Whereas MPD and pontomesencephalic angle were significantly lower in patients with IH when compared with the control group (P < 0.001), mesencephalon anterior-posterior/medial-lateral diameter ratio was significantly higher (P < 0.001). For qualitative signs, the highest individual distinctive power was dural enhancement with area under the ROC curve (AUC) of 0.838. For quantitative metrics, the highest individual distinctive power was MPD with AUC of 0.947. The best accuracy in the diagnosis of IH was obtained by combination of dural enhancement, venous engorgement, and MPD with an AUC of 1.00. This study showed that the combined use of dural enhancement, venous engorgement, and MPD had diagnostic accuracy of 100 % for the diagnosis of IH. Therefore, a more accurate IH diagnosis can be provided with combination of quantitative metrics with qualitative signs.

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

Power conditioning system modelling for nuclear electric propulsion

NASA Astrophysics Data System (ADS)

Metcalf, Kenneth J.

1993-11-01

NASA LeRC is currently developing a Fortran based model of a complete nuclear electric propulsion (NEP) vehicle that would be used for piloted and cargo missions to the Moon or Mars. The proposed vehicle design will use either a Brayton or K-Rankine power conversion cycle to drive a turbine coupled with a rotary alternator. Two thruster types are also being studied, ion and magnetoplasmadynamic (MPD). In support of this NEP model, Rocketdyne developed a power management and distribution (PMAD) subroutine that provides parametric outputs for selected alternator operating voltages and frequencies, thruster types, system power levels, and electronics coldplate temperatures. The end-to-end PMAD model described is based on the direct use of the alternator voltage and frequency for transmitting power to either ion or MPD thrusters. This low frequency transmission approach was compared with dc and high frequency ac designs, and determined to have the lowest mass, highest efficiency, highest reliability and lowest development costs. While its power quality is not as good as that provided by a high frequency system, it was considered adequate for both ion and MPD engine applications. The low frequency architecture will be used as the reference in future NEP PMAD studies.

Power Conditioning System Modelling for Nuclear Electric Propulsion

NASA Technical Reports Server (NTRS)

Metcalf, Kenneth J.

1993-01-01

NASA LeRC is currently developing a Fortran based model of a complete nuclear electric propulsion (NEP) vehicle that would be used for piloted and cargo missions to the Moon or Mars. The proposed vehicle design will use either a Brayton or K-Rankine power conversion cycle to drive a turbine coupled with a rotary alternator. Two thruster types are also being studied, ion and magnetoplasmadynamic (MPD). In support of this NEP model, Rocketdyne developed a power management and distribution (PMAD) subroutine that provides parametric outputs for selected alternator operating voltages and frequencies, thruster types, system power levels, and electronics coldplate temperatures. The end-to-end PMAD model described is based on the direct use of the alternator voltage and frequency for transmitting power to either ion or MPD thrusters. This low frequency transmission approach was compared with dc and high frequency ac designs, and determined to have the lowest mass, highest efficiency, highest reliability and lowest development costs. While its power quality is not as good as that provided by a high frequency system, it was considered adequate for both ion and MPD engine applications. The low frequency architecture will be used as the reference in future NEP PMAD studies.

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.

Design and optimization of organic rankine cycle for low temperature geothermal power plant

NASA Astrophysics Data System (ADS)

Barse, Kirtipal A.

Rising oil prices and environmental concerns have increased attention to renewable energy. Geothermal energy is a very attractive source of renewable energy. Although low temperature resources (90°C to 150°C) are the most common and most abundant source of geothermal energy, they were not considered economical and technologically feasible for commercial power generation. Organic Rankine Cycle (ORC) technology makes it feasible to use low temperature resources to generate power by using low boiling temperature organic liquids. The first hypothesis for this research is that using ORC is technologically and economically feasible to generate electricity from low temperature geothermal resources. The second hypothesis for this research is redesigning the ORC system for the given resource condition will improve efficiency along with improving economics. ORC model was developed using process simulator and validated with the data obtained from Chena Hot Springs, Alaska. A correlation was observed between the critical temperature of the working fluid and the efficiency for the cycle. Exergy analysis of the cycle revealed that the highest exergy destruction occurs in evaporator followed by condenser, turbine and working fluid pump for the base case scenarios. Performance of ORC was studied using twelve working fluids in base, Internal Heat Exchanger and turbine bleeding constrained and non-constrained configurations. R601a, R245ca, R600 showed highest first and second law efficiency in the non-constrained IHX configuration. The highest net power was observed for R245ca, R601a and R601 working fluids in the non-constrained base configuration. Combined heat exchanger area and size parameter of the turbine showed an increasing trend as the critical temperature of the working fluid decreased. The lowest levelized cost of electricity was observed for R245ca followed by R601a, R236ea in non-constrained base configuration. The next best candidates in terms of LCOE were R601a, R245ca and R600 in non-constrained IHX configuration. LCOE is dependent on net power and higher net power favors to lower the cost of electricity. Overall R245ca, R601, R601a, R600 and R236ea show better performance among the fluids studied. Non constrained configurations display better performance compared to the constrained configurations. Base non-constrained offered the highest net power and lowest LCOE.

An experimental comparative study of the efficiency of twisted and flat flapping wings during hovering flight.

PubMed

Phan, Hoang Vu; Truong, Quang Tri; Park, Hoon Cheol

2017-04-19

This work presents a parametric study to find a proper wing configuration for achieving economical flight using unsteady blade element theory, which is based on the 3D kinematics of a flapping wing. Power loading was first considered as a performance parameter for the study. The power loadings at each wing section along the wingspan were obtained for various geometric angles of attack (AoAs) by calculating the ratios of the vertical forces generated and the power consumed by that particular wing section. The results revealed that the power loading of a negatively twisted wing could be higher than the power loading that a flat wing can have; the power loading of the negatively twisted wing was approximately 5.9% higher. Given the relatively low average geometric AoA (α A,root   ≈  44° and α A,tip   ≈  25°), the vertical force produced by the twisted wing for the highest power loading was approximately 24.4% less than that produced by the twisted wing for the strongest vertical force. Therefore, for a given wing geometry and flapping amplitude, a flapping-wing micro air vehicle required a 13.5% increase in flapping frequency to generate the same strongest cycle-average vertical force while saving about 24.3% power. However, when force 3 /power 2 and force 2 /power ratios were considered as performance indices, the twisted wings for the highest force 3 /power 2 (α A,root   ≈  43° and α A,tip   ≈  30°) and force 2 /power (α A,root   ≈  43° and α A,tip   ≈  36°) required only 6.5% and 4% increases in flapping frequency and consumed 26.2% and 25.3% less power, respectively. Thus, it is preferable to use a flapping wing operating at a high frequency using the geometric AoAs for the highest power loading, force 3 /power 2 ratio, and force 2 /power ratio over a flapping wing operating at a low frequency using a high geometric AoA with the strongest vertical force. Additionally, by considering both aerodynamic and inertial forces, this study obtained average geometric AoAs in the range of 30° to 40°, which are similar to those of a typical hovering insect's wings. Therefore, the operation of an aerodynamically uneconomical, high AoA in a hovering insect's wings during flight is explainable.

The countermovement jump to monitor neuromuscular status: A meta-analysis.

PubMed

Claudino, João Gustavo; Cronin, John; Mezêncio, Bruno; McMaster, Daniel Travis; McGuigan, Michael; Tricoli, Valmor; Amadio, Alberto Carlos; Serrão, Julio Cerca

2017-04-01

The primary objective of this meta-analysis was to compare countermovement jump (CMJ) performance in studies that reported the highest value as opposed to average value for the purposes of monitoring neuromuscular status (i.e., fatigue and supercompensation). The secondary aim was to determine the sensitivity of the dependent variables. Systematic review with meta-analysis. The meta-analysis was conducted on the highest or average of a number of CMJ variables. Multiple literature searches were undertaken in Pubmed, Scopus, and Web of Science to identify articles utilizing CMJ to monitor training status. Effect sizes (ES) with 95% confidence interval (95% CI) were calculated using the mean and standard deviation of the pre- and post-testing data. The coefficient of variation (CV) with 95% CI was also calculated to assess the level of instability of each variable. Heterogeneity was assessed using a random-effects model. 151 articles were included providing a total of 531 ESs for the meta-analyses; 85.4% of articles used highest CMJ height, 13.2% used average and 1.3% used both when reporting changes in CMJ performance. Based on the meta-analysis, average CMJ height was more sensitive than highest CMJ height in detecting CMJ fatigue and supercompensation. Furthermore, other CMJ variables such as peak power, mean power, peak velocity, peak force, mean impulse, and power were sensitive in tracking the supercompensation effects of training. The average CMJ height was more sensitive than highest CMJ height in monitoring neuromuscular status; however, further investigation is needed to determine the sensitivity of other CMJ performance variables. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

29 CFR 1910.1027 - Cadmium.

Code of Federal Regulations, 2010 CFR

2010-07-01

... respirators when they experience eye irritation. (C) Provide HEPA filters for powered and non-powered air.... High-efficiency particulate air (HEPA) filter means a filter capable of trapping and retaining at least..., the employer shall sample the employee(s) expected to have the highest cadmium exposures. (2) Specific...

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

Oxygen Uptake Efficiency Plateau Best Predicts Early Death in Heart Failure

PubMed Central

Hansen, James E.; Stringer, William W.

2012-01-01

Background: The responses of oxygen uptake efficiency (ie, oxygen uptake/ventilation = V˙o2/V˙e) and its highest plateau (OUEP) during incremental cardiopulmonary exercise testing (CPET) in patients with chronic left heart failure (HF) have not been previously reported. We planned to test the hypothesis that OUEP during CPET is the best single predictor of early death in HF. Methods: We evaluated OUEP, slope of V˙o2 to log(V˙e) (oxygen uptake efficiency slope), oscillatory breathing, and all usual resting and CPET measurements in 508 patients with low-ejection-fraction (< 35%) HF. Each had further evaluations at other sites, including cardiac catheterization. Outcomes were 6-month all-reason mortality and morbidity (death or > 24 h cardiac hospitalization). Statistical analyses included area under curve of receiver operating characteristics, ORs, univariate and multivariate Cox regression, and Kaplan-Meier plots. Results: OUEP, which requires only moderate exercise, was often reduced in patients with HF. A low % predicted OUEP was the single best predictor of mortality (P < .0001), with an OR of 13.0 (P < .001). When combined with oscillatory breathing, the OR increased to 56.3, superior to all other resting or exercise parameters or combinations of parameters. Other statistical analyses and morbidity analysis confirmed those findings. Conclusions: OUEP is often reduced in patients with HF. Low % predicted OUEP (< 65% predicted) is the single best predictor of early death, better than any other CPET or other cardiovascular measurement. Paired with oscillatory breathing, it is even more powerful. PMID:22030802

Predicting variations of perceptual performance across individuals from neural activity using pattern classifiers.

PubMed

Das, Koel; Giesbrecht, Barry; Eckstein, Miguel P

2010-07-15

Within the past decade computational approaches adopted from the field of machine learning have provided neuroscientists with powerful new tools for analyzing neural data. For instance, previous studies have applied pattern classification algorithms to electroencephalography data to predict the category of presented visual stimuli, human observer decision choices and task difficulty. Here, we quantitatively compare the ability of pattern classifiers and three ERP metrics (peak amplitude, mean amplitude, and onset latency of the face-selective N170) to predict variations across individuals' behavioral performance in a difficult perceptual task identifying images of faces and cars embedded in noise. We investigate three different pattern classifiers (Classwise Principal Component Analysis, CPCA; Linear Discriminant Analysis, LDA; and Support Vector Machine, SVM), five training methods differing in the selection of training data sets and three analyses procedures for the ERP measures. We show that all three pattern classifier algorithms surpass traditional ERP measurements in their ability to predict individual differences in performance. Although the differences across pattern classifiers were not large, the CPCA method with training data sets restricted to EEG activity for trials in which observers expressed high confidence about their decisions performed the highest at predicting perceptual performance of observers. We also show that the neural activity predicting the performance across individuals was distributed through time starting at 120ms, and unlike the face-selective ERP response, sustained for more than 400ms after stimulus presentation, indicating that both early and late components contain information correlated with observers' behavioral performance. Together, our results further demonstrate the potential of pattern classifiers compared to more traditional ERP techniques as an analysis tool for modeling spatiotemporal dynamics of the human brain and relating neural activity to behavior. Copyright 2010 Elsevier Inc. All rights reserved.

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

Newman, Jennifer F.; Clifton, Andrew

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

POWER Web Access Data

Atmospheric Science Data Center

2018-05-27

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

EVALUATING THE PREDICTIVE VALIDITY OF SUICIDAL INTENT AND MEDICAL LETHALITY IN YOUTH

PubMed Central

Sapyta, Jeffrey; Goldston, David B.; Erkanli, Alaattin; Daniel, Stephanie S.; Heilbron, Nicole; Mayfield, Andrew; Treadway, S. Lyn

2012-01-01

Objectives To examine whether suicidal intent and medical lethality of past suicide attempts are predictive of future attempts, the association between intent and lethality, and the consistency of these characteristics across repeated attempts among youth. Method Suicide attempts in a 15-year prospective study of 180 formerly psychiatrically hospitalized adolescents (Mage at hospitalization = 14.83; 51% female; 80% Caucasian) were characterized using the Subjective Intent Rating Scale and Lethality of Attempt Rating Scale. Anderson-Gill recurrent events survival models and generalized estimating equations were used to assess predictive validity. Generalized linear models were used to examine stability of characteristics across attempts. Results Neither intent nor lethality from the most recent attempt predicted future attempts. The highest level of intent and most severe lethality of attempts during the follow-up predicted subsequent attempts, but the degree to which highest intent and most severe lethality contributed to prediction after considering methods of suicide attempts, past number of attempts, or psychiatric diagnoses was mixed. Across successive attempts, there was little consistency in reported characteristics. Intent and lethality were related to each other only for attempts occurring in early adulthood. Conclusions Highest intent and lethality were better predictors of future attempts than intent and lethality of the most recent attempt. However, these characteristics should only be considered as predictors within the context of other factors. For youth, clinicians should not infer true intent from the lethality of attempts, nor assume that characteristics of future suicide attempts will be similar to previous attempts. PMID:22250854

Observations of gamma-ray pulsars at the highest energies with the Fermi Large Area Telescope

NASA Astrophysics Data System (ADS)

Saz Parkinson, Pablo

2016-07-01

One of the most exciting developments in pulsar astrophysics in recent years has been the detection, with ground-based instruments (VERITAS, MAGIC), of pulsed gamma-ray emission from the Crab at very high energies (VHE, E>100 GeV). The Large Area Telescope (LAT) on board the Fermi satellite has detected over 160 pulsars above 100 MeV. Twenty-eight of these have been shown to emit pulsations above 10 GeV and approximately a dozen show emission above 25 GeV. While most gamma-ray pulsars are well-fitted in the GeV range by a power law with an exponential cut-off at around a few GeV, some emission models predict emission at energies above 100 GeV, either through a power-law extrapolation of the low-energy spectrum, or via a new (e.g. Inverse Compton) component. We will present results of our search for high-energy emission from LAT-detected gamma-ray pulsars using the latest Pass 8 data and discuss the prospects of finding the next VHE pulsar, providing a good target (or targets) for follow-up observations with current and future ground-based observatories, like CTA.

Improving Remote Health Monitoring: A Low-Complexity ECG Compression Approach

PubMed Central

Al-Ali, Abdulla; Mohamed, Amr; Ward, Rabab

2018-01-01

Recent advances in mobile technology have created a shift towards using battery-driven devices in remote monitoring settings and smart homes. Clinicians are carrying out diagnostic and screening procedures based on the electrocardiogram (ECG) signals collected remotely for outpatients who need continuous monitoring. High-speed transmission and analysis of large recorded ECG signals are essential, especially with the increased use of battery-powered devices. Exploring low-power alternative compression methodologies that have high efficiency and that enable ECG signal collection, transmission, and analysis in a smart home or remote location is required. Compression algorithms based on adaptive linear predictors and decimation by a factor B/K are evaluated based on compression ratio (CR), percentage root-mean-square difference (PRD), and heartbeat detection accuracy of the reconstructed ECG signal. With two databases (153 subjects), the new algorithm demonstrates the highest compression performance (CR=6 and PRD=1.88) and overall detection accuracy (99.90% sensitivity, 99.56% positive predictivity) over both databases. The proposed algorithm presents an advantage for the real-time transmission of ECG signals using a faster and more efficient method, which meets the growing demand for more efficient remote health monitoring. PMID:29337892

Optimisation of Microwave-Assisted Extraction of Pomegranate (Punica granatum L.) Seed Oil and Evaluation 
of Its Physicochemical and Bioactive Properties.

PubMed

Çavdar, Hasene Keskin; Yanık, Derya Koçak; Gök, Uğur; Göğüş, Fahrettin

2017-03-01

Pomegranate seed oil was extracted in a closed-vessel high-pressure microwave system. The characteristics of the obtained oil, such as fatty acid composition, free fatty acidity, total phenolic content, antioxidant activity and colour, were compared to those of the oil obtained by cold solvent extraction. Response surface methodology was applied to optimise extraction conditions: power (176-300 W), time (5-20 min), particle size ( d =0.125-0.800 mm) and solvent to sample ratio (2:1, 6:1 and 10:1, by mass). The predicted highest extraction yield (35.19%) was obtained using microwave power of 220 W, particle size in the range of d =0.125-0.450 mm and solvent-to-sample ratio of 10:1 (by mass) in 5 min extraction time. Microwave-assisted solvent extraction (MASE) resulted in higher extraction yield than that of Soxhlet (34.70% in 8 h) or cold (17.50% in 8 h) extraction. The dominant fatty acid of pomegranate seed oil was punicic acid (86%) irrespective of the extraction method. Oil obtained by MASE had better physicochemical properties, total phenolic content and antioxidant activity than the oil obtained by cold solvent extraction.

Development and validation of chemistry agnostic flow battery cost performance model and application to nonaqueous electrolyte systems: Chemistry agnostic flow battery cost performance model

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

Crawford, Alasdair; Thomsen, Edwin; Reed, David

2016-04-20

A chemistry agnostic cost performance model is described for a nonaqueous flow battery. The model predicts flow battery performance by estimating the active reaction zone thickness at each electrode as a function of current density, state of charge, and flow rate using measured data for electrode kinetics, electrolyte conductivity, and electrode-specific surface area. Validation of the model is conducted using a 4kW stack data at various current densities and flow rates. This model is used to estimate the performance of a nonaqueous flow battery with electrode and electrolyte properties used from the literature. The optimized cost for this system ismore » estimated for various power and energy levels using component costs provided by vendors. The model allows optimization of design parameters such as electrode thickness, area, flow path design, and operating parameters such as power density, flow rate, and operating SOC range for various application duty cycles. A parametric analysis is done to identify components and electrode/electrolyte properties with the highest impact on system cost for various application durations. A pathway to 100$kWh -1 for the storage system is identified.« less

Numerical investigation on effect of blade shape for stream water wheel performance.

NASA Astrophysics Data System (ADS)

Yah, N. F.; Oumer, A. N.; Aziz, A. A.; Sahat, I. M.

2018-04-01

Stream water wheels are one of the oldest and commonly used types of wheels for the production of energy. Moreover, they are economical, efficient and sustainable. However, few amounts of research works are available in the open literature. This paper aims to develop numerical model for investigation of the effect of blade shape on the performance of stream water wheel. The numerical model was simulated using Computational Fluid Dynamics (CFD) method and the developed model was validated by comparing the simulation results with experimental data obtained from literature. The performance of straight, curved type 1 and curved type 2 was observed and the power generated by each blade design was identified. The inlet velocity was set to 0.3 m/s static pressure outlet. The obtained results indicate that the highest power was generated by the Curved type 2 compared to straight blade and curved type 1. From the CFD result, Curved type 1 was able to generate 0.073 Watt while Curved type 2 generate 0.064 Watt. The result obtained were consistent with the experiment result hence can be used the numerical model as a guide to numerically predict the water wheel performance

Improving Remote Health Monitoring: A Low-Complexity ECG Compression Approach.

PubMed

Elgendi, Mohamed; Al-Ali, Abdulla; Mohamed, Amr; Ward, Rabab

2018-01-16

Recent advances in mobile technology have created a shift towards using battery-driven devices in remote monitoring settings and smart homes. Clinicians are carrying out diagnostic and screening procedures based on the electrocardiogram (ECG) signals collected remotely for outpatients who need continuous monitoring. High-speed transmission and analysis of large recorded ECG signals are essential, especially with the increased use of battery-powered devices. Exploring low-power alternative compression methodologies that have high efficiency and that enable ECG signal collection, transmission, and analysis in a smart home or remote location is required. Compression algorithms based on adaptive linear predictors and decimation by a factor B / K are evaluated based on compression ratio (CR), percentage root-mean-square difference (PRD), and heartbeat detection accuracy of the reconstructed ECG signal. With two databases (153 subjects), the new algorithm demonstrates the highest compression performance ( CR = 6 and PRD = 1.88 ) and overall detection accuracy (99.90% sensitivity, 99.56% positive predictivity) over both databases. The proposed algorithm presents an advantage for the real-time transmission of ECG signals using a faster and more efficient method, which meets the growing demand for more efficient remote health monitoring.

Ultrasonic-assisted extraction and in-vitro antioxidant activity of polysaccharide from Hibiscus leaf.

PubMed

Afshari, Kasra; Samavati, Vahid; Shahidi, Seyed-Ahmad

2015-03-01

The effects of ultrasonic power, extraction time, extraction temperature, and the water-to-raw material ratio on extraction yield of crude polysaccharide from the leaf of Hibiscus rosa-sinensis (HRLP) were optimized by statistical analysis using response surface methodology. The response surface methodology (RSM) was used to optimize HRLP extraction yield by implementing the Box-Behnken design (BBD). The experimental data obtained were fitted to a second-order polynomial equation using multiple regression analysis and also analyzed by appropriate statistical methods (ANOVA). Analysis of the results showed that the linear and quadratic terms of these four variables had significant effects. The optimal conditions for the highest extraction yield of HRLP were: ultrasonic power, 93.59 W; extraction time, 25.71 min; extraction temperature, 93.18°C; and the water to raw material ratio, 24.3 mL/g. Under these conditions, the experimental yield was 9.66±0.18%, which is well in close agreement with the value predicted by the model 9.526%. The results demonstrated that HRLP had strong scavenging activities in vitro on DPPH and hydroxyl radicals. Copyright © 2014 Elsevier B.V. All rights reserved.

Temperature-dependent electrochemical heat generation in a commercial lithium-ion battery

NASA Astrophysics Data System (ADS)

Bandhauer, Todd M.; Garimella, Srinivas; Fuller, Thomas F.

2014-02-01

Lithium-ion batteries suffer from inherent thermal limitations (i.e., capacity fade and thermal runaway); thus, it is critical to understand heat generation experienced in the batteries under normal operation. In the current study, reversible and irreversible electrochemical heat generation rates were measured experimentally on a small commercially available C/LiFePO4 lithium-ion battery designed for high-rate applications. The battery was tested over a wide range of temperatures (10-60 °C) and discharge and charge rates (∼C/4-5C) to elucidate their effects. Two samples were tested in a specially designed wind tunnel to maintain constant battery surface temperature within a maximum variation of ±0.88 °C. A data normalization technique was employed to account for the observed capacity fade, which was largest at the highest rates. The heat rate was shown to increase with both increasing rate and decreasing temperature, and the reversible heat rate was shown to be significant even at the highest rate and temperature (7.4% at 5C and 55 °C). Results from cycling the battery using a dynamic power profile also showed that constant-current data predict the dynamic performance data well. In addition, the reversible heat rate in the dynamic simulation was shown to be significant, especially for charge-depleting HEV applications.

47 CFR 95.607 - CB transmitter modification.

Code of Federal Regulations, 2010 CFR

2010-10-01

... transmitting frequencies, increased modulation level, a different form of modulation, or increased TP (RF... modulating frequency, typically 0.1 seconds at maximum power) or peak envelope power (TP averaged during 1 RF cycle at the highest crest of the modulation envelope), as measured at the transmitter output antenna...

Measurement of the temperature distribution inside the power cable using distributed temperature system

NASA Astrophysics Data System (ADS)

Jaros, Jakub; Liner, Andrej; Papes, Martin; Vasinek, Vladimir; Mach, Veleslav; Hruby, David; Kajnar, Tomas; Perecar, Frantisek

2015-01-01

Nowadays, the power cables are manufactured to fulfill the following condition - the highest allowable temperature of the cable during normal operation and the maximum allowable temperature at short circuit conditions cannot exceed the condition of the maximum allowable internal temperature. The distribution of the electric current through the conductor leads to the increase of the amplitude of electrons in the crystal lattice of the cables material. The consequence of this phenomenon is the increase of friction and the increase of collisions between particles inside the material, which causes the temperature increase of the carrying elements. The temperature increase is unwanted phenomena, because it is causing losses. In extreme cases, the long-term overload leads to the cable damaging or fire. This paper deals with the temperature distribution measurement inside the power cables using distributed temperature system. With cooperation with Kabex company, the tube containing optical fibers was installed into the center of power cables. These fibers, except telecommunications purposes, can be also used as sensors in measurements carrying out with distributed temperature system. These systems use the optical fiber as a sensor and allow the continual measurement of the temperature along the whole cable in real time with spatial resolution 1 m. DTS systems are successfully deployed in temperature measurement applications in industry areas yet. These areas include construction, drainage, hot water etc. Their advantages are low cost, resistance to electromagnetic radiation and the possibility of real time monitoring at the distance of 8 km. The location of the optical fiber in the center of the power cable allows the measurement of internal distribution of the temperature during overloading the cable. This measurement method can be also used for prediction of short-circuit and its exact location.

Microwaving logs for energy savings and improved paper properties for mechanical pulps

Treesearch

C. Tim Scott; John Klungness; Mike Lentz; Eric Horn; Masood Akhtar

2002-01-01

High-power microwave cooking of commercial black spruce pulpwood logs was investigated as a pretreatment for mechanical pulping. Several dozen logs were treated at a variety of power levels (10 to 50 kW) and for various times (1 to 10 min). The mechanical pulping trials resulted in significant energy savings-up to 15% for the highest power level. In addition, there was...

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.

Hydrodynamic modeling and feasibility study of harnessing tidal power at the Bay of Fundy

NASA Astrophysics Data System (ADS)

Chang, Jen

Due to rising fuel costs and environmental concerns, energy generation from alternative power source has become one of the most important issues in energy policy. Tidal power is one of the alternative energy sources. The tidal range at the Bay of Fundy is the largest in the world (approximately 16 meters). It represents a prime location for harnessing tidal power using the daily rising and ebbing tide. In this study, a two dimensional finite element model has been developed and applied to simulate the tidal responses, including water level and flow velocity, in the Bay of Fundy region. The simulation results are used to choose the suitable location for energy development and to predict possible energy generated from different types of generation methods. Fluid motion is assumed to be governed by the shallow water equation since the wave length associated with tide is much longer than the water depth in the Bay of Fundy. By using a real time series of water elevation at the entrance of the bay, the computer model finds tidal response for each node in the study area, which is then verified by the observation record from several tidal gauge stations inside the bay. This study shows that the at-site cost of the energy for barrage type tidal power plants is around 0.065 to 0.097 per kWh at the recommended Shepody Bay, Cumberland Basin, and Cobequid Bay. The cost of energy for the current turbine type tidal power plants is 0.13/kWh to 0.24/kWh at the area with highest current velocity. Compared with the recent bill of the local power company, the at-site unit cost of energy from the barrage type of tidal power plant is feasible, but the environmental concerns of channel blocking by barrage present a formidable constraint. For the current turbine type of tidal power plant, even the most suitable sites are not financially feasible under current technology, but this type of power generation may become feasible as oil prices continue to increase and more efficient turbines become available.

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.

An advanced concept secondary power systems study for an advanced transport technology aircraft

NASA Technical Reports Server (NTRS)

1972-01-01

The application of advanced technology to the design of an integrated secondary power system for future near-sonic long-range transports was investigated. The study showed that the highest payoff is achieved by utilizing secondary power equipment that contributes to minimum cruise drag. This is best accomplished by the use of the dedicated auxiliary power unit concept (inflight APU) as the prime power source for an airplane with a body-mounted engine or by the use of the internal engine generator concept (electrical power extraction from the propulsion engine) for an airplane with a wing-pod-mounted engine.

Detecting Solar-like Oscillations in Red Giants with Deep Learning

NASA Astrophysics Data System (ADS)

Hon, Marc; Stello, Dennis; Zinn, Joel C.

2018-05-01

Time-resolved photometry of tens of thousands of red giant stars from space missions like Kepler and K2 has created the need for automated asteroseismic analysis methods. The first and most fundamental step in such analysis is to identify which stars show oscillations. It is critical that this step be performed with no, or little, detection bias, particularly when performing subsequent ensemble analyses that aim to compare the properties of observed stellar populations with those from galactic models. However, an efficient, automated solution to this initial detection step still has not been found, meaning that expert visual inspection of data from each star is required to obtain the highest level of detections. Hence, to mimic how an expert eye analyzes the data, we use supervised deep learning to not only detect oscillations in red giants, but also to predict the location of the frequency at maximum power, ν max, by observing features in 2D images of power spectra. By training on Kepler data, we benchmark our deep-learning classifier against K2 data that are given detections by the expert eye, achieving a detection accuracy of 98% on K2 Campaign 6 stars and a detection accuracy of 99% on K2 Campaign 3 stars. We further find that the estimated uncertainty of our deep-learning-based ν max predictions is about 5%. This is comparable to human-level performance using visual inspection. When examining outliers, we find that the deep-learning results are more likely to provide robust ν max estimates than the classical model-fitting method.

A neural algorithm for the non-uniform and adaptive sampling of biomedical data.

PubMed

Mesin, Luca

2016-04-01

Body sensors are finding increasing applications in the self-monitoring for health-care and in the remote surveillance of sensitive people. The physiological data to be sampled can be non-stationary, with bursts of high amplitude and frequency content providing most information. Such data could be sampled efficiently with a non-uniform schedule that increases the sampling rate only during activity bursts. A real time and adaptive algorithm is proposed to select the sampling rate, in order to reduce the number of measured samples, but still recording the main information. The algorithm is based on a neural network which predicts the subsequent samples and their uncertainties, requiring a measurement only when the risk of the prediction is larger than a selectable threshold. Four examples of application to biomedical data are discussed: electromyogram, electrocardiogram, electroencephalogram, and body acceleration. Sampling rates are reduced under the Nyquist limit, still preserving an accurate representation of the data and of their power spectral densities (PSD). For example, sampling at 60% of the Nyquist frequency, the percentage average rectified errors in estimating the signals are on the order of 10% and the PSD is fairly represented, until the highest frequencies. The method outperforms both uniform sampling and compressive sensing applied to the same data. The discussed method allows to go beyond Nyquist limit, still preserving the information content of non-stationary biomedical signals. It could find applications in body sensor networks to lower the number of wireless communications (saving sensor power) and to reduce the occupation of memory. Copyright © 2016 Elsevier Ltd. All rights reserved.

Highest integration in microelectronics: Development of digital ASICs for PARS3-LR

NASA Astrophysics Data System (ADS)

Scholler, Peter; Vonlutz, Rainer

Essential electronic system components by PARS3-LR, show high requirements in calculation power, power consumption and reliability, by immediately increasing integration thicknesses. These problems are solved by using integrated circuits, developed by LSI LOGIC, that uses the technical and economic advantages of this leading edge technology.

14 CFR 33.84 - Engine overtorque test.

Code of Federal Regulations, 2011 CFR

2011-01-01

... STANDARDS: AIRCRAFT ENGINES Block Tests; Turbine Aircraft Engines § 33.84 Engine overtorque test. (a) If approval of a maximum engine overtorque is sought for an engine incorporating a free power turbine... at least 21/2 minutes duration. (2) A power turbine rotational speed equal to the highest speed at...

14 CFR 33.84 - Engine overtorque test.

Code of Federal Regulations, 2014 CFR

2014-01-01

... STANDARDS: AIRCRAFT ENGINES Block Tests; Turbine Aircraft Engines § 33.84 Engine overtorque test. (a) If approval of a maximum engine overtorque is sought for an engine incorporating a free power turbine... at least 21/2 minutes duration. (2) A power turbine rotational speed equal to the highest speed at...

14 CFR 33.84 - Engine overtorque test.

Code of Federal Regulations, 2013 CFR

2013-01-01

... STANDARDS: AIRCRAFT ENGINES Block Tests; Turbine Aircraft Engines § 33.84 Engine overtorque test. (a) If approval of a maximum engine overtorque is sought for an engine incorporating a free power turbine... at least 21/2 minutes duration. (2) A power turbine rotational speed equal to the highest speed at...

47 CFR 74.798 - Digital television transition notices by broadcasters.

Code of Federal Regulations, 2012 CFR

2012-10-01

... the highest number of viewers is watching. Stations have the discretion as to the form of these... SERVICES Low Power TV, TV Translator, and TV Booster Stations § 74.798 Digital television transition notices by broadcasters. (a) Each low power television, TV translator and Class A television station...

47 CFR 74.798 - Digital television transition notices by broadcasters.

Code of Federal Regulations, 2013 CFR

2013-10-01

... the highest number of viewers is watching. Stations have the discretion as to the form of these... SERVICES Low Power TV, TV Translator, and TV Booster Stations § 74.798 Digital television transition notices by broadcasters. (a) Each low power television, TV translator and Class A television station...

47 CFR 74.798 - Digital television transition notices by broadcasters.

Code of Federal Regulations, 2011 CFR

2011-10-01

... the highest number of viewers is watching. Stations have the discretion as to the form of these... SERVICES Low Power TV, TV Translator, and TV Booster Stations § 74.798 Digital television transition notices by broadcasters. (a) Each low power television, TV translator and Class A television station...

47 CFR 74.798 - Digital television transition notices by broadcasters.

Code of Federal Regulations, 2014 CFR

2014-10-01

... the highest number of viewers is watching. Stations have the discretion as to the form of these... SERVICES Low Power TV, TV Translator, and TV Booster Stations § 74.798 Digital television transition notices by broadcasters. (a) Each low power television, TV translator and Class A television station...

Prognostic Value of Quantitative Metabolic Metrics on Baseline Pre-Sunitinib FDG PET/CT in Advanced Renal Cell Carcinoma

PubMed Central

Minamimoto, Ryogo; Barkhodari, Amir; Harshman, Lauren; Srinivas, Sandy; Quon, Andrew

2016-01-01

Purpose The objective of this study was to prospectively evaluate various quantitative metrics on FDG PET/CT for monitoring sunitinib therapy and predicting prognosis in patients with metastatic renal cell cancer (mRCC). Methods Seventeen patients (mean age: 59.0 ± 11.6) prospectively underwent a baseline FDG PET/CT and interim PET/CT after 2 cycles (12 weeks) of sunitinib therapy. We measured the highest maximum standardized uptake value (SUVmax) of all identified lesions (highest SUVmax), sum of SUVmax with maximum six lesions (sum of SUVmax), total lesion glycolysis (TLG) and metabolic tumor volume (MTV) from baseline PET/CT and interim PET/CT, and the % decrease in highest SUVmax of lesion (%Δ highest SUVmax), the % decrease in sum of SUVmax, the % decrease in TLG (%ΔTLG) and the % decrease in MTV (%ΔMTV) between baseline and interim PET/CT, and the imaging results were validated by clinical follow-up at 12 months after completion of therapy for progression free survival (PFS). Results At 12 month follow-up, 6/17 (35.3%) patients achieved PFS, while 11/17 (64.7%) patients were deemed to have progression of disease or recurrence within the previous 12 months. At baseline, PET/CT demonstrated metabolically active cancer in all cases. Using baseline PET/CT alone, all of the quantitative imaging metrics were predictive of PFS. Using interim PET/CT, the %Δ highest SUVmax, %Δ sum of SUVmax, and %ΔTLG were also predictive of PFS. Otherwise, interim PET/CT showed no significant difference between the two survival groups regardless of the quantitative metric utilized including MTV and TLG. Conclusions Quantitative metabolic measurements on baseline PET/CT appears to be predictive of PFS at 12 months post-therapy in patients scheduled to undergo sunitinib therapy for mRCC. Change between baseline and interim PET/CT also appeared to have prognostic value but otherwise interim PET/CT after 12 weeks of sunitinib did not appear to be predictive of PFS. PMID:27123976

Mechanical function of the heart and its alteration during myocardial ischemia and infarction. Specific reference to coronary atherosclerosis.

PubMed

Swan, H J

1979-12-01

Altered regional mechanical myocardial performance is an early, sensitive marker of myocardial ischemia, and can be estimated in man with reasonable accuracy. Identification, localization and quantification of abnormalities in mechanical performance can be used to predict the presence of coronary artery disease. Testing techniques that have little or no effect on diagnostic efficiency must be replaced with more sensitive indicators of ischemia. If experimental data are validated by findings in human subjects, accurate identification of regional wall motion changes during test conditions should prove to be a powerful marker of ischemia. To be of value, a diagnostic test must strongly increase the frequency of identification of subjects with a high probabilty for the presence of coronary artery disease in an otherwise low-prevalence population, and of those with known disease who are at the highest risk for complications including myocardial infarction or death.

Integrated numerical modeling of a laser gun injector

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

Liu, H.; Benson, S.; Bisognano, J.

1993-06-01

CEBAF is planning to incorporate a laser gun injector into the linac front end as a high-charge cw source for a high-power free electron laser and nuclear physics. This injector consists of a DC laser gun, a buncher, a cryounit and a chicane. The performance of the injector is predicted based on integrated numerical modeling using POISSON, SUPERFISH and PARMELA. The point-by-point method incorporated into PARMELA by McDonald is chosen for space charge treatment. The concept of ``conditioning for final bunching`` is employed to vary several crucial parameters of the system for achieving highest peak current while maintaining low emittancemore » and low energy spread. Extensive parameter variation studies show that the design will perform beyond the specifications for FEL operations aimed at industrial applications and fundamental scientific research. The calculation also shows that the injector will perform as an extremely bright cw electron source.« less

The genome of Eucalyptus grandis.

PubMed

Myburg, Alexander A; Grattapaglia, Dario; Tuskan, Gerald A; Hellsten, Uffe; Hayes, Richard D; Grimwood, Jane; Jenkins, Jerry; Lindquist, Erika; Tice, Hope; Bauer, Diane; Goodstein, David M; Dubchak, Inna; Poliakov, Alexandre; Mizrachi, Eshchar; Kullan, Anand R K; Hussey, Steven G; Pinard, Desre; van der Merwe, Karen; Singh, Pooja; van Jaarsveld, Ida; Silva-Junior, Orzenil B; Togawa, Roberto C; Pappas, Marilia R; Faria, Danielle A; Sansaloni, Carolina P; Petroli, Cesar D; Yang, Xiaohan; Ranjan, Priya; Tschaplinski, Timothy J; Ye, Chu-Yu; Li, Ting; Sterck, Lieven; Vanneste, Kevin; Murat, Florent; Soler, Marçal; Clemente, Hélène San; Saidi, Naijib; Cassan-Wang, Hua; Dunand, Christophe; Hefer, Charles A; Bornberg-Bauer, Erich; Kersting, Anna R; Vining, Kelly; Amarasinghe, Vindhya; Ranik, Martin; Naithani, Sushma; Elser, Justin; Boyd, Alexander E; Liston, Aaron; Spatafora, Joseph W; Dharmwardhana, Palitha; Raja, Rajani; Sullivan, Christopher; Romanel, Elisson; Alves-Ferreira, Marcio; Külheim, Carsten; Foley, William; Carocha, Victor; Paiva, Jorge; Kudrna, David; Brommonschenkel, Sergio H; Pasquali, Giancarlo; Byrne, Margaret; Rigault, Philippe; Tibbits, Josquin; Spokevicius, Antanas; Jones, Rebecca C; Steane, Dorothy A; Vaillancourt, René E; Potts, Brad M; Joubert, Fourie; Barry, Kerrie; Pappas, Georgios J; Strauss, Steven H; Jaiswal, Pankaj; Grima-Pettenati, Jacqueline; Salse, Jérôme; Van de Peer, Yves; Rokhsar, Daniel S; Schmutz, Jeremy

2014-06-19

Eucalypts are the world's most widely planted hardwood trees. Their outstanding diversity, adaptability and growth have made them a global renewable resource of fibre and energy. We sequenced and assembled >94% of the 640-megabase genome of Eucalyptus grandis. Of 36,376 predicted protein-coding genes, 34% occur in tandem duplications, the largest proportion thus far in plant genomes. Eucalyptus also shows the highest diversity of genes for specialized metabolites such as terpenes that act as chemical defence and provide unique pharmaceutical oils. Genome sequencing of the E. grandis sister species E. globulus and a set of inbred E. grandis tree genomes reveals dynamic genome evolution and hotspots of inbreeding depression. The E. grandis genome is the first reference for the eudicot order Myrtales and is placed here sister to the eurosids. This resource expands our understanding of the unique biology of large woody perennials and provides a powerful tool to accelerate comparative biology, breeding and biotechnology.

Optimization of PEG-based extraction of polysaccharides from Dendrobium nobile Lindl. and bioactivity study.

PubMed

Zhang, Yi; Wang, Hongxin; Wang, Peng; Ma, ChaoYang; He, GuoHua; Rahman, Md Ramim Tanver

2016-11-01

Polyethylene glycol (PEG) as a green solvent was employed to extract polysaccharide. The optimal conditions for PEG-based ultrasonic extraction of Dendrobium nobile Lindl. polysaccharide (JCP) were determined by response surface methodology. Under the optimal conditions: extraction temperature of 58.5°C; ultrasound power of 193W, and the concentration of polyethylene glycol-200 (PEG-200) solution of 45%, the highest JCP yield was obtained as 15.23±0.57%, which was close to the predicted yield, 15.57%. UV and FT-IR analysis revealed the general characteristic absorption peaks of both JCP with water extraction (JCP w ) and PEG-200 solvent extraction (JCP p ). Thermal analysis of both JCPs was performed with Thermal Gravimetric Analyzer (TGA) and Differential Scanning Calorimeter (DSC). Antioxidant activities of two polysaccharides were also compared and no significant difference in vitro was obtained. Copyright © 2016 Elsevier B.V. All rights reserved.

Temporal order memory assessed during spatiotemporal navigation as a behavioral cognitive marker for differential Alzheimer's disease diagnosis.

PubMed

Bellassen, Virginie; Iglói, Kinga; de Souza, Leonardo Cruz; Dubois, Bruno; Rondi-Reig, Laure

2012-02-08

Episodic memory impairment is a hallmark for early diagnosis of Alzheimer's disease. Most actual tests used to diagnose Alzheimer's disease do not assess the spatiotemporal properties of episodic memory and lead to false-positive or -negative diagnosis. We used a newly developed, nonverbal navigation test for Human, based on the objective experimental testing of a spatiotemporal experience, to differentially Alzheimer's disease at the mild stage (N = 16 patients) from frontotemporal lobar degeneration (N = 11 patients) and normal aging (N = 24 subjects). Comparing navigation parameters and standard neuropsychological tests, temporal order memory appeared to have the highest predictive power for mild Alzheimer's disease diagnosis versus frontotemporal lobar degeneration and normal aging. This test was also nonredundant with classical neuropsychological tests. As a conclusion, our results suggest that temporal order memory tested in a spatial navigation task may provide a selective behavioral marker of Alzheimer's disease.

Determinants of Self-Care in Diabetic Patients Based on Health Belief Model

PubMed Central

Dehghani-Tafti, Abbasali; Mahmoodabad, Seyed Saeed Mazloomy; Morowatisharifabad, Mohammad Ali; Ardakani, Mohammad Afkhami; Rezaeipandari, Hassan; Lotfi, Mohammad Hassan

2015-01-01

Introduction: The aim of this study was to determine self-care predictors in diabetic patients based on health belief model. Materials and Methods: The cross-sectional study was conducted on 110 diabetic patients referred to health service centers in Ardakan city, Yazd, Iran. The data was collected by a questionnaire including perceived benefits, barriers, severity, susceptibility, self-efficacy, social support, self-care behaviors and demographic variables. Results: Regularly medicine use (mean= 6.48 times per week) and shoes checking (mean= 1.17 times per week) were reported as the highest and the lowest self-care behaviors respectively. Health belief model constructs including perceived benefits, barriers, severity, susceptibility, self-efficacy and social support predicted 33.5% of the observed variance of self-care behaviors. Perceived susceptibility and self-efficacy had positive effect on self-care behavior; whereas perceived barrier’s has negative effect. Self-efficacy, perceived susceptibility and barriers were most powerful predictor respectively. Conclusion: The findings approved the efficiency of health belief model in prediction of self-care behaviors among diabetic patients. The findings realized the health belief model structure; therefore, it can be used as a framework for designing and implementing educational interventions in diabetes control plans. PMID:26156902

Computational analysis on plug-in hybrid electric motorcycle chassis

NASA Astrophysics Data System (ADS)

Teoh, S. J.; Bakar, R. A.; Gan, L. M.

2013-12-01

Plug-in hybrid electric motorcycle (PHEM) is an alternative to promote sustainability lower emissions. However, the PHEM overall system packaging is constrained by limited space in a motorcycle chassis. In this paper, a chassis applying the concept of a Chopper is analysed to apply in PHEM. The chassis 3dimensional (3D) modelling is built with CAD software. The PHEM power-train components and drive-train mechanisms are intergraded into the 3D modelling to ensure the chassis provides sufficient space. Besides that, a human dummy model is built into the 3D modelling to ensure the rider?s ergonomics and comfort. The chassis 3D model then undergoes stress-strain simulation. The simulation predicts the stress distribution, displacement and factor of safety (FOS). The data are used to identify the critical point, thus suggesting the chassis design is applicable or need to redesign/ modify to meet the require strength. Critical points mean highest stress which might cause the chassis to fail. This point occurs at the joints at triple tree and bracket rear absorber for a motorcycle chassis. As a conclusion, computational analysis predicts the stress distribution and guideline to develop a safe prototype chassis.

Factors influencing happiness of the grandmothers raising grandchildren in rural areas of Northern Thailand.

PubMed

Nanthamongkolchai, Sutham; Munsawaengsub, Chokchai; Taechaboonsermsak, Pimsurang; Powwattana, Arpaporn

2013-12-01

To study the factors influencing happiness of grandmothers raising grandchildren in the rural areas of Northern Thailand. Cross-sectional survey research was conducted among 400 grandmothers, aged 50-79 years, who raised their grandchildren in the rural areas of Northern Thailand. Participants were selected by cluster sampling. Data were collected through a structured interview from April to July 2009 and analyzed by frequency, percentage, Pearson product moment correlation coefficient, and Multiple regression analysis. Nearly half (46.8%) of grandmothers raising grandchildren had high level of happiness, followed by moderate level (40.4%) and low level (12.8%). The factors, which significantly influenced the happiness of the grandmothers, were self-esteem, social support, and family relationships (p-value < 0.05). In addition, self-esteem, social support, and family relationships could significantly predict happiness of the grandmothers by 48.1%. Self-esteem had the highest predictive power of happiness among grandmothers. The factors influencing happiness of grandmothers raising grandchildren were self-esteem, social support, and family relationships. To promote happiness of grandmothers, responsible organizations should establish activities that enhance the grandmother's self-esteem, provide sufficient social support, and promote good family relationships.

Foreign exchange market data analysis reveals statistical features that predict price movement acceleration.

PubMed

Nacher, Jose C; Ochiai, Tomoshiro

2012-05-01

Increasingly accessible financial data allow researchers to infer market-dynamics-based laws and to propose models that are able to reproduce them. In recent years, several stylized facts have been uncovered. Here we perform an extensive analysis of foreign exchange data that leads to the unveiling of a statistical financial law. First, our findings show that, on average, volatility increases more when the price exceeds the highest (or lowest) value, i.e., breaks the resistance line. We call this the breaking-acceleration effect. Second, our results show that the probability P(T) to break the resistance line in the past time T follows power law in both real data and theoretically simulated data. However, the probability calculated using real data is rather lower than the one obtained using a traditional Black-Scholes (BS) model. Taken together, the present analysis characterizes a different stylized fact of financial markets and shows that the market exceeds a past (historical) extreme price fewer times than expected by the BS model (the resistance effect). However, when the market does, we predict that the average volatility at that time point will be much higher. These findings indicate that any Markovian model does not faithfully capture the market dynamics.

Ecology has contrasting effects on genetic variation within species versus rates of molecular evolution across species in water beetles.

PubMed

Fujisawa, Tomochika; Vogler, Alfried P; Barraclough, Timothy G

2015-01-22

Comparative analysis is a potentially powerful approach to study the effects of ecological traits on genetic variation and rate of evolution across species. However, the lack of suitable datasets means that comparative studies of correlates of genetic traits across an entire clade have been rare. Here, we use a large DNA-barcode dataset (5062 sequences) of water beetles to test the effects of species ecology and geographical distribution on genetic variation within species and rates of molecular evolution across species. We investigated species traits predicted to influence their genetic characteristics, such as surrogate measures of species population size, latitudinal distribution and habitat types, taking phylogeny into account. Genetic variation of cytochrome oxidase I in water beetles was positively correlated with occupancy (numbers of sites of species presence) and negatively with latitude, whereas substitution rates across species depended mainly on habitat types, and running water specialists had the highest rate. These results are consistent with theoretical predictions from nearly-neutral theories of evolution, and suggest that the comparative analysis using large databases can give insights into correlates of genetic variation and molecular evolution.

Foreign exchange market data analysis reveals statistical features that predict price movement acceleration

NASA Astrophysics Data System (ADS)

Nacher, Jose C.; Ochiai, Tomoshiro

2012-05-01

Increasingly accessible financial data allow researchers to infer market-dynamics-based laws and to propose models that are able to reproduce them. In recent years, several stylized facts have been uncovered. Here we perform an extensive analysis of foreign exchange data that leads to the unveiling of a statistical financial law. First, our findings show that, on average, volatility increases more when the price exceeds the highest (or lowest) value, i.e., breaks the resistance line. We call this the breaking-acceleration effect. Second, our results show that the probability P(T) to break the resistance line in the past time T follows power law in both real data and theoretically simulated data. However, the probability calculated using real data is rather lower than the one obtained using a traditional Black-Scholes (BS) model. Taken together, the present analysis characterizes a different stylized fact of financial markets and shows that the market exceeds a past (historical) extreme price fewer times than expected by the BS model (the resistance effect). However, when the market does, we predict that the average volatility at that time point will be much higher. These findings indicate that any Markovian model does not faithfully capture the market dynamics.

Predicting of soil erosion with regarding to rainfall erosivity and soil erodibility

NASA Astrophysics Data System (ADS)

Suif, Zuliziana; Razak, Mohd Amirun Anis Ab; Ahmad, Nordila

2018-02-01

The soil along the hill and slope are wearing away due to erosion and it can take place due to occurrence of weak and heavy rainfall. The aim of this study is to predict the soil erosion degree in Universiti Pertahanan Nasional Malaysia (UPNM) area focused on two major factor which is soil erodibility and rainfall erosivity. Soil erodibility is the possibilities of soil to detach and carried away during rainfall and runoff. The "ROM" scale was used in this study to determine the degree of soil erodibility, namely low, moderate, high, and very high. As for rainfall erosivity, the erosive power caused by rainfall that cause soil loss. A daily rainfall data collected from January to April was analyzed by using ROSE index classification to identify the potential risk of soil erosion. The result shows that the soil erodibilty are moderate at MTD`s hill, high at behind of block Lestari and Landslide MTD hill, and critical at behind the mess cadet. While, the highest rainfall erosivity was recorded in March and April. Overall, this study would benefit the organization greatly in saving cost in landslide protection as relevant authorities can take early measures repairing the most affected area of soil erosion.

Ecological niche modelling of potential West Nile virus vector mosquito species and their geographical association with equine epizootics in Italy.

PubMed

Mughini-Gras, Lapo; Mulatti, Paolo; Severini, Francesco; Boccolini, Daniela; Romi, Roberto; Bongiorno, Gioia; Khoury, Cristina; Bianchi, Riccardo; Montarsi, Fabrizio; Patregnani, Tommaso; Bonfanti, Lebana; Rezza, Giovanni; Capelli, Gioia; Busani, Luca

2014-01-01

In Italy, West Nile virus (WNV) equine outbreaks have occurred annually since 2008. Characterizing WNV vector habitat requirements allows for the identification of areas at risk of viral amplification and transmission. Maxent-based ecological niche models were developed using literature records of 13 potential WNV Italian vector mosquito species to predict their habitat suitability range and to investigate possible geographical associations with WNV equine outbreak occurrence in Italy from 2008 to 2010. The contribution of different environmental variables to the niche models was also assessed. Suitable habitats for Culex pipiens, Aedes albopictus, and Anopheles maculipennis were widely distributed; Culex modestus, Ochlerotatus geniculatus, Ochlerotatus caspius, Coquillettidia richiardii, Aedes vexans, and Anopheles plumbeus were concentrated in north-central Italy; Aedes cinereus, Culex theileri, Ochlerotatus dorsalis, and Culiseta longiareolata were restricted to coastal/southern areas. Elevation, temperature, and precipitation variables showed the highest predictive power. Host population and landscape variables provided minor contributions. WNV equine outbreaks had a significantly higher probability to occur in habitats suitable for Cx. modestus and Cx. pipiens, providing circumstantial evidence that the potential distribution of these two species coincides geographically with the observed distribution of the disease in equines.

Overview of MST Research

NASA Astrophysics Data System (ADS)

Sarff, J. S.

2016-10-01

MST progress in advancing the RFP for (1) fusion plasma confinement with ohmic heating and minimal external magnetization, (2) predictive capability in toroidal confinement physics, and (3) basic plasma physics is summarized. Validation of key plasma models is a program priority. Programmable power supplies (PPS) are being developed to maximize inductive capability. Well-controlled flattops with current as low as 0.02 MA are produced with an existing PPS, and Ip <= 0.8 MA is anticipated with a second PPS under construction. The Lundquist number spans S =10(4 - 9) for 0.02-0.8 MA, allowing nonlinear MHD validation using NIMROD and DEBS at low S to be connected to highest S experiments. The PPS also enables MST tokamak operation for studying transients and runaway electron suppression with RMPs. Gyrokinetic modeling with GENE predicts unstable TEM in improved-confinement plasmas. Fluctuations are measured with TEM properties including a density-gradient threshold larger than for tokamak plasmas. Probe measurements hint that drift waves are also excited via the turbulent cascade in standard RFP plasmas. Turbulent energization of an electron tail occurs during sawtooth reconnection. New diagnostics are being developed to measure the energetic ion profile and transport from EP instabilities with NBI. Supported by US DoE and NSF.

Seasonal variations as predictive factors of the comet assay parameters: a retrospective study.

PubMed

Geric, Marko; Gajski, Goran; Orešcanin, Višnja; Garaj-Vrhovac, Vera

2018-02-24

Since there are several predicting factors associated with the comet assay parameters, we have decided to assess the impact of seasonal variations on the comet assay results. A total of 162 volunteers were retrospectively studied, based on the date when blood donations were made. The groups (winter, spring, summer and autumn) were matched in terms of age, gender, smoking status, body mass index and medical diagnostic exposure in order to minimise the impact of other possible predictors. Means and medians of the comet assay parameters were higher when blood was sampled in the warmer period of the year, the values of parameters being the highest during summer. Correlation of meteorological data (air temperature, sun radiation and sun insolation) was observed when data were presented as the median per person. Using multivariate analysis, sampling season and exposure to medical radiation were proved to be the most influential predictors for the comet assay parameters. Taken together, seasonal variation is another variable that needs to be accounted for when conducting a cohort study. Further studies are needed in order to improve the statistical power of the results related to the impact of sun radiation, air temperature and sun insolation on the comet assay parameters.

Maximal Power of the Lower Limbs of Youth Gymnasts and Biomechanical Indicators of the Forward Handspring Vault Versus the Sports Result

PubMed Central

Kochanowicz, Andrzej; Kochanowicz, Kazimierz; Mieszkowski, Jan; Aschenbrenner, Piotr; Bielec, Grzegorz; Szark-Eckardt, Mirosława

2016-01-01

Abstract The aim of the study was to define the relationship between maximal power of lower limbs, the biomechanics of the forward handspring vault and the score received during a gymnastics competition. The research involved 42 gymnasts aged 9-11 years competing in the Poland’s Junior Championships. The study consisted of three stages: first -estimating the level of indicators of maximal power of lower limbs tested on a force plate during the countermovement jump; second - estimating the level of biomechanical indicators of the front handspring vault. For both mentioned groups of indicators and the score received by gymnasts during the vault, linear correlation analyses were made. The last stage consisted of conducting multiple regression analysis in order to predict the performance level of the front handspring vault. Results showed a positive correlation (0.401, p < 0.05) of lower limbs’ maximal power (1400 ± 502 W) with the judges’ score for the front handstand vault (13.38 ± 1.02 points). However, the highest significant (p < 0.001) correlation with the judges’ score was revealed in the angle of the hip joint in the second phase of the flight (196.00 ± 16.64°) and the contact time of hands with the vault surface (0.264 ± 0.118 s), where correlation coefficients were: -0.671 and -0.634, respectively. In conclusion, the angles of the hip joint in the second phase of the flight and when the hands touched the vault surface proved to be the most important indicators for the received score. PMID:28149408

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.

Applications of statistical physics to technology price evolution

NASA Astrophysics Data System (ADS)

McNerney, James

Understanding how changing technology affects the prices of goods is a problem with both rich phenomenology and important policy consequences. Using methods from statistical physics, I model technology-driven price evolution. First, I examine a model for the price evolution of individual technologies. The price of a good often follows a power law equation when plotted against its cumulative production. This observation turns out to have significant consequences for technology policy aimed at mitigating climate change, where technologies are needed that achieve low carbon emissions at low cost. However, no theory adequately explains why technology prices follow power laws. To understand this behavior, I simplify an existing model that treats technologies as machines composed of interacting components. I find that the power law exponent of the price trajectory is inversely related to the number of interactions per component. I extend the model to allow for more realistic component interactions and make a testable prediction. Next, I conduct a case-study on the cost evolution of coal-fired electricity. I derive the cost in terms of various physical and economic components. The results suggest that commodities and technologies fall into distinct classes of price models, with commodities following martingales, and technologies following exponentials in time or power laws in cumulative production. I then examine the network of money flows between industries. This work is a precursor to studying the simultaneous evolution of multiple technologies. Economies resemble large machines, with different industries acting as interacting components with specialized functions. To begin studying the structure of these machines, I examine 20 economies with an emphasis on finding common features to serve as targets for statistical physics models. I find they share the same money flow and industry size distributions. I apply methods from statistical physics to show that industries cluster the same way according to industry type. Finally, I use these industry money flows to model the price evolution of many goods simultaneously, where network effects become important. I derive a prediction for which goods tend to improve most rapidly. The fastest-improving goods are those with the highest mean path lengths in the money flow network.

Wind speed and power characteristics of Kalasin province, Thailand

NASA Astrophysics Data System (ADS)

Polnumtiang, Supachai; Tangchaichit, Kiatfa

2018-05-01

This paper presents a wind energy assessment of Kalasin province in the Upper North-Eastern region of Thailand. Four year wind data were recorded continuously from January 2012 to December 2015 at different heights of 60, 90 and 120 m above ground level (AGL). The mean wind speeds were found to be 3.14, 3.63 and 3.94 m/s at 60, 90 and 120 m AGL, respectively. The majority of wind directions for this region are distributed from the East to South directions. The highest wind power density was observed in the summer season, followed by winter and rainy seasons, in order. Four commercial wind turbines were selected to estimate energy yield output using the WAsP 10.0 software application; the results show that VESTAS with rated power of 2.0 MW was estimated to give 2,747 MWh/year with the highest capacity factor of 15.68%.

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.

ETHOS - an effective theory of structure formation: predictions for the high-redshift Universe - abundance of galaxies and reionization

NASA Astrophysics Data System (ADS)

Lovell, Mark R.; Zavala, Jesús; Vogelsberger, Mark; Shen, Xuejian; Cyr-Racine, Francis-Yan; Pfrommer, Christoph; Sigurdson, Kris; Boylan-Kolchin, Michael; Pillepich, Annalisa

2018-07-01

We contrast predictions for the high-redshift galaxy population and reionization history between cold dark matter (CDM) and an alternative self-interacting dark matter model based on the recently developed ETHOS framework that alleviates the small-scale CDM challenges within the Local Group. We perform the highest resolution hydrodynamical cosmological simulations (a 36 Mpc3 volume with gas cell mass of ˜ 105 M_{⊙} and minimum gas softening of ˜180 pc) within ETHOS to date - plus a CDM counterpart - to quantify the abundance of galaxies at high redshift and their impact on reionization. We find that ETHOS predicts galaxies with higher ultraviolet (UV) luminosities than their CDM counterparts and a faster build-up of the faint end of the UV luminosity function. These effects, however, make the optical depth to reionization less sensitive to the power spectrum cut-off: the ETHOS model differs from the CDM τ value by only 10 per cent and is consistent with Planck limits if the effective escape fraction of UV photons is 0.1-0.5. We conclude that current observations of high-redshift luminosity functions cannot differentiate between ETHOS and CDM models, but deep James Webb Space Telescope surveys of strongly lensed, inherently faint galaxies have the potential to test non-CDM models that offer attractive solutions to CDM's Local Group problems.

Critical Song Features for Auditory Pattern Recognition in Crickets

PubMed Central

Meckenhäuser, Gundula; Hennig, R. Matthias; Nawrot, Martin P.

2013-01-01

Many different invertebrate and vertebrate species use acoustic communication for pair formation. In the cricket Gryllus bimaculatus, females recognize their species-specific calling song and localize singing males by positive phonotaxis. The song pattern of males has a clear structure consisting of brief and regular pulses that are grouped into repetitive chirps. Information is thus present on a short and a long time scale. Here, we ask which structural features of the song critically determine the phonotactic performance. To this end we employed artificial neural networks to analyze a large body of behavioral data that measured females’ phonotactic behavior under systematic variation of artificially generated song patterns. In a first step we used four non-redundant descriptive temporal features to predict the female response. The model prediction showed a high correlation with the experimental results. We used this behavioral model to explore the integration of the two different time scales. Our result suggested that only an attractive pulse structure in combination with an attractive chirp structure reliably induced phonotactic behavior to signals. In a further step we investigated all feature sets, each one consisting of a different combination of eight proposed temporal features. We identified feature sets of size two, three, and four that achieve highest prediction power by using the pulse period from the short time scale plus additional information from the long time scale. PMID:23437054

A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran.

PubMed

Khosravi, Khabat; Pham, Binh Thai; Chapi, Kamran; Shirzadi, Ataollah; Shahabi, Himan; Revhaug, Inge; Prakash, Indra; Tien Bui, Dieu

2018-06-15

Floods are one of the most damaging natural hazards causing huge loss of property, infrastructure and lives. Prediction of occurrence of flash flood locations is very difficult due to sudden change in climatic condition and manmade factors. However, prior identification of flood susceptible areas can be done with the help of machine learning techniques for proper timely management of flood hazards. In this study, we tested four decision trees based machine learning models namely Logistic Model Trees (LMT), Reduced Error Pruning Trees (REPT), Naïve Bayes Trees (NBT), and Alternating Decision Trees (ADT) for flash flood susceptibility mapping at the Haraz Watershed in the northern part of Iran. For this, a spatial database was constructed with 201 present and past flood locations and eleven flood-influencing factors namely ground slope, altitude, curvature, Stream Power Index (SPI), Topographic Wetness Index (TWI), land use, rainfall, river density, distance from river, lithology, and Normalized Difference Vegetation Index (NDVI). Statistical evaluation measures, the Receiver Operating Characteristic (ROC) curve, and Freidman and Wilcoxon signed-rank tests were used to validate and compare the prediction capability of the models. Results show that the ADT model has the highest prediction capability for flash flood susceptibility assessment, followed by the NBT, the LMT, and the REPT, respectively. These techniques have proven successful in quickly determining flood susceptible areas. Copyright © 2018 Elsevier B.V. All rights reserved.

Impact of climate change on runoff in Lake Urmia basin, Iran

NASA Astrophysics Data System (ADS)

Sanikhani, Hadi; Kisi, Ozgur; Amirataee, Babak

2018-04-01

Investigation of the impact of climate change on water resources is very necessary in dry and arid regions. In the first part of this paper, the climate model Long Ashton Research Station Weather Generator (LARS-WG) was used for downscaling climate data including rainfall, solar radiation, and minimum and maximum temperatures. Two different case studies including Aji-Chay and Mahabad-Chay River basins as sub-basins of Lake Urmia in the northwest part of Iran were considered. The results indicated that the LARS-WG successfully downscaled the climatic variables. By application of different emission scenarios (i.e., A1B, A2, and B1), an increasing trend in rainfall and a decreasing trend in temperature were predicted for both the basins over future time periods. In the second part of this paper, gene expression programming (GEP) was applied for simulating runoff of the basins in the future time periods including 2020, 2055, and 2090. The input combination including rainfall, solar radiation, and minimum and maximum temperatures in current and prior time was selected as the best input combination with highest predictive power for runoff prediction. The results showed that the peak discharge will decrease by 50 and 55.9% in 2090 comparing with the baseline period for the Aji-Chay and Mahabad-Chay basins, respectively. The results indicated that the sustainable adaptation strategies are necessary for these basins for protection of water resources in future.

A minimally invasive methodology based on morphometric parameters for day 2 embryo quality assessment.

PubMed

Molina, Inmaculada; Lázaro-Ibáñez, Elisa; Pertusa, Jose; Debón, Ana; Martínez-Sanchís, Juan Vicente; Pellicer, Antonio

2014-10-01

The risk of multiple pregnancy to maternal-fetal health can be minimized by reducing the number of embryos transferred. New tools for selecting embryos with the highest implantation potential should be developed. The aim of this study was to evaluate the ability of morphological and morphometric variables to predict implantation by analysing images of embryos. This was a retrospective study of 135 embryo photographs from 112 IVF-ICSI cycles carried out between January and March 2011. The embryos were photographed immediately before transfer using Cronus 3 software. Their images were analysed using the public program ImageJ. Significant effects (P < 0.05), and higher discriminant power to predict implantation were observed for the morphometric embryo variables compared with morphological ones. The features for successfully implanted embryos were as follows: four cells on day 2 of development; all blastomeres with circular shape (roundness factor greater than 0.9), an average zona pellucida thickness of 13 µm and an average of 17695.1 µm² for the embryo area. Embryo size, which is described by its area and the average roundness factor for each cell, provides two objective variables to consider when predicting implantation. This approach should be further investigated for its potential ability to improve embryo scoring. Copyright © 2014 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

A prediction tool incorporating the biomarker S-100B for patient selection for completion lymph node dissection in stage III melanoma.

PubMed

Damude, S; Wevers, K P; Murali, R; Kruijff, S; Hoekstra, H J; Bastiaannet, E

2017-09-01

Completion lymph node dissection (CLND) in sentinel node (SN)-positive melanoma patients is accompanied with morbidity, while about 80% yield no additional metastases in non-sentinel nodes (NSNs). A prediction tool for NSN involvement could be of assistance in patient selection for CLND. This study investigated which parameters predict NSN-positivity, and whether the biomarker S-100B improves the accuracy of a prediction model. Recorded clinicopathologic factors were tested for their association with NSN-positivity in 110 SN-positive patients who underwent CLND. A prediction model was developed with multivariable logistic regression, incorporating all predictive factors. Five models were compared for their predictive power by calculating the Area Under the Curve (AUC). A weighted risk score, 'S-100B Non-Sentinel Node Risk Score' (SN-SNORS), was derived for the model with the highest AUC. Besides, a nomogram was developed as visual representation. NSN-positivity was present in 24 (21.8%) patients. Sex, ulceration, number of harvested SNs, number of positive SNs, and S-100B value were independently associated with NSN-positivity. The AUC for the model including all these factors was 0.78 (95%CI 0.69-0.88). SN-SNORS was the sum of scores for the five parameters. Scores of ≤9.5, 10-11.5, and ≥12 were associated with low (0%), intermediate (21.0%) and high (43.2%) risk of NSN involvement. A prediction tool based on five parameters, including the biomarker S-100B, showed accurate risk stratification for NSN-involvement in SN-positive melanoma patients. If validated in future studies, this tool could help to identify patients with low risk for NSN-involvement. Copyright © 2017 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

SU-E-T-630: Predictive Modeling of Mortality, Tumor Control, and Normal Tissue Complications After Stereotactic Body Radiotherapy for Stage I Non-Small Cell Lung Cancer

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

Lindsay, WD; Oncora Medical, LLC, Philadelphia, PA; Berlind, CG

Purpose: While rates of local control have been well characterized after stereotactic body radiotherapy (SBRT) for stage I non-small cell lung cancer (NSCLC), less data are available characterizing survival and normal tissue toxicities, and no validated models exist assessing these parameters after SBRT. We evaluate the reliability of various machine learning techniques when applied to radiation oncology datasets to create predictive models of mortality, tumor control, and normal tissue complications. Methods: A dataset of 204 consecutive patients with stage I non-small cell lung cancer (NSCLC) treated with stereotactic body radiotherapy (SBRT) at the University of Pennsylvania between 2009 and 2013more » was used to create predictive models of tumor control, normal tissue complications, and mortality in this IRB-approved study. Nearly 200 data fields of detailed patient- and tumor-specific information, radiotherapy dosimetric measurements, and clinical outcomes data were collected. Predictive models were created for local tumor control, 1- and 3-year overall survival, and nodal failure using 60% of the data (leaving the remainder as a test set). After applying feature selection and dimensionality reduction, nonlinear support vector classification was applied to the resulting features. Models were evaluated for accuracy and area under ROC curve on the 81-patient test set. Results: Models for common events in the dataset (such as mortality at one year) had the highest predictive power (AUC = .67, p < 0.05). For rare occurrences such as radiation pneumonitis and local failure (each occurring in less than 10% of patients), too few events were present to create reliable models. Conclusion: Although this study demonstrates the validity of predictive analytics using information extracted from patient medical records and can most reliably predict for survival after SBRT, larger sample sizes are needed to develop predictive models for normal tissue toxicities and more advanced machine learning methodologies need be consider in the future.« less

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

PubMed

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

2008-01-01

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

Blockage effects on the hydrodynamic performance of a marine cross-flow turbine.

PubMed

Consul, Claudio A; Willden, Richard H J; McIntosh, Simon C

2013-02-28

This paper explores the influence of blockage and free-surface deformation on the hydrodynamic performance of a generic marine cross-flow turbine. Flows through a three-bladed turbine with solidity 0.125 are simulated at field-test blade Reynolds numbers, O(10(5)-10(6)), for three different cross-stream blockages: 12.5, 25 and 50 per cent. Two representations of the free-surface boundary are considered: rigid lid and deformable free surface. Increasing the blockage is observed to lead to substantial increases in the power coefficient; the highest power coefficient computed is 1.23. Only small differences are observed between the two free-surface representations, with the deforming free-surface turbine out-performing the rigid lid turbine by 6.7 per cent in power at the highest blockage considered. This difference is attributed to the increase in effective blockage owing to the deformation of the free surface. Hydrodynamic efficiency, the ratio of useful power generated to overall power removed from the flow, is found to increase with blockage, which is consistent with the presence of a higher flow velocity through the core of the turbine at higher blockage ratios. Froude number is found to have little effect on thrust and power coefficients, but significant influence on surface elevation drop across the turbine.

THz polariton laser using an intracavity Mg:LiNbO₃ crystal with protective Teflon coating.

PubMed

Ortega, Tiago A; Pask, Helen M; Spence, David J; Lee, Andrew J

2017-02-20

An enhancement in the performance of a THz polariton laser based on an intracavity magnesium-doped lithium niobate crystal (Mg:LiNbO₃) in surface-emitted (SE) configuration is demonstrated resulting from the deposition of a protective Teflon coating on the total internal reflection surface of the crystal. In this cavity geometry the resonating fields undergo total internal reflection (TIR) inside the lithium niobate, and laser damage to that surface can be a limiting factor in performance. The protective layer prevents laser damage to the crystal surface, enabling higher pump power, yielding higher THz output power and wider frequency tuning range. With the unprotected crystal, narrow-band THz output tunable from 1.50 to 2.81 THz was produced, with maximum average output power of 20.1 µW at 1.76 THz for 4 W diode pump power (limited by laser damage to the crystal). With the Teflon coating, no laser damage to the crystal was observed, and the system produced narrow-band THz output tunable from 1.46 to 3.84 THz, with maximum average output power of 56.8 µW at 1.76 THz for 6.5 W diode pump power. This is the highest average output power and the highest diode-to-terahertz conversion efficiency ever reported for an intracavity terahertz polariton laser.

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.

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

Power quality analysis based on spatial correlation

NASA Astrophysics Data System (ADS)

Li, Jiangtao; Zhao, Gang; Liu, Haibo; Li, Fenghou; Liu, Xiaoli

2018-03-01

With the industrialization and urbanization, the status of electricity in the production and life is getting higher and higher. So the prediction of power quality is the more potential significance. Traditional power quality analysis methods include: power quality data compression, disturbance event pattern classification, disturbance parameter calculation. Under certain conditions, these methods can predict power quality. This paper analyses the temporal variation of power quality of one provincial power grid in China from time angle. The distribution of power quality was analyzed based on spatial autocorrelation. This paper tries to prove that the research idea of geography is effective for mining the potential information of power quality.

The value of novel invasive hemodynamic parameters added to the TIMI risk score for short-term prognosis assessment in patients with ST segment elevation myocardial infarction.

PubMed

Tesak, Martin; Kala, Petr; Jarkovsky, Jiri; Poloczek, Martin; Bocek, Otakar; Jerabek, Petr; Kubková, Lenka; Manousek, Jan; Spinar, Jindrich; Mebazaa, Alexandre; Parenica, Jiri; Cohen-Solal, Alain

2016-07-01

We compared the prognostic capacity of conventional and novel invasive parameters derived from the slope of the preload recruitable stroke work relationship (PRSW) in STEMI patients and assessed their contribution to the TIMI risk score. Left ventricular end-diastolic pressure (EDP), ejection fraction (EF), pressure adjusted maximum rate of pressure change in the left ventricle (dP/dt/P), aortic systolic pressure to EDP ratio (SBP/EDP) and end-diastolic volume adjusted stroke work (EW), derived from the slope of the PRSW relationship, were obtained during the emergency cardiac catheterization in 523 STEMI patients. The predictive power of the analyzed parameters for 30-day and 1-year mortality was evaluated using C-statistics and reclassification analysis was adopted to assess the improvement in TIMI score. The highest area under the curve (AUC) values for 30-day mortality were observed for EW (0.872(95% confidence interval 0.801-0.943)), SBP/EDP (0.843(0.758-0.928)) and EF (0.833(0.735-0.931)); p<0.001 for all values. For 1-year mortality the best predictive value was found for EW (0.806(0.724-0.887) and EF (0.793(0.703-0.883)); p<0.001 for both. The addition of EDP, SBP/EDP ratio and EW to TIMI score significantly increased the AUC according to De Long's test. For 30-day mortality, increased discriminative power following addition to the TIMI score was observed for EW and SBP/EDP (Integrated Discrimination Improvement was 0.086(0.033-0.140), p=0.002 and 0.078(0.028-0.128), p=0.002, respectively). EW and SBP/EDP are prognostic markers with high predictive value for 30-day and 1-year mortality. Both parameters, easily obtained during emergency catheterization, improve the discriminatory capacity of the TIMI score for 30-day mortality. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Outcome scoring systems for short-term prognosis in critically ill cirrhotic patients.

PubMed

Tu, Kun-Hua; Jenq, Chang-Chyi; Tsai, Ming-Hung; Hsu, Hsiang-Hao; Chang, Ming-Yang; Tian, Ya-Chung; Hung, Cheng-Chieh; Fang, Ji-Tseng; Yang, Chih-Wei; Chen, Yung-Chang

2011-11-01

Cirrhotic patients admitted to intensive care units (ICUs) have high mortality rates. This study evaluated specific predictors and scoring systems for hospital and 6-month mortality in critically ill cirrhotic patients. This investigation is a prospective clinical study performed in a 10-bed specialized hepatogastroenterology ICU in a tertiary care university hospital in Taiwan. Two hundred two consecutive cirrhotic patients admitted to the ICU during a 2-year period were enrolled in this study. Demographic, clinical, and laboratory variables recorded on the first day of ICU admission and scoring systems applied were prospectively recorded for post hoc analysis for predicting survival. The overall hospital mortality was 59.9%, and the 6-month mortality rate was 70.8%. The main causes of cirrhosis were hepatitis B (29%), hepatitis C (22%), and alcoholism (20%). The major cause of ICU admission was upper gastrointestinal bleeding (36%). Multiple logistic regression analysis revealed that the Acute Kidney Injury Network (AKIN) score at the 48th hour of ICU admission and the Sequential Organ Failure Assessment (SOFA) as well as the Model for End-Stage Liver Disease scores on the first day of ICU admission were independent risk factors for hospital mortality. The SOFA score had the best discriminatory power (0.872 ± 0.036), whereas the AKIN had the best Youden index (0.57) and the highest correctness of prediction (79%). Cumulative survival rates at the 6-month follow-up after hospital discharge differed significantly (P < 0.05) for AKIN stage 0 vs. stages 1, 2, and 3, and for AKIN stage 1 vs. stage 3. The AKIN, SOFA, and Model for End-stage Liver Disease (MELD) scores showed well discriminative power in predicting hospital mortality in this group of patients. The AKIN scoring system proved to be a reproducible evaluation tool with excellent prognostic abilities for these patients.

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.

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.

Molecular Characterization and Antioxidant Potential of Three Wild Culinary-Medicinal Mushrooms from Tripura, Northeast India.

PubMed

Das, Aparajita Roy; Borthakur, Madhusmita; Saha, Ajay Krishna; Joshi, Santa Ram; Das, Panna

2017-01-01

The aim of this study was to characterize 3 wild culinary-medicinal mushrooms using molecular tools and to analyze their antioxidant activity. Antioxidant properties were studied by evaluating free radical scavenging, reducing power, and chelating effect. The mushrooms were identified as Lentinus squarrosulus, L. tuber-regium, and Macrocybe gigantean by amplifying internal transcribed spacer regions of ribosomal DNA. The results demonstrated that the methanolic extract of M. gigantean has the highest free radical scavenging effect and chelating effect, whereas the methanolic extract of L. squarrosulus has the highest reducing power. The highest total phenol content and the most ascorbic acid were found in the M. gigantean extracts. Among the 3 mushroom extracts, M. gigantean displayed the most potent antioxidant activity. Molecular characterization using the nuclear ribosomal internal transcribed spacer region as a universal DNA marker was an effective tool in the identification and phylogenetic analysis of the studied mushrooms. The study also indicated that these wild macrofungi are rich sources of natural antioxidants.

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.).

Machinery safety of lathe machine using SHARP-systemic human action reliability procedure: a pilot case study in academic laboratory

NASA Astrophysics Data System (ADS)

Suryoputro, M. R.; Sari, A. D.; Sugarindra, M.; Arifin, R.

2017-12-01

This research aimed to understand the human reliability analysis, to find the SHARP method with its functionality on case study and also emphasize the practice in Lathe machine, continued with identifying improvement that could be made to the existing safety system. SHARP comprises of 7 stages including definition, screening, breakdown, representation, impact assessment, quantification and documentation. These steps were combined and analysed using HIRA, FTA and FMEA. HIRA analysed the lathe at academic laboratory showed the level of the highest risk with a score of 9 for the activities of power transmission parts and a score of 6 for activities which shall mean the moving parts required to take action to reduce the level of risk. Hence, the highest RPN values obtained in the power transmission activities with a value of 18 in the power transmission and then the activities of moving parts is 12 and the activities of the operating point of 8. Thus, this activity has the highest risk of workplace accidents in the operation. On the academic laboratory the improvement made on the engineering control initially with a machine guarding and completed with necessary administrative controls (SOP, work permit, training and routine cleaning) and dedicated PPEs.

Global risk from the atmospheric dispersion of radionuclides by nuclear power plant accidents in the coming decades

NASA Astrophysics Data System (ADS)

Christoudias, T.; Proestos, Y.; Lelieveld, J.

2014-05-01

We estimate the global risk from the release and atmospheric dispersion of radionuclides from nuclear power plant accidents using the EMAC atmospheric chemistry-general circulation model. We included all nuclear reactors that are currently operational, under construction and planned or proposed. We implemented constant continuous emissions from each location in the model and simulated atmospheric transport and removal via dry and wet deposition processes over 20 years (2010-2030), driven by boundary conditions based on the IPCC A2 future emissions scenario. We present global overall and seasonal risk maps for potential surface layer concentrations and ground deposition of radionuclides, and estimate potential doses to humans from inhalation and ground-deposition exposures to radionuclides. We find that the risk of harmful doses due to inhalation is typically highest in the Northern Hemisphere during boreal winter, due to relatively shallow boundary layer development and limited mixing. Based on the continued operation of the current nuclear power plants, we calculate that the risk of radioactive contamination to the citizens of the USA will remain to be highest worldwide, followed by India and France. By including stations under construction and those that are planned and proposed, our results suggest that the risk will become highest in China, followed by India and the USA.

Global risk from the atmospheric dispersion of radionuclides by nuclear power plant accidents in the coming decades

NASA Astrophysics Data System (ADS)

Christoudias, T.; Proestos, Y.; Lelieveld, J.

2013-11-01

We estimate the global risk from the release and atmospheric dispersion of radionuclides from nuclear power plant accidents using the EMAC atmospheric chemistry-general circulation model. We included all nuclear reactors that are currently operational, under construction and planned or proposed. We implemented constant continuous emissions from each location in the model and simulated atmospheric transport and removal via dry and wet deposition processes over 20 yr (2010-2030), driven by boundary conditions based on the IPCC A2 future emissions scenario. We present global overall and seasonal risk maps for potential surface layer concentrations and ground deposition of radionuclides, and estimate potential dosages to humans from the inhalation and the exposure to ground deposited radionuclides. We find that the risk of harmful doses due to inhalation is typically highest during boreal winter due to relatively shallow boundary layer development and reduced mixing. Based on the continued operation of the current nuclear power plants, we calculate that the risk of radioactive contamination to the citizens of the USA will remain to be highest worldwide, followed by India and France. By including stations under construction and those that are planned and proposed our results suggest that the risk will become highest in China, followed by India and the USA.

Global Risk from the Atmospheric Dispersion of Radionuclides by Nuclear Power Plant Accidents in the Coming Decades

NASA Astrophysics Data System (ADS)

Christoudias, T.; Proestos, Y.; Lelieveld, J.

2014-12-01

We estimate the global risk from the release and atmospheric dispersion of radionuclides from nuclear power plant accidents using the EMAC atmospheric chemistry-general circulation model. We included all nuclear reactors that are currently operational, under construction and planned or proposed. We implemented constant continuous emissions from each location in the model and simulated atmospheric transport and removal via dry and wet deposition processes over 20 years (2010-2030), driven by boundary conditions based on the IPCC A2 future emissions scenario. We present global overall and seasonal risk maps for potential surface layer concentrations and ground deposition of radionuclides, and estimate potential doses to humans from inhalation and ground-deposition exposures to radionuclides. We find that the risk of harmful doses due to inhalation is typically highest in the Northern Hemisphere during boreal winter, due to relatively shallow boundary layer development and limited mixing. Based on the continued operation of the current nuclear power plants, we calculate that the risk of radioactive contamination to the citizens of the USA will remain to be highest worldwide, followed by India and France. By including stations under construction and those that are planned and proposed, our results suggest that the risk will become highest in China, followed by India and the USA.

The influence of mass configurations on velocity amplified vibrational energy harvesters

NASA Astrophysics Data System (ADS)

O'Donoghue, D.; Frizzell, R.; Kelly, G.; Nolan, K.; Punch, J.

2016-05-01

Vibrational energy harvesters scavenge ambient vibrational energy, offering an alternative to batteries for the autonomous operation of low power electronics. Velocity amplified electromagnetic generators (VAEGs) utilize the velocity amplification effect to increase power output and operational bandwidth, compared to linear resonators. A detailed experimental analysis of the influence of mass ratio and number of degrees-of-freedom (dofs) on the dynamic behaviour and power output of a macro-scale VAEG is presented. Various mass configurations are tested under drop-test and sinusoidal forced excitation, and the system performances are compared. For the drop-test, increasing mass ratio and number of dofs increases velocity amplification. Under forced excitation, the impacts between the masses are more complex, inducing greater energy losses. This results in the 2-dof systems achieving the highest velocities and, hence, highest output voltages. With fixed transducer size, higher mass ratios achieve higher voltage output due to the superior velocity amplification. Changing the magnet size to a fixed percentage of the final mass showed the increase in velocity of the systems with higher mass ratios is not significant enough to overcome the reduction in transducer size. Consequently, the 3:1 mass ratio systems achieved the highest output voltage. These findings are significant for the design of future reduced-scale VAEGs.

Evaluation of the Antioxidant Capacities and Cytotoxic Effects of Ten Parmeliaceae Lichen Species

PubMed Central

González-Burgos, E.; Divakar, P. K.; Crespo, A.

2016-01-01

Parmeliaceae represents the largest and widespread family of lichens and includes species that attract much interest regarding pharmacological activities, due to their production of unique secondary metabolites. The current work aimed to investigate the in vitro antioxidant and cytotoxic activities of the methanol extracts of ten Parmeliaceae species, collected in different continents. Methanol extraction afforded high phenolic content in the extracts. The antioxidant activity displayed by lichens was evaluated through chemical assays, such as the ORAC (Oxygen Radical Absorbance Capacity) and 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging activities and the ferric reducing antioxidant power (FRAP). A moderately positive correlation was found between the phenolic content and the antioxidant properties for all the species: R: 0.7430 versus ORAC values, R: 0.7457 versus DPPH scavenging capacity, and R: 0.7056 versus FRAP reducing power. The methanol extract of Flavoparmelia euplecta exhibited the highest ORAC value, the extract of Myelochroa irrugans showed the maximum DPPH scavenging capacity, and Hypotrachyna cirrhata methanol extract demonstrated the highest reducing power. Further, the cytotoxic activity of the ten species was investigated on the human cancer cell lines HepG2 and MCF-7; Myelochroa irrugans exhibited the highest anticancer potential. The pharmacological activities shown here could be attributed to their phytochemical constituents. PMID:28074101

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.

Design and Analysis of Photovoltaic (PV) Power Plant at Different Locations in Malaysia

NASA Astrophysics Data System (ADS)

Islam, M. A.; Hasanuzzaman, M.; Rahim, N. A.

2018-05-01

Power generation from sun oriented vitality through a photovoltaic (PV) system is ended up prevalent over the world due to clean innovation. Geographical location of Malaysia is very favorable for PV power generation system. The Malaysian government has also taken different steps to increase the use of solar energy especially by emphasizing on building integrated PV (BIPV) system. Comparative study on the feasibility of BIPV installation at the different location of Malaysia is rarely found. On the other hand, solar cell temperature has a negative impact on the electricity generation. So in this study cost effectiveness and initial investment cost of building integrated grid connected solar PV power plant in different regions of Malaysia have been carried. The effect of PV solar cell temperature on the payback period (PBP) is also investigated. Highest PBP is 12.38 years at Selangor and lowest PBP is 9.70 years at Sabah (Kota Kinabalu). Solar cell temperature significantly increases the PBP of PV plant and highest 14.64% and lowest 13.20% raise of PBP are encountered at Penang and Sarawak respectively.

Development Status of High-Thrust Density Electrostatic Engines

NASA Technical Reports Server (NTRS)

Patterson, Michael J.; Haag, Thomas W.; Foster, John E.; Young, Jason A.; Crofton, Mark W.

2017-01-01

Ion thruster technology offers the highest performance and efficiency of any mature electric propulsion thruster. It has by far the highest demonstrated total impulse of any technology option, demonstrated at input power levels appropriate for primary propulsion. It has also been successfully implemented for primary propulsion in both geocentric and heliocentric environments, with excellent ground/in-space correlation of both its performance and life. Based on these attributes there is compelling reasoning to continue the development of this technology: it is a leading candidate for high power applications; and it provides risk reduction for as-yet unproven alternatives. As such it is important that the operational limitations of ion thruster technology be critically examined and in particular for its application to primary propulsion its capabilities relative to thrust the density and thrust-to-power ratio be understood. This publication briefly addresses some of the considerations relative to achieving high thrust density and maximizing thrust-to-power ratio with ion thruster technology, and discusses the status of development work in this area being executed under a collaborative effort among NASA Glenn Research Center, the Aerospace Corporation, and the University of Michigan.

[A study of complexity and power spectrum of cortical EEG and hippocampal potential in rats under different behavioral states].

PubMed

Feng, Zhou-yan; Zheng, Xiao-xiang

2002-08-01

Objective. To study the complexity and the power spectrum of cortical EEG and hippocampal potential in rats under waking and sleep states. Method. Cortical EEG and hippocampal potential were collected by implanted electrodes in freely moving rats. Algorithmic complexity (Kc), approximate entropy (ApEn), power spectral density (PSD) and gravity frequency of PSD of the potential waves were calculated. Result. The complexity of hippocampal potential was higher than that of cortical EEG under every state. The complexity of cortical EEG was lowest under the state of non rapid eye movement (NREM) sleep. The complexity of hippocampal potential was highest under waking state. The total power of both potentials in 0.5- 30 Hz frequency band showed their highest values under NREM state. Conclusion. The values of Kc and ApEn are closely related to the distributions of PSD. When there are evident peaks in PSD, the complexities of signals will decrease. The complexities may be used to distinguish the difference between cortical EEG and hippocampal potential, or large differences between the same kind of potentials under different behavioral states.

Antioxidative activities of hydrolysates from edible birds nest using enzymatic hydrolysis

NASA Astrophysics Data System (ADS)

Muhammad, Nurul Nadia; Babji, Abdul Salam; Ayub, Mohd Khan

2015-09-01

Edible bird's nest protein hydrolysates (EBN) were prepared via enzymatic hydrolysis to investigate its antioxidant activity. Two types of enzyme (alcalase and papain) were used in this study and EBN had been hydrolysed with different hydrolysis time (30, 60, 90 and 120 min). Antioxidant activities in EBN protein hydrolysate were measured using DPPH, ABTS+ and Reducing Power Assay. From this study, increased hydrolysis time from 30 min to 120 min contributed to higher DH, as shown by alcalase (40.59%) and papain (24.94%). For antioxidant assay, EBN hydrolysed with papain showed higher scavenging activity and reducing power ability compared to alcalase. The highest antioxidant activity for papain was at 120 min hydrolysis time with ABTS (54.245%), DPPH (49.78%) and Reducing Power (0.0680). Meanwhile for alcalase, the highest antioxidant activity was at 30 min hydrolysis time. Even though scavenging activity for EBN protein hydrolysates were high, the reducing power ability was quite low as compared to BHT and ascorbic Acid. This study showed that EBN protein hydrolysate with alcalase and papain treatments potentially exhibit high antioxidant activity which have not been reported before.

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.

An Open-Access Modeled Passenger Flow Matrix for the Global Air Network in 2010

PubMed Central

Huang, Zhuojie; Wu, Xiao; Garcia, Andres J.; Fik, Timothy J.; Tatem, Andrew J.

2013-01-01

The expanding global air network provides rapid and wide-reaching connections accelerating both domestic and international travel. To understand human movement patterns on the network and their socioeconomic, environmental and epidemiological implications, information on passenger flow is required. However, comprehensive data on global passenger flow remain difficult and expensive to obtain, prompting researchers to rely on scheduled flight seat capacity data or simple models of flow. This study describes the construction of an open-access modeled passenger flow matrix for all airports with a host city-population of more than 100,000 and within two transfers of air travel from various publicly available air travel datasets. Data on network characteristics, city population, and local area GDP amongst others are utilized as covariates in a spatial interaction framework to predict the air transportation flows between airports. Training datasets based on information from various transportation organizations in the United States, Canada and the European Union were assembled. A log-linear model controlling the random effects on origin, destination and the airport hierarchy was then built to predict passenger flows on the network, and compared to the results produced using previously published models. Validation analyses showed that the model presented here produced improved predictive power and accuracy compared to previously published models, yielding the highest successful prediction rate at the global scale. Based on this model, passenger flows between 1,491 airports on 644,406 unique routes were estimated in the prediction dataset. The airport node characteristics and estimated passenger flows are freely available as part of the Vector-Borne Disease Airline Importation Risk (VBD-Air) project at: www.vbd-air.com/data. PMID:23691194

An open-access modeled passenger flow matrix for the global air network in 2010.

PubMed

Huang, Zhuojie; Wu, Xiao; Garcia, Andres J; Fik, Timothy J; Tatem, Andrew J

2013-01-01

The expanding global air network provides rapid and wide-reaching connections accelerating both domestic and international travel. To understand human movement patterns on the network and their socioeconomic, environmental and epidemiological implications, information on passenger flow is required. However, comprehensive data on global passenger flow remain difficult and expensive to obtain, prompting researchers to rely on scheduled flight seat capacity data or simple models of flow. This study describes the construction of an open-access modeled passenger flow matrix for all airports with a host city-population of more than 100,000 and within two transfers of air travel from various publicly available air travel datasets. Data on network characteristics, city population, and local area GDP amongst others are utilized as covariates in a spatial interaction framework to predict the air transportation flows between airports. Training datasets based on information from various transportation organizations in the United States, Canada and the European Union were assembled. A log-linear model controlling the random effects on origin, destination and the airport hierarchy was then built to predict passenger flows on the network, and compared to the results produced using previously published models. Validation analyses showed that the model presented here produced improved predictive power and accuracy compared to previously published models, yielding the highest successful prediction rate at the global scale. Based on this model, passenger flows between 1,491 airports on 644,406 unique routes were estimated in the prediction dataset. The airport node characteristics and estimated passenger flows are freely available as part of the Vector-Borne Disease Airline Importation Risk (VBD-Air) project at: www.vbd-air.com/data.

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 ...

Drinking and Smoking Habits of Students at Northern Territory University.

ERIC Educational Resources Information Center

Roberts, Kathryn L.; Jackson, Adrian S.

Persons in the Northern Territory who drink have the highest per capita daily consumption of alcohol and the highest rate of tobacco smoking in Australia. This study identifies the drinking patterns and demographic and personal variables that might predict risk levels for Northern Territory University (NTU) students and therefore give direction to…

Evaluation of a microwave high-power reception-conversion array for wireless power transmission

NASA Technical Reports Server (NTRS)

Dickinson, R. M.

1975-01-01

Initial performance tests of a 24-sq m area array of rectenna elements are presented. The array is used as the receiving portion of a wireless microwave power transmission engineering verification test system. The transmitting antenna was located at a range of 1.54 km. Output dc voltage and power, input RF power, efficiency, and operating temperatures were obtained for a variety of dc load and RF incident power levels at 2388 MHz. Incident peak RF intensities of up to 170 mW/sq cm yielded up to 30.4 kW of dc output power. The highest derived collection-conversion efficiency of the array was greater than 80 percent.

Electromyographic analysis of traditional and nontraditional abdominal exercises: implications for rehabilitation and training.

PubMed

Escamilla, Rafael F; Babb, Eric; DeWitt, Ryan; Jew, Patrick; Kelleher, Patrick; Burnham, Toni; Busch, Juliann; D'Anna, Kristen; Mowbray, Ryan; Imamura, Rodney T

2006-05-01

Performing nontraditional abdominal exercises with devices such as abdominal straps, the Power Wheel, and the Ab Revolutionizer has been suggested as a way to activate abdominal and extraneous (nonabdominal) musculature as effectively as more traditional abdominal exercises, such as the crunch and bent-knee sit-up. The purpose of this study was to test the effectiveness of traditional and nontraditional abdominal exercises in activating abdominal and extraneous musculature. Twenty-one men and women who were healthy and between 23 and 43 years of age were recruited for this study. Surface electromyography (EMG) was used to assess muscle activity from the upper and lower rectus abdominis, external and internal oblique, rectus femoris, latissimus dorsi, and lumbar paraspinal muscles while each exercise was performed. The EMG data were normalized to maximum voluntary muscle contractions. Differences in muscle activity were assessed by a 1-way, repeated-measures analysis of variance. Upper and lower rectus abdominis, internal oblique, and latissimus dorsi muscle EMG activity were highest for the Power Wheel (pike, knee-up, and roll-out), hanging knee-up with straps, and reverse crunch inclined 30 degrees. External oblique muscle EMG activity was highest for the Power Wheel (pike, knee-up, and roll-out) and hanging knee-up with straps. Rectus femoris muscle EMG activity was highest for the Power Wheel (pike and knee-up), reverse crunch inclined 30 degrees, and bent-knee sit-up. Lumbar paraspinal muscle EMG activity was low and similar among exercises. The Power Wheel (pike, knee-up, and roll-out), hanging knee-up with straps, and reverse crunch inclined 30 degrees not only were the most effective exercises in activating abdominal musculature but also were the most effective in activating extraneous musculature. The relatively high rectus femoris muscle activity obtained with the Power Wheel (pike and knee-up), reverse crunch inclined 30 degrees, and bent-knee sit-up may be problematic for some people with low back problems.

Three-Dimensional Magnetic Analysis Technique Developed for Evaluating Stirling Convertor Linear Alternators

NASA Technical Reports Server (NTRS)

Geng, Steven M.

2003-01-01

The Department of Energy, the Stirling Technology Company (STC), and the NASA Glenn Research Center are developing Stirling convertors for Stirling radioisotope generators to provide electrical power for future NASA deep space missions. STC is developing the 55-We technology demonstration convertor (TDC) under contract to the Department of Energy. The Department of Energy recently named Lockheed Martin as the system integration contractor for the Stirling radioisotope generator development project. Lockheed Martin will develop the Stirling radioisotope generator engineering unit and has contract options to develop the qualification unit and the first flight unit. Glenn s role includes an in-house project to provide convertor, component, and materials testing and evaluation in support of the overall power system development. As a part of this work, Glenn has established an in-house Stirling research laboratory for testing, analyzing, and evaluating Stirling machines. STC has built four 55-We convertors for NASA, and these are being tested at Glenn. A cross-sectional view of the 55-We TDC is shown in the figure. Of critical importance to the successful development of the Stirling convertor for space power applications is the development of a lightweight and highly efficient linear alternator. In support, Glenn has been developing finite element analysis and finite element method tools for performing various linear alternator thermal and electromagnetic analyses and evaluating design configurations. A three-dimensional magnetostatic finite element model of STC's 55-We TDC linear alternator was developed to evaluate the demagnetization fields affecting the alternator magnets. Since the actual linear alternator hardware is symmetric to the quarter section about the axis of motion, only a quarter section of the alternator was modeled. The components modeled included the mover laminations, the neodymium-iron-boron magnets, the stator laminations, and the copper coils. The three-dimensional magnetostatic model was then coupled with a circuit simulator model of the alternator load and convertor controller. The coupled model was then used to generate alternator terminal voltage and current predictions. The predicted voltage and current waveforms agreed well with the experimental data, which tended to validate the accuracy of the coupled model. The model was then used to generate predictions of the demagnetization fields acting on the alternator magnets for the alternator under load. The preliminary model predictions indicate that the highest potential for demagnetization is along the inside surface of the uncovered magnets. The demagnetization field for the uncovered magnets when the mover is positioned at the end of a stroke is higher than it is when the mover is at the position of maximum induced voltage or maximum alternator current. Assuming normal load conditions, the model predicted that the onset of demagnetization is most likely to occur for magnet temperatures above 101 C.

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.

A W-band integrated power module using MMIC MESFET power amplifiers and varactor doublers

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

Ho, T.C.; Chen, Seng Woon; Pande, K.

1993-12-01

A high-performance integrated power module using U-band MMIC MESFET power amplifiers in conjunction with W-band MMIC high efficiency varactor doublers has been developed for millimeter-wave system applications. This paper presents the design, fabrication, and performance of this W-band integrated power module. Measured results of the complete integrated power module show an output power of 90 mW with an overall associated gain of 29.5 dB at 94 GHz. A saturated power of over 95 mW was also achieved. These results represent the highest reported power and gain at W-band using MESFET and varactor frequency doubling technologies. This integrated power module ismore » suitable for the future 94 GHz missile seeker applications.« less

Added prognostic value of ischaemic threshold in radionuclide myocardial perfusion imaging: a common-sense integration of exercise tolerance and ischaemia severity.

PubMed

Marini, Cecilia; Acampa, Wanda; Bauckneht, Matteo; Daniele, Stefania; Capitanio, Selene; Cantoni, Valeria; Fiz, Francesco; Zampella, Emilia; Dib, Bassam; Assante, Roberta; Bruzzi, Paolo; Sambuceti, Gianmario; Cuocolo, Alberto

2015-04-01

Reversible ischaemia at radionuclide myocardial perfusion imaging (MPI) accurately predicts risk of cardiac death and nonfatal myocardial infarction (major adverse cardiac events, MACE). This prognostic penetrance might be empowered by accounting for exercise tolerance as an indirect index of ischaemia severity. The present study aimed to verify this hypothesis integrating imaging assessment of ischaemia severity with exercise maximal rate pressure product (RPP) in a large cohort of patients with suspected or known coronary artery disease (CAD). We analysed 1,502 consecutive patients (1,014 men aged 59 ± 10 years) submitted to exercise stress/rest MPI. To account for exercise tolerance, the summed difference score (SDS) was divided by RPP at tracer injection providing a clinical prognostic index (CPI). Reversible ischaemia was documented in 357 patients (24 %) and was classified by SDS as mild (SDS 2-4) in 180, moderate (SDS 5-7) in 118 and severe (SDS >7) in 59. CPI values of ischaemic patients were clustered into tertiles with lowest and highest values indicating low and high risk, respectively. CPI modified SDS risk prediction in 119/357 (33 %) patients. During a 60-month follow-up, MACE occurred in 68 patients. Kaplan-Meier analysis revealed that CPI significantly improved predictive power for MACE incidence with respect to SDS alone. Multivariate Cox analysis confirmed the additive independent value of CPI-derived information. Integration of ischaemic threshold and ischaemia extension and severity can improve accuracy of exercise MPI in predicting long-term outcome in a large cohort of patients with suspected or known CAD.

Neuropsychological predictors of conversion to probable Alzheimer disease in elderly with mild cognitive impairment.

PubMed

García-Herranz, Sara; Díaz-Mardomingo, M Carmen; Peraita, Herminia

2016-09-01

In the field of neuropsychology, it is essential to determine which neuropsychological tests predict Alzheimer's disease (AD) in people with mild cognitive impairment (MCI) and which cut-off points should be used to identify people at greater risk for converting to dementia. The aim of the present study was to analyse the predictive value of the cognitive tests included in a neuropsychological battery for conversion to AD among MCI participants and to analyse the influence of some sociodemographic variables - sex, age, schooling - and others, such as follow-up time and emotional state. A total of 105 participants were assessed with a neuropsychological battery at baseline and during a 3-year follow-up period. For the present study, the data were analysed at baseline. During the follow-up period, 24 participants (22.85%) converted to dementia (2.79 ± 1.14 years) and 81 (77.14%) remained as MCI. The logistic regression analysis determined that the long delay cued recall and the performance time of the Rey figure test were the best predictive tests of conversion to dementia after an MCI diagnosis. Concerning the sociodemographic factors, sex had the highest predictive power. The results reveal the relevance of the neuropsychological data obtained in the first assessment. Specifically, the data obtained in the episodic verbal memory tests and tests that assess visuospatial and executive components may help to identify people with MCI who may develop AD in an interval not longer than 4 years, with the masculine gender being an added risk factor. © 2015 The British Psychological Society.

Poverty, AIDS and child health: identifying highest-risk children in South Africa.

PubMed

Cluver, Lucie; Boyes, Mark; Orkin, Mark; Sherr, Lorraine

2013-10-11

Identifying children at the highest risk of negative health effects is a prerequisite to effective public health policies in Southern Africa. A central ongoing debate is whether poverty, orphanhood or parental AIDS most reliably indicates child health risks. Attempts to address this key question have been constrained by a lack of data allowing distinction of AIDS-specific parental death or morbidity from other causes of orphanhood and chronic illness. To examine whether household poverty, orphanhood and parental illness (by AIDS or other causes) independently or interactively predict child health, developmental and HIV-infection risks. We interviewed 6 002 children aged 10 - 17 years in 2009 - 2011, using stratified random sampling in six urban and rural sites across three South African provinces. Outcomes were child mental health risks, educational risks and HIV-infection risks. Regression models that controlled for socio-demographic co-factors tested potential impacts and interactions of poverty, AIDS-specific and other orphanhood and parental illness status. Household poverty independently predicted child mental health and educational risks, AIDS orphanhood independently predicted mental health risks and parental AIDS illness independently predicted mental health, educational and HIV-infection risks. Interaction effects of poverty with AIDS orphanhood and parental AIDS illness were found across all outcomes. No effects, or interactions with poverty, were shown by AIDS-unrelated orphanhood or parental illness. The identification of children at highest risk requires recognition and measurement of both poverty and parental AIDS. This study shows negative impacts of poverty and AIDS-specific vulnerabilities distinct from orphanhood and adult illness more generally. Additionally, effects of interaction between family AIDS and poverty suggest that, where these co-exist, children are at highest risk of all.

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.

An Approach for Predicting Essential Genes Using Multiple Homology Mapping and Machine Learning Algorithms.

PubMed

Hua, Hong-Li; Zhang, Fa-Zhan; Labena, Abraham Alemayehu; Dong, Chuan; Jin, Yan-Ting; Guo, Feng-Biao

Investigation of essential genes is significant to comprehend the minimal gene sets of cell and discover potential drug targets. In this study, a novel approach based on multiple homology mapping and machine learning method was introduced to predict essential genes. We focused on 25 bacteria which have characterized essential genes. The predictions yielded the highest area under receiver operating characteristic (ROC) curve (AUC) of 0.9716 through tenfold cross-validation test. Proper features were utilized to construct models to make predictions in distantly related bacteria. The accuracy of predictions was evaluated via the consistency of predictions and known essential genes of target species. The highest AUC of 0.9552 and average AUC of 0.8314 were achieved when making predictions across organisms. An independent dataset from Synechococcus elongatus , which was released recently, was obtained for further assessment of the performance of our model. The AUC score of predictions is 0.7855, which is higher than other methods. This research presents that features obtained by homology mapping uniquely can achieve quite great or even better results than those integrated features. Meanwhile, the work indicates that machine learning-based method can assign more efficient weight coefficients than using empirical formula based on biological knowledge.

High-power diode-side-pumped rod Tm:YAG laser at 2.07 μm.

PubMed

Wang, Caili; Niu, Yanxiong; Du, Shifeng; Zhang, Chao; Wang, Zhichao; Li, Fangqin; Xu, Jialin; Bo, Yong; Peng, Qinjun; Cui, Dafu; Zhang, Jingyuan; Xu, Zuyan

2013-11-01

We report a high-power diode-laser (LD) side-pumped rod Tm:YAG laser of around 2 μm. The laser was water-cooled at 8°C and yielded a maximum output power of 267 W at 2.07 μm, which is the highest output power for an all solid-state cw 2.07 μm rod Tm:YAG laser reported as far as we know. The corresponding optical-optical conversion efficiency was 20.7%, and the slope efficiency was about 29.8%, respectively.

Comparison of personal characteristics, tobacco use, and health states in Chaldean, Arab American, and non-Middle Eastern White adults.

PubMed

Jamil, H; Templin, T; Fakhouri, M; Rice, V H; Khouri, R; Fakhouri, H; Al-Omran, Hasan; Al-Fauori, Ibrahim; Baker, Omar

2009-08-01

This study compared and contrasted personal characteristics, tobacco use (cigarette and water pipe smoking), and health states in Chaldean, Arab American and non-Middle Eastern White adults attending an urban community service center. The average age was 39.4 (SD = 14.2). The three groups differed significantly (P < .006) on ethnicity, age, gender distribution, marital status, language spoken, education, employment, and annual income. Current cigarette smoking was highest for non-Middle Eastern White adults (35.4%) and current water pipe smoking was highest for Arab Americans (3.6%). Arab Americans were more likely to smoke both cigarettes and the narghile (4.3%). Health problems were highest among former smokers in all three ethnic groups. Being male, older, unmarried, and non-Middle Eastern White predicted current cigarette smoking; being Arab or Chaldean and having less formal education predicted current water pipe use.

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.

Multi-class biological tissue classification based on a multi-classifier: Preliminary study of an automatic output power control for ultrasonic surgical units.

PubMed

Youn, Su Hyun; Sim, Taeyong; Choi, Ahnryul; Song, Jinsung; Shin, Ki Young; Lee, Il Kwon; Heo, Hyun Mu; Lee, Daeweon; Mun, Joung Hwan

2015-06-01

Ultrasonic surgical units (USUs) have the advantage of minimizing tissue damage during surgeries that require tissue dissection by reducing problems such as coagulation and unwanted carbonization, but the disadvantage of requiring manual adjustment of power output according to the target tissue. In order to overcome this limitation, it is necessary to determine the properties of in vivo tissues automatically. We propose a multi-classifier that can accurately classify tissues based on the unique impedance of each tissue. For this purpose, a multi-classifier was built based on single classifiers with high classification rates, and the classification accuracy of the proposed model was compared with that of single classifiers for various electrode types (Type-I: 6 mm invasive; Type-II: 3 mm invasive; Type-III: surface). The sensitivity and positive predictive value (PPV) of the multi-classifier by cross checks were determined. According to the 10-fold cross validation results, the classification accuracy of the proposed model was significantly higher (p<0.05 or <0.01) than that of existing single classifiers for all electrode types. In particular, the classification accuracy of the proposed model was highest when the 3mm invasive electrode (Type-II) was used (sensitivity=97.33-100.00%; PPV=96.71-100.00%). The results of this study are an important contribution to achieving automatic optimal output power adjustment of USUs according to the properties of individual tissues. Copyright © 2015 Elsevier Ltd. All rights reserved.

Impact of follicular G-CSF quantification on subsequent embryo transfer decisions: a proof of concept study.

PubMed

Lédée, N; Gridelet, V; Ravet, S; Jouan, C; Gaspard, O; Wenders, F; Thonon, F; Hincourt, N; Dubois, M; Foidart, J M; Munaut, C; Perrier d'Hauterive, S

2013-02-01

Previous experiments have shown that granulocyte colony-stimulating factor (G-CSF), quantified in the follicular fluid (FF) of individual oocytes, correlates with the potential for an ongoing pregnancy of the corresponding fertilized oocytes among selected transferred embryos. Here we present a proof of concept study aimed at evaluating the impact of including FF G-CSF quantification in the embryo transfer decisions. FF G-CSF was quantified with the Luminex XMap technology in 523 individual FF samples corresponding to 116 fresh transferred embryos, 275 frozen embryos and 131 destroyed embryos from 78 patients undergoing ICSI. Follicular G-CSF was highly predictive of subsequent implantation. The receiving operator characteristics curve methodology showed its higher discriminatory power to predict ongoing pregnancy in multivariate logistic regression analysis for FF G-CSF compared with embryo morphology [0.77 (0.69-0.83), P < 0.001 versus 0.66 (0.58-0.73), P = 0.01)]. Embryos were classified by their FF G-CSF concentration: Class I over 30 pg/ml (a highest positive predictive value for implantation), Class II from 30 to 18.4 pg/ml and Class III <18.4 pg/ml (a highest negative predictive value). Embryos derived from Class I follicles had a significantly higher implantation rate (IR) than those from Class II and III follicles (36 versus 16.6 and 6%, P < 0.001). Embryos derived from Class I follicles with an optimal morphology reached an IR of 54%. Frozen-thawed embryos transfer derived from Class I follicles had an IR of 37% significantly higher than those from Class II and III follicles, respectively, of 8 and 5% (P < 0.001). Thirty-five per cent of the frozen embryos but also 10% of the destroyed embryos were derived from G-CSF Class I follicles. Non-optimal embryos appear to have been transferred in 28% (22/78) of the women, and their pregnancy rate was significantly lower than that of women who received at least one optimal embryo (18 versus 36%, P = 0.04). Monitoring FF G-CSF for the selection of embryos with a better potential for pregnancy might improve the effectiveness of IVF by reducing the time and cost required for obtaining a pregnancy.

Improved accuracy of intraocular lens power calculation with the Zeiss IOLMaster.

PubMed

Olsen, Thomas

2007-02-01

This study aimed to demonstrate how the level of accuracy in intraocular lens (IOL) power calculation can be improved with optical biometry using partial optical coherence interferometry (PCI) (Zeiss IOLMaster) and current anterior chamber depth (ACD) prediction algorithms. Intraocular lens power in 461 consecutive cataract operations was calculated using both PCI and ultrasound and the accuracy of the results of each technique were compared. To illustrate the importance of ACD prediction per se, predictions were calculated using both a recently published 5-variable method and the Haigis 2-variable method and the results compared. All calculations were optimized in retrospect to account for systematic errors, including IOL constants and other off-set errors. The average absolute IOL prediction error (observed minus expected refraction) was 0.65 dioptres with ultrasound and 0.43 D with PCI using the 5-variable ACD prediction method (p < 0.00001). The number of predictions within +/- 0.5 D, +/- 1.0 D and +/- 2.0 D of the expected outcome was 62.5%, 92.4% and 99.9% with PCI, compared with 45.5%, 77.3% and 98.4% with ultrasound, respectively (p < 0.00001). The 2-variable ACD method resulted in an average error in PCI predictions of 0.46 D, which was significantly higher than the error in the 5-variable method (p < 0.001). The accuracy of IOL power calculation can be significantly improved using calibrated axial length readings obtained with PCI and modern IOL power calculation formulas incorporating the latest generation ACD prediction algorithms.

Using a Guided Machine Learning Ensemble Model to Predict Discharge Disposition following Meningioma Resection.

PubMed

Muhlestein, Whitney E; Akagi, Dallin S; Kallos, Justiss A; Morone, Peter J; Weaver, Kyle D; Thompson, Reid C; Chambless, Lola B

2018-04-01

Objective  Machine learning (ML) algorithms are powerful tools for predicting patient outcomes. This study pilots a novel approach to algorithm selection and model creation using prediction of discharge disposition following meningioma resection as a proof of concept. Materials and Methods  A diversity of ML algorithms were trained on a single-institution database of meningioma patients to predict discharge disposition. Algorithms were ranked by predictive power and top performers were combined to create an ensemble model. The final ensemble was internally validated on never-before-seen data to demonstrate generalizability. The predictive power of the ensemble was compared with a logistic regression. Further analyses were performed to identify how important variables impact the ensemble. Results  Our ensemble model predicted disposition significantly better than a logistic regression (area under the curve of 0.78 and 0.71, respectively, p  = 0.01). Tumor size, presentation at the emergency department, body mass index, convexity location, and preoperative motor deficit most strongly influence the model, though the independent impact of individual variables is nuanced. Conclusion  Using a novel ML technique, we built a guided ML ensemble model that predicts discharge destination following meningioma resection with greater predictive power than a logistic regression, and that provides greater clinical insight than a univariate analysis. These techniques can be extended to predict many other patient outcomes of interest.

Hybrid robust predictive optimization method of power system dispatch

DOEpatents

Chandra, Ramu Sharat [Niskayuna, NY; Liu, Yan [Ballston Lake, NY; Bose, Sumit [Niskayuna, NY; de Bedout, Juan Manuel [West Glenville, NY

2011-08-02

A method of power system dispatch control solves power system dispatch problems by integrating a larger variety of generation, load and storage assets, including without limitation, combined heat and power (CHP) units, renewable generation with forecasting, controllable loads, electric, thermal and water energy storage. The method employs a predictive algorithm to dynamically schedule different assets in order to achieve global optimization and maintain the system normal operation.

Power capability evaluation for lithium iron phosphate batteries based on multi-parameter constraints estimation

NASA Astrophysics Data System (ADS)

Wang, Yujie; Pan, Rui; Liu, Chang; Chen, Zonghai; Ling, Qiang

2018-01-01

The battery power capability is intimately correlated with the climbing, braking and accelerating performance of the electric vehicles. Accurate power capability prediction can not only guarantee the safety but also regulate driving behavior and optimize battery energy usage. However, the nonlinearity of the battery model is very complex especially for the lithium iron phosphate batteries. Besides, the hysteresis loop in the open-circuit voltage curve is easy to cause large error in model prediction. In this work, a multi-parameter constraints dynamic estimation method is proposed to predict the battery continuous period power capability. A high-fidelity battery model which considers the battery polarization and hysteresis phenomenon is presented to approximate the high nonlinearity of the lithium iron phosphate battery. Explicit analyses of power capability with multiple constraints are elaborated, specifically the state-of-energy is considered in power capability assessment. Furthermore, to solve the problem of nonlinear system state estimation, and suppress noise interference, the UKF based state observer is employed for power capability prediction. The performance of the proposed methodology is demonstrated by experiments under different dynamic characterization schedules. The charge and discharge power capabilities of the lithium iron phosphate batteries are quantitatively assessed under different time scales and temperatures.

Balancing computation and communication power in power constrained clusters

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

Piga, Leonardo; Paul, Indrani; Huang, Wei

Systems, apparatuses, and methods for balancing computation and communication power in power constrained environments. A data processing cluster with a plurality of compute nodes may perform parallel processing of a workload in a power constrained environment. Nodes that finish tasks early may be power-gated based on one or more conditions. In some scenarios, a node may predict a wait duration and go into a reduced power consumption state if the wait duration is predicted to be greater than a threshold. The power saved by power-gating one or more nodes may be reassigned for use by other nodes. A cluster agentmore » may be configured to reassign the unused power to the active nodes to expedite workload processing.« less

Modeling of a resonant heat engine

NASA Astrophysics Data System (ADS)

Preetham, B. S.; Anderson, M.; Richards, C.

2012-12-01

A resonant heat engine in which the piston assembly is replaced by a sealed elastic cavity is modeled and analyzed. A nondimensional lumped-parameter model is derived and used to investigate the factors that control the performance of the engine. The thermal efficiency predicted by the model agrees with that predicted from the relation for the Otto cycle based on compression ratio. The predictions show that for a fixed mechanical load, increasing the heat input results in increased efficiency. The output power and power density are shown to depend on the loading for a given heat input. The loading condition for maximum output power is different from that required for maximum power density.

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

NASA Astrophysics Data System (ADS)

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

2013-05-01

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

Prediction of the effects of propeller operation on the static longitudinal stability of single-engine tractor monoplanes with flaps retracted

NASA Technical Reports Server (NTRS)

Weil, Joseph; Sleeman, William C , Jr

1949-01-01

The effects of propeller operation on the static longitudinal stability of single-engine tractor monoplanes are analyzed, and a simple method is presented for computing power-on pitching-moment curves for flap-retracted flight conditions. The methods evolved are based on the results of powered-model wind-tunnel investigations of 28 model configurations. Correlation curves are presented from which the effects of power on the downwash over the tail and the stabilizer effectiveness can be rapidly predicted. The procedures developed enable prediction of power-on longitudinal stability characteristics that are generally in very good agreement with experiment.

An Operating Method Using Prediction of Photovoltaic Power for a Photovoltaic-Diesel Hybrid Power Generation System

NASA Astrophysics Data System (ADS)

Yamamoto, Shigehiro; Sumi, Kazuyoshi; Nishikawa, Eiichi; Hashimoto, Takeshi

This paper describes a novel operating method using prediction of photovoltaic (PV) power for a photovoltaic-diesel hybrid power generation system. The system is composed of a PV array, a storage battery, a bi-directional inverter and a diesel engine generator (DG). The proposed method enables the system to save fuel consumption by using PV energy effectively, reducing charge and discharge energy of the storage battery, and avoiding low-load operation of the DG. The PV power is simply predicted from a theoretical equation of solar radiation and the observed PV energy for a constant time before the prediction. The amount of fuel consumption of the proposed method is compared with that of other methods by a simulation based on measurement data of the PV power at an actual PV generation system for one year. The simulation results indicate that the amount of fuel consumption of the proposed method is smaller than that of any other methods, and is close to that of the ideal operation of the DG.

A Comparison between Bench Press Throw and Ballistic Push-Up tests to assess upper-body power in trained individuals.

PubMed

Bartolomei, Sandro; Nigro, Federico; Ruggeri, Sandro; Lanzoni, Ivan Malagoli; Ciacci, Simone; Merni, Franco; Sadres, Eliahu; Hoffman, Jay R; Semprini, Gabriele

2018-03-06

The purpose of the present study was to validate the ballistic push-up test performed with hands on a force plate (BPU) as a method to measure upper-body power. Twenty-eight experienced resistance trained men (age = 25.4 ± 5.2 y; body mass = 78.5 ± 9.0 kg; body height = 179.6 ± 7.8 cm) performed, two days apart, a bench press 1RM test and upper-body power tests. Mean power and peak power were assessed using the bench press throw test (BT) and the BPU test performed in randomized order. The area under the force/power curve (AUC) obtained at BT was also calculated. Power expressed at BPU was estimated using a time-based prediction equation. Mean force and the participant's body weight were used to predict the bench press 1RM. Pearson product moment correlations were used to examine relationships between the power assessment methods and between the predicted 1RM bench and the actual value. Large correlations (0.79; p < 0.001) were found between AUC and mean power expressed at BPU. Large correlations were also detected between mean power and peak power expressed at BT and BPU (0.75; p < 0.001 and 0.74; p < 0.001, respectively). Very large correlations (0.87; p < 0.001) were found between the 1RM bench and the 1RM predicted by the BPU. Results of the present study indicate that BPU represents a valid and reliable method to estimate the upper-body power in resistance-trained individuals.

Development and internal validation of a side-specific, multiparametric magnetic resonance imaging-based nomogram for the prediction of extracapsular extension of prostate cancer.

PubMed

Martini, Alberto; Gupta, Akriti; Lewis, Sara C; Cumarasamy, Shivaram; Haines, Kenneth G; Briganti, Alberto; Montorsi, Francesco; Tewari, Ashutosh K

2018-04-19

To develop a nomogram for predicting side-specific extracapsular extension (ECE) for planning nerve-sparing radical prostatectomy. We retrospectively analysed data from 561 patients who underwent robot-assisted radical prostatectomy between February 2014 and October 2015. To develop a side-specific predictive model, we considered the prostatic lobes separately. Four variables were included: prostate-specific antigen; highest ipsilateral biopsy Gleason grade; highest ipsilateral percentage core involvement; and ECE on multiparametric magnetic resonance imaging (mpMRI). A multivariable logistic regression analysis was fitted to predict side-specific ECE. A nomogram was built based on the coefficients of the logit function. Internal validation was performed using 'leave-one-out' cross-validation. Calibration was graphically investigated. The decision curve analysis was used to evaluate the net clinical benefit. The study population consisted of 829 side-specific cases, after excluding negative biopsy observations (n = 293). ECE was reported on mpMRI and final pathology in 115 (14%) and 142 (17.1%) cases, respectively. Among these, mpMRI was able to predict ECE correctly in 57 (40.1%) cases. All variables in the model except highest percentage core involvement were predictors of ECE (all P ≤ 0.006). All variables were considered for inclusion in the nomogram. After internal validation, the area under the curve was 82.11%. The model demonstrated excellent calibration and improved clinical risk prediction, especially when compared with relying on mpMRI prediction of ECE alone. When retrospectively applying the nomogram-derived probability, using a 20% threshold for performing nerve-sparing, nine out of 14 positive surgical margins (PSMs) at the site of ECE resulted above the threshold. We developed an easy-to-use model for the prediction of side-specific ECE, and hope it serves as a tool for planning nerve-sparing radical prostatectomy and in the reduction of PSM in future series. © 2018 The Authors BJU International © 2018 BJU International Published by John Wiley & Sons Ltd.

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

12 CFR 747.302 - Rules of practice; remainder of board of directors.

Code of Federal Regulations, 2010 CFR

2010-01-01

...) Power of attorney and notice of appearance. Any person who is a member in good standing of the bar of the highest court of any State, possession, territory, Commonwealth, or the District of Columbia may... required to file with the NCUA Board a power of attorney showing his or her authority to act in such...

Prediction of absolute risk of fragility fracture at 10 years in a Spanish population: validation of the WHO FRAX ™ tool in Spain

PubMed Central

2011-01-01

Background Age-related bone loss is asymptomatic, and the morbidity of osteoporosis is secondary to the fractures that occur. Common sites of fracture include the spine, hip, forearm and proximal humerus. Fractures at the hip incur the greatest morbidity and mortality and give rise to the highest direct costs for health services. Their incidence increases exponentially with age. Independently changes in population demography, the age - and sex- specific incidence of osteoporotic fractures appears to be increasing in developing and developed countries. This could mean more than double the expected burden of osteoporotic fractures in the next 50 years. Methods/Design To assess the predictive power of the WHO FRAX™ tool to identify the subjects with the highest absolute risk of fragility fracture at 10 years in a Spanish population, a predictive validation study of the tool will be carried out. For this purpose, the participants recruited by 1999 will be assessed. These were referred to scan-DXA Department from primary healthcare centres, non hospital and hospital consultations. Study population: Patients attended in the national health services integrated into a FRIDEX cohort with at least one Dual-energy X-ray absorptiometry (DXA) measurement and one extensive questionnaire related to fracture risk factors. Measurements: At baseline bone mineral density measurement using DXA, clinical fracture risk factors questionnaire, dietary calcium intake assessment, history of previous fractures, and related drugs. Follow up by telephone interview to know fragility fractures in the 10 years with verification in electronic medical records and also to know the number of falls in the last year. The absolute risk of fracture will be estimated using the FRAX™ tool from the official web site. Discussion Since more than 10 years ago numerous publications have recognised the importance of other risk factors for new osteoporotic fractures in addition to low BMD. The extension of a method for calculating the risk (probability) of fractures using the FRAX™ tool is foreseeable in Spain and this would justify a study such as this to allow the necessary adjustments in calibration of the parameters included in the logarithmic formula constituted by FRAX™. PMID:21272372

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

Energy harvesting for human wearable and implantable bio-sensors.

PubMed

Mitcheson, Paul D

2010-01-01

There are clear trade-offs between functionality, battery lifetime and battery volume for wearable and implantable wireless-biosensors which energy harvesting devices may be able to overcome. Reliable energy harvesting has now become a reality for machine condition monitoring and is finding applications in chemical process plants, refineries and water treatment works. However, practical miniature devices that can harvest sufficient energy from the human body to power a wireless bio-sensor are still in their infancy. This paper reviews the options for human energy harvesting in order to determine power availability for harvester-powered body sensor networks. The main competing technologies for energy harvesting from the human body are inertial kinetic energy harvesting devices and thermoelectric devices. These devices are advantageous to some other types as they can be hermetically sealed. In this paper the fundamental limit to the power output of these devices is compared as a function of generator volume when attached to a human whilst walking and running. It is shown that the kinetic energy devices have the highest fundamental power limits in both cases. However, when a comparison is made between the devices using device effectivenesses figures from previously demonstrated prototypes presented in the literature, the thermal device is competitive with the kinetic energy harvesting device when the subject is running and achieves the highest power density when the subject is walking.

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.

Determination of the diagnostic value of the Modified Mallampati Score, Upper Lip Bite Test and Facial Angle in predicting difficult intubation: A prospective descriptive study.

PubMed

Mahmoodpoor, Ata; Soleimanpour, Hassan; Golzari, Samad Ej; Nejabatian, Arezoo; Pourlak, Tannaz; Amani, Masoumeh; Hajmohammadi, Saeed; Hosseinzadeh, Hamzeh; Esfanjani, Robab Mehdizadeh

2017-02-01

Difficult intubation is a significant cause of mortality and morbidity related to anesthesia. We decided to evaluate the value of Modified Mallampati Score, Upper Lip Bite Test and Facial Angle in the prediction of difficult intubation. In a prospective descriptive study, data from 132 patients who were candidates for elective maxillofacial surgeries under general anesthesia were gathered. Facial Angles were measured by a maxillofacial surgeon according to cephalometry. The Modified Mallampati Score and Upper Lip Bite Test were first measured by an anesthesiologist and then another anesthesiologist was assigned to record the Cormack and Lehane score during the intubation. Grades 3 and 4 were considered as difficult intubation. Sensitivity, specificity, positive predictive value, negative predictive value and Youden index were calculated for all tests. Difficult intubation was reported in 12% of the patients. Facial Angle≤82.5° can predict difficult intubation with 87.5% sensitivity and 88.8% specificity. Among the three tests, a high Modified Mallampati Score had the highest specificity (94.5%) and a high Modified Mallampati Score and Facial Angle (FA≤82.5°) had the highest sensitivity (87.5%). The highest NPV, sensitivity and Youden index were observed when using Facial Angle with the Modified Mallampati Score or with Upper Lip Bite Test. Facial Angle has a high sensitivity, NPV and Youden index for the prediction of difficult intubation, but the best result is achieved when Facial Angle is used in combination with either the Modified Mallampati Score or Upper Lip Bit Test. Copyright © 2017 Elsevier Inc. All rights reserved.

Predicting obstructive coronary artery disease using carotid ultrasound parameters: a nomogram from a large real-world clinical data.

PubMed

Wu, Na; Chen, Xinghua; Li, Mingyang; Qu, Xiaolong; Li, Yueli; Xie, Weijia; Wu, Long; Xiang, Ying; Li, Yafei; Zhong, Li

2018-05-21

Carotid ultrasound is a non-invasive tool for risk assessment of coronary artery disease (CAD). There is no consensus on which carotid ultrasound parameter constitutes the best measurement of atherosclerosis. We investigated which model of carotid ultrasound parameters and clinical risk factors (CRF) have the highest predictive value for CAD. We enrolled 2431 consecutive patients who have suspected CAD and underwent coronary angiography and carotid ultrasound with measurements of carotid intima-media thickness (CIMT), total number of plaques and areas of different types of plaques classified by echogenicity. Total number of plaques demonstrated the highest incremental prediction ability to predict CAD over CRF (area under the curve [AUC] 0.752 vs 0.701, net reclassification index [NRI] = 0.514, P < 0.001), followed by area of maximum mixed and soft plaques. CIMT had no significant incremental value over CRF (AUC 0.704 vs 0.701, P = 0.241; NRI = 0.062, P = 0.168). The model comprising total number of plaques, areas of maximum soft, hard and mixed plaques plus CRF had the highest discriminatory (AUC = 0.757) and reclassification value (NRI = 0.567) for CAD. A nomogram based on this model was developed to predict CAD. For subjects at low and intermediate risk, the model comprising total number of plaques plus CRF was the best. Total number of plaques, area of maximum soft, hard and mixed plaques showed significantly incremental prediction ability over CRF. A nomogram based on these factors provided an intuitive and practical method in detecting CAD. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Purchasing power of civil servant health workers in Mozambique.

PubMed

Ferrinho, Fátima; Amaral, Marta; Russo, Giuliano; Ferrinho, Paulo

2012-01-01

Health workers' purchasing power is an important consideration in the development of strategies for health workforce development. This work explores the purchasing power variation of Mozambican public sector health workers, between 1999 and 2007. In general, the calculated purchasing power increased for most careers under study, and the highest percentage increase was observed for the lowest remuneration careers, contributing in this way for a relative reduction in the difference between the higher and the lower salaries. This was done through a simple and easy-to-apply methodology to estimate salaries' capitalization rate, by means of the accumulated inflation rate, after taking wage revisions into account. All the career categories in the Ministry of Health and affiliated public sector institutions were considered. Health workers' purchasing power is an important consideration in the development of strategies for health workforce development. This work explores the purchasing power variation of Mozambican public sector health workers, between 1999 and 2007. In general, the calculated purchasing power increased for most careers under study, and the highest percentage increase was observed for the lowest remuneration careers, contributing in this way for a relative reduction in the difference between the higher and the lower salaries. These results seem to contradict a commonly held assumption that health sector pay has deteriorated over the years, and with substantial damage for the poorest. Further studies appear to be needed to design a more accurate methodology to better understand the evolution and impact of public sector health workers' remunerations across the years.

Biomechanical evaluation of tibial bone adaptation after revision total knee arthroplasty: A comparison of different implant systems

PubMed Central

Quilez, María Paz; Seral, Belen; Pérez, María Angeles

2017-01-01

The best methods to manage tibial bone defects following total knee arthroplasty remain under debate. Different fixation systems exist to help surgeons reconstruct knee osseous bone loss (such as tantalum cones, cement, modular metal augments, autografts, allografts and porous metaphyseal sleeves) However, the effects of the various solutions on the long-term outcome remain unknown. In the present work, a bone remodeling mathematical model was used to predict bone remodeling after total knee arthroplasty (TKA) revision. Five different types of prostheses were analyzed: one with a straight stem; two with offset stems, with and without supplements; and two with sleeves, with and without stems. Alterations in tibia bone density distribution and implant Von Mises stresses were quantified. In all cases, the bone density decreased in the proximal epiphysis and medullary channels, and an increase in bone density was predicted in the diaphysis and around stem tips. The highest bone resorption was predicted for the offset prosthesis without the supplement, and the highest bone formation was computed for the straight stem. The highest Von Mises stress was obtained for the straight tibial stem, and the lowest was observed for the stemless metaphyseal sleeves prosthesis. The computational model predicted different behaviors among the five systems. We were able to demonstrate the importance of choosing an adequate revision system and that in silico models may help surgeons choose patient-specific treatments. PMID:28886100

Measured and predicted rotor performance for the SERI advanced wind turbine blades

NASA Astrophysics Data System (ADS)

Tangler, J.; Smith, B.; Kelley, N.; Jager, D.

1992-02-01

Measured and predicted rotor performance for the Solar Energy Research Institute (SERI) advanced wind turbine blades were compared to assess the accuracy of predictions and to identify the sources of error affecting both predictions and measurements. An awareness of these sources of error contributes to improved prediction and measurement methods that will ultimately benefit future rotor design efforts. Propeller/vane anemometers were found to underestimate the wind speed in turbulent environments such as the San Gorgonio Pass wind farm area. Using sonic or cup anemometers, good agreement was achieved between predicted and measured power output for wind speeds up to 8 m/sec. At higher wind speeds an optimistic predicted power output and the occurrence of peak power at wind speeds lower than measurements resulted from the omission of turbulence and yaw error. In addition, accurate two-dimensional (2-D) airfoil data prior to stall and a post stall airfoil data synthesization method that reflects three-dimensional (3-D) effects were found to be essential for accurate performance prediction.

NASA Lewis Stirling engine computer code evaluation

NASA Technical Reports Server (NTRS)

Sullivan, Timothy J.

1989-01-01

In support of the U.S. Department of Energy's Stirling Engine Highway Vehicle Systems program, the NASA Lewis Stirling engine performance code was evaluated by comparing code predictions without engine-specific calibration factors to GPU-3, P-40, and RE-1000 Stirling engine test data. The error in predicting power output was -11 percent for the P-40 and 12 percent for the Re-1000 at design conditions and 16 percent for the GPU-3 at near-design conditions (2000 rpm engine speed versus 3000 rpm at design). The efficiency and heat input predictions showed better agreement with engine test data than did the power predictions. Concerning all data points, the error in predicting the GPU-3 brake power was significantly larger than for the other engines and was mainly a result of inaccuracy in predicting the pressure phase angle. Analysis into this pressure phase angle prediction error suggested that improvements to the cylinder hysteresis loss model could have a significant effect on overall Stirling engine performance predictions.

Magnetic storm effects in electric power systems and prediction needs

NASA Technical Reports Server (NTRS)

Albertson, V. D.; Kappenman, J. G.

1979-01-01

Geomagnetic field fluctuations produce spurious currents in electric power systems. These currents enter and exit through points remote from each other. The fundamental period of these currents is on the order of several minutes which is quasi-dc compared to the normal 60 Hz or 50 Hz power system frequency. Nearly all of the power systems problems caused by the geomagnetically induced currents result from the half-cycle saturation of power transformers due to simultaneous ac and dc excitation. The effects produced in power systems are presented, current research activity is discussed, and magnetic storm prediction needs of the power industry are listed.

A variable capacitance based modeling and power capability predicting method for ultracapacitor

NASA Astrophysics Data System (ADS)

Liu, Chang; Wang, Yujie; Chen, Zonghai; Ling, Qiang

2018-01-01

Methods of accurate modeling and power capability predicting for ultracapacitors are of great significance in management and application of lithium-ion battery/ultracapacitor hybrid energy storage system. To overcome the simulation error coming from constant capacitance model, an improved ultracapacitor model based on variable capacitance is proposed, where the main capacitance varies with voltage according to a piecewise linear function. A novel state-of-charge calculation approach is developed accordingly. After that, a multi-constraint power capability prediction is developed for ultracapacitor, in which a Kalman-filter-based state observer is designed for tracking ultracapacitor's real-time behavior. Finally, experimental results verify the proposed methods. The accuracy of the proposed model is verified by terminal voltage simulating results under different temperatures, and the effectiveness of the designed observer is proved by various test conditions. Additionally, the power capability prediction results of different time scales and temperatures are compared, to study their effects on ultracapacitor's power capability.

The aerodynamic cost of flight in bats--comparing theory with measurement

NASA Astrophysics Data System (ADS)

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

2012-11-01

Aerodynamic theory has long been used to predict the aerodynamic power required for animal flight. However, even though the actuator disk model does not account for the flapping motion of a wing, it is used for lack of any better model. The question remains: how close are these predictions to reality? We designed a study to compare predicted aerodynamic power to measured power from the kinetic energy contained in the wake shed behind a bat flying in a wind tunnel. A high-accuracy displaced light-sheet stereo PIV system was used in the Trefftz plane to capture the wake behind four bats flown over a range of flight speeds (1-6m/s). The total power in the wake was computed from the wake vorticity and these estimates were compared with the power predicted using Pennycuick's model for bird flight as well as estimates derived from measurements of the metabolic cost of flight, previously acquired from the same individuals.

Multiple-scale prediction of forest loss risk across Borneo

Treesearch

Samuel A. Cushman; Ewan A. Macdonald; Erin L. Landguth; Yadvinder Malhi; David W. Macdonald

2017-01-01

Context: The forests of Borneo have among the highest biodiversity and also the highest forest loss rates on the planet. Objectives: Our objectives were to: (1) compare multiple modelling approaches, (2) evaluate the utility of landscape composition and configuration as predictors, (3) assess the influence of the ratio of forest loss and persistence points in the...

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.

The role of inserted polymers in polymeric insulation materials: insights from QM/MD simulations.

PubMed

Li, Chunyang; Zhao, Hong; Zhang, Hui; Wang, Ying; Wu, Zhijian; Han, Baozhong

2018-02-28

In this study, we performed a quantum chemical molecular dynamics (QM/MD) simulation to investigate the space charge accumulation process in copolymers of polyethylene (PE) with ethylene acrylic acid (EAA), ethylene vinyl acetate (EVA), styrene-ethylene-butadiene-styrene (SEBS), and black carbon (BC). We predicted that BC, especially branched BC, would possess the highest electron affinity and is identified as the most promising filler in power cable insulation. Following incorporations of 0-4 high-energy electrons into the composites, branched BC exhibited the highest stability and almost all electrons were trapped by it. Therefore, PE was protected efficiently and BC can be considered as an efficient filler for high voltage cables and an inhibitor of tree formation. On the contrary, although EAA, EVA, and SEBS can trap high-energy electrons, the latter can be supersaturated in composites of EAA, EVA, and SEBS with PE. The inserted polymers was unavoidably destroyed following C-H and C-O bond cleavage, which results from the interactions and charge transfer between PE and inserted polymers. The content effects of -COOH, benzene, and -OCOCH 3 groups on the electron trapping, mobility and stability of PE were also investigated systematically. We hope this knowledge gained from this work will be helpful in understanding the role of inserted polymers and the growth mechanisms of electrical treeing in high voltage cable insulation.

Comparative studies on the constituents, antioxidant and anticancer activities of extracts from different varieties of corn silk.

PubMed

Tian, Jingge; Chen, Haixia; Chen, Shuhan; Xing, Lisha; Wang, Yanwei; Wang, Jia

2013-10-01

The purpose of this study was to analyze the influence of varieties on the constituents, antioxidant and anticancer activities of corn silk. The contents of total phenolic and flavonoids and individual flavonoids in six corn silk varieties (Denghai6702, Delinong988, Tunyu808, Zhongdan909, Liangyu208, Jingke968) were comparatively analyzed by colourimetric methods, high performance liquid chromatography (HPLC) methods and antioxidant activities were assessed using a panel of in vitro assays, including 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical-scavenging activity assay, the inhibitory effects on lipid peroxidation (MDA) assay and ferric reducing/antioxidant power (FRAP) assay, and the cytotoxicity against human prostatic carcinoma cells PC3 and breast carcinoma cells MDA-MB-231 and MCF7 were also evaluated. Results showed that Zhongdan909 exhibited the highest total phenolic content while Tunyu808 had the highest flavonoid content among the six species. Zhongdan909 showed the highest DPPH radical scavenging activity, the highest inhibitory effect on lipid peroxidation and the strongest cytotoxicity against breast carcinoma cells MCF7, while Tunyu808 exhibited the highest reducing power. There were good relationships between the total phenolic and flavonoid contents and antioxidant activities (r > 0.78) and the cytotoxicity against breast carcinoma cells MCF7 (r > 0.79). This study suggested that corn silk could be potentially used as a readily accessible source of natural antioxidants and formononetin was one of the main antioxidant constituents in corn silk.

Antioxidant and Anti-Inflammatory Activities of Hydrolysates and Peptide Fractions Obtained by Enzymatic Hydrolysis of Selected Heat-Treated Edible Insects.

PubMed

Zielińska, Ewelina; Baraniak, Barbara; Karaś, Monika

2017-09-02

This study investigated the effect of heat treatment of edible insects on antioxidant and anti-inflammatory activities of peptides obtained by in vitro gastrointestinal digestion and absorption process thereof. The antioxidant potential of edible insect hydrolysates was determined as free radical-scavenging activity, ion chelating activity, and reducing power, whereas the anti-inflammatory activity was expressed as lipoxygenase and cyclooxygenase-2 inhibitory activity. The highest antiradical activity against DPPH • (2,2-diphenyl-1-picrylhydrazyl radical) was noted for a peptide fraction from baked cricket Gryllodes sigillatus hydrolysate (IC 50 value 10.9 µg/mL) and that against ABTS •+ (2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) radical) was the highest for raw mealworm Tenebrio molitor hydrolysate (inhibitory concentration (IC 50 value) 5.3 µg/mL). The peptides obtained from boiled locust Schistocerca gregaria hydrolysate showed the highest Fe 2+ chelation ability (IC 50 value 2.57 µg/mL); furthermore, the highest reducing power was observed for raw G. sigillatus hydrolysate (0.771). The peptide fraction from a protein preparation from the locust S. gregaria exhibited the most significant lipoxygenase and cyclooxygenase-2 inhibitory activity (IC 50 value 3.13 µg/mL and 5.05 µg/mL, respectively).

Multi-criteria decision analysis of concentrated solar power with thermal energy storage and dry cooling.

PubMed

Klein, Sharon J W

2013-12-17

Decisions about energy backup and cooling options for parabolic trough (PT) concentrated solar power have technical, economic, and environmental implications. Although PT development has increased rapidly in recent years, energy policies do not address backup or cooling option requirements, and very few studies directly compare the diverse implications of these options. This is the first study to compare the annual capacity factor, levelized cost of energy (LCOE), water consumption, land use, and life cycle greenhouse gas (GHG) emissions of PT with different backup options (minimal backup (MB), thermal energy storage (TES), and fossil fuel backup (FF)) and different cooling options (wet (WC) and dry (DC). Multicriteria decision analysis was used with five preference scenarios to identify the highest-scoring energy backup-cooling combination for each preference scenario. MB-WC had the highest score in the Economic and Climate Change-Economy scenarios, while FF-DC and FF-WC had the highest scores in the Equal and Availability scenarios, respectively. TES-DC had the highest score for the Environmental scenario. DC was ranked 1-3 in all preference scenarios. Direct comparisons between GHG emissions and LCOE and between GHG emissions and land use suggest a preference for TES if backup is require for PT plants to compete with baseload generators.

Antioxidant and Anti-Inflammatory Activities of Hydrolysates and Peptide Fractions Obtained by Enzymatic Hydrolysis of Selected Heat-Treated Edible Insects

PubMed Central

Zielińska, Ewelina; Baraniak, Barbara; Karaś, Monika

2017-01-01

This study investigated the effect of heat treatment of edible insects on antioxidant and anti-inflammatory activities of peptides obtained by in vitro gastrointestinal digestion and absorption process thereof. The antioxidant potential of edible insect hydrolysates was determined as free radical-scavenging activity, ion chelating activity, and reducing power, whereas the anti-inflammatory activity was expressed as lipoxygenase and cyclooxygenase-2 inhibitory activity. The highest antiradical activity against DPPH• (2,2-diphenyl-1-picrylhydrazyl radical) was noted for a peptide fraction from baked cricket Gryllodes sigillatus hydrolysate (IC50 value 10.9 µg/mL) and that against ABTS•+ (2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) radical) was the highest for raw mealworm Tenebrio molitor hydrolysate (inhibitory concentration (IC50 value) 5.3 µg/mL). The peptides obtained from boiled locust Schistocerca gregaria hydrolysate showed the highest Fe2+ chelation ability (IC50 value 2.57 µg/mL); furthermore, the highest reducing power was observed for raw G. sigillatus hydrolysate (0.771). The peptide fraction from a protein preparation from the locust S. gregaria exhibited the most significant lipoxygenase and cyclooxygenase-2 inhibitory activity (IC50 value 3.13 µg/mL and 5.05 µg/mL, respectively). PMID:28869499

Assessment of soil contamination by (210)Po and (210)Pb around heavy oil and natural gas fired power plants.

PubMed

Al-Masri, M S; Haddad, Kh; Doubal, A W; Awad, I; Al-Khatib, Y

2014-06-01

Soil contamination by (210)Pb and (210)Po around heavy oil and natural gas power plants has been investigated; fly and bottom ash containing enhanced levels of (210)Pb and (210)Po were found to be the main source of surface soil contamination. The results showed that (210)Pb and (210)Po in fly-ash (economizer, superheater) is highly enriched with (210)Pb and (210)Po, while bottom-ash (boiler) is depleted. The highest (210)Pb and (210)Po activity concentrations were found to be in economizer ash, whereas the lowest activity concentration was in the recirculator ash. On the other hand, (210)Pb and (210)Po activity concentrations in soil samples were found to be higher inside the plant site area than those samples collected from surrounding areas. The highest levels were found in the vicinity of Mhardeh and Tishreen power plants; both plants are operated by heavy oil and natural fuels, while the lowest values were found to be in those samples collected from Nasrieh power plant, which is only operated by one type of fuel, viz. natural gas. In addition, the levels of surface soil contamination have decreased as the distance from the power plant site center increased. Copyright © 2014 Elsevier Ltd. All rights reserved.

Two-steps microwave-assisted treatment on acid hydrolysis of sago pith for bioethanol production

NASA Astrophysics Data System (ADS)

Sunarti, T. C.; Yanti, S. D.; Ruriani, E.

2017-05-01

Sago is a genus of palm that can be utilized to produce fermentable sugars as substrate for bioethanol. Sago pith is a heterogeneous substrate consists of starch and fiber. Acid hydrolysis by microwave heating radiation can break down starch and fibers together in a very short time, so it is considered to be very efficient process. The use of microwave energy (as power level) and variation of heating time can produce fermentable sugar with certain characteristics. This study included the preparation and analysis of sago pith flour; process of acid hydrolysis (0.3 M and 0.5 M H2SO4) using two steps microwave heating, first with power level 30% (1, 2 and 3 min) and second with power level 70% (3 min); and ethanol production. The conventional treatment (autoclaving at 121°C for 15 min) was carried for the comparison. The highest fermentable sugar (105.7 g/l) was resulted from microwave heating with power level 30% for 2 min followed by the power level 70% for 3 min. This hydrolyzate then used as substrate for bioethanol fermentation and partially neutralized (pH 3, 4, 5) by using yeast Issatchenkia orientalis, and the highest ethanol (2.8 g/l) was produced in pH 5.

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.

Evaluation of four commercial quantitative real-time PCR kits with inhibited and degraded samples.

PubMed

Holmes, Amy S; Houston, Rachel; Elwick, Kyleen; Gangitano, David; Hughes-Stamm, Sheree

2018-05-01

DNA quantification is a vital step in forensic DNA analysis to determine the optimal input amount for DNA typing. A quantitative real-time polymerase chain reaction (qPCR) assay that can predict DNA degradation or inhibitors present in the sample prior to DNA amplification could aid forensic laboratories in creating a more streamlined and efficient workflow. This study compares the results from four commercial qPCR kits: (1) Investigator® Quantiplex® Pro Kit, (2) Quantifiler® Trio DNA Quantification Kit, (3) PowerQuant® System, and (4) InnoQuant® HY with high molecular weight DNA, low template samples, degraded samples, and DNA spiked with various inhibitors.The results of this study indicate that all kits were comparable in accurately predicting quantities of high quality DNA down to the sub-picogram level. However, the InnoQuant(R) HY kit showed the highest precision across the DNA concentration range tested in this study. In addition, all kits performed similarly with low concentrations of forensically relevant PCR inhibitors. However, in general, the Investigator® Quantiplex® Pro Kit was the most tolerant kit to inhibitors and provided the most accurate quantification results with higher concentrations of inhibitors (except with salt). PowerQuant® and InnoQuant® HY were the most sensitive to inhibitors, but they did indicate significant levels of PCR inhibition. When quantifying degraded samples, each kit provided different degradation indices (DI), with Investigator® Quantiplex® Pro indicating the largest DI and Quantifiler® Trio indicating the smallest DI. When the qPCR kits were paired with their respective STR kit to genotype highly degraded samples, the Investigator® 24plex QS and GlobalFiler® kits generated more complete profiles when the small target concentrations were used for calculating input amount.

Objective approach for analysis of noise source characteristics and acoustic conditions in noisy computerized embroidery workrooms.

PubMed

Aliabadi, Mohsen; Golmohammadi, Rostam; Mansoorizadeh, Muharram

2014-03-01

It is highly important to analyze the acoustic properties of workrooms in order to identify best noise control measures from the standpoint of noise exposure limits. Due to the fact that sound pressure is dependent upon environments, it cannot be a suitable parameter for determining the share of workroom acoustic characteristics in producing noise pollution. This paper aims to empirically analyze noise source characteristics and acoustic properties of noisy embroidery workrooms based on special parameters. In this regard, reverberation time as the special room acoustic parameter in 30 workrooms was measured based on ISO 3382-2. Sound power quantity of embroidery machines was also determined based on ISO 9614-3. Multiple linear regression was employed for predicting reverberation time based on acoustic features of the workrooms using MATLAB software. The results showed that the measured reverberation times in most of the workrooms were approximately within the ranges recommended by ISO 11690-1. Similarity between reverberation time values calculated by the Sabine formula and measured values was relatively poor (R (2) = 0.39). This can be due to the inaccurate estimation of the acoustic influence of furniture and formula preconditions. Therefore, this value cannot be considered representative of an actual acoustic room. However, the prediction performance of the regression method with root mean square error (RMSE) = 0.23 s and R (2) = 0.69 is relatively acceptable. Because the sound power of the embroidery machines was relatively high, these sources get the highest priority when it comes to applying noise controls. Finally, an objective approach for the determination of the share of workroom acoustic characteristics in producing noise could facilitate the identification of cost-effective noise controls.

The spatial structure of transnational human activity.

PubMed

Deutschmann, Emanuel

2016-09-01

Starting from conflictive predictions of hitherto disconnected debates in the natural and social sciences, this article examines the spatial structure of transnational human activity (THA) worldwide (a) across eight types of mobility and communication and (b) in its development over time. It is shown that the spatial structure of THA is similar to that of animal displacements and local-scale human motion in that it can be approximated by Lévy flights with heavy tails that obey power laws. Scaling exponent and power-law fit differ by type of THA, being highest in refuge-seeking and tourism and lowest in student exchange. Variance in the availability of resources and opportunities for satisfying associated needs appears to explain these differences. Over time (1960-2010), the Lévy-flight pattern remains intact and remarkably stable, contradicting the popular notion that socio-technological trends lead to a "death of distance." Humans have not become more "global" over time, they rather became more mobile in general, i.e. they move and communicate more at all distances. Hence, it would be more adequate to speak of "mobilization" than of "globalization." Longitudinal change occurs only in some types of THA and predominantly at short distances, indicating regional rather than global shifts. Copyright © 2016 Elsevier Inc. All rights reserved.

Compatibility approach for the improvement of oxide thermoelectric converters for industrial heat recovery applications

NASA Astrophysics Data System (ADS)

Saucke, Gesine; Populoh, Sascha; Thiel, Philipp; Xie, Wenjie; Funahashi, Ryoji; Weidenkaff, Anke

2015-07-01

New ceramic Ca3Co3.9O9+δ /CaMn0.97W0.03O3-δ thermoelectric generators with different cross section areas A p and A n of the p- and the n-type leg are fabricated, characterized, and tested at high temperatures in long-term tests. The variation of the measured power output and the efficiency with changing A p / A n ratio is discussed and compared with calculations based on the measured material properties. The highest conversion efficiencies are reached for ratios close to the one predicted by the compatibility approach, whereas an improper choice of A p / A n leads to a strong reduction of the efficiency. A volume power density of 1.4 W/cm3 and an efficiency of 1.08% are found for the most promising generator (temperature difference Δ T = 734 K and A p / A n = 1.12). The results reveal the major importance of the A p / A n ratio for the conversion efficiency and subsequently cost and weight reduction issues, both crucial for a large scale application of thermoelectric converters. Additionally, the oxide generators proved to be very reliable, as after more than 110 h of high temperature energy conversion, no degradation is observable.

Optimisation of Microwave-Assisted Extraction of Pomegranate (Punica granatum L.) Seed Oil and Evaluation 
of Its Physicochemical and Bioactive Properties

PubMed Central

Çavdar, Hasene Keskin; Gök, Uğur; Göğüş, Fahrettin

2017-01-01

Summary Pomegranate seed oil was extracted in a closed-vessel high-pressure microwave system. The characteristics of the obtained oil, such as fatty acid composition, free fatty acidity, total phenolic content, antioxidant activity and colour, were compared to those of the oil obtained by cold solvent extraction. Response surface methodology was applied to optimise extraction conditions: power (176–300 W), time (5–20 min), particle size (d=0.125–0.800 mm) and solvent to sample ratio (2:1, 6:1 and 10:1, by mass). The predicted highest extraction yield (35.19%) was obtained using microwave power of 220 W, particle size in the range of d=0.125–0.450 mm and solvent-to-sample ratio of 10:1 (by mass) in 5 min extraction time. Microwave-assisted solvent extraction (MASE) resulted in higher extraction yield than that of Soxhlet (34.70% in 8 h) or cold (17.50% in 8 h) extraction. The dominant fatty acid of pomegranate seed oil was punicic acid (86%) irrespective of the extraction method. Oil obtained by MASE had better physicochemical properties, total phenolic content and antioxidant activity than the oil obtained by cold solvent extraction. PMID:28559737

Central composite rotatable design for investigation of microwave-assisted extraction of okra pod hydrocolloid.

PubMed

Samavati, Vahid

2013-10-01

Microwave-assisted extraction (MAE) technique was employed to extract the hydrocolloid from okra pods (OPH). The optimal conditions for microwave-assisted extraction of OPH were determined by response surface methodology. A central composite rotatable design (CCRD) was applied to evaluate the effects of three independent variables (microwave power (X1: 100-500 W), extraction time (X2: 30-90 min), and extraction temperature (X3: 40-90 °C)) on the extraction yield of OPH. The correlation analysis of the mathematical-regression model indicated that quadratic polynomial model could be employed to optimize the microwave extraction of OPH. The optimal conditions to obtain the highest recovery of OPH (14.911±0.27%) were as follows: microwave power, 395.56 W; extraction time, 67.11 min and extraction temperature, 73.33 °C. Under these optimal conditions, the experimental values agreed with the predicted ones by analysis of variance. It indicated high fitness of the model used and the success of response surface methodology for optimizing OPH extraction. After method development, the DPPH radical scavenging activity of the OPH was evaluated. MAE showed obvious advantages in terms of high extraction efficiency and radical scavenging activity of extract within the shorter extraction time. Copyright © 2013 Elsevier B.V. All rights reserved.

A novel multi-model neuro-fuzzy-based MPPT for three-phase grid-connected photovoltaic system

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

Chaouachi, Aymen; Kamel, Rashad M.; Nagasaka, Ken

This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three multi-layered feed forwarded Artificial Neural Networks (ANN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated ANN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology,more » comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and nonlinear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network and the Perturb and Observe (P and O) algorithm dispositive. (author)« less

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

NASA Technical Reports Server (NTRS)

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

1979-01-01

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

Robust logistic regression to narrow down the winner's curse for rare and recessive susceptibility variants.

PubMed

Kesselmeier, Miriam; Lorenzo Bermejo, Justo

2017-11-01

Logistic regression is the most common technique used for genetic case-control association studies. A disadvantage of standard maximum likelihood estimators of the genotype relative risk (GRR) is their strong dependence on outlier subjects, for example, patients diagnosed at unusually young age. Robust methods are available to constrain outlier influence, but they are scarcely used in genetic studies. This article provides a non-intimidating introduction to robust logistic regression, and investigates its benefits and limitations in genetic association studies. We applied the bounded Huber and extended the R package 'robustbase' with the re-descending Hampel functions to down-weight outlier influence. Computer simulations were carried out to assess the type I error rate, mean squared error (MSE) and statistical power according to major characteristics of the genetic study and investigated markers. Simulations were complemented with the analysis of real data. Both standard and robust estimation controlled type I error rates. Standard logistic regression showed the highest power but standard GRR estimates also showed the largest bias and MSE, in particular for associated rare and recessive variants. For illustration, a recessive variant with a true GRR=6.32 and a minor allele frequency=0.05 investigated in a 1000 case/1000 control study by standard logistic regression resulted in power=0.60 and MSE=16.5. The corresponding figures for Huber-based estimation were power=0.51 and MSE=0.53. Overall, Hampel- and Huber-based GRR estimates did not differ much. Robust logistic regression may represent a valuable alternative to standard maximum likelihood estimation when the focus lies on risk prediction rather than identification of susceptibility variants. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Generation of 180 W average green power from a frequency-doubled picosecond rod fiber amplifier

DOE PAGES

Zhao, Zhi; Sheehy, Brian; Minty, Michiko

2017-03-29

Here, we report on the generation of 180 W average green power from a frequency-doubled picosecond rod fiber amplifier. In an Yb-doped fiber master-oscillator-power-amplifier system, 2.3-ps 704 MHz pulses are first amplified in small-core fibers and then in large-mode-area rod fibers to produce 270 W average infrared power with a high polarization extinction ratio and diffraction-limited beam quality. By carrying out frequency doubling in a lithium triborate (LBO) crystal, 180 W average green power is generated. To the best of our knowledge, this is the highest average green power achieved in fiber-based laser systems.

Adolescent physical activity predicts high education and socio-economic position in adulthood.

PubMed

Koivusilta, Leena K; Nupponen, Heimo; Rimpelä, Arja H

2012-04-01

Based on the knowledge on beneficial effects of physical activity (PA) on health and fitness, we hypothesized that PA in adolescence is related to high education and socio-economic position (SEP) in adulthood. Improved school performance may mediate the hypothesized relationship. The Adolescent Health and Lifestyle Surveys (AHLS), collected biennially in 1981-89 (baseline) and representing 14- and 16-year-old Finns were individually linked with national registries of the highest educational level and SEP. Of the sample, 10 498 (78%) responded the surveys and were followed till the end of 2001 (age group of 28-38 years). Multinomial logistic regression analysis was used to study the associations between the outcomes (highest attained educational level, SEP) and PA (sports clubs, spontaneous, intensity). Participating in sports club or spontaneous PA and practicing with high intensity in adolescence were associated with higher educational levels and SEP in adulthood. Childhood socio-economic background only slightly influenced the associations and largely, PA predicted the outcomes independently of background. Particularly among girls, school performance partly accounted for the associations between PA and the highest educational level and the highest SEP. Participation in PA in adolescence and particularly its high intensity, predicts higher educational levels and SEP in early middle age. School performance to some degree mediates the impact of PA. PA behaviours in adolescence-or possibilities to participate in PA-are a potential mechanism in generating better health of higher socio-economic and educational groups in adult age.

Comparison of four kinds of extraction techniques and kinetics of microwave-assisted extraction of vanillin from Vanilla planifolia Andrews.

PubMed

Dong, Zhizhe; Gu, Fenglin; Xu, Fei; Wang, Qinghuang

2014-04-15

Vanillin yield, microscopic structure, antioxidant activity and overall odour of vanilla extracts obtained by different treatments were investigated. MAE showed the strongest extraction power, shortest time and highest antioxidant activity. Maceration gave higher vanillin yields than UAE and PAE, similar antioxidant activity with UAE, but longer times than UAE and PAE. Overall odour intensity of different vanilla extracts obtained by UAE, PAE and MAE were similar, while higher than maceration extracts. Then, powered vanilla bean with a sample/solvent ratio of 4 g/100 mL was selected as the optimum condition for MAE. Next, compared with other three equations, two-site kinetic equation with lowest RMSD and highest R²(adj) was shown to be more suitable in describing the kinetics of vanillin extraction. By fitting the parameters C(eq), k₁, k₂, and f, a kinetics model was constructed to describe vanillin extraction in terms of irradiation power, ethanol concentration, and extraction time. Copyright © 2013 Elsevier Ltd. All rights reserved.

Metalorganic vapor phase epitaxial growth of red and infrared vertical-cavity surface-emitting laser diodes

NASA Astrophysics Data System (ADS)

Schneider, R. P.; Lott, J. A.; Lear, K. L.; Choquette, K. D.; Crawford, M. H.; Kilcoyne, S. P.; Figiel, J. J.

1994-12-01

Metalorganic vapor phase epitaxy (MOVPE) is used for the growth of vertical-cavity surface-emitting laser (VCSEL) diodes. MOVPE exhibits a number of important advantages over the more commonly-used molecular-beam epitaxial (MBE) techniques, including ease of continuous compositional grading and carbon doping for low-resistance p-type distributed Bragg reflectors (DBRs), higher growth rates for rapid throughput and greater versatility in choice of materials and dopants. Planar gain-guided red VCSELs based on AlGaInP/AlGaAs heterostructures lase continuous-wave at room temperature, with voltage thresholds between 2.5 and 3 V and maximum power outputs of over 0.3 mW. Top-emitting infra-red (IR) VCSELs exhibit the highest power-conversion (wall-plug) efficiencies (21%), lowest threshold voltage (1.47 V), and highest single mode power (4.4 mW from an 8 μm device) yet reported. These results establish MOVPE as a preferred growth technique for this important new family of photonic devices.

Exploring the motivational brain: effects of implicit power motivation on brain activation in response to facial expressions of emotion.

PubMed

Schultheiss, Oliver C; Wirth, Michelle M; Waugh, Christian E; Stanton, Steven J; Meier, Elizabeth A; Reuter-Lorenz, Patricia

2008-12-01

This study tested the hypothesis that implicit power motivation (nPower), in interaction with power incentives, influences activation of brain systems mediating motivation. Twelve individuals low (lowest quartile) and 12 individuals high (highest quartile) in nPower, as assessed per content coding of picture stories, were selected from a larger initial participant pool and participated in a functional magnetic resonance imaging study during which they viewed high-dominance (angry faces), low-dominance (surprised faces) and control stimuli (neutral faces, gray squares) under oddball-task conditions. Consistent with hypotheses, high-power participants showed stronger activation in response to emotional faces in brain structures involved in emotion and motivation (insula, dorsal striatum, orbitofrontal cortex) than low-power participants.

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.

High power far-infrared optical parametric oscillator with high beam quality

NASA Astrophysics Data System (ADS)

Qian, Chuan-Peng; Shen, Ying-Jie; Dai, Tong-Yu; Duan, Xiao-Ming; Yao, Bao-Quan

2016-11-01

A high power ZnGeP2 (ZGP) optical parametric oscillator (OPO) with good beam quality pumped by a Q-switched Ho:YAG laser was demonstrated. The maximum output power of the ZGP OPO with a four-mirror ring cavity was about 5.04 W around 8.1 μm with 83.9 W Ho incident pump power, corresponding to a slope efficiency of 9.2 %. The ZGP OPO produced 36.0 ns far-IR pulse laser in the 8.0-8.3 μm spectral regions. The beam quality was measured to be M2 1.6 at the highest output power.

High-power laser with Nd:YAG single-crystal fiber grown by the micro-pulling-down technique

NASA Astrophysics Data System (ADS)

Didierjean, Julien; Castaing, Marc; Balembois, François; Georges, Patrick; Perrodin, Didier; Fourmigué, Jean Marie; Lebbou, Kherreddine; Brenier, Alain; Tillement, Olivier

2006-12-01

We present optical characterization and laser results achieved with single-crystal fibers directly grown by the micro-pulling-down technique. We investigate the spectroscopic and optical quality of the fiber, and we present the first laser results. We achieved a cw laser power of 10 W at 1064 nm for an incident pump power of 60 W at 808 nm and 360 kW peak power for 12 ns pulses at 1 kHz in the Q-switched regime. It is, to the best of our knowledge, the highest laser power ever achieved with directly grown single-crystal fibers.

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.

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

Jin, Ke; Zhang, Yanwen; Zhu, Zihua

Accurate information of electronic stopping power is fundamental for broad advances in electronic industry, space exploration, national security, and sustainable energy technologies. The Stopping and Range of Ions in Matter (SRIM) code has been widely applied to predict stopping powers and ion distributions for decades. Recent experimental results have, however, shown considerable errors in the SRIM predictions for stopping of heavy ions in compounds containing light elements, indicating an urgent need to improve current stopping power models. The electronic stopping powers of 35Cl, 80Br, 127I, and 197Au ions are experimentally determined in two important functional materials, SiC and SiO2, frommore » tens to hundreds keV/u based on a single ion technique. By combining with the reciprocity theory, new electronic stopping powers are suggested in a region from 0 to 15 MeV, where large deviations from SRIM predictions are observed. For independent experimental validation of the electronic stopping powers we determined, Rutherford backscattering spectrometry (RBS) and secondary ion mass spectrometry (SIMS) are utilized to measure the depth profiles of implanted Au ions in SiC with energies from 700 keV to 15 MeV. The measured ion distributions from both RBS and SIMS are considerably deeper (up to ~30%) than the predictions from the commercial SRIM code. In comparison, the new electronic stopping power values are utilized in a modified TRIM-85 (the original version of the SRIM) code, M-TRIM, to predict ion distributions, and the results are in good agreement with the experimentally measured ion distributions.« less

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

Atmospheric Science Data Center

2018-03-01

The Prediction Of Worldwide Energy Resource (POWER) Project facilitates access to NASA's satellite and modeling analysis for Renewable Energy, Sustainable Buildings and Agroclimatology applications.  A   new ...

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

PubMed Central

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

2016-01-01

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

All-solid state symmetric supercapacitors based on compressible and flexible free-standing 3D carbon nanotubes (CNTs)/poly(3,4-ethylenedioxythiophene) (PEDOT) sponge electrodes

NASA Astrophysics Data System (ADS)

He, Xin; Yang, Wenyao; Mao, Xiling; Xu, Lu; Zhou, Yujiu; Chen, Yan; Zhao, Yuetao; Yang, Yajie; Xu, Jianhua

2018-02-01

Flexible supercapacitors that maintain electrochemical performance under deformation have attracted much attention for the potential application in the flexible electronics market. A compressible and flexible free-standing electrodes sponge and all-solid-state symmetric supercapacitors based on as-prepared electrodes are presented. The carbon nanotubes (CNTs) framework is synthesized by chemical vapor deposition (CVD) method, and then composited with poly (3,4-ethylenedioxythiophene) PEDOT by the electrodeposition. This CNTs/PEDOT sponge electrode shows highest mass-specific capacitance of 147 Fg-1 at 0.5 A g-1, tuned by the PEDOT mass loading, and exhibits good cyclic stability with the evidence that more than 95% of capacitance is remained after 3000 cycles. Furthermore, the symmetric supercapacitor shows the highest energy density of 12.6 Wh kg-1 under the power density of 1 kW kg-1 and highest power density of 10.2 kW kg-1 with energy density of 8 Wh kg-1, which exhibits both high energy density and power density. The electrochemical performance of composite electrode also indicates that the operate voltage of device could be extend to 1.4 V by the n-doping and p-doping process in different potential of PEDOT component. This flexible supercapacitor maintains stable electrochemical performance working on different bending condition, which shows promising prospect for wearable energy storage applications.

Theoretical and perceived balance of power inside Spanish public hospitals

PubMed Central

2001-01-01

Background The hierarchical pyramid inside Spanish public hospitals was radically changed by the Health Reform Law promulgated in 1986. According to it, the manpower of the hospitals was divided into three divisions (Medical, Nursing, General Services/Administration), which from then on occupied the same level, only subject to the general manager. Ten years after the implementation of the law, the present study was designed in order to investigate if the legal changes had indeed produced a real change in the balance of power inside the hospitals, as perceived by the different workers within them. Materials and Methods A questionnaire was administered to 1,027 workers from four different public hospitals (two university-based and two district hospitals). The participants belonged to all divisions, and to all three operative levels (staff, supervisory and managerial) within them. The questionnaire inquired about the perceived power inside each division and hierarchical level, as well as about that of the other divisions and hierarchical levels. Results Every division attributed the least power to itself. The Nursing and the Administrative division attributed the highest power to the physicians, and these attributed the highest power to the General Services/Administrative division. All hierarchical levels (including the formal top of the pyramid) attributed significantly more power to the other than to them. Conclusions More than ten years after the implementation of the new law, the majority of workers still perceive that the real power within the hospitals is held by the physicians (whereas these feel that it has shifted to the administrators). No division or hierarchical level believes it holds any significant degree of power, and this carries with it the danger of also not accepting any responsibility. PMID:11574049

Theoretical and perceived balance of power inside Spanish public hospitals.

PubMed

Salvadores, P; Schneider, J; Zubero, I

2001-01-01

The hierarchical pyramid inside Spanish public hospitals was radically changed by the Health Reform Law promulgated in 1986. According to it, the manpower of the hospitals was divided into three divisions (Medical, Nursing, General Services/Administration), which from then on occupied the same level, only subject to the general manager. Ten years after the implementation of the law, the present study was designed in order to investigate if the legal changes had indeed produced a real change in the balance of power inside the hospitals, as perceived by the different workers within them. A questionnaire was administered to 1,027 workers from four different public hospitals (two university-based and two district hospitals). The participants belonged to all divisions, and to all three operative levels (staff, supervisory and managerial) within them. The questionnaire inquired about the perceived power inside each division and hierarchical level, as well as about that of the other divisions and hierarchical levels. Every division attributed the least power to itself. The Nursing and the Administrative division attributed the highest power to the physicians, and these attributed the highest power to the General Services/Administrative division. All hierarchical levels (including the formal top of the pyramid) attributed significantly more power to the other than to them. More than ten years after the implementation of the new law, the majority of workers still perceive that the real power within the hospitals is held by the physicians (whereas these feel that it has shifted to the administrators). No division or hierarchical level believes it holds any significant degree of power, and this carries with it the danger of also not accepting any responsibility.

Fatigue in repeated-sprint exercise is related to muscle power factors and reduced neuromuscular activity.

PubMed

Mendez-Villanueva, Alberto; Hamer, Peter; Bishop, David

2008-07-01

The purpose of this study was (1) to determine the relationship between each individual's anaerobic power reserve (APR) [i.e., the difference between the maximum anaerobic (Pana) and aerobic power (Paer)] and fatigability during repeated-sprint exercise and (2) to examine the acute effects of repeated sprints on neuromuscular activity, as evidenced by changes in the surface electromyogram (EMG) signals. Eight healthy males carried out tests to determine Pana (defined as the highest power output attained during a 6-s cycling sprint), Paer (defined as the highest power output achieved during a progressive, discontinuous cycling test to failure) and a repeated cycling sprint test (10 x 6-s max sprints with 30 s rest). Peak power output (PPO) and mean power output (MPO) were calculated for each maximal 6-s cycling bout. Root mean square (RMS) was utilized to quantify EMG activity from the vastus lateralis (VL) muscle of the right leg. Over the ten sprints, PPO and MPO decreased by 24.6 and 28.3% from the maximal value (i.e., sprint 1), respectively. Fatigue index during repeated sprints was significantly correlated with APR (R = 0.87; P < 0.05). RMS values decreased over the ten sprints by 14.6% (+/-6.3%). There was a strong linear relationship (R2 = 0.97; P < 0.05) between the changes in MPO and EMG RMS from the vastus lateralis muscle during the ten sprints. The individual advantage in fatigue-resistance when performing a repeated sprint task was related with a lower anaerobic power reserve. Additionally, a suboptimal net motor unit activity might also impair the ability to repeatedly generate maximum power outputs.

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.

A Habitat-based Wind-Wildlife Collision Model with Application to the Upper Great Plains Region

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

Forcey, Greg, M.

Most previous studies on collision impacts at wind facilities have taken place at the site-specific level and have only examined small-scale influences on mortality. In this study, we examine landscape-level influences using a hierarchical spatial model combined with existing datasets and life history knowledge for: Horned Lark, Red-eyed Vireo, Mallard, American Avocet, Golden Eagle, Whooping Crane, red bat, silver-haired bat, and hoary bat. These species were modeled in the central United States within Bird Conservation Regions 11, 17, 18, and 19. For the bird species, we modeled bird abundance from existing datasets as a function of habitat variables known tomore » be preferred by each species to develop a relative abundance prediction for each species. For bats, there are no existing abundance datasets so we identified preferred habitat in the landscape for each species and assumed that greater amounts of preferred habitat would equate to greater abundance of bats. The abundance predictions for bird and bats were modeled with additional exposure factors known to influence collisions such as visibility, wind, temperature, precipitation, topography, and behavior to form a final mapped output of predicted collision risk within the study region. We reviewed published mortality studies from wind farms in our study region and collected data on reported mortality of our focal species to compare to our modeled predictions. We performed a sensitivity analysis evaluating model performance of 6 different scenarios where habitat and exposure factors were weighted differently. We compared the model performance in each scenario by evaluating observed data vs. our model predictions using spearmans rank correlations. Horned Lark collision risk was predicted to be highest in the northwestern and west-central portions of the study region with lower risk predicted elsewhere. Red-eyed Vireo collision risk was predicted to be the highest in the eastern portions of the study region and in the forested areas of the western portion; the lowest risk was predicted in the treeless portions of the northwest portion of the study area. Mallard collision risk was predicted to be highest in the eastern central portion of the prairie potholes and in Iowa which has a high density of pothole wetlands; lower risk was predicted in the more arid portions of the study area. Predicted collision risk for American Avocet was similar to Mallard and was highest in the prairie pothole region and lower elsewhere. Golden Eagle collision risk was predicted to be highest in the mountainous areas of the western portion of the study area and lowest in the eastern portion of the prairie potholes. Whooping Crane predicted collision risk was highest within the migration corridor that the birds follow through in the central portion of the study region; predicted collision risk was much lower elsewhere. Red bat collision risk was highly driven by large tracts of forest and river corridors which made up most of the areas of higher collision risk. Silver-haired bat and hoary bat predicted collision risk were nearly identical and driven largely by forest and river corridors as well as locations with warmer temperatures, and lower average wind speeds. Horned Lark collisions were mostly influenced by abundance and predictions showed a moderate correlation between observed and predicted mortality (r = 0.55). Red bat, silver-haired bat, and hoary bat predictions were much higher and shown a strong correlations with observed mortality with correlations of 0.85, 0.90, and 0.91 respectively. Red bat collisions were influenced primarily by habitat, while hoary bat and silver-haired bat collisions were influenced mainly by exposure variables. Stronger correlations between observed and predicted collision for bats than for Horned Larks can likely be attributed to stronger habitat associations and greater influences of weather on behavior for bats. Although the collision predictions cannot be compared among species, our model outputs provide a convenient and easy landscape-level tool to quickly screen for siting issues at a high level. The model resolution is suitable for state or multi-county siting but users are cautioned against using these models for micrositing. The U.S. Fish and Wildlife Service recently released voluntary land-based wind energy guidelines for assessing impacts of a wind facility to wildlife using a tiered approach. The tiered approach uses an iterative approach for assessing impacts to wildlife in levels of increasing detail from landscape-level screening to site-specific field studies. Our models presented in this paper would be applicable to be used as tools to conduct screening at the tier 1 level and would not be appropriate to complete smaller scale tier 2 and tier 3 level studies. For smaller scale screening ancillary field studies should be conducted at the site-specific level to validate collision predictions.« less

Microvascular stress analysis. Part I: simulation of microvascular anastomoses using finite element analysis.

PubMed

Al-Sukhun, Jehad; Lindqvist, Christian; Ashammakhi, Nureddin; Penttilä, Heikki

2007-03-01

To develop a finite element model (FEM) to study the effect of the stress and strain, in microvascular anastomoses that result from the geometrical mismatch of anastomosed vessels. FEMs of end-to-end and end-to-side anastomoses were constructed. Simulations were made using finite element software (NISA). We investigated the angle of inset in the end-to-side anastomosis and the discrepancy in the size of the opening in the vessel between the host and recipient vessels. The FEMs were used to predict principal and shear stress and strain at the position of each node. Two types of vascular deformation were predicted during different simulations: longitudinal distortion, and rotational distortion. Stress values ranged from 151.1 to 282.4MPa for the maximum principal stress, from -122.9 to -432.2MPa for the minimum principal stress, and from 122.1 to 333.1MPa for the maximum shear stress. The highest values were recorded when there was a 50% mismatch in the diameter of the vessels at the site of the end-to-end anastomosis. The effect of the vessel's size discrepancy on the blood flow and deformation was remarkable in the end-to-end anastomosis. End-to-side anastomosis was superior to end-to-end anastomosis. FEM is a powerful tool to study vascular deformation, as it predicts deformation and biomechanical processes at sites where physical measurements are likely to remain impossible in living humans.

Combined use of serum MCP-1/IL-10 ratio and uterine artery Doppler index significantly improves the prediction of preeclampsia.

PubMed

Cui, Shihong; Gao, Yanan; Zhang, Linlin; Wang, Yuan; Zhang, Lindong; Liu, Pingping; Liu, Ling; Chen, Juan

2017-10-01

Monocyte chemotactic protein-1 (MCP-1, or CCL2) is a member of the chemokine subfamily involved in recruitment of monocytes in inflammatory tissues. IL-10 is a key regulator for maintaining the balance of anti-inflammatory and pro-inflammatory milieu at the feto-maternal interface. Doppler examination has been routinely performed for the monitoring and management of preeclampsia patients. This study evaluates the efficiency of these factors alone, or in combination, for the predication of preeclampsia. The serum levels of MCP-1 and IL-10 in 78 preeclampsia patients and 143 age-matched normal controls were measured. The Doppler ultrasonography was performed and Artery Pulsatility Index (PI) and Resistance Index (RI) were calculated for the same subjects. It was found that while the second-trimester serum MCP-1, IL-10, MCP-1/IL-10 ratio, PI, and RI showed some power in predicting preeclampsia, the combination of MCP-1/IL-10 and PI and RI accomplishes the highest efficiency, achieving an AUC of 0.973 (95% CI, 0.000-1.000, P<0.001), a sensitivity of 94%, and a specificity of 80%. The use of MCP-1/IL-10 ratio in combination with ultrasound findings appears to provide a promising modality for predicting preeclampsia. Future studies using a larger sample can be conducted to construct an algorithm capable of quantitative assessment on the risk of preeclampsia. Copyright © 2016 Elsevier B.V. All rights reserved.

Dysphagia risk assessment in acute left-hemispheric middle cerebral artery stroke.

PubMed

Somasundaram, Sriramya; Henke, Christian; Neumann-Haefelin, Tobias; Isenmann, Stefan; Hattingen, Elke; Lorenz, Matthias W; Singer, Oliver C

2014-01-01

Bedside evaluation of dysphagia may be challenging in left middle cerebral artery (MCA) stroke due to frequently existing aphasia. Here we analyse the predictive value of common bedside screening tests and of two items of cortical dysfunction, aphasia and buccofacial apraxia (BFA), for the detection of dysphagia. We prospectively examined 67 consecutive patients with clinical and imaging evidence of acute (<72 h) left MCA stroke. Dysphonia, dysarthria, abnormal volitional cough and abnormal gag reflex were assessed followed by a standardized 50-ml water-swallowing test determining the symptoms cough and voice change after swallow. Aphasia and BFA were assessed according to defined criteria. Fibre-optic endoscopic evaluation of swallowing (FEES) was performed for validation of dysphagia. 41 (61%) patients had FEES-proven dysphagia. Abnormal gag reflex, abnormal volitional cough, cough after swallow, aphasia and BFA were significantly more frequent in dysphagic as compared to non-dysphagic patients, while dysphonia, dysarthria and voice change after swallow were not. Aphasia and BFA had the highest sensitivity (97 and 78%, respectively) and high negative predictive values (89 and 68%, respectively) for dysphagia. Multivariate regression analysis did not identify an independent predictor of dysphagia. In left MCA stroke, the sensitivity and specificity of common bedside dysphagia screening methods are low. In contrast, aphasia and BFA have a high sensitivity and high negative predictive power, presumably due to the neuro-anatomical overlap between cortical regions involved in swallowing, speech production, imitation and voluntary movement control. © 2014 S. Karger AG, Basel.

High-power diode laser bars as pump sources for fiber lasers and amplifiers (Invited Paper)

NASA Astrophysics Data System (ADS)

Bonati, G.; Hennig, P.; Wolff, D.; Voelckel, H.; Gabler, T.; Krause, U.; T'nnermann, A.; Reich, M.; Limpert, J.; Werner, E.; Liem, A.

2005-04-01

Fiber lasers are pumped by fibercoupled, multimode single chip devices at 915nm. That"s what everybody assumes when asked for the type of fiber laser pumps and it was like this for many years. Coming up as an amplifier for telecom applications, the amount of pump power needed was in the range of several watts. Highest pump powers for a limited market entered the ten watts range. This is a range of power that can be covered by highly reliable multimode chips, that have to survive up to 25 years, e.g. in submarine applications. With fiber lasers entering the power range and the application fields of rod and thin disc lasers, the amount of pump power needed raised into the area of several hundred watts. In this area of pump power, usually bar based pumps are used. This is due to the much higher cost pressure of the industrial customers compared to telecom customers. We expect more then 70% of all industrial systems to be pumped by diode laser bars. Predictions that bar based pumps survive for just a thousand hours in cw-operation and fractions of this if pulsed are wrong. Bar based pumps have to perform on full power for 10.000h on Micro channel heat sinks and 20.000h on passive heatsinks in industrial applications, and they do. We will show a variety of data, "real" long time tests and statistics from the JENOPTIK Laserdiode as well as data of thousands of bars in the field, showing that bar based pumps are not just well suitable for industrial applications on high power levels, but even showing benefits compared to chip based pumps. And it"s reasonable, that the same objectives of cost effectiveness, power and lifetime apply as well to thin disc, rod and slab lasers as to fiber lasers. Due to the pumping of fiber lasers, examples will be shown, how to utilize bars for high brightness fiber coupling. In this area, the automation is on its way to reduce the costs on the fibercoupling, similar to what had been done in the single chip business. All these efforts are part of the JENOPTIK Laserdiode"s LongLifeTechnologie.

Numerical Predictions of Wind Turbine Power and Aerodynamic Loads for the NREL Phase II and IV Combined Experiment Rotor

NASA Technical Reports Server (NTRS)

Duque, Earl P. N.; Johnson, Wayne; vanDam, C. P.; Chao, David D.; Cortes, Regina; Yee, Karen

1999-01-01

Accurate, reliable and robust numerical predictions of wind turbine rotor power remain a challenge to the wind energy industry. The literature reports various methods that compare predictions to experiments. The methods vary from Blade Element Momentum Theory (BEM), Vortex Lattice (VL), to variants of Reynolds-averaged Navier-Stokes (RaNS). The BEM and VL methods consistently show discrepancies in predicting rotor power at higher wind speeds mainly due to inadequacies with inboard stall and stall delay models. The RaNS methodologies show promise in predicting blade stall. However, inaccurate rotor vortex wake convection, boundary layer turbulence modeling and grid resolution has limited their accuracy. In addition, the inherently unsteady stalled flow conditions become computationally expensive for even the best endowed research labs. Although numerical power predictions have been compared to experiment. The availability of good wind turbine data sufficient for code validation experimental data that has been extracted from the IEA Annex XIV download site for the NREL Combined Experiment phase II and phase IV rotor. In addition, the comparisons will show data that has been further reduced into steady wind and zero yaw conditions suitable for comparisons to "steady wind" rotor power predictions. In summary, the paper will present and discuss the capabilities and limitations of the three numerical methods and make available a database of experimental data suitable to help other numerical methods practitioners validate their own work.

Projected electric power demands for the Potomac Electric Power Company

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

Wilson, J.W.

1975-07-01

Included are chapters on the background of the Potomac Electric Power Company, forecasting future power demand, demand modeling, accuracy of market predictions, and total power system requirements. (DG)

Power law behavior of RR-interval variability in healthy middle-aged persons, patients with recent acute myocardial infarction, and patients with heart transplants

NASA Technical Reports Server (NTRS)

Bigger, J. T. Jr; Steinman, R. C.; Rolnitzky, L. M.; Fleiss, J. L.; Albrecht, P.; Cohen, R. J.

1996-01-01

BACKGROUND. The purposes of the present study were (1) to establish normal values for the regression of log(power) on log(frequency) for, RR-interval fluctuations in healthy middle-aged persons, (2) to determine the effects of myocardial infarction on the regression of log(power) on log(frequency), (3) to determine the effect of cardiac denervation on the regression of log(power) on log(frequency), and (4) to assess the ability of power law regression parameters to predict death after myocardial infarction. METHODS AND RESULTS. We studied three groups: (1) 715 patients with recent myocardial infarction; (2) 274 healthy persons age and sex matched to the infarct sample; and (3) 19 patients with heart transplants. Twenty-four-hour RR-interval power spectra were computed using fast Fourier transforms and log(power) was regressed on log(frequency) between 10(-4) and 10(-2) Hz. There was a power law relation between log(power) and log(frequency). That is, the function described a descending straight line that had a slope of approximately -1 in healthy subjects. For the myocardial infarction group, the regression line for log(power) on log(frequency) was shifted downward and had a steeper negative slope (-1.15). The transplant (denervated) group showed a larger downward shift in the regression line and a much steeper negative slope (-2.08). The correlation between traditional power spectral bands and slope was weak, and that with log(power) at 10(-4) Hz was only moderate. Slope and log(power) at 10(-4) Hz were used to predict mortality and were compared with the predictive value of traditional power spectral bands. Slope and log(power) at 10(-4) Hz were excellent predictors of all-cause mortality or arrhythmic death. To optimize the prediction of death, we calculated a log(power) intercept that was uncorrelated with the slope of the power law regression line. We found that the combination of slope and zero-correlation log(power) was an outstanding predictor, with a relative risk of > 10, and was better than any combination of the traditional power spectral bands. The combination of slope and log(power) at 10(-4) Hz also was an excellent predictor of death after myocardial infarction. CONCLUSIONS. Myocardial infarction or denervation of the heart causes a steeper slope and decreased height of the power law regression relation between log(power) and log(frequency) of RR-interval fluctuations. Individually and, especially, combined, the power law regression parameters are excellent predictors of death of any cause or arrhythmic death and predict these outcomes better than the traditional power spectral bands.

Biofuel cell operating on activated THP-1 cells: A fuel and substrate study.

PubMed

Javor, Kristina; Tisserant, Jean-Nicolas; Stemmer, Andreas

2017-01-15

It is known that electrochemical energy can be harvested from mammalian cells, more specifically from white blood cells (WBC). This study focuses on an improved biofuel cell operating on phorbol myristate acetate (PMA) activated THP-1 human monocytic cells. Electrochemical investigation showed strong evidence pointing towards hydrogen peroxide being the primary current source, confirming that the current originates from NADPH oxidase activity. Moreover, an adequate substrate for differentiation and activation of THP-1 cells was examined. ITO, gold, platinum and glass were tested and the amount of superoxide anion produced by NADPH oxidase was measured by spectrophotometry through WST-1 reduction at 450nm and used as an indicator of cellular activity and viability. These substrates were subsequently used in a conventional two-compartment biofuel cell where the power density output was recorded. The material showing the highest cell activity compared to the reference cell culture plate and the highest power output was ITO. Under our experimental conditions, a power density of 4.5μW/cm 2 was reached. To the best of our knowledge, this is a threefold higher power output than other leukocyte biofuel cells. Copyright © 2016 Elsevier B.V. All rights reserved.

An inter-lighting interference cancellation scheme for MISO-VLC systems

NASA Astrophysics Data System (ADS)

Kim, Kyuntak; Lee, Kyujin; Lee, Kyesan

2017-08-01

In this paper, we propose an inter-lighting interference cancellation (ILIC) scheme to reduce the interference between adjacent light-emitting diodes (LEDs) and enhance the transmission capacity of multiple-input-single-output (MISO)-visible light communication (VLC) systems. In indoor environments, multiple LEDs have normally been used as lighting sources, allowing the design of MISO-VLC systems. To enhance the transmission capacity, different data should be simultaneously transmitted from each LED; however, that can lead to interference between adjacent LEDs. In that case, relatively low-received power signals are subjected to large interference because wireless optical systems generally use intensity modulation and direct detection. Thus, only the signal with the highest received power can be detected, while the other received signals cannot be detected. To solve this problem, we propose the ILIC scheme for MISO-VLC systems. The proposed scheme preferentially detects the highest received power signal, and this signal is referred as interference signal by an interference component generator. Then, relatively low-received power signal can be detected by cancelling the interference signal from the total received signals. Therefore, the performance of the proposed scheme can improve the total average bit error rate and throughput of a MISO-VLC system.

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.

University of North Carolina Caries Risk Assessment Study: comparisons of high risk prediction, any risk prediction, and any risk etiologic models.

PubMed

Beck, J D; Weintraub, J A; Disney, J A; Graves, R C; Stamm, J W; Kaste, L M; Bohannan, H M

1992-12-01

The purpose of this analysis is to compare three different statistical models for predicting children likely to be at risk of developing dental caries over a 3-yr period. Data are based on 4117 children who participated in the University of North Carolina Caries Risk Assessment Study, a longitudinal study conducted in the Aiken, South Carolina, and Portland, Maine areas. The three models differed with respect to either the types of variables included or the definition of disease outcome. The two "Prediction" models included both risk factor variables thought to cause dental caries and indicator variables that are associated with dental caries, but are not thought to be causal for the disease. The "Etiologic" model included only etiologic factors as variables. A dichotomous outcome measure--none or any 3-yr increment, was used in the "Any Risk Etiologic model" and the "Any Risk Prediction Model". Another outcome, based on a gradient measure of disease, was used in the "High Risk Prediction Model". The variables that are significant in these models vary across grades and sites, but are more consistent among the Etiologic model than the Predictor models. However, among the three sets of models, the Any Risk Prediction Models have the highest sensitivity and positive predictive values, whereas the High Risk Prediction Models have the highest specificity and negative predictive values. Considerations in determining model preference are discussed.

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.

Antioxidant activity of selected plant species; potential new sources of natural antioxidants.

PubMed

Nićiforović, N; Mihailović, V; Masković, P; Solujić, S; Stojković, A; Pavlović Muratspahić, D

2010-11-01

The aim of this study was to examine six plants from Serbia for their potential antioxidant activity. Therefore, six antioxidant activity assays were carried out, including: total antioxidant capacity, DPPH free-radical scavenging, the inhibitory activity toward lipid peroxidation, Fe(3+)- reducing power, Fe(2+)- chelating ability and hydroxyl radical scavenging activity. Total phenolic and flavonoid contents were also determined for each alcoholic extract. Cotinus coggygria extract contained the highest amount of total phenols (413mg GAE /g dry extract), while the highest proportion of flavonoids was found in the Echium vulgare methanol extract (105 mg RU/g). Cotinus coggygria and Halacsya sendtneri alcoholic extracts showed the highest total antioxidant capacity (313 and 231 mg AA/g dry extract), as well as DPPH free-radical scavenging (IC(50)=9 and 99 μg/ml), inhibitory activity toward lipid peroxidation (IC(50)=3 and 17 μg/ml) and reducing power. Whereas, the greatest hydroxyl radical scavenging activity, as well as ferrous ion chelating ability showed Echium vulgare, Echium rubrum and Halacsya sendtneri. Copyright © 2010 Elsevier Ltd. All rights reserved.

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

75 W 40% efficiency single-mode all-fiber erbium-doped laser cladding pumped at 976 nm.

PubMed

Kotov, L V; Likhachev, M E; Bubnov, M M; Medvedkov, O I; Yashkov, M V; Guryanov, A N; Lhermite, J; Février, S; Cormier, E

2013-07-01

Optimization of Yb-free Er-doped fiber for lasers and amplifiers cladding pumped at 976 nm was performed in this Letter. The single-mode fiber design includes an increased core diameter of 34 μm and properly chosen erbium and co-dopant concentrations. We demonstrate an all-fiber high power laser and power amplifier based on this fiber with the record slope efficiency of 40%. To the best of our knowledge, the achieved output power of 75 W is the highest power reported for such lasers.

A cladding-pumped, tunable holmium doped fiber laser.

PubMed

Simakov, Nikita; Hemming, Alexander; Clarkson, W Andrew; Haub, John; Carter, Adrian

2013-11-18

We present a tunable, high power cladding-pumped holmium doped fiber laser. The laser generated >15 W CW average power across a wavelength range of 2.043 - 2.171 μm, with a maximum output power of 29.7 W at 2.120 μm. The laser also produced 18.2 W when operating at 2.171 µm. To the best of our knowledge this is the highest power operation of a holmium doped laser at a wavelength >2.15 µm. We discuss the significance of background losses and fiber design for achieving efficient operation in holmium doped fibers.

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…

Predicting performance of axial pump inducer of LOX booster turbo-pump of staged combustion cycle based rocket engine using CFD

NASA Astrophysics Data System (ADS)

Mishra, Arpit; Ghosh, Parthasarathi

2015-12-01

For low cost, high thrust, space missions with high specific impulse and high reliability, inert weight needs to be minimized and thereby increasing the delivered payload. Turbopump feed system for a liquid propellant rocket engine (LPRE) has the highest power to weight ratio. Turbopumps are primarily equipped with an axial flow inducer to achieve the high angular velocity and low suction pressure in combination with increased system reliability. Performance of the turbopump strongly depends on the performance of the inducer. Thus, for designing a LPRE turbopump, demands optimization of the inducer geometry based on the performance of different off-design operating regimes. In this paper, steady-state CFD analysis of the inducer of a liquid oxygen (LOX) axial pump used as a booster pump for an oxygen rich staged combustion cycle rocket engine has been presented using ANSYS® CFX. Attempts have been made to obtain the performance characteristic curves for the LOX pump inducer. The formalism has been used to predict the performance of the inducer for the throttling range varying from 80% to 113% of nominal thrust and for the different rotational velocities from 4500 to 7500 rpm. The results have been analysed to determine the region of cavitation inception for different inlet pressure.

Quantifying pollen-vegetation relationships to reconstruct ancient forests using 19th-century forest composition and pollen data

USGS Publications Warehouse

Dawson, Andria; Paciorek, Christopher J.; McLachlan, Jason S.; Goring, Simon; Williams, John W.; Jackson, Stephen T.

2016-01-01

Mitigation of climate change and adaptation to its effects relies partly on how effectively land-atmosphere interactions can be quantified. Quantifying composition of past forest ecosystems can help understand processes governing forest dynamics in a changing world. Fossil pollen data provide information about past forest composition, but rigorous interpretation requires development of pollen-vegetation models (PVMs) that account for interspecific differences in pollen production and dispersal. Widespread and intensified land-use over the 19th and 20th centuries may have altered pollen-vegetation relationships. Here we use STEPPS, a Bayesian hierarchical spatial PVM, to estimate key process parameters and associated uncertainties in the pollen-vegetation relationship. We apply alternate dispersal kernels, and calibrate STEPPS using a newly developed Euro-American settlement-era calibration data set constructed from Public Land Survey data and fossil pollen samples matched to the settlement-era using expert elicitation. Models based on the inverse power-law dispersal kernel outperformed those based on the Gaussian dispersal kernel, indicating that pollen dispersal kernels are fat tailed. Pine and birch have the highest pollen productivities. Pollen productivity and dispersal estimates are generally consistent with previous understanding from modern data sets, although source area estimates are larger. Tests of model predictions demonstrate the ability of STEPPS to predict regional compositional patterns.

Suicide Risk across Latent Class Subgroups: A Test of the Generalizability of the Interpersonal Psychological Theory of Suicide.

PubMed

Ma, Jennifer S; Batterham, Philip J; Calear, Alison L; Han, Jin

2018-01-06

It remains unclear whether the Interpersonal Psychological Theory of Suicide (IPTS; Joiner, ) is generalizable to the population or holds more explanatory power for certain subgroups compared to others. The aim of this study was to (1) identify subgroups of individuals who endorsed suicide ideation in the past month based on a range of mental health and demographic variables, (2) compare levels of the IPTS constructs within these subgroups, and (3) test the IPTS predictions for suicide ideation and suicide attempt for each group. Latent class, negative binomial, linear, and logistic regression analyses were conducted on population-based data obtained from 1,321 adults recruited from Facebook. Among participants reporting suicide ideation, four distinct patterns of risk factors emerged based on age and severity of mental health symptoms. Groups with highly elevated mental health symptoms reported the highest levels of thwarted belongingness and perceived burdensomeness. Tests of the IPTS interactions provided partial support for the theory, primarily in young adults with elevated mental health symptoms. Lack of support found for the IPTS predictions across the subgroups and full sample in this study raise some questions around the broad applicability of the theory. © 2018 The American Association of Suicidology.

Quantifying pollen-vegetation relationships to reconstruct ancient forests using 19th-century forest composition and pollen data

NASA Astrophysics Data System (ADS)

Dawson, Andria; Paciorek, Christopher J.; McLachlan, Jason S.; Goring, Simon; Williams, John W.; Jackson, Stephen T.

2016-04-01

Mitigation of climate change and adaptation to its effects relies partly on how effectively land-atmosphere interactions can be quantified. Quantifying composition of past forest ecosystems can help understand processes governing forest dynamics in a changing world. Fossil pollen data provide information about past forest composition, but rigorous interpretation requires development of pollen-vegetation models (PVMs) that account for interspecific differences in pollen production and dispersal. Widespread and intensified land-use over the 19th and 20th centuries may have altered pollen-vegetation relationships. Here we use STEPPS, a Bayesian hierarchical spatial PVM, to estimate key process parameters and associated uncertainties in the pollen-vegetation relationship. We apply alternate dispersal kernels, and calibrate STEPPS using a newly developed Euro-American settlement-era calibration data set constructed from Public Land Survey data and fossil pollen samples matched to the settlement-era using expert elicitation. Models based on the inverse power-law dispersal kernel outperformed those based on the Gaussian dispersal kernel, indicating that pollen dispersal kernels are fat tailed. Pine and birch have the highest pollen productivities. Pollen productivity and dispersal estimates are generally consistent with previous understanding from modern data sets, although source area estimates are larger. Tests of model predictions demonstrate the ability of STEPPS to predict regional compositional patterns.

Predicting the Spatial Distribution of Aspen Growth Potential in the Upper Great Lakes Region

Treesearch

Eric J. Gustafson; Sue M. Lietz; John L. Wright

2003-01-01

One way to increase aspen yields is to produce aspen on sites where aspen growth potential is highest. Aspen growth rates are typically predicted using site index, but this is impractical for landscape-level assessments. We tested the hypothesis that aspen growth can be predicted from site and climate variables and generated a model to map the spatial variability of...

Validity of four approaches of using repeaters' MCAT scores in medical school admissions to predict USMLE Step 1 total scores.

PubMed

Zhao, Xiaohui; Oppler, Scott; Dunleavy, Dana; Kroopnick, Marc

2010-10-01

This study investigated the validity of four approaches (the average, most recent, highest-within-administration, and highest-across-administration approaches) of using repeaters' Medical College Admission Test (MCAT) scores to predict Step 1 scores. Using the differential predication method, this study investigated the magnitude of differences in the expected Step 1 total scores between MCAT nonrepeaters and three repeater groups (two-time, three-time, and four-time test takers) for the four scoring approaches. For the average score approach, matriculants with the same MCAT average are expected to achieve similar Step 1 total scores regardless of whether the individual attempted the MCAT exam one or multiple times. For the other three approaches, repeaters are expected to achieve lower Step 1 scores than nonrepeaters; for a given MCAT score, as the number of attempts increases, the expected Step 1 decreases. The effect was strongest for the highest-across-administration approach, followed by the highest-within-administration approach, and then the most recent approach. Using the average score is the best approach for considering repeaters' MCAT scores in medical school admission decisions.

Jupiter Temperatures

NASA Image and Video Library

1997-09-29

This is one of the highest resolution images ever recorded of Jupiter temperature field. It was obtained by NASA Galileo mission. This map, shown in the lower panel, indicates the forces powering Jovian winds.

Using abiotic variables to predict importance of sites for species representation.

PubMed

Albuquerque, Fabio; Beier, Paul

2015-10-01

In systematic conservation planning, species distribution data for all sites in a planning area are used to prioritize each site in terms of the site's importance toward meeting the goal of species representation. But comprehensive species data are not available in most planning areas and would be expensive to acquire. As a shortcut, ecologists use surrogates, such as occurrences of birds or another well-surveyed taxon, or land types defined from remotely sensed data, in the hope that sites that represent the surrogates also represent biodiversity. Unfortunately, surrogates have not performed reliably. We propose a new type of surrogate, predicted importance, that can be developed from species data for a q% subset of sites. With species data from this subset of sites, importance can be modeled as a function of abiotic variables available at no charge for all terrestrial areas on Earth. Predicted importance can then be used as a surrogate to prioritize all sites. We tested this surrogate with 8 sets of species data. For each data set, we used a q% subset of sites to model importance as a function of abiotic variables, used the resulting function to predict importance for all sites, and evaluated the number of species in the sites with highest predicted importance. Sites with the highest predicted importance represented species efficiently for all data sets when q = 25% and for 7 of 8 data sets when q = 20%. Predicted importance requires less survey effort than direct selection for species representation and meets representation goals well compared with other surrogates currently in use. This less expensive surrogate may be useful in those areas of the world that need it most, namely tropical regions with the highest biodiversity, greatest biodiversity loss, most severe lack of inventory data, and poorly developed protected area networks. © 2015 Society for Conservation Biology.

Spatiotemporal distribution and fluctuation of radiocesium in Tokyo Bay in the five years following the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident

PubMed Central

Yamazaki, Hideo; Hinokio, Ryoichi; Yamashiki, Yosuke Alexandre; Azuma, Ryokei

2018-01-01

A monitoring survey was conducted from August 2011 to July 2016 of the spatiotemporal distribution in the 400 km2 area of the northern part of Tokyo Bay and in rivers flowing into it of radiocesium released from the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident. The average inventory in the river mouth (10 km2) was 131 kBq⋅m-2 and 0.73 kBq⋅m-2 in the central bay (330 km2) as the decay corrected value on March 16, 2011. Most of the radiocesium that flowed into Tokyo Bay originated in the northeastern section of the Tokyo metropolitan area, where the highest precipitation zone of 137Cs in soil was almost the same level as that in Fukushima City, then flowed into and was deposited in the Old-Edogawa River estuary, deep in Tokyo Bay. The highest precipitation of radiocesium measured in the high contaminated zone was 460 kBq⋅m-2. The inventory in sediment off the estuary of Old-Edogawa was 20.1 kBq⋅m-2 in August 2011 immediately after the accident, but it increased to 104 kBq⋅m-2 in July 2016. However, the radiocesium diffused minimally in sediments in the central area of Tokyo Bay in the five years following the FDNPP accident. The flux of radiocesium off the estuary decreased slightly immediately after the accident and conformed almost exactly to the values predicted based on its radioactive decay. Contrarily, the inventory of radiocesium in the sediment has increased. It was estimated that of the 8.33 TBq precipitated from the atmosphere in the catchment regions of the rivers Edogawa and Old-Edogawa, 1.31 TBq migrated through rivers and was deposited in the sediments of the Old-Edogawa estuary by July 2016. Currently, 0.25 TBq⋅yr-1 of radiocesium continues to flow into the deep parts of Tokyo Bay. PMID:29494667

High-Q plasmas in the TFTR tokamak

NASA Astrophysics Data System (ADS)

Jassby, D. L.; Barnes, C. W.; Bell, M. G.; Bitter, M.; Boivin, R.; Bretz, N. L.; Budny, R. V.; Bush, C. E.; Dylla, H. F.; Efthimion, P. C.; Fredrickson, E. D.; Hawryluk, R. J.; Hill, K. W.; Hosea, J.; Hsuan, H.; Janos, A. C.; Jobes, F. C.; Johnson, D. W.; Johnson, L. C.; Kamperschroer, J.; Kieras-Phillips, C.; Kilpatrick, S. J.; LaMarche, P. H.; LeBlanc, B.; Mansfield, D. K.; Marmar, E. S.; McCune, D. C.; McGuire, K. M.; Meade, D. M.; Medley, S. S.; Mikkelsen, D. R.; Mueller, D.; Owens, D. K.; Park, H. K.; Paul, S. F.; Pitcher, S.; Ramsey, A. T.; Redi, M. H.; Sabbagh, S. A.; Scott, S. D.; Snipes, J.; Stevens, J.; Strachan, J. D.; Stratton, B. C.; Synakowski, E. J.; Taylor, G.; Terry, J. L.; Timberlake, J. R.; Towner, H. H.; Ulrickson, M.; von Goeler, S.; Wieland, R. M.; Williams, M.; Wilson, J. R.; Wong, K.-L.; Young, K. M.; Zarnstorff, M. C.; Zweben, S. J.

1991-08-01

In the Tokamak Fusion Test Reactor (TFTR) [Plasma Phys. Controlled Fusion 26, 11 (1984)], the highest neutron source strength Sn and D-D fusion power gain QDD are realized in the neutral-beam-fueled and heated ``supershot'' regime that occurs after extensive wall conditioning to minimize recycling. For the best supershots, Sn increases approximately as P1.8b. The highest-Q shots are characterized by high Te (up to 12 keV), Ti (up to 34 keV), and stored energy (up to 4.7 MJ), highly peaked density profiles, broad Te profiles, and lower Zeff. Replacement of critical areas of the graphite limiter tiles with carbon-fiber composite tiles and improved alignment with the plasma have mitigated the ``carbon bloom.'' Wall conditioning by lithium pellet injection prior to the beam pulse reduces carbon influx and particle recycling. Empirically, QDD increases with decreasing pre-injection carbon radiation, and increases strongly with density peakedness [ne(0)/] during the beam pulse. To date, the best fusion results are Sn=5×1016 n/sec, QDD=1.85×10-3, and neutron yield=4.0×1016 n/pulse, obtained at Ip=1.6-1.9 MA and beam energy Eb=95-103 keV, with nearly balanced co- and counter-injected beam power. Computer simulations of supershot plasmas show that typically 50%-60% of Sn arises from beam-target reactions, with the remainder divided between beam-beam and thermonuclear reactions, the thermonuclear fraction increasing with Pb. The simulations predict that QDT=0.3-0.4 would be obtained for the best present plasma conditions, if half the deuterium neutral beams were to be replaced by tritium beams. Somewhat higher values are calculated if D beams are injected into a predominantly tritium target plasma. The projected central beta of fusion alphas is 0.4%-0.6%, a level sufficient for the study of alpha-induced collective effects.

What is the most accurate lymph node staging method for perihilar cholangiocarcinoma? Comparison of UICC/AJCC pN stage, number of metastatic lymph nodes, lymph node ratio, and log odds of metastatic lymph nodes.

PubMed

Conci, S; Ruzzenente, A; Sandri, M; Bertuzzo, F; Campagnaro, T; Bagante, F; Capelli, P; D'Onofrio, M; Piccino, M; Dorna, A E; Pedrazzani, C; Iacono, C; Guglielmi, A

2017-04-01

We compared the prognostic performance of the International Union Against Cancer/American Joint Committee on Cancer (UICC/AJCC) 7th edition pN stage, number of metastatic LNs (MLNs), LN ratio (LNR), and log odds of MLNs (LODDS) in patients with perihilar cholangiocarcinoma (PCC) undergoing curative surgery in order to identify the best LN staging method. Ninety-nine patients who underwent surgery with curative intent for PCC in a single tertiary hepatobiliary referral center were included in the study. Two approaches were used to evaluate and compare the predictive power of the different LN staging methods: one based on the estimation of variable importance with prediction error rate and the other based on the calculation of the receiver operating characteristic (ROC) curve. LN dissection was performed in 92 (92.9%) patients; 49 were UICC/AJCC pN0 (49.5%), 33 pN1 (33.3%), and 10 pN2 (10.1%). The median number of LNs retrieved was 8. The prediction error rate ranged from 42.7% for LODDS to 47.1% for UICC/AJCC pN stage. Moreover, LODDS was the variable with the highest area under the ROC curve (AUC) for prediction of 3-year survival (AUC = 0.71), followed by LNR (AUC = 0.60), number of MLNs (AUC = 0.59), and UICC/AJCC pN stage (AUC = 0.54). The number of MLNs, LNR, and LODDS appear to better predict survival than the UICC/AJCC pN stage in patients undergoing curative surgery for PCC. Moreover, LODDS seems to be the most accurate and predictive LN staging method. Copyright © 2017 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Ultrasonication and the quality of human milk: variation of power and time of exposure.

PubMed

Christen, Lukas; Lai, Ching Tat; Hartmann, Peter E

2012-08-01

Donor human milk is pasteurized to prevent the potential risk of the transmission of pathogens to preterm infants. Currently, Holder pasteurization (human milk held at 62·5°C for 30 min) is used in most human milk banks, but has the disadvantage that it results in excessive inactivation of important bioactive components. Power-ultrasound (20-100 kHz) is an emerging technology for the preservation of foods and could be an alternative method for the treatment of human milk. The aim of this study was to investigate the effect of different ultrasound settings on the elimination of Escherichia coli and the retention of bile salt stimulated lipase (BSSL) activity. Ultrasonication with a constant power decreased Esch. coli viability exponentially over time until the processing temperature increased to sub-pasteurization level to between 51·4 and 58·5°C, then a log10 1·3 decrease was observed (P<0·05). BSSL activity decreased to 91% until a temperature of 51·4°C and then it decreased to 8% between 51·4 and 64·9°C. Ultrasonication with a constant energy and various power and exposure times showed the highest temperature (53·7°C) when treated with the longest exposure time and lowest ultrasound-power (276 s at 3·62 W) compared with 37·6°C for 39 s at 25·64 W. The findings predict that the viability of Esch. coli could be reduced by log10 5 with a minimal loss of activity of BSSL by applying 13·8 kJ of energy in 12 ml of human milk using high ultrasound power over a short exposure time to ensure that the temperature remains below the critical level for protein denaturation. Alternatively, the use of lower power settings such as the 26 W used in the present studies would require a cooling system to ensure the human milk BSSL was protected against temperature denaturation.

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

Predicting Social Trust with Binary Logistic Regression

ERIC Educational Resources Information Center

Adwere-Boamah, Joseph; Hufstedler, Shirley

2015-01-01

This study used binary logistic regression to predict social trust with five demographic variables from a national sample of adult individuals who participated in The General Social Survey (GSS) in 2012. The five predictor variables were respondents' highest degree earned, race, sex, general happiness and the importance of personally assisting…

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.

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.

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.

Wavelength switchable high-power diode-side-pumped rod Tm:YAG Laser around 2µm.

PubMed

Wang, Caili; Du, Shifeng; Niu, Yanxiong; Wang, Zhichao; Zhang, Chao; Bian, Qi; Guo, Chuan; Xu, Jialin; Bo, Yong; Peng, Qinjun; Cui, Dafu; Zhang, Jingyuan; Lei, Wenqiang; Xu, Zuyan

2013-03-25

We report a high-power diode-side-pumped rod Tm:YAG laser operated at either 2.07 or 2.02 µm depending on the transmission of pumped output coupler. The laser yields 115W of continuous-wave output power at 2.07 µm with 5% output coupling, which is the highest output power for all solid-state 2.07 μm cw rod Tm:YAG laser reported so far. With an output coupler of 10% transmission, the center wavelength of the laser is switched to 2.02 μm with an output power of 77.1 W. This is the first observation of high-power wavelength switchable diode-side-pumped rod Tm:YAG laser around 2 µm.

A 250 MHz, high power mode-locked Nd:GdVO4 oscillator with low timing jitter under 879 nm direct pumping

NASA Astrophysics Data System (ADS)

Zhang, F. F.; Zuo, J. W.; Wang, Z. M.; Yang, J.; Cheng, H. L.; Zong, N.; Yang, F.; Peng, Q. J.; Xu, Z. Y.

2013-04-01

We developed a high power mode-locked Nd:GdVO4 oscillator with low timing jitter directly pumped by an 879 nm diode. Under the absorbed pump power of 13.8 W, a maximum output power of 5.68 W at 1063 nm was obtained with a repetition rate of ˜250 MHz, corresponding to a slope efficiency of 78.7%. The measured pulse width and root mean square timing jitter at the output power of 5.35 W were 7.4 ps and 286 fs, respectively. To the best of our knowledge, this is the highest output power for a picosecond Nd:GdVO4 oscillator with low timing jitter.

Comparison of ISS Power System Telemetry with Analytically Derived Data for Shadowed Cases

NASA Technical Reports Server (NTRS)

Fincannon, H. James

2002-01-01

Accurate International Space Station (ISS) power prediction requires the quantification of solar array shadowing. Prior papers have discussed the NASA Glenn Research Center (GRC) ISS power system tool SPACE (System Power Analysis for Capability Evaluation) and its integrated shadowing algorithms. On-orbit telemetry has become available that permits the correlation of theoretical shadowing predictions with actual data. This paper documents the comparison of a shadowing metric (total solar array current) as derived from SPACE predictions and on-orbit flight telemetry data for representative significant shadowing cases. Images from flight video recordings and the SPACE computer program graphical output are used to illustrate the comparison. The accuracy of the SPACE shadowing capability is demonstrated for the cases examined.

Modelling and assessment of the electric field strength caused by mobile phone to the human head.

PubMed

Buckus, Raimondas; Strukcinskiene, Birute; Raistenskis, Juozas; Stukas, Rimantas

2016-06-01

Electromagnetic field exposure is the one of the most important physical agents that actively affects live organisms and environment. Active use of mobile phones influences the increase of electromagnetic field radiation. The aim of the study was to measure and assess the electric field strength caused by mobile phones to the human head. In this paper the software "COMSOL Multiphysics" was used to establish the electric field strength created by mobile phones around the head. The second generation (2G) Global System for Mobile (GSM) phones that operate in the frequency band of 900 MHz and reach the power of 2 W have a stronger electric field than (2G) GSM mobile phones that operate in the higher frequency band of 1,800 MHz and reach the power up to 1 W during conversation. The third generation of (3G) UMTS smart phones that effectively use high (2,100 MHz) radio frequency band emit the smallest electric field strength values during conversation. The highest electric field strength created by mobile phones is around the ear, i.e. the mobile phone location. The strength of mobile phone electric field on the phantom head decreases exponentially while moving sidewards from the center of the effect zone (the ear), and constitutes 1-12% of the artificial head's surface. The highest electric field strength values of mobile phones are associated with their higher power, bigger specific energy absorption rate (SAR) and lower frequency of mobile phone. The stronger electric field emitted by the more powerful mobile phones takes a higher percentage of the head surface. The highest electric field strength created by mobile phones is distributed over the user's ear.

Purchasing power of civil servant health workers in Mozambique

PubMed Central

Ferrinho, Fátima; Amaral, Marta; Russo, Giuliano; Ferrinho, Paulo

2012-01-01

Background Health workers’ purchasing power is an important consideration in the development of strategies for health workforce development. This work explores the purchasing power variation of Mozambican public sector health workers, between 1999 and 2007. In general, the calculated purchasing power increased for most careers under study, and the highest percentage increase was observed for the lowest remuneration careers, contributing in this way for a relative reduction in the difference between the higher and the lower salaries. Methods This was done through a simple and easy-to-apply methodology to estimate salaries’ capitalization rate, by means of the accumulated inflation rate, after taking wage revisions into account. All the career categories in the Ministry of Health and affiliated public sector institutions were considered. Results Health workers’ purchasing power is an important consideration in the development of strategies for health workforce development. This work explores the purchasing power variation of Mozambican public sector health workers, between 1999 and 2007. In general, the calculated purchasing power increased for most careers under study, and the highest percentage increase was observed for the lowest remuneration careers, contributing in this way for a relative reduction in the difference between the higher and the lower salaries. Conclusion These results seem to contradict a commonly held assumption that health sector pay has deteriorated over the years, and with substantial damage for the poorest. Further studies appear to be needed to design a more accurate methodology to better understand the evolution and impact of public sector health workers’ remunerations across the years. PMID:22368757

Active cooling of pulse compression diffraction gratings for high energy, high average power ultrafast lasers

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

Alessi, David A.; Rosso, Paul A.; Nguyen, Hoang T.

Laser energy absorption and subsequent heat removal from diffraction gratings in chirped pulse compressors poses a significant challenge in high repetition rate, high peak power laser development. In order to understand the average power limitations, we have modeled the time-resolved thermo-mechanical properties of current and advanced diffraction gratings. We have also developed and demonstrated a technique of actively cooling Petawatt scale, gold compressor gratings to operate at 600W of average power - a 15x increase over the highest average power petawatt laser currently in operation. As a result, combining this technique with low absorption multilayer dielectric gratings developed in ourmore » group would enable pulse compressors for petawatt peak power lasers operating at average powers well above 40kW.« less

A 500-600 MHz GaN power amplifier with RC-LC stability network

NASA Astrophysics Data System (ADS)

Ma, Xinyu; Duan, Baoxing; Yang, Yintang

2017-08-01

A 500-600 MHz high-efficiency, high-power GaN power amplifier is designed and realized on the basis of the push-pull structure. The RC-LC stability network is proposed and applied to the power amplifier circuit for the first time. The RC-LC stability network can significantly reduce the high gain out the band, which eliminates the instability of the power amplifier circuit. The developed power amplifier exhibits 58.5 dBm (700 W) output power with a 17 dB gain and 85% PAE at 500-600 MHz, 300 μs, 20% duty cycle. It has the highest PAE in P-band among the products at home and abroad. Project supported by the National Key Basic Research Program of China (No. 2014CB339901).

Active cooling of pulse compression diffraction gratings for high energy, high average power ultrafast lasers

DOE PAGES

Alessi, David A.; Rosso, Paul A.; Nguyen, Hoang T.; ...

2016-12-26

Laser energy absorption and subsequent heat removal from diffraction gratings in chirped pulse compressors poses a significant challenge in high repetition rate, high peak power laser development. In order to understand the average power limitations, we have modeled the time-resolved thermo-mechanical properties of current and advanced diffraction gratings. We have also developed and demonstrated a technique of actively cooling Petawatt scale, gold compressor gratings to operate at 600W of average power - a 15x increase over the highest average power petawatt laser currently in operation. As a result, combining this technique with low absorption multilayer dielectric gratings developed in ourmore » group would enable pulse compressors for petawatt peak power lasers operating at average powers well above 40kW.« less

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

Prediction and characterization of application power use in a high-performance computing environment

DOE PAGES

Bugbee, Bruce; Phillips, Caleb; Egan, Hilary; ...

2017-02-27

Power use in data centers and high-performance computing (HPC) facilities has grown in tandem with increases in the size and number of these facilities. Substantial innovation is needed to enable meaningful reduction in energy footprints in leadership-class HPC systems. In this paper, we focus on characterizing and investigating application-level power usage. We demonstrate potential methods for predicting power usage based on a priori and in situ characteristics. Lastly, we highlight a potential use case of this method through a simulated power-aware scheduler using historical jobs from a real scientific HPC system.

General fuel cell hybrid synergies and hybrid system testing status

NASA Astrophysics Data System (ADS)

Winkler, Wolfgang; Nehter, Pedro; Williams, Mark C.; Tucker, David; Gemmen, Randy

FCT hybrid power systems offer the highest efficiency and the cleanest emissions of all fossil fuelled power. The engineering for the highest possible efficiency at lowest cost and weight depends on general system architecture issues and the performance of the components. Presented in this paper are system studies which provide direction for the most efficient path toward achieving the most beneficial result for this technology. Ultimately, fuel cell-turbine (FCT) hybrid systems applicable to integrated gasification combined cycle power systems will form the basis for reaching the goals for advanced coal-based power generation. The FCT hybrid power island will also be important for the FutureGen plant and will provide new options for carbon dioxide capture and sequestration as well as power and hydrogen generation. The system studies presented in this paper provide insight to current technology 'benchmarks' versus expected benefits from hybrid applications. Discussion is also presented on the effects of different balance of plant arrangements and approaches. Finally, we discuss the status of US DOE is sponsored projects that are looking to help understand the unique requirements for these systems. One of these projects, Hyper, will provide information on FCT dynamics and will help identify technical needs and opportunities for cycle advancement. The methods studied show promise for effective control of a hybrid system without the direct intervention of isolation valves or check valves in the main pressure loop of the system, which introduce substantial pressure losses, allowing for realization of the full potential efficiency of the hybrid system.

NREL Projects Awarded More Than $3 Million to Advance Novel Solar

Science.gov Websites

in Grid Operations," evaluating a research solution to better integrate solar power generation funding program, which advances state-of-the-art techniques for predicting solar power generation to Office to advance predictive modeling of solar power as part of its Solar Forecasting 2 funding program

Predictive Ability of the Medicine Ball Chest Throw and Vertical Jump Tests for Determining Muscular Strength and Power in Adolescents

ERIC Educational Resources Information Center

Hackett, Daniel A.; Davies, Timothy B.; Ibel, Denis; Cobley, Stephen; Sanders, Ross

2018-01-01

This study examined the predictive ability of the medicine ball chest throw and vertical jump for muscular strength and power in adolescents. One hundred and ninety adolescents participated in this study. Participants performed trials of the medicine ball chest throw and vertical jump, with vertical jump peak power calculated via an estimation…

Nonlinear Recurrent Neural Network Predictive Control for Energy Distribution of a Fuel Cell Powered Robot

PubMed Central

Chen, Qihong; Long, Rong; Quan, Shuhai

2014-01-01

This paper presents a neural network predictive control strategy to optimize power distribution for a fuel cell/ultracapacitor hybrid power system of a robot. We model the nonlinear power system by employing time variant auto-regressive moving average with exogenous (ARMAX), and using recurrent neural network to represent the complicated coefficients of the ARMAX model. Because the dynamic of the system is viewed as operating- state- dependent time varying local linear behavior in this frame, a linear constrained model predictive control algorithm is developed to optimize the power splitting between the fuel cell and ultracapacitor. The proposed algorithm significantly simplifies implementation of the controller and can handle multiple constraints, such as limiting substantial fluctuation of fuel cell current. Experiment and simulation results demonstrate that the control strategy can optimally split power between the fuel cell and ultracapacitor, limit the change rate of the fuel cell current, and so as to extend the lifetime of the fuel cell. PMID:24707206

The rate of transient beta frequency events predicts behavior across tasks and species

PubMed Central

Law, Robert; Tsutsui, Shawn; Moore, Christopher I; Jones, Stephanie R

2017-01-01

Beta oscillations (15-29Hz) are among the most prominent signatures of brain activity. Beta power is predictive of healthy and abnormal behaviors, including perception, attention and motor action. In non-averaged signals, beta can emerge as transient high-power 'events'. As such, functionally relevant differences in averaged power across time and trials can reflect changes in event number, power, duration, and/or frequency span. We show that functionally relevant differences in averaged beta power in primary somatosensory neocortex reflect a difference in the number of high-power beta events per trial, i.e. event rate. Further, beta events occurring close to the stimulus were more likely to impair perception. These results are consistent across detection and attention tasks in human magnetoencephalography, and in local field potentials from mice performing a detection task. These results imply that an increased propensity of beta events predicts the failure to effectively transmit information through specific neocortical representations. PMID:29106374

Influence of fundamental mode fill factor on disk laser output power and laser beam quality

NASA Astrophysics Data System (ADS)

Cheng, Zhiyong; Yang, Zhuo; Shao, Xichun; Li, Wei; Zhu, Mengzhen

2017-11-01

An three-dimensional numerical model based on finite element method and Fox-Li method with angular spectrum diffraction theoy is developed to calculate the output power and power density distribution of Yb:YAG disk laser. We invest the influence of fundamental mode fill factor(the ratio of fundamental mode size and pump spot size) on the output power and laser beam quality. Due to aspherical aberration and soft aperture effect in laser disk, high beam quality can be achieve with relative lower efficiency. The highest output power of fundamental laser mode is influenced by the fundamental mode fill factor. Besides we find that optimal mode fill factor increase with pump spot size.

High-power highly stable passively Q-switched fiber laser based on monolayer graphene

NASA Astrophysics Data System (ADS)

Wu, Hanshuo; Song, Jiaxin; Wu, Jian; Xu, Jiangming; Xiao, Hu; Leng, Jinyong; Zhou, Pu

2018-03-01

We demonstrate a monolayer graphene-based passively Q-switched fiber laser with three-stage amplifiers that can deliver an average power of over 80 W at 1064 nm. The highest average power achieved is 84.1 W, with a pulse energy of 1.67 mJ. To the best of our knowledge this is the first report of a high-power passively Q-switched fiber laser in the 1 µm range. More importantly, the Q-switched fiber laser operated stably during a week of tests for a few hours per day, which proves the stability and practical application potential of graphene in high-power pulsed fiber lasers.

Carbon nanotube scaffolds with controlled porosity as electromagnetic absorbing materials in the gigahertz range

NASA Astrophysics Data System (ADS)

González, M.; Crespo, M.; Baselga, J.; Pozuelo, J.

2016-05-01

Control of the microscopic structure of CNT nanocomposites allows modulation of the electromagnetic shielding in the gigahertz range. The porosity of CNT scaffolds has been controlled by two freezing protocols and a subsequent lyophilization step: fast freezing in liquid nitrogen and slow freezing at -20 °C. Mercury porosimetry shows that slowly frozen specimens present a more open pore size (100-150 μm) with a narrow distribution whereas specimens frozen rapidly show a smaller pore size and a heterogeneous distribution. 3D-scaffolds containing 3, 4, 6 and 7% CNT were infiltrated with epoxy and specimens with 2, 5 and 8 mm thicknesses were characterized in the GHz range. Samples with the highest pore size and porosity presented the lowest reflected power (about 30%) and the highest absorbed power (about 70%), which allows considering them as electromagnetic radiation absorbing materials.Control of the microscopic structure of CNT nanocomposites allows modulation of the electromagnetic shielding in the gigahertz range. The porosity of CNT scaffolds has been controlled by two freezing protocols and a subsequent lyophilization step: fast freezing in liquid nitrogen and slow freezing at -20 °C. Mercury porosimetry shows that slowly frozen specimens present a more open pore size (100-150 μm) with a narrow distribution whereas specimens frozen rapidly show a smaller pore size and a heterogeneous distribution. 3D-scaffolds containing 3, 4, 6 and 7% CNT were infiltrated with epoxy and specimens with 2, 5 and 8 mm thicknesses were characterized in the GHz range. Samples with the highest pore size and porosity presented the lowest reflected power (about 30%) and the highest absorbed power (about 70%), which allows considering them as electromagnetic radiation absorbing materials. Electronic supplementary information (ESI) available: Scheme of hydrogenated derivative of diglycidyl ether of bisphenol-A (HDGEBA) and m-xylylenediamine; X-ray diffractograms of pristine CNT and oxidized CNT; glass transition temperatures of composites; electromagnetic shielding analysis in the 1-18 GHz frequency range. See DOI: 10.1039/c6nr02133f

Applying a radiomics approach to predict prognosis of lung cancer patients

NASA Astrophysics Data System (ADS)

Emaminejad, Nastaran; Yan, Shiju; Wang, Yunzhi; Qian, Wei; Guan, Yubao; Zheng, Bin

2016-03-01

Radiomics is an emerging technology to decode tumor phenotype based on quantitative analysis of image features computed from radiographic images. In this study, we applied Radiomics concept to investigate the association among the CT image features of lung tumors, which are either quantitatively computed or subjectively rated by radiologists, and two genomic biomarkers namely, protein expression of the excision repair cross-complementing 1 (ERCC1) genes and a regulatory subunit of ribonucleotide reductase (RRM1), in predicting disease-free survival (DFS) of lung cancer patients after surgery. An image dataset involving 94 patients was used. Among them, 20 had cancer recurrence within 3 years, while 74 patients remained DFS. After tumor segmentation, 35 image features were computed from CT images. Using the Weka data mining software package, we selected 10 non-redundant image features. Applying a SMOTE algorithm to generate synthetic data to balance case numbers in two DFS ("yes" and "no") groups and a leave-one-case-out training/testing method, we optimized and compared a number of machine learning classifiers using (1) quantitative image (QI) features, (2) subjective rated (SR) features, and (3) genomic biomarkers (GB). Data analyses showed relatively lower correlation among the QI, SR and GB prediction results (with Pearson correlation coefficients < 0.5 including between ERCC1 and RRM1 biomarkers). By using area under ROC curve as an assessment index, the QI, SR and GB based classifiers yielded AUC = 0.89+/-0.04, 0.73+/-0.06 and 0.76+/-0.07, respectively, which showed that all three types of features had prediction power (AUC>0.5). Among them, using QI yielded the highest performance.

Using iron studies to predict HFE mutations in New Zealand: implications for laboratory testing.

PubMed

O'Toole, Rebecca; Romeril, Kenneth; Bromhead, Collette

2017-04-01

The diagnosis of hereditary haemochromatosis (HH) is not straightforward because symptoms are often absent or non-specific. Biochemical markers of iron-overloading may be affected by other conditions. To measure the correlation between iron studies and HFE genotype to inform evidence-based recommendations for laboratory testing in New Zealand. Results from 2388 patients genotyped for C282Y, H63D and S65C in Wellington, New Zealand from 2007 to 2013 were compared with their biochemical phenotype as quantified by serum ferritin (SF), transferrin saturation (TS), serum iron (SI) and serum transferrin (ST). The predictive power of these markers was evaluated by receiver operator characteristic (ROC) curve analysis, and if a statistically significant association for a variable was seen, sensitivity, specificity and predictive values were calculated. Test ordering patterns showed that 62% of HFE genotyping tests were ordered because of an elevated SF alone and only 11% of these had a C-reactive protein test to rule out an acute phase reaction. The association between SF and significant HFE genotypes SF was low. However, TS values ≥45% predicted HH mutations with the highest sensitivity and specificity. A SF of >1000 µg/L was found in one at-risk patient (C282Y homozygote) who had a TS <45%. Our analysis highlights the need for clear guidelines for investigation of hyperferritinaemia and HH in New Zealand. Using our findings, we developed an evidence-based laboratory testing algorithm based on a TS ≥45%, a SF ≥1000 µg/L and/or a family history of HH which identified all C282Y homozygotes in this study. © 2016 Royal Australasian College of Physicians.

Predicting Ebola infection: A malaria-sensitive triage score for Ebola virus disease

PubMed Central

Okoni-Williams, Harry Henry; Suma, Mohamed; Mancuso, Brooke; Al-Dikhari, Ahmed; Faouzi, Mohamed

2017-01-01

Background The non-specific symptoms of Ebola Virus Disease (EVD) pose a major problem to triage and isolation efforts at Ebola Treatment Centres (ETCs). Under the current triage protocol, half the patients allocated to high-risk “probable” wards were EVD(-): a misclassification speculated to predispose nosocomial EVD infection. A better understanding of the statistical relevance of individual triage symptoms is essential in resource-poor settings where rapid, laboratory-confirmed diagnostics are often unavailable. Methods/Principal findings This retrospective cohort study analyses the clinical characteristics of 566 patients admitted to the GOAL-Mathaska ETC in Sierra Leone. The diagnostic potential of each characteristic was assessed by multivariate analysis and incorporated into a statistically weighted predictive score, designed to detect EVD as well as discriminate malaria. Of the 566 patients, 28% were EVD(+) and 35% were malaria(+). Malaria was 2-fold more common in EVD(-) patients (p<0.05), and thus an important differential diagnosis. Univariate analyses comparing EVD(+) vs. EVD(-) and EVD(+)/malaria(-) vs. EVD(-)/malaria(+) cohorts revealed 7 characteristics with the highest odds for EVD infection, namely: reported sick-contact, conjunctivitis, diarrhoea, referral-time of 4–9 days, pyrexia, dysphagia and haemorrhage. Oppositely, myalgia was more predictive of EVD(-) or EVD(-)/malaria(+). Including these 8 characteristics in a triage score, we obtained an 89% ability to discriminate EVD(+) from either EVD(-) or EVD(-)/malaria(+). Conclusions/Significance This study proposes a highly predictive and easy-to-use triage tool, which stratifies the risk of EVD infection with 89% discriminative power for both EVD(-) and EVD(-)/malaria(+) differential diagnoses. Improved triage could preserve resources by identifying those in need of more specific differential diagnostics as well as bolster infection prevention/control measures by better compartmentalizing the risk of nosocomial infection. PMID:28231242

Predicting Ebola infection: A malaria-sensitive triage score for Ebola virus disease.

PubMed

Hartley, Mary-Anne; Young, Alyssa; Tran, Anh-Minh; Okoni-Williams, Harry Henry; Suma, Mohamed; Mancuso, Brooke; Al-Dikhari, Ahmed; Faouzi, Mohamed

2017-02-01

The non-specific symptoms of Ebola Virus Disease (EVD) pose a major problem to triage and isolation efforts at Ebola Treatment Centres (ETCs). Under the current triage protocol, half the patients allocated to high-risk "probable" wards were EVD(-): a misclassification speculated to predispose nosocomial EVD infection. A better understanding of the statistical relevance of individual triage symptoms is essential in resource-poor settings where rapid, laboratory-confirmed diagnostics are often unavailable. This retrospective cohort study analyses the clinical characteristics of 566 patients admitted to the GOAL-Mathaska ETC in Sierra Leone. The diagnostic potential of each characteristic was assessed by multivariate analysis and incorporated into a statistically weighted predictive score, designed to detect EVD as well as discriminate malaria. Of the 566 patients, 28% were EVD(+) and 35% were malaria(+). Malaria was 2-fold more common in EVD(-) patients (p<0.05), and thus an important differential diagnosis. Univariate analyses comparing EVD(+) vs. EVD(-) and EVD(+)/malaria(-) vs. EVD(-)/malaria(+) cohorts revealed 7 characteristics with the highest odds for EVD infection, namely: reported sick-contact, conjunctivitis, diarrhoea, referral-time of 4-9 days, pyrexia, dysphagia and haemorrhage. Oppositely, myalgia was more predictive of EVD(-) or EVD(-)/malaria(+). Including these 8 characteristics in a triage score, we obtained an 89% ability to discriminate EVD(+) from either EVD(-) or EVD(-)/malaria(+). This study proposes a highly predictive and easy-to-use triage tool, which stratifies the risk of EVD infection with 89% discriminative power for both EVD(-) and EVD(-)/malaria(+) differential diagnoses. Improved triage could preserve resources by identifying those in need of more specific differential diagnostics as well as bolster infection prevention/control measures by better compartmentalizing the risk of nosocomial infection.

Prospective comparison of severity scores for predicting mortality in community-acquired pneumonia.

PubMed

Luque, Sonia; Gea, Joaquim; Saballs, Pere; Ferrández, Olivia; Berenguer, Nuria; Grau, Santiago

2012-06-01

Specific prognostic models for community acquired pneumonia (CAP) to guide treatment decisions have been developed, such us the Pneumonia Severity Index (PSI) and the Confusion, Urea nitrogen, Respiratory rate, Blood pressure and age ≥ 65 years index (CURB-65). Additionally, general models are available such as the Mortality Probability Model (MPM-II). So far, which score performs better in CAP remains controversial. The objective was to compare PSI and CURB-65 and the general model, MPM-II, for predicting 30-day mortality in patients admitted with CAP. Prospective observational study including all consecutive patients hospitalised with a confirmed diagnosis of CAP and treated according to the hospital guidelines. Comparison of the overall discriminatory power of the models was performed by calculating the area under a receiver operator characteristic curve (AUC ROC curve) and calibration through the Goodness-of-fit test. One hundred and fifty two patients were included (mean age 73.0 years; 69.1% male; 75.0% with more than one comorbid condition). Seventy-five percent of the patients were classified as high-risk subjects according to the PSI, versus 61.2% according to the CURB-65. The 30-day mortality rate was 11.8%. All three scores obtained acceptable and similar values of the AUCs of the ROC curve for predicting mortality. Despite all rules showed good calibration, this seemed to be better for CURB-65. CURB-65 also revealed the highest positive likelihood ratio. CURB-65 performs similar to PSI or MPMII for predicting 30-day mortality in patients with CAP. Consequently, this simple model can be regarded as a valid alternative to the more complex rules.