Predictions of Experimentally Observed Stochastic Ground Vibrations Induced by Blasting

PubMed Central

Kostić, Srđan; Perc, Matjaž; Vasović, Nebojša; Trajković, Slobodan

2013-01-01

In the present paper, we investigate the blast induced ground motion recorded at the limestone quarry “Suva Vrela” near Kosjerić, which is located in the western part of Serbia. We examine the recorded signals by means of surrogate data methods and a determinism test, in order to determine whether the recorded ground velocity is stochastic or deterministic in nature. Longitudinal, transversal and the vertical ground motion component are analyzed at three monitoring points that are located at different distances from the blasting source. The analysis reveals that the recordings belong to a class of stationary linear stochastic processes with Gaussian inputs, which could be distorted by a monotonic, instantaneous, time-independent nonlinear function. Low determinism factors obtained with the determinism test further confirm the stochastic nature of the recordings. Guided by the outcome of time series analysis, we propose an improved prediction model for the peak particle velocity based on a neural network. We show that, while conventional predictors fail to provide acceptable prediction accuracy, the neural network model with four main blast parameters as input, namely total charge, maximum charge per delay, distance from the blasting source to the measuring point, and hole depth, delivers significantly more accurate predictions that may be applicable on site. We also perform a sensitivity analysis, which reveals that the distance from the blasting source has the strongest influence on the final value of the peak particle velocity. This is in full agreement with previous observations and theory, thus additionally validating our methodology and main conclusions. PMID:24358140

Health determinants of nutritional status in community-dwelling older population: the VERISAÚDE study.

PubMed

Maseda, Ana; Gómez-Caamaño, Sarai; Lorenzo-López, Laura; López-López, Rocío; Diego-Diez, Clara; Sanluís-Martínez, Verónica; Valdiglesias, Vanessa; Millán-Calenti, José C

2016-08-01

Malnutrition is a common and relevant syndrome in elderly people due to its influence on quality of life. The main aim of the present study was to identify health determinants of malnutrition or risk of malnutrition. Cross-sectional study collecting information on sociodemographic and health factors (co-morbidity, cognitive or affective problems, prescription medication use, frailty status, self-rated health) as determinants of nutritional status, assessed by the short form of the Mini Nutritional Assessment. Forty-three senior centres from Galicia (north-western Spain) participated to recruit participants. A representative community-dwelling sample of 749 elderly people aged ≥65 years. Of the total participants, 14·3 % were malnourished/at risk of malnutrition. Presence of overweight or obesity, depressive symptoms, polypharmacy (use of five or more prescription medications), presence of pre-frailty or frailty status and poor self-rated health showed the strongest relationship to malnutrition/risk of malnutrition. This model predicted 86·0 % of the cases correctly. The best determinants for women were polypharmacy and poor self-rated health, reaching 82·8 % of cases of malnourishment/risk of malnutrition predicted correctly. In men, the main determinants were overweight or obesity, depressive symptomatology and polypharmacy, with 89·8 % of cases of malnourishmen/risk of malnutrition predicted correctly. Screening for nutritional status and its determinant factors should be included as part of comprehensive assessments to ensure an early screening of malnutrition and to propose possible intervention strategies that would be important for both elderly people and the health-care system.

UV observations of blue stragglers and population 2 K dwarfs

NASA Technical Reports Server (NTRS)

Carney, B. W.; Bond, H. E.

1986-01-01

Blue stragglers are stars, found usually in either open or globular clusters, that appear to lie on the main sequence, but are brighter and bluer than the cluster turn-off. Currently, two rival models are invoked to explain this apparently pathological behavior: internal mixing (so that fresh fuel is brought into the stellar core); and mass transfer (by which a normal main sequence star acquires mass from an evolving nearby companion and so moves up the main sequence). The latter model predicts that in the absence of complete mass transfer (i.e., coalescence), blue stragglers should be binary systems with the fainter star in a post-main sequence evolutionary state. It is important to ascertain the cause of this phenomenon since stellar evolution models of main sequence stars play such a vital role in astronomy. If mass transfer is involved, one may easily exclude binaries from age determinations of clusters, but if mixing is the cause, our age determinations will be much less accurate unless we can determine whether all stars or only some mix, and what causes the mixing to occur at all.

Power Aware Distributed Systems

DTIC Science & Technology

2004-01-01

detection or threshold functions to trigger the main CPU. The main processor can sleep and either wakeup on a schedule or by a positive threshold event...the RTOS must determine if wake-up latency can be tolerated (or, if it could be hidden by pre- wakeup ). The prediction accuracy for scheduling ...and processor shutdown/ wakeup . This analysis can be used to accurately analyze the schedulability of non-concrete periodic task sets, scheduled using

Predicting various biodiesel fuel properties

USDA-ARS?s Scientific Manuscript database

Several essential fuel properties of biodiesel are largely determined by the properties of the fatty esters which are its main components. These include cetane number, kinematic viscosity, oxidative stability, and cold flow which are contained in almost all biodiesel standards but also other propert...

An Examination of Motivational Regulations, Dispositional Flow and Social Physique Anxiety among College Students for Exercise: A Self-Determination Theory Approach

ERIC Educational Resources Information Center

Ersöz, Gözde

2016-01-01

Based on self-determination theory (SDT), the main goal of this study is to analyze dispositional flow and social physique anxiety (SPA) that could be predicted by gender, BMI and motivational regulations and to examine motivational regulations, dispositional flow and SPA of college students in terms of stage of change for exercise. Participants…

Predictors of the Elementary School Proficiency Exams and Issues of Equality in Educational Facilities

ERIC Educational Resources Information Center

Erdogan, Irfan; Meseci Giorgetti, Filiz; Cifcili, Vakur

2011-01-01

The main purpose of this study is to determine whether school/student, classroom/student, teacher/student ratio, and the Human Development Index (I.G.E.) rates by province predict a province's total 6th and 7th grade Elementary School Proficiency Exam (SBS) scores. To determine the relationships between the province's total 6th and 7th grade SBS…

How personal resources predict work engagement and self-rated performance among construction workers: a social cognitive perspective.

PubMed

Lorente, Laura; Salanova, Marisa; Martínez, Isabel M; Vera, María

2014-06-01

Traditionally, research focussing on psychosocial factors in the construction industry has focused mainly on the negative aspects of health and on results such as occupational accidents. This study, however, focuses on the specific relationships among the different positive psychosocial factors shared by construction workers that could be responsible for occupational well-being and outcomes such as performance. The main objective of this study was to test whether personal resources predict self-rated job performance through job resources and work engagement. Following the predictions of Bandura's Social Cognitive Theory and the motivational process of the Job Demands-Resources Model, we expect that the relationship between personal resources and performance will be fully mediated by job resources and work engagement. The sample consists of 228 construction workers. Structural equation modelling supports the research model. Personal resources (i.e. self-efficacy, mental and emotional competences) play a predicting role in the perception of job resources (i.e. job control and supervisor social support), which in turn leads to work engagement and self-rated performance. This study emphasises the crucial role that personal resources play in determining how people perceive job resources by determining the levels of work engagement and, hence, their self-rated job performance. Theoretical and practical implications are discussed. © 2014 International Union of Psychological Science.

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

PubMed

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

2016-01-01

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

Model parameter-related optimal perturbations and their contributions to El Niño prediction errors

NASA Astrophysics Data System (ADS)

Tao, Ling-Jiang; Gao, Chuan; Zhang, Rong-Hua

2018-04-01

Errors in initial conditions and model parameters (MPs) are the main sources that limit the accuracy of ENSO predictions. In addition to exploring the initial error-induced prediction errors, model errors are equally important in determining prediction performance. In this paper, the MP-related optimal errors that can cause prominent error growth in ENSO predictions are investigated using an intermediate coupled model (ICM) and a conditional nonlinear optimal perturbation (CNOP) approach. Two MPs related to the Bjerknes feedback are considered in the CNOP analysis: one involves the SST-surface wind coupling ({α _τ } ), and the other involves the thermocline effect on the SST ({α _{Te}} ). The MP-related optimal perturbations (denoted as CNOP-P) are found uniformly positive and restrained in a small region: the {α _τ } component is mainly concentrated in the central equatorial Pacific, and the {α _{Te}} component is mainly located in the eastern cold tongue region. This kind of CNOP-P enhances the strength of the Bjerknes feedback and induces an El Niño- or La Niña-like error evolution, resulting in an El Niño-like systematic bias in this model. The CNOP-P is also found to play a role in the spring predictability barrier (SPB) for ENSO predictions. Evidently, such error growth is primarily attributed to MP errors in small areas based on the localized distribution of CNOP-P. Further sensitivity experiments firmly indicate that ENSO simulations are sensitive to the representation of SST-surface wind coupling in the central Pacific and to the thermocline effect in the eastern Pacific in the ICM. These results provide guidance and theoretical support for the future improvement in numerical models to reduce the systematic bias and SPB phenomenon in ENSO predictions.

Stochastic or statistic? Comparing flow duration curve models in ungauged basins and changing climates

NASA Astrophysics Data System (ADS)

Müller, M. F.; Thompson, S. E.

2015-09-01

The prediction of flow duration curves (FDCs) in ungauged basins remains an important task for hydrologists given the practical relevance of FDCs for water management and infrastructure design. Predicting FDCs in ungauged basins typically requires spatial interpolation of statistical or model parameters. This task is complicated if climate becomes non-stationary, as the prediction challenge now also requires extrapolation through time. In this context, process-based models for FDCs that mechanistically link the streamflow distribution to climate and landscape factors may have an advantage over purely statistical methods to predict FDCs. This study compares a stochastic (process-based) and statistical method for FDC prediction in both stationary and non-stationary contexts, using Nepal as a case study. Under contemporary conditions, both models perform well in predicting FDCs, with Nash-Sutcliffe coefficients above 0.80 in 75 % of the tested catchments. The main drives of uncertainty differ between the models: parameter interpolation was the main source of error for the statistical model, while violations of the assumptions of the process-based model represented the main source of its error. The process-based approach performed better than the statistical approach in numerical simulations with non-stationary climate drivers. The predictions of the statistical method under non-stationary rainfall conditions were poor if (i) local runoff coefficients were not accurately determined from the gauge network, or (ii) streamflow variability was strongly affected by changes in rainfall. A Monte Carlo analysis shows that the streamflow regimes in catchments characterized by a strong wet-season runoff and a rapid, strongly non-linear hydrologic response are particularly sensitive to changes in rainfall statistics. In these cases, process-based prediction approaches are strongly favored over statistical models.

Comparing statistical and process-based flow duration curve models in ungauged basins and changing rain regimes

NASA Astrophysics Data System (ADS)

Müller, M. F.; Thompson, S. E.

2016-02-01

The prediction of flow duration curves (FDCs) in ungauged basins remains an important task for hydrologists given the practical relevance of FDCs for water management and infrastructure design. Predicting FDCs in ungauged basins typically requires spatial interpolation of statistical or model parameters. This task is complicated if climate becomes non-stationary, as the prediction challenge now also requires extrapolation through time. In this context, process-based models for FDCs that mechanistically link the streamflow distribution to climate and landscape factors may have an advantage over purely statistical methods to predict FDCs. This study compares a stochastic (process-based) and statistical method for FDC prediction in both stationary and non-stationary contexts, using Nepal as a case study. Under contemporary conditions, both models perform well in predicting FDCs, with Nash-Sutcliffe coefficients above 0.80 in 75 % of the tested catchments. The main drivers of uncertainty differ between the models: parameter interpolation was the main source of error for the statistical model, while violations of the assumptions of the process-based model represented the main source of its error. The process-based approach performed better than the statistical approach in numerical simulations with non-stationary climate drivers. The predictions of the statistical method under non-stationary rainfall conditions were poor if (i) local runoff coefficients were not accurately determined from the gauge network, or (ii) streamflow variability was strongly affected by changes in rainfall. A Monte Carlo analysis shows that the streamflow regimes in catchments characterized by frequent wet-season runoff and a rapid, strongly non-linear hydrologic response are particularly sensitive to changes in rainfall statistics. In these cases, process-based prediction approaches are favored over statistical models.

Protection from visible light by commonly used textiles is not predicted by ultraviolet protection.

PubMed

Van den Keybus, Caroline; Laperre, Jan; Roelandts, Rik

2006-01-01

Interest is increasing in the prevention of acute and chronic actinic damage provided by clothing. This interest has focused mainly on protection against ultraviolet irradiation, but it has now also turned to protection against visible light. This change is mainly due to the action spectrum in the visible light range of some photodermatoses and the increasing interest in photodynamic therapy. The ultraviolet protection provided by commercially available textiles can be graded by determining an ultraviolet protection factor. Several methods have already been used to determine the ultraviolet protection factor. The fact that protection from visible light by textiles cannot be predicted by their ultraviolet protection makes the situation more complicated. This study attempts to determine whether or not the ultraviolet protection factor value of a particular textile is a good parameter for gauging its protection in the visible light range and concludes that a protection factor of textile materials against visible light needs to be developed. This development should go beyond the protection factor definition used in this article, which has some limitations, and should take into account the exact action spectrum for which the protection is needed.

[Consumer's psychological processes of hoarding and avoidant purchasing after the Tohoku earthquake].

PubMed

Ohtomo, Shoji; Hirose, Yukio

2014-02-01

This study examined psychological processes of consumers that had determined hoarding and avoidant purchasing behaviors after the Tohoku earthquake within a dual-process model. The model hypothesized that both intentional motivation based on reflective decision and reactive motivation based on non-reflective decision predicted the behaviors. This study assumed that attitude, subjective norm and descriptive norm in relation to hoarding and avoidant purchasing were determinants of motivations. Residents in the Tokyo metropolitan area (n = 667) completed internet longitudinal surveys at three times (April, June, and November, 2011). The results indicated that intentional and reactive motivation determined avoidant purchasing behaviors in June; only intentional motivation determined the behaviors in November. Attitude was a main determinant of the motivations each time. Moreover, previous behaviors predicted future behaviors. In conclusion, purchasing behaviors were intentional rather than reactive behaviors. Furthermore, attitude and previous behaviors were important determinants in the dual-process model. Attitude and behaviors formed in April continued to strengthen the subsequent decisions of purchasing behavior.

Predictors of Errors of Novice Java Programmers

ERIC Educational Resources Information Center

Bringula, Rex P.; Manabat, Geecee Maybelline A.; Tolentino, Miguel Angelo A.; Torres, Edmon L.

2012-01-01

This descriptive study determined which of the sources of errors would predict the errors committed by novice Java programmers. Descriptive statistics revealed that the respondents perceived that they committed the identified eighteen errors infrequently. Thought error was perceived to be the main source of error during the laboratory programming…

Predictors of Depressive Symptoms among Foster Caregivers

ERIC Educational Resources Information Center

Cole, Susan A.; Eamon, Mary Keegan

2007-01-01

Objectives: The main purposes of this study were to determine (1) the prevalence of depressive symptoms among foster caregivers, (2) the social-demographics, risk factors, and social support predicting depressive symptoms, and (3) whether social support buffered the effects of the risk factors in the Illinois Foster Caregivers Study. Method:…

Predicting Entrepreneurial Motivation among University Students: The Role of Entrepreneurship Education

ERIC Educational Resources Information Center

Farhangmehr, Minoo; Gonçalves, Paulo; Sarmento, Maria

2016-01-01

Purpose: The purpose of this paper is to better understand the main drivers of entrepreneurial motivation among university students and to determine whether entrepreneurship education has a moderating effect on improving the impact of knowledge base and entrepreneurship competencies on entrepreneurial motivation. Design/methodology/approach: This…

Preparation for implementation of the mechanistic-empirical pavement design guide in Michigan : part 2 - evaluation of rehabilitation fixes (part 2).

DOT National Transportation Integrated Search

2013-08-01

The overall goal of Global Sensitivity Analysis (GSA) is to determine sensitivity of pavement performance prediction models to the variation in the design input values. The main difference between GSA and detailed sensitivity analyses is the way the ...

Determine Important Nuclear Fragmentation Processes for Space Radiation Protection in Human Space Explorations

NASA Technical Reports Server (NTRS)

Lin, Zi-wei

2004-01-01

Space radiation from cosmic ray particles is one of the main challenges for long-term human space explorations such as a permanent moon base or a trip to Mars. Material shielding may provide significant radiation protection to astronauts, and models have been developed in order to evaluate the effectiveness of different shielding materials and to predict radiation environment inside the spacecraft. In this study we determine the nuclear fragmentation cross sections which will most effect the radiation risk behind typical radiation shielding materials. These cross sections thus need more theoretical studies and accurate experimental measurements in order for us to more precisely predict the radiation risk in human space explorations.

Determine Important Nuclear Fragmentation Processes for Space Radiation Protection in Human Space Explorations

NASA Technical Reports Server (NTRS)

Lin, Zi-Wei

2004-01-01

Space radiation from cosmic ray particles is one of the main challenges for long-term human space explorations such as a permanent moon base or a trip to Mars. Material shielding may provide significant radiation protection to astronauts, and models have been developed in order to evaluate the effectiveness of different shielding materials and to predict radiation environment inside the spacecraft. In this study we determine the nuclear fragmentation cross sections which will most affect the radiation risk behind typical radiation shielding materials. These cross sections thus need more theoretical studies and accurate experimental measurements in order for us to more precisely predict the radiation risk in human space exploration.

Determine Important Nuclear Fragmentation Processes for Space Radiation Protection in Human Space Explorations

NASA Technical Reports Server (NTRS)

Lin, Zi-Wei

2004-01-01

Space radiation from cosmic ray particles is one of the main challenges for long-term human space explorations such as a permanent moon base or a trip to Mars. Material shielding may provide significant radiation protection to astronauts, and models have been developed in order to evaluate the effectiveness of different shielding materials and to predict radiation environment inside the spacecraft. In this study we determine the nuclear fragmentation cross sections which will most affect the radiation risk behind typical radiation shielding materials. These cross sections thus need more theoretical studies and accurate experimental measurements in order for us to more precisely predict the radiation risk in human space explorations.

Radial basis function neural networks applied to NASA SSME data

NASA Technical Reports Server (NTRS)

Wheeler, Kevin R.; Dhawan, Atam P.

1993-01-01

This paper presents a brief report on the application of Radial Basis Function Neural Networks (RBFNN) to the prediction of sensor values for fault detection and diagnosis of the Space Shuttle's Main Engines (SSME). The location of the Radial Basis Function (RBF) node centers was determined with a K-means clustering algorithm. A neighborhood operation about these center points was used to determine the variances of the individual processing notes.

Lithium in lower-main-sequence stars of the Alpha Persei cluster

NASA Technical Reports Server (NTRS)

Balachandran, Suchitra; Lambert, David L.; Stauffer, John R.

1988-01-01

Lithium abundances are presented for main-sequence stars of spectral types F, G, and K in the young open cluster Alpha Per. For 46 cluster members, a correlation between Li abundance and projected rotational velocity v sin i is found: all of the Li-poor stars are slow rotators. Two explanations are proposed to account for the correlation: (1) that the Li depletion is introduced following a rapid spin-down phase experienced by young low-mass stars, and that this episode of Li depletion may be the dominant one determining the spread of Li abundances among young low-mass main-sequence stars, and (2) that star formation has occurred over a finite period such that the older stars have undergone a spin-down and depletion of Li by a means that may or may not depend on rotation. The Li abundance in the warm and rapidly rotating stars appears to be undepleted, as is predicted by recent models of pre-main-sequence stars. The depletion observed in the cool stars exceeds the level predicted by these models.

Integrating urban recharge uncertainty into standard groundwater modeling practice: A case study on water main break predictions for the Barton Springs segment of the Edwards Aquifer, Austin, Texas

NASA Astrophysics Data System (ADS)

Sinner, K.; Teasley, R. L.

2016-12-01

Groundwater models serve as integral tools for understanding flow processes and informing stakeholders and policy makers in management decisions. Historically, these models tended towards a deterministic nature, relying on historical data to predict and inform future decisions based on model outputs. This research works towards developing a stochastic method of modeling recharge inputs from pipe main break predictions in an existing groundwater model, which subsequently generates desired outputs incorporating future uncertainty rather than deterministic data. The case study for this research is the Barton Springs segment of the Edwards Aquifer near Austin, Texas. Researchers and water resource professionals have modeled the Edwards Aquifer for decades due to its high water quality, fragile ecosystem, and stakeholder interest. The original case study and model that this research is built upon was developed as a co-design problem with regional stakeholders and the model outcomes are generated specifically for communication with policy makers and managers. Recently, research in the Barton Springs segment demonstrated a significant contribution of urban, or anthropogenic, recharge to the aquifer, particularly during dry period, using deterministic data sets. Due to social and ecological importance of urban water loss to recharge, this study develops an evaluation method to help predicted pipe breaks and their related recharge contribution within the Barton Springs segment of the Edwards Aquifer. To benefit groundwater management decision processes, the performance measures captured in the model results, such as springflow, head levels, storage, and others, were determined by previous work in elicitation of problem framing to determine stakeholder interests and concerns. The results of the previous deterministic model and the stochastic model are compared to determine gains to stakeholder knowledge through the additional modeling

Main predictors of periphyton species richness depend on adherence strategy and cell size

PubMed Central

Siqueira, Tadeu; Landeiro, Victor Lemes; Rodrigues, Liliana; Bonecker, Claudia Costa; Rodrigues, Luzia Cleide; Santana, Natália Fernanda; Thomaz, Sidinei Magela; Bini, Luis Mauricio

2017-01-01

Periphytic algae are important components of aquatic ecosystems. However, the factors driving periphyton species richness variation remain largely unexplored. Here, we used data from a subtropical floodplain (Upper Paraná River floodplain, Brazil) to quantify the influence of environmental variables (total suspended matter, temperature, conductivity, nutrient concentrations, hydrology, phytoplankton biomass, phytoplankton species richness, aquatic macrophyte species richness and zooplankton density) on overall periphytic algal species richness and on the richness of different algal groups defined by morphological traits (cell size and adherence strategy). We expected that the coefficients of determination of the models estimated for different trait-based groups would be higher than the model coefficient of determination of the entire algal community. We also expected that the relative importance of explanatory variables in predicting species richness would differ among algal groups. The coefficient of determination for the model used to predict overall periphytic algal species richness was higher than the ones obtained for models used to predict the species richness of the different groups. Thus, our first prediction was not supported. Species richness of aquatic macrophytes was the main predictor of periphyton species richness of the entire community and a significant predictor of the species richness of small mobile, large mobile and small-loosely attached algae. Abiotic variables, phytoplankton species richness, chlorophyll-a concentration, and hydrology were also significant predictors, depending on the group. These results suggest that habitat heterogeneity (as proxied by aquatic macrophytes richness) is important for maintaining periphyton species richness in floodplain environments. However, other factors played a role, suggesting that the analysis of species richness of different trait-based groups unveils relationships that were not detectable when the entire community was analysed together. PMID:28742122

Predicting the occurrence of wildfires with binary structured additive regression models.

PubMed

Ríos-Pena, Laura; Kneib, Thomas; Cadarso-Suárez, Carmen; Marey-Pérez, Manuel

2017-02-01

Wildfires are one of the main environmental problems facing societies today, and in the case of Galicia (north-west Spain), they are the main cause of forest destruction. This paper used binary structured additive regression (STAR) for modelling the occurrence of wildfires in Galicia. Binary STAR models are a recent contribution to the classical logistic regression and binary generalized additive models. Their main advantage lies in their flexibility for modelling non-linear effects, while simultaneously incorporating spatial and temporal variables directly, thereby making it possible to reveal possible relationships among the variables considered. The results showed that the occurrence of wildfires depends on many covariates which display variable behaviour across space and time, and which largely determine the likelihood of ignition of a fire. The joint possibility of working on spatial scales with a resolution of 1 × 1 km cells and mapping predictions in a colour range makes STAR models a useful tool for plotting and predicting wildfire occurrence. Lastly, it will facilitate the development of fire behaviour models, which can be invaluable when it comes to drawing up fire-prevention and firefighting plans. Copyright © 2016 Elsevier Ltd. All rights reserved.

Feasibility in multispectral imaging for predicting the content of bioactive compounds in intact tomato fruit.

PubMed

Liu, Changhong; Liu, Wei; Chen, Wei; Yang, Jianbo; Zheng, Lei

2015-04-15

Tomato is an important health-stimulating fruit because of the antioxidant properties of its main bioactive compounds, dominantly lycopene and phenolic compounds. Nowadays, product differentiation in the fruit market requires an accurate evaluation of these value-added compounds. An experiment was conducted to simultaneously and non-destructively measure lycopene and phenolic compounds content in intact tomatoes using multispectral imaging combined with chemometric methods. Partial least squares (PLS), least squares-support vector machines (LS-SVM) and back propagation neural network (BPNN) were applied to develop quantitative models. Compared with PLS and LS-SVM, BPNN model considerably improved the performance with coefficient of determination in prediction (RP(2))=0.938 and 0.965, residual predictive deviation (RPD)=4.590 and 9.335 for lycopene and total phenolics content prediction, respectively. It is concluded that multispectral imaging is an attractive alternative to the standard methods for determination of bioactive compounds content in intact tomatoes, providing a useful platform for infield fruit sorting/grading. Copyright © 2014 Elsevier Ltd. All rights reserved.

Advanced Methods for Determining Prediction Uncertainty in Model-Based Prognostics with Application to Planetary Rovers

NASA Technical Reports Server (NTRS)

Daigle, Matthew J.; Sankararaman, Shankar

2013-01-01

Prognostics is centered on predicting the time of and time until adverse events in components, subsystems, and systems. It typically involves both a state estimation phase, in which the current health state of a system is identified, and a prediction phase, in which the state is projected forward in time. Since prognostics is mainly a prediction problem, prognostic approaches cannot avoid uncertainty, which arises due to several sources. Prognostics algorithms must both characterize this uncertainty and incorporate it into the predictions so that informed decisions can be made about the system. In this paper, we describe three methods to solve these problems, including Monte Carlo-, unscented transform-, and first-order reliability-based methods. Using a planetary rover as a case study, we demonstrate and compare the different methods in simulation for battery end-of-discharge prediction.

[A site index model for Larix principis-rupprechtii plantation in Saihanba, north China].

PubMed

Wang, Dong-zhi; Zhang, Dong-yan; Jiang, Feng-ling; Bai, Ye; Zhang, Zhi-dong; Huang, Xuan-rui

2015-11-01

It is often difficult to estimate site indices for different types of plantation by using an ordinary site index model. The objective of this paper was to establish a site index model for plantations in varied site conditions, and assess the site qualities. In this study, a nonlinear mixed site index model was constructed based on data from the second class forest resources inventory and 173 temporary sample plots. The results showed that the main limiting factors for height growth of Larix principis-rupprechtii were elevation, slope, soil thickness and soil type. A linear regression model was constructed for the main constraining site factors and dominant tree height, with the coefficient of determination being 0.912, and the baseline age of Larix principis-rupprechtii determined as 20 years. The nonlinear mixed site index model parameters for the main site types were estimated (R2 > 0.85, the error between the predicted value and the actual value was in the range of -0.43 to 0.45, with an average root mean squared error (RMSE) in the range of 0.907 to 1.148). The estimation error between the predicted value and the actual value of dominant tree height for the main site types was in the confidence interval of [-0.95, 0.95]. The site quality of the high altitude-shady-sandy loam-medium soil layer was the highest and that of low altitude-sunny-sandy loam-medium soil layer was the lowest, while the other two sites were moderate.

Prediction of Temperatures of Austenite Equilibrium Transformations in Steels During Thermomechanical Processing

NASA Astrophysics Data System (ADS)

Samadian, Pedram; Parsa, Mohammad Habibi; Ahmadabadi, M. Nili; Mirzadeh, Hamed

2014-10-01

Knowledge about the transformation temperatures is crucial in processing of steels especially in thermomechanical processes because microstructures and mechanical properties after processing are closely related to the extent and type of transformations. The experimental determination of critical temperatures is costly, and therefore, it is preferred to predict them by mathematical methods. In the current work, new thermodynamically based models were developed for computing the Ae3 and Acm temperatures in the equilibrium cooling conditions when austenite is deformed at elevated temperatures. The main advantage of the proposed models is their capability to predict the temperatures of austenite equilibrium transformations in steels with total alloying elements (Mn + Si + Ni + Cr + Mo + Cu) less than 5 wt.% and Si less than 1 wt.% under the deformation conditions just by using the chemical potential of constituents, without the need for determining the total Gibbs free energy of steel which requires many experiments and computations.

Stress in nurses: stress-related affect and its determinants examined over the nursing day.

PubMed

Johnston, Derek W; Jones, Martyn C; Charles, Kathryn; McCann, Sharon K; McKee, Lorna

2013-06-01

Nurses are a stressed group and this may affect their health and work performance. The determinants of occupational stress in nurses and other occupational groups have almost invariably been examined in between subject studies. This study aimed to determine if the main determinants of occupation stress, i.e. demand, control, effort and reward, operate within nurses. A real time study using personal digital-assistant-based ecological momentary assessment to measure affect and its hypothesised determinants every 90 min in 254 nurses over three nursing shifts. The measures were negative affect, positive affect, demand/effort, control and reward. While the effects varied in magnitude between people, in general increased negative affect was predicted by high demand/effort, low control and low reward. Control and reward moderated the effects of demand/effort. High positive affect was predicted by high demand/effort, control and reward. The same factors are associated with variations in stress-related affect within nurses as between.

Branded by a Test

ERIC Educational Resources Information Center

Popham, W. James

2006-01-01

Scholastic Aptitude Test (SAT) and American College Program (ACT) scores are the main determinants of college entrance in the USA. It is widely assumed that these tests are predictive of success both during college and in later life, but such views are incorrect. Another widely-held view, held by many educators, is that the SAT and ACT are…

Preparation for implementation of the mechanistic-empirical pavement design guide in Michigan : part 2 - evaluation of rehabilitation fixes (part 1).

DOT National Transportation Integrated Search

2013-08-01

The main objectives of Task 2 of the project were to determine the impact of various input variables on the predicted pavement performance for the selected rehabilitation design alternatives in the MEPDG/DARWin-ME, and to verify the pavement performa...

Concentration determination of collagen and proteoglycan in bovine nasal cartilage by Fourier transform infrared imaging and PLS

NASA Astrophysics Data System (ADS)

Zhang, Xuexi; Xiao, Zhi-Yan; Yin, Jianhua; Xia, Yang

2014-09-01

Fourier transform infrared imaging (FTIRI) combined with chemometrics can be used to detect the structure of bio-macromolecule, measure the concentrations of some components, and so on. In this study, FTIRI with Partial Least-Squares (PLS) regression was applied to study the concentration of two main components in bovine nasal cartilage (BNC), collagen and proteoglycan. An infrared spectrum library was built by mixing the collagen and chondroitin 6-sulfate (main of proteoglycan) at different ratios. Some pretreatments are needed for building PLS model. FTIR images were collected from BNC sections at 6.25μm and 25μm pixel size. The spectra extracted from BNC-FTIR images were imported into the PLS regression program to predict the concentrations of collagen and proteoglycan. These PLS-determined concentrations are agreed with the result in our previous work and biochemical analytical results. The prediction shows that the concentrations of collagen and proteoglycan in BNC are comparative on the whole. However, the concentration of proteoglycan is a litter higher than that of collagen, to some extent.

Location of food stores near schools does not predict the weight status of Maine high school students.

PubMed

Harris, David E; Blum, Janet Whatley; Bampton, Matthew; O'Brien, Liam M; Beaudoin, Christina M; Polacsek, Michele; O'Rourke, Karen A

2011-01-01

To examine the relationship between stores selling calorie-dense food near schools and student obesity risk, with the hypothesis that high availability predicts increased risk. Mail surveys determined height, weight, and calorie-dense food consumption for 552 students at 11 Maine high schools. Driving distance from all food stores within 2 km (1.24 miles) of schools (or the closest store) was computed, and the impact of food store density and proximity to schools on student body mass index was determined by logistic regression. Ten schools had ≥ 1 store selling soda, and 8 schools had ≥1 fast-food restaurant within 1 km (0.62 miles). There were no significant relationships between the proximity or density of food stores around schools and student obesity risk. Students obtained sugar-sweetened beverages in many locations including at school. Unhealthful food choices are ubiquitous. Consequently, stores selling these food items near schools have no significant affect on student obesity. Copyright © 2011 Society for Nutrition Education. Published by Elsevier Inc. All rights reserved.

Determination of coefficient defining leaf area development in different genotypes, plant types and planting densities in peanut (Arachis hypogeae L.).

PubMed

Halilou, Oumarou; Hissene, Halime Mahamat; Clavijo Michelangeli, José A; Hamidou, Falalou; Sinclair, Thomas R; Soltani, Afshin; Mahamane, Saadou; Vadez, Vincent

2016-12-01

Rapid leaf area development may be attractive under a number of cropping conditions to enhance the vigor of crop establishment and allow rapid canopy closure for maximizing light interception and shading of weed competitors. This study was undertaken to determine (1) if parameters describing leaf area development varied among ten peanut ( Arachis hypogeae L.) genotypes grown in field and pot experiments, (2) if these parameters were affected by the planting density, and (3) if these parameters varied between Spanish and Virginia genotypes. Leaf area development was described by two steps: prediction of main stem number of nodes based on phyllochron development and plant leaf area dependent based on main stem node number. There was no genetic variation in the phyllochron measured in the field. However, the phyllochron was much longer for plants grown in pots as compared to the field-grown plants. These results indicated a negative aspect of growing peanut plants in the pots used in this experiment. In contrast to phyllochron, there was no difference in the relationship between plant leaf area and main stem node number between the pot and field experiments. However, there was genetic variation in both the pot and field experiments in the exponential coefficient (PLAPOW) of the power function used to describe leaf area development from node number. This genetic variation was confirmed in another experiment with a larger number of genotypes, although possible G × E interaction for the PLAPOW was found. Sowing density did not affect the power function relating leaf area to main stem node number. There was also no difference in the power function coefficient between Spanish and Virginia genotypes. SSM (Simple Simulation model) reliably predicted leaf canopy development in groundnut. Indeed the leaf area showed a close agreement between predicted and observed values up to 60000 cm 2  m -2 . The slightly higher prediction in India and slightly lower prediction in Niger reflected GxE interactions. Until more understanding is obtained on the possible GxE interaction effects on the canopy development, a generic PLAPOW value of 2.71, no correction for sowing density, and a phyllochron on 53 °C could be used to model canopy development in peanut.

Nuclear Fragmentation Processes Relevant for Human Space Radiation Protection

NASA Technical Reports Server (NTRS)

Lin, Zi-Wei

2007-01-01

Space radiation from cosmic ray particles is one of the main challenges for human space explorations such-as a moon base or a trip to Mars. Models have been developed in order to predict the radiation exposure to astronauts and to evaluate the effectiveness of different shielding materials, and a key ingredient in these models is the physics of nuclear fragmentations. We have developed a semi-analytical method to determine which partial cross sections of nuclear fragmentations most affect the radiation dose behind shielding materials due to exposure to galactic cosmic rays. The cross sections thus determined will require more theoretical and/or experimental studies in order for us to better predict, reduce and mitigate the radiation exposure in human space explorations.

Early Recurrence After Hepatectomy for Colorectal Liver Metastases: What Optimal Definition and What Predictive Factors?

PubMed Central

Imai, Katsunori; Allard, Marc-Antoine; Benitez, Carlos Castro; Vibert, Eric; Sa Cunha, Antonio; Cherqui, Daniel; Castaing, Denis; Bismuth, Henri; Baba, Hideo

2016-01-01

Background. The purpose of this study was to determine the optimal definition and elucidate the predictive factors of early recurrence after surgery for colorectal liver metastases (CRLM). Methods. Among 987 patients who underwent curative surgery for CRLM from 1990 to 2012, 846 with a minimum follow-up period of 24 months were eligible for this study. The minimum p value approach of survival after initial recurrence was used to determine the optimal cutoff for the definition of early recurrence. The predictive factors of early recurrence and prognostic factors of survival were analyzed. Results. For 667 patients (79%) who developed recurrence, the optimal cutoff point of early recurrence was determined to be 8 months after surgery. The impact of early recurrence on survival was demonstrated mainly in patients who received preoperative chemotherapy. Among the 691 patients who received preoperative chemotherapy, recurrence was observed in 562 (81%), and survival in patients with early recurrence was significantly worse than in those with late recurrence (5-year survival 18.5% vs. 53.4%, p < .0001). Multivariate logistic analysis identified age ≤57 years (p = .0022), >1 chemotherapy line (p = .03), disease progression during last-line chemotherapy (p = .024), >3 tumors (p = .0014), and carbohydrate antigen 19-9 >60 U/mL (p = .0003) as independent predictors of early recurrence. Salvage surgery for recurrence significantly improved survival, even in patients with early recurrence. Conclusion. The optimal cutoff point of early recurrence was determined to be 8 months. The preoperative prediction of early recurrence is possible and crucial for designing effective perioperative chemotherapy regimens. Implications for Practice: In this study, the optimal cutoff point of early recurrence was determined to be 8 months after surgery based on the minimum p value approach, and its prognostic impact was demonstrated mainly in patients who received preoperative chemotherapy. Five factors, including age, number of preoperative chemotherapy lines, response to last-line chemotherapy, number of tumors, and carbohydrate antigen 19-9 concentrations, were identified as predictors of early recurrence. Salvage surgery for recurrence significantly improved survival, even in patients with early recurrence. For better selection of patients who could truly benefit from surgery and should also receive strong postoperative chemotherapy, the accurate preoperative prediction of early recurrence is crucial. PMID:27125753

Soft Computing Methods for Disulfide Connectivity Prediction.

PubMed

Márquez-Chamorro, Alfonso E; Aguilar-Ruiz, Jesús S

2015-01-01

The problem of protein structure prediction (PSP) is one of the main challenges in structural bioinformatics. To tackle this problem, PSP can be divided into several subproblems. One of these subproblems is the prediction of disulfide bonds. The disulfide connectivity prediction problem consists in identifying which nonadjacent cysteines would be cross-linked from all possible candidates. Determining the disulfide bond connectivity between the cysteines of a protein is desirable as a previous step of the 3D PSP, as the protein conformational search space is highly reduced. The most representative soft computing approaches for the disulfide bonds connectivity prediction problem of the last decade are summarized in this paper. Certain aspects, such as the different methodologies based on soft computing approaches (artificial neural network or support vector machine) or features of the algorithms, are used for the classification of these methods.

Development, Validation and Deployment of a Real Time 30 Day Hospital Readmission Risk Assessment Tool in the Maine Healthcare Information Exchange.

PubMed

Hao, Shiying; Wang, Yue; Jin, Bo; Shin, Andrew Young; Zhu, Chunqing; Huang, Min; Zheng, Le; Luo, Jin; Hu, Zhongkai; Fu, Changlin; Dai, Dorothy; Wang, Yicheng; Culver, Devore S; Alfreds, Shaun T; Rogow, Todd; Stearns, Frank; Sylvester, Karl G; Widen, Eric; Ling, Xuefeng B

2015-01-01

Identifying patients at risk of a 30-day readmission can help providers design interventions, and provide targeted care to improve clinical effectiveness. This study developed a risk model to predict a 30-day inpatient hospital readmission for patients in Maine, across all payers, all diseases and all demographic groups. Our objective was to develop a model to determine the risk for inpatient hospital readmission within 30 days post discharge. All patients within the Maine Health Information Exchange (HIE) system were included. The model was retrospectively developed on inpatient encounters between January 1, 2012 to December 31, 2012 from 24 randomly chosen hospitals, and then prospectively validated on inpatient encounters from January 1, 2013 to December 31, 2013 using all HIE patients. A risk assessment tool partitioned the entire HIE population into subgroups that corresponded to probability of hospital readmission as determined by a corresponding positive predictive value (PPV). An overall model c-statistic of 0.72 was achieved. The total 30-day readmission rates in low (score of 0-30), intermediate (score of 30-70) and high (score of 70-100) risk groupings were 8.67%, 24.10% and 74.10%, respectively. A time to event analysis revealed the higher risk groups readmitted to a hospital earlier than the lower risk groups. Six high-risk patient subgroup patterns were revealed through unsupervised clustering. Our model was successfully integrated into the statewide HIE to identify patient readmission risk upon admission and daily during hospitalization or for 30 days subsequently, providing daily risk score updates. The risk model was validated as an effective tool for predicting 30-day readmissions for patients across all payer, disease and demographic groups within the Maine HIE. Exposing the key clinical, demographic and utilization profiles driving each patient's risk of readmission score may be useful to providers in developing individualized post discharge care plans.

Modeling the milling tool wear by using an evolutionary SVM-based model from milling runs experimental data

NASA Astrophysics Data System (ADS)

Nieto, Paulino José García; García-Gonzalo, Esperanza; Vilán, José Antonio Vilán; Robleda, Abraham Segade

2015-12-01

The main aim of this research work is to build a new practical hybrid regression model to predict the milling tool wear in a regular cut as well as entry cut and exit cut of a milling tool. The model was based on Particle Swarm Optimization (PSO) in combination with support vector machines (SVMs). This optimization mechanism involved kernel parameter setting in the SVM training procedure, which significantly influences the regression accuracy. Bearing this in mind, a PSO-SVM-based model, which is based on the statistical learning theory, was successfully used here to predict the milling tool flank wear (output variable) as a function of the following input variables: the time duration of experiment, depth of cut, feed, type of material, etc. To accomplish the objective of this study, the experimental dataset represents experiments from runs on a milling machine under various operating conditions. In this way, data sampled by three different types of sensors (acoustic emission sensor, vibration sensor and current sensor) were acquired at several positions. A second aim is to determine the factors with the greatest bearing on the milling tool flank wear with a view to proposing milling machine's improvements. Firstly, this hybrid PSO-SVM-based regression model captures the main perception of statistical learning theory in order to obtain a good prediction of the dependence among the flank wear (output variable) and input variables (time, depth of cut, feed, etc.). Indeed, regression with optimal hyperparameters was performed and a determination coefficient of 0.95 was obtained. The agreement of this model with experimental data confirmed its good performance. Secondly, the main advantages of this PSO-SVM-based model are its capacity to produce a simple, easy-to-interpret model, its ability to estimate the contributions of the input variables, and its computational efficiency. Finally, the main conclusions of this study are exposed.

Myth and Reality: A Response to Lynn on the Determinants of Italy's North-South Imbalances

ERIC Educational Resources Information Center

Felice, Emanuele; Giugliano, Ferdinando

2011-01-01

In his article "In Italy, North-South differences in IQ predict differences in income, education, infant mortality, stature, and literacy," Richard Lynn claims to have found the reason causing the divergence between the Northern and the Southern regions of Italy. This article identifies the four main hypotheses formulated in his paper…

Prediction of ultrasonic properties from grain angle

Treesearch

M.F. Kabir

2001-01-01

The ultrasonic properties of rubber wood were evaluated in three main symmetry axes – longitudinal (L), radial (R) and tangential direction and also at an angle rotating from the symmetry axes at different moisture content. The ultrasonic velocity were determined with a commercial ultrasonic tester of 45 kHz pulsed longitudinal waves. The experimental results were...

Building Academic Quality in Distance Higher Education. A Monograph in Higher Education Evaluation and Policy.

ERIC Educational Resources Information Center

Chacon-Duque, Fabio J.

The factors that determine course completion and achievement in college distance education were investigated using a sample of 25 courses offered through the Independent Learning Program at the Pennsylvania State University. The main objective was to develop a multivariate model to explain and predict outcomes of distance education. Additional…

Relationships of the Dimensions of Intercultural Communication Competence.

ERIC Educational Resources Information Center

Chen, Guo-Ming

To determine which measures best predict the seven dimensions of the Intercultural Behavioral Assessment Indices, a study examined 149 international students (mainly from the Far East, Asia, Middle East, Africa, and Europe) at a large midwestern university in the spring of 1986. Average age was 27.5 years, and average length of stay in the United…

Modeling and experimental assessment of a buried Leu–Ile mutation in dengue envelope domain III

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

Kulkarni, Manjiri R.; Numoto, Nobutaka; Ito, Nobutoshi

Envelope protein domain III (ED3) of the dengue virus is important for both antibody binding and host cell interaction. Here, we focused on how a L387I mutation in the protein core could take place in DEN4 ED3, but cannot be accommodated in DEN3 ED3 without destabilizing its structure. To this end, we modeled a DEN4-L387I structure using the Penultimate Rotamer Library and taking the DEN4 ED3 main-chain as a fixed template. We found that three out of seven Ile{sup 387} conformers fit in DEN4 ED3 without introducing the severe atomic clashes that are observed when DEN3 serotype’s ED3 is usedmore » as a template. A more extensive search using 273 side-chain rotamers of the residues surrounding Ile{sup 387} confirmed this prediction. In order to assess the prediction, we determined the crystal structure of DEN4-L387I at 2 Å resolution. Ile{sup 387} indeed adopted one of the three predicted rotamers. Altogether, this study demonstrates that the effects of single mutations are to a large extent successfully predicted by systematically modeling the side-chain structures of the mutated as well as those of its surrounding residues using fixed main-chain structures and assessing inter-atomic steric clashes. More accurate and reliable predictions require considering sub-angstrom main-chain deformation, which remains a challenging task. - Highlights: • We mutated L387I of DEN4 ED3 and examined its effects on structure and stability. • We modeled the side-chain of Ile{sup 387} using DEN4 ED3's structure as a template. • We determined the crystal structure of DEN4-L387I and confirmed the modeling. • Side-chain repacking occurring around Ile{sup 387} involved >3 inter-connected residues. • These results explained why L387I mutation in DEN4 ED3 conserves thermostability.« less

Prediction of Incident Hypertension Within the Next Year: Prospective Study Using Statewide Electronic Health Records and Machine Learning

PubMed Central

Zhang, Yan; Wang, Oliver; Jin, Bo; Xia, Minjie; Liu, Modi; Zhou, Xin; Wu, Qian; Guo, Yanting; Zhu, Chunqing; Li, Yu-Ming; Culver, Devore S; Alfreds, Shaun T; Stearns, Frank; Sylvester, Karl G; Widen, Eric

2018-01-01

Background As a high-prevalence health condition, hypertension is clinically costly, difficult to manage, and often leads to severe and life-threatening diseases such as cardiovascular disease (CVD) and stroke. Objective The aim of this study was to develop and validate prospectively a risk prediction model of incident essential hypertension within the following year. Methods Data from individual patient electronic health records (EHRs) were extracted from the Maine Health Information Exchange network. Retrospective (N=823,627, calendar year 2013) and prospective (N=680,810, calendar year 2014) cohorts were formed. A machine learning algorithm, XGBoost, was adopted in the process of feature selection and model building. It generated an ensemble of classification trees and assigned a final predictive risk score to each individual. Results The 1-year incident hypertension risk model attained areas under the curve (AUCs) of 0.917 and 0.870 in the retrospective and prospective cohorts, respectively. Risk scores were calculated and stratified into five risk categories, with 4526 out of 381,544 patients (1.19%) in the lowest risk category (score 0-0.05) and 21,050 out of 41,329 patients (50.93%) in the highest risk category (score 0.4-1) receiving a diagnosis of incident hypertension in the following 1 year. Type 2 diabetes, lipid disorders, CVDs, mental illness, clinical utilization indicators, and socioeconomic determinants were recognized as driving or associated features of incident essential hypertension. The very high risk population mainly comprised elderly (age>50 years) individuals with multiple chronic conditions, especially those receiving medications for mental disorders. Disparities were also found in social determinants, including some community-level factors associated with higher risk and others that were protective against hypertension. Conclusions With statewide EHR datasets, our study prospectively validated an accurate 1-year risk prediction model for incident essential hypertension. Our real-time predictive analytic model has been deployed in the state of Maine, providing implications in interventions for hypertension and related diseases and hopefully enhancing hypertension care. PMID:29382633

Risk of fire occurrence in arid and semi-arid ecosystems of Iran: an investigation using Bayesian belief networks.

PubMed

Bashari, Hossein; Naghipour, Ali Asghar; Khajeddin, Seyed Jamaleddin; Sangoony, Hamed; Tahmasebi, Pejman

2016-09-01

Identifying areas that have a high risk of burning is a main component of fire management planning. Although the available tools can predict the fire risks, these are poor in accommodating uncertainties in their predictions. In this study, we accommodated uncertainty in wildfire prediction using Bayesian belief networks (BBNs). An influence diagram was developed to identify the factors influencing wildfire in arid and semi-arid areas of Iran, and it was populated with probabilities to produce a BBNs model. The behavior of the model was tested using scenario and sensitivity analysis. Land cover/use, mean annual rainfall, mean annual temperature, elevation, and livestock density were recognized as the main variables determining wildfire occurrence. The produced model had good accuracy as its ROC area under the curve was 0.986. The model could be applied in both predictive and diagnostic analysis for answering "what if" and "how" questions. The probabilistic relationships within the model can be updated over time using observation and monitoring data. The wildfire BBN model may be updated as new knowledge emerges; hence, it can be used to support the process of adaptive management.

Accounting for occurrences: an explanation for some novel tendencies in causal judgment from contingency information.

PubMed

White, Peter A

2009-06-01

Contingency information is information about empirical associations between possible causes and outcomes. In the present research, it is shown that, under some circumstances, there is a tendency for negative contingencies to lead to positive causal judgments and for positive contingencies to lead to negative causal judgments. If there is a high proportion of instances in which a candidate cause (CC) being judged is present, these tendencies are predicted by weighted averaging models of causal judgment. If the proportion of such instances is low, the predictions of weighted averaging models break down. It is argued that one of the main aims of causal judgment is to account for occurrences of the outcome. Thus, a CC is not given a high causal judgment if there are few or no occurrences of it, regardless of the objective contingency. This argument predicts that, if there is a low proportion of instances in which a CC is present, causal judgments are determined mainly by the number of Cell A instances (i.e., CC present, outcome occurs), and that this explains why weighted averaging models fail to predict judgmental tendencies under these circumstances. Experimental results support this argument.

Expanding a dynamic flux balance model of yeast fermentation to genome-scale

PubMed Central

2011-01-01

Background Yeast is considered to be a workhorse of the biotechnology industry for the production of many value-added chemicals, alcoholic beverages and biofuels. Optimization of the fermentation is a challenging task that greatly benefits from dynamic models able to accurately describe and predict the fermentation profile and resulting products under different genetic and environmental conditions. In this article, we developed and validated a genome-scale dynamic flux balance model, using experimentally determined kinetic constraints. Results Appropriate equations for maintenance, biomass composition, anaerobic metabolism and nutrient uptake are key to improve model performance, especially for predicting glycerol and ethanol synthesis. Prediction profiles of synthesis and consumption of the main metabolites involved in alcoholic fermentation closely agreed with experimental data obtained from numerous lab and industrial fermentations under different environmental conditions. Finally, fermentation simulations of genetically engineered yeasts closely reproduced previously reported experimental results regarding final concentrations of the main fermentation products such as ethanol and glycerol. Conclusion A useful tool to describe, understand and predict metabolite production in batch yeast cultures was developed. The resulting model, if used wisely, could help to search for new metabolic engineering strategies to manage ethanol content in batch fermentations. PMID:21595919

Prediction of stellar occultations by distant solar system bodies in the Gaia era

NASA Astrophysics Data System (ADS)

Desmars, Josselin; Camargo, Julio; Sicardy, Bruno; Braga-Ribas, Felipe; Vieira-Martins, Roberto; Assafin, Marcelo; Bérard, Diane; Benedetti-Rossi, Gustavo

2018-04-01

Stellar occultations are a unique technique to access physical characteristics of distant solar system objects from the ground. They allow the measure of the size and the shape at kilometric level, the detection of tenuous atmospheres (few nanobars), and the investigation of close vicinity (satellites, rings) of Transneptunian objects and Centaurs. This technique is made successful thanks to accurate predictions of occultations. Accuracy of the predictions depends on the uncertainty in the position of the occulted star and the object's orbit. The Gaia stellar catalogue (Gaia Collaboration (2017)) now allows to get accurate astrometric stellar positions (to the mas level). The main uncertainty remains on the orbit. In this context, we now take advantage of the NIMA method (Desmars et al.(2015)) for the orbit determination and of the Gaia DR1 catalogue for the astrometry. In this document, we show how the orbit determination is improved by reducing current and some past observations with Gaia DR1. Moreover, we also use more than 45 past positive occultations observed in the 2009-2017 period to derive very accurate astrometric positions only depending on the position of the occulted stars (about few mas with Gaia DR1). We use the case of (10199) Chariklo as an illustration. The main limitation lies in the imprecision of the proper motions which is going to be solved by the Gaia DR2 release.

Evaluation of SSME test data reduction methods

NASA Technical Reports Server (NTRS)

Santi, L. Michael

1994-01-01

Accurate prediction of hardware and flow characteristics within the Space Shuttle Main Engine (SSME) during transient and main-stage operation requires a significant integration of ground test data, flight experience, and computational models. The process of integrating SSME test measurements with physical model predictions is commonly referred to as data reduction. Uncertainties within both test measurements and simplified models of the SSME flow environment compound the data integration problem. The first objective of this effort was to establish an acceptability criterion for data reduction solutions. The second objective of this effort was to investigate the data reduction potential of the ROCETS (Rocket Engine Transient Simulation) simulation platform. A simplified ROCETS model of the SSME was obtained from the MSFC Performance Analysis Branch . This model was examined and tested for physical consistency. Two modules were constructed and added to the ROCETS library to independently check the mass and energy balances of selected engine subsystems including the low pressure fuel turbopump, the high pressure fuel turbopump, the low pressure oxidizer turbopump, the high pressure oxidizer turbopump, the fuel preburner, the oxidizer preburner, the main combustion chamber coolant circuit, and the nozzle coolant circuit. A sensitivity study was then conducted to determine the individual influences of forty-two hardware characteristics on fourteen high pressure region prediction variables as returned by the SSME ROCETS model.

Prediction of Sliding Friction Coefficient Based on a Novel Hybrid Molecular-Mechanical Model.

PubMed

Zhang, Xiaogang; Zhang, Yali; Wang, Jianmei; Sheng, Chenxing; Li, Zhixiong

2018-08-01

Sliding friction is a complex phenomenon which arises from the mechanical and molecular interactions of asperities when examined in a microscale. To reveal and further understand the effects of micro scaled mechanical and molecular components of friction coefficient on overall frictional behavior, a hybrid molecular-mechanical model is developed to investigate the effects of main factors, including different loads and surface roughness values, on the sliding friction coefficient in a boundary lubrication condition. Numerical modelling was conducted using a deterministic contact model and based on the molecular-mechanical theory of friction. In the contact model, with given external loads and surface topographies, the pressure distribution, real contact area, and elastic/plastic deformation of each single asperity contact were calculated. Then asperity friction coefficient was predicted by the sum of mechanical and molecular components of friction coefficient. The mechanical component was mainly determined by the contact width and elastic/plastic deformation, and the molecular component was estimated as a function of the contact area and interfacial shear stress. Numerical results were compared with experimental results and a good agreement was obtained. The model was then used to predict friction coefficients in different operating and surface conditions. Numerical results explain why applied load has a minimum effect on the friction coefficients. They also provide insight into the effect of surface roughness on the mechanical and molecular components of friction coefficients. It is revealed that the mechanical component dominates the friction coefficient when the surface roughness is large (Rq > 0.2 μm), while the friction coefficient is mainly determined by the molecular component when the surface is relatively smooth (Rq < 0.2 μm). Furthermore, optimal roughness values for minimizing the friction coefficient are recommended.

An anomalous basaltic meteorite from the innermost main belt.

PubMed

Bland, Philip A; Spurny, Pavel; Towner, Martin C; Bevan, Alex W R; Singleton, Andrew T; Bottke, William F; Greenwood, Richard C; Chesley, Steven R; Shrbeny, Lukas; Borovicka, Jiri; Ceplecha, Zdenek; McClafferty, Terence P; Vaughan, David; Benedix, Gretchen K; Deacon, Geoff; Howard, Kieren T; Franchi, Ian A; Hough, Robert M

2009-09-18

Triangulated observations of fireballs allow us to determine orbits and fall positions for meteorites. The great majority of basaltic meteorites are derived from the asteroid 4 Vesta. We report on a recent fall that has orbital properties and an oxygen isotope composition that suggest a distinct parent body. Although its orbit was almost entirely contained within Earth's orbit, modeling indicates that it originated from the innermost main belt. Because the meteorite parent body would likely be classified as a V-type asteroid, V-type precursors for basaltic meteorites unrelated to Vesta may reside in the inner main belt. This starting location is in agreement with predictions of a planetesimal evolution model that postulates the formation of differentiated asteroids in the terrestrial planet region, with surviving fragments concentrated in the innermost main belt.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Prediction of pork quality parameters by applying fractals and data mining on MRI.

PubMed

Caballero, Daniel; Pérez-Palacios, Trinidad; Caro, Andrés; Amigo, José Manuel; Dahl, Anders B; ErsbØll, Bjarne K; Antequera, Teresa

2017-09-01

This work firstly investigates the use of MRI, fractal algorithms and data mining techniques to determine pork quality parameters non-destructively. The main objective was to evaluate the capability of fractal algorithms (Classical Fractal algorithm, CFA; Fractal Texture Algorithm, FTA and One Point Fractal Texture Algorithm, OPFTA) to analyse MRI in order to predict quality parameters of loin. In addition, the effect of the sequence acquisition of MRI (Gradient echo, GE; Spin echo, SE and Turbo 3D, T3D) and the predictive technique of data mining (Isotonic regression, IR and Multiple linear regression, MLR) were analysed. Both fractal algorithm, FTA and OPFTA are appropriate to analyse MRI of loins. The sequence acquisition, the fractal algorithm and the data mining technique seems to influence on the prediction results. For most physico-chemical parameters, prediction equations with moderate to excellent correlation coefficients were achieved by using the following combinations of acquisition sequences of MRI, fractal algorithms and data mining techniques: SE-FTA-MLR, SE-OPFTA-IR, GE-OPFTA-MLR, SE-OPFTA-MLR, with the last one offering the best prediction results. Thus, SE-OPFTA-MLR could be proposed as an alternative technique to determine physico-chemical traits of fresh and dry-cured loins in a non-destructive way with high accuracy. Copyright © 2017. Published by Elsevier Ltd.

Modeling the prediction of business intelligence system effectiveness.

PubMed

Weng, Sung-Shun; Yang, Ming-Hsien; Koo, Tian-Lih; Hsiao, Pei-I

2016-01-01

Although business intelligence (BI) technologies are continually evolving, the capability to apply BI technologies has become an indispensable resource for enterprises running in today's complex, uncertain and dynamic business environment. This study performed pioneering work by constructing models and rules for the prediction of business intelligence system effectiveness (BISE) in relation to the implementation of BI solutions. For enterprises, effectively managing critical attributes that determine BISE to develop prediction models with a set of rules for self-evaluation of the effectiveness of BI solutions is necessary to improve BI implementation and ensure its success. The main study findings identified the critical prediction indicators of BISE that are important to forecasting BI performance and highlighted five classification and prediction rules of BISE derived from decision tree structures, as well as a refined regression prediction model with four critical prediction indicators constructed by logistic regression analysis that can enable enterprises to improve BISE while effectively managing BI solution implementation and catering to academics to whom theory is important.

What causes similarity in catchments?

NASA Astrophysics Data System (ADS)

Savenije, Hubert

2014-05-01

One of the biggest issues in hydrology is how to handle the heterogeneity of catchment properties at different scales. But is this really such a big issue? Is this problem not merely the consequence of how we conceptualise and how we model catchments? Is there not far more similarity than we observe. Maybe we are not looking at the right things or at the right scale to see the similarity. The identity of catchments is largely determined by: the landscape, the ecosystem living on the landscape, and the geology, in that order. Soils, which are often seen as a crucial aspect of hydrological behaviour, are far less important, as will be demonstrated. The main determinants of hydrological behaviour are: the landscape composition, the rooting depth and the phenology. These determinants are a consequence of landscape and ecosystem evolution, which, in turn, are the manifestations of entropy production. There are striking similarities between catchments. The different runoff processes from hillslopes are linked and similar in different environments (McDonnell, 2013). Wetlands behave similarly all over the world. The key is to classify landscapes and to link the ecosystems living on them to climate. The ecosystem then is the main controller of hydrological behaviour. Besides phenology, the rooting depth is key in determining runoff behaviour. Both are strongly linked to climate and much less to soil properties. An example is given of how rooting depth is determined by climate, and how rooting depth can be predicted without calibration, providing a strong constraints on the prediction of rainfall partitioning and catchment runoff.

Cold flow testing of the Space Shuttle Main Engine high pressure fuel turbine model

NASA Technical Reports Server (NTRS)

Hudson, Susan T.; Gaddis, Stephen W.; Johnson, P. D.; Boynton, James L.

1991-01-01

In order to experimentally determine the performance of the Space Shuttle Main Engine (SSME) High Pressure Fuel Turbopump (HPFTP) turbine, a 'cold' air flow turbine test program was established at NASA's Marshall Space Flight Center. As part of this test program, a baseline test of Rocketdyne's HPFTP turbine has been completed. The turbine performance and turbine diagnostics such as airfoil surface static pressure distributions, static pressure drops through the turbine, and exit swirl angles were investigated at the turbine design point, over its operating range, and at extreme off-design points. The data was compared to pretest predictions with good results. The test data has been used to improve meanline prediction codes and is now being used to validate various three-dimensional codes. The data will also be scaled to engine conditions and used to improve the SSME steady-state performance model.

The Quality of School Life and Burnout as Predictors of Subjective Well-Being among Teachers

ERIC Educational Resources Information Center

Cenkseven-Onder, Fulya; Sari, Mediha

2009-01-01

The main purpose of this study is to determine the rate of how teachers' subjective wellbeing is predicted by their perceptions about the quality of school life and burnout levels. The participants of the study consisted of 161 teachers (93 females, 68 males) who were working in elementary schools in Adana central districts. The Positive-Negative…

The Effect of Breastfeeding and Stimulation in the Home on Cognitive Development in One-Year-Old Infants

ERIC Educational Resources Information Center

Sloan, Seaneen; Stewart, Moira; Dunne, Laura

2010-01-01

Research on the effects of breastfeeding on child cognitive development has produced conflicting results, and many studies do not account for infant stimulation in the home. The aim of this study is to determine whether breastfeeding predicts enhanced cognitive development in one-year-old infants after controlling for the main socio-economic and…

Resources of Mathematics Self-Efficacy and Perception of Science Self-Efficacy as Predictors of Academic Achievement

ERIC Educational Resources Information Center

Kaya, Deniz; Bozdag, Hüseyin Cihan

2016-01-01

The main objective of this study is to determine the predictive power of mathematics self-efficacy resources and perception of science self-efficacy on academic achievement. The study, adopting a relational screening model, was conducted with a total of 698 students in sixth, seventh and eighth grade level of a state secondary school. Mathematics…

Nonlinear rotordynamics analysis. [Space Shuttle Main Engine turbopumps

NASA Technical Reports Server (NTRS)

Noah, Sherif T.

1991-01-01

Effective analysis tools were developed for predicting the nonlinear rotordynamic behavior of the Space Shuttle Main Engine (SSME) turbopumps under steady and transient operating conditions. Using these methods, preliminary parametric studies were conducted on both generic and actual HPOTP (high pressure oxygen turbopump) models. In particular, a novel modified harmonic balance/alternating Fourier transform (HB/AFT) method was developed and used to conduct a preliminary study of the effects of fluid, bearing and seal forces on the unbalanced response of a multi-disk rotor in the presence of bearing clearances. The method makes it possible to determine periodic, sub-, super-synchronous and chaotic responses of a rotor system. The method also yields information about the stability of the obtained response, thus allowing bifurcation analyses. This provides a more effective capability for predicting the response under transient conditions by searching in proximity of resonance peaks. Preliminary results were also obtained for the nonlinear transient response of an actual HPOTP model using an efficient, newly developed numerical method based on convolution integration. Currently, the HB/AFT is being extended for determining the aperiodic response of nonlinear systems. Initial results show the method to be promising.

Study and modeling of the evolution of gas-liquid partitioning of hydrogen sulfide in model solutions simulating winemaking fermentations.

PubMed

Mouret, Jean-Roch; Sablayrolles, Jean-Marie; Farines, Vincent

2015-04-01

The knowledge of gas-liquid partitioning of aroma compounds during winemaking fermentation could allow optimization of fermentation management, maximizing concentrations of positive markers of aroma and minimizing formation of molecules, such as hydrogen sulfide (H2S), responsible for defects. In this study, the effect of the main fermentation parameters on the gas-liquid partition coefficients (Ki) of H2S was assessed. The Ki for this highly volatile sulfur compound was measured in water by an original semistatic method developed in this work for the determination of gas-liquid partitioning. This novel method was validated and then used to determine the Ki of H2S in synthetic media simulating must, fermenting musts at various steps of the fermentation process, and wine. Ki values were found to be mainly dependent on the temperature but also varied with the composition of the medium, especially with the glucose concentration. Finally, a model was developed to quantify the gas-liquid partitioning of H2S in synthetic media simulating must to wine. This model allowed a very accurate prediction of the partition coefficient of H2S: the difference between observed and predicted values never exceeded 4%.

Near-infrared hyperspectral imaging and partial least squares regression for rapid and reagentless determination of Enterobacteriaceae on chicken fillets.

PubMed

Feng, Yao-Ze; Elmasry, Gamal; Sun, Da-Wen; Scannell, Amalia G M; Walsh, Des; Morcy, Noha

2013-06-01

Bacterial pathogens are the main culprits for outbreaks of food-borne illnesses. This study aimed to use the hyperspectral imaging technique as a non-destructive tool for quantitative and direct determination of Enterobacteriaceae loads on chicken fillets. Partial least squares regression (PLSR) models were established and the best model using full wavelengths was obtained in the spectral range 930-1450 nm with coefficients of determination R(2)≥ 0.82 and root mean squared errors (RMSEs) ≤ 0.47 log(10)CFUg(-1). In further development of simplified models, second derivative spectra and weighted PLS regression coefficients (BW) were utilised to select important wavelengths. However, the three wavelengths (930, 1121 and 1345 nm) selected from BW were competent and more preferred for predicting Enterobacteriaceae loads with R(2) of 0.89, 0.86 and 0.87 and RMSEs of 0.33, 0.40 and 0.45 log(10)CFUg(-1) for calibration, cross-validation and prediction, respectively. Besides, the constructed prediction map provided the distribution of Enterobacteriaceae bacteria on chicken fillets, which cannot be achieved by conventional methods. It was demonstrated that hyperspectral imaging is a potential tool for determining food sanitation and detecting bacterial pathogens on food matrix without using complicated laboratory regimes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Study of the Effect of a Closed-End Side Branch on Sinusoidally Perturbed Flow of Liquid in a Line

NASA Technical Reports Server (NTRS)

Lewis, William; Blade, Robert J.; Dorsch, Robert G.

1963-01-01

Classical undamped acoustic-wave theory was used to determine analytical relations among sinusoidal perturbations of pressure and flow at the ends of a hydraulic-transmission line having a closed-end branch of arbitrary length attached at an arbitrary point. Experimental data were obtained for the equilateral case (a branch half as long as the main line connected to the main line at the midpoint) at mean flow speeds of 5 to 10 feet per second. Measured pressure-perturbation ratios agreed closely with analytical predictions. As frequencies for which the branch length was an odd multiple of 1/4 wavelength, waves in the main line were almost completely reflected at the junction point.

RNA secondary structure prediction with pseudoknots: Contribution of algorithm versus energy model.

PubMed

Jabbari, Hosna; Wark, Ian; Montemagno, Carlo

2018-01-01

RNA is a biopolymer with various applications inside the cell and in biotechnology. Structure of an RNA molecule mainly determines its function and is essential to guide nanostructure design. Since experimental structure determination is time-consuming and expensive, accurate computational prediction of RNA structure is of great importance. Prediction of RNA secondary structure is relatively simpler than its tertiary structure and provides information about its tertiary structure, therefore, RNA secondary structure prediction has received attention in the past decades. Numerous methods with different folding approaches have been developed for RNA secondary structure prediction. While methods for prediction of RNA pseudoknot-free structure (structures with no crossing base pairs) have greatly improved in terms of their accuracy, methods for prediction of RNA pseudoknotted secondary structure (structures with crossing base pairs) still have room for improvement. A long-standing question for improving the prediction accuracy of RNA pseudoknotted secondary structure is whether to focus on the prediction algorithm or the underlying energy model, as there is a trade-off on computational cost of the prediction algorithm versus the generality of the method. The aim of this work is to argue when comparing different methods for RNA pseudoknotted structure prediction, the combination of algorithm and energy model should be considered and a method should not be considered superior or inferior to others if they do not use the same scoring model. We demonstrate that while the folding approach is important in structure prediction, it is not the only important factor in prediction accuracy of a given method as the underlying energy model is also as of great value. Therefore we encourage researchers to pay particular attention in comparing methods with different energy models.

Potential and limits to unravel the genetic architecture and predict the variation of Fusarium head blight resistance in European winter wheat (Triticum aestivum L.).

PubMed

Jiang, Y; Zhao, Y; Rodemann, B; Plieske, J; Kollers, S; Korzun, V; Ebmeyer, E; Argillier, O; Hinze, M; Ling, J; Röder, M S; Ganal, M W; Mette, M F; Reif, J C

2015-03-01

Genome-wide mapping approaches in diverse populations are powerful tools to unravel the genetic architecture of complex traits. The main goals of our study were to investigate the potential and limits to unravel the genetic architecture and to identify the factors determining the accuracy of prediction of the genotypic variation of Fusarium head blight (FHB) resistance in wheat (Triticum aestivum L.) based on data collected with a diverse panel of 372 European varieties. The wheat lines were phenotyped in multi-location field trials for FHB resistance and genotyped with 782 simple sequence repeat (SSR) markers, and 9k and 90k single-nucleotide polymorphism (SNP) arrays. We applied genome-wide association mapping in combination with fivefold cross-validations and observed surprisingly high accuracies of prediction for marker-assisted selection based on the detected quantitative trait loci (QTLs). Using a random sample of markers not selected for marker-trait associations revealed only a slight decrease in prediction accuracy compared with marker-based selection exploiting the QTL information. The same picture was confirmed in a simulation study, suggesting that relatedness is a main driver of the accuracy of prediction in marker-assisted selection of FHB resistance. When the accuracy of prediction of three genomic selection models was contrasted for the three marker data sets, no significant differences in accuracies among marker platforms and genomic selection models were observed. Marker density impacted the accuracy of prediction only marginally. Consequently, genomic selection of FHB resistance can be implemented most cost-efficiently based on low- to medium-density SNP arrays.

Combining techniques for screening and evaluating interaction terms on high-dimensional time-to-event data.

PubMed

Sariyar, Murat; Hoffmann, Isabell; Binder, Harald

2014-02-26

Molecular data, e.g. arising from microarray technology, is often used for predicting survival probabilities of patients. For multivariate risk prediction models on such high-dimensional data, there are established techniques that combine parameter estimation and variable selection. One big challenge is to incorporate interactions into such prediction models. In this feasibility study, we present building blocks for evaluating and incorporating interactions terms in high-dimensional time-to-event settings, especially for settings in which it is computationally too expensive to check all possible interactions. We use a boosting technique for estimation of effects and the following building blocks for pre-selecting interactions: (1) resampling, (2) random forests and (3) orthogonalization as a data pre-processing step. In a simulation study, the strategy that uses all building blocks is able to detect true main effects and interactions with high sensitivity in different kinds of scenarios. The main challenge are interactions composed of variables that do not represent main effects, but our findings are also promising in this regard. Results on real world data illustrate that effect sizes of interactions frequently may not be large enough to improve prediction performance, even though the interactions are potentially of biological relevance. Screening interactions through random forests is feasible and useful, when one is interested in finding relevant two-way interactions. The other building blocks also contribute considerably to an enhanced pre-selection of interactions. We determined the limits of interaction detection in terms of necessary effect sizes. Our study emphasizes the importance of making full use of existing methods in addition to establishing new ones.

SPY: a new scission-point model based on microscopic inputs to predict fission fragment properties

NASA Astrophysics Data System (ADS)

Panebianco, Stefano; Dubray, Nöel; Goriely, Stéphane; Hilaire, Stéphane; Lemaître, Jean-François; Sida, Jean-Luc

2014-04-01

Despite the difficulty in describing the whole fission dynamics, the main fragment characteristics can be determined in a static approach based on a so-called scission-point model. Within this framework, a new Scission-Point model for the calculations of fission fragment Yields (SPY) has been developed. This model, initially based on the approach developed by Wilkins in the late seventies, consists in performing a static energy balance at scission, where the two fragments are supposed to be completely separated so that their macroscopic properties (mass and charge) can be considered as fixed. Given the knowledge of the system state density, averaged quantities such as mass and charge yields, mean kinetic and excitation energy can then be extracted in the framework of a microcanonical statistical description. The main advantage of the SPY model is the introduction of one of the most up-to-date microscopic descriptions of the nucleus for the individual energy of each fragment and, in the future, for their state density. These quantities are obtained in the framework of HFB calculations using the Gogny nucleon-nucleon interaction, ensuring an overall coherence of the model. Starting from a description of the SPY model and its main features, a comparison between the SPY predictions and experimental data will be discussed for some specific cases, from light nuclei around mercury to major actinides. Moreover, extensive predictions over the whole chart of nuclides will be discussed, with particular attention to their implication in stellar nucleosynthesis. Finally, future developments, mainly concerning the introduction of microscopic state densities, will be briefly discussed.

On-road driving impairments and associated cognitive deficits after stroke.

PubMed

Devos, Hannes; Tant, Mark; Akinwuntan, Abiodun E

2014-01-01

Little is known about the critical on-road driving skills that get affected after a stroke. The purpose of this study was to investigate the key on-road driving impairments and their associated cognitive deficits after a stroke. A second aim was to investigate if lateralization of stroke impacts results of the cognitive and on-road driving tests. In this cross-sectional study, 99 participants with a first-ever stroke who were actively driving prior to stroke underwent a cognitive battery and a standardized road test that evaluated 13 specific on-road driving skills. These on-road driving skills were mapped onto an existing, theoretical framework that categorized the on-road items into hierarchic clusters of operational, tactical, visuo-integrative, and mixed driving skills. The total score on the road test and the on-road decision, made by a certified fitness-to-drive expert, decided the main outcome. The critical on-road driving skills predicting the on-road decision were identified using logistic regression analysis. Linear regression analysis was employed to determine the cognitive impairments leading to poor total on-road scores. Analyses were repeated for right- and left-sided strokes. In all, 37 persons scored poorly on the road test. These participants performed worse in all hierarchic clusters of on-road driving. Performances on the operational cluster and the visuo-integrative cluster best predicted on-road decisions (R(2) = 0.60). 'Lane changing' and 'understanding, insight, and quality of traffic participation' were the critical skill deficits leading to poor performance on the road test (R(2) = 0.65). Divided attention was the main determinant of on-road scores in the total group (R(2) = 0.06). Participants with right-sided stroke performed worse on visual field, visual neglect, visual scanning, visuo-constructive skills, and divided attention compared with those with left-sided stroke. Divided attention was the main determinant of total on-road scores in the right-sided stroke group (R(2) = 0.10). A combination of visual scanning, speed of processing, and executive dysfunction yielded the best model to predict on-road scores in left-sided strokes (R(2) = 0.46). Poor performance in the road test after stroke is determined by critical operational and visuo-integrative driving impairments. Specific and different driving evaluation and training programs are needed for right- and left-sided strokes. © 2014 S. Karger AG, Basel.

Narrative Ability of Children with Speech Sound Disorders and the Prediction of Later Literacy Skills

ERIC Educational Resources Information Center

Wellman, Rachel L.; Lewis, Barbara A.; Freebairn, Lisa A.; Avrich, Allison A.; Hansen, Amy J.; Stein, Catherine M.

2011-01-01

Purpose: The main purpose of this study was to examine how children with isolated speech sound disorders (SSDs; n = 20), children with combined SSDs and language impairment (LI; n = 20), and typically developing children (n = 20), ages 3;3 (years;months) to 6;6, differ in narrative ability. The second purpose was to determine if early narrative…

Review of the Non-Experimental Evidence from Developmental and Cognitive Psychological, Education Science and Neuroscience That Provided the Impetus for the Development of the Intervention

ERIC Educational Resources Information Center

Grissmer, David; Grimm, Kevin J.

2013-01-01

Duncan et al. (2007) presented a new methodology for identifying kindergarten readiness factors and quantifying their importance by determining which of children's developing skills measured around kindergarten entrance would predict later reading and math achievement. The main objectives of this paper are threefold: (a) provide new empirical…

Decrease in the orbital period of Hercules X-1

NASA Technical Reports Server (NTRS)

Deeter, John E.; Boynton, Paul E.; Miyamoto, Sigenori; Kitamoto, Shunji; Nagase, Fumiaki; Kawai, Nobuyuki

1991-01-01

From a pulse-timing analysis of Ginga observations of the binary X-ray pulsar Her X-1 obtained during the interval 1989 April-June local orbital parameters are determined for a short high state. An orbital epoch is also determined in the adjacent main high state. By comparing these orbital solutions with previously published results, a decrease is detected in the orbital period for Her X-1 over the interval 1971-1989. The value is substantially larger than the value predicted from current estimates of the mass-transfer rate, and motivates consideration of other mechanisms of mass transfer and/or mass loss. A second result from these observations is a close agreement between orbital parameters determined separately in main high and short high states. This agreement places strong constraints on the obliquity of the stellar companion, HZ Her, if undergoing forced precession with a 35-day period. As a consequence further doubt is placed on the slaved-disk model as the underlying cause of the 35-day cycle in Her X-1.

Do Maximal Roller Skiing Speed and Double Poling Performance Predict Youth Cross-Country Skiing Performance?

PubMed Central

Stöggl, Roland; Müller, Erich; Stöggl, Thomas

2017-01-01

The aims of the current study were to analyze whether specific roller skiing tests and cycle length are determinants of youth cross-country (XC) skiing performance, and to evaluate sex specific differences by applying non-invasive diagnostics. Forty-nine young XC skiers (33 boys; 13.8 ± 0.6 yrs and 16 girls; 13.4 ± 0.9 yrs) performed roller skiing tests consisting of both shorter (50 m) and longer durations (575 m). Test results were correlated with on snow XC skiing performance (PXC) based on 3 skating and 3 classical distance competitions (3 to 6 km). The main findings of the current study were: 1) Anthropometrics and maturity status were related to boys’, but not to girls’ PXC; 2) Significant moderate to acceptable correlations between girls’ and boys’ short duration maximal roller skiing speed (double poling, V2 skating, leg skating) and PXC were found; 3) Boys’ PXC was best predicted by double poling test performance on flat and uphill, while girls’ performance was mainly predicted by uphill double poling test performance; 4) When controlling for maturity offset, boys’ PXC was still highly associated with the roller skiing tests. The use of simple non-invasive roller skiing tests for determination of PXC represents practicable support for ski clubs, schools or skiing federations in the guidance and evaluation of young talent. Key points Double poling tests on flat and uphill terrain and short duration maximal speed tests were the highest cross-country skiing predicting factors in girls and boys. Only in the boys there was an effect of maturation on the performance outcomes, pointing out that girls seem to be almost fully matured at the age of 13 in contrast to the boys. Roller skiing tests over short distance (50-m) and longer distance 225 m and 350 m are stable and valid measures and suitable for performance prediction in youth cross-country skiers. PMID:28912656

The Addicted-Self Model of addictive behavior cessation: does it predict recovery for gender, ethnic, age and drug preference populations?

PubMed

Fiorentine, Robert; Hillhouse, Maureen P

2004-01-01

Although previous research provided empirical support for the main assumptions of the Addicted-Self (A-S) Model of recovery, it is not known whether the model predicts recovery for various gender, ethnic, age, and drug preference populations. It may be that the model predicts recovery only for some groups of addicts and should not be viewed as a general theory of the recovery process. Addressing this concern using data from the Los Angeles Target Cities Drug Treatment Enhancement Project, it was determined that only trivial population differences exist in the primary variables associated with the A-S Model. The A-S Model predicts abstinence with about the same degree of accuracy and parsimony for all populations. The findings indicate that the A-S Model is a general theory of drug and alcohol addictive behavior cessation.

The role of predictability and structure in word stress processing: an ERP study on Cairene Arabic and a cross-linguistic comparison

PubMed Central

Domahs, Ulrike; Knaus, Johannes A.; El Shanawany, Heba; Wiese, Richard

2014-01-01

This article presents neurolinguistic data on word stress perception in Cairene Arabic, in comparison to previous results on German and Turkish. The main goal is to investigate how central properties of stress systems such as predictability of stress and metrical structure are reflected in the prosodic processing of words. Cairene Arabic is a language with a regular foot-based word stress system, leading to highly predictable placement of word stress. An ERP study on Cairene Arabic is reported, in which a stress violation paradigm is used to investigate the factors predictability of stress and foot structure. The results of the experiment show that for Cairene Arabic the internal structure of prosodic words in terms of feet determines prosodic processing. This structure effect is complemented by a frequency effect for stress patterns. PMID:25374546

Hierarchical Ensemble Methods for Protein Function Prediction

PubMed Central

2014-01-01

Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relationships between functional classes that characterize both the Gene Ontology and FunCat taxonomies motivate the development of hierarchy-aware prediction methods that showed significantly better performances than hierarchical-unaware “flat” prediction methods. In this paper, we provide a comprehensive review of hierarchical methods for protein function prediction based on ensembles of learning machines. According to this general approach, a separate learning machine is trained to learn a specific functional term and then the resulting predictions are assembled in a “consensus” ensemble decision, taking into account the hierarchical relationships between classes. The main hierarchical ensemble methods proposed in the literature are discussed in the context of existing computational methods for protein function prediction, highlighting their characteristics, advantages, and limitations. Open problems of this exciting research area of computational biology are finally considered, outlining novel perspectives for future research. PMID:25937954

Ergonomics study on mobile phones for thumb physiology discomfort

NASA Astrophysics Data System (ADS)

Bendero, J. M. S.; Doon, M. E. R.; Quiogue, K. C. A.; Soneja, L. C.; Ong, N. R.; Sauli, Z.; Vairavan, R.

2017-09-01

The study was conducted on Filipino undergraduate college students and aimed to find out about the significant factors associated with mobile phone usage and its effect on thumb pain.A correlation-prediction analysisand Multiple Linear Regression was adopted and used as the main tool in determining the significant factors and coming up with predictive models on thumb related pain. With the use of the software Statistical Package for the Social Sciences or SPSS in conducting linear regression, 2 significant factors on thumb-related pain (percentage of time using portrait as screen orientation when text messaging, amount of time playing games using one hand in a day) were found.

Allan Deviation Plot as a Tool for Quartz-Enhanced Photoacoustic Sensors Noise Analysis.

PubMed

Giglio, Marilena; Patimisco, Pietro; Sampaolo, Angelo; Scamarcio, Gaetano; Tittel, Frank K; Spagnolo, Vincenzo

2016-04-01

We report here on the use of the Allan deviation plot to analyze the long-term stability of a quartz-enhanced photoacoustic (QEPAS) gas sensor. The Allan plot provides information about the optimum averaging time for the QEPAS signal and allows the prediction of its ultimate detection limit. The Allan deviation can also be used to determine the main sources of noise coming from the individual components of the sensor. Quartz tuning fork thermal noise dominates for integration times up to 275 s, whereas at longer averaging times, the main contribution to the sensor noise originates from laser power instabilities.

Iterative procedures for space shuttle main engine performance models

NASA Technical Reports Server (NTRS)

Santi, L. Michael

1989-01-01

Performance models of the Space Shuttle Main Engine (SSME) contain iterative strategies for determining approximate solutions to nonlinear equations reflecting fundamental mass, energy, and pressure balances within engine flow systems. Both univariate and multivariate Newton-Raphson algorithms are employed in the current version of the engine Test Information Program (TIP). Computational efficiency and reliability of these procedures is examined. A modified trust region form of the multivariate Newton-Raphson method is implemented and shown to be superior for off nominal engine performance predictions. A heuristic form of Broyden's Rank One method is also tested and favorable results based on this algorithm are presented.

Predictability of the future development of aggressive behavior of cranial dural arteriovenous fistulas based on decision tree analysis.

PubMed

Satomi, Junichiro; Ghaibeh, A Ammar; Moriguchi, Hiroki; Nagahiro, Shinji

2015-07-01

The severity of clinical signs and symptoms of cranial dural arteriovenous fistulas (DAVFs) are well correlated with their pattern of venous drainage. Although the presence of cortical venous drainage can be considered a potential predictor of aggressive DAVF behaviors, such as intracranial hemorrhage or progressive neurological deficits due to venous congestion, accurate statistical analyses are currently not available. Using a decision tree data mining method, the authors aimed at clarifying the predictability of the future development of aggressive behaviors of DAVF and at identifying the main causative factors. Of 266 DAVF patients, 89 were eligible for analysis. Under observational management, 51 patients presented with intracranial hemorrhage/infarction during the follow-up period. The authors created a decision tree able to assess the risk for the development of aggressive DAVF behavior. Evaluated by 10-fold cross-validation, the decision tree's accuracy, sensitivity, and specificity were 85.28%, 88.33%, and 80.83%, respectively. The tree shows that the main factor in symptomatic patients was the presence of cortical venous drainage. In its absence, the lesion location determined the risk of a DAVF developing aggressive behavior. Decision tree analysis accurately predicts the future development of aggressive DAVF behavior.

Macro-microscopic mass formulae and nuclear mass predictions

NASA Astrophysics Data System (ADS)

Royer, G.; Guilbaud, M.; Onillon, A.

2010-12-01

Different mass formulae derived from the liquid drop model and the pairing and shell energies of the Thomas-Fermi model have been studied and compared. They include or not the diffuseness correction to the Coulomb energy, the charge exchange correction term, the curvature energy, different forms of the Wigner term and powers of the relative neutron excess I=(N-Z)/A. Their coefficients have been determined by a least square fitting procedure to 2027 experimental atomic masses (G. Audi et al. (2003) [1]). The Coulomb diffuseness correction Z/A term or the charge exchange correction Z/A term plays the main role to improve the accuracy of the mass formula. The Wigner term and the curvature energy can also be used separately but their coefficients are very unstable. The different fits lead to a surface energy coefficient of around 17-18 MeV. A large equivalent rms radius ( r=1.22-1.24 fm) or a shorter central radius may be used. An rms deviation of 0.54 MeV can be reached between the experimental and theoretical masses. The remaining differences come probably mainly from the determination of the shell and pairing energies. Mass predictions of selected expressions have been compared to 161 new experimental masses and the correct agreement allows to provide extrapolations to masses of 656 selected exotic nuclei.

2D imaging of helium ion velocity in the DIII-D divertor

NASA Astrophysics Data System (ADS)

Samuell, C. M.; Porter, G. D.; Meyer, W. H.; Rognlien, T. D.; Allen, S. L.; Briesemeister, A.; Mclean, A. G.; Zeng, L.; Jaervinen, A. E.; Howard, J.

2018-05-01

Two-dimensional imaging of parallel ion velocities is compared to fluid modeling simulations to understand the role of ions in determining divertor conditions and benchmark the UEDGE fluid modeling code. Pure helium discharges are used so that spectroscopic He+ measurements represent the main-ion population at small electron temperatures. Electron temperatures and densities in the divertor match simulated values to within about 20%-30%, establishing the experiment/model match as being at least as good as those normally obtained in the more regularly simulated deuterium plasmas. He+ brightness (HeII) comparison indicates that the degree of detachment is captured well by UEDGE, principally due to the inclusion of E ×B drifts. Tomographically inverted Coherence Imaging Spectroscopy measurements are used to determine the He+ parallel velocities which display excellent agreement between the model and the experiment near the divertor target where He+ is predicted to be the main-ion species and where electron-dominated physics dictates the parallel momentum balance. Upstream near the X-point where He+ is a minority species and ion-dominated physics plays a more important role, there is an underestimation of the flow velocity magnitude by a factor of 2-3. These results indicate that more effort is required to be able to correctly predict ion momentum in these challenging regimes.

Integrated Cryogenic Experiment (ICE) microsphere investigation

NASA Technical Reports Server (NTRS)

Spradley, I.; Read, D.

1989-01-01

The main objective is to determine the performance of microsphere insulation in a 0-g environment and compare its performance to reference insulations such as multilayer insulation. The Lockheed Helium Extended-Life Dewar (HELD) is used to provide superfluid-helium cold sink for the experiment. The use of HELD allows the low-g dynamic properties of Passive Orbital Disconnect Struts (PODS) to be characterized and provides a flight demonstration of the PODS system. The thermal performance of microspheres in 1 and 0 g was predicted, a flight experiment was designed to determine microsphere thermal performance, and the interface was also designed between the experimental package and the shuttle through HELD and the Hitchhiker-M carrier. A single test cell was designed and fabricated. The cell was filled with uncoated glass microspheres and tested with a liquid-nitrogen cold sink. The data were found to agree with predictions of microsphere performance in 1 g.

Genetic Determinants of Drug Resistance in Mycobacterium tuberculosis and Their Diagnostic Value

PubMed Central

Sultana, Razvan; Iartchouk, Oleg; Bozeman, Sam; Galagan, James; Sisk, Peter; Stolte, Christian; Nebenzahl-Guimaraes, Hanna; Jacobson, Karen; Sloutsky, Alexander; Kaur, Devinder; Posey, James; Kreiswirth, Barry N.; Kurepina, Natalia; Rigouts, Leen; Streicher, Elizabeth M.; Victor, Tommie C.; Warren, Robin M.; van Soolingen, Dick; Murray, Megan

2016-01-01

Rationale: The development of molecular diagnostics that detect both the presence of Mycobacterium tuberculosis in clinical samples and drug resistance–conferring mutations promises to revolutionize patient care and interrupt transmission by ensuring early diagnosis. However, these tools require the identification of genetic determinants of resistance to the full range of antituberculosis drugs. Objectives: To determine the optimal molecular approach needed, we sought to create a comprehensive catalog of resistance mutations and assess their sensitivity and specificity in diagnosing drug resistance. Methods: We developed and validated molecular inversion probes for DNA capture and deep sequencing of 28 drug-resistance loci in M. tuberculosis. We used the probes for targeted sequencing of a geographically diverse set of 1,397 clinical M. tuberculosis isolates with known drug resistance phenotypes. We identified a minimal set of mutations to predict resistance to first- and second-line antituberculosis drugs and validated our predictions in an independent dataset. We constructed and piloted a web-based database that provides public access to the sequence data and prediction tool. Measurements and Main Results: The predicted resistance to rifampicin and isoniazid exceeded 90% sensitivity and specificity but was lower for other drugs. The number of mutations needed to diagnose resistance is large, and for the 13 drugs studied it was 238 across 18 genetic loci. Conclusions: These data suggest that a comprehensive M. tuberculosis drug resistance diagnostic will need to allow for a high dimension of mutation detection. They also support the hypothesis that currently unknown genetic determinants, potentially discoverable by whole-genome sequencing, encode resistance to second-line tuberculosis drugs. PMID:26910495

The determinants of spread of Ebola virus disease - an evidence from the past outbreak experiences.

PubMed

Gałas, Aleksander

2014-01-01

The paper summarizes available evidence regarding the determinants of spread of Ebola virus disease, including health care and community related risk factors. It was observed that the level of uncertainty for the estimations is relatively high which may hinder to make some predictions for the future evolution of EVD outbreak. The natural history of EVD has shown that the disease may pose a problem to developed countries and may present a thread to individuals. Although observed modes of transmission mainly include direct contact and contaminated staff, high case fatality ratio and frequent contacts among individuals in developed countries are among determinants which may lead to the development of the EVD outbreak.

Message frames interact with motivational systems to determine depth of message processing.

PubMed

Shen, Lijiang; Dillard, James Price

2009-09-01

Although several theoretical perspectives predict that negatively framed messages will be processed more deeply than positively framed messages, a recent meta-analysis found no such difference. In this article, the authors explore 2 explanations for this inconsistency. One possibility is methodological: the statistics used in the primary studies underestimated framing effects on depth of message processing because the data were maldistributed. The other is theoretical: the absence of a main effect is veridical, but framing interacts with individual differences that predispose individuals to greater or lesser depth of processing. Data from 2 experiments (Ns = 286 and 252) were analyzed via tobit regression, a technique designed to overcome the limitations of maldistributed data. One study showed the predicted main effect for framing, but the other did not. Both studies showed the anticipated interaction: Depth of processing correlated positively with a measure of the behavioral activation system in the advantage framing condition, whereas depth of processing correlated positively with the behavioral inhibition system in the disadvantage framing condition.

Predicting binding poses and affinities for protein - ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimation

NASA Astrophysics Data System (ADS)

Grudinin, Sergei; Kadukova, Maria; Eisenbarth, Andreas; Marillet, Simon; Cazals, Frédéric

2016-09-01

The 2015 D3R Grand Challenge provided an opportunity to test our new model for the binding free energy of small molecules, as well as to assess our protocol to predict binding poses for protein-ligand complexes. Our pose predictions were ranked 3-9 for the HSP90 dataset, depending on the assessment metric. For the MAP4K dataset the ranks are very dispersed and equal to 2-35, depending on the assessment metric, which does not provide any insight into the accuracy of the method. The main success of our pose prediction protocol was the re-scoring stage using the recently developed Convex-PL potential. We make a thorough analysis of our docking predictions made with AutoDock Vina and discuss the effect of the choice of rigid receptor templates, the number of flexible residues in the binding pocket, the binding pocket size, and the benefits of re-scoring. However, the main challenge was to predict experimentally determined binding affinities for two blind test sets. Our affinity prediction model consisted of two terms, a pairwise-additive enthalpy, and a non pairwise-additive entropy. We trained the free parameters of the model with a regularized regression using affinity and structural data from the PDBBind database. Our model performed very well on the training set, however, failed on the two test sets. We explain the drawback and pitfalls of our model, in particular in terms of relative coverage of the test set by the training set and missed dynamical properties from crystal structures, and discuss different routes to improve it.

Space Shuttle Main Engine performance analysis

NASA Technical Reports Server (NTRS)

Santi, L. Michael

1993-01-01

For a number of years, NASA has relied primarily upon periodically updated versions of Rocketdyne's power balance model (PBM) to provide space shuttle main engine (SSME) steady-state performance prediction. A recent computational study indicated that PBM predictions do not satisfy fundamental energy conservation principles. More recently, SSME test results provided by the Technology Test Bed (TTB) program have indicated significant discrepancies between PBM flow and temperature predictions and TTB observations. Results of these investigations have diminished confidence in the predictions provided by PBM, and motivated the development of new computational tools for supporting SSME performance analysis. A multivariate least squares regression algorithm was developed and implemented during this effort in order to efficiently characterize TTB data. This procedure, called the 'gains model,' was used to approximate the variation of SSME performance parameters such as flow rate, pressure, temperature, speed, and assorted hardware characteristics in terms of six assumed independent influences. These six influences were engine power level, mixture ratio, fuel inlet pressure and temperature, and oxidizer inlet pressure and temperature. A BFGS optimization algorithm provided the base procedure for determining regression coefficients for both linear and full quadratic approximations of parameter variation. Statistical information relative to data deviation from regression derived relations was also computed. A new strategy for integrating test data with theoretical performance prediction was also investigated. The current integration procedure employed by PBM treats test data as pristine and adjusts hardware characteristics in a heuristic manner to achieve engine balance. Within PBM, this integration procedure is called 'data reduction.' By contrast, the new data integration procedure, termed 'reconciliation,' uses mathematical optimization techniques, and requires both measurement and balance uncertainty estimates. The reconciler attempts to select operational parameters that minimize the difference between theoretical prediction and observation. Selected values are further constrained to fall within measurement uncertainty limits and to satisfy fundamental physical relations (mass conservation, energy conservation, pressure drop relations, etc.) within uncertainty estimates for all SSME subsystems. The parameter selection problem described above is a traditional nonlinear programming problem. The reconciler employs a mixed penalty method to determine optimum values of SSME operating parameters associated with this problem formulation.

Predicting the sensitivity to ion therapy based on the response to photon irradiation--experimental evidence and mathematical modelling.

PubMed

Mohanty, Chitralekha; Zielinska-Chomej, Katarzyna; Edgren, Margareta; Hirayama, Ryoichi; Murakami, Takeshi; Lind, Bengt; Toma-Dasu, Iuliana

2014-06-01

The use of ion radiation therapy is growing due to the continuously increasing positive clinical experience obtained. Therefore, there is a high interest in radio-biological experiments comparing the relative efficiency in cell killing of ions and photons as photons are currently the main radiation modality used for cancer treatment. This comparison is particularly important since the treatment planning systems (TPSs) used at the main ion therapy Centers make use of parameters describing the cellular response to photons, respectively ions, determined in vitro. It was, therefore, the aim of this article to compare the effects of high linear energy transfer (LET) ion radiation with low LET photons and determine whether the cellular response to low LET could predict the response to high LET irradiation. Clonogenic cell survival data of five tumor cell lines irradiated with different ion beams of similar, clinically-relevant, LET were studied in relation to response to low LET photons. Two mathematical models were used to fit the data, the repairable-conditionally repairable damage (RCR) model and the linear quadratic (LQ) model. The results indicate that the relative biological efficiency of the high LET radiation assessed with the RCR model could be predicted based only on the response to the low LET irradiation. The particular features of the RCR model indicate that tumor cells showing a large capacity for repairing the damage will have the larger benefit from radiation therapy with ion beams. Copyright© 2014 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Soil erodibility for water erosion: A perspective and Chinese experiences

NASA Astrophysics Data System (ADS)

Wang, Bin; Zheng, Fenli; Römkens, Mathias J. M.; Darboux, Frédéric

2013-04-01

Knowledge of soil erodibility is an essential requirement for erosion prediction, conservation planning, and the assessment of sediment related environmental effects of watershed agricultural practices. This paper reviews the status of soil erodibility evaluations and determinations based on 80 years of upland area erosion research mainly in China and the USA. The review synthesizes the general research progress made by discussing the basic concepts of erodibility and its evaluation, determination, and prediction as well as knowledge of its spatio-temporal variations. The authors found that soil erodibility is often inappropriately or inaccurately applied in describing soil loss caused by different soil erosion component processes and mechanisms. Soil erodibility indicators were related to intrinsic soil properties and exogenic erosional forces, measurements, and calculations. The present review describes major needs including: (1) improved definition of erodibility, (2) modified erodibility determinations in erosion models, especially for specific geographical locations and in the context of different erosion sub-processes, (3) advanced methodologies for quantifying erodibilities of different soil erosion sub-processes, and (4) a better understanding of the mechanism that causes temporal variations in soil erodibility. The review also provides a more rational basis for future research on soil erodibility and supports predictive modeling of soil erosion processes and the development of improved conservation practices.

Case study on prediction of remaining methane potential of landfilled municipal solid waste by statistical analysis of waste composition data.

PubMed

Sel, İlker; Çakmakcı, Mehmet; Özkaya, Bestamin; Suphi Altan, H

2016-10-01

Main objective of this study was to develop a statistical model for easier and faster Biochemical Methane Potential (BMP) prediction of landfilled municipal solid waste by analyzing waste composition of excavated samples from 12 sampling points and three waste depths representing different landfilling ages of closed and active sections of a sanitary landfill site located in İstanbul, Turkey. Results of Principal Component Analysis (PCA) were used as a decision support tool to evaluation and describe the waste composition variables. Four principal component were extracted describing 76% of data set variance. The most effective components were determined as PCB, PO, T, D, W, FM, moisture and BMP for the data set. Multiple Linear Regression (MLR) models were built by original compositional data and transformed data to determine differences. It was observed that even residual plots were better for transformed data the R(2) and Adjusted R(2) values were not improved significantly. The best preliminary BMP prediction models consisted of D, W, T and FM waste fractions for both versions of regressions. Adjusted R(2) values of the raw and transformed models were determined as 0.69 and 0.57, respectively. Copyright © 2016 Elsevier Ltd. All rights reserved.

Socio-ecological predictors of participation and dropout in organised sports during childhood.

PubMed

Vella, Stewart A; Cliff, Dylan P; Okely, Anthony D

2014-05-13

The purpose of this study was to explore the socio-ecological determinants of participation and dropout in organised sports in a nationally-representative sample of Australian children. Data were drawn from Waves 3 and 4 of the Longitudinal Study of Australian Children. In total, 4042 children aged 8.25 (SD = 0.44) years at baseline were included, with 24-months between Waves. Socio-ecological predictors were reported by parents and teachers, while cognitive and health measures were assessed by trained professionals. All predictors were assessed at age 8, and used to predict participation and dropout by age 10. Seven variables at age 8 were shown to positively predict participation in organised sports at age 10. These included: sex (boy); fewer people in household; higher household income; main language spoken at home (English); higher parental education; child taken to a sporting event; and, access to a specialist PE teacher during primary school. Four variables predicted dropout from organised sports by age 10: lower household income; main language spoken at home (non-English); lower parental education; and, child not taken to a sporting event. The interplay between child sex, socioeconomic indicators, and parental support is important in predicting children's participation in organised sports. Multilevel and multicomponent interventions to promote participation and prevent dropout should be underpinned by the Socio-Ecological Model and targeted to high risk populations using multiple levels of risk.

Comparison of observed and predicted abutment scour at selected bridges in Maine.

DOT National Transportation Integrated Search

2008-01-01

Maximum abutment-scour depths predicted with five different methods were compared to : maximum abutment-scour depths observed at 100 abutments at 50 bridge sites in Maine with a : median bridge age of 66 years. Prediction methods included the Froehli...

Computational prediction of hemolysis in a centrifugal ventricular assist device.

PubMed

Pinotti, M; Rosa, E S

1995-03-01

This paper describes the use of computational fluid dynamics (CFD) to predict numerically the hemolysis in centrifugal pumps. A numerical hydrodynamical model, based on the full Navier-Stokes equation, was used to obtain the flow in a vaneless centrifugal pump (of corotating disks type). After proper postprocessing, critical zones in the channel were identified by means of two-dimensional color-coded maps of %Hb release. Simulation of different conditions revealed that flow behavior at the entrance region of the channel is the main cause of blood trauma in such devices. A useful feature resulting from the CFD simulation is the visualization of critical flow zones that are impossible to determine experimentally with in vitro hemolysis tests.

Prediction of helicopter rotor noise in hover

NASA Astrophysics Data System (ADS)

Kusyumov, A. N.; Mikhailov, S. A.; Garipova, L. I.; Batrakov, A. S.; Barakos, G.

2015-05-01

Two mathematical models are used in this work to estimate the acoustics of a hovering main rotor. The first model is based on the Ffowcs Williams-Howkings equations using the formulation of Farassat. An analytical approach is followed for this model, to determine the thickness and load noise contributions of the rotor blade in hover. The second approach allows using URANS and RANS CFD solutions and based on numerical solution of the Ffowcs Williams-Howkings equations. The employed test cases correspond to a model rotor available at the KNRTUKAI aerodynamics laboratory. The laboratory is equipped with a system of acoustic measurements, and comparisons between predictions and measurements are to be attempted as part of this work.

Mapping and predictive variations of soil bacterial richness across France

PubMed Central

Dequietd, Samuel; Saby, Nicolas P. A.; Lelièvre, Mélanie; Nowak, Virginie; Tripied, Julie; Régnier, Tiffanie; Jolivet, Claudy; Arrouays, Dominique; Wincker, Patrick; Cruaud, Corinne; Karimi, Battle; Bispo, Antonio; Maron, Pierre Alain; Chemidlin Prévost-Bouré, Nicolas; Ranjard, Lionel

2017-01-01

Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across France, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) influencing this distribution, and iii) to develop a statistical predictive model of soil bacterial richness. We used the French Soil Quality Monitoring Network (RMQS), which covers all of France with 2,173 sites. The soil bacterial richness (i.e. OTU number) was determined by pyrosequencing 16S rRNA genes and related to the soil characteristics, climatic conditions, geomorphology, land use and space. Mapping of bacterial richness revealed a heterogeneous spatial distribution, structured into patches of about 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance), the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively), and the land use (1.4%). Based on these drivers, a predictive model was developed, which allows a good prediction of the bacterial richness (R2adj of 0.56) and provides a reference value for a given pedoclimatic condition. PMID:29059218

In silico environmental chemical science: properties and processes from statistical and computational modelling

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

Tratnyek, Paul G.; Bylaska, Eric J.; Weber, Eric J.

2017-01-01

Quantitative structure–activity relationships (QSARs) have long been used in the environmental sciences. More recently, molecular modeling and chemoinformatic methods have become widespread. These methods have the potential to expand and accelerate advances in environmental chemistry because they complement observational and experimental data with “in silico” results and analysis. The opportunities and challenges that arise at the intersection between statistical and theoretical in silico methods are most apparent in the context of properties that determine the environmental fate and effects of chemical contaminants (degradation rate constants, partition coefficients, toxicities, etc.). The main example of this is the calibration of QSARs usingmore » descriptor variable data calculated from molecular modeling, which can make QSARs more useful for predicting property data that are unavailable, but also can make them more powerful tools for diagnosis of fate determining pathways and mechanisms. Emerging opportunities for “in silico environmental chemical science” are to move beyond the calculation of specific chemical properties using statistical models and toward more fully in silico models, prediction of transformation pathways and products, incorporation of environmental factors into model predictions, integration of databases and predictive models into more comprehensive and efficient tools for exposure assessment, and extending the applicability of all the above from chemicals to biologicals and materials.« less

Development of Probabilistic Life Prediction Methodologies and Testing Strategies for MEMS and CMC's

NASA Technical Reports Server (NTRS)

Jadaan, Osama

2003-01-01

This effort is to investigate probabilistic life prediction methodologies for ceramic matrix composites and MicroElectroMechanical Systems (MEMS) and to analyze designs that determine stochastic properties of MEMS. For CMC's this includes a brief literature survey regarding lifing methodologies. Also of interest for MEMS is the design of a proper test for the Weibull size effect in thin film (bulge test) specimens. The Weibull size effect is a consequence of a stochastic strength response predicted from the Weibull distribution. Confirming that MEMS strength is controlled by the Weibull distribution will enable the development of a probabilistic design methodology for MEMS - similar to the GRC developed CARES/Life program for bulk ceramics. A main objective of this effort is to further develop and verify the ability of the Ceramics Analysis and Reliability Evaluation of Structures/Life (CARES/Life) code to predict the time-dependent reliability of MEMS structures subjected to multiple transient loads. A second set of objectives is to determine the applicability/suitability of the CARES/Life methodology for CMC analysis, what changes would be needed to the methodology and software, and if feasible, run a demonstration problem. Also important is an evaluation of CARES/Life coupled to the ANSYS Probabilistic Design System (PDS) and the potential of coupling transient reliability analysis to the ANSYS PDS.

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

PubMed

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

2014-12-09

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

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

PubMed Central

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

2014-01-01

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

The prediction of candidate genes for cervix related cancer through gene ontology and graph theoretical approach.

PubMed

Hindumathi, V; Kranthi, T; Rao, S B; Manimaran, P

2014-06-01

With rapidly changing technology, prediction of candidate genes has become an indispensable task in recent years mainly in the field of biological research. The empirical methods for candidate gene prioritization that succors to explore the potential pathway between genetic determinants and complex diseases are highly cumbersome and labor intensive. In such a scenario predicting potential targets for a disease state through in silico approaches are of researcher's interest. The prodigious availability of protein interaction data coupled with gene annotation renders an ease in the accurate determination of disease specific candidate genes. In our work we have prioritized the cervix related cancer candidate genes by employing Csaba Ortutay and his co-workers approach of identifying the candidate genes through graph theoretical centrality measures and gene ontology. With the advantage of the human protein interaction data, cervical cancer gene sets and the ontological terms, we were able to predict 15 novel candidates for cervical carcinogenesis. The disease relevance of the anticipated candidate genes was corroborated through a literature survey. Also the presence of the drugs for these candidates was detected through Therapeutic Target Database (TTD) and DrugMap Central (DMC) which affirms that they may be endowed as potential drug targets for cervical cancer.

Motor Skill Competence and Perceived Motor Competence: Which Best Predicts Physical Activity among Girls?

PubMed

Khodaverdi, Zeinab; Bahram, Abbas; Khalaji, Hassan; Kazemnejad, Anoshirvan

2013-10-01

The main purpose of this study was to determine which correlate, perceived motor competence or motor skill competence, best predicts girls' physical activity behavior. A sample of 352 girls (mean age=8.7, SD=0.3 yr) participated in this study. To assess motor skill competence and perceived motor competence, each child completed the Test of Gross Motor Development-2 and Physical Ability sub-scale of Marsh's Self-Description Questionnaire. Children's physical activity was assessed by the Physical Activity Questionnaire for Older Children. Multiple linear regression model was used to determine whether perceived motor competence or motor skill competence best predicts moderate-to-vigorous self-report physical activity. Multiple regression analysis indicated that motor skill competence and perceived motor competence predicted 21% variance in physical activity (R(2)=0.21, F=48.9, P=0.001), and motor skill competence (R(2)=0.15, ᵝ=0.33, P= 0.001) resulted in more variance than perceived motor competence (R(2)=0.06, ᵝ=0.25, P=0.001) in physical activity. Results revealed motor skill competence had more influence in comparison with perceived motor competence on physical activity level. We suggest interventional programs based on motor skill competence and perceived motor competence should be administered or implemented to promote physical activity in young girls.

Anharmonic and Quantum Fluctuations in Molecular Crystals: A First-Principles Study of the Stability of Paracetamol

NASA Astrophysics Data System (ADS)

Rossi, Mariana; Gasparotto, Piero; Ceriotti, Michele

2016-09-01

Molecular crystals often exist in multiple competing polymorphs, showing significantly different physicochemical properties. Computational crystal structure prediction is key to interpret and guide the search for the most stable or useful form, a real challenge due to the combinatorial search space, and the complex interplay of subtle effects that work together to determine the relative stability of different structures. Here we take a comprehensive approach based on different flavors of thermodynamic integration in order to estimate all contributions to the free energies of these systems with density-functional theory, including the oft-neglected anharmonic contributions and nuclear quantum effects. We take the two main stable forms of paracetamol as a paradigmatic example. We find that anharmonic contributions, different descriptions of van der Waals interactions, and nuclear quantum effects all matter to quantitatively determine the stability of different phases. Our analysis highlights the many challenges inherent in the development of a quantitative and predictive framework to model molecular crystals. However, it also indicates which of the components of the free energy can benefit from a cancellation of errors that can redeem the predictive power of approximate models, and suggests simple steps that could be taken to improve the reliability of ab initio crystal structure prediction.

Hip and knee extensor moments predict vertical jump height in adolescent girls.

PubMed

Ford, Kevin R; Myer, Gregory D; Brent, Jensen L; Hewett, Timothy E

2009-07-01

Biomechanical factors, such as hip and knee extensor moments, related to drop jump (DJ) performance have not been investigated in adolescent girls. The purpose of this study was to determine the key independent biomechanical variables that predict overall vertical jump performance in adolescent girls. Sixteen high school adolescent girls from club-sponsored and high school-sponsored volleyball teams performed DJ at 3 different drop heights (15, 30, and 45 cm). A motion analysis system consisting of 10 digital cameras and a force platform was used to calculate vertical jump height, joint angles, and joint moments during the tasks. A multiple linear regression was used to determine the biomechanical parameters that were best predictive of vertical jump height at each box drop distance. The 2 predictor variables in all 3 models were knee and hip extensor moments. The models predicted 82.9, 81.9, and 88% of the vertical jump height variance in the 15, 30, and 45 cm trials, respectively. The results of the investigation indicate that knee and hip joint moments are the main contributors to vertical jump height during the DJ in adolescent girls. Strength and conditioning specialists attempting to improve vertical jump performance should target power and strength training to the hip and knee extensors in their athletes.

Mapping and predictive variations of soil bacterial richness across France.

PubMed

Terrat, Sébastien; Horrigue, Walid; Dequiedt, Samuel; Saby, Nicolas P A; Lelièvre, Mélanie; Nowak, Virginie; Tripied, Julie; Régnier, Tiffanie; Jolivet, Claudy; Arrouays, Dominique; Wincker, Patrick; Cruaud, Corinne; Karimi, Battle; Bispo, Antonio; Maron, Pierre Alain; Chemidlin Prévost-Bouré, Nicolas; Ranjard, Lionel

2017-01-01

Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across France, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) influencing this distribution, and iii) to develop a statistical predictive model of soil bacterial richness. We used the French Soil Quality Monitoring Network (RMQS), which covers all of France with 2,173 sites. The soil bacterial richness (i.e. OTU number) was determined by pyrosequencing 16S rRNA genes and related to the soil characteristics, climatic conditions, geomorphology, land use and space. Mapping of bacterial richness revealed a heterogeneous spatial distribution, structured into patches of about 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance), the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively), and the land use (1.4%). Based on these drivers, a predictive model was developed, which allows a good prediction of the bacterial richness (R2adj of 0.56) and provides a reference value for a given pedoclimatic condition.

Solar-Type Stars with the Suppression of Convection at an Early Stage of Evolution

NASA Astrophysics Data System (ADS)

Oreshina, A. V.; Baturin, V. A.; Ayukov, S. V.; Gorshkov, A. B.

2017-12-01

The evolution of a solar-mass star before and on the main sequence is analyzed in light of the diminished efficiency of convection in the first 500 Myr. A numerical simulation has been performed with the CESAM2k code. It is shown that the suppression of convection in the early stages of evolution leads to a somewhat higher lithium content than that predicted by the classical solar model. In addition, the star's effective temperature decreases. Ignoring this phenomenon may lead to errors in age and mass determinations for young stars (before the main sequence) from standard evolutionary tracks in the temperature-luminosity diagram. At a later stage of evolution, after 500 Myr, the efficiency of convection tends to the solar value. At this stage, the star's inner structure becomes classical; it does not depend on the previous history. On the contrary, the photospheric lithium abundance contains information about the star's past. In other words, there may exist main-sequence solar-mass stars of the same age (above 500 Myr), radius, and luminosity, yet with different photospheric lithium contents. The main results of this work add considerably to the popular method for determining the age of solar-type stars from lithium abundances.

Fracture Mechanics Analysis of LH2 Feed Line Flow Liners

NASA Technical Reports Server (NTRS)

James, Mark A.; Dawicke, David S.; Brzowski, Matthew B.; Raju, Ivatury S.; Elliott, Kenny B.; Harris, Charles E.

2006-01-01

Inspections of the Space Shuttle Main Engine revealed fatigue cracks growing from slots in the flow liner of the liquid hydrogen (LH2) feed lines. During flight, the flow liners experience complex loading induced by flow of LH2 and the resonance characteristics of the structure. The flow liners are made of Inconel 718 and had previously not been considered a fracture critical component. However, fatigue failure of a flow liner could have catastrophic effect on the Shuttle engines. A fracture mechanics study was performed to determine if a damage tolerance approach to life management was possible and to determine the sensitivity to the load spectra, material properties, and crack size. The load spectra were derived separately from ground tests and material properties were obtained from coupon tests. The stress-intensity factors for the fatigue cracks were determined from a shell-dynamics approach that simulated the dominant resonant frequencies. Life predictions were obtained using the NASGRO life prediction code. The results indicated that adequate life could not be demonstrated for initial crack lengths of the size that could be detected by traditional NDE techniques.

Prediction of Injuries and Injury Types in Army Basic Training, Infantry, Armor, and Cavalry Trainees Using a Common Fitness Screen

PubMed Central

Sefton, JoEllen M.; Lohse, K. R.; McAdam, J. S.

2016-01-01

Context: Musculoskeletal injuries (MSIs) are among the most important challenges facing our military. They influence career success and directly affect military readiness. Several methods of screening initial entry training (IET) soldiers are being tested in an effort to predict which soldiers will sustain an MSI and to develop injury-prevention programs. The Army 1-1-1 Fitness Assessment was examined to determine if it could be used as a screening and MSI prediction mechanism in male IET soldiers. Objective: To determine if a relationship existed among the Army 1-1-1 Fitness Assessment results and MSI, MSI type, and program of instruction (POI) in male IET soldiers. Design: Retrospective cohort study. Setting: Fort Benning, Georgia. Patients or Other Participants: Male Army IET soldiers (N = 1788). Main Outcome Measure(s): The likelihood of sustaining acute and overuse MSI was modelled using separate logistic regression analyses. The POI, run time, push-ups and sit-ups (combined into a single score), and IET soldier age were tested as predictors in a series of linear models. Results: With POI controlled, slower run time, fewer push-ups and sit-ups, and older age were positively correlated with acute MSI; only slower run time was correlated with overuse MSI. For both MSI types, cavalry POIs had a higher risk of acute and overuse MSIs than did basic combat training, armor, or infantry POIs. Conclusions: The 1-1-1 Fitness Assessment predicted both the likelihood of MSI occurrence and type of MSI (acute or overuse). One-mile (1.6-km) run time predicted both overuse and acute MSIs, whereas the combined push-up and sit-up score predicted only acute MSIs. The MSIs varied by type of training (infantry, basic, armor, cavalry), which allowed the development of prediction equations by POI. We determined 1-1-1 Fitness Assessment cutoff scores for each event, thereby allowing the evaluation to be used as an MSI screening mechanism for IET soldiers. PMID:28068160

Investigation of the collision line broadening problem as applicable to the NASA Optical Plume Anomaly Detection (OPAD) system, phase 1

NASA Astrophysics Data System (ADS)

Dean, Timothy C.; Ventrice, Carl A.

1995-05-01

As a final report for phase 1 of the project, the researchers are submitting to the Tennessee Tech Office of Research the following two papers (reprinted in this report): 'Collision Line Broadening Effects on Spectrometric Data from the Optical Plume Anomaly System (OPAD),' presented at the 30th AIAA/ASME/SAE/ASEE Joint Propulsion Conference, 27-29 June 1994, and 'Calculation of Collision Cross Sections for Atomic Line Broadening in the Plume of the Space Shuttle Main Engine (SSME),' presented at the IEEE Southeastcon '95, 26-29 March 1995. These papers fully state the problem and the progress made up to the end of NASA Fiscal Year 1994. The NASA OPAD system was devised to predict concentrations of anomalous species in the plume of the Space Shuttle Main Engine (SSME) through analysis of spectrometric data. The self absorption of the radiation of these plume anomalies is highly dependent on the line shape of the atomic transition of interest. The Collision Line Broadening paper discusses the methods used to predict line shapes of atomic transitions in the environment of a rocket plume. The Voigt profile is used as the line shape factor since both Doppler and collisional line broadening are significant. Methods used to determine the collisional cross sections are discussed and the results are given and compared with experimental data. These collisional cross sections are then incorporated into the current self absorbing radiative model and the predicted spectrum is compared to actual spectral data collected from the Stennis Space Center Diagnostic Test Facility rocket engine. The second paper included in this report investigates an analytical method for determining the cross sections for collision line broadening by molecular perturbers, using effective central force interaction potentials. These cross sections are determined for several atomic species with H2, one of the principal constituents of the SSME plume environment, and compared with experimental data.

2012 AAPS National Biotech Conference Open Forum: a perspective on the current state of immunogenicity prediction and risk management.

PubMed

Rajadhyaksha, Manoj; Subramanyam, Meena; Rup, Bonnie

2013-10-01

The immunogenicity profile of a biotherapeutic is determined by multiple product-, process- or manufacturing-, patient- and treatment-related factors and the bioanalytical methodology used to monitor for immunogenicity. This creates a complex situation that limits direct correlation of individual factors to observed immunogenicity rates. Therefore, mechanistic understanding of how these factors individually or in concert could influence the overall incidence and clinical risk of immunogenicity is crucial to provide the best benefit/risk profile for a given biotherapeutic in a given indication and to inform risk mitigation strategies. Advances in the field of immunogenicity have included development of best practices for monitoring anti-drug antibody development, categorization of risk factors contributing to immunogenicity, development of predictive tools, and development of effective strategies for risk management and mitigation. Thus, the opportunity to ask "where we are now and where we would like to go from here?" was the main driver for organizing an Open Forum on Improving Immunogenicity Risk Prediction and Management, conducted at the 2012 American Association of Pharmaceutical Scientists' (AAPS) National Biotechnology Conference in San Diego. The main objectives of the Forum include the following: to understand the nature of immunogenicity risk factors, to identify analytical tools used and animal models and management strategies needed to improve their predictive value, and finally to identify collaboration opportunities to improve the reliability of risk prediction, mitigation, and management. This meeting report provides the Forum participant's and author's perspectives on the barriers to advancing this field and recommendations for overcoming these barriers through collaborative efforts.

A new air quality monitoring and early warning system: Air quality assessment and air pollutant concentration prediction.

PubMed

Yang, Zhongshan; Wang, Jian

2017-10-01

Air pollution in many countries is worsening with industrialization and urbanization, resulting in climate change and affecting people's health, thus, making the work of policymakers more difficult. It is therefore both urgent and necessary to establish amore scientific air quality monitoring and early warning system to evaluate the degree of air pollution objectively, and predict pollutant concentrations accurately. However, the integration of air quality assessment and air pollutant concentration prediction to establish an air quality system is not common. In this paper, we propose a new air quality monitoring and early warning system, including an assessment module and forecasting module. In the air quality assessment module, fuzzy comprehensive evaluation is used to determine the main pollutants and evaluate the degree of air pollution more scientifically. In the air pollutant concentration prediction module, a novel hybridization model combining complementary ensemble empirical mode decomposition, a modified cuckoo search and differential evolution algorithm, and an Elman neural network, is proposed to improve the forecasting accuracy of six main air pollutant concentrations. To verify the effectiveness of this system, pollutant data for two cities in China are used. The result of the fuzzy comprehensive evaluation shows that the major air pollutants in Xi'an and Jinan are PM 10 and PM 2.5 respectively, and that the air quality of Xi'an is better than that of Jinan. The forecasting results indicate that the proposed hybrid model is remarkably superior to all benchmark models on account of its higher prediction accuracy and stability. Copyright © 2017 Elsevier Inc. All rights reserved.

Error reduction and parameter optimization of the TAPIR method for fast T1 mapping.

PubMed

Zaitsev, M; Steinhoff, S; Shah, N J

2003-06-01

A methodology is presented for the reduction of both systematic and random errors in T(1) determination using TAPIR, a Look-Locker-based fast T(1) mapping technique. The relations between various sequence parameters were carefully investigated in order to develop recipes for choosing optimal sequence parameters. Theoretical predictions for the optimal flip angle were verified experimentally. Inversion pulse imperfections were identified as the main source of systematic errors in T(1) determination with TAPIR. An effective remedy is demonstrated which includes extension of the measurement protocol to include a special sequence for mapping the inversion efficiency itself. Copyright 2003 Wiley-Liss, Inc.

Artificial neural network intelligent method for prediction

NASA Astrophysics Data System (ADS)

Trifonov, Roumen; Yoshinov, Radoslav; Pavlova, Galya; Tsochev, Georgi

2017-09-01

Accounting and financial classification and prediction problems are high challenge and researchers use different methods to solve them. Methods and instruments for short time prediction of financial operations using artificial neural network are considered. The methods, used for prediction of financial data as well as the developed forecasting system with neural network are described in the paper. The architecture of a neural network used four different technical indicators, which are based on the raw data and the current day of the week is presented. The network developed is used for forecasting movement of stock prices one day ahead and consists of an input layer, one hidden layer and an output layer. The training method is algorithm with back propagation of the error. The main advantage of the developed system is self-determination of the optimal topology of neural network, due to which it becomes flexible and more precise The proposed system with neural network is universal and can be applied to various financial instruments using only basic technical indicators as input data.

The Extent and Prediction of Heavy Metal Pollution in Soils of Shahrood and Damghan, Iran.

PubMed

Sakizadeh, Mohamad; Mirzaei, Rouhollah; Ghorbani, Hadi

2015-12-01

The levels of 12 heavy metals (Ag, Ba, Be, Cd, Co, Cr, Cu, Ni, Pb, Tl, V, Zn) were considered in 229 soil samples in Semnan Province, Iran. To discriminate between natural and anthropogenic inputs of heavy metals, factor analysis was used. Seven factors accounting for 90.5 % of the total variance were extracted. The mining and agricultural activities along with geogenic sources have been attributed as the main causes of the levels of heavy metals in the study area. The partial least squares regression was utilized to predict the level of soil pollution index (SPI) considering the concentrations of 12 heavy metals. The eigenvectors from the first three PLS represented more than 98 % of the overall variance. The correlation coefficient between the observed and predicted SPI was 0.99 indicating the high efficiency of this method. The resultant coefficient of determination for three PLS components was 0.984 confirming the predictive ability of this method.

Prediction of Backbreak in Open-Pit Blasting Operations Using the Machine Learning Method

NASA Astrophysics Data System (ADS)

Khandelwal, Manoj; Monjezi, M.

2013-03-01

Backbreak is an undesirable phenomenon in blasting operations. It can cause instability of mine walls, falling down of machinery, improper fragmentation, reduced efficiency of drilling, etc. The existence of various effective parameters and their unknown relationships are the main reasons for inaccuracy of the empirical models. Presently, the application of new approaches such as artificial intelligence is highly recommended. In this paper, an attempt has been made to predict backbreak in blasting operations of Soungun iron mine, Iran, incorporating rock properties and blast design parameters using the support vector machine (SVM) method. To investigate the suitability of this approach, the predictions by SVM have been compared with multivariate regression analysis (MVRA). The coefficient of determination (CoD) and the mean absolute error (MAE) were taken as performance measures. It was found that the CoD between measured and predicted backbreak was 0.987 and 0.89 by SVM and MVRA, respectively, whereas the MAE was 0.29 and 1.07 by SVM and MVRA, respectively.

The evolution of rotating stars. III - Predicted surface rotation velocities for stars which conserve total angular momentum

NASA Technical Reports Server (NTRS)

Endal, A. S.; Sofia, S.

1979-01-01

Predicted surface rotation velocities for Population I stars at 10, 7, 5, 3, and 1.5 solar masses are presented. The surface velocities were computed for angular momentum with no radial redistribution, complete redistribution, and partial redistribution as predicted by consideration of circulation currents in rotating stars. Near the main sequence, rotational effects can reduce the moment of inertia of a star, so nonrotating models underestimate the expected velocities for evolving stars. On the red giant branch, angular momentum redistribution reduces the surface velocity by a factor of 2 or more, relative to the velocity expected for no radial redistribution. This removes the discrepancy between predicted and observed rotation rates for the K giants and makes it unlikely that these stars lose significant amounts of angular momentum by stellar winds. Calculations indicate that improved observations of the red giants in the Hyades cluster can be used to determine how angular momentum is redistributed by convection

Analytical Solution to the Pneumatic Transient Rod System at ACRR

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

Fehr, Brandon Michael

2016-01-08

The ACRR pulse is pneumatically driven by nitrogen in a system of pipes, valves and hoses up to the connection of the pneumatic system and mechanical linkages of the transient rod (TR). The main components of the TR pneumatic system are the regulator, accumulator, solenoid valve and piston-cylinder assembly. The purpose of this analysis is to analyze the flow of nitrogen through the TR pneumatic system in order to develop a motion profile of the piston during the pulse and be able to predict the pressure distributions inside both the cylinder and accumulators. The predicted pressure distributions will be validatedmore » against pressure transducer data, while the motion profile will be compared to proximity switch data. By predicting the motion of the piston, pulse timing will be determined and provided to the engineers/operators for verification. The motion profile will provide an acceleration distribution to be used in Razorback to more accurately predict reactivity insertion into the system.« less

Dynamic properties and damping predictions for laminated plates: High order theories - Timoshenko beam

NASA Astrophysics Data System (ADS)

Diveyev, Bohdan; Konyk, Solomija; Crocker, Malcolm J.

2018-01-01

The main aim of this study is to predict the elastic and damping properties of composite laminated plates. This problem has an exact elasticity solution for simple uniform bending and transverse loading conditions. This paper presents a new stress analysis method for the accurate determination of the detailed stress distributions in laminated plates subjected to cylindrical bending. Some approximate methods for the stress state predictions for laminated plates are presented here. The present method is adaptive and does not rely on strong assumptions about the model of the plate. The theoretical model described here incorporates deformations of each sheet of the lamina, which account for the effects of transverse shear deformation, transverse normal strain-stress and nonlinear variation of displacements with respect to the thickness coordinate. Predictions of the dynamic and damping values of laminated plates for various geometrical, mechanical and fastening properties are presented. Comparison with the Timoshenko beam theory is systematically made for analytical and approximation variants.

Learning and Study Strategies Inventory subtests and factors as predictors of National Board of Chiropractic Examiners Part 1 examination performance.

PubMed

Schutz, Christine M; Dalton, Leanne; Tepe, Rodger E

2013-01-01

This study was designed to extend research on the relationship between chiropractic students' learning and study strategies and national board examination performance. Sixty-nine first trimester chiropractic students self-administered the Learning and Study Strategies Inventory (LASSI). Linear trends tests (for continuous variables) and Mantel-Haenszel trend tests (for categorical variables) were utilized to determine if the 10 LASSI subtests and 3 factors predicted low, medium and high levels of National Board of Chiropractic Examiners (NBCE) Part 1 scores. Multiple regression was performed to predict overall mean NBCE examination scores using the 3 LASSI factors as predictor variables. Four LASSI subtests (Anxiety, Concentration, Selecting Main Ideas, Test Strategies) and one factor (Goal Orientation) were significantly associated with NBCE examination levels. One factor (Goal Orientation) was a significant predictor of overall mean NBCE examination performance. Learning and study strategies are predictive of NBCE Part 1 examination performance in chiropractic students. The current study found LASSI subtests Anxiety, Concentration, Selecting Main Ideas, and Test Strategies, and the Goal-Orientation factor to be significant predictors of NBCE scores. The LASSI may be useful to educators in preparing students for academic success. Further research is warranted to explore the effects of learning and study strategies training on GPA and NBCE performance.

A Rainfall- and Temperature-Driven Abundance Model for Aedes albopictus Populations

PubMed Central

Tran, Annelise; L’Ambert, Grégory; Lacour, Guillaume; Benoît, Romain; Demarchi, Marie; Cros, Myriam; Cailly, Priscilla; Aubry-Kientz, Mélaine; Balenghien, Thomas; Ezanno, Pauline

2013-01-01

The mosquito Aedes (Stegomyia) albopictus (Skuse) (Diptera: Culicidae) is an invasive species which has colonized Southern Europe in the last two decades. As it is a competent vector for several arboviruses, its spread is of increasing public health concern, and there is a need for appropriate monitoring tools. In this paper, we have developed a modelling approach to predict mosquito abundance over time, and identify the main determinants of mosquito population dynamics. The model is temperature- and rainfall-driven, takes into account egg diapause during unfavourable periods, and was used to model the population dynamics of Ae. albopictus in the French Riviera since 2008. Entomological collections of egg stage from six locations in Nice conurbation were used for model validation. We performed a sensitivity analysis to identify the key parameters of the mosquito population dynamics. Results showed that the model correctly predicted entomological field data (Pearson r correlation coefficient values range from 0.73 to 0.93). The model’s main control points were related to adult’s mortality rates, the carrying capacity in pupae of the environment, and the beginning of the unfavourable period. The proposed model can be efficiently used as a tool to predict Ae. albopictus population dynamics, and to assess the efficiency of different control strategies. PMID:23624579

Arms race between selfishness and policing: two-trait quantitative genetic model for caste fate conflict in eusocial Hymenoptera.

PubMed

Dobata, Shigeto

2012-12-01

Policing against selfishness is now regarded as the main force maintaining cooperation, by reducing costly conflict in complex social systems. Although policing has been studied extensively in social insect colonies, its coevolution against selfishness has not been fully captured by previous theories. In this study, I developed a two-trait quantitative genetic model of the conflict between selfish immature females (usually larvae) and policing workers in eusocial Hymenoptera over the immatures' propensity to develop into new queens. This model allows for the analysis of coevolution between genomes expressed in immatures and workers that collectively determine the immatures' queen caste fate. The main prediction of the model is that a higher level of polyandry leads to a smaller fraction of queens produced among new females through caste fate policing. The other main prediction of the present model is that, as a result of arms race, caste fate policing by workers coevolves with exaggerated selfishness of the immatures achieving maximum potential to develop into queens. Moreover, the model can incorporate genetic correlation between traits, which has been largely unexplored in social evolution theory. This study highlights the importance of understanding social traits as influenced by the coevolution of conflicting genomes. © 2012 The Author. Evolution© 2012 The Society for the Study of Evolution.

Quality of life, functional impairment and social factors as determinants of nutritional status in older adults: The VERISAÚDE study.

PubMed

Maseda, Ana; Diego-Diez, Clara; Lorenzo-López, Laura; López-López, Rocío; Regueiro-Folgueira, Laura; Millán-Calenti, José C

2018-06-01

Malnutrition is an important and growing health problem in elderly people. The main aim of this research was to examine the relationship between socio-demographic factors, social resources, functional status and quality of life and malnutrition or risk of malnutrition in elders. A cross-sectional study was conducted with a representative sample of 749 community-dwelling elders aged 65 years and over. A comprehensive assessment was carried out, including the collection of socio-demographic factors, social resources by the Older Americans Resources and Services Scale, nutritional status by the Mini-Nutritional Assessment-Short Form, functional status by the Lawton's instrumental activities of daily living scale and quality of life by the World Health Organizations's Quality of Life measure-brief version (WHOQOL-BREF). Being female, the presence of totally impaired social resources and low scores in the physical health domain of the WHOQOL-BREF were the strongest determinants of malnutrition/risk of malnutrition. This model predicted 85.7% of the cases correctly. In men, the best determinants were being unmarried and having poor satisfaction with their health, with a percentage of 89.8% of cases of poor nutritional status correctly predicted. The best determinant for women was also the physical health domain of the WHOQOL-BREF, reaching a correct prediction of 83.0% of malnutrition/risk of it. Nutritional status assessment and potential determinant factors should be incorporated as part of comprehensive assessments for early identification of malnutrition and to determine appropriate intervention strategies to address this public health problem in older adults. Copyright © 2017 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Reconciling phase diffusion and Hartree-Fock approximation in condensate systems

NASA Astrophysics Data System (ADS)

Giorgi, Gian Luca; de Pasquale, Ferdinando

2012-01-01

Despite the weakly interacting regime, the physics of Bose-Einstein condensates is widely affected by particle-particle interactions. They determine quantum phase diffusion, which is known to be the main cause of loss of coherence. Studying a simple model of two interacting Bose systems, we show how to predict the appearance of phase diffusion beyond the Bogoliubov approximation, providing a self-consistent treatment in the framework of a generalized Hartree-Fock-Bogoliubov perturbation theory.

Improved Performance and Safety for High Energy Batteries Through Use of Hazard Anticipation and Capacity Prediction

NASA Technical Reports Server (NTRS)

Atwater, Terrill

1993-01-01

Prediction of the capacity remaining in used high rate, high energy batteries is important information to the user. Knowledge of the capacity remaining in used batteries results in better utilization. This translates into improved readiness and cost savings due to complete, efficient use. High rate batteries, due to their chemical nature, are highly sensitive to misuse (i.e., over discharge or very high rate discharge). Battery failure due to misuse or manufacturing defects could be disastrous. Since high rate, high energy batteries are expensive and energetic, a reliable method of predicting both failures and remaining energy has been actively sought. Due to concerns over safety, the behavior of lithium/sulphur dioxide cells at different temperatures and current drains was examined. The main thrust of this effort was to determine failure conditions for incorporation in hazard anticipation circuitry. In addition, capacity prediction formulas have been developed from test data. A process that performs continuous, real-time hazard anticipation and capacity prediction was developed. The introduction of this process into microchip technology will enable the production of reliable, safe, and efficient high energy batteries.

Predicting the locations of naturally fishless lakes

USGS Publications Warehouse

Schilling, Emily Gaenzle; Loftin, C.S.; Degoosh, K.E.; Huryn, Alexander D.; Webster, K.E.

2008-01-01

1. Fish have been introduced into many previously fishless lakes throughout North America over the past 100+ years. It is difficult to determine the historical distribution of fishless lakes, however, because these introductions have not always been well-documented. 2. Due to its glacial history and low human population density, the state of Maine (U.S.A.) may host the greatest number of naturally fishless lakes in the northeastern United States. However, less than one-quarter of Maine's 6000+ lakes have been surveyed for fish presence, and no accurate assessments of either the historical or current abundance and distribution of fishless lakes exist. 3. We developed methods to assess the abundance and distribution of Maine's naturally fishless lakes (0.6-10.1 ha). We hypothesized that the historical distribution of fishless lakes across a landscape is controlled by geomorphic and geographic conditions. 4. We used ArcGIS to identify landscape-scale geomorphic and geographic factors (e.g. connectivity, surrounding slope) correlated with fish absence in two geomorphic regions of Maine - the western and interior mountains and the eastern lowlands and foothills. By using readily available geographic information systems data our method was not limited to field-visited sites. We estimated the likelihood that a particular lake is fishless with a stepwise logistic regression model developed for each region. 5. The absence of fish from western lakes is related to altitude (+), minimum percent slope in the 500 m buffer (+), maximum percent slope in the 500 m buffer (+) and percent cover of herbaceous-emergent wetland in 1000 m buffer (-). The absence of fish from eastern lakes is related to the lack of a stream within 50 m of the lake. 6. The models predict that a total of 4% (131) of study lakes in the two regions were historically fishless, with the eastern region hosting a greater proportion than the western region. 7. We verified the model predictions with two complementary approaches. First we visited 21 lakes predicted to be fishless and assessed current fish presence with gillnetting. Second, we used paleolimnological techniques based on the abundance of Chaoborus americanus mandibles in the bottom segments of sediment cores. Fifteen of the 21 lakes predicted to be fishless currently contain fish. Paleolimnological evidence, however, suggests that nine of the 15 lakes were historically fishless and thus were subject to undocumented fish introductions. 8. Our approach efficiently predicts the distribution Maine's naturally fishless lakes, and our results indicate that these habitats have declined due to fish introductions. Our method could be applied to other regions with similar geographic and geomorphic constraints on fish distributions as a tool to enhance conservation of a limited resource that provides habitat for unique biological communities. ?? 2007 Blackwell Publishing Ltd.

Fully Ab-Initio Determination of the Thermoelectric Properties of Half-Heusler NiTiSn: Crucial Role of Interstitial Ni Defects.

PubMed

Berche, Alexandre; Jund, Philippe

2018-05-23

For thermoelectric applications, ab initio methods generally fail to predict the transport properties of the materials because of their inability to predict properly the carrier concentrations that control the electronic properties. In this work, a methodology to fill in this gap is applied on the NiTiSn half Heusler phase. For that, we show that the main defects act as donor of electrons and are responsible of the electronic properties of the material. Indeed, the presence of Ni i interstitial defects explains the experimental valence band spectrum and its associated band gap reported in the literature. Moreover, combining the DOS of the solid solutions with the determination of the energy of formation of charged defects, we show that Ni i defects are also responsible of the measured carrier concentration in experimentally supposed "pure" NiTiSn compounds. Subsequently the thermoelectric properties of NiTiSn can be calculated using a fully ab initio description and an overall correct agreement with experiments is obtained. This methodology can be extended to predict the result of extrinsic doping and thus to select the most efficient dopant for specific thermoelectric applications.

Model for predicting peak expiratory flow rate of Nigerian workers in a cement factory in Itori, Ogun State, Nigeria.

PubMed

Ismaila, Salami Olasunkanmi; Akanbi, Olusegun Gabriel; Olaoniye, Wasiu

2015-01-01

The main aim of the study was to propose a model for predicting the peak expiratory flow rate (PEFR) of Nigerian workers in a cement factory. Sixty randomly selected non-smoker and healthy workers (30 in production sections, 30 in the administrative section of the factory) participated in the study. Their physical characteristics and PEFR were measured. Multiple correlations using SPSS version 16.0 were performed on the data. The values of PEFR, using the obtained model, were compared with the measured values using a two-tailed t test. There were positive correlations among age, height and PEFR. A prediction equation for PEFR based on age, height, weight and years of exposure (experience) was obtained with R² = .843 (p < 0.001). The developed model will be useful for the management in determining PEFR of workers in the cement industry for possible medical attention.

Prediction of surface roughness and cutting force under MQL turning of AISI 4340 with nano fluid by using response surface methodology

NASA Astrophysics Data System (ADS)

Patole, Pralhad B.; Kulkarni, Vivek V.

2018-06-01

This paper presents an investigation into the minimum quantity lubrication mode with nano fluid during turning of alloy steel AISI 4340 work piece material with the objective of experimental model in order to predict surface roughness and cutting force and analyze effect of process parameters on machinability. Full factorial design matrix was used for experimental plan. According to design of experiment surface roughness and cutting force were measured. The relationship between the response variables and the process parameters is determined through the response surface methodology, using a quadratic regression model. Results show how much surface roughness is mainly influenced by feed rate and cutting speed. The depth of cut exhibits maximum influence on cutting force components as compared to the feed rate and cutting speed. The values predicted from the model and experimental values are very close to each other.

Modelling biological invasions: species traits, species interactions, and habitat heterogeneity.

PubMed

Cannas, Sergio A; Marco, Diana E; Páez, Sergio A

2003-05-01

In this paper we explore the integration of different factors to understand, predict and control ecological invasions, through a general cellular automaton model especially developed. The model includes life history traits of several species in a modular structure interacting multiple cellular automata. We performed simulations using field values corresponding to the exotic Gleditsia triacanthos and native co-dominant trees in a montane area. Presence of G. triacanthos juvenile bank was a determinant condition for invasion success. Main parameters influencing invasion velocity were mean seed dispersal distance and minimum reproductive age. Seed production had a small influence on the invasion velocity. Velocities predicted by the model agreed well with estimations from field data. Values of population density predicted matched field values closely. The modular structure of the model, the explicit interaction between the invader and the native species, and the simplicity of parameters and transition rules are novel features of the model.

Observations of magnetic fields on solar-type stars

NASA Technical Reports Server (NTRS)

Marcy, G. W.

1982-01-01

Magnetic-field observations were carried out for 29 G and K main-sequence stars. The area covering-factors of magnetic regions tends to be greater in the K dwarfs than in the G dwarfs. However, no spectral-type dependence is found for the field strengths, contrary to predictions that pressure equilibrium with the ambient photospheric gas pressure would determine the surface field strengths. Coronal soft X-ray fluxes from the G and K dwarfs correlate well with the fraction of the stellar surface covered by magnetic regions. The dependence of coronal soft X-ray fluxes on photospheric field strengths is consistent with Stein's predicted generation-rates for Alfven waves. These dependences are inconsistent with the one dynamo model for which a specific prediction is offered. Finally, time variability of magnetic fields is seen on the two active stars that have been extensively monitored. Significant changes in magnetic fields are seen to occur on timescales as short as one day.

Why are men more likely to support group-based dominance than women? The mediating role of gender identification.

PubMed

Dambrun, Michaël; Duarte, Sandra; Guimond, Serge

2004-06-01

Arguing from a sociobiological perspective, Sidanius and Pratto (1999) have shown that the male/female difference in social dominance orientation (SDO) is largely invariant across cultural, situational and contextual boundaries. The main objective of this study was to test the validity of Social Dominance Theory (SDT) by contrasting it with a model derived from Social Identity Theory (SIT). More specifically, while SIT predicts that gender identification mediates the effect of gender on SDO, SDT predicts the reverse. According to SDT, the degree to which men and women endorse status legitimizing ideology should determine to what extent they identify with their gender group. Using structural equation modelling, the results provide strong support for the SIT model and no support for SDT predictions. Implications of these results for social dominance theory and its sociobiologically based invariance hypothesis are discussed.

Fatigue life analysis of a turboprop reduction gearbox

NASA Technical Reports Server (NTRS)

Lewicki, D. G.; Black, J. D.; Savage, M.; Coy, J. J.

1985-01-01

A fatigue life analysis of the Allison T56/501 turboprop reduction gearbox was developed. The life and reliability of the gearbox was based on the lives and reliabilities of the main power train bearings and gears. The bearing and gear lives were determined using the Lundberg-Palmgren theory and a mission profile. The five planet bearing set had the shortest calculated life among the various gearbox components, which agreed with field experience where the planet bearing had the greatest incidences of failure. The analytical predictions of relative lives among the various bearings were in reasonable agreement with field experience. The predicted gearbox life was in excellent agreement with field data when the material life adjustment factors alone were used. The gearbox had a lower predicted life in comparison with field data when no life adjustment factors were used or when lubrication life adjustment factors were used either alone or in combination with the material factors.

Fatigue life analysis of a turboprop reduction gearbox

NASA Technical Reports Server (NTRS)

Lewicki, D. G.; Coy, J. J.; Black, J. D.; Savage, M.

1986-01-01

A fatigue life analysis of the Allison T56/501 turboprop reduction gearbox was developed. The life and reliability of the gearbox was based on the lives and reliabilities of the main power train bearings and gears. The bearing and gear lives were determined using the Lundberg-Palmgren theory and a mission profile. The five planet bearing set had the shortest calculated life among the various gearbox components, which agreed with field experience where the planet bearing had the greatest incidences of failure. The analytical predictions of relative lives among the various bearings were in reasonable agreement with field experience. The predicted gearbox life was in excellent agreement with field data when the material life adjustment factors alone were used. The gearbox had a lower predicted life in comparison with field data when no life adjustment factors were used or when lubrication life adjustment factors were used either alone or in combination with the material factors.

Stoichio-Kinetic Modeling of Fenton Chemistry in a Meat-Mimetic Aqueous-Phase Medium.

PubMed

Oueslati, Khaled; Promeyrat, Aurélie; Gatellier, Philippe; Daudin, Jean-Dominique; Kondjoyan, Alain

2018-05-31

Fenton reaction kinetics, which involved an Fe(II)/Fe(III) oxidative redox cycle, were studied in a liquid medium that mimics meat composition. Muscle antioxidants (enzymes, peptides, and vitamins) were added one by one in the medium to determine their respective effects on the formation of superoxide and hydroxyl radicals. A stoichio-kinetic mathematical model was used to predict the formation of these radicals under different iron and H 2 O 2 concentrations and temperature conditions. The difference between experimental and predicted results was mainly due to iron reactivity, which had to be taken into account in the model, and to uncertainties on some of the rate constant values introduced in the model. This stoichio-kinetic model will be useful to predict oxidation during meat processes, providing it can be completed to take into account the presence of myoglobin in the muscle.

Predicting stellar angular diameters from V, IC, H and K photometry

NASA Astrophysics Data System (ADS)

Adams, Arthur D.; Boyajian, Tabetha S.; von Braun, Kaspar

2018-01-01

Determining the physical properties of microlensing events depends on having accurate angular sizes of the source star. Using long baseline optical interferometry, we are able to measure the angular sizes of nearby stars with uncertainties ≤2 per cent. We present empirically derived relations of angular diameters which are calibrated using both a sample of dwarfs/subgiants and a sample of giant stars. These relations are functions of five colour indices in the visible and near-infrared, and have uncertainties of 1.8-6.5 per cent depending on the colour used. We find that a combined sample of both main-sequence and evolved stars of A-K spectral types is well fitted by a single relation for each colour considered. We find that in the colours considered, metallicity does not play a statistically significant role in predicting stellar size, leading to a means of predicting observed sizes of stars from colour alone.

Experimental and statistical post-validation of positive example EST sequences carrying peroxisome targeting signals type 1 (PTS1)

PubMed Central

Lingner, Thomas; Kataya, Amr R. A.; Reumann, Sigrun

2012-01-01

We recently developed the first algorithms specifically for plants to predict proteins carrying peroxisome targeting signals type 1 (PTS1) from genome sequences.1 As validated experimentally, the prediction methods are able to correctly predict unknown peroxisomal Arabidopsis proteins and to infer novel PTS1 tripeptides. The high prediction performance is primarily determined by the large number and sequence diversity of the underlying positive example sequences, which mainly derived from EST databases. However, a few constructs remained cytosolic in experimental validation studies, indicating sequencing errors in some ESTs. To identify erroneous sequences, we validated subcellular targeting of additional positive example sequences in the present study. Moreover, we analyzed the distribution of prediction scores separately for each orthologous group of PTS1 proteins, which generally resembled normal distributions with group-specific mean values. The cytosolic sequences commonly represented outliers of low prediction scores and were located at the very tail of a fitted normal distribution. Three statistical methods for identifying outliers were compared in terms of sensitivity and specificity.” Their combined application allows elimination of erroneous ESTs from positive example data sets. This new post-validation method will further improve the prediction accuracy of both PTS1 and PTS2 protein prediction models for plants, fungi, and mammals. PMID:22415050

Experimental and statistical post-validation of positive example EST sequences carrying peroxisome targeting signals type 1 (PTS1).

PubMed

Lingner, Thomas; Kataya, Amr R A; Reumann, Sigrun

2012-02-01

We recently developed the first algorithms specifically for plants to predict proteins carrying peroxisome targeting signals type 1 (PTS1) from genome sequences. As validated experimentally, the prediction methods are able to correctly predict unknown peroxisomal Arabidopsis proteins and to infer novel PTS1 tripeptides. The high prediction performance is primarily determined by the large number and sequence diversity of the underlying positive example sequences, which mainly derived from EST databases. However, a few constructs remained cytosolic in experimental validation studies, indicating sequencing errors in some ESTs. To identify erroneous sequences, we validated subcellular targeting of additional positive example sequences in the present study. Moreover, we analyzed the distribution of prediction scores separately for each orthologous group of PTS1 proteins, which generally resembled normal distributions with group-specific mean values. The cytosolic sequences commonly represented outliers of low prediction scores and were located at the very tail of a fitted normal distribution. Three statistical methods for identifying outliers were compared in terms of sensitivity and specificity." Their combined application allows elimination of erroneous ESTs from positive example data sets. This new post-validation method will further improve the prediction accuracy of both PTS1 and PTS2 protein prediction models for plants, fungi, and mammals.

Fate of heavy metals during municipal solid waste incineration.

PubMed

Abanades, S; Flamant, G; Gagnepain, B; Gauthier, D

2002-02-01

A thermodynamic analysis was performed to determine whether it is suitable to predict the heavy metal (HM) speciation during the Municipal Solid Waste Incineration process. The fate of several selected metals (Cd, Pb, Zn, Cr, Hg, As, Cu, Co, Ni) during incineration was theoretically investigated. The equilibrium analysis predicted the metal partitioning during incineration and determined the impact of operating conditions (temperature and gas composition) on their speciation. The study of the gas composition influence was based on the effects of the contents of oxygen (reducing or oxidising conditions) and chlorine on the HM partitioning. The theoretical HM speciation which was calculated in a complex system representing a burning sample of Municipal Solid Waste can explain the real partitioning (obtained from literature results) of all metals among the various ashes except for Pb. Then, the results of the thermodynamic study were compared with those of characterisation of real incinerator residues, using complementary techniques (chemical extraction series and X-ray micro-analyses). These analysis were performed to determine experimentally the speciation of the three representative metals Cr, Pb, and Zn. The agreement is good for Cr and Zn but not for Pb again, which mainly shows unleachable chemical speciations in the residues. Pb tends to remain in the bottom ash whereas thermodynamics often predicts its complete volatilisation under chlorides, and thus its presence exclusively in fly ash.

Socio-ecological predictors of participation and dropout in organised sports during childhood

PubMed Central

2014-01-01

Background The purpose of this study was to explore the socio-ecological determinants of participation and dropout in organised sports in a nationally-representative sample of Australian children. Methods Data were drawn from Waves 3 and 4 of the Longitudinal Study of Australian Children. In total, 4042 children aged 8.25 (SD = 0.44) years at baseline were included, with 24-months between Waves. Socio-ecological predictors were reported by parents and teachers, while cognitive and health measures were assessed by trained professionals. All predictors were assessed at age 8, and used to predict participation and dropout by age 10. Results Seven variables at age 8 were shown to positively predict participation in organised sports at age 10. These included: sex (boy); fewer people in household; higher household income; main language spoken at home (English); higher parental education; child taken to a sporting event; and, access to a specialist PE teacher during primary school. Four variables predicted dropout from organised sports by age 10: lower household income; main language spoken at home (non-English); lower parental education; and, child not taken to a sporting event. Conclusions The interplay between child sex, socioeconomic indicators, and parental support is important in predicting children’s participation in organised sports. Multilevel and multicomponent interventions to promote participation and prevent dropout should be underpinned by the Socio-Ecological Model and targeted to high risk populations using multiple levels of risk. PMID:24885978

Do developmental milestones at 4, 8, 12 and 24 months predict IQ at 5-6 years old? Results of the EDEN mother-child cohort.

PubMed

Peyre, Hugo; Charkaluk, Marie-Laure; Forhan, Anne; Heude, Barbara; Ramus, Franck

2017-03-01

The present study aims: (i) to determine how well developmental milestones at 4, 8, 12 and 24 months may predict IQ at 5-6 years old, (ii) to identify cognitive domains during the first two years that best predict later IQ and (iii) to determine whether children with IQ in the normal range at 5-6 years old may differ from disabled (IQ < 70) and gifted children (IQ > 130) with regard to their early cognitive development. The main developmental milestones were collected through self-administered questionnaires rated by parents at 4, 8, 12 and 24 months and through parental questionnaires administered by a trained interviewer and questionnaires completed following a medical examination at 12 months. These questionnaires were derived from the Brunet-Lézine Psychomotor Development Scale and they addressed several cognitive domains (gross and fine motor skills, language and socialization). (i) Developmental milestones predict a substantial part of the later IQ variance from 24 months (R 2  ∼ 20%). (ii) Early language skills more strongly predict later IQ than the other cognitive domains. (iii) Several cognitive domains, but particularly language skills, predict disabled children at 5-6 years old (from the age of 8 months) and gifted children (from the age of 12 months). The present study provides valuable information for early developmental assessment and could contribute to a better understanding of intellectual development. Copyright © 2016 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.

Dengue: recent past and future threats

PubMed Central

Rogers, David J.

2015-01-01

This article explores four key questions about statistical models developed to describe the recent past and future of vector-borne diseases, with special emphasis on dengue: (1) How many variables should be used to make predictions about the future of vector-borne diseases?(2) Is the spatial resolution of a climate dataset an important determinant of model accuracy?(3) Does inclusion of the future distributions of vectors affect predictions of the futures of the diseases they transmit?(4) Which are the key predictor variables involved in determining the distributions of vector-borne diseases in the present and future?Examples are given of dengue models using one, five or 10 meteorological variables and at spatial resolutions of from one-sixth to two degrees. Model accuracy is improved with a greater number of descriptor variables, but is surprisingly unaffected by the spatial resolution of the data. Dengue models with a reduced set of climate variables derived from the HadCM3 global circulation model predictions for the 1980s are improved when risk maps for dengue's two main vectors (Aedes aegypti and Aedes albopictus) are also included as predictor variables; disease and vector models are projected into the future using the global circulation model predictions for the 2020s, 2040s and 2080s. The Garthwaite–Koch corr-max transformation is presented as a novel way of showing the relative contribution of each of the input predictor variables to the map predictions. PMID:25688021

Modelling morphology evolution during solidification of IPP in processing conditions

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

Pantani, R., E-mail: rpantani@unisa.it, E-mail: fedesantis@unisa.it, E-mail: vsperanza@unisa.it, E-mail: gtitomanlio@unisa.it; De Santis, F., E-mail: rpantani@unisa.it, E-mail: fedesantis@unisa.it, E-mail: vsperanza@unisa.it, E-mail: gtitomanlio@unisa.it; Speranza, V., E-mail: rpantani@unisa.it, E-mail: fedesantis@unisa.it, E-mail: vsperanza@unisa.it, E-mail: gtitomanlio@unisa.it

During polymer processing, crystallization takes place during or soon after flow. In most of cases, the flow field dramatically influences both the crystallization kinetics and the crystal morphology. On their turn, crystallinity and morphology affect product properties. Consequently, in the last decade, researchers tried to identify the main parameters determining crystallinity and morphology evolution during solidification In processing conditions. In this work, we present an approach to model flow-induced crystallization with the aim of predicting the morphology after processing. The approach is based on: interpretation of the FIC as the effect of molecular stretch on the thermodynamic crystallization temperature; modelingmore » the molecular stretch evolution by means of a model simple and easy to be implemented in polymer processing simulation codes; identification of the effect of flow on nucleation density and spherulites growth rate by means of simple experiments; determination of the condition under which fibers form instead of spherulites. Model predictions reproduce most of the features of final morphology observed in the samples after solidification.« less

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

PubMed

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

2017-12-01

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

Degradation Prediction Model Based on a Neural Network with Dynamic Windows

PubMed Central

Zhang, Xinghui; Xiao, Lei; Kang, Jianshe

2015-01-01

Tracking degradation of mechanical components is very critical for effective maintenance decision making. Remaining useful life (RUL) estimation is a widely used form of degradation prediction. RUL prediction methods when enough run-to-failure condition monitoring data can be used have been fully researched, but for some high reliability components, it is very difficult to collect run-to-failure condition monitoring data, i.e., from normal to failure. Only a certain number of condition indicators in certain period can be used to estimate RUL. In addition, some existing prediction methods have problems which block RUL estimation due to poor extrapolability. The predicted value converges to a certain constant or fluctuates in certain range. Moreover, the fluctuant condition features also have bad effects on prediction. In order to solve these dilemmas, this paper proposes a RUL prediction model based on neural network with dynamic windows. This model mainly consists of three steps: window size determination by increasing rate, change point detection and rolling prediction. The proposed method has two dominant strengths. One is that the proposed approach does not need to assume the degradation trajectory is subject to a certain distribution. The other is it can adapt to variation of degradation indicators which greatly benefits RUL prediction. Finally, the performance of the proposed RUL prediction model is validated by real field data and simulation data. PMID:25806873

Relation between working memory and self-regulation capacities and the level of social skills acquisition in people with moderate intellectual disability.

PubMed

Dučić, Bojan; Gligorović, Milica; Kaljača, Svetlana

2018-03-01

Social competence deficit is one of the main characteristics of intellectual disability. The aim of this paper is to determine the influence of working memory (WM) and self-regulation (SR) on social skills in persons with moderate intellectual disability (MID). The sample included 41 participants with MID, aged 14-21. Memorizing animals and maze tasks were used for WM assessment. SR skills were assessed by the Behavioral Multitask Batteries. Social skills were rated by the Socialization subscale from the Adaptive Behavior Assessment System II, which consists of two parts. Social skills part could mainly be predicted from SR scores (β = -.441), followed by WM (β = .390) and IQ score (β = .382). Only WM score (β = .494) had a predictive value for Leisure time part. As WM had a greater influence on social skills, incorporating WM training into programmes for improving social skills in persons with MID should be considered. © 2017 John Wiley & Sons Ltd.

Adaptation des systèmes de production agricole au changement climatiqueAdaptation of agricultural production systems to climatic change

NASA Astrophysics Data System (ADS)

Seguin, Bernard

2003-06-01

The adaptation of agricultural production systems to climatic change needs to firstly consider the predictable impact upon vegetal production, using the available knowledge on crop ecophysiology applied for simulating the effects of climate scenarios, including the increase of atmospheric CO 2. The predicted consequences are firstly presented in general terms. They are thereafter detailed for each main type of production in France (annual crops, pastures and perennial crops), taking into account recent observations about the evolution of climate and related consequences on crop phenology (especially fruit trees and vine). They lead to identify the main lines for the adaptation at the level of present cropping systems, considered as geographically stable. However, this level needs to be completed by a second one, corresponding to a possible shift in latitude or altitude, as well as the introduction of new crops. Ultimately, a third level of adaptation will correspond to the evolution of territories and land use, whose determinants will be discussed in the conclusion. To cite this article: B. Seguin, C. R. Geoscience 335 (2003).

Computation of inlet reference plane flow-field for a subscale free-jet forebody/inlet model and comparison to experimental data

NASA Astrophysics Data System (ADS)

McClure, M. D.; Sirbaugh, J. R.

1991-02-01

The computational fluid dynamics (CFD) computer code PARC3D was used to predict the inlet reference plane (IRP) flow field for a side-mounted inlet and forebody simulator in a free jet for five different flow conditions. The calculations were performed for free-jet conditions, mass flow rates, and inlet configurations that matched the free-jet test conditions. In addition, viscous terms were included in the main flow so that the viscous free-jet shear layers emanating from the free-jet nozzle exit were modeled. A measure of the predicted accuracy was determined as a function of free-stream Mach number, angle-of-attack, and sideslip angle.

The predictive mind and the experience of visual art work

PubMed Central

Kesner, Ladislav

2014-01-01

Among the main challenges of the predictive brain/mind concept is how to link prediction at the neural level to prediction at the cognitive-psychological level and finding conceptually robust and empirically verifiable ways to harness this theoretical framework toward explaining higher-order mental and cognitive phenomena, including the subjective experience of aesthetic and symbolic forms. Building on the tentative prediction error account of visual art, this article extends the application of the predictive coding framework to the visual arts. It does so by linking this theoretical discussion to a subjective, phenomenological account of how a work of art is experienced. In order to engage more deeply with a work of art, viewers must be able to tune or adapt their prediction mechanism to recognize art as a specific class of objects whose ontological nature defies predictability, and they must be able to sustain a productive flow of predictions from low-level sensory, recognitional to abstract semantic, conceptual, and affective inferences. The affective component of the process of predictive error optimization that occurs when a viewer enters into dialog with a painting is constituted both by activating the affective affordances within the image and by the affective consequences of prediction error minimization itself. The predictive coding framework also has implications for the problem of the culturality of vision. A person’s mindset, which determines what top–down expectations and predictions are generated, is co-constituted by culture-relative skills and knowledge, which form hyperpriors that operate in the perception of art. PMID:25566111

The predictive mind and the experience of visual art work.

PubMed

Kesner, Ladislav

2014-01-01

Among the main challenges of the predictive brain/mind concept is how to link prediction at the neural level to prediction at the cognitive-psychological level and finding conceptually robust and empirically verifiable ways to harness this theoretical framework toward explaining higher-order mental and cognitive phenomena, including the subjective experience of aesthetic and symbolic forms. Building on the tentative prediction error account of visual art, this article extends the application of the predictive coding framework to the visual arts. It does so by linking this theoretical discussion to a subjective, phenomenological account of how a work of art is experienced. In order to engage more deeply with a work of art, viewers must be able to tune or adapt their prediction mechanism to recognize art as a specific class of objects whose ontological nature defies predictability, and they must be able to sustain a productive flow of predictions from low-level sensory, recognitional to abstract semantic, conceptual, and affective inferences. The affective component of the process of predictive error optimization that occurs when a viewer enters into dialog with a painting is constituted both by activating the affective affordances within the image and by the affective consequences of prediction error minimization itself. The predictive coding framework also has implications for the problem of the culturality of vision. A person's mindset, which determines what top-down expectations and predictions are generated, is co-constituted by culture-relative skills and knowledge, which form hyperpriors that operate in the perception of art.

On the apparent positions of T Tauri stars in the H-R diagram

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

Kenyon, S.J.; Hartmann, L.W.

1990-01-01

The spread in apparent luminosities of T Tauri stars caused by occultation and emission from protostellar disks is investigated. A random distribution of disk inclination angles, coupled with a plausible range of accretion rates, introduces a significant scatter in apparent luminosities for intrinsically identical stars. The observed dispersion of luminosities for K7-M1 Hayashi track stars thought to have disks in Taurus-Auriga is similar to predictions of the simple accretion disk model, which suggets that age determinations form many pre-main-sequence stars are uncertain. The results also suggest that Stahler's birthline for convective track pre-main-sequence stars may be located at slightly lowermore » luminosities than previously thought. 38 refs.« less

Approximation of properties of hyperelastic materials with use of energy-based models and biaxial tension data

NASA Astrophysics Data System (ADS)

Jamróz, Weronika

2016-06-01

The paper shows the way enrgy-based models aproximate mechanical properties of hiperelastic materials. Main goal of research was to create a method of finding a set of material constants that are included in a strain energy function that constitutes a heart of an energy-based model. The most optimal set of material constants determines the best adjustment of a theoretical stress-strain relation to the experimental one. This kind of adjustment enables better prediction of behaviour of a chosen material. In order to obtain more precised solution the approximation was made with use of data obtained in a modern experiment widely describen in [1]. To save computation time main algorithm is based on genetic algorithms.

Predicting capillarity of mudrocks for geological storage of CO2

NASA Astrophysics Data System (ADS)

Busch, Andreas; Amann-Hildenbrand, Alexandra

2013-04-01

Various rock types were investigated, with the main focus on the determination and prediction of the capillary breakthrough and snap-off pressure in mudrocks (e.g. shales, siltstones, mudstones). Knowledge about these two critical pressures is important for the prediction of the capillary sealing capacity of CO2 storage sites. Capillary pressure experiments, when performed on low-permeable core plugs, are difficult and time consuming. Laboratory measurements on core plugs under in-situ conditions are mostly performed using nitrogen, but also with methane and carbon dioxide. Therefore, mercury porosimetry measurements (MIP) are preferably used in the industry to determine an equivalent value for the capillary breakthrough pressure. These measurements have the advantage to be quick and cheap and only require cuttings or trim samples. When evaluating the database in detail we find that (1) MIP data plot well with the drainage breakthrough pressures determined on sample plugs, while the conversion of the system Hg/air to CO2/brine using interfacial and wettability data does not provide a uniform match, potentially caused by non fully water-wet conditions; (2) brine permeability versus capillary breakthrough pressure determined on sample plugs shows a good match and could provide a first estimate of Pc-values since permeability is easier to determine than capillary breakthrough pressures. For imbibition snap-off pressures a good correlation was found for CH4 measured on sample plugs only; (3) porosity shows a fairly good correlation with permeability for sandstone only, and with plug-derived capillary breakthrough pressures for sandstones, carbonates and evaporates. No such correlations exist for mudrocks; (4) air and brine-derived permeabilities show an excellent correlation and (5) from the data used we do not infer any direct correlations between specific surface area (SSA), mineralogy or organic carbon content with permeability or capillary pressure however were able to predict permeabilities using a more sophisticated model that relies on several of these parameters.

Space shuttle main engine plume radiation model

NASA Technical Reports Server (NTRS)

Reardon, J. E.; Lee, Y. C.

1978-01-01

The methods are described which are used in predicting the thermal radiation received by space shuttles, from the plumes of the main engines. Radiation to representative surface locations were predicted using the NASA gaseous plume radiation GASRAD program. The plume model is used with the radiative view factor (RAVFAC) program to predict sea level radiation at specified body points. The GASRAD program is described along with the predictions. The RAVFAC model is also discussed.

The Continuing Allure of Cure: A Response to Alex Broadbent's "Prediction, Understanding, and Medicine".

PubMed

Harris, Chadwin

2018-05-09

In "Prediction, Understanding, and Medicine," Alex Broadbent rejects the curative thesis, the view that the core medical competence is to cure, in favor of his predictive thesis that the main intellectual medical competence is to explain and the main practical medical competence is to predict. Broadbent thinks his account explains the phenomenon of multiple consultation, which is the fact that people persist in consulting alternative medical traditions despite having access to mainstream medicine. I argue that Broadbent's explanation of multiple consultation makes sense only from the perspective of patients who migrate from mainstream to alternative consultation. His explanation is not as convincing when we consider alternative-to-mainstream migration. I also provide an argument against Broadbent's view that prediction is medicine's main practical competence and argue that, when it comes to explaining most cases of multiple consultation, the curative thesis provides a more convincing explanation than the predictive thesis.

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

Brochard, J.; Charras, T.; Ghoudi, M.

Modifications to a computer code for ductile fracture assessment of piping systems with postulated circumferential through-wall cracks under static or dynamic loading are very briefly described. The modifications extend the capabilities of the CASTEM2000 code to the determination of fracture parameters under creep conditions. The main advantage of the approach is that thermal loads can be evaluated as secondary stresses. The code is applicable to piping systems for which crack propagation predictions differ significantly depending on whether thermal stresses are considered as primary or secondary stresses.

Space shuttle engineering and operations support. Orbiter to spacelab electrical power interface. Avionics system engineering

NASA Technical Reports Server (NTRS)

Emmons, T. E.

1976-01-01

The results are presented of an investigation of the factors which affect the determination of Spacelab (S/L) minimum interface main dc voltage and available power from the orbiter. The dedicated fuel cell mode of powering the S/L is examined along with the minimum S/L interface voltage and available power using the predicted fuel cell power plant performance curves. The values obtained are slightly lower than current estimates and represent a more marginal operating condition than previously estimated.

Mathematical modeling in biological populations through branching processes. Application to salmonid populations.

PubMed

Molina, Manuel; Mota, Manuel; Ramos, Alfonso

2015-01-01

This work deals with mathematical modeling through branching processes. We consider sexually reproducing animal populations where, in each generation, the number of progenitor couples is determined in a non-predictable environment. By using a class of two-sex branching processes, we describe their demographic dynamics and provide several probabilistic and inferential contributions. They include results about the extinction of the population and the estimation of the offspring distribution and its main moments. We also present an application to salmonid populations.

Motor Skill Competence and Perceived Motor Competence: Which Best Predicts Physical Activity among Girls?

PubMed Central

Khodaverdi, Zeinab; Bahram, Abbas; Khalaji, Hassan; Kazemnejad, Anoshirvan

2013-01-01

Abstract Background The main purpose of this study was to determine which correlate, perceived motor competence or motor skill competence, best predicts girls’ physical activity behavior. Methods A sample of 352 girls (mean age=8.7, SD=0.3 yr) participated in this study. To assess motor skill competence and perceived motor competence, each child completed the Test of Gross Motor Development-2 and Physical Ability sub-scale of Marsh’s Self-Description Questionnaire. Children’s physical activity was assessed by the Physical Activity Questionnaire for Older Children. Multiple linear regression model was used to determine whether perceived motor competence or motor skill competence best predicts moderate-to-vigorous self-report physical activity. Results Multiple regression analysis indicated that motor skill competence and perceived motor competence predicted 21% variance in physical activity (R2=0.21, F=48.9, P=0.001), and motor skill competence (R2=0.15, ᵝ=0.33, P= 0.001) resulted in more variance than perceived motor competence (R2=0.06, ᵝ=0.25, P=0.001) in physical activity. Conclusion Results revealed motor skill competence had more influence in comparison with perceived motor competence on physical activity level. We suggest interventional programs based on motor skill competence and perceived motor competence should be administered or implemented to promote physical activity in young girls. PMID:26060623

Validity of total and segmental impedance measurements for prediction of body composition across ethnic population groups.

PubMed

Deurenberg, P; Deurenberg-Yap, M; Schouten, F J M

2002-03-01

To test the impact of body build factors on the validity of impedance-based body composition predictions across (ethnic) population groups and to study the suitability of segmental impedance measurements. Cross-sectional observational study. Ministry of Health and School of Physical Education, Nanyang Technological University, Singapore. A total of 291 female and male Chinese, Malays and Indian Singaporeans, aged 18-69, body mass index (BMI) 16.0-40.2 kg/ m2. Anthropometric parameters were measured in addition to impedance (100 kHz) of the total body, arms and legs. Impedance indexes were calculated as height2/impedance. Arm length (span) and leg length (sitting height), wrist and knee width were measured from which body build indices were calculated. Total body water (TBW) was measured using deuterium oxide dilution. Extra cellular water (ECW) was measured using bromide dilution. Body fat percentage was determined using a chemical four-compartment model. The bias of TBW predicted from total body impedance index (bias: measured minus predicted TBW) was different among the three ethnic groups, TBW being significantly underestimated in Indians compared to Chinese and Malays. This bias was found to be dependent on body water distribution (ECW/TBW) and parameters of body build, mainly relative (to height) arm length. After correcting for differences in body water distribution and body build parameters the differences in bias across the ethnic groups disappeared. The impedance index using total body impedance was better correlated with TBW than the impedance index of arm or leg impedance, even after corrections for body build parameters. The study shows that ethnic-specific bias of impedance-based prediction formulas for body composition is due mainly to differences in body build among the ethnic groups. This means that the use of 'general' prediction equations across different (ethnic) population groups without prior testing of their validity should be avoided. Total body impedance has higher predictive value than segmental impedance.

A first European scale multimedia fate modelling of BDE-209 from 1970 to 2020.

PubMed

Earnshaw, Mark R; Jones, Kevin C; Sweetman, Andy J

2015-01-01

The European Variant Berkeley Trent (EVn-BETR) multimedia fugacity model is used to test the validity of previously derived emission estimates and predict environmental concentrations of the main decabromodiphenyl ether congener, BDE-209. The results are presented here and compared with measured environmental data from the literature. Future multimedia concentration trends are predicted using three emission scenarios (Low, Realistic and High) in the dynamic unsteady state mode covering the period 1970-2020. The spatial and temporal distributions of emissions are evaluated. It is predicted that BDE-209 atmospheric concentrations peaked in 2004 and will decline to negligible levels by 2025. Freshwater concentrations should have peaked in 2011, one year after the emissions peak with sediment concentrations peaking in 2013. Predicted atmospheric concentrations are in good agreement with measured data for the Realistic (best estimate of emissions) and High (worst case scenario) emission scenarios. The Low emission scenario consistently underestimates measured data. The German unilateral ban on the use of DecaBDE in the textile industry is simulated in an additional scenario, the effects of which are mainly observed within Germany with only a small effect on the surrounding areas. Overall, the EVn-BTER model predicts atmospheric concentrations reasonably well, within a factor of 5 and 1.2 for the Realistic and High emission scenarios respectively, providing partial validation for the original emission estimate. Total mean MEC:PEC shows the High emission scenario predicts the best fit between air, freshwater and sediment data. An alternative spatial distribution of emissions is tested, based on higher consumption in EBFRIP member states, resulting in improved agreement between MECs and PECs in comparison with the Uniform spatial distribution based on population density. Despite good agreement between modelled and measured point data, more long-term monitoring datasets are needed to compare predicted trends in concentration to determine the rate of change of POPs within the environment. Copyright © 2014 Elsevier Ltd. All rights reserved.

Novel modes and adaptive block scanning order for intra prediction in AV1

NASA Astrophysics Data System (ADS)

Hadar, Ofer; Shleifer, Ariel; Mukherjee, Debargha; Joshi, Urvang; Mazar, Itai; Yuzvinsky, Michael; Tavor, Nitzan; Itzhak, Nati; Birman, Raz

2017-09-01

The demand for streaming video content is on the rise and growing exponentially. Networks bandwidth is very costly and therefore there is a constant effort to improve video compression rates and enable the sending of reduced data volumes while retaining quality of experience (QoE). One basic feature that utilizes the spatial correlation of pixels for video compression is Intra-Prediction, which determines the codec's compression efficiency. Intra prediction enables significant reduction of the Intra-Frame (I frame) size and, therefore, contributes to efficient exploitation of bandwidth. In this presentation, we propose new Intra-Prediction algorithms that improve the AV1 prediction model and provide better compression ratios. Two (2) types of methods are considered: )1( New scanning order method that maximizes spatial correlation in order to reduce prediction error; and )2( New Intra-Prediction modes implementation in AVI. Modern video coding standards, including AVI codec, utilize fixed scan orders in processing blocks during intra coding. The fixed scan orders typically result in residual blocks with high prediction error mainly in blocks with edges. This means that the fixed scan orders cannot fully exploit the content-adaptive spatial correlations between adjacent blocks, thus the bitrate after compression tends to be large. To reduce the bitrate induced by inaccurate intra prediction, the proposed approach adaptively chooses the scanning order of blocks according to criteria of firstly predicting blocks with maximum number of surrounding, already Inter-Predicted blocks. Using the modified scanning order method and the new modes has reduced the MSE by up to five (5) times when compared to conventional TM mode / Raster scan and up to two (2) times when compared to conventional CALIC mode / Raster scan, depending on the image characteristics (which determines the percentage of blocks predicted with Inter-Prediction, which in turn impacts the efficiency of the new scanning method). For the same cases, the PSNR was shown to improve by up to 7.4dB and up to 4 dB, respectively. The new modes have yielded 5% improvement in BD-Rate over traditionally used modes, when run on K-Frame, which is expected to yield 1% of overall improvement.

Prediction of coagulation and flocculation processes using ANN models and fuzzy regression.

PubMed

Zangooei, Hossein; Delnavaz, Mohammad; Asadollahfardi, Gholamreza

2016-09-01

Coagulation and flocculation are two main processes used to integrate colloidal particles into larger particles and are two main stages of primary water treatment. Coagulation and flocculation processes are only needed when colloidal particles are a significant part of the total suspended solid fraction. Our objective was to predict turbidity of water after the coagulation and flocculation process while other parameters such as types and concentrations of coagulants, pH, and influent turbidity of raw water were known. We used a multilayer perceptron (MLP), a radial basis function (RBF) of artificial neural networks (ANNs) and various kinds of fuzzy regression analysis to predict turbidity after the coagulation and flocculation processes. The coagulant used in the pilot plant, which was located in water treatment plant, was poly aluminum chloride. We used existing data, including the type and concentrations of coagulant, pH and influent turbidity, of the raw water because these types of data were available from the pilot plant for simulation and data was collected by the Tehran water authority. The results indicated that ANNs had more ability in simulating the coagulation and flocculation process and predicting turbidity removal with different experimental data than did the fuzzy regression analysis, and may have the ability to reduce the number of jar tests, which are time-consuming and expensive. The MLP neural network proved to be the best network compared to the RBF neural network and fuzzy regression analysis in this study. The MLP neural network can predict the effluent turbidity of the coagulation and the flocculation process with a coefficient of determination (R 2 ) of 0.96 and root mean square error of 0.0106.

Fatigue Behavior of Steel Fiber Reinforced High-Strength Concrete under Different Stress Levels

NASA Astrophysics Data System (ADS)

Zhang, Chong; Gao, Danying; Gu, Zhiqiang

2017-12-01

The investigation was conducted to study the fatigue behavior of steel fiber reinforced high-strength concrete (SFRHSC) beams. A series of 5 SFRHSC beams was conducted flexural fatigue tests at different stress level S of 0.5, 0.55, 0.6, 0.7 and 0.8 respectively. Static test was conducted to determine the ultimate static capacity prior to fatigue tests. Fatigue modes and S-N curves were analyzed. Besides, two fatige life prediction model were analyzed and compared. It was found that stress level S significantly influenced the fatigue life of SFRHSC beams and the fatigue behavior of SFRHSC beams was mainly determined by the tensile reinforcement.

SSME single-crystal turbine blade dynamics

NASA Technical Reports Server (NTRS)

Moss, Larry A.

1988-01-01

A study was performrd to determine the dynamic characteristics of the Space Shuttle Main Engine high pressure fuel turbopump (HPFTP) blades made of single crystal (SC) material. The first and second stage drive turbine blades of HPFTP were examined. The nonrotating natural frequencies were determined experimentally and analytically. The experimental results of the SC second stage blade were used to verify the analytical procedures. The study examined the SC first stage blade natural frequencies with respect to crystal orientation at typical operating conditions. The SC blade dynamic response was predicted to be less than the directionally solidified base. Crystal axis orientation optimization indicated that the third mode interference will exist in any SC orientation.

SSME single crystal turbine blade dynamics

NASA Technical Reports Server (NTRS)

Moss, Larry A.; Smith, Todd E.

1987-01-01

A study was performed to determine the dynamic characteristics of the Space Shuttle main engine high pressure fuel turbopump (HPFTP) blades made of single crystal (SC) material. The first and second stage drive turbine blades of HPFTP were examined. The nonrotating natural frequencies were determined experimentally and analytically. The experimental results of the SC second stage blade were used to verify the analytical procedures. The analytical study examined the SC first stage blade natural frequencies with respect to crystal orientation at typical operating conditions. The SC blade dynamic response was predicted to be less than the directionally solidified blade. Crystal axis orientation optimization indicated the third mode interference will exist in any SC orientation.

How can the health belief model and self-determination theory predict both influenza vaccination and vaccination intention ? A longitudinal study among university students.

PubMed

Fall, Estelle; Izaute, Marie; Chakroun-Baggioni, Nadia

2018-06-01

Background and objective Seasonal influenza is frequent among students and often responsible for impaired academic performance and lower levels of general health. However, the vaccination rate in this population is very low. As the seasonal influenza vaccine is not compulsory in France, it is important to improve the vaccination uptake by identifying predictors of both intention and behaviour. This study investigated the effect of decisional balance, motivation and self-efficacy on vaccination acceptance using the Extended Health Belief Model (HBM) and Self-Determination Theory (SDT). Design and Main Outcome Measures University students were invited to fill in an online survey to answer questions about their influenza vaccination intention, and HBM and SDT constructs. A one-year longitudinal follow-up study investigated vaccination behaviour. Results Autonomous motivation and self-efficacy significantly influenced the intention to have the influenza vaccine, and vaccine behaviour at one-year follow-up. Intention predicted a significant proportion of variation (51%) in behaviour, and mediated the effect of these predictors on vaccination behaviour. Conclusion These results suggest that motivation concepts of the Self-Determination Theory can be adequately combined with the Health Belief Model to understand vaccination behaviour.

Computer Aided Dosimetry and Verification of Exposure to Radiation

NASA Astrophysics Data System (ADS)

Waller, Edward; Stodilka, Robert Z.; Leach, Karen E.; Lalonde, Louise

2002-06-01

In the timeframe following the September 11th attacks on the United States, increased emphasis has been placed on Chemical, Biological, Radiological and Nuclear (CBRN) preparedness. Of prime importance is rapid field assessment of potential radiation exposure to Canadian Forces field personnel. This work set up a framework for generating an 'expert' computer system for aiding and assisting field personnel in determining the extent of radiation insult to military personnel. Data was gathered by review of the available literature, discussions with medical and health physics personnel having hands-on experience dealing with radiation accident victims, and from experience of the principal investigator. Flow charts and generic data fusion algorithms were developed. Relationships between known exposure parameters, patient interview and history, clinical symptoms, clinical work-ups, physical dosimetry, biological dosimetry, and dose reconstruction as critical data indicators were investigated. The data obtained was examined in terms of information theory. A main goal was to determine how best to generate an adaptive model (i.e. when more data becomes available, how is the prediction improved). Consideration was given to determination of predictive algorithms for health outcome. In addition. the concept of coding an expert medical treatment advisor system was developed (U)

Decrease in the Orbital Period of Hercules X-1

NASA Technical Reports Server (NTRS)

Deeter, John E.; Boynton, Paul E.; Miyamoto, Sigenori; Kitamoto, Shunji; Nagase, Fumiaki; Kawai, Nobuyuki

1991-01-01

From a pulse-timing analysis of Ginga observations of the binary X-ray pulsar Her X-1 obtained during the interval 1989 April-June we have determined local orbital parameters for a Short High state. We have also determined an orbital epoch in the adjacent Main High state. By comparing these orbital solutions with previously published results, we have detected a decrease in the orbital period for Her X-1 at an average rate of dot-P/P = (- 1.32 +/- 0.16) x 10(exp -8) yr(exp -1) over the interval 1971-1989. This is substantially larger than the value predicted from current estimates of the mass transfer rate, and motivates consideration of other mechanisms of mass transfer and/or mass loss. A second result from these observations is a close agreement between orbital parameters determined separately in Main High and Short High states. This agreement places strong constraints on the obliquity of the stellar companion, HZ Her, if undergoing forced precession with a 35 day period. As a consequence further doubt is placed on the slaved-disk model as the underlying cause of the 35 day cycle in Her X-1.

Helicopter main-rotor speed effects: A comparison of predicted ranges of detection from the aural detection program ICHIN and the electronic detection program ARCAS

NASA Technical Reports Server (NTRS)

Mueller, Arnold W.; Smith, Charles D.

1991-01-01

NASA LaRC personnel have conducted a strudy of the predicted acoustic detection ranges associated with reduced helicopter main rotor speeds. This was accomplished by providing identical input information to both the aural detection program ICHIN 6, (I Can Hear It Now, version 6) and the electronic acoustic detection program ARCAS (Assessment of Rotorcraft Detection by Acoustics Sensing). In this study, it was concluded that reducing the main rotor speed of the helicopter by 27 percent reduced both the predicted aural and electronic detection ranges by approximately 50 percent. Additionally, ARCAS was observed to function better with narrowband spectral input than with one-third octave band spectral inputs and the predicted electronic range of acoustic detection is greater than the predicted aural detection range.

A quantitative study for determination of sugar concentration using attenuated total reflectance terahertz (ATR-THz) spectroscopy

NASA Astrophysics Data System (ADS)

Suhandy, Diding; Suzuki, Tetsuhito; Ogawa, Yuichi; Kondo, Naoshi; Ishihara, Takeshi; Takemoto, Yuichiro

2011-06-01

The objective of our research was to use ATR-THz spectroscopy together with chemometric for quantitative study in food analysis. Glucose, fructose and sucrose are main component of sugar both in fresh and processed fruits. The use of spectroscopic-based method for sugar determination is well reported especially using visible, near infrared (NIR) and middle infrared (MIR) spectroscopy. However, the use of terahertz spectroscopy for sugar determination in fruits has not yet been reported. In this work, a quantitative study for sugars determination using attenuated total reflectance terahertz (ATR-THz) spectroscopy was conducted. Each samples of glucose, fructose and sucrose solution with different concentrations were prepared respectively and their absorbance spectra between wavenumber 20 and 450 cm-1 (between 0.6 THz and 13.5 THz) were acquired using a terahertz-based Fourier Transform spectrometer (FARIS-1S, JASCO Co., Japan). This spectrometer was equipped with a high pressure of mercury lamp as light source and a pyroelectric sensor made from deuterated L-alanine triglycine sulfate (DLTGS) as detector. Each spectrum was acquired using 16 cm-1 of resolution and 200 scans for averaging. The spectra of water and sugar solutions were compared and discussed. The results showed that increasing sugar concentration caused decreasing absorbance. The correlation between sugar concentration and its spectra was investigated using multivariate analysis. Calibration models for glucose, fructose and sucrose determination were developed using partial least squares (PLS) regression. The calibration model was evaluated using some parameters such as coefficient of determination (R2), standard error of calibration (SEC), standard error of prediction (SEP), bias between actual and predicted sugar concentration value and ratio prediction to deviation (RPD) parameter. The cross validation method was used to validate each calibration model. It is showed that the use of ATR-THz spectroscopy combined with appropriate chemometric can be a potential for a rapid determination of sugar concentrations.

Fate and Prediction of Phenolic Secoiridoid Compounds throughout the Different Stages of the Virgin Olive Oil Making Process

PubMed Central

2017-01-01

The evolution of the main phenolic secoiridoid compounds throughout the different stages of the virgin olive oil making process—crushing, malaxation and liquid-solid separation—is studied here, with the goal of making possible the prediction of the partition and transformation that take place in the different steps of the process. The concentration of hydroxytyrosol secoiridoids produced under the different crushing conditions studied are reasonably proportional to the intensity of the milling stage, and strongly depend on the olive variety processed. During malaxation, the content of the main phenolic secoiridoids is reduced, especially in the case of the hydroxytyrosol derivatives, in which a variety-dependent behaviour is observed. The prediction of the concentration of phenolic secoiridoids finally transferred from the kneaded paste to the virgin olive oil is also feasible, and depends on the phenolic content and amount of water in the olive paste. The determination of the phenolic compounds in the olive fruit, olive paste and olive oil has been carried out by LC-MS (Liquid-Chromatography Mass-Spectrometry). This improved knowledge could help in the use of more adequate processing conditions for the production of virgin olive oil with desired properties; for example, higher or lower phenolic content, as the amount of these minor components is directly related to its sensory, antioxidant and healthy properties. PMID:28771173

Clinical history as a predictor of penicillin skin test outcome.

PubMed

Wong, Benjamin B L; Keith, Paul K; Waserman, Susan

2006-08-01

Up to 10% of the population reports an "allergy" to penicillin, whereas approximately 1.1% has positive penicillin skin test results. Where penicillin skin tests are unavailable, some have advocated using history to decide whether to use a penicillin-related antibiotic. To determine if clinical history predicts penicillin skin test results. Retrospective medical record review of 94 consecutive patients who had previously taken penicillin referred for penicillin allergy. Case histories were taken, penicillin skin tests performed, and an oral challenge recommended if skin test results were negative. Of 91 cases studied, the average patient age was 27 years (range, 6 months to 82 years; 36% female). Fifty-two (57%) experienced hives as their main adverse reaction. Sixteen (18%) had at least 1 positive test result. Of this group, 9 had hives as their main symptom, whereas 1 had respiratory problems and 1 had angioedema. Most patients with positive skin test results had experienced their reaction at least 3 years ago. Regression analysis showed that age, sex, and clinical history, including type of reaction, time of reaction after penicillin ingestion, or time since the last reaction, were not associated with skin test positivity. Seventy-two (96%) of the 75 patients who had negative skin test results underwent oral challenge. Seventy had negative challenge results. The negative predictive value of a negative penicillin skin test result was 97%. Clinical history was not predictive of subsequent penicillin skin test results.

Fate and Prediction of Phenolic Secoiridoid Compounds throughout the Different Stages of the Virgin Olive Oil Making Process.

PubMed

Fregapane, Giuseppe; Salvador, M Desamparados

2017-08-03

The evolution of the main phenolic secoiridoid compounds throughout the different stages of the virgin olive oil making process-crushing, malaxation and liquid-solid separation-is studied here, with the goal of making possible the prediction of the partition and transformation that take place in the different steps of the process. The concentration of hydroxytyrosol secoiridoids produced under the different crushing conditions studied are reasonably proportional to the intensity of the milling stage, and strongly depend on the olive variety processed. During malaxation, the content of the main phenolic secoiridoids is reduced, especially in the case of the hydroxytyrosol derivatives, in which a variety-dependent behaviour is observed. The prediction of the concentration of phenolic secoiridoids finally transferred from the kneaded paste to the virgin olive oil is also feasible, and depends on the phenolic content and amount of water in the olive paste. The determination of the phenolic compounds in the olive fruit, olive paste and olive oil has been carried out by LC-MS (Liquid-Chromatography Mass-Spectrometry). This improved knowledge could help in the use of more adequate processing conditions for the production of virgin olive oil with desired properties; for example, higher or lower phenolic content, as the amount of these minor components is directly related to its sensory, antioxidant and healthy properties.

Structural Analysis: Folds Classification of metasedimentary rock in the Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Shamsuddin, A.

2017-10-01

Understanding shear zone characteristics of deformation are a crucial part in the oil and gas industry as it might increase the knowledge of the fracture characteristics and lead to the prediction of the location of fracture zones or fracture swarms. This zone might give high influence on reservoir performance. There are four general types of shear zones which are brittle, ductile, semibrittle and brittle-ductile transition zones. The objective of this study is to study and observe the structural geometry of the shear zones and its implication as there is a lack of understanding, especially in the subsurface area because of the limitation of seismic resolution. A field study was conducted on the metasedimentary rocks (shear zone) which are exposed along the coastal part of the Peninsular Malaysia as this type of rock resembles the types of rock in the subsurface. The analysis in this area shows three main types of rock which are non-foliated metaquartzite and foliated rock which can be divided into slate and phyllite. Two different fold classification can be determined in this study. Layer 1 with phyllite as the main type of rock can be classified in class 1C and layer 2 with slate as the main type of rock can be classified in class 1A. This study will benefit in predicting the characteristics of the fracture and fracture zones.

Determinants of maternal antenatal state-anxiety in mid-pregnancy: Role of maternal feelings about the pregnancy.

PubMed

Akiki, Salwa; Avison, William R; Speechley, Kathy N; Campbell, M Karen

2016-05-15

The current state of research into antenatal anxiety is lacking in a comprehensive understanding of determinants. This study aims to expand knowledge in this area, with the main objective being to determine potential determinants of maternal antenatal state-anxiety. Data used for this cross-sectional study were obtained from the Prenatal Health Project: a population cohort study of 2357 women in London, Ontario. 1992 women in their second trimester met inclusion criteria for this study. The primary hypothesis was that "feelings about the pregnancy" would be a determinant of antenatal state-anxiety after controlling for other potential covariates. The abbreviated version of the Spielberger State and Trait Anxiety Inventory (STAI) was used to measure state-anxiety. Univariate analyses and multiple linear regression were performed to identify variables predictive of state-anxiety. Stress, feeling unsure/unhappy about the pregnancy and having low self-esteem, low mastery and low social support from one's partner and family were statistically significant determinants of state-anxiety during the second trimester. In addition, anxiety was found to be inversely related to gestational age. The two main limitations of the study were the use of a self-report screening tool (STAI) as the measure of anxious symptoms rather than a clinical diagnosis, and possible recall bias of feelings about the pregnancy. We concluded that how a woman feels about her pregnancy was a determinant of state-anxiety. This study contributes knowledge aiming to help women improve their mental health during pregnancy by identifying important determinants of state-anxiety. Copyright © 2016 Elsevier B.V. All rights reserved.

Genome wide predictions of miRNA regulation by transcription factors.

PubMed

Ruffalo, Matthew; Bar-Joseph, Ziv

2016-09-01

Reconstructing regulatory networks from expression and interaction data is a major goal of systems biology. While much work has focused on trying to experimentally and computationally determine the set of transcription-factors (TFs) and microRNAs (miRNAs) that regulate genes in these networks, relatively little work has focused on inferring the regulation of miRNAs by TFs. Such regulation can play an important role in several biological processes including development and disease. The main challenge for predicting such interactions is the very small positive training set currently available. Another challenge is the fact that a large fraction of miRNAs are encoded within genes making it hard to determine the specific way in which they are regulated. To enable genome wide predictions of TF-miRNA interactions, we extended semi-supervised machine-learning approaches to integrate a large set of different types of data including sequence, expression, ChIP-seq and epigenetic data. As we show, the methods we develop achieve good performance on both a labeled test set, and when analyzing general co-expression networks. We next analyze mRNA and miRNA cancer expression data, demonstrating the advantage of using the predicted set of interactions for identifying more coherent and relevant modules, genes, and miRNAs. The complete set of predictions is available on the supporting website and can be used by any method that combines miRNAs, genes, and TFs. Code and full set of predictions are available from the supporting website: http://cs.cmu.edu/~mruffalo/tf-mirna/ zivbj@cs.cmu.edu 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.

A NEW CLINICAL PREDICTION CRITERION ACCURATELY DETERMINES A SUBSET OF PATIENTS WITH BILATERAL PRIMARY ALDOSTERONISM BEFORE ADRENAL VENOUS SAMPLING.

PubMed

Kocjan, Tomaz; Janez, Andrej; Stankovic, Milenko; Vidmar, Gaj; Jensterle, Mojca

2016-05-01

Adrenal venous sampling (AVS) is the only available method to distinguish bilateral from unilateral primary aldosteronism (PA). AVS has several drawbacks, so it is reasonable to avoid this procedure when the results would not affect clinical management. Our objective was to identify a clinical criterion that can reliably predict nonlateralized AVS as a surrogate for bilateral PA that is not treated surgically. A retrospective diagnostic cross-sectional study conducted at Slovenian national endocrine referral center included 69 consecutive patients (mean age 56 ± 8 years, 21 females) with PA who underwent AVS. PA was confirmed with the saline infusion test (SIT). AVS was performed sequentially during continuous adrenocorticotrophic hormone (ACTH) infusion. The main outcome measures were variables associated with nonlateralized AVS to derive a clinical prediction rule. Sixty-seven (97%) patients had a successful AVS and were included in the statistical analysis. A total of 39 (58%) patients had nonlateralized AVS. The combined criterion of serum potassium ≥3.5 mmol/L, post-SIT aldosterone <18 ng/dL, and either no or bilateral tumor found on computed tomography (CT) imaging had perfect estimated specificity (and thus 100% positive predictive value) for bilateral PA, saving an estimated 16% of the patients (11/67) from unnecessary AVS. The best overall classification accuracy (50/67 = 75%) was achieved using the post-SIT aldosterone level <18 ng/dL alone, which yielded 74% sensitivity and 75% specificity for predicting nonlateralized AVS. Our clinical prediction criterion appears to accurately determine a subset of patients with bilateral PA who could avoid unnecessary AVS and immediately commence with medical treatment.

Biological and functional relevance of CASP predictions

PubMed Central

Liu, Tianyun; Ish‐Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D.

2017-01-01

Abstract Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo‐sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo‐sites), and Ten sites containing important motifs, loops, or key residues with important disease‐associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best‐ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand‐binding sites, most prediction methods have higher performance on apo‐sites than holo‐sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein‐protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein‐protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. PMID:28975675

Near-infrared reflectance spectroscopy (NIRS) for rapid determination of ginsenoside Rg1 and Re in Chinese patent medicine Naosaitong pill

NASA Astrophysics Data System (ADS)

Zhang, Wei; Qu, Zhengyi; Wang, Yingping; Yao, Chunlin; Bai, Xueyuan; Bian, Shuai; Zhao, Bing

2015-03-01

Ginsenosides in plant samples have been extensively studied because protopanaxadiol saponins are ubiquitous in Chinese patent medicines, in which they can be used in promoting human health as the main active ingredients. A method for rapid determination of two ginsenosides (Rg1 and Re) in Naosaitong (NST) samples using near-infrared reflectance spectroscopy (NIRS) is studied to determine the contents of ginsenoside Rg1 and Re in this work. Partial least square (PLS) regression was used for building the calibration models, and the effects of spectral preprocessing and variable selection on the models are investigated for optimization of the models. A total of 93 samples were scanned by NIRS, and also by high performance liquid chromatography coupled to a diode array detector to determine the contents of ginsenoside Rg1 and Re. The calibration models for Rg1 and Re had high values of the coefficient of determination (R2) (0.9766 and 0.9764) and low root mean square error of cross validation (RMSECV) (0.0136 and 0.0104), and the values of the standard error of prediction set (SEP) are 0.00764 and 0.0103, which indicate a good correlation between reference values and NIRS predicted values. The overall results show that NIRS could be applied for the rapid determination of the contents of ginsenosides in Ginseng byproducts for pharmaceuticals that develop high-quality Chinese patent medicines.

Personalized risk prediction of postoperative cognitive impairment - rationale for the EU-funded BioCog project.

PubMed

Winterer, G; Androsova, G; Bender, O; Boraschi, D; Borchers, F; Dschietzig, T B; Feinkohl, I; Fletcher, P; Gallinat, J; Hadzidiakos, D; Haynes, J D; Heppner, F; Hetzer, S; Hendrikse, J; Ittermann, B; Kant, I M J; Kraft, A; Krannich, A; Krause, R; Kühn, S; Lachmann, G; van Montfort, S J T; Müller, A; Nürnberg, P; Ofosu, K; Pietsch, M; Pischon, T; Preller, J; Renzulli, E; Scheurer, K; Schneider, R; Slooter, A J C; Spies, C; Stamatakis, E; Volk, H D; Weber, S; Wolf, A; Yürek, F; Zacharias, N

2018-04-01

Postoperative cognitive impairment is among the most common medical complications associated with surgical interventions - particularly in elderly patients. In our aging society, it is an urgent medical need to determine preoperative individual risk prediction to allow more accurate cost-benefit decisions prior to elective surgeries. So far, risk prediction is mainly based on clinical parameters. However, these parameters only give a rough estimate of the individual risk. At present, there are no molecular or neuroimaging biomarkers available to improve risk prediction and little is known about the etiology and pathophysiology of this clinical condition. In this short review, we summarize the current state of knowledge and briefly present the recently started BioCog project (Biomarker Development for Postoperative Cognitive Impairment in the Elderly), which is funded by the European Union. It is the goal of this research and development (R&D) project, which involves academic and industry partners throughout Europe, to deliver a multivariate algorithm based on clinical assessments as well as molecular and neuroimaging biomarkers to overcome the currently unsatisfying situation. Copyright © 2017. Published by Elsevier Masson SAS.

Predicting Insulin Absorption and Glucose Uptake during Exercise in Type 1 Diabetes

NASA Astrophysics Data System (ADS)

Frank, Spencer; Hinshaw, Ling; Basu, Rita; Szeri, Andrew; Basu, Ananda

2017-11-01

A dose of insulin infused into subcutaneous tissue has been shown to absorb more quickly during exercise, potentially causing hypoglycemia in persons with type 1 diabetes. We develop a model that relates exercise-induced physiological changes to enhanced insulin-absorption (k) and glucose uptake (GU). Drawing on concepts of the microcirculation we derive a relationship that reveals that k and GU are mainly determined by two physiological parameters that characterize the tissue: the tissue perfusion rate (Q) and the capillary permeability surface area (PS). Independently measured values of Q and PS from the literature are used in the model to make predictions of k and GU. We compare these predictions to experimental observations of healthy and diabetic patients that are given a meal followed by rest or exercise. The experiments show that during exercise insulin concentrations significantly increase and that glucose levels fall rapidly. The model predictions are consistent with the experiments and show that increases in Q and PS directly increase k and GU. This mechanistic understanding provides a basis for handling exercise in control algorithms for an artificial pancreas. Now at University of British Columbia.

Modeling enzyme production with Aspergillus oryzae in pilot scale vessels with different agitation, aeration, and agitator types.

PubMed

Albaek, Mads O; Gernaey, Krist V; Hansen, Morten S; Stocks, Stuart M

2011-08-01

The purpose of this article is to demonstrate how a model can be constructed such that the progress of a submerged fed-batch fermentation of a filamentous fungus can be predicted with acceptable accuracy. The studied process was enzyme production with Aspergillus oryzae in 550 L pilot plant stirred tank reactors. Different conditions of agitation and aeration were employed as well as two different impeller geometries. The limiting factor for the productivity was oxygen supply to the fermentation broth, and the carbon substrate feed flow rate was controlled by the dissolved oxygen tension. In order to predict the available oxygen transfer in the system, the stoichiometry of the reaction equation including maintenance substrate consumption was first determined. Mainly based on the biomass concentration a viscosity prediction model was constructed, because rising viscosity of the fermentation broth due to hyphal growth of the fungus leads to significant lower mass transfer towards the end of the fermentation process. Each compartment of the model was shown to predict the experimental results well. The overall model can be used to predict key process parameters at varying fermentation conditions. Copyright © 2011 Wiley Periodicals, Inc.

Physiologically-Based Pharmacokinetic Modeling of Macitentan: Prediction of Drug-Drug Interactions.

PubMed

de Kanter, Ruben; Sidharta, Patricia N; Delahaye, Stéphane; Gnerre, Carmela; Segrestaa, Jerome; Buchmann, Stephan; Kohl, Christopher; Treiber, Alexander

2016-03-01

Macitentan is a novel dual endothelin receptor antagonist for the treatment of pulmonary arterial hypertension (PAH). It is metabolized by cytochrome P450 (CYP) enzymes, mainly CYP3A4, to its active metabolite ACT-132577. A physiological-based pharmacokinetic (PBPK) model was developed by combining observations from clinical studies and physicochemical parameters as well as absorption, distribution, metabolism and excretion parameters determined in vitro. The model predicted the observed pharmacokinetics of macitentan and its active metabolite ACT-132577 after single and multiple dosing. It performed well in recovering the observed effect of the CYP3A4 inhibitors ketoconazole and cyclosporine, and the CYP3A4 inducer rifampicin, as well as in predicting interactions with S-warfarin and sildenafil. The model was robust enough to allow prospective predictions of macitentan-drug combinations not studied, including an alternative dosing regimen of ketoconazole and nine other CYP3A4-interacting drugs. Among these were the HIV drugs ritonavir and saquinavir, which were included because HIV infection is a known risk factor for the development of PAH. This example of the application of PBPK modeling to predict drug-drug interactions was used to support the labeling of macitentan (Opsumit).

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.

Combination of serum angiopoietin-2 and uterine artery Doppler for prediction of preeclampsia.

PubMed

Puttapitakpong, Ploynin; Phupong, Vorapong

2016-02-01

The aim of this study was to determine the predictive value of the combination of serum angiopoietin-2 (Ang-2) levels and uterine artery Doppler for the detection of preeclampsia in women at 16-18 weeks of gestation and to identify other pregnancy complications that could be predicted with these combined tests. Maternal serum Ang-2 levels were measured, and uterine artery Doppler was performed in 400 pregnant women. The main outcome was preeclampsia. The predictive values of this combination were calculated. Twenty-five women (6.3%) developed preeclampsia. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of uterine artery Doppler combined with serum Ang-2 levels for the prediction of preeclampsia were 24.0%, 94.4%, 22.2% and 94.9%, respectively. For the prediction of early-onset preeclampsia, the sensitivity, specificity, PPV and NPV were 57.1%, 94.1%, 14.8% and 99.2%, respectively. Patients with abnormal uterine artery Doppler and abnormal serum Ang-2 levels (above 19.5 ng ml(-1)) were at higher risk for preterm delivery (relative risk=2.7, 95% confidence interval 1.2-5.8). Our findings revealed that the combination of uterine artery Doppler and serum Ang-2 levels at 16-18 weeks of gestation can be used to predict early-onset preeclampsia but not overall preeclampsia. Thus, this combination may be a useful early second trimester screening test for the prediction of early-onset preeclampsia.

Optimized model tuning in medical systems.

PubMed

Kléma, Jirí; Kubalík, Jirí; Lhotská, Lenka

2005-12-01

In medical systems it is often advantageous to utilize specific problem situations (cases) in addition to or instead of a general model. Decisions are then based on relevant past cases retrieved from a case memory. The reliability of such decisions depends directly on the ability to identify cases of practical relevance to the current situation. This paper discusses issues of automated tuning in order to obtain a proper definition of mutual case similarity in a specific medical domain. The main focus is on a reasonably time-consuming optimization of the parameters that determine case retrieval and further utilization in decision making/ prediction. The two case studies - mortality prediction after cardiological intervention, and resource allocation at a spa - document that the optimization process is influenced by various characteristics of the problem domain.

Adiabatic invariant analysis of dark and dark-bright soliton stripes in two-dimensional Bose-Einstein condensates

NASA Astrophysics Data System (ADS)

Kevrekidis, P. G.; Wang, Wenlong; Carretero-González, R.; Frantzeskakis, D. J.

2018-06-01

In the present work, we develop an adiabatic invariant approach for the evolution of quasi-one-dimensional (stripe) solitons embedded in a two-dimensional Bose-Einstein condensate. The results of the theory are obtained both for the one-component case of dark soliton stripes, as well as for the considerably more involved case of the two-component dark-bright (alias "filled dark") soliton stripes. In both cases, analytical predictions regarding the stability and dynamics of these structures are obtained. One of our main findings is the determination of the instability modes of the waves as a function of the parameters of the system (such as the trap strength and the chemical potential). Our analytical predictions are favorably compared with results of direct numerical simulations.

Trend analysis of vegetation in Louisiana's Atchafalaya river basin

USGS Publications Warehouse

O'Neil, Calvin P.; deSteiguer, J. Edward; North, Gary W.

1978-01-01

The purpose of the study was to determine vegetation succession trends; produce a current vegetation map of the basin; and to develop a mathematical model capable of predicting vegetation changes based on hydrologic factors. A statistical relationship of forests and hydrological variables with forest succession constraints predicted forest acreage totals for 16 forest categories within 70% or better of actual values in two-thirds of the cases. Using time-lapsed photography covering 42 years, 23 categories were described. The succession trend of vegetation since 1930, by sedimentation, had been toward mixed hardwoods, except for isolated areas. Satellite MSS Band 7 imagery was used to map the current vegetation into three main categories and for assessment of acreage. Additionally, a geological anomaly was recognized on satellite imagery indication an effect on drainage and sedimentation.

Serum Methylarginines and Spirometry-Measured Lung Function in Older Adults

PubMed Central

McEvoy, Mark A.; Schofield, Peter W.; Smith, Wayne T.; Agho, Kingsley; Mangoni, Arduino A.; Soiza, Roy L.; Peel, Roseanne; Hancock, Stephen J.; Carru, Ciriaco; Zinellu, Angelo; Attia, John R.

2013-01-01

Rationale Methylarginines are endogenous nitric oxide synthase inhibitors that have been implicated in animal models of lung disease but have not previously been examined for their association with spirometric measures of lung function in humans. Objectives This study measured serum concentrations of asymmetric and symmetric dimethylarginine in a representative sample of older community-dwelling adults and determined their association with spirometric lung function measures. Methods Data on clinical, lifestyle, and demographic characteristics, methylated arginines, and L-arginine (measured using LC-MS/MS) were collected from a population-based sample of older Australian adults from the Hunter Community Study. The five key lung function measures included as outcomes were Forced Expiratory Volume in 1 second, Forced Vital Capacity, Forced Expiratory Volume in 1 second to Forced Vital Capacity ratio, Percent Predicted Forced Expiratory Volume in 1 second, and Percent Predicted Forced Vital Capacity. Measurements and Main Results In adjusted analyses there were statistically significant independent associations between a) higher asymmetric dimethylarginine, lower Forced Expiratory Volume in 1 second and lower Forced Vital Capacity; and b) lower L-arginine/asymmetric dimethylarginine ratio, lower Forced Expiratory Volume in 1 second, lower Percent Predicted Forced Expiratory Volume in 1 second and lower Percent Predicted Forced Vital Capacity. By contrast, no significant associations were observed between symmetric dimethylarginine and lung function. Conclusions After adjusting for clinical, demographic, biochemical, and pharmacological confounders, higher serum asymmetric dimethylarginine was independently associated with a reduction in key measures of lung function. Further research is needed to determine if methylarginines predict the decline in lung function. PMID:23690915

A protein-dependent side-chain rotamer library.

PubMed

Bhuyan, Md Shariful Islam; Gao, Xin

2011-12-14

Protein side-chain packing problem has remained one of the key open problems in bioinformatics. The three main components of protein side-chain prediction methods are a rotamer library, an energy function and a search algorithm. Rotamer libraries summarize the existing knowledge of the experimentally determined structures quantitatively. Depending on how much contextual information is encoded, there are backbone-independent rotamer libraries and backbone-dependent rotamer libraries. Backbone-independent libraries only encode sequential information, whereas backbone-dependent libraries encode both sequential and locally structural information. However, side-chain conformations are determined by spatially local information, rather than sequentially local information. Since in the side-chain prediction problem, the backbone structure is given, spatially local information should ideally be encoded into the rotamer libraries. In this paper, we propose a new type of backbone-dependent rotamer library, which encodes structural information of all the spatially neighboring residues. We call it protein-dependent rotamer libraries. Given any rotamer library and a protein backbone structure, we first model the protein structure as a Markov random field. Then the marginal distributions are estimated by the inference algorithms, without doing global optimization or search. The rotamers from the given library are then re-ranked and associated with the updated probabilities. Experimental results demonstrate that the proposed protein-dependent libraries significantly outperform the widely used backbone-dependent libraries in terms of the side-chain prediction accuracy and the rotamer ranking ability. Furthermore, without global optimization/search, the side-chain prediction power of the protein-dependent library is still comparable to the global-search-based side-chain prediction methods.

Predicting Incursion of Plant Invaders into Kruger National Park, South Africa: The Interplay of General Drivers and Species-Specific Factors

PubMed Central

Jarošík, Vojtěch; Pyšek, Petr; Foxcroft, Llewellyn C.; Richardson, David M.; Rouget, Mathieu; MacFadyen, Sandra

2011-01-01

Background Overcoming boundaries is crucial for incursion of alien plant species and their successful naturalization and invasion within protected areas. Previous work showed that in Kruger National Park, South Africa, this process can be quantified and that factors determining the incursion of invasive species can be identified and predicted confidently. Here we explore the similarity between determinants of incursions identified by the general model based on a multispecies assemblage, and those identified by species-specific models. We analyzed the presence and absence of six invasive plant species in 1.0×1.5 km segments along the border of the park as a function of environmental characteristics from outside and inside the KNP boundary, using two data-mining techniques: classification trees and random forests. Principal Findings The occurrence of Ageratum houstonianum, Chromolaena odorata, Xanthium strumarium, Argemone ochroleuca, Opuntia stricta and Lantana camara can be reliably predicted based on landscape characteristics identified by the general multispecies model, namely water runoff from surrounding watersheds and road density in a 10 km radius. The presence of main rivers and species-specific combinations of vegetation types are reliable predictors from inside the park. Conclusions The predictors from the outside and inside of the park are complementary, and are approximately equally reliable for explaining the presence/absence of current invaders; those from the inside are, however, more reliable for predicting future invasions. Landscape characteristics determined as crucial predictors from outside the KNP serve as guidelines for management to enact proactive interventions to manipulate landscape features near the KNP to prevent further incursions. Predictors from the inside the KNP can be used reliably to identify high-risk areas to improve the cost-effectiveness of management, to locate invasive plants and target them for eradication. PMID:22194893

Predicting incursion of plant invaders into Kruger National Park, South Africa: the interplay of general drivers and species-specific factors.

PubMed

Jarošík, Vojtěch; Pyšek, Petr; Foxcroft, Llewellyn C; Richardson, David M; Rouget, Mathieu; MacFadyen, Sandra

2011-01-01

Overcoming boundaries is crucial for incursion of alien plant species and their successful naturalization and invasion within protected areas. Previous work showed that in Kruger National Park, South Africa, this process can be quantified and that factors determining the incursion of invasive species can be identified and predicted confidently. Here we explore the similarity between determinants of incursions identified by the general model based on a multispecies assemblage, and those identified by species-specific models. We analyzed the presence and absence of six invasive plant species in 1.0×1.5 km segments along the border of the park as a function of environmental characteristics from outside and inside the KNP boundary, using two data-mining techniques: classification trees and random forests. The occurrence of Ageratum houstonianum, Chromolaena odorata, Xanthium strumarium, Argemone ochroleuca, Opuntia stricta and Lantana camara can be reliably predicted based on landscape characteristics identified by the general multispecies model, namely water runoff from surrounding watersheds and road density in a 10 km radius. The presence of main rivers and species-specific combinations of vegetation types are reliable predictors from inside the park. The predictors from the outside and inside of the park are complementary, and are approximately equally reliable for explaining the presence/absence of current invaders; those from the inside are, however, more reliable for predicting future invasions. Landscape characteristics determined as crucial predictors from outside the KNP serve as guidelines for management to enact proactive interventions to manipulate landscape features near the KNP to prevent further incursions. Predictors from the inside the KNP can be used reliably to identify high-risk areas to improve the cost-effectiveness of management, to locate invasive plants and target them for eradication.

Applying theory of planned behavior to predict exercise maintenance in sarcopenic elderly.

PubMed

Ahmad, Mohamad Hasnan; Shahar, Suzana; Teng, Nur Islami Mohd Fahmi; Manaf, Zahara Abdul; Sakian, Noor Ibrahim Mohd; Omar, Baharudin

2014-01-01

This study aimed to determine the factors associated with exercise behavior based on the theory of planned behavior (TPB) among the sarcopenic elderly people in Cheras, Kuala Lumpur. A total of 65 subjects with mean ages of 67.5±5.2 (men) and 66.1±5.1 (women) years participated in this study. Subjects were divided into two groups: 1) exercise group (n=34; 25 men, nine women); and 2) the control group (n=31; 22 men, nine women). Structural equation modeling, based on TPB components, was applied to determine specific factors that most contribute to and predict actual behavior toward exercise. Based on the TPB's model, attitude (β=0.60) and perceived behavioral control (β=0.24) were the major predictors of intention to exercise among men at the baseline. Among women, the subjective norm (β=0.82) was the major predictor of intention to perform the exercise at the baseline. After 12 weeks, attitude (men's, β=0.68; women's, β=0.24) and subjective norm (men's, β=0.12; women's, β=0.87) were the predictors of the intention to perform the exercise. "Feels healthier with exercise" was the specific factor to improve the intention to perform and to maintain exercise behavior in men (β=0.36) and women (β=0.49). "Not motivated to perform exercise" was the main barrier among men's intention to exercise. The intention to perform the exercise was able to predict actual behavior regarding exercise at the baseline and at 12 weeks of an intervention program. As a conclusion, TPB is a useful model to determine and to predict maintenance of exercise in the sarcopenic elderly.

Applying theory of planned behavior to predict exercise maintenance in sarcopenic elderly

PubMed Central

Ahmad, Mohamad Hasnan; Shahar, Suzana; Teng, Nur Islami Mohd Fahmi; Manaf, Zahara Abdul; Sakian, Noor Ibrahim Mohd; Omar, Baharudin

2014-01-01

This study aimed to determine the factors associated with exercise behavior based on the theory of planned behavior (TPB) among the sarcopenic elderly people in Cheras, Kuala Lumpur. A total of 65 subjects with mean ages of 67.5±5.2 (men) and 66.1±5.1 (women) years participated in this study. Subjects were divided into two groups: 1) exercise group (n=34; 25 men, nine women); and 2) the control group (n=31; 22 men, nine women). Structural equation modeling, based on TPB components, was applied to determine specific factors that most contribute to and predict actual behavior toward exercise. Based on the TPB’s model, attitude (β=0.60) and perceived behavioral control (β=0.24) were the major predictors of intention to exercise among men at the baseline. Among women, the subjective norm (β=0.82) was the major predictor of intention to perform the exercise at the baseline. After 12 weeks, attitude (men’s, β=0.68; women’s, β=0.24) and subjective norm (men’s, β=0.12; women’s, β=0.87) were the predictors of the intention to perform the exercise. “Feels healthier with exercise” was the specific factor to improve the intention to perform and to maintain exercise behavior in men (β=0.36) and women (β=0.49). “Not motivated to perform exercise” was the main barrier among men’s intention to exercise. The intention to perform the exercise was able to predict actual behavior regarding exercise at the baseline and at 12 weeks of an intervention program. As a conclusion, TPB is a useful model to determine and to predict maintenance of exercise in the sarcopenic elderly. PMID:25258524

Determinants of plasma PCB, brominated flame retardants, and organochlorine pesticides in pregnant women and 3 year old children in The Norwegian Mother and Child Cohort Study.

PubMed

Caspersen, Ida Henriette; Kvalem, Helen Engelstad; Haugen, Margaretha; Brantsæter, Anne Lise; Meltzer, Helle Margrete; Alexander, Jan; Thomsen, Cathrine; Frøshaug, May; Bremnes, Nanna Margrethe Bruun; Broadwell, Sharon Lynn; Granum, Berit; Kogevinas, Manolis; Knutsen, Helle Katrine

2016-04-01

Exposure to persistent organic pollutants (POPs) during prenatal and postnatal life has been extensively studied in relation to adverse health effects in children. The aim was to identify determinants of the concentrations of polychlorinated biphenyls (PCBs), brominated flame retardants (polybrominated diphenyl ethers, PBDEs; polybrominated biphenyl, PBB), and organochlorine pesticides (OCPs) in blood samples from pregnant women and children in The Norwegian Mother and Child Cohort Study (MoBa). Blood samples were collected from two independent subsamples within MoBa; a group of women (n=96) enrolled in mid-pregnancy during the years 2002-2008 and a group of 3 year old children (n=99) participating during 2010-2011. PCB congeners (74, 99, 138, 153, 180, 170, 194, 209, 105, 114, 118, 156, 157, 167, and 189), brominated flame retardants (PBDE-28, 47, 99, 100, 153, 154, and PBB-153), as well as the OCPs hexachlorobenzene (HCB), oxychlordane, 4,4'dichlorodiphenyltrichloroethane (DDT), and 4,4'dichlorodiphenyldichloroethylene (DDE) were measured in both pregnant women and children. Age, low parity, and low pre-pregnant BMI were the most important determinants of increased plasma concentrations of POPs in pregnant women. In 3 year old children, prolonged breastfeeding duration was a major determinant of increased POP concentrations. Estimated dietary exposure to PCBs during pregnancy was positively associated with plasma concentrations in 3 year old children, but not in pregnant women. Plasma concentrations were approximately 40% higher in children compared to pregnant women. Several factors associated with exposure and toxicokinetics, i.e. accumulation, excretion and transfer via breastmilk of POPs were the main predictors of POP levels in pregnant women and children. Diet, which is the main exposure source for these compounds in the general population, was found to predict PCB levels only among children. For the PBDEs, for which non-dietary sources are more important, toxicokinetic factors appeared to have less predictive impact. Copyright © 2015 Elsevier Inc. All rights reserved.

Orbit of the OJ287 black hole binary as determined from the General Relativity centenary flare

NASA Astrophysics Data System (ADS)

Valtonen, Mauri; Gopakumar, Achamveedu; Mikkola, Seppo; Zola, Staszek; Ciprini, Stefano; Matsumoto, Katsura; Sadakane, Kozo; Kidger, Mark; Gazeas, Kosmas; Nilsson, Kari; Berdyugin, Andrei; Piirola, Vilppu; Jermak, Helen; Baliyan, Kiran; Hudec, Rene; Reichart, Daniel

2016-05-01

OJ287 goes through large optical flares twice each 12 years. The times of these flares have been predicted successfully now 5 times using a black hole binary model. In this model a secondary black hole goes around a primary black hole, impacting the accretion disk of the latter twice per orbital period, creating a thermal flare. Together with 6 flares from the historical data base, the set of flare timings determines uniquely the 7 parameters of the model: the two masses, the primary spin, the major axis, eccentricity and the phase of the orbit, plus a time delay parameter that gives the extent of time between accretion disk impacts and the related optical flares. Based on observations by the OJ287-15/16 Collaboration, OJ287 went into the phase of rapid flux rise on November 25, on the centenary of Einstein’s General Relativity, and peaked on December 5. At that time OJ287 was the brightest in over 30 years in optical wavelengths. The flare was of low polarization, and did not extend beyond the optical/UV region of the spectrum. On top of the main flare there were a number of small flares; their excess brightness correlates well with the simultaneous X-ray data. With these properties the main flare qualifies as the marker of the orbit of the secondary going around the primary black hole. Since the orbit solution is strongly over-determined, its parameters are known very accurately, at better than one percent level for the masses and the spin. The next flare is predicted to peak on July 28, 2019.Detailed monitoring of this event should allow us to test, for the first time, the celebrated black hole no-hair theorem for a massive black hole at the 10% level. The present data is consistent with the theorem only at a 30% level. The main difficulty in observing OJ287 from Earth at our predicted epoch is its closeness to the sun. Therefore, it is desirable to monitor OJ287 from a space-based telescope not in the vicinity of Earth. Unfortunately, this unique opportunity for testing the above celebrated theorem of General Relativity using OJ287 will not be available again until after several orbital cycles.The full list of participants in the OJ287-15/16 Collaboration is found in ApJL 819, L37, 2016.

The Maternal Legacy: Female Identity Predicts Offspring Sex Ratio in the Loggerhead Sea Turtle.

PubMed

Reneker, Jaymie L; Kamel, Stephanie J

2016-07-01

In organisms with temperature-dependent sex determination, the incubation environment plays a key role in determining offspring sex ratios. Given that global temperatures have warmed approximately 0.6 °C in the last century, it is necessary to consider how organisms will adjust to climate change. To better understand the degree to which mothers influence the sex ratios of their offspring, we use 24 years of nesting data for individual female loggerhead sea turtles (Caretta caretta) observed on Bald Head Island, North Carolina. We find that maternal identity is the best predictor of nest sex ratio in univariate and multivariate predictive models. We find significant variability in estimated nest sex ratios among mothers, but a high degree of consistency within mothers, despite substantial spatial and temporal thermal variation. Our results suggest that individual differences in nesting preferences are the main driver behind divergences in nest sex ratios. As such, a female's ability to plastically adjust her nest sex ratios in response to environmental conditions is constrained, potentially limiting how individuals behaviorally mitigate the effects of environmental change. Given that many loggerhead populations already show female-biased offspring sex ratios, understanding maternal behavioral responses is critical for predicting the future of long-lived species vulnerable to extinction.

The Maternal Legacy: Female Identity Predicts Offspring Sex Ratio in the Loggerhead Sea Turtle

PubMed Central

Reneker, Jaymie L.; Kamel, Stephanie J.

2016-01-01

In organisms with temperature-dependent sex determination, the incubation environment plays a key role in determining offspring sex ratios. Given that global temperatures have warmed approximately 0.6 °C in the last century, it is necessary to consider how organisms will adjust to climate change. To better understand the degree to which mothers influence the sex ratios of their offspring, we use 24 years of nesting data for individual female loggerhead sea turtles (Caretta caretta) observed on Bald Head Island, North Carolina. We find that maternal identity is the best predictor of nest sex ratio in univariate and multivariate predictive models. We find significant variability in estimated nest sex ratios among mothers, but a high degree of consistency within mothers, despite substantial spatial and temporal thermal variation. Our results suggest that individual differences in nesting preferences are the main driver behind divergences in nest sex ratios. As such, a female’s ability to plastically adjust her nest sex ratios in response to environmental conditions is constrained, potentially limiting how individuals behaviorally mitigate the effects of environmental change. Given that many loggerhead populations already show female-biased offspring sex ratios, understanding maternal behavioral responses is critical for predicting the future of long-lived species vulnerable to extinction. PMID:27363786

Determination and prediction of the magnetic anisotropy of Mn ions.

PubMed

Duboc, Carole

2016-10-24

This tutorial is dedicated to the investigation of magnetic anisotropy using both electron paramagnetic resonance (EPR) spectroscopy for its experimental determination and quantum chemistry for its theoretical prediction. Such an approach could lead to the definition of magneto-structural correlation essential for the rational design of complexes with targeted magnetic properties or for the identification of unknown reactive metallic species involved in catalysis. To illustrate this combined approach the high spin Mn II , Mn III and Mn IV ions have been taken as specific examples. The first part deals with the analysis of the EPR experiments as a function of the ions under investigation and the conditions of the measurements, specifically: (i) EPR spectra recorded under high vs. low frequency conditions with respect to magnetic anisotropy, (ii) EPR spectra of non-integer (Kramers) vs. integer (non-Kramers) spin states and (iii) mono- vs. multi-frequency EPR spectra. In the second part, two main quantum chemical approaches, which have proven their capability to predict magnetic anisotropy, are described. More importantly, these calculations give access to the different contributions of zero field splitting, key information for the full understanding of magnetic anisotropy. The last part demonstrates that such a combined experimental and theoretical approach allows for the definition of magneto-structural correlations.

Correlated miR-mRNA expression signatures of mouse hematopoietic stem and progenitor cell subsets predict "Stemness" and "Myeloid" interaction networks.

PubMed

Heiser, Diane; Tan, Yee Sun; Kaplan, Ian; Godsey, Brian; Morisot, Sebastien; Cheng, Wen-Chih; Small, Donald; Civin, Curt I

2014-01-01

Several individual miRNAs (miRs) have been implicated as potent regulators of important processes during normal and malignant hematopoiesis. In addition, many miRs have been shown to fine-tune intricate molecular networks, in concert with other regulatory elements. In order to study hematopoietic networks as a whole, we first created a map of global miR expression during early murine hematopoiesis. Next, we determined the copy number per cell for each miR in each of the examined stem and progenitor cell types. As data is emerging indicating that miRs function robustly mainly when they are expressed above a certain threshold (∼100 copies per cell), our database provides a resource for determining which miRs are expressed at a potentially functional level in each cell type. Finally, we combine our miR expression map with matched mRNA expression data and external prediction algorithms, using a Bayesian modeling approach to create a global landscape of predicted miR-mRNA interactions within each of these hematopoietic stem and progenitor cell subsets. This approach implicates several interaction networks comprising a "stemness" signature in the most primitive hematopoietic stem cell (HSC) populations, as well as "myeloid" patterns associated with two branches of myeloid development.

Novel kinetic model of the removal of divalent heavy metal ions from aqueous solutions by natural clinoptilolite.

PubMed

Jovanovic, Mina; Rajic, Nevenka; Obradovic, Bojana

2012-09-30

Removal of heavy metal ions from aqueous solutions using zeolites is widely described by pseudo-second order kinetics although this model may not be valid under all conditions. In this work, we have extended approaches used for derivation of this model in order to develop a novel kinetic model that is related to the ion exchange mechanism underlying sorption of metal ions in zeolites. The novel model assumed two reversible steps, i.e. release of sodium ions from the zeolite lattice followed by bonding of the metal ion. The model was applied to experimental results of Cu(II) sorption by natural clinoptilolite-rich zeolitic tuff at different initial concentrations and temperatures and then validated by predictions of ion exchange kinetics of other divalent heavy metal ions (i.e. Mn(II), Zn(II) and Pb(II)). Model predictions were in excellent agreements with experimental data for all investigated systems. In regard to the proposed mechanism, modeling results implied that the sodium ion release rate was constant for all investigated metals while the overall rate was mainly determined by the rate of heavy metal ion bonding to the lattice. In addition, prediction capabilities of the novel model were demonstrated requiring one experimentally determined parameter, only. Copyright © 2012 Elsevier B.V. All rights reserved.

Application of Time-series Model to Predict Groundwater Quality Parameters for Agriculture: (Plain Mehran Case Study)

NASA Astrophysics Data System (ADS)

Mehrdad Mirsanjari, Mir; Mohammadyari, Fatemeh

2018-03-01

Underground water is regarded as considerable water source which is mainly available in arid and semi arid with deficient surface water source. Forecasting of hydrological variables are suitable tools in water resources management. On the other hand, time series concepts is considered efficient means in forecasting process of water management. In this study the data including qualitative parameters (electrical conductivity and sodium adsorption ratio) of 17 underground water wells in Mehran Plain has been used to model the trend of parameters change over time. Using determined model, the qualitative parameters of groundwater is predicted for the next seven years. Data from 2003 to 2016 has been collected and were fitted by AR, MA, ARMA, ARIMA and SARIMA models. Afterward, the best model is determined using information criterion or Akaike (AIC) and correlation coefficient. After modeling parameters, the map of agricultural land use in 2016 and 2023 were generated and the changes between these years were studied. Based on the results, the average of predicted SAR (Sodium Adsorption Rate) in all wells in the year 2023 will increase compared to 2016. EC (Electrical Conductivity) average in the ninth and fifteenth holes and decreases in other wells will be increased. The results indicate that the quality of groundwater for Agriculture Plain Mehran will decline in seven years.

Predicting Occurrence of Spine Surgery Complications Using "Big Data" Modeling of an Administrative Claims Database.

PubMed

Ratliff, John K; Balise, Ray; Veeravagu, Anand; Cole, Tyler S; Cheng, Ivan; Olshen, Richard A; Tian, Lu

2016-05-18

Postoperative metrics are increasingly important in determining standards of quality for physicians and hospitals. Although complications following spinal surgery have been described, procedural and patient variables have yet to be incorporated into a predictive model of adverse-event occurrence. We sought to develop a predictive model of complication occurrence after spine surgery. We used longitudinal prospective data from a national claims database and developed a predictive model incorporating complication type and frequency of occurrence following spine surgery procedures. We structured our model to assess the impact of features such as preoperative diagnosis, patient comorbidities, location in the spine, anterior versus posterior approach, whether fusion had been performed, whether instrumentation had been used, number of levels, and use of bone morphogenetic protein (BMP). We assessed a variety of adverse events. Prediction models were built using logistic regression with additive main effects and logistic regression with main effects as well as all 2 and 3-factor interactions. Least absolute shrinkage and selection operator (LASSO) regularization was used to select features. Competing approaches included boosted additive trees and the classification and regression trees (CART) algorithm. The final prediction performance was evaluated by estimating the area under a receiver operating characteristic curve (AUC) as predictions were applied to independent validation data and compared with the Charlson comorbidity score. The model was developed from 279,135 records of patients with a minimum duration of follow-up of 30 days. Preliminary assessment showed an adverse-event rate of 13.95%, well within norms reported in the literature. We used the first 80% of the records for training (to predict adverse events) and the remaining 20% of the records for validation. There was remarkable similarity among methods, with an AUC of 0.70 for predicting the occurrence of adverse events. The AUC using the Charlson comorbidity score was 0.61. The described model was more accurate than Charlson scoring (p < 0.01). We present a modeling effort based on administrative claims data that predicts the occurrence of complications after spine surgery. We believe that the development of a predictive modeling tool illustrating the risk of complication occurrence after spine surgery will aid in patient counseling and improve the accuracy of risk modeling strategies. Copyright © 2016 by The Journal of Bone and Joint Surgery, Incorporated.

Discrimination of orange beverage emulsions with different formulations using multivariate analysis.

PubMed

Mirhosseini, Hamed; Tan, Chin Ping

2010-06-01

The constituents in a food emulsion interact with each other, either physically or chemically, determining the overall physico-chemical and organoleptic properties of the final product. Thus, the main objective of present study was to investigate the effect of emulsion components on beverage emulsion properties. In most cases, the second-order polynomial regression models with no significant (P > 0.05) lack of fit and high adjusted coefficient of determination (adjusted R(2), 0.851-0.996) were significantly fitted to explain the beverage emulsion properties as function of main emulsion components. The main effect of gum arabic was found to be significant (P < 0.05) in all response regression models. Orange beverage emulsion containing 222.0 g kg(-1) gum arabic, 2.4 g kg(-1) xanthan gum and 152.7 g kg(-1) orange oil was predicted to provide the desirable emulsion properties. The present study suggests that the concentration of gum arabic should be considered as a primary critical factor for the formulation of orange beverage emulsion. This study also indicated that the interaction effect between xanthan gum and orange oil showed the most significant (P < 0.05) effect among all interaction effects influencing all the physicochemical properties except for density. Copyright (c) 2010 Society of Chemical Industry.

[Overload felt by the figure of the main caregiver in a cohort of patients with multiple pathologies].

PubMed

Moreno-Gaviño, Lourdes; Bernabeu-Wittel, Máximo; Alvarez-Tello, Margarita; Rincón Gómez, Manuel; Bohórquez Colombo, Pilar; Cassani Garza, Manuel; Ollero Baturone, Manuel; García-Morillo, Salvador

2008-04-01

To determine the profile of the main caregiver (MC) and the factors associated with her/his care burden, in a multi-centre cohort of patients with multiple pathologies (PMP). Multi-centre cross-sectional study. Four health districts in the Virgen del Rocío University Hospitals Health Area, Seville, Spain. The PMP cohort was created by checking all the patients who satisfied the health department criteria for PMP (2002): patients suffering from chronic diseases in 2 or more of the 7 clinical categories defined. The profile of PMP caregiver was determined for all patients. The caregiver strain index (CSI) was determined by the index of care stress (ICS). Predictive factors were analysed by the Student t, ANOVA, and Pearson's tests. Multivariate analysis was performed by a forward stepwise linear regression model. The interview was attended by 461 (69%) out of 662 eligible PMP. Of these, 293 (63.6%) had an MC whose mean age was 62 (15) years; 80% of them were women. First-degree relatives made up 88% of caregivers, with spouses 49.7% of them (n=146). In 41.5%, the CSI was >7 points (mean CSI was 5.35 [3.5]). This was higher in those caring for PMP with neurological illnesses (7 [3.2 vs 4.5 [3.3]; P=.0001). The CSI was compared directly with the medical vulnerability of the PMP (R=0.37; P=.001), cognitive deterioration on the Pfeiffer scale (PS) (R=0.4; P=.0001), and inversely with functional status on Barthel's scale (BS) (R=-0.67; P=.0001). Patient's age (P=.03), his/her medical vulnerability (P=.016) and functional (P< .0001) and cognitive (P=.019) deterioration were independently associated with the CSI. The profile of the MC of the PMP cohort corresponded mainly to first-degree female relatives around sixty years old. The burden of care was high in more than a third of them. Predictive factors were age, medical vulnerability, and the functional and cognitive deterioration of the PMP.

Using predicted 30 day mortality to plan postoperative colorectal surgery care: a cohort study.

PubMed

Swart, M; Carlisle, J B; Goddard, J

2017-01-01

Preoperative identification of high-risk surgical patients might help to reduce postoperative morbidity and mortality. Using a patient's predicted 30 day mortality to plan postoperative high-dependency unit (HDU) care after elective colorectal surgery might be associated with reduced postoperative morbidity. The 30 day postoperative mortality was predicted for 504 elective colorectal surgical patients in a preoperative clinic. The prediction was used to determine postoperative surgical ward or HDU care. Those with a predicted 30 day mortality of 1-3% mortality, and thus deemed at intermediate risk, had either planned HDU care (n=68) or planned ward care (n=139). The main outcome measures were emergency laparotomy and unplanned critical care admission. There were more emergency laparotomies and unplanned critical care admissions in patients with a predicted 30 day mortality of 1-3% who went to an HDU after surgery compared with patients who went to a ward: 0 vs 14 (10%), P=0.0056 and 0 vs 22 (16%), P=0.0002, respectively. Planned postoperative critical care was associated with a lower rate of complications after elective colorectal surgery. © The Author 2016. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Deciphering mRNA Sequence Determinants of Protein Production Rate

NASA Astrophysics Data System (ADS)

Szavits-Nossan, Juraj; Ciandrini, Luca; Romano, M. Carmen

2018-03-01

One of the greatest challenges in biophysical models of translation is to identify coding sequence features that affect the rate of translation and therefore the overall protein production in the cell. We propose an analytic method to solve a translation model based on the inhomogeneous totally asymmetric simple exclusion process, which allows us to unveil simple design principles of nucleotide sequences determining protein production rates. Our solution shows an excellent agreement when compared to numerical genome-wide simulations of S. cerevisiae transcript sequences and predicts that the first 10 codons, which is the ribosome footprint length on the mRNA, together with the value of the initiation rate, are the main determinants of protein production rate under physiological conditions. Finally, we interpret the obtained analytic results based on the evolutionary role of the codons' choice for regulating translation rates and ribosome densities.

Perceived STD risk, relationship, and health values in adolescents' delaying sexual intercourse with new partners

PubMed Central

Rosengard, C; Adler, N; Millstein, S; Gurvey, J; Ellen, J

2004-01-01

Objectives: To examine the amount of time adolescents waited to have intercourse with past partners (main and casual), and intentions to delay with future partners. To determine psychosocial factors which predict delay intentions among adolescent males and females with future partners (main and casual). Methods: Adolescent STD clinic attendees were approached before clinical appointments to participate in an interview. Data from 205 participants who had previous experience with both main and casual partners were used in the current study. Results: Adolescents waited less time to have intercourse with most recent casual than with most recent main partners (χ2 = 31.97, p<0.0001). The amount of time waited with past partners was shorter than intended time to wait in future relationships (medians of 1 month v 2 months (main) (t = 3.47, p<0.0010; medians of 2 weeks v 1 month (casual) (t = 6.14, p<0.0001)). Factors influencing intentions to delay intercourse with future main partners differed by sex; males were negatively influenced by importance of sex in relationships, while females were positively influenced by importance of intimacy in relationships, perceived risk of STDs, and health values. Conclusions: Implications for designing interventions for adolescent males and females are discussed. PMID:15054176

Prediction of main factors’ values of air transportation system safety based on system dynamics

NASA Astrophysics Data System (ADS)

Spiridonov, A. Yu; Rezchikov, A. F.; Kushnikov, V. A.; Ivashchenko, V. A.; Bogomolov, A. S.; Filimonyuk, L. Yu; Dolinina, O. N.; Kushnikova, E. V.; Shulga, T. E.; Tverdokhlebov, V. A.; Kushnikov, O. V.; Fominykh, D. S.

2018-05-01

On the basis of the system-dynamic approach [1-8], a set of models has been developed that makes it possible to analyse and predict the values of the main safety indicators for the operation of aviation transport systems.

The predictive protective control of the heat exchanger

NASA Astrophysics Data System (ADS)

Nevriva, Pavel; Filipova, Blanka; Vilimec, Ladislav

2016-06-01

The paper deals with the predictive control applied to flexible cogeneration energy system FES. FES was designed and developed by the VITKOVICE POWER ENGINEERING joint-stock company and represents a new solution of decentralized cogeneration energy sources. In FES, the heating medium is flue gas generated by combustion of a solid fuel. The heated medium is power gas, which is a gas mixture of air and water steam. Power gas is superheated in the main heat exchanger and led to gas turbines. To protect the main heat exchanger against damage by overheating, the novel predictive protective control based on the mathematical model of exchanger was developed. The paper describes the principle, the design and the simulation of the predictive protective method applied to main heat exchanger of FES.

A broad assessment of factors determining Culicoides imicola abundance: modelling the present and forecasting its future in climate change scenarios.

PubMed

Acevedo, Pelayo; Ruiz-Fons, Francisco; Estrada, Rosa; Márquez, Ana Luz; Miranda, Miguel Angel; Gortázar, Christian; Lucientes, Javier

2010-12-06

Bluetongue (BT) is still present in Europe and the introduction of new serotypes from endemic areas in the African continent is a possible threat. Culicoides imicola remains one of the most relevant BT vectors in Spain and research on the environmental determinants driving its life cycle is key to preventing and controlling BT. Our aim was to improve our understanding of the biotic and abiotic determinants of C. imicola by modelling its present abundance, studying the spatial pattern of predicted abundance in relation to BT outbreaks, and investigating how the predicted current distribution and abundance patterns might change under future (2011-2040) scenarios of climate change according to the Intergovernmental Panel on Climate Change. C. imicola abundance data from the bluetongue national surveillance programme were modelled with spatial, topoclimatic, host and soil factors. The influence of these factors was further assessed by variation partitioning procedures. The predicted abundance of C. imicola was also projected to a future period. Variation partitioning demonstrated that the pure effect of host and topoclimate factors explained a high percentage (>80%) of the variation. The pure effect of soil followed in importance in explaining the abundance of C. imicola. A close link was confirmed between C. imicola abundance and BT outbreaks. To the best of our knowledge, this study is the first to consider wild and domestic hosts in predictive modelling for an arthropod vector. The main findings regarding the near future show that there is no evidence to suggest that there will be an important increase in the distribution range of C. imicola; this contrasts with an expected increase in abundance in the areas where it is already present in mainland Spain. What may be expected regarding the future scenario for orbiviruses in mainland Spain, is that higher predicted C. imicola abundance may significantly change the rate of transmission of orbiviruses.

Statistical similarity measures for link prediction in heterogeneous complex networks

NASA Astrophysics Data System (ADS)

Shakibian, Hadi; Charkari, Nasrollah Moghadam

2018-07-01

The majority of the link prediction measures in heterogeneous complex networks rely on the nodes connectivities while less attention has been paid to the importance of the nodes and paths. In this paper, we propose some new meta-path based statistical similarity measures to properly perform link prediction task. The main idea in the proposed measures is to drive some co-occurrence events in a number of co-occurrence matrices that are occurred between the visited nodes obeying a meta-path. The extracted co-occurrence matrices are analyzed in terms of the energy, inertia, local homogeneity, correlation, and information measure of correlation to determine various information theoretic measures. We evaluate the proposed measures, denoted as link energy, link inertia, link local homogeneity, link correlation, and link information measure of correlation, using a standard DBLP network data set. The results of the AUC score and Precision rate indicate the validity and accuracy of the proposed measures in comparison to the popular meta-path based similarity measures.

Asteroids - the modern challenge of celestial dynamics

NASA Astrophysics Data System (ADS)

Dikova, Smiliana

2002-11-01

Among the most powerful statements in Science are those that mark absolute limits to knowledge. For example, Relativity and Quantum Theory touched the limits of speed and accuracy. Deterministic Chaos - the new scientific paradigma of our days, also falls in this class theories. Chaos means complexity in space and unpredictability in time. It shows the limit of our basic counting system and leads to a limited predictability of the long time dynamical evolution. Perhaps for that reason, in 1986 Sir James Lighthill remarked for all physicists: "We collectively wish to apologize for having misled the general educated public by spreading ideas about the determinism of systems satisfying Newton's laws of motion that, after 1960, were proved incorrect." Our main thesis is that Asteroid Dynamics is the arena where the drama Chaos versus predictability is initiated and developed. The aim of the present research is to show the way in which Deterministic Chaos restricts the long term dynamical predictability of asteroid motions.

Dynamic interpretation of geoid anomalies

NASA Technical Reports Server (NTRS)

Hager, Bradford H.

1988-01-01

The NASA Geodynamics program has as two of its missions precise determination of spatial variations in earth's geopotential (or geoid) and highly accurate monitoring of polar motion, including changes in the length of day (LOD). For the past several years, data sets provided by NASA, along with data and models from other areas of geophysic were used to place fundamental contraints on the large scale dynamics of earth and her sister planet Venus. The main approach was using fluid mechanical models of mantle flow to predict the long-wavelength variations in the geoid.

Vapor ingestion in Centaur liquid-hydrogen tank

NASA Technical Reports Server (NTRS)

Symons, E. P.

1977-01-01

Vapor ingestion phenomena were investigated using scale models of the Centaur liquid hydrogen tank to determine the height of the free surface of the liquid when vapor is intially ingested into the tank outlet. Data are compared with an analysin and, is general the agreement is very good. Predictions are presented for minimum liquid levels required in the Centaur liquid hydrogen tank in order to prevent vapor ingestion when restarting the engines in space and the quantities of liquid remaining in the tank at vapor ingestion during main engine firing.

Application of empirical mode decomposition with local linear quantile regression in financial time series forecasting.

PubMed

Jaber, Abobaker M; Ismail, Mohd Tahir; Altaher, Alsaidi M

2014-01-01

This paper mainly forecasts the daily closing price of stock markets. We propose a two-stage technique that combines the empirical mode decomposition (EMD) with nonparametric methods of local linear quantile (LLQ). We use the proposed technique, EMD-LLQ, to forecast two stock index time series. Detailed experiments are implemented for the proposed method, in which EMD-LPQ, EMD, and Holt-Winter methods are compared. The proposed EMD-LPQ model is determined to be superior to the EMD and Holt-Winter methods in predicting the stock closing prices.

Stratigraphy and structure of coalbed methane reservoirs in the United States: an overview

USGS Publications Warehouse

Pashin, J.C.

1998-01-01

Stratigraphy and geologic structure determine the shape, continuity and permeability of coal and are therefore critical considerations for designing exploration and production strategies for coalbed methane. Coal in the United states is dominantly of Pennsylvanian, Cretaceous and Tertiary age, and to date, more than 90% of the coalbed methane produced is from Pennsylvanian and cretaceous strata of the Black Warrior and San Juan Basins. Investigations of these basins establish that sequence stratigraphy is a promising approach for regional characterization of coalbed methane reservoirs. Local stratigraphic variation within these strata is the product of sedimentologic and tectonic processes and is a consideration for selecting completion zones. Coalbed methane production in the United States is mainly from foreland and intermontane basins containing diverse compression and extensional structures. Balanced structural models can be used to construct and validate cross sections as well as to quantify layer-parallel strain and predict the distribution of fractures. Folds and faults influence gas and water production in diverse ways. However, interwell heterogeneity related to fractures and shear structures makes the performance of individual wells difficult to predict.Stratigraphy and geologic structure determine the shape, continuity and permeability of coal and are therefore critical considerations for designing exploration and production strategies for coalbed methane. Coal in the United States is dominantly of Pennsylvanian, Cretaceous and Tertiary age, and to date, more than 90% of the coalbed methane produced is from Pennsylvanian and Cretaceous strata of the Black Warrior and San Juan Basins. Investigations of these basins establish that sequence stratigraphy is a promising approach for regional characterization of coalbed methane reservoirs. Local stratigraphic variation within these strata is the product of sedimentologic and tectonic processes and is a consideration for selecting completion zones. Coalbed methane production in the United States is mainly from foreland and intermontane basins containing diverse compressional and extensional structures. Balanced structural models can be used to construct and validate cross sections as well as to quantify layer-parallel strain and predict the distribution of fractures. Folds and faults influence gas and water production in diverse ways. However, interwell heterogeneity related to fractures and shear structures makes the performance of individual wells difficult to predict.

Thinning of the ice sheet in northwest Greenland over the past forty years.

PubMed

Paterson, W S; Reeh, N

2001-11-01

Thermal expansion of the oceans, as well as melting of glaciers, ice sheets and ice caps have been the main contributors to global sea level rise over the past century. The greatest uncertainty in predicting future sea level changes lies with our estimates of the mass balance of the ice sheets in Greenland and Antarctica. Satellite measurements have been used to determine changes in these ice sheets on short timescales, demonstrating that surface-elevation changes on timescales of decades or less result mainly from variations in snow accumulation. Here we present direct measurements of the changes in surface elevation between 1954 and 1995 on a traverse across the north Greenland ice sheet. Measurements over a time interval of this length should reflect changes in ice flow-the important quantity for predicting changes in sea level-relatively unperturbed by short-term fluctuations in snow accumulation. We find only small changes in the eastern part of the transect, except for some thickening of the north ice stream. On the west side, however, the thinning rates of the ice sheet are significantly higher and thinning extends to higher elevations than had been anticipated from previous studies.

Results of magnetospheric barium ion cloud experiment of 1971

NASA Technical Reports Server (NTRS)

Adamson, D.; Fricke, C. L.; Long, S. A. T.

1975-01-01

The barium ion cloud experiment involved the release of about 2 kg of barium at an altitude of 31 482 km, a latitude of 6.926 N., and a longitude of 74.395 W. Significant erosion of plasma from the main ion core occurred during the initial phase of the ion cloud expansion. From the motion of the outermost striational filaments, the electric field components were determined to be 0.19 mV/m in the westerly direction and 0.68 mV/m in the inward direction. The differences between these components and those measured from balloons flown in the proximity of the extremity of the field line through the release point implied the existence of potential gradients along the magnetic field lines. The deceleration of the main core was greater than theoretically predicted. This was attributed to the formation of a polarization wake, resulting in an increase of the area of interaction and resistive dissipation at ionospheric levels. The actual orientation of the magnetic field line through the release point differed by about 10.5 deg from that predicted by magnetic field models that did not include the effect of ring current.

Assessment and prediction of urban air pollution caused by motor transport exhaust gases using computer simulation methods

NASA Astrophysics Data System (ADS)

Boyarshinov, Michael G.; Vaismana, Yakov I.

2016-10-01

The following methods were used in order to identify the pollution fields of urban air caused by the motor transport exhaust gases: the mathematical model, which enables to consider the influence of the main factors that determine pollution fields formation in the complex spatial domain; the authoring software designed for computational modeling of the gas flow, generated by numerous mobile point sources; the results of computing experiments on pollutant spread analysis and evolution of their concentration fields. The computational model of exhaust gas distribution and dispersion in a spatial domain, which includes urban buildings, structures and main traffic arteries, takes into account a stochastic character of cars apparition on the borders of the examined territory and uses a Poisson process. The model also considers the traffic lights switching and permits to define the fields of velocity, pressure and temperature of the discharge gases in urban air. The verification of mathematical model and software used confirmed their satisfactory fit to the in-situ measurements data and the possibility to use the obtained computing results for assessment and prediction of urban air pollution caused by motor transport exhaust gases.

Cartilage analysis by reflection spectroscopy

NASA Astrophysics Data System (ADS)

Laun, T.; Muenzer, M.; Wenzel, U.; Princz, S.; Hessling, M.

2015-07-01

A cartilage bioreactor with analytical functions for cartilage quality monitoring is being developed. For determining cartilage composition, reflection spectroscopy in the visible (VIS) and near infrared (NIR) spectral region is evaluated. Main goal is the determination of the most abundant cartilage compounds water, collagen I and collagen II. Therefore VIS and NIR reflection spectra of different cartilage samples of cow, pig and lamb are recorded. Due to missing analytical instrumentation for identifying the cartilage composition of these samples, typical literature concentration values are used for the development of chemometric models. In spite of these limitations the chemometric models provide good cross correlation results for the prediction of collagen I and II and water concentration based on the visible and the NIR reflection spectra.

The San Andreas fault experiment. [gross tectonic plates relative velocity

NASA Technical Reports Server (NTRS)

Smith, D. E.; Vonbun, F. O.

1973-01-01

A plan was developed during 1971 to determine gross tectonic plate motions along the San Andreas Fault System in California. Knowledge of the gross motion along the total fault system is an essential component in the construction of realistic deformation models of fault regions. Such mathematical models will be used in the future for studies which will eventually lead to prediction of major earthquakes. The main purpose of the experiment described is the determination of the relative velocity of the North American and the Pacific Plates. This motion being so extremely small, cannot be measured directly but can be deduced from distance measurements between points on opposite sites of the plate boundary taken over a number of years.

Application of Statistical Thermodynamics To Predict the Adsorption Properties of Polypeptides in Reversed-Phase HPLC.

PubMed

Tarasova, Irina A; Goloborodko, Anton A; Perlova, Tatyana Y; Pridatchenko, Marina L; Gorshkov, Alexander V; Evreinov, Victor V; Ivanov, Alexander R; Gorshkov, Mikhail V

2015-07-07

The theory of critical chromatography for biomacromolecules (BioLCCC) describes polypeptide retention in reversed-phase HPLC using the basic principles of statistical thermodynamics. However, whether this theory correctly depicts a variety of empirical observations and laws introduced for peptide chromatography over the last decades remains to be determined. In this study, by comparing theoretical results with experimental data, we demonstrate that the BioLCCC: (1) fits the empirical dependence of the polypeptide retention on the amino acid sequence length with R(2) > 0.99 and allows in silico determination of the linear regression coefficients of the log-length correction in the additive model for arbitrary sequences and lengths and (2) predicts the distribution coefficients of polypeptides with an accuracy from 0.98 to 0.99 R(2). The latter enables direct calculation of the retention factors for given solvent compositions and modeling of the migration dynamics of polypeptides separated under isocratic or gradient conditions. The obtained results demonstrate that the suggested theory correctly relates the main aspects of polypeptide separation in reversed-phase HPLC.

Joint nonlinearity effects in the design of a flexible truss structure control system

NASA Technical Reports Server (NTRS)

Mercadal, Mathieu

1986-01-01

Nonlinear effects are introduced in the dynamics of large space truss structures by the connecting joints which are designed with rather important tolerances to facilitate the assembly of the structures in space. The purpose was to develop means to investigate the nonlinear dynamics of the structures, particularly the limit cycles that might occur when active control is applied to the structures. An analytical method was sought and derived to predict the occurrence of limit cycles and to determine their stability. This method is mainly based on the quasi-linearization of every joint using describing functions. This approach was proven successful when simple dynamical systems were tested. Its applicability to larger systems depends on the amount of computations it requires, and estimates of the computational task tend to indicate that the number of individual sources of nonlinearity should be limited. Alternate analytical approaches, which do not account for every single nonlinearity, or the simulation of a simplified model of the dynamical system should, therefore, be investigated to determine a more effective way to predict limit cycles in large dynamical systems with an important number of distributed nonlinearities.

Research on the Mechanism of In-Plane Vibration on Friction Reduction

PubMed Central

Wang, Peng; Ni, Hongjian; Wang, Ruihe; Liu, Weili; Lu, Shuangfang

2017-01-01

A modified model for predicting the friction force between drill-string and borehole wall under in-plane vibrations was developed. It was found that the frictional coefficient in sliding direction decreased significantly after applying in-plane vibration on the bottom specimen. The friction reduction is due to the direction change of friction force, elastic deformation of surface asperities and the change of frictional coefficient. Normal load, surface topography, vibration direction, velocity ratio and interfacial shear factor are the main influence factors of friction force in sliding direction. Lower driving force can be realized for a pair of determinate rubbing surfaces under constant normal load by setting the driving direction along the minimum arithmetic average attack angle direction, and applying intense longitudinal vibration on the rubbing pair. The modified model can significantly improve the accuracy in predicting frictional coefficient under vibrating conditions, especially under the condition of lower velocity ratio. The results provide a theoretical gist for friction reduction technology by vibrating drill-string, and provide a reference for determination of frictional coefficient during petroleum drilling process, which has great significance for realizing digitized and intelligent drilling. PMID:28862679

An extension of the Theory of Planned Behavior to predict willingness to pay for the conservation of an urban park.

PubMed

López-Mosquera, Natalia; García, Teresa; Barrena, Ramo

2014-03-15

This paper relates the concept of moral obligation and the components of the Theory of Planned Behavior to determine their influence on the willingness to pay of visitors for park conservation. The sample consists of 190 visitors to an urban Spanish park. The mean willingness to pay estimated was 12.67€ per year. The results also indicated that moral norm was the major factor in predicting behavioral intention, followed by attitudes. The new relations established between the components of the Theory of Planned Behavior show that social norms significantly determine the attitudes, moral norms and perceived behavioral control of individuals. The proportion of explained variance shows that the inclusion of moral norms improves the explanatory power of the original model of the Theory of Planned Behavior (32-40%). Community-based social marketing and local campaigns are the main strategies that should be followed by land managers with the objective of promoting responsible, pro-environmental attitudes as well as a greater willingness to pay for this type of goods. Copyright © 2014 Elsevier Ltd. All rights reserved.

Prediction of preterm birth in twin gestations using biophysical and biochemical tests

PubMed Central

Conde-Agudelo, Agustin; Romero, Roberto

2018-01-01

The objective of this study was to determine the performance of biophysical and biochemical tests for the prediction of preterm birth in both asymptomatic and symptomatic women with twin gestations. We identified a total of 19 tests proposed to predict preterm birth, mainly in asymptomatic women. In these women, a single measurement of cervical length with transvaginal ultrasound before 25 weeks of gestation appears to be a good test to predict preterm birth. Its clinical potential is enhanced by the evidence that vaginal progesterone administration in asymptomatic women with twin gestations and a short cervix reduces neonatal morbidity and mortality associated with spontaneous preterm delivery. Other tests proposed for the early identification of asymptomatic women at increased risk of preterm birth showed minimal to moderate predictive accuracy. None of the tests evaluated in this review meet the criteria to be considered clinically useful to predict preterm birth among patients with an episode of preterm labor. However, a negative cervicovaginal fetal fibronectin test could be useful in identifying women who are not at risk for delivering within the next week, which could avoid unnecessary hospitalization and treatment. This review underscores the need to develop accurate tests for predicting preterm birth in twin gestations. Moreover, the use of interventions in these patients based on test results should be associated with the improvement of perinatal outcomes. PMID:25072736

Prediction of preterm birth in twin gestations using biophysical and biochemical tests.

PubMed

Conde-Agudelo, Agustin; Romero, Roberto

2014-12-01

The objective of this study was to determine the performance of biophysical and biochemical tests for the prediction of preterm birth in both asymptomatic and symptomatic women with twin gestations. We identified a total of 19 tests proposed to predict preterm birth, mainly in asymptomatic women. In these women, a single measurement of cervical length with transvaginal ultrasound before 25 weeks of gestation appears to be a good test to predict preterm birth. Its clinical potential is enhanced by the evidence that vaginal progesterone administration in asymptomatic women with twin gestations and a short cervix reduces neonatal morbidity and mortality associated with spontaneous preterm delivery. Other tests proposed for the early identification of asymptomatic women at increased risk of preterm birth showed minimal to moderate predictive accuracy. None of the tests evaluated in this review meet the criteria to be considered clinically useful to predict preterm birth among patients with an episode of preterm labor. However, a negative cervicovaginal fetal fibronectin test could be useful in identifying women who are not at risk for delivering within the next week, which could avoid unnecessary hospitalization and treatment. This review underscores the need to develop accurate tests for predicting preterm birth in twin gestations. Moreover, the use of interventions in these patients based on test results should be associated with the improvement of perinatal outcomes. Copyright © 2014. Published by Elsevier Inc.

Dissecting the relationship between protein structure and sequence variation

NASA Astrophysics Data System (ADS)

Shahmoradi, Amir; Wilke, Claus; Wilke Lab Team

2015-03-01

Over the past decade several independent works have shown that some structural properties of proteins are capable of predicting protein evolution. The strength and significance of these structure-sequence relations, however, appear to vary widely among different proteins, with absolute correlation strengths ranging from 0 . 1 to 0 . 8 . Here we present the results from a comprehensive search for the potential biophysical and structural determinants of protein evolution by studying more than 200 structural and evolutionary properties in a dataset of 209 monomeric enzymes. We discuss the main protein characteristics responsible for the general patterns of protein evolution, and identify sequence divergence as the main determinant of the strengths of virtually all structure-evolution relationships, explaining ~ 10 - 30 % of observed variation in sequence-structure relations. In addition to sequence divergence, we identify several protein structural properties that are moderately but significantly coupled with the strength of sequence-structure relations. In particular, proteins with more homogeneous back-bone hydrogen bond energies, large fractions of helical secondary structures and low fraction of beta sheets tend to have the strongest sequence-structure relation. BEACON-NSF center for the study of evolution in action.

Galactic helium-to-metals enrichment ratio (Delta Y/ Delta Z) from the analysis of local main sequence stars observed by HIPPARCOS

NASA Astrophysics Data System (ADS)

Gennaro, M.; Prada Moroni, P. G.; Degl'Innocenti, S.

We discuss the reliability of one of the most used method to determine the Helium-to-metals enrichment ratio, Delta Y / Delta Z, i.e. the photometric comparison of a selected data set of local disk low Main Sequence (MS) stars observed by HIPPARCOS and a new grid of stellar models with up-to-date input physics. Most of the attention has been devoted to evaluate the effects on the final results of different sources of uncertainty (observational errors, evolutionary effects, selection criteria, systematic uncertainties of the models, numerical errors). As a check of the result the procedure has been repeated using another, independent, data set: the low-MS of the Hyades cluster. The obtained of Delta Y/ Delta Z for the Hyades, together with spectroscopic determinations of [Fe/H] ratio, have been used to obtain the Y and Z values for the cluster. Isochrones have been calculated with the estimated chemical composition, obtaining a very good agreement between the predicted position of the Hyades MS and the observational data in the Color - Magnitude Diagram (CMD).

Galactic ΔY/ΔZ from the analysis of solar neighborhood main sequence stars

NASA Astrophysics Data System (ADS)

Gennaro, M.; Moroni, P. G. Prada; Degl'Innocenti, S.

2009-05-01

We discuss the reliability of one of the most used method to determine the helium-to-metals enrichment ratio (ΔY/ΔZ), i.e. the photometric comparison of a selected data set of local disk low main sequence (MS) stars observed by Hipparcos with a new grid of stellar models with up-to-date input physics. Most of the attention has been devoted to evaluate the effects on the final results of different sources of uncertainty (observational errors, evolutionary effects, selection criteria, systematic uncertainties of the models, numerical errors). As a check of the result the procedure has been repeated using another, independent, data set: the low-MS of the Hyades cluster. The obtained ΔY/ΔZ for the Hyades, together with spectroscopic determinations of [Fe/H] ratio, have been used to obtain the Y and Z values for the cluster. Isochrones have been calculated with the estimated chemical composition, obtaining a very good agreement between the predicted position of the Hyades MS and the observational data in the color-magnitude diagram.

Methodologies on estimating the energy requirements for maintenance and determining the net energy contents of feed ingredients in swine: a review of recent work.

PubMed

Li, Zhongchao; Liu, Hu; Li, Yakui; Lv, Zhiqian; Liu, Ling; Lai, Changhua; Wang, Junjun; Wang, Fenglai; Li, Defa; Zhang, Shuai

2018-01-01

In the past two decades, a considerable amount of research has focused on the determination of the digestible (DE) and metabolizable energy (ME) contents of feed ingredients fed to swine. Compared with the DE and ME systems, the net energy (NE) system is assumed to be the most accurate estimate of the energy actually available to the animal. However, published data pertaining to the measured NE content of ingredients fed to growing pigs are limited. Therefore, the Feed Data Group at the Ministry of Agricultural Feed Industry Centre (MAFIC) located at China Agricultural University has evaluated the NE content of many ingredients using indirect calorimetry. The present review summarizes the NE research works conducted at MAFIC and compares these results with those from other research groups on methodological aspect. These research projects mainly focus on estimating the energy requirements for maintenance and its impact on the determination, prediction, and validation of the NE content of several ingredients fed to swine. The estimation of maintenance energy is affected by methodology, growth stage, and previous feeding level. The fasting heat production method and the curvilinear regression method were used in MAFIC to estimate the NE requirement for maintenance. The NE contents of different feedstuffs were determined using indirect calorimetry through standard experimental procedure in MAFIC. Previously generated NE equations can also be used to predict NE in situations where calorimeters are not available. Although popular, the caloric efficiency is not a generally accepted method to validate the energy content of individual feedstuffs. In the future, more accurate and dynamic NE prediction equations aiming at specific ingredients should be established, and more practical validation approaches need to be developed.

Proximate analyses and predicting HHV of chars obtained from cocracking of petroleum vacuum residue with coal, plastics and biomass.

PubMed

Ahmaruzzaman, M

2008-07-01

Higher heating value (HHV) and analysis of chars obtained from cocracking of petroleum vacuum residue (XVR) with coal (SC), biomass (BG, CL) and plastics (PP, PS, BL) are important which define the energy content and determine the clean and efficient use of these chars. The main aim of the present study is to analyze the char obtained from cocracking in terms of their proximate analysis data and determination of the HHV of the chars. The char obtained from XVR+PP cocracking showed a HHV of 32.84 MJ/kg, whereas that from CL cracking showed a HHV of 18.52 MJ/kg. The experimentally determined heating values of the char samples obtained from cocracking have been correlated with the theoretical equation based on proximate analysis data. There exists a variety of correlations for predicting HHV from proximate analysis of fuels. Based upon proximate analysis data, the models were tested. The best results show coefficient of determination (R2) of 0.965 and average absolute and bias error of 3.07% and 0.41%, respectively. The heating values obtained from the model were in good agreement with that obtained by experiment. Proximate analysis of the chars obtained from the cocracking of XVR with coal, biomass and plastics showed that there exists a definite interaction of the reactive species, when they were cocracked together.

Main Determinants of Catastrophic Health Expenditures: A Bayesian Logit Approach on Iranian Household Survey Data (2010)

PubMed Central

Fazaeli, Ali Akbar; Ghaderi, Hossein; Fazaeli, Amir Abbas; Lotfi, Farhad; Salehi, Masoud; Mehrara, Mohsen

2015-01-01

Background: During recent decades, increase in both health care expenditures and improvement of the awareness as well as health expectations have created some problems with regard to finance healthcare expenditures so that the issue of health financing by households has been determined as a major challenge in health sector. According to the definition by the World Health Organization, catastrophic health expenditure is considered if financial contribution for health service is more than 40% of income remaining after subsistence needs have been met. Objectives: The purpose of our study was determination of Main factors on catastrophic health expenditures in Iranian households. Patients and Methods: In this study, using an econometrics Bayesian logit model, determinants of the appearance of catastrophic health expenditure based on household budget data collected in 2010 were evaluated. Results: Among Iranian households, the following groups were more likely to encounter with unsustainable health expenditures: rural households, households with the numbers of the elderly more than 65 years, illiterate householders, unemployed householders, households with some unemployed persons, households in upper rank and households with larger equivalent household size were higher than the average of community could significantly predict catastrophic health expenditures. Conclusions: About 2.1% of households were faced with catastrophic health expenditures in 2010. Thus, the implemented policies could not make considerable and significant change in improving justice in financing in health systems. PMID:25946936

Main determinants of catastrophic health expenditures: a Bayesian logit approach on Iranian household survey data (2010).

PubMed

Fazaeli, Ali Akbar; Ghaderi, Hossein; Abbas Fazaeli, Amir; Lotfi, Farhad; Salehi, Masoud; Mehrara, Mohsen

2015-01-26

During recent decades, increase in both health care expenditures and improvement of the awareness as well as health expectations have created some problems with regard to finance healthcare expenditures so that the issue of health financing by households has been determined as a major challenge in health sector. According to the definition by the World Health Organization, catastrophic health expenditure is considered if financial contribution for health service is more than 40% of income remaining after subsistence needs have been met. The purpose of our study was determination of Main factors on catastrophic health expenditures in Iranian households. In this study, using an econometrics Bayesian logit model, determinants of the appearance of catastrophic health expenditure based on household budget data collected in 2010 were evaluated. Among Iranian households, the following groups were more likely to encounter with unsustainable health expenditures: rural households, households with the numbers of the elderly more than 65 years, illiterate householders, unemployed householders, households with some unemployed persons, households in upper rank and households with larger equivalent household size were higher than the average of community could significantly predict catastrophic health expenditures. About 2.1% of households were faced with catastrophic health expenditures in 2010. Thus, the implemented policies could not make considerable and significant change in improving justice in financing in health systems.

Bioaccumulation of Zn and Ag Nanoparticles in the Earthworms (Eisenia fetida)

NASA Astrophysics Data System (ADS)

Ha, Lee Seung; Sung-Dae, Kim; Yi, Yang Song; Byeong-Gweon, Lee

2014-05-01

Many studies are carried out to evaluate environmental effects of engineered nanoparticles (ENPs). Most of the previous studies primarily focused on the effects of nanoparticles into the aquatic environment and human. Model studies predict that ENPs released into environment would transferred primarily to the soil of the terrestrial environment. Despite this prediction, biogeochemical behavior of ENPs in soil environment as well as bioavailability of ENPs to soil-dwelling organisms such as earthworm, springtail, isopod and nematodes are poorly understood. The main goal of this study was to compare the bioaccumulation factor (BAFs) and subcellular partitioning of nanoparticles in the soil-dwelling earthworm (Eisenia fetida) from ENP (ZnO and Ag nanoparticles) or ionic metal (Zn2+, Ag+) contaminated soil. And the sequential extraction was also used to determine the mobility of metals in soil which could be used as to predict bioavailability and compare that with bioaccumulation factor. The radiotracer method was employed to trace the transfer of ENPs and ionic metal among different environmental media and animals. Radiolabeled 65ZnO, 110mAgNPs coated with PVP or citrate were synthesized in the laboratory and their chemical and biological behavior was compared to ionic 65Zn and 110mAg. The BAFs of Zn and Ag in the earthworms were determined after animals exposed to the contaminated soils. After the 7 days of elimination phase, subcellular partitioning of metals were also obtained. BAF for ZnO(0.06) was 31 times lower than that for Zn ion (1.86), suggesting that ZnO was less bioavailable than its ionic form from contaminated soil. On the other hands, BAFs for AgNPs coated with PVP (0.12) or with citrate (0.11) were comparable to those for Ag ion (0.17), indicating that Ag from contaminated soil was bioavailable in a similar rate regardless of chemical forms. The subcellular partitioning results showed that bioaccumulated Zn from Zn ion and ZnO contaminated soil were present mainly in HSP (heat-sensitive protein) while cellullar Ag from Ag ion and AgNPs (Ag/PVP, Ag/citrate) treatments were found mostly in cellular debris. No statistical difference in partitioning of metals among different subcelluar pools was found between the metal forms. Zn from ZnO contaminated solis was found largely in carbonate fraction (41%), while Zn from Zn ion treatment was found in Fe-Mn Oxide (29%). Association of Zn to mobile fractions (ZnO; 65%, Zn ion; 35%) suggest that Zn from ZnO contaminated soil would be more bioavailable than that from Zn ion treatment. However, the BAFs for Zn in the animals did not follow this prediction. Majority of Ag from AgNPs or Ag ion contaminated soil was bound mainly to biologically inert fractions mainly in organic matter, surphide fractions, and residual fractions. Consistent with these findings, the BAFs of Ag in the worms exposed to Ag contaminated soils were generally lower than those for Zn treatments.

Predicting the Poaceae pollen season: six month-ahead forecasting and identification of relevant features

NASA Astrophysics Data System (ADS)

Navares, Ricardo; Aznarte, José Luis

2017-04-01

In this paper, we approach the problem of predicting the concentrations of Poaceae pollen which define the main pollination season in the city of Madrid. A classification-based approach, based on a computational intelligence model (random forests), is applied to forecast the dates in which risk concentration levels are to be observed. Unlike previous works, the proposal extends the range of forecasting horizons up to 6 months ahead. Furthermore, the proposed model allows to determine the most influential factors for each horizon, making no assumptions about the significance of the weather features. The performace of the proposed model proves it as a successful tool for allergy patients in preventing and minimizing the exposure to risky pollen concentrations and for researchers to gain a deeper insight on the factors driving the pollination season.

Scale relativity and quantization of planet obliquities.

NASA Astrophysics Data System (ADS)

Nottale, L.

1998-07-01

The author applies the theory of scale relativity to the equations of rotational motion of solid bodies. He predicts in the new framework that the obliquities and inclinations of planets and satellites in the solar system must be quantized. Namely, one expects their distribution to be no longer uniform between 0 and π, but instead to display well-defined peaks of probability density at angles θk = kπ/n. The author shows in the present paper that the observational data agree very well with the prediction for n = 7, including the retrograde bodies and those which are heeled over the ecliptic plane. In particular, the value 23°27' of the obliquity of the Earth, which partly determines its climate, is not a random one, but lies in one of the main probability peaks at θ = π/7.

Predicting the Poaceae pollen season: six month-ahead forecasting and identification of relevant features.

PubMed

Navares, Ricardo; Aznarte, José Luis

2017-04-01

In this paper, we approach the problem of predicting the concentrations of Poaceae pollen which define the main pollination season in the city of Madrid. A classification-based approach, based on a computational intelligence model (random forests), is applied to forecast the dates in which risk concentration levels are to be observed. Unlike previous works, the proposal extends the range of forecasting horizons up to 6 months ahead. Furthermore, the proposed model allows to determine the most influential factors for each horizon, making no assumptions about the significance of the weather features. The performace of the proposed model proves it as a successful tool for allergy patients in preventing and minimizing the exposure to risky pollen concentrations and for researchers to gain a deeper insight on the factors driving the pollination season.

Making Sense of Atmospheric Models and Fundamental Stellar Properties at the Bottom of the Main Sequence

NASA Astrophysics Data System (ADS)

Dieterich, Sergio; Henry, Todd; Jao, W.-C.; Washington, Robert; Silverstein, Michele; Winters, J.; RECONS

2018-01-01

We present a detailed comparison of atmospheric model predictions and photometric observations for late M and L dwarfs. We discuss which wavelength regions are best for determining the fundamental properties of these cool stellar and substellar atmospheres and use this analysis to refine the HR diagram for the hydrogen burning limit first presented in 2014. We also add several new objects to the HR diagram and find little qualitative difference in the HR diagram's overall morphology when compared to our 2014 results. The L2 dwarf 2MASS 0523-1403 remains the smallest hydrogen burning star for which we calculated a radius, thus likely indicating the end of the stellar main sequence. This work is supported by the NSF Astronomy and Astrophysics Postdoctoral Fellowship program through grant AST-1400680.

Main Trend Extraction Based on Irregular Sampling Estimation and Its Application in Storage Volume of Internet Data Center

PubMed Central

Dou, Chao

2016-01-01

The storage volume of internet data center is one of the classical time series. It is very valuable to predict the storage volume of a data center for the business value. However, the storage volume series from a data center is always “dirty,” which contains the noise, missing data, and outliers, so it is necessary to extract the main trend of storage volume series for the future prediction processing. In this paper, we propose an irregular sampling estimation method to extract the main trend of the time series, in which the Kalman filter is used to remove the “dirty” data; then the cubic spline interpolation and average method are used to reconstruct the main trend. The developed method is applied in the storage volume series of internet data center. The experiment results show that the developed method can estimate the main trend of storage volume series accurately and make great contribution to predict the future volume value. 
 PMID:28090205

Main Trend Extraction Based on Irregular Sampling Estimation and Its Application in Storage Volume of Internet Data Center.

PubMed

Miao, Beibei; Dou, Chao; Jin, Xuebo

2016-01-01

The storage volume of internet data center is one of the classical time series. It is very valuable to predict the storage volume of a data center for the business value. However, the storage volume series from a data center is always "dirty," which contains the noise, missing data, and outliers, so it is necessary to extract the main trend of storage volume series for the future prediction processing. In this paper, we propose an irregular sampling estimation method to extract the main trend of the time series, in which the Kalman filter is used to remove the "dirty" data; then the cubic spline interpolation and average method are used to reconstruct the main trend. The developed method is applied in the storage volume series of internet data center. The experiment results show that the developed method can estimate the main trend of storage volume series accurately and make great contribution to predict the future volume value. 
 .

Application of multispectral imaging to determine quality attributes and ripeness stage in strawberry fruit.

PubMed

Liu, Changhong; Liu, Wei; Lu, Xuzhong; Ma, Fei; Chen, Wei; Yang, Jianbo; Zheng, Lei

2014-01-01

Multispectral imaging with 19 wavelengths in the range of 405-970 nm has been evaluated for nondestructive determination of firmness, total soluble solids (TSS) content and ripeness stage in strawberry fruit. Several analysis approaches, including partial least squares (PLS), support vector machine (SVM) and back propagation neural network (BPNN), were applied to develop theoretical models for predicting the firmness and TSS of intact strawberry fruit. Compared with PLS and SVM, BPNN considerably improved the performance of multispectral imaging for predicting firmness and total soluble solids content with the correlation coefficient (r) of 0.94 and 0.83, SEP of 0.375 and 0.573, and bias of 0.035 and 0.056, respectively. Subsequently, the ability of multispectral imaging technology to classify fruit based on ripeness stage was tested using SVM and principal component analysis-back propagation neural network (PCA-BPNN) models. The higher classification accuracy of 100% was achieved using SVM model. Moreover, the results of all these models demonstrated that the VIS parts of the spectra were the main contributor to the determination of firmness, TSS content estimation and classification of ripeness stage in strawberry fruit. These results suggest that multispectral imaging, together with suitable analysis model, is a promising technology for rapid estimation of quality attributes and classification of ripeness stage in strawberry fruit.

Testing Pneumonia Vaccines in the Elderly: Determining a Case Definition for Pneumococcal Pneumonia in the Absence of a Gold Standard.

PubMed

Jokinen, Jukka; Snellman, Marja; Palmu, Arto A; Saukkoriipi, Annika; Verlant, Vincent; Pascal, Thierry; Devaster, Jeanne-Marie; Hausdorff, William P; Kilpi, Terhi M

2018-06-01

Clinical assessments of vaccines to prevent pneumococcal community-acquired pneumonia (CAP) require sensitive and specific case definitions, but there is no gold standard diagnostic test. To develop a new case definition suitable for vaccine efficacy studies, we applied latent class analysis (LCA) to the results from 7 diagnostic tests for pneumococcal etiology on clinical specimens from 323 elderly persons with radiologically confirmed pneumonia enrolled in the Finnish Community-Acquired Pneumonia Epidemiology study during 2005-2007. Compared with the conventional use of LCA, which is mainly to determine sensitivities and specificities of different tests, we instead used LCA as an appropriate instrument to predict the probability of pneumococcal etiology for each CAP case based on individual test profiles, and we used the predictions to minimize the sample size that would be needed for a vaccine efficacy trial. When compared with the conventional laboratory criteria of encapsulated pneumococci in culture, in blood culture or high-quality sputum culture, or urine antigen positivity, our optimized case definition for pneumococcal CAP resulted in a trial sample size that was almost 20,000 subjects smaller. We believe that the novel application of LCA detailed here to determine a case definition for pneumococcal CAP could also be similarly applied to other diseases without a gold standard.

Advantages and disadvantages of technologies for HER2 testing in breast cancer specimens.

PubMed

Furrer, Daniela; Sanschagrin, François; Jacob, Simon; Diorio, Caroline

2015-11-01

Human epidermal growth factor receptor 2 (HER2) plays a central role as a prognostic and predictive marker in breast cancer specimens. Reliable HER2 evaluation is central to determine the eligibility of patients with breast cancer to targeted anti-HER2 therapies such as trastuzumab and lapatinib. Presently, several methods exist for the determination of HER2 status at different levels (protein, RNA, and DNA level). In this review, we discuss the main advantages and disadvantages of the techniques developed so far for the evaluation of HER2 status in breast cancer specimens. Each technique has its own advantages and disadvantages. It is therefore not surprising that no consensus has been reached so far on which technique is the best for the determination of HER2 status. Currently, emphasis must be put on standardization of procedures, internal and external quality control assessment, and competency evaluation of already existing methods to ensure accurate, reliable, and clinically meaningful test results. Development of new robust and accurate diagnostic assays should also be encouraged. In addition, large clinical trials are warranted to identify the technique that most reliably predicts a positive response to anti-HER2 drugs. Copyright© by the American Society for Clinical Pathology.

Quantifying predictability in a model with statistical features of the atmosphere

PubMed Central

Kleeman, Richard; Majda, Andrew J.; Timofeyev, Ilya

2002-01-01

The Galerkin truncated inviscid Burgers equation has recently been shown by the authors to be a simple model with many degrees of freedom, with many statistical properties similar to those occurring in dynamical systems relevant to the atmosphere. These properties include long time-correlated, large-scale modes of low frequency variability and short time-correlated “weather modes” at smaller scales. The correlation scaling in the model extends over several decades and may be explained by a simple theory. Here a thorough analysis of the nature of predictability in the idealized system is developed by using a theoretical framework developed by R.K. This analysis is based on a relative entropy functional that has been shown elsewhere by one of the authors to measure the utility of statistical predictions precisely. The analysis is facilitated by the fact that most relevant probability distributions are approximately Gaussian if the initial conditions are assumed to be so. Rather surprisingly this holds for both the equilibrium (climatological) and nonequilibrium (prediction) distributions. We find that in most cases the absolute difference in the first moments of these two distributions (the “signal” component) is the main determinant of predictive utility variations. Contrary to conventional belief in the ensemble prediction area, the dispersion of prediction ensembles is generally of secondary importance in accounting for variations in utility associated with different initial conditions. This conclusion has potentially important implications for practical weather prediction, where traditionally most attention has focused on dispersion and its variability. PMID:12429863

A model to forecast short-term snowmelt runoff using synoptic observations of streamflow, temperature, and precipitation

USGS Publications Warehouse

Tangborn, Wendell V.

1980-01-01

Snowmelt runoff is forecast with a statistical model that utilizes daily values of stream discharge, gaged precipitation, and maximum and minimum observations of air temperature. Synoptic observations of these variables are made at existing low- and medium-altitude weather stations, thus eliminating the difficulties and expense of new, high-altitude installations. Four model development steps are used to demonstrate the influence on prediction accuracy of basin storage, a preforecast test season, air temperature (to estimate ablation), and a prediction based on storage. Daily ablation is determined by a technique that employs both mean temperature and a radiative index. Radiation (both long- and short-wave components) is approximated by using the range in daily temperature, which is shown to be closely related to mean cloud cover. A technique based on the relationship between prediction error and prediction season weather utilizes short-term forecasts of precipitation and temperature to improve the final prediction. Verification of the model is accomplished by a split sampling technique for the 1960–1977 period. Short- term (5–15 days) predictions of runoff throughout the main snowmelt season are demonstrated for mountain drainages in western Washington, south-central Arizona, western Montana, and central California. The coefficient of prediction (Cp) based on actual, short-term predictions for 18 years is for Thunder Creek (Washington), 0.69; for South Fork Flathead River (Montana), 0.45; for the Black River (Arizona), 0.80; and for the Kings River (California), 0.80.

Biological and functional relevance of CASP predictions.

PubMed

Liu, Tianyun; Ish-Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D; Altman, Russ B

2018-03-01

Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo-sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo-sites), and Ten sites containing important motifs, loops, or key residues with important disease-associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best-ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand-binding sites, most prediction methods have higher performance on apo-sites than holo-sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein-protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein-protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. © 2017 The Authors Proteins: Structure, Function and Bioinformatics Published by Wiley Periodicals, Inc.

Uncertainties in s -process nucleosynthesis in low mass stars determined from Monte Carlo variations

NASA Astrophysics Data System (ADS)

Cescutti, G.; Hirschi, R.; Nishimura, N.; den Hartogh, J. W.; Rauscher, T.; Murphy, A. St J.; Cristallo, S.

2018-05-01

The main s-process taking place in low mass stars produces about half of the elements heavier than iron. It is therefore very important to determine the importance and impact of nuclear physics uncertainties on this process. We have performed extensive nuclear reaction network calculations using individual and temperature-dependent uncertainties for reactions involving elements heavier than iron, within a Monte Carlo framework. Using this technique, we determined the uncertainty in the main s-process abundance predictions due to nuclear uncertainties link to weak interactions and neutron captures on elements heavier than iron. We also identified the key nuclear reactions dominating these uncertainties. We found that β-decay rate uncertainties affect only a few nuclides near s-process branchings, whereas most of the uncertainty in the final abundances is caused by uncertainties in neutron capture rates, either directly producing or destroying the nuclide of interest. Combined total nuclear uncertainties due to reactions on heavy elements are in general small (less than 50%). Three key reactions, nevertheless, stand out because they significantly affect the uncertainties of a large number of nuclides. These are 56Fe(n,γ), 64Ni(n,γ), and 138Ba(n,γ). We discuss the prospect of reducing uncertainties in the key reactions identified in this study with future experiments.

Kinetics of thermal decomposition of some biomasses in an inert environment. An investigation of the effect of lead loaded by biosorption.

PubMed

Martín-Lara, María Ángeles; Iáñez-Rodríguez, Irene; Blázquez, Gabriel; Quesada, Lucía; Pérez, Antonio; Calero, Mónica

2017-12-01

The thermal behavior of some types of raw and lead-polluted biomasses typical in south Spain was studied by non-isothermal thermogravimetry. Experiments were carried out in nitrogen atmosphere at three heating rates (5, 10 and 20°C/min). The results of thermogravimetric tests carried out proved that the presence of lead did not change the main degradation pathways of selected biomass (almond shell (AS) and olive pomace (OP)). However, from a point of view of mass loss, lead-polluted samples showed higher decomposition temperatures and decomposition at higher rate. The determination of activation energies was performed by isoconversional methods of Flynn-Wall-Ozawa (FWO), Kissinger-Akahira-Sunose (KAS) and Friedman (FR). In general, lead-polluted samples showed lower activation energies than raw ones. Then, Coast-Redfern method was applied to determine kinetic function. The kinetic function that seems to determine the mechanism of thermal degradation of main components of all samples was nth order reaction. Finally, a model based on three parallel reactions (for three pseudocomponents) that fit to nth order reactions was evaluated. This model was appropriate to predict the pyrolysis behavior of the raw and lead-polluted samples in all pyrolysis conditions studied. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of the first georeferenced map of Rhipicephalus (Boophilus) spp. in Mexico from 1970 to date and prediction of its spatial distribution.

PubMed

Alcala-Canto, Yazmin; Figueroa-Castillo, Juan Antonio; Ibarra-Velarde, Froylán; Vera-Montenegro, Yolanda; Cervantes-Valencia, María Eugenia; Salem, Abdelfattah Z M; Cuéllar-Ordaz, Jorge Alfredo

2018-05-07

The tick genus Ripicephalus (Boophilus), particularly R. microplus, is one of the most important ectoparasites that affects livestock health and considered an epidemiological risk because it causes significant economic losses due, mainly, to restrictions in the export of infested animals to several countries. Its spatial distribution has been tied to environmental factors, mainly warm temperatures and high relative humidity. In this work, we integrated a dataset consisting of 5843 records of Rhipicephalus spp., in Mexico covering close to 50 years to know which environmental variables mostly influence this ticks' distribution. Occurrences were georeferenced using the software DIVA-GIS and the potential current distribution was modelled using the maximum entropy method (Maxent). The algorithm generated a map of high predictive capability (Area under the curve = 0.942), providing the various contribution and permutation importance of the tested variables. Precipitation seasonality, particularly in March, and isothermality were found to be the most significant climate variables in determining the probability of spatial distribution of Rhipicephalus spp. in Mexico (15.7%, 36.0% and 11.1%, respectively). Our findings demonstrate that Rhipicephalus has colonized Mexico widely, including areas characterized by different types of climate. We conclude that the Maxent distribution model using Rhipicephalus records and a set of environmental variables can predict the extent of the tick range in this country, information that should support the development of integrated control strategies.

Investigation of Characteristics and Predictive Factors Affecting Mortality from Aluminum Phosphide Poisoning, Iran.

PubMed

Navabi, Seyed Mohammad Navabi; Navabi, Seyed Jafar; Aghaei, Abbas; Shaahmadi, Zahra; Heydari, Ruhollah

2018-05-27

Aluminum phosphide (ALP) or rice tablet is one of the most effective rodenticides used for the protection of grain storages from animals and rodents. ALP poisoning annually leads to mortality in human beings. The aim of this study was to evaluate the characteristics and predictive factors affecting mortality from ALP poisoning. This study evaluated patients with ALP poisoning referred to Imam Khomeini hospital in Kermanshah from 2014 to 2015. There are several data gathered from patient such as age, sex, number of consumed tablets, the number of attempts to commit suicide, elapsed time from consuming till treatment, blood pressure, PH, HCO3 and PCO2. Survivors (recovery) and non-survivors (death) from ALP poisoning are also evaluated in this study. Univariate logistic regression and multivariate analysis have been applied for data analysis. In this study, 48 patients were male and 29 patients were female, respectively (total 77 patient). The average age of survivors and non-survivors were 28.69 and 31.34 years, respectively. All cases (100%) of ALP poisoning were tried to commit suicide. The results showed that the main predictive variables of mortality from ALP poisoning were blood pressure, PH and elapsed time from consuming till treatment. The prognosis of death for patients with ALP poisoning can be determined by awareness of some of the main characteristics or factors such as blood pressure, PH and elapsed time from consuming till treatment. This can give a possibility for healthcare groups to consider more measures in patients with ALP poisoning.

Dynamic modeling of temperature change in outdoor operated tubular photobioreactors.

PubMed

Androga, Dominic Deo; Uyar, Basar; Koku, Harun; Eroglu, Inci

2017-07-01

In this study, a one-dimensional transient model was developed to analyze the temperature variation of tubular photobioreactors operated outdoors and the validity of the model was tested by comparing the predictions of the model with the experimental data. The model included the effects of convection and radiative heat exchange on the reactor temperature throughout the day. The temperatures in the reactors increased with increasing solar radiation and air temperatures, and the predicted reactor temperatures corresponded well to the measured experimental values. The heat transferred to the reactor was mainly through radiation: the radiative heat absorbed by the reactor medium, ground radiation, air radiation, and solar (direct and diffuse) radiation, while heat loss was mainly through the heat transfer to the cooling water and forced convection. The amount of heat transferred by reflected radiation and metabolic activities of the bacteria and pump work was negligible. Counter-current cooling was more effective in controlling reactor temperature than co-current cooling. The model developed identifies major heat transfer mechanisms in outdoor operated tubular photobioreactors, and accurately predicts temperature changes in these systems. This is useful in determining cooling duty under transient conditions and scaling up photobioreactors. The photobioreactor design and the thermal modeling were carried out and experimental results obtained for the case study of photofermentative hydrogen production by Rhodobacter capsulatus, but the approach is applicable to photobiological systems that are to be operated under outdoor conditions with significant cooling demands.

A composite measure to explore visual disability in primary progressive multiple sclerosis.

PubMed

Poretto, Valentina; Petracca, Maria; Saiote, Catarina; Mormina, Enricomaria; Howard, Jonathan; Miller, Aaron; Lublin, Fred D; Inglese, Matilde

2017-01-01

Optical coherence tomography (OCT) and magnetic resonance imaging (MRI) can provide complementary information on visual system damage in multiple sclerosis (MS). The objective of this paper is to determine whether a composite OCT/MRI score, reflecting cumulative damage along the entire visual pathway, can predict visual deficits in primary progressive multiple sclerosis (PPMS). Twenty-five PPMS patients and 20 age-matched controls underwent neuro-ophthalmologic evaluation, spectral-domain OCT, and 3T brain MRI. Differences between groups were assessed by univariate general linear model and principal component analysis (PCA) grouped instrumental variables into main components. Linear regression analysis was used to assess the relationship between low-contrast visual acuity (LCVA), OCT/MRI-derived metrics and PCA-derived composite scores. PCA identified four main components explaining 80.69% of data variance. Considering each variable independently, LCVA 1.25% was significantly predicted by ganglion cell-inner plexiform layer (GCIPL) thickness, thalamic volume and optic radiation (OR) lesion volume (adjusted R 2 0.328, p  = 0.00004; adjusted R 2 0.187, p  = 0.002 and adjusted R 2 0.180, p  = 0.002). The PCA composite score of global visual pathway damage independently predicted both LCVA 1.25% (adjusted R 2 value 0.361, p  = 0.00001) and LCVA 2.50% (adjusted R 2 value 0.323, p  = 0.00003). A multiparametric score represents a more comprehensive and effective tool to explain visual disability than a single instrumental metric in PPMS.

Mathematical modeling and experimental validation of the spatial distribution of boron in the root of Arabidopsis thaliana identify high boron accumulation in the tip and predict a distinct root tip uptake function.

PubMed

Shimotohno, Akie; Sotta, Naoyuki; Sato, Takafumi; De Ruvo, Micol; Marée, Athanasius F M; Grieneisen, Verônica A; Fujiwara, Toru

2015-04-01

Boron, an essential micronutrient, is transported in roots of Arabidopsis thaliana mainly by two different types of transporters, BORs and NIPs (nodulin26-like intrinsic proteins). Both are plasma membrane localized, but have distinct transport properties and patterns of cell type-specific accumulation with different polar localizations, which are likely to affect boron distribution. Here, we used mathematical modeling and an experimental determination to address boron distributions in the root. A computational model of the root is created at the cellular level, describing the boron transporters as observed experimentally. Boron is allowed to diffuse into roots, in cells and cell walls, and to be transported over plasma membranes, reflecting the properties of the different transporters. The model predicts that a region around the quiescent center has a higher concentration of soluble boron than other portions. To evaluate this prediction experimentally, we determined the boron distribution in roots using laser ablation-inductivity coupled plasma-mass spectrometry. The analysis indicated that the boron concentration is highest near the tip and is lower in the more proximal region of the meristem zone, similar to the pattern of soluble boron distribution predicted by the model. Our model also predicts that upward boron flux does not continuously increase from the root tip toward the mature region, indicating that boron taken up in the root tip is not efficiently transported to shoots. This suggests that root tip-absorbed boron is probably used for local root growth, and that instead it is the more mature root regions which have a greater role in transporting boron toward the shoots. © The Author 2015. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.

Mathematical Modeling and Experimental Validation of the Spatial Distribution of Boron in the Root of Arabidopsis thaliana Identify High Boron Accumulation in the Tip and Predict a Distinct Root Tip Uptake Function

PubMed Central

Shimotohno, Akie; Sotta, Naoyuki; Sato, Takafumi; De Ruvo, Micol; Marée, Athanasius F.M.; Grieneisen, Verônica A.; Fujiwara, Toru

2015-01-01

Boron, an essential micronutrient, is transported in roots of Arabidopsis thaliana mainly by two different types of transporters, BORs and NIPs (nodulin26-like intrinsic proteins). Both are plasma membrane localized, but have distinct transport properties and patterns of cell type-specific accumulation with different polar localizations, which are likely to affect boron distribution. Here, we used mathematical modeling and an experimental determination to address boron distributions in the root. A computational model of the root is created at the cellular level, describing the boron transporters as observed experimentally. Boron is allowed to diffuse into roots, in cells and cell walls, and to be transported over plasma membranes, reflecting the properties of the different transporters. The model predicts that a region around the quiescent center has a higher concentration of soluble boron than other portions. To evaluate this prediction experimentally, we determined the boron distribution in roots using laser ablation-inductivity coupled plasma-mass spectrometry. The analysis indicated that the boron concentration is highest near the tip and is lower in the more proximal region of the meristem zone, similar to the pattern of soluble boron distribution predicted by the model. Our model also predicts that upward boron flux does not continuously increase from the root tip toward the mature region, indicating that boron taken up in the root tip is not efficiently transported to shoots. This suggests that root tip-absorbed boron is probably used for local root growth, and that instead it is the more mature root regions which have a greater role in transporting boron toward the shoots. PMID:25670713

Fast detection and visualization of minced lamb meat adulteration using NIR hyperspectral imaging and multivariate image analysis.

PubMed

Kamruzzaman, Mohammed; Sun, Da-Wen; ElMasry, Gamal; Allen, Paul

2013-01-15

Many studies have been carried out in developing non-destructive technologies for predicting meat adulteration, but there is still no endeavor for non-destructive detection and quantification of adulteration in minced lamb meat. The main goal of this study was to develop and optimize a rapid analytical technique based on near-infrared (NIR) hyperspectral imaging to detect the level of adulteration in minced lamb. Initial investigation was carried out using principal component analysis (PCA) to identify the most potential adulterate in minced lamb. Minced lamb meat samples were then adulterated with minced pork in the range 2-40% (w/w) at approximately 2% increments. Spectral data were used to develop a partial least squares regression (PLSR) model to predict the level of adulteration in minced lamb. Good prediction model was obtained using the whole spectral range (910-1700 nm) with a coefficient of determination (R(2)(cv)) of 0.99 and root-mean-square errors estimated by cross validation (RMSECV) of 1.37%. Four important wavelengths (940, 1067, 1144 and 1217 nm) were selected using weighted regression coefficients (Bw) and a multiple linear regression (MLR) model was then established using these important wavelengths to predict adulteration. The MLR model resulted in a coefficient of determination (R(2)(cv)) of 0.98 and RMSECV of 1.45%. The developed MLR model was then applied to each pixel in the image to obtain prediction maps to visualize the distribution of adulteration of the tested samples. The results demonstrated that the laborious and time-consuming tradition analytical techniques could be replaced by spectral data in order to provide rapid, low cost and non-destructive testing technique for adulterate detection in minced lamb meat. Copyright © 2012 Elsevier B.V. All rights reserved.

ACUTE PANCREATITIS GRAVITY PREDICTIVE FACTORS: WHICH AND WHEN TO USE THEM?

PubMed Central

FERREIRA, Alexandre de Figueiredo; BARTELEGA, Janaina Alves; URBANO, Hugo Corrêa de Andrade; de SOUZA, Iure Kalinine Ferraz

2015-01-01

Introduction: Acute pancreatitis has as its main causes lithiasic biliary disease and alcohol abuse. Most of the time, the disease shows a self-limiting course, with a rapid recovery, only with supportive treatment. However, in a significant percentage of cases, it runs with important local and systemic complications associated with high mortality rates. Aim: To present the current state of the use of these prognostic factors (predictive scores) of gravity, as the time of application, complexity and specificity. Method: A non-systematic literature review through 28 papers, with emphasis on 13 articles published in indexed journals between 2008 and 2013 using Lilacs, Medline, Pubmed. Results: Several clinical, laboratory analysis, molecular and image variables can predict the development of severe acute pancreatitis. Some of them by themselves can be determinant to the progression of the disease to a more severe form, such as obesity, hematocrit, age and smoking. Hematocrit with a value lower than 44% and serum urea lower than 20 mg/dl, both at admission, appear as risk factors for pancreatic necrosis. But the PCR differentiates mild cases of serious ones in the first 24 h. Multifactorial scores measured on admission and during the first 48 h of hospitalization have been used in intensive care units, being the most ones used: Ranson, Apache II, Glasgow, Iget and Saps II. Conclusion: Acute pancreatitis is a disease in which several prognostic factors are employed being useful in predicting mortality and on the development of the severe form. It is suggested that the association of a multifactorial score, especially the Saps II associated with Iget, may increase the prognosis accuracy. However, the professional's preferences, the experience on the service as well as the available tools, are factors that have determined the choice of the most suitable predictive score. PMID:26537149

Fractal Theory for Permeability Prediction, Venezuelan and USA Wells

NASA Astrophysics Data System (ADS)

Aldana, Milagrosa; Altamiranda, Dignorah; Cabrera, Ana

2014-05-01

Inferring petrophysical parameters such as permeability, porosity, water saturation, capillary pressure, etc, from the analysis of well logs or other available core data has always been of critical importance in the oil industry. Permeability in particular, which is considered to be a complex parameter, has been inferred using both empirical and theoretical techniques. The main goal of this work is to predict permeability values on different wells using Fractal Theory, based on a method proposed by Pape et al. (1999). This approach uses the relationship between permeability and the geometric form of the pore space of the rock. This method is based on the modified equation of Kozeny-Carman and a fractal pattern, which allows determining permeability as a function of the cementation exponent, porosity and the fractal dimension. Data from wells located in Venezuela and the United States of America are analyzed. Employing data of porosity and permeability obtained from core samples, and applying the Fractal Theory method, we calculated the prediction equations for each well. At the beginning, this was achieved by training with 50% of the data available for each well. Afterwards, these equations were tested inferring over 100% of the data to analyze possible trends in their distribution. This procedure gave excellent results in all the wells in spite of their geographic distance, generating permeability models with the potential to accurately predict permeability logs in the remaining parts of the well for which there are no core samples, using even porority logs. Additionally, empirical models were used to determine permeability and the results were compared with those obtained by applying the fractal method. The results indicated that, although there are empirical equations that give a proper adjustment, the prediction results obtained using fractal theory give a better fit to the core reference data.

Biochemical verification of the self-reported smoking status of screened male smokers of the Dutch-Belgian randomized controlled lung cancer screening trial.

PubMed

van der Aalst, Carlijn M; de Koning, Harry J

2016-04-01

Smoking is the main cause of lung cancer, so data linked to smoking behaviour are important in lung cancer screening trials. However, self-reporting data concerning smoking behaviour are mainly used. The aim of this study was to biochemically determine the validity and reliability of self-reported smoking status among smokers at high risk for developing lung cancer participating in the Dutch-Belgian lung cancer screening (NELSON) trial. For this sub study, a random sample of 475 men was selected who were scheduled for the fourth screening round in the NELSON trial. They were asked to complete a short questionnaire to verify the smoking behaviour for the previous seven days and a blood sample was collected to measure the cotinine level. The validity (sensitivity (Se), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV)) and reliability (Kappa) of the self-reported smoking status compared to the cotinine level (as golden standard) were determined. Both a completed questionnaire as well as a cotinine level were available for 199 (41.9%) participants. Based on these data, Se and Sp were respectively 98% (95%-Confidence Interval (CI): 91-99) and 98% (95%-CI: 93-100). PPV and NPV were 98% and 96% and Kappa was 0.96. In conclusion, the validity of the self-reported smoking status turned out to be reliable amongst men at high risk for developing lung cancer who participate in the NELSON lung cancer screening trial. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Optimization of parameters affecting signal intensity in an LTQ-orbitrap in negative ion mode: A design of experiments approach.

PubMed

Lemonakis, Nikolaos; Skaltsounis, Alexios-Leandros; Tsarbopoulos, Anthony; Gikas, Evagelos

2016-01-15

A multistage optimization of all the parameters affecting detection/response in an LTQ-orbitrap analyzer was performed, using a design of experiments methodology. The signal intensity, a critical issue for mass analysis, was investigated and the optimization process was completed in three successive steps, taking into account the three main regions of an orbitrap, the ion generation, the ion transmission and the ion detection regions. Oleuropein and hydroxytyrosol were selected as the model compounds. Overall, applying this methodology the sensitivity was increased more than 24%, the resolution more than 6.5%, whereas the elapsed scan time was reduced nearly to its half. A high-resolution LTQ Orbitrap Discovery mass spectrometer was used for the determination of the analytes of interest. Thus, oleuropein and hydroxytyrosol were infused via the instruments syringe pump and they were analyzed employing electrospray ionization (ESI) in the negative high-resolution full-scan ion mode. The parameters of the three main regions of the LTQ-orbitrap were independently optimized in terms of maximum sensitivity. In this context, factorial design, response surface model and Plackett-Burman experiments were performed and analysis of variance was carried out to evaluate the validity of the statistical model and to determine the most significant parameters for signal intensity. The optimum MS conditions for each analyte were summarized and the method optimum condition was achieved by maximizing the desirability function. Our observation showed good agreement between the predicted optimum response and the responses collected at the predicted optimum conditions. Copyright © 2015 Elsevier B.V. All rights reserved.

Drought Tolerance in Pinus halepensis Seed Sources As Identified by Distinctive Physiological and Molecular Markers

PubMed Central

Taïbi, Khaled; del Campo, Antonio D.; Vilagrosa, Alberto; Bellés, José M.; López-Gresa, María Pilar; Pla, Davinia; Calvete, Juan J.; López-Nicolás, José M.; Mulet, José M.

2017-01-01

Drought is one of the main constraints determining forest species growth, survival and productivity, and therefore one of the main limitations for reforestation or afforestation. The aim of this study is to characterize the drought response at the physiological and molecular level of different Pinus halepensis (common name Aleppo pine) seed sources, previously characterized in field trials as drought-sensitive or drought-tolerant. This approach aims to identify different traits capable of predicting the ability of formerly uncharacterized seedlings to cope with drought stress. Gas-exchange, water potential, photosynthetic pigments, soluble sugars, free amino acids, glutathione and proteomic analyses were carried out on control and drought-stressed seedlings in greenhouse conditions. Gas-exchange determinations were also assessed in field-planted seedlings in order to validate the greenhouse experimental conditions. Drought-tolerant seed sources presented higher values of photosynthetic rates, water use efficiency, photosynthetic pigments and soluble carbohydrates concentrations. We observed the same pattern of variation of photosynthesis rate and maximal efficiency of PSII in field. Interestingly drought-tolerant seed sources exhibited increased levels of glutathione, methionine and cysteine. The proteomic profile of drought tolerant seedlings identified two heat shock proteins and an enzyme related to methionine biosynthesis that were not present in drought sensitive seedlings, pointing to the synthesis of sulfur amino acids as a limiting factor for drought tolerance in Pinus halepensis. Our results established physiological and molecular traits useful as distinctive markers to predict drought tolerance in Pinus halepensis provenances that could be reliably used in reforestation programs in drought prone areas. PMID:28791030

Drought Tolerance in Pinus halepensis Seed Sources As Identified by Distinctive Physiological and Molecular Markers.

PubMed

Taïbi, Khaled; Del Campo, Antonio D; Vilagrosa, Alberto; Bellés, José M; López-Gresa, María Pilar; Pla, Davinia; Calvete, Juan J; López-Nicolás, José M; Mulet, José M

2017-01-01

Drought is one of the main constraints determining forest species growth, survival and productivity, and therefore one of the main limitations for reforestation or afforestation. The aim of this study is to characterize the drought response at the physiological and molecular level of different Pinus halepensis (common name Aleppo pine) seed sources, previously characterized in field trials as drought-sensitive or drought-tolerant. This approach aims to identify different traits capable of predicting the ability of formerly uncharacterized seedlings to cope with drought stress. Gas-exchange, water potential, photosynthetic pigments, soluble sugars, free amino acids, glutathione and proteomic analyses were carried out on control and drought-stressed seedlings in greenhouse conditions. Gas-exchange determinations were also assessed in field-planted seedlings in order to validate the greenhouse experimental conditions. Drought-tolerant seed sources presented higher values of photosynthetic rates, water use efficiency, photosynthetic pigments and soluble carbohydrates concentrations. We observed the same pattern of variation of photosynthesis rate and maximal efficiency of PSII in field. Interestingly drought-tolerant seed sources exhibited increased levels of glutathione, methionine and cysteine. The proteomic profile of drought tolerant seedlings identified two heat shock proteins and an enzyme related to methionine biosynthesis that were not present in drought sensitive seedlings, pointing to the synthesis of sulfur amino acids as a limiting factor for drought tolerance in Pinus halepensis . Our results established physiological and molecular traits useful as distinctive markers to predict drought tolerance in Pinus halepensis provenances that could be reliably used in reforestation programs in drought prone areas.

The energy and protein value of wheat, maize and blend DDGS for cattle and evaluation of prediction methods.

PubMed

De Boever, J L; Blok, M C; Millet, S; Vanacker, J; De Campeneere, S

2014-11-01

The chemical composition inclusive amino acids (AAs) and the energy and protein value of three wheat, three maize and seven blend (mainly wheat) dried distillers grains and solubles (DDGS) were determined. The net energy for lactation (NEL) was derived from digestion coefficients obtained with sheep. The digestible protein in the intestines (DVE) and the degraded protein balance (OEB) were determined by nylon bag incubations in the rumen and the intestines of cannulated cows. Additional chemical parameters like acid-detergent insoluble CP (ADICP), protein solubility in water, in borate-phosphate buffer and in pepsin-HCl, in vitro digestibility (cellulase, protease, rumen fluid) and colour scores (L*, a*, b*) were evaluated as potential predictors of the energy and protein value. Compared to wheat DDGS (WDDGS), maize DDGS (MDDGS) had a higher NEL-value (8.49 v. 7.38 MJ/kg DM), a higher DVE-content (216 v. 198 g/kg DM) and a lower OEB-value (14 v. 66 g/kg DM). The higher energy value of MDDGS was mainly due to the higher crude fat (CFA) content (145 v. 76 g/kg DM) and also to better digestible cell-walls, whereas the higher protein value was mainly due to the higher percentage of rumen bypass protein (RBP: 69.8 v. 55.6%). The NEL-value of blend DDGS (BDDGS) was in between that of the pure DDGS-types, whereas its DVE-value was similar to MDDGS. Although lower in CP and total AAs, MDDGS provided a similar amount of essential AAs as the other DDGS-types. Lysine content was most reduced in the production of WDDGS and cysteine in MDDGS. Fat content explained 68.6% of the variation in NEL, with hemicellulose and crude ash as extra explaining variables. The best predictor for RBP as well as for OEB was the protein solubility in pepsin-HCl (R 2=77.3% and 83.5%). Intestinal digestibility of RBP could best be predicted by ADF (R 3=73.6%) and the combination of CFA and NDF could explain 60.2% of the variation in the content of absorbable microbial protein. The availability of AAs could accurately be predicted from the rumen bypass and intestinal digestibility of CP.

On the comparison of stochastic model predictive control strategies applied to a hydrogen-based microgrid

NASA Astrophysics Data System (ADS)

Velarde, P.; Valverde, L.; Maestre, J. M.; Ocampo-Martinez, C.; Bordons, C.

2017-03-01

In this paper, a performance comparison among three well-known stochastic model predictive control approaches, namely, multi-scenario, tree-based, and chance-constrained model predictive control is presented. To this end, three predictive controllers have been designed and implemented in a real renewable-hydrogen-based microgrid. The experimental set-up includes a PEM electrolyzer, lead-acid batteries, and a PEM fuel cell as main equipment. The real experimental results show significant differences from the plant components, mainly in terms of use of energy, for each implemented technique. Effectiveness, performance, advantages, and disadvantages of these techniques are extensively discussed and analyzed to give some valid criteria when selecting an appropriate stochastic predictive controller.

Development of a CSP plant energy yield calculation tool applying predictive models to analyze plant performance sensitivities

NASA Astrophysics Data System (ADS)

Haack, Lukas; Peniche, Ricardo; Sommer, Lutz; Kather, Alfons

2017-06-01

At early project stages, the main CSP plant design parameters such as turbine capacity, solar field size, and thermal storage capacity are varied during the techno-economic optimization to determine most suitable plant configurations. In general, a typical meteorological year with at least hourly time resolution is used to analyze each plant configuration. Different software tools are available to simulate the annual energy yield. Software tools offering a thermodynamic modeling approach of the power block and the CSP thermal cycle, such as EBSILONProfessional®, allow a flexible definition of plant topologies. In EBSILON, the thermodynamic equilibrium for each time step is calculated iteratively (quasi steady state), which requires approximately 45 minutes to process one year with hourly time resolution. For better presentation of gradients, 10 min time resolution is recommended, which increases processing time by a factor of 5. Therefore, analyzing a large number of plant sensitivities, as required during the techno-economic optimization procedure, the detailed thermodynamic simulation approach becomes impracticable. Suntrace has developed an in-house CSP-Simulation tool (CSPsim), based on EBSILON and applying predictive models, to approximate the CSP plant performance for central receiver and parabolic trough technology. CSPsim significantly increases the speed of energy yield calculations by factor ≥ 35 and has automated the simulation run of all predefined design configurations in sequential order during the optimization procedure. To develop the predictive models, multiple linear regression techniques and Design of Experiment methods are applied. The annual energy yield and derived LCOE calculated by the predictive model deviates less than ±1.5 % from the thermodynamic simulation in EBSILON and effectively identifies the optimal range of main design parameters for further, more specific analysis.

High Velocity Jet Noise Source Location and Reduction. Task 6. Supplement. Computer Programs: Engineering Correlation (M*S) Jet Noise Prediction Method and Unified Aeroacoustic Prediction Model (M*G*B) for Nozzles of Arbitary Shape.

DTIC Science & Technology

1979-03-01

LSPFIT 112 4.3.5 SLICE 112 4.3.6 CRD 113 4.3.7 OUTPUT 113 4.3.8 SHOCK 115 4.3.9 ATMOS 115 4.3.10 PNLC 115 4.4 Program Usage and Logic 116 4.5 Description...number MAIN, SLICE, OUTPUT F Intermediate variable LSPFIT FAC Intermediate variable PNLC FC Center frequency SLICE FIRSTU Flight velocity Ua MAIN, SLICE...Index CRD J211 Index CRD K Index, also wave number MAIN, SLICE, PNLC KN Surrounding boundary index MAIN KNCAS Case counter MAIN KNK Surrounding

Prediction of bioavailability of selected bisphosphonates using in silico methods towards categorization into a biopharmaceutical classification system.

PubMed

Biernacka, Joanna; Betlejewska-Kielak, Katarzyna; Kłosińska-Szmurło, Ewa; Pluciński, Franciszek A; Mazurek, Aleksander P

2013-01-01

The physicochemical properties relevant to biological activity of selected bisphosphonates such as clodronate disodium salt, etidronate disodium salt, pamidronate disodium salt, alendronate sodium salt, ibandronate sodium salt, risedronate sodium salt and zoledronate disodium salt were determined using in silico methods. The main aim of our research was to investigate and propose molecular determinants thataffect bioavailability of above mentioned compounds. These determinants are: stabilization energy (deltaE), free energy of solvation (deltaG(solv)), electrostatic potential, dipole moment, as well as partition and distribution coefficients estimated by the log P and log D values. Presented values indicate that selected bisphosphonates a recharacterized by high solubility and low permeability. The calculated parameters describing both solubility and permeability through biological membranes seem to be a good bioavailability indicators of bisphosphonates examined and can be a useful tool to include into Biopharmaceutical Classification System (BCS) development.

Reference Frames in Earth Rotation Theories

NASA Astrophysics Data System (ADS)

Ferrándiz, José M.; Belda, Santiago; Heinkelmann, Robert; Getino, Juan; Schuh, Harald; Escapa, Alberto

2015-04-01

Nowadays the determination of the Earth Orientation Parameters (EOP) and the different Terrestrial Reference Frames (TRF) are not independent. The available theories of Earth rotation aims at providing the orientation of a certain reference system linked somehow to the Earth with respect to a given celestial system, considered as inertial. In the past years a considerable effort has been dedicated to the improvement of the TRF realizations, following the lines set up in the 1980's. However, the reference systems used in the derivation of the theories have been rather considered as something fully established, not deserving a special attention. In this contribution we review the definitions of the frames used in the main theoretical approaches, focusing on those used in the construction of IAU2000, and the extent to which their underlying hypotheses hold. The results are useful to determine the level of consistency of the predicted and determined EOP.

Modified empirical Solar Radiation Pressure model for IRNSS constellation

NASA Astrophysics Data System (ADS)

Rajaiah, K.; Manamohan, K.; Nirmala, S.; Ratnakara, S. C.

2017-11-01

Navigation with Indian Constellation (NAVIC) also known as Indian Regional Navigation Satellite System (IRNSS) is India's regional navigation system designed to provide position accuracy better than 20 m over India and the region extending to 1500 km around India. The reduced dynamic precise orbit estimation is utilized to determine the orbit broadcast parameters for IRNSS constellation. The estimation is mainly affected by the parameterization of dynamic models especially Solar Radiation Pressure (SRP) model which is a non-gravitational force depending on shape and attitude dynamics of the spacecraft. An empirical nine parameter solar radiation pressure model is developed for IRNSS constellation, using two-way range measurements from IRNSS C-band ranging system. The paper addresses the development of modified SRP empirical model for IRNSS (IRNSS SRP Empirical Model, ISEM). The performance of the ISEM was assessed based on overlap consistency, long term prediction, Satellite Laser Ranging (SLR) residuals and compared with ECOM9, ECOM5 and new-ECOM9 models developed by Center for Orbit Determination in Europe (CODE). For IRNSS Geostationary Earth Orbit (GEO) and Inclined Geosynchronous Orbit (IGSO) satellites, ISEM has shown promising results with overlap RMS error better than 5.3 m and 3.5 m respectively. Long term orbit prediction using numerical integration has improved with error better than 80%, 26% and 7.8% in comparison to ECOM9, ECOM5 and new-ECOM9 respectively. Further, SLR based orbit determination with ISEM shows 70%, 47% and 39% improvement over 10 days orbit prediction in comparison to ECOM9, ECOM5 and new-ECOM9 respectively and also highlights the importance of wide baseline tracking network.

Uncertainties in the production of p nuclides in thermonuclear supernovae determined by Monte Carlo variations

NASA Astrophysics Data System (ADS)

Nishimura, N.; Rauscher, T.; Hirschi, R.; Murphy, A. St J.; Cescutti, G.; Travaglio, C.

2018-03-01

Thermonuclear supernovae originating from the explosion of a white dwarf accreting mass from a companion star have been suggested as a site for the production of p nuclides. Such nuclei are produced during the explosion, in layers enriched with seed nuclei coming from prior strong s processing. These seeds are transformed into proton-richer isotopes mainly by photodisintegration reactions. Several thousand trajectories from a 2D explosion model were used in a Monte Carlo approach. Temperature-dependent uncertainties were assigned individually to thousands of rates varied simultaneously in post-processing in an extended nuclear reaction network. The uncertainties in the final nuclear abundances originating from uncertainties in the astrophysical reaction rates were determined. In addition to the 35 classical p nuclides, abundance uncertainties were also determined for the radioactive nuclides 92Nb, 97, 98Tc, 146Sm, and for the abundance ratios Y(92Mo)/Y(94Mo), Y(92Nb)/Y(92Mo), Y(97Tc)/Y(98Ru), Y(98Tc)/Y(98Ru), and Y(146Sm)/Y(144Sm), important for Galactic Chemical Evolution studies. Uncertainties found were generally lower than a factor of 2, although most nucleosynthesis flows mainly involve predicted rates with larger uncertainties. The main contribution to the total uncertainties comes from a group of trajectories with high peak density originating from the interior of the exploding white dwarf. The distinction between low-density and high-density trajectories allows more general conclusions to be drawn, also applicable to other simulations of white dwarf explosions.

Persistent hypogonadotropic hypogonadism in men after severe traumatic brain injury: temporal hormone profiles and outcome prediction

PubMed Central

Barton, David J.; Kumar, Raj G.; McCullough, Emily H.; Galang, Gary; Arenth, Patricia M.; Berga, Sarah L.; Wagner, Amy K.

2015-01-01

Objective (1) Examine relationships between persistent hypogonadotropic hypogonadism (PHH) and long-term outcomes after severe traumatic brain injury (TBI); (2) determine if sub-acute testosterone levels can predict PHH. Setting Level 1 trauma center at a university hospital. Participants Consecutive sample of men with severe TBI between 2004 and 2009. Design Prospective cohort study. Main Measures Post-TBI blood samples were collected during week 1, every 2 weeks until 26 weeks, and at 52 weeks. Serum hormone levels were measured, and individuals were designated as having PHH if ≥50% of samples met criteria for hypogonadotropic hypogonadism. At 6 and 12 months post-injury, we assessed global outcome, disability, functional cognition, depression, and quality-of-life. Results We recruited 78 men; median (IQR) age was 28.5 (22–42) years. 34 patients (44%) had PHH during the first year post-injury. Multivariable regression, controlling for age, demonstrated PHH status predicted worse global outcome scores, more disability, and reduced functional cognition at 6 and 12 months post-TBI. Two-step testosterone screening for PHH at 12–16 weeks post-injury yielded a sensitivity of 79% and specificity of 100%. Conclusion PHH status in men predicts poor outcome after severe TBI, and PHH can accurately be predicted at 12–16 weeks. PMID:26360007

Improving Allergen Prediction in Main Crops Using a Weighted Integrative Method.

PubMed

Li, Jing; Wang, Jing; Li, Jing

2017-12-01

As a public health problem, food allergy is frequently caused by food allergy proteins, which trigger a type-I hypersensitivity reaction in the immune system of atopic individuals. The food allergens in our daily lives are mainly from crops including rice, wheat, soybean and maize. However, allergens in these main crops are far from fully uncovered. Although some bioinformatics tools or methods predicting the potential allergenicity of proteins have been proposed, each method has their limitation. In this paper, we built a novel algorithm PREAL W , which integrated PREAL, FAO/WHO criteria and motif-based method by a weighted average score, to benefit the advantages of different methods. Our results illustrated PREAL W has better performance significantly in the crops' allergen prediction. This integrative allergen prediction algorithm could be useful for critical food safety matters. The PREAL W could be accessed at http://lilab.life.sjtu.edu.cn:8080/prealw .

Bayesian assurance and sample size determination in the process validation life-cycle.

PubMed

Faya, Paul; Seaman, John W; Stamey, James D

2017-01-01

Validation of pharmaceutical manufacturing processes is a regulatory requirement and plays a key role in the assurance of drug quality, safety, and efficacy. The FDA guidance on process validation recommends a life-cycle approach which involves process design, qualification, and verification. The European Medicines Agency makes similar recommendations. The main purpose of process validation is to establish scientific evidence that a process is capable of consistently delivering a quality product. A major challenge faced by manufacturers is the determination of the number of batches to be used for the qualification stage. In this article, we present a Bayesian assurance and sample size determination approach where prior process knowledge and data are used to determine the number of batches. An example is presented in which potency uniformity data is evaluated using a process capability metric. By using the posterior predictive distribution, we simulate qualification data and make a decision on the number of batches required for a desired level of assurance.

The role of repetitive thought in determining posttraumatic growth and distress following interpersonal trauma.

PubMed

Allbaugh, Lucy Jane; Wright, Margaret O'Dougherty; Folger, Susan F

2016-01-01

Repetitive thought (RT) strategies have been linked to a range of negative outcomes following traumatic interpersonal events but are proposed to serve an adaptive function under particular circumstances. This study examined outcomes following RT within a transdiagnostic framework, and explored the potentially adaptive nature of trait-like and event-related RT. The centrality of a traumatic event to one's identity was explored as a context under which the adaptive nature of RT might change. Young adults with interpersonal violence experiences (N = 163) reported use of trait-like and event-related RT, centrality of the event, depressive, anxious, and posttraumatic stress symptoms (PTSS), posttraumatic depreciation and posttraumatic growth. Hierarchical multiple regression analyses were used to examine main and moderating effects of four types of RT and event centrality on outcome variables. Centrality positively predicted depressive symptoms and PTSS, depreciation, and growth. Brooding RT positively predicted all negative outcomes. Reflecting RT positively predicted anxious symptoms and PTSS and depreciation. Only deliberate RT positively predicted growth. Centrality did not moderate any examined relationships. Findings highlight the importance of addressing specific types of RT in interventions with survivors and of considering centrality as a robust contributor to outcomes following interpersonal violence.

Driving Errors in Parkinson’s Disease: Moving Closer to Predicting On-Road Outcomes

PubMed Central

Brumback, Babette; Monahan, Miriam; Malaty, Irene I.; Rodriguez, Ramon L.; Okun, Michael S.; McFarland, Nikolaus R.

2014-01-01

Age-related medical conditions such as Parkinson’s disease (PD) compromise driver fitness. Results from studies are unclear on the specific driving errors that underlie passing or failing an on-road assessment. In this study, we determined the between-group differences and quantified the on-road driving errors that predicted pass or fail on-road outcomes in 101 drivers with PD (mean age = 69.38 ± 7.43) and 138 healthy control (HC) drivers (mean age = 71.76 ± 5.08). Participants with PD had minor differences in demographics and driving habits and history but made more and different driving errors than HC participants. Drivers with PD failed the on-road test to a greater extent than HC drivers (41% vs. 9%), χ2(1) = 35.54, HC N = 138, PD N = 99, p < .001. The driving errors predicting on-road pass or fail outcomes (95% confidence interval, Nagelkerke R2 =.771) were made in visual scanning, signaling, vehicle positioning, speeding (mainly underspeeding, t(61) = 7.004, p < .001, and total errors. Although it is difficult to predict on-road outcomes, this study provides a foundation for doing so. PMID:24367958

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

NASA Astrophysics Data System (ADS)

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

2010-06-01

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

A machine learning approach for predicting CRISPR-Cas9 cleavage efficiencies and patterns underlying its mechanism of action.

PubMed

Abadi, Shiran; Yan, Winston X; Amar, David; Mayrose, Itay

2017-10-01

The adaptation of the CRISPR-Cas9 system as a genome editing technique has generated much excitement in recent years owing to its ability to manipulate targeted genes and genomic regions that are complementary to a programmed single guide RNA (sgRNA). However, the efficacy of a specific sgRNA is not uniquely defined by exact sequence homology to the target site, thus unintended off-targets might additionally be cleaved. Current methods for sgRNA design are mainly concerned with predicting off-targets for a given sgRNA using basic sequence features and employ elementary rules for ranking possible sgRNAs. Here, we introduce CRISTA (CRISPR Target Assessment), a novel algorithm within the machine learning framework that determines the propensity of a genomic site to be cleaved by a given sgRNA. We show that the predictions made with CRISTA are more accurate than other available methodologies. We further demonstrate that the occurrence of bulges is not a rare phenomenon and should be accounted for in the prediction process. Beyond predicting cleavage efficiencies, the learning process provides inferences regarding patterns that underlie the mechanism of action of the CRISPR-Cas9 system. We discover that attributes that describe the spatial structure and rigidity of the entire genomic site as well as those surrounding the PAM region are a major component of the prediction capabilities.

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

PubMed

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

2017-09-20

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

lncRNATargets: A platform for lncRNA target prediction based on nucleic acid thermodynamics.

PubMed

Hu, Ruifeng; Sun, Xiaobo

2016-08-01

Many studies have supported that long noncoding RNAs (lncRNAs) perform various functions in various critical biological processes. Advanced experimental and computational technologies allow access to more information on lncRNAs. Determining the functions and action mechanisms of these RNAs on a large scale is urgently needed. We provided lncRNATargets, which is a web-based platform for lncRNA target prediction based on nucleic acid thermodynamics. The nearest-neighbor (NN) model was used to calculate binging-free energy. The main principle of NN model for nucleic acid assumes that identity and orientation of neighbor base pairs determine stability of a given base pair. lncRNATargets features the following options: setting of a specific temperature that allow use not only for human but also for other animals or plants; processing all lncRNAs in high throughput without RNA size limitation that is superior to any other existing tool; and web-based, user-friendly interface, and colored result displays that allow easy access for nonskilled computer operators and provide better understanding of results. This technique could provide accurate calculation on the binding-free energy of lncRNA-target dimers to predict if these structures are well targeted together. lncRNATargets provides high accuracy calculations, and this user-friendly program is available for free at http://www.herbbol.org:8001/lrt/ .

Limitations of ultrasonography for diagnosing white matter damage in preterm infants

PubMed Central

Debillon, T; N'Guyen, S; Muet, A; Quere, M; Moussaly, F; Roze, J

2003-01-01

Objectives: To compare the accuracy of ultrasonography (US) and magnetic resonance imaging (MRI) in diagnosing white matter abnormalities in preterm infants and to determine the specific indications for MRI. Design: Prospective cohort study. Setting: A neonatal intensive care unit in France. Patients: All preterm infants (≤ 33 weeks gestation) without severe respiratory distress syndrome precluding MRI. Main outcome measures: US and MRI performed contemporaneously during the third postnatal week were analysed by an independent observer. The findings were compared with those of a term MRI scan, the results of which were taken as the final diagnosis. Statistical analysis was performed to determine which early imaging study best predicted the term MRI findings. Results: The early US and MRI findings (79 infants) correlated closely for severe lesions (cystic periventricular leucomalacia and parenchymal infarction; κ coefficient = 0.86) but not for moderate lesions (non-cystic leucomalacia and parenchymal punctate haemorrhages; κ = 0.62). Overall, early MRI findings predicted late MRI findings in 98% of patients (95% confidence interval (CI) 89.5 to 99.9) compared with only 68% for early US (95% CI 52.1 to 79.2). Conclusions: US is highly effective in detecting severe lesions of the white matter in preterm infants, but MRI seems to be necessary for the diagnosis of less severe damage. MRI performed at about the third week of life is highly predictive of the final diagnosis at term. PMID:12819157

The role of residence time in diagnostic models of global carbon storage capacity: model decomposition based on a traceable scheme.

PubMed

Yizhao, Chen; Jianyang, Xia; Zhengguo, Sun; Jianlong, Li; Yiqi, Luo; Chengcheng, Gang; Zhaoqi, Wang

2015-11-06

As a key factor that determines carbon storage capacity, residence time (τE) is not well constrained in terrestrial biosphere models. This factor is recognized as an important source of model uncertainty. In this study, to understand how τE influences terrestrial carbon storage prediction in diagnostic models, we introduced a model decomposition scheme in the Boreal Ecosystem Productivity Simulator (BEPS) and then compared it with a prognostic model. The result showed that τE ranged from 32.7 to 158.2 years. The baseline residence time (τ'E) was stable for each biome, ranging from 12 to 53.7 years for forest biomes and 4.2 to 5.3 years for non-forest biomes. The spatiotemporal variations in τE were mainly determined by the environmental scalar (ξ). By comparing models, we found that the BEPS uses a more detailed pool construction but rougher parameterization for carbon allocation and decomposition. With respect to ξ comparison, the global difference in the temperature scalar (ξt) averaged 0.045, whereas the moisture scalar (ξw) had a much larger variation, with an average of 0.312. We propose that further evaluations and improvements in τ'E and ξw predictions are essential to reduce the uncertainties in predicting carbon storage by the BEPS and similar diagnostic models.

The role of residence time in diagnostic models of global carbon storage capacity: model decomposition based on a traceable scheme

PubMed Central

Yizhao, Chen; Jianyang, Xia; Zhengguo, Sun; Jianlong, Li; Yiqi, Luo; Chengcheng, Gang; Zhaoqi, Wang

2015-01-01

As a key factor that determines carbon storage capacity, residence time (τE) is not well constrained in terrestrial biosphere models. This factor is recognized as an important source of model uncertainty. In this study, to understand how τE influences terrestrial carbon storage prediction in diagnostic models, we introduced a model decomposition scheme in the Boreal Ecosystem Productivity Simulator (BEPS) and then compared it with a prognostic model. The result showed that τE ranged from 32.7 to 158.2 years. The baseline residence time (τ′E) was stable for each biome, ranging from 12 to 53.7 years for forest biomes and 4.2 to 5.3 years for non-forest biomes. The spatiotemporal variations in τE were mainly determined by the environmental scalar (ξ). By comparing models, we found that the BEPS uses a more detailed pool construction but rougher parameterization for carbon allocation and decomposition. With respect to ξ comparison, the global difference in the temperature scalar (ξt) averaged 0.045, whereas the moisture scalar (ξw) had a much larger variation, with an average of 0.312. We propose that further evaluations and improvements in τ′E and ξw predictions are essential to reduce the uncertainties in predicting carbon storage by the BEPS and similar diagnostic models. PMID:26541245

[Is streptococcal pharyngitis diagnosis possible?].

PubMed

Marín Cañada, Jaime; Cubillo Serna, Ana; Gómez-Escalonilla Cruz, Nieves; Garzón de la Iglesia, Jesús; Benito Ortiz, Luis; Reyes Fernández, M Nieves

2007-07-01

To determine the validity of the Centor score (cervical adenopathy, tonsillar exudate, fever, and absence of catarrh symptoms) in diagnosing streptococcal pharyngitis (gold standard: throat swab). Descriptive study. San Fernando 2 Health Centre, Madrid (outer urban area), Spain. On hundred forty patients over 14 years old who had a "sore throat" as main symptom and attended clinic between 14 February and 12 May, 2005. Sensitivity, specificity, positive and negative predictive values, and the probability quotients of the Centor score were determined. Pharyngeal throat culture was used as the reference method. Thirty four patients had positive throat culture (24.3%; 95% CI, 17.6%-32.4%). Finding the 4 criteria in the Centor score had a positive predictive value (PPV) of 48.1% (95% CI, 30.7%-66.0%) and a negative predictive value (NPV) of 81.4% (95% CI, 73.3%-87.5%); although only fever (OR, 3.64; 95% CI, 1.40-9.49) and tonsillar exudate (OR, 6.18; 95% CI, 2.08-18.35) were linked to streptococcal aetiology. The high NPV and specificity of the clinical score makes the diagnosis of non-streptococcal pharyngitis very accurate. However, the PPV is low: a high Centor score (3 or 4 criteria) does not mean streptococcal pharyngitis with certainty. What approach to take with patients suspected of streptococcal pharyngitis is not yet resolved (microbiological test, early antibiotic, or postponed antibiotic).

Independent Predictors of Prognosis Based on Oral Cavity Squamous Cell Carcinoma Surgical Margins.

PubMed

Buchakjian, Marisa R; Ginader, Timothy; Tasche, Kendall K; Pagedar, Nitin A; Smith, Brian J; Sperry, Steven M

2018-05-01

Objective To conduct a multivariate analysis of a large cohort of oral cavity squamous cell carcinoma (OCSCC) cases for independent predictors of local recurrence (LR) and overall survival (OS), with emphasis on the relationship between (1) prognosis and (2) main specimen permanent margins and intraoperative tumor bed frozen margins. Study Design Retrospective cohort study. Setting Tertiary academic head and neck cancer program. Subjects and Methods This study included 426 patients treated with OCSCC resection between 2005 and 2014 at University of Iowa Hospitals and Clinics. Patients underwent excision of OCSCC with intraoperative tumor bed frozen margin sampling and main specimen permanent margin assessment. Multivariate analysis of the data set to predict LR and OS was performed. Results Independent predictors of LR included nodal involvement, histologic grade, and main specimen permanent margin status. Specifically, the presence of a positive margin (odds ratio, 6.21; 95% CI, 3.3-11.9) or <1-mm/carcinoma in situ margin (odds ratio, 2.41; 95% CI, 1.19-4.87) on the main specimen was an independent predictor of LR, whereas intraoperative tumor bed margins were not predictive of LR on multivariate analysis. Similarly, independent predictors of OS on multivariate analysis included nodal involvement, extracapsular extension, and a positive main specimen margin. Tumor bed margins did not independently predict OS. Conclusion The main specimen margin is a strong independent predictor of LR and OS on multivariate analysis. Intraoperative tumor bed frozen margins do not independently predict prognosis. We conclude that emphasis should be placed on evaluating the main specimen margins when estimating prognosis after OCSCC resection.

Metal Ion Speciation and Dissolved Organic Matter Composition in Soil Solutions

NASA Astrophysics Data System (ADS)

Benedetti, M. F.; Ren, Z. L.; Bravin, M.; Tella, M.; Dai, J.

2014-12-01

Knowledge of the speciation of heavy metals and the role of dissolved organic matter (DOM) in soil solution is a key to understand metal mobility and ecotoxicity. In this study, soil column-Donnan membrane technique (SC-DMT) was used to measure metal speciation of Cd, Cu, Ni, Pb, and Zn in eighteen soil solutions, covering a wide range of metal sources and concentrations. DOM composition in these soil solutions was also determined. Our results show that in soil solution Pb and Cu are dominant in complex form, whereas Cd, Ni and Zn mainly exist as free ions; for the whole range of soil solutions, only 26.2% of DOM is reactive and consists mainly of fulvic acid (FA). The metal speciation measured by SC-DMT was compared to the predicted ones obtained via the NICA-Donnan model using the measured FA concentrations. The free ion concentrations predicted by speciation modelling were in good agreement with the measurements. Diffusive gradients in thin-films gels (DGT) were also performed to quantify the labile metal species in the fluxes from solid phase to solution in fourteen soils. The concentrations of metal species detected by DGT were compared with the free ion concentrations measured by DMT and the maximum concentrations calculated based on the predicted metal speciation in SC-DMT soil solutions. It is concluded that both inorganic species and a fraction of FA bound species account for the amount of labile metals measured by DGT, consistent with the dynamic features of this technique. The comparisons between measurements using analytical techniques and mechanistic model predictions provided mutual validation in their performance. Moreover, we show that to make accurate modelling of metal speciation in soil solutions, the knowledge of DOM composition is the crucial information, especially for Cu; like in previous studies the modelling of Pb speciation is not optimal and an updated of Pb generic binding parameters is required to reduce model prediction uncertainties.

On the Validity of Validity Scales: The Importance of Defensive Responding in the Prediction of Institutional Misconduct

ERIC Educational Resources Information Center

Edens, John F.; Ruiz, Mark A.

2006-01-01

This study examined the effects of defensive responding on the prediction of institutional misconduct among male inmates (N = 349) who completed the Personality Assessment Inventory (L. C. Morey, 1991). Hierarchical logistic regression analyses demonstrated significant main effects for the Antisocial Features (ANT) scale as well as main effects…

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

Lorenzetti, E.A.; Brennan, P.A.; Hook, S.C.

The authors present graphical solutions to the extensional fault-related folding equations of Xiao and Suppe (1992), simplifying the prediction of normal fault location or rollover geometry from subsurface data. These equations also predict the extent of bed thinning and elongation in hanging wall strata. They have derived new equations that relate change in fault slip across a fault bend to fault geometry. Applying these equations in seismic interpretation makes it easier to (1) construct balanced cross-sections, (2) account for the slip observed, and (3) determine the growth history of extensional fault-related folds. They have applied these concepts to several southeastmore » Asian rift basins in Malaysia, Myanmar, Indonesia, and Thailand. These basins were formed by early Tertiary crustal extension, producing rollover structures in which sediment supply generally did not keep up with subsidence. These under-filled, internally drained depressions periodically contained lakes, providing the environment for deposition of organic-rich strata that ultimately became hydrocarbon source rock. Typically, the main basin bounding faults dip 35-55[degrees] near their upper terminations and flatten to become subhorizontal. Synthetic and antithetic secondary faults are usually present. Late compaction faulting often propagates upward from major extensional faults and may reactivate the upper portions of these faults. In many basins, late compression produced inversion structures. By applying the concepts of extensional fault-related folding to these basins, they can (1) explain observed geometries, (2) predict poorly imaged geometries, (3) predict the location of source and reservoir facies, and (4) determine the timing of faulting relative to deposition of source and reservoir rocks.« less

Global vision of druggability issues: applications and perspectives.

PubMed

Abi Hussein, Hiba; Geneix, Colette; Petitjean, Michel; Borrel, Alexandre; Flatters, Delphine; Camproux, Anne-Claude

2017-02-01

During the preliminary stage of a drug discovery project, the lack of druggability information and poor target selection are the main causes of frequent failures. Elaborating on accurate computational druggability prediction methods is a requirement for prioritizing target selection, designing new drugs and avoiding side effects. In this review, we describe a survey of recently reported druggability prediction methods mainly based on networks, statistical pocket druggability predictions and virtual screening. An application for a frequent mutation of p53 tumor suppressor is presented, illustrating the complementarity of druggability prediction approaches, the remaining challenges and potential new drug development perspectives. Copyright © 2016 Elsevier Ltd. All rights reserved.

Soil-pipe interaction modeling for pipe behavior prediction with super learning based methods

NASA Astrophysics Data System (ADS)

Shi, Fang; Peng, Xiang; Liu, Huan; Hu, Yafei; Liu, Zheng; Li, Eric

2018-03-01

Underground pipelines are subject to severe distress from the surrounding expansive soil. To investigate the structural response of water mains to varying soil movements, field data, including pipe wall strains in situ soil water content, soil pressure and temperature, was collected. The research on monitoring data analysis has been reported, but the relationship between soil properties and pipe deformation has not been well-interpreted. To characterize the relationship between soil property and pipe deformation, this paper presents a super learning based approach combining feature selection algorithms to predict the water mains structural behavior in different soil environments. Furthermore, automatic variable selection method, e.i. recursive feature elimination algorithm, were used to identify the critical predictors contributing to the pipe deformations. To investigate the adaptability of super learning to different predictive models, this research employed super learning based methods to three different datasets. The predictive performance was evaluated by R-squared, root-mean-square error and mean absolute error. Based on the prediction performance evaluation, the superiority of super learning was validated and demonstrated by predicting three types of pipe deformations accurately. In addition, a comprehensive understand of the water mains working environments becomes possible.

The effect of mineral composition on the sorption of cesium ions on geological formations.

PubMed

Kónya, József; Nagy, Noémi M; Nemes, Zoltán

2005-10-15

The sorption of cesium-137 on rock samples, mainly on clay rocks, is determined as a function of the mineral composition of the rocks. A relation between the mineral groups (tectosilicates, phyllosilicates, clay minerals, carbonates) and their cesium sorption properties is shown. A linear model is constructed by which the distribution coefficients of the different minerals can be calculated from the mineral composition and the net distribution coefficient of the rock. On the basis of the distribution coefficients of the minerals the cesium sorption properties of other rocks can be predicted.

[Prediction of regional soil quality based on mutual information theory integrated with decision tree algorithm].

PubMed

Lin, Fen-Fang; Wang, Ke; Yang, Ning; Yan, Shi-Guang; Zheng, Xin-Yu

2012-02-01

In this paper, some main factors such as soil type, land use pattern, lithology type, topography, road, and industry type that affect soil quality were used to precisely obtain the spatial distribution characteristics of regional soil quality, mutual information theory was adopted to select the main environmental factors, and decision tree algorithm See 5.0 was applied to predict the grade of regional soil quality. The main factors affecting regional soil quality were soil type, land use, lithology type, distance to town, distance to water area, altitude, distance to road, and distance to industrial land. The prediction accuracy of the decision tree model with the variables selected by mutual information was obviously higher than that of the model with all variables, and, for the former model, whether of decision tree or of decision rule, its prediction accuracy was all higher than 80%. Based on the continuous and categorical data, the method of mutual information theory integrated with decision tree could not only reduce the number of input parameters for decision tree algorithm, but also predict and assess regional soil quality effectively.

Body size, performance and fitness in galapagos marine iguanas.

PubMed

Wikelski, Martin; Romero, L Michael

2003-07-01

Complex organismal traits such as body size are influenced by innumerable selective pressures, making the prediction of evolutionary trajectories for those traits difficult. A potentially powerful way to predict fitness in natural systems is to study the composite response of individuals in terms of performance measures, such as foraging or reproductive performance. Once key performance measures are identified in this top-down approach, we can determine the underlying physiological mechanisms and gain predictive power over long-term evolutionary processes. Here we use marine iguanas as a model system where body size differs by more than one order of magnitude between island populations. We identified foraging efficiency as the main performance measure that constrains body size. Mechanistically, foraging performance is determined by food pasture height and the thermal environment, influencing intake and digestion. Stress hormones may be a flexible way of influencing an individual's response to low-food situations that may be caused by high population density, famines, or anthropogenic disturbances like oil spills. Reproductive performance, on the other hand, increases with body size and is mediated by higher survival of larger hatchlings from larger females and increased mating success of larger males. Reproductive performance of males may be adjusted via plastic hormonal feedback mechanisms that allow individuals to assess their social rank annually within the current population size structure. When integrated, these data suggest that reproductive performance favors increased body size (influenced by reproductive hormones), with an overall limit imposed by foraging performance (influenced by stress hormones). Based on our mechanistic understanding of individual performances we predicted an evolutionary increase in maximum body size caused by global warming trends. We support this prediction using specimens collected during 1905. We also show in a common-garden experiment that body size may have a genetic component in iguanids. This 'performance paradigm' allows predictions about adaptive evolution in natural populations.

Are High-Impact Species Predictable? An Analysis of Naturalised Grasses in Northern Australia

PubMed Central

van Klinken, Rieks D.; Panetta, F. Dane; Coutts, Shaun R.

2013-01-01

Predicting which species are likely to cause serious impacts in the future is crucial for targeting management efforts, but the characteristics of such species remain largely unconfirmed. We use data and expert opinion on tropical and subtropical grasses naturalised in Australia since European settlement to identify naturalised and high-impact species and subsequently to test whether high-impact species are predictable. High-impact species for the three main affected sectors (environment, pastoral and agriculture) were determined by assessing evidence against pre-defined criteria. Twenty-one of the 155 naturalised species (14%) were classified as high-impact, including four that affected more than one sector. High-impact species were more likely to have faster spread rates (regions invaded per decade) and to be semi-aquatic. Spread rate was best explained by whether species had been actively spread (as pasture), and time since naturalisation, but may not be explanatory as it was tightly correlated with range size and incidence rate. Giving more weight to minimising the chance of overlooking high-impact species, a priority for biosecurity, meant a wider range of predictors was required to identify high-impact species, and the predictive power of the models was reduced. By-sector analysis of predictors of high impact species was limited by their relative rarity, but showed sector differences, including to the universal predictors (spread rate and habitat) and life history. Furthermore, species causing high impact to agriculture have changed in the past 10 years with changes in farming practice, highlighting the importance of context in determining impact. A rationale for invasion ecology is to improve the prediction and response to future threats. Although our study identifies some universal predictors, it suggests improved prediction will require a far greater emphasis on impact rather than invasiveness, and will need to account for the individual circumstances of affected sectors and the relative rarity of high-impact species. PMID:23874718

Intensity and Duration of Negative Emotions: Comparing the Role of Appraisals and Regulation Strategies

PubMed Central

Brans, Karen; Verduyn, Philippe

2014-01-01

Intensity and duration are two central characteristics of an emotional response. Appraisals and regulation strategies are among the most important determinants of these emotion features. However, as intensity and duration are only moderately correlated, appraisals and regulation strategies may be differently related to these characteristics. A systematic empirical study comparing predictors of emotion intensity and duration is missing. The goal of the present study is to fill this gap. Participants were asked to recall recently experienced episodes of anger, fear, disgust, guilt, sadness, and shame. Subsequently, they were asked to answer a number of questions regarding (a) the intensity and duration of these emotions, (b) their appraisal of the emotion-eliciting event, and (c) their use of a wide range of regulation strategies. Emotion intensity was found to be mainly predicted by appraisals whereas emotion duration was equally well predicted by appraisals and regulation strategies. PMID:24670979

Numerical simulations of fire spread in a Pinus pinaster needles fuel bed

NASA Astrophysics Data System (ADS)

Menage, D.; Chetehouna, K.; Mell, W.

2012-11-01

The main aim of this paper is to extend the cases of WFDS model validation by comparing its predictions to literature data on a ground fire spreading in a Pinus pinaster needles fuel bed. This comparison is based on the experimental results of Mendes-Lopes and co-workers. This study is performed using the same domain as in the experiments (3.0m×1.2m×0.9m) with a mesh of 49,280 cells. We investigate the influence of wind (varied between 0 and 2 m/s) and moisture content (10 and 18%) on the rate of spread. The WFDS rate of spread is determined using a cross-correlation function of ground temperature profiles. The simulated rate of spread, as well as temperature, compared favourably to experimental values and show the WFDS model capacity to predict ground fires in Pinus Pinaster fuel beds.

A common periodic table of codons and amino acids.

PubMed

Biro, J C; Benyó, B; Sansom, C; Szlávecz, A; Fördös, G; Micsik, T; Benyó, Z

2003-06-27

A periodic table of codons has been designed where the codons are in regular locations. The table has four fields (16 places in each) one with each of the four nucleotides (A, U, G, C) in the central codon position. Thus, AAA (lysine), UUU (phenylalanine), GGG (glycine), and CCC (proline) were placed into the corners of the fields as the main codons (and amino acids) of the fields. They were connected to each other by six axes. The resulting nucleic acid periodic table showed perfect axial symmetry for codons. The corresponding amino acid table also displaced periodicity regarding the biochemical properties (charge and hydropathy) of the 20 amino acids and the position of the stop signals. The table emphasizes the importance of the central nucleotide in the codons and predicts that purines control the charge while pyrimidines determine the polarity of the amino acids. This prediction was experimentally tested.

Compression in Working Memory and Its Relationship With Fluid Intelligence.

PubMed

Chekaf, Mustapha; Gauvrit, Nicolas; Guida, Alessandro; Mathy, Fabien

2018-06-01

Working memory has been shown to be strongly related to fluid intelligence; however, our goal is to shed further light on the process of information compression in working memory as a determining factor of fluid intelligence. Our main hypothesis was that compression in working memory is an excellent indicator for studying the relationship between working-memory capacity and fluid intelligence because both depend on the optimization of storage capacity. Compressibility of memoranda was estimated using an algorithmic complexity metric. The results showed that compressibility can be used to predict working-memory performance and that fluid intelligence is well predicted by the ability to compress information. We conclude that the ability to compress information in working memory is the reason why both manipulation and retention of information are linked to intelligence. This result offers a new concept of intelligence based on the idea that compression and intelligence are equivalent problems. Copyright © 2018 Cognitive Science Society, Inc.

Prediction of Fatigue Crack Growth in Gas Turbine Engine Blades Using Acoustic Emission

PubMed Central

Zhang, Zhiheng; Yang, Guoan; Hu, Kun

2018-01-01

Fatigue failure is the main type of failure that occurs in gas turbine engine blades and an online monitoring method for detecting fatigue cracks in blades is urgently needed. Therefore, in this present study, we propose the use of acoustic emission (AE) monitoring for the online identification of the blade status. Experiments on fatigue crack propagation based on the AE monitoring of gas turbine engine blades and TC11 titanium alloy plates were conducted. The relationship between the cumulative AE hits and the fatigue crack length was established, before a method of using the AE parameters to determine the crack propagation stage was proposed. A method for predicting the degree of crack propagation and residual fatigue life based on the AE energy was obtained. The results provide a new method for the online monitoring of cracks in the gas turbine engine blade. PMID:29693556

Neonatal seizures in a rural Iranian district hospital: etiologies, incidence and predicting factors.

PubMed

Sadeghian, Afsaneh; Damghanian, Maryam; Shariati, Mohammad

2012-01-01

Current study determined the overall incidence, common causes as well as main predictors of this final diagnosis among neonates admitted to a rural district hospital in Iran. This study was conducted on 699 neonates who were candidate for admission to the NICU. Study population was categorized in the case group, including patients exposed to final diagnosis of neonatal seizures and the control group without this diagnosis. Neonatal seizure was reported as final diagnosis in 25 (3.6%) of neonates. The most frequent discharge diagnosis in the seizure group was neonatal sepsis and in the non-seizure group was respiratory problems. No significant difference was found in early fatality rate between neonates with and without seizures (8.0% vs. 10.1%). Only gestational age <38 week had a relationship with the appearance of neonatal seizure. Low gestational age has a crucial role for predicting appearance of seizure in Iranian neonates.

Prediction of Fatigue Crack Growth in Gas Turbine Engine Blades Using Acoustic Emission.

PubMed

Zhang, Zhiheng; Yang, Guoan; Hu, Kun

2018-04-25

Fatigue failure is the main type of failure that occurs in gas turbine engine blades and an online monitoring method for detecting fatigue cracks in blades is urgently needed. Therefore, in this present study, we propose the use of acoustic emission (AE) monitoring for the online identification of the blade status. Experiments on fatigue crack propagation based on the AE monitoring of gas turbine engine blades and TC11 titanium alloy plates were conducted. The relationship between the cumulative AE hits and the fatigue crack length was established, before a method of using the AE parameters to determine the crack propagation stage was proposed. A method for predicting the degree of crack propagation and residual fatigue life based on the AE energy was obtained. The results provide a new method for the online monitoring of cracks in the gas turbine engine blade.

Structural optimization and recent large ground antenna installations

NASA Technical Reports Server (NTRS)

Levy, Roy

1989-01-01

Within the past several years, the Jet Propulsion Laboratory has designed and built major ground antenna structures in Spain, Australia, and California. One of the antennas at each location is a 70 meter-diameter structure that is a retrofit of the existing 64 meter antenna. The 64 meter existing antennas were first stripped back to a 34 meter interior and then completely new construction with deeper trusses was added to extend the interior to 70 meters. The 70 meter project included the rare opportunity to collect field data to compare with predictions of the finite-element analytical models. The new quadripod design was tested for its lower mode natural frequencies and the main reflector was measured by theodolite to determine deflections of subsets of the backup-structure deformations under load. The emphasis here is to examine measurement results and possibly provide some appreciation of the relationship of predictions made from the design model to actual measurements.

Predictor laws for pictorial flight displays

NASA Technical Reports Server (NTRS)

Grunwald, A. J.

1985-01-01

Two predictor laws are formulated and analyzed: (1) a circular path law based on constant accelerations perpendicular to the path and (2) a predictor law based on state transition matrix computations. It is shown that for both methods the predictor provides the essential lead zeros for the path-following task. However, in contrast to the circular path law, the state transition matrix law furnishes the system with additional zeros that entirely cancel out the higher-frequency poles of the vehicle dynamics. On the other hand, the circular path law yields a zero steady-state error in following a curved trajectory with a constant radius. A combined predictor law is suggested that utilizes the advantages of both methods. A simple analysis shows that the optimal prediction time mainly depends on the level of precision required in the path-following task, and guidelines for determining the optimal prediction time are given.

Prognostic markers of pediatric meningococcal sepsis.

PubMed

Briassoulis, George; Galani, Angeliki

2014-09-01

Having available tools to determine the prognosis of pediatric meningococcal sepsis at admission to the Intensive Care Unit or during the course of the disease constitutes a clinical necessity. Recently, new readily measurable circulating biomarkers have been described as an additional tool for severity classification and prediction of mortality in meningococcal disease. These biomarkers have been associated with increased risk of mortality scores and a number of organ failures in heterogeneous samples of critically ill children. In future, genetic markers may be used for identification of high-risk patients by creating prediction rules for clinical course and sequelae, and potentially provide more insight in the complex immune response in meningococcal sepsis. We briefly summarize the data pointing at the emerging genome-wide expression profiling studies and review the prognostic value of the main markers investigated in pediatric meningococcal sepsis putting them in the current frame of sepsis in general.

Exploring the Correlation Between Nontraditional Variables and Student Success: A Longitudinal Study.

PubMed

Strickland, Haley Perkins; Cheshire, Michelle Haney

2017-06-01

The purpose of this project was to determine whether a correlation exists between the traditional admission criteria of grade point averages with the potential admission criteria of emotional intelligence (EI) scores or critical thinking (CT) scores to predict upper division student outcomes. A quantitative, longitudinal design was selected to examine the identified variables to predict undergraduate student success. The recruiting sample included a convenience sample drawn from 112 junior-level undergraduate nursing students beginning their first of a five-semester nursing program. EI and HESI ® CT scores did not significantly correlate with main analysis variables. Although EI and CT scores were not significant in this study, it remains vital to incorporate EI and CT activities throughout the curriculum to develop students' ability to think like a nurse and, therefore, be successful in nursing practice. [J Nurs Educ. 2017;56(6):351-355.]. Copyright 2017, SLACK Incorporated.

Hysteresis in the Cell Response to Time-Dependent Substrate Stiffness

PubMed Central

Besser, Achim; Schwarz, Ulrich S.

2010-01-01

Abstract Mechanical cues like the rigidity of the substrate are main determinants for the decision-making of adherent cells. Here we use a mechano-chemical model to predict the cellular response to varying substrate stiffnesses. The model equations combine the mechanics of contractile actin filament bundles with a model for the Rho-signaling pathway triggered by forces at cell-matrix contacts. A bifurcation analysis of cellular contractility as a function of substrate stiffness reveals a bistable response, thus defining a lower threshold of stiffness, below which cells are not able to build up contractile forces, and an upper threshold of stiffness, above which cells are always in a strongly contracted state. Using the full dynamical model, we predict that rate-dependent hysteresis will occur in the cellular traction forces when cells are exposed to substrates of time-dependent stiffness. PMID:20655823

Solving Assembly Sequence Planning using Angle Modulated Simulated Kalman Filter

NASA Astrophysics Data System (ADS)

Mustapa, Ainizar; Yusof, Zulkifli Md.; Adam, Asrul; Muhammad, Badaruddin; Ibrahim, Zuwairie

2018-03-01

This paper presents an implementation of Simulated Kalman Filter (SKF) algorithm for optimizing an Assembly Sequence Planning (ASP) problem. The SKF search strategy contains three simple steps; predict-measure-estimate. The main objective of the ASP is to determine the sequence of component installation to shorten assembly time or save assembly costs. Initially, permutation sequence is generated to represent each agent. Each agent is then subjected to a precedence matrix constraint to produce feasible assembly sequence. Next, the Angle Modulated SKF (AMSKF) is proposed for solving ASP problem. The main idea of the angle modulated approach in solving combinatorial optimization problem is to use a function, g(x), to create a continuous signal. The performance of the proposed AMSKF is compared against previous works in solving ASP by applying BGSA, BPSO, and MSPSO. Using a case study of ASP, the results show that AMSKF outperformed all the algorithms in obtaining the best solution.

Baseline estimation in flame's spectra by using neural networks and robust statistics

NASA Astrophysics Data System (ADS)

Garces, Hugo; Arias, Luis; Rojas, Alejandro

2014-09-01

This work presents a baseline estimation method in flame spectra based on artificial intelligence structure as a neural network, combining robust statistics with multivariate analysis to automatically discriminate measured wavelengths belonging to continuous feature for model adaptation, surpassing restriction of measuring target baseline for training. The main contributions of this paper are: to analyze a flame spectra database computing Jolliffe statistics from Principal Components Analysis detecting wavelengths not correlated with most of the measured data corresponding to baseline; to systematically determine the optimal number of neurons in hidden layers based on Akaike's Final Prediction Error; to estimate baseline in full wavelength range sampling measured spectra; and to train an artificial intelligence structure as a Neural Network which allows to generalize the relation between measured and baseline spectra. The main application of our research is to compute total radiation with baseline information, allowing to diagnose combustion process state for optimization in early stages.

The derivation and validation of a simple model for predicting in-hospital mortality of acutely admitted patients to internal medicine wards.

PubMed

Sakhnini, Ali; Saliba, Walid; Schwartz, Naama; Bisharat, Naiel

2017-06-01

Limited information is available about clinical predictors of in-hospital mortality in acute unselected medical admissions. Such information could assist medical decision-making.To develop a clinical model for predicting in-hospital mortality in unselected acute medical admissions and to test the impact of secondary conditions on hospital mortality.This is an analysis of the medical records of patients admitted to internal medicine wards at one university-affiliated hospital. Data obtained from the years 2013 to 2014 were used as a derivation dataset for creating a prediction model, while data from 2015 was used as a validation dataset to test the performance of the model. For each admission, a set of clinical and epidemiological variables was obtained. The main diagnosis at hospitalization was recorded, and all additional or secondary conditions that coexisted at hospital admission or that developed during hospital stay were considered secondary conditions.The derivation and validation datasets included 7268 and 7843 patients, respectively. The in-hospital mortality rate averaged 7.2%. The following variables entered the final model; age, body mass index, mean arterial pressure on admission, prior admission within 3 months, background morbidity of heart failure and active malignancy, and chronic use of statins and antiplatelet agents. The c-statistic (ROC-AUC) of the prediction model was 80.5% without adjustment for main or secondary conditions, 84.5%, with adjustment for the main diagnosis, and 89.5% with adjustment for the main diagnosis and secondary conditions. The accuracy of the predictive model reached 81% on the validation dataset.A prediction model based on clinical data with adjustment for secondary conditions exhibited a high degree of prediction accuracy. We provide a proof of concept that there is an added value for incorporating secondary conditions while predicting probabilities of in-hospital mortality. Further improvement of the model performance and validation in other cohorts are needed to aid hospitalists in predicting health outcomes.

Evaluation of Airframe Noise Reduction Concepts via Simulations Using a Lattice Boltzmann Approach

NASA Technical Reports Server (NTRS)

Fares, Ehab; Casalino, Damiano; Khorrami, Mehdi R.

2015-01-01

Unsteady computations are presented for a high-fidelity, 18% scale, semi-span Gulfstream aircraft model in landing configuration, i.e. flap deflected at 39 degree and main landing gear deployed. The simulations employ the lattice Boltzmann solver PowerFLOW® to simultaneously capture the flow physics and acoustics in the near field. Sound propagation to the far field is obtained using a Ffowcs Williams and Hawkings acoustic analogy approach. In addition to the baseline geometry, which was presented previously, various noise reduction concepts for the flap and main landing gear are simulated. In particular, care is taken to fully resolve the complex geometrical details associated with these concepts in order to capture the resulting intricate local flow field thus enabling accurate prediction of their acoustic behavior. To determine aeroacoustic performance, the farfield noise predicted with the concepts applied is compared to high-fidelity simulations of the untreated baseline configurations. To assess the accuracy of the computed results, the aerodynamic and aeroacoustic impact of the noise reduction concepts is evaluated numerically and compared to experimental results for the same model. The trends and effectiveness of the simulated noise reduction concepts compare well with measured values and demonstrate that the computational approach is capable of capturing the primary effects of the acoustic treatment on a full aircraft model.

The Impact of Maternal Obesity and Excessive Gestational Weight Gain on Maternal and Infant Outcomes in Maine: Analysis of Pregnancy Risk Assessment Monitoring System Results from 2000 to 2010.

PubMed

Baugh, Nancy; Harris, David E; Aboueissa, AbouEl-Makarim; Sarton, Cheryl; Lichter, Erika

2016-01-01

The objective of this study is to understand the relationships between prepregnancy obesity and excessive gestational weight gain (GWG) and adverse maternal and fetal outcomes. Pregnancy risk assessment monitoring system (PRAMS) data from Maine for 2000-2010 were used to determine associations between demographic, socioeconomic, and health behavioral variables and maternal and infant outcomes. Multivariate logistic regression analysis was performed on the independent variables of age, race, smoking, previous live births, marital status, education, BMI, income, rurality, alcohol use, and GWG. Dependent variables included maternal hypertension, premature birth, birth weight, infant admission to the intensive care unit (ICU), and length of hospital stay of the infant. Excessive prepregnancy BMI and excessive GWG independently predicted maternal hypertension. A high prepregnancy BMI increased the risk of the infant being born prematurely, having a longer hospital stay, and having an excessive birth weight. Excessive GWG predicted a longer infant hospital stay and excessive birth weight. A low pregnancy BMI and a lower than recommended GWG were also associated with poor outcomes: prematurity, low birth weight, and an increased risk of the infant admitted to ICU. These findings support the importance of preconception care that promotes achievement of a healthy weight to enhance optimal reproductive outcomes.

Deposition and material response from Mach 0.3 burner rig combustion of SRC 2 fuels

NASA Technical Reports Server (NTRS)

Santoro, G. J.; Kohl, F. J.; Stearns, C. A.; Fryburg, G. C.; Johnson, J. R.

1980-01-01

Collectors at 1173K (900 C) were exposed to the combustion products of a Mach 0.3 burner rig fueled with various industrial turbine liquid fuels from solvent refined coals. Four fuels were employed: a naphtha, a light oil, a wash solvent and a mid-heavy distillate blend. The response of four superalloys (IN-100, U 700, IN 792 and M-509) to exposure to the combustion gases from the SRC-2 naphtha and resultant deposits was also determined. The SRC-2 fuel analysis and insights obtained during the combustion experience are discussed. Particular problems encountered were fuel instability and reactions of the fuel with hardware components. The major metallic elements which contributed to the deposits were copper, iron, chromium, calcium, aluminum, nickel, silicon, titanium, zinc, and sodium. The deposits were found to be mainly metal oxides. An equilibrium thermodynamic analysis was employed to predict the chemical composition of the deposits. The agreement between the predicted and observed compounds was excellent. No hot corrosion was observed. This was expected because the deposits contained very little sodium or potassium and consisted mainly of the unreactive oxides. However, the amounts of deposits formed indicated that fouling is a potential problem with the use of these fuels.

Detection of triterpene acids distribution in loquat (Eriobotrya japonica) leaf using hyperspectral imaging

NASA Astrophysics Data System (ADS)

Shi, Jiyong; Chen, Wu; Zou, Xiaobo; Xu, Yiwei; Huang, Xiaowei; Zhu, Yaodi; Shen, Tingting

2018-01-01

Hyperspectral images (431-962 nm) and partial least squares (PLS) were used to detect the distribution of triterpene acids within loquat (Eriobotrya japonica) leaves. 72 fresh loquat leaves in the young group, mature group and old group were collected for hyperspectral imaging; and triterpene acids content of the loquat leaves was analyzed using high performance liquid chromatography (HPLC). Then the spectral data of loquat leaf hyperspectral images and the triterpene acids content were employed to build calibration models. After spectra pre-processing and wavelength selection, an optimum calibration model (Rp = 0.8473, RMSEP = 2.61 mg/g) for predicting triterpene acids was obtained by synergy interval partial least squares (siPLS). Finally, spectral data of each pixel in the loquat leaf hyperspectral image were extracted and substituted into the optimum calibration model to predict triterpene acids content of each pixel. Therefore, the distribution map of triterpene acids content was obtained. As shown in the distribution map, triterpene acids are accumulated mainly in the leaf mesophyll regions near the main veins, and triterpene acids concentration of young group is less than that of mature and old groups. This study showed that hyperspectral imaging is suitable to determine the distribution of active constituent content in medical herbs in a rapid and non-invasive manner.

Assessment of a Revised Management Strategy for Patients With Intraductal Papillary Mucinous Neoplasms Involving the Main Pancreatic Duct.

PubMed

Sugimoto, Motokazu; Elliott, Irmina A; Nguyen, Andrew H; Kim, Stephen; Muthusamy, V Raman; Watson, Rabindra; Hines, O Joe; Dawson, David W; Reber, Howard A; Donahue, Timothy R

2017-01-18

According to the 2012 International Consensus Guidelines, the diagnostic criterion of intraductal papillary mucinous neoplasms (IPMNs) involving the main duct (MD IPMNs) or the main and branch ducts (mixed IPMNs) of the pancreatic system is a main pancreatic duct (MPD) diameter of 5.0 mm or greater on computed tomography (CT) or magnetic resonance imaging (MRI). However, surgical resection is recommended for patients with an MPD diameter of 10.0 mm or greater, which is characterized as a high-risk stigma. An MPD diameter of 5.0 to 9.0 mm is not an indication for immediate resection. To determine an appropriate cutoff (ie, one with high sensitivity and negative predictive value) of the MPD diameter on CT or MRI as a prognostic factor for malignant disease and to propose a new management algorithm for patients with MD or mixed IPMNs. This retrospective cohort study included 103 patients who underwent surgical resection for a preoperative diagnosis of MD or mixed IPMN and in whom IPMN was confirmed by surgical pathologic findings at a single institution from July 1, 1996, to December 31, 2015. Malignant disease was defined as high-grade dysplasia or invasive adenocarcinoma on results of surgical pathologic evaluation. An appropriate MPD diameter on preoperative CT or MRI to predict malignant disease was determined using a receiver operating characteristic curve analysis. The prognostic value of the new management algorithm that incorporated the new MPD diameter cutoff was evaluated. Among the 103 patients undergoing resection for an MD or mixed IPMN (59 men [57.3%]; 44 women [42.7%]; median [range] age, 71 [48-86] years), 64 (62.1%) had malignant disease. Diagnostic accuracy for malignant neoplasms was highest at an MPD diameter cutoff of 7.2 mm (area under the receiver operating characteristic curve, 0.70; 95% CI, 0.59-0.81). An MPD diameter of 7.2 mm or greater was also an independent prognostic factor for malignant neoplasms (odds ratio, 12.76; 95% CI, 2.43-66.88; P = .003) on logistic regression analysis after controlling for preoperative variables. The new management algorithm, which included an MPD diameter of 7.2 mm or greater as one of the high-risk stigmata, had a higher sensitivity (100%), negative predictive value (100%), and accuracy (66%) for malignant disease than the 2012 version of the International Consensus Guidelines (95%, 57%, and 63%, respectively). In this single-center, retrospective analysis, an MPD diameter of 7.2 mm was identified as an optimal cutoff for a prognostic factor for malignant disease in MD or mixed IPMN. These data support lowering the accepted criteria for MPD diameter when selecting patients for resection vs surveillance so as not to overlook cancer in IPMN.

On predicting the extent of magnetic aging in electrical steels

NASA Astrophysics Data System (ADS)

Ray, Santanu Kumar; Mohanty, Omkar Nath

1989-02-01

Magnetic aging of steels is essentially the result of an increase in coercive force, inhibition of ferrite domain wall movement by precipitated carbide particles being the main cause of this increase. In the present work, the nature of the carbides precipitating in four grades of electrical steels has been looked into. Existing postulations have been invoked to predict the extent of coercive force enhancement due to metastable (ɛ) and stable (cementite) carbides which have been observed to precipitate in these steels. The model of Drabecki and Wyslocki when applied to the case of metastable carbide predicts its contribution to the coercive force fairly accurately. None of the existing models, however, succeeds in suggesting the extent of the increases accruing from the presence of the stable carbide (cementite) particles. Each of the models takes into account only one or two of the isolated aspects of magnetic interaction between matrix and precipitate. It appears that for cementite, whose several magnetic characteristics are quite different from those of the ferrite matrix, all possible interaction parameters have to be taken into account to determine the actual mechanism.

Evaluation of CFD to Determine Two-Dimensional Airfoil Characteristics for Rotorcraft Applications

NASA Technical Reports Server (NTRS)

Smith, Marilyn J.; Wong, Tin-Chee; Potsdam, Mark; Baeder, James; Phanse, Sujeet

2004-01-01

The efficient prediction of helicopter rotor performance, vibratory loads, and aeroelastic properties still relies heavily on the use of comprehensive analysis codes by the rotorcraft industry. These comprehensive codes utilize look-up tables to provide two-dimensional aerodynamic characteristics. Typically these tables are comprised of a combination of wind tunnel data, empirical data and numerical analyses. The potential to rely more heavily on numerical computations based on Computational Fluid Dynamics (CFD) simulations has become more of a reality with the advent of faster computers and more sophisticated physical models. The ability of five different CFD codes applied independently to predict the lift, drag and pitching moments of rotor airfoils is examined for the SC1095 airfoil, which is utilized in the UH-60A main rotor. Extensive comparisons with the results of ten wind tunnel tests are performed. These CFD computations are found to be as good as experimental data in predicting many of the aerodynamic performance characteristics. Four turbulence models were examined (Baldwin-Lomax, Spalart-Allmaras, Menter SST, and k-omega).

Prediction of conformational changes by single mutation in the hepatitis B virus surface antigen (HBsAg) identified in HBsAg-negative blood donors.

PubMed

Ie, Susan I; Thedja, Meta D; Roni, Martono; Muljono, David H

2010-11-18

Selection of hepatitis B virus (HBV) by host immunity has been suggested to give rise to variants with amino acid substitutions at or around the 'a' determinant of the surface antigen (HBsAg), the main target of antibody neutralization and diagnostic assays. However, there have never been successful attempts to provide evidence for this hypothesis, partly because the 3 D structure of HBsAg molecules has not been determined. Tertiary structure prediction of HBsAg solely from its primary amino acid sequence may reveal the molecular energetic of the mutated proteins. We carried out this preliminary study to analyze the predicted HBsAg conformation changes of HBV variants isolated from Indonesian blood donors undetectable by HBsAg assays and its significance, compared to other previously-reported variants that were associated with diagnostic failure. Three HBV variants (T123A, M133L and T143M) and a wild type sequence were analyzed together with frequently emerged variants T123N, M133I, M133T, M133V, and T143L. Based on the Jameson-Wolf algorithm for calculating antigenic index, the first two amino acid substitutions resulted in slight changes in the antigenicity of the 'a' determinant, while all four of the comparative variants showed relatively more significant changes. In the pattern T143M, changes in antigenic index were more significant, both in its coverage and magnitude, even when compared to variant T143L. These data were also partially supported by the tertiary structure prediction, in which the pattern T143M showed larger shift in the HBsAg second loop structure compared to the others. Single amino acid substitutions within or near the 'a' determinant of HBsAg may alter antigenicity properties of variant HBsAg, which can be shown by both its antigenic index and predicted 3 D conformation. Findings in this study emphasize the significance of variant T143M, the prevalent isolate with highest degree of antigenicity changes found in Indonesian blood donors. This highlights the importance of evaluating the effects of protein structure alterations on the sensitivity of screening methods being used in detection of ongoing HBV infection, as well as the use of vaccines and immunoglobulin therapy in contributing to the selection of HBV variants.

Quantitative prediction of fractures using the finite element method: A case study of the lower Silurian Longmaxi Formation in northern Guizhou, South China

NASA Astrophysics Data System (ADS)

Liu, Jingshou; Ding, Wenlong; Yang, Haimeng; Jiu, Kai; Wang, Zhe; Li, Ang

2018-04-01

Natural fractures have long been considered important factors in the production of gas from shale reservoirs because they can connect pore spaces and enlarge transport channels, thereby influencing the migration, accumulation and preservation of shale gas. Industrial-level shale gas production has been initiated in the lower Silurian Longmaxi Formation in northern Guizhou, South China. However, it is important to quantitatively predict the distribution of natural fractures in the lower Silurian shale reservoirs to locate additional 'sweet spots' in northern Guizhou. In this study, data obtained from outcrops, cores, thin sections, field-emission scanning electron microscope (FE-SEM) images and X-ray diffraction (XRD) were used to determine the developmental characteristics and controlling factors of these fractures. Correlation analysis indicated that the mechanical parameters of the Longmaxi shale are mainly related to the total organic carbon (TOC), quartz, clay, calcite and dolomite contents. The spatial variations in the mechanical parameters of the Longmaxi shale were determined based on the spatial variations in the TOC and mineral contents. Then, a heterogeneous geomechanical model of the study area was established based on interpretations of the fault systems derived from seismic data and acoustic emission (AE) experiments performed on samples of the relevant rocks. The paleotectonic stress fields during the Yanshanian period were obtained using the finite element method (FEM). Finally, a fracture density calculation model was established to analyze the quantitative development of fractures, and the effects of faults and mechanical parameters on the development of fractures were determined. The results suggest that the main developmental period of tectonic fractures in the Longmaxi Formation was the Early Yanshanian period. During this time, the horizontal principal stress conditions were dominated by a SE-NW-trending (135-315°) compressional stress field, and the Longmaxi Formation experienced a maximum tectonic stress of 110-120 MPa. This simulated paleotectonic stress field was mainly controlled by faults and the contents of TOC, quartz, clay, calcite and dolomite; at different positions along the same fault, the degree of fracture development varies significantly. Overall, the distribution of fractures in the Longmaxi Formation can be used to optimize well deployment and provides a basis for the future exploration of shale gas.

Beryllium abundances along the evolutionary sequence of the open cluster IC 4651 - A new test for hydrodynamical stellar models

NASA Astrophysics Data System (ADS)

Smiljanic, R.; Pasquini, L.; Charbonnel, C.; Lagarde, N.

2010-02-01

Context. Previous analyses of lithium abundances in main sequence and red giant stars have revealed the action of mixing mechanisms other than convection in stellar interiors. Beryllium abundances in stars with Li abundance determinations can offer valuable complementary information on the nature of these mechanisms. Aims: Our aim is to derive Be abundances along the whole evolutionary sequence of an open cluster. We focus on the well-studied open cluster IC 4651. These Be abundances are used with previously determined Li abundances, in the same sample stars, to investigate the mixing mechanisms in a range of stellar masses and evolutionary stages. Methods: Atmospheric parameters were adopted from a previous abundance analysis by the same authors. New Be abundances have been determined from high-resolution, high signal-to-noise UVES spectra using spectrum synthesis and model atmospheres. The careful synthetic modeling of the Be lines region is used to calculate reliable abundances in rapidly rotating stars. The observed behavior of Be and Li is compared to theoretical predictions from stellar models including rotation-induced mixing, internal gravity waves, atomic diffusion, and thermohaline mixing. Results: Beryllium is detected in all the main sequence and turn-off sample stars, both slow- and fast-rotating stars, including the Li-dip stars, but is not detected in the red giants. Confirming previous results, we find that the Li dip is also a Be dip, although the depletion of Be is more modest than for Li in the corresponding effective temperature range. For post-main-sequence stars, the Be dilution starts earlier within the Hertzsprung gap than expected from classical predictions, as does the Li dilution. A clear dispersion in the Be abundances is also observed. Theoretical stellar models including the hydrodynamical transport processes mentioned above are able to reproduce all the observed features well. These results show a good theoretical understanding of the Li and Be behavior along the color-magnitude diagram of this intermediate-age cluster for stars more massive than 1.2 M⊙. Based on observations made with the ESO VLT, at Paranal Observatory, under programs 065.L-0427 and 067.D-0126.Current address: European Southern Observatory, Karl-Schwarzschild-Str. 2, 85748 Garching bei München, Germany.

Predictive model of complexity in early palliative care: a cohort of advanced cancer patients (PALCOM study).

PubMed

Tuca, Albert; Gómez-Martínez, Mónica; Prat, Aleix

2018-01-01

Model of early palliative care (PC) integrated in oncology is based on shared care from the diagnosis to the end of life and is mainly focused on patients with greater complexity. However, there is no definition or tools to evaluate PC complexity. The objectives of the study were to identify the factors influencing level determination of complexity, propose predictive models, and build a complexity scale of PC. We performed a prospective, observational, multicenter study in a cohort of advanced cancer patients with an estimated prognosis ≤ 6 months. An ad hoc structured evaluation including socio-demographic and clinical data, symptom burden, functional and cognitive status, psychosocial problems, and existential-ethic dilemmas was recorded systematically. According to this multidimensional evaluation, investigator classified patients as high, medium, or low palliative complexity, associated to need of basic or specialized PC. Logistic regression was used to identify the variables influencing determination of level of PC complexity and explore predictive models. We included 324 patients; 41% were classified as having high PC complexity and 42.9% as medium, both levels being associated with specialized PC. Variables influencing determination of PC complexity were as follows: high symptom burden (OR 3.19 95%CI: 1.72-6.17), difficult pain (OR 2.81 95%CI:1.64-4.9), functional status (OR 0.99 95%CI:0.98-0.9), and social-ethical existential risk factors (OR 3.11 95%CI:1.73-5.77). Logistic analysis of variables allowed construct a complexity model and structured scales (PALCOM 1 and 2) with high predictive value (AUC ROC 76%). This study provides a new model and tools to assess complexity in palliative care, which may be very useful to manage referral to specialized PC services, and agree intensity of their intervention in a model of early-shared care integrated in oncology.

Predicting the reference evapotranspiration based on tensor decomposition

NASA Astrophysics Data System (ADS)

Misaghian, Negin; Shamshirband, Shahaboddin; Petković, Dalibor; Gocic, Milan; Mohammadi, Kasra

2017-11-01

Most of the available models for reference evapotranspiration (ET0) estimation are based upon only an empirical equation for ET0. Thus, one of the main issues in ET0 estimation is the appropriate integration of time information and different empirical ET0 equations to determine ET0 and boost the precision. The FAO-56 Penman-Monteith, adjusted Hargreaves, Blaney-Criddle, Priestley-Taylor, and Jensen-Haise equations were utilized in this study for estimating ET0 for two stations of Belgrade and Nis in Serbia using collected data for the period of 1980 to 2010. Three-order tensor is used to capture three-way correlations among months, years, and ET0 information. Afterward, the latent correlations among ET0 parameters were found by the multiway analysis to enhance the quality of the prediction. The suggested method is valuable as it takes into account simultaneous relations between elements, boosts the prediction precision, and determines latent associations. Models are compared with respect to coefficient of determination ( R 2), mean absolute error (MAE), and root-mean-square error (RMSE). The proposed tensor approach has a R 2 value of greater than 0.9 for all selected ET0 methods at both selected stations, which is acceptable for the ET0 prediction. RMSE is ranged between 0.247 and 0.485 mm day-1 at Nis station and between 0.277 and 0.451 mm day-1 at Belgrade station, while MAE is between 0.140 and 0.337 mm day-1 at Nis and between 0.208 and 0.360 mm day-1 at Belgrade station. The best performances are achieved by Priestley-Taylor model at Nis station ( R 2 = 0.985, MAE = 0.140 mm day-1, RMSE = 0.247 mm day-1) and FAO-56 Penman-Monteith model at Belgrade station (MAE = 0.208 mm day-1, RMSE = 0.277 mm day-1, R 2 = 0.975).

Measured Copper Toxicity to Cnesterodon decemmaculatus (Pisces: Poeciliidae) and Predicted by Biotic Ligand Model in Pilcomayo River Water: A Step for a Cross-Fish-Species Extrapolation

PubMed Central

Casares, María Victoria; de Cabo, Laura I.; Seoane, Rafael S.; Natale, Oscar E.; Castro Ríos, Milagros; Weigandt, Cristian; de Iorio, Alicia F.

2012-01-01

In order to determine copper toxicity (LC50) to a local species (Cnesterodon decemmaculatus) in the South American Pilcomayo River water and evaluate a cross-fish-species extrapolation of Biotic Ligand Model, a 96 h acute copper toxicity test was performed. The dissolved copper concentrations tested were 0.05, 0.19, 0.39, 0.61, 0.73, 1.01, and 1.42 mg Cu L−1. The 96 h Cu LC50 calculated was 0.655 mg L−1 (0.823 − 0.488). 96-h Cu LC50 predicted by BLM for Pimephales promelas was 0.722 mg L−1. Analysis of the inter-seasonal variation of the main water quality parameters indicates that a higher protective effect of calcium, magnesium, sodium, sulphate, and chloride is expected during the dry season. The very high load of total suspended solids in this river might be a key factor in determining copper distribution between solid and solution phases. A cross-fish-species extrapolation of copper BLM is valid within the water quality parameters and experimental conditions of this toxicity test. PMID:22523491

Determination of design and operation parameters for upper atmospheric research instrumentation to yield optimum resolution with deconvolution. Appendix 7. [Transform Domain Skiprope Observer for tethered satellites

NASA Technical Reports Server (NTRS)

Ioup, George E.; Ioup, Juliette W.

1993-01-01

Because of the interesting science which can be performed using a satellite attached by a very long tether to a mother vehicle in orbit, such as the Space Shuttle, NASA will deploy TSS-1 (Tethered Satellite System) in 1992. A very long tether (20 km in this case) has the possibility of undergoing oscillations of several different types, or modes, and higher harmonics of these modes. The purpose of this document is to describe a method for detecting the amplitude, frequency, and phase (and predicting future motion in the steady state) of these modes, in particular, the skiprope mode, using tethered satellite dynamics measurements. Specifically the rotation rate data about two orthogonal axes, calculated from output from satellite gyroscopes, are used. The data of interest are the satellite pitch and roll rate measurements. NASA has determined to use two methods to diagnose skiprope properties and predict future values. One of these, a Fourier transform domain approach, is the subject of this notebook. The main program and all subroutines are described along with the test plan for evaluating the Frequency Domain Skiprope Observer.

Potential radiological impact of tornadoes on the safety of Nuclear Fuel Services' West Valley Fuel Reprocessing Plant. Volume I. Tornado effects on head-end cell airflow

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

Holloway, L.J.; Andrae, R.W.

1981-09-01

This report describes results of a parametric study of the impacts of a tornado-generated depressurization on airflow in the contaminated process cells within the presently inoperative Nuclear Fuel Services fuel reprocessing facility near West Valley, NY. The study involved the following tasks: (1) mathematical modeling of installed ventilation and abnormal exhaust pathways from the cells and prediction of tornado-induced airflows in these pathways; (2) mathematical modeling of individual cell flow characteristics and prediction of in-cell velocities induced by flows from step 1; and (3) evaluation of the results of steps 1 and 2 to determine whether any of the pathwaysmore » investigated have the potential for releasing quantities of radioactively contaminated air from the main process cells. The study has concluded that in the event of a tornado strike, certain pathways from the cells have the potential to release radioactive materials of the atmosphere. Determination of the quantities of radioactive material released from the cells through pathways identified in step 3 is presented in Part II of this report.« less

Food powders flowability characterization: theory, methods, and applications.

PubMed

Juliano, Pablo; Barbosa-Cánovas, Gustavo V

2010-01-01

Characterization of food powders flowability is required for predicting powder flow from hoppers in small-scale systems such as vending machines or at the industrial scale from storage silos or bins dispensing into powder mixing systems or packaging machines. This review covers conventional and new methods used to measure flowability in food powders. The method developed by Jenike (1964) for determining hopper outlet diameter and hopper angle has become a standard for the design of bins and is regarded as a standard method to characterize flowability. Moreover, there are a number of shear cells that can be used to determine failure properties defined by Jenike's theory. Other classic methods (compression, angle of repose) and nonconventional methods (Hall flowmeter, Johanson Indicizer, Hosokawa powder tester, tensile strength tester, powder rheometer), used mainly for the characterization of food powder cohesiveness, are described. The effect of some factors preventing flow, such as water content, temperature, time consolidation, particle composition and size distribution, is summarized for the characterization of specific food powders with conventional and other methods. Whereas time-consuming standard methods established for hopper design provide flow properties, there is yet little comparative evidence demonstrating that other rapid methods may provide similar flow prediction.

Development of LC-MS determination method and back-propagation ANN pharmacokinetic model of corynoxeine in rat.

PubMed

Ma, Jianshe; Cai, Jinzhang; Lin, Guanyang; Chen, Huilin; Wang, Xianqin; Wang, Xianchuan; Hu, Lufeng

2014-05-15

Corynoxeine(CX), isolated from the extract of Uncaria rhynchophylla, is a useful and prospective compound in the prevention and treatment for vascular diseases. A simple and selective liquid chromatography mass spectrometry (LC-MS) method was developed to determine the concentration of CX in rat plasma. The chromatographic separation was achieved on a Zorbax SB-C18 (2.1 mm × 150 mm, 5 μm) column with acetonitrile-0.1% formic acid in water as mobile phase. Selective ion monitoring (SIM) mode was used for quantification using target ions m/z 383 for CX and m/z 237 for the carbamazepine (IS). After the LC-MS method was validated, it was applied to a back-propagation artificial neural network (BP-ANN) pharmacokinetic model study of CX in rats. The results showed that after intravenous administration of CX, it was mainly distributed in blood and eliminated quickly, t1/2 was less than 1h. The predicted concentrations generated by BP-ANN model had a high correlation coefficient (R>0.99) with experimental values. The developed BP-ANN pharmacokinetic model can be used to predict the concentration of CX in rats. Copyright © 2014 Elsevier B.V. All rights reserved.

The Relationship Between Confrontation Naming and Story Gist Production in Aphasia.

PubMed

Richardson, Jessica D; Dalton, Sarah Grace; Fromm, Davida; Forbes, Margaret; Holland, Audrey; MacWhinney, Brian

2018-03-01

The purpose of this study was to examine the relationship between picture naming performance and the ability to communicate the gist, or essential elements, of a story. We also sought to determine if this relationship varied according to Western Aphasia Battery-Revised (WAB-R; Kertesz, 2007) aphasia subtype. Demographic information, test scores, and transcripts of 258 individuals with aphasia completing 3 narrative tasks were retrieved from the AphasiaBank database. Narratives were subjected to a main concept analysis to determine gist production. A correlation analysis was used to investigate the relationship between naming scores and main concept production for the whole group of persons with aphasia and for WAB-R subtypes separately. We found strong correlations between naming test scores and narrative gist production for the large sample of persons with aphasia. However, the strength of the correlations varied by WAB-R subtype. Picture naming may accurately predict gist production for individuals with Broca's and Wernicke's aphasia, but not for other WAB-R subtypes. Given the current reprioritization of outcome measurement, picture naming may not be an appropriate surrogate measure for functional communication for all persons with aphasia. https://doi.org/10.23641/asha.5851848.

Rapid development of xylanase assay conditions using Taguchi methodology.

PubMed

Prasad Uday, Uma Shankar; Bandyopadhyay, Tarun Kanti; Bhunia, Biswanath

2016-11-01

The present investigation is mainly concerned with the rapid development of extracellular xylanase assay conditions by using Taguchi methodology. The extracellular xylanase was produced from Aspergillus niger (KP874102.1), a new strain isolated from a soil sample of the Baramura forest, Tripura West, India. Four physical parameters including temperature, pH, buffer concentration and incubation time were considered as key factors for xylanase activity and were optimized using Taguchi robust design methodology for enhanced xylanase activity. The main effect, interaction effects and optimal levels of the process factors were determined using signal-to-noise (S/N) ratio. The Taguchi method recommends the use of S/N ratio to measure quality characteristics. Based on analysis of the S/N ratio, optimal levels of the process factors were determined. Analysis of variance (ANOVA) was performed to evaluate statistically significant process factors. ANOVA results showed that temperature contributed the maximum impact (62.58%) on xylanase activity, followed by pH (22.69%), buffer concentration (9.55%) and incubation time (5.16%). Predicted results showed that enhanced xylanase activity (81.47%) can be achieved with pH 2, temperature 50°C, buffer concentration 50 Mm and incubation time 10 min.

Promoting CPAP adherence in clinical practice: A survey of Swedish and Norwegian CPAP practitioners' beliefs and practices.

PubMed

Broström, Anders; Pakpour, Amir H; Nilsen, Per; Gardner, Benjamin; Ulander, Martin

2018-03-01

The benefits of continuous positive airway pressure (CPAP) treatment for obstructive sleep apnea are well established, but adherence tends to be low. Research exploring CPAP practitioners' beliefs around determinants of CPAP adherence, and the actions they use in clinical practice to promote CPAP adherence is lacking. This study aimed to: (i) develop and validate a questionnaire to assess beliefs and current practices among CPAP practitioners; (ii) explore practitioners' beliefs regarding the main determinants of patient adherence, and the actions practitioners most commonly use to promote CPAP adherence; and (iii) explore the associations between perceived determinants and adherence-promotion actions. One-hundred and forty-two CPAP practitioners in Sweden and Norway, representing 93% of all Swedish and 62% of all Norwegian CPAP centres, were surveyed via a questionnaire exploring potential determinants (18 items) and adherence-promotion actions (20 items). Confirmatory factor analysis and second-order structural equational modelling were used to identify patterns of beliefs, and potential associations with adherence-promotion actions. Patients' knowledge, motivation and attitudes were perceived by practitioners to be the main determinants of CPAP adherence, and educating patients about effects, management and treatment adjustments were the most common practices. Knowledge was shown to predict educational and informational actions (e.g. education about obstructive sleep apnea and CPAP). Educational and informational actions were associated with medical actions (e.g. treatment adjustment), but knowledge, attitude and support had no association with medical actions. These findings indicate that a wide variety of determinants and actions are considered important, though the only relationship observed between beliefs and actions was found for knowledge and educational and informational actions. © 2018 European Sleep Research Society.

Improving Fermi Orbit Determination and Prediction in an Uncertain Atmospheric Drag Environment

NASA Technical Reports Server (NTRS)

Vavrina, Matthew A.; Newman, Clark P.; Slojkowski, Steven E.; Carpenter, J. Russell

2014-01-01

Orbit determination and prediction of the Fermi Gamma-ray Space Telescope trajectory is strongly impacted by the unpredictability and variability of atmospheric density and the spacecraft's ballistic coefficient. Operationally, Global Positioning System point solutions are processed with an extended Kalman filter for orbit determination, and predictions are generated for conjunction assessment with secondary objects. When these predictions are compared to Joint Space Operations Center radar-based solutions, the close approach distance between the two predictions can greatly differ ahead of the conjunction. This work explores strategies for improving prediction accuracy and helps to explain the prediction disparities. Namely, a tuning analysis is performed to determine atmospheric drag modeling and filter parameters that can improve orbit determination as well as prediction accuracy. A 45% improvement in three-day prediction accuracy is realized by tuning the ballistic coefficient and atmospheric density stochastic models, measurement frequency, and other modeling and filter parameters.

A method for mapping flood hazard along roads.

PubMed

Kalantari, Zahra; Nickman, Alireza; Lyon, Steve W; Olofsson, Bo; Folkeson, Lennart

2014-01-15

A method was developed for estimating and mapping flood hazard probability along roads using road and catchment characteristics as physical catchment descriptors (PCDs). The method uses a Geographic Information System (GIS) to derive candidate PCDs and then identifies those PCDs that significantly predict road flooding using a statistical modelling approach. The method thus allows flood hazards to be estimated and also provides insights into the relative roles of landscape characteristics in determining road-related flood hazards. The method was applied to an area in western Sweden where severe road flooding had occurred during an intense rain event as a case study to demonstrate its utility. The results suggest that for this case study area three categories of PCDs are useful for prediction of critical spots prone to flooding along roads: i) topography, ii) soil type, and iii) land use. The main drivers among the PCDs considered were a topographical wetness index, road density in the catchment, soil properties in the catchment (mainly the amount of gravel substrate) and local channel slope at the site of a road-stream intersection. These can be proposed as strong indicators for predicting the flood probability in ungauged river basins in this region, but some care is needed in generalising the case study results other potential factors are also likely to influence the flood hazard probability. Overall, the method proposed represents a straightforward and consistent way to estimate flooding hazards to inform both the planning of future roadways and the maintenance of existing roadways. Copyright © 2013 Elsevier Ltd. All rights reserved.

An increase in visceral fat is associated with a decrease in the taste and olfactory capacity

PubMed Central

Fernandez-Garcia, Jose Carlos; Alcaide, Juan; Santiago-Fernandez, Concepcion; Roca-Rodriguez, MM.; Aguera, Zaida; Baños, Rosa; Botella, Cristina; de la Torre, Rafael; Fernandez-Real, Jose M.; Fruhbeck, Gema; Gomez-Ambrosi, Javier; Jimenez-Murcia, Susana; Menchon, Jose M.; Casanueva, Felipe F.; Fernandez-Aranda, Fernando; Tinahones, Francisco J.; Garrido-Sanchez, Lourdes

2017-01-01

Introduction Sensory factors may play an important role in the determination of appetite and food choices. Also, some adipokines may alter or predict the perception and pleasantness of specific odors. We aimed to analyze differences in smell–taste capacity between females with different weights and relate them with fat and fat-free mass, visceral fat, and several adipokines. Materials and methods 179 females with different weights (from low weight to morbid obesity) were studied. We analyzed the relation between fat, fat-free mass, visceral fat (indirectly estimated by bioelectrical impedance analysis with visceral fat rating (VFR)), leptin, adiponectin and visfatin. The smell and taste assessments were performed through the "Sniffin’ Sticks" and "Taste Strips" respectively. Results We found a lower score in the measurement of smell (TDI-score (Threshold, Discrimination and Identification)) in obese subjects. All the olfactory functions measured, such as threshold, discrimination, identification and the TDI-score, correlated negatively with age, body mass index (BMI), leptin, fat mass, fat-free mass and VFR. In a multiple linear regression model, VFR mainly predicted the TDI-score. With regard to the taste function measurements, the normal weight subjects showed a higher score of taste functions. However a tendency to decrease was observed in the groups with greater or lesser BMI. In a multiple linear regression model VFR and age mainly predicted the total taste scores. Discussion We show for the first time that a reverse relationship exists between visceral fat and sensory signals, such as smell and taste, across a population with different body weight conditions. PMID:28158237

Longitudinal Examination of the Influence of Individual Posttraumatic Stress Disorder Symptoms and Clusters of Symptoms on the Initiation of Cigarette Smoking.

PubMed

Seelig, Amber D; Bensley, Kara M; Williams, Emily C; Armenta, Richard F; Rivera, Anna C; Peterson, Arthur V; Jacobson, Isabel G; Littman, Alyson J; Maynard, Charles; Bricker, Jonathan B; Rull, Rudolph P; Boyko, Edward J

2018-06-06

The aim of this study was to determine whether specific individual posttraumatic stress disorder (PTSD) symptoms or symptom clusters predict cigarette smoking initiation. Longitudinal data from the Millennium Cohort Study were used to estimate the relative risk for smoking initiation associated with PTSD symptoms among 2 groups: (1) all individuals who initially indicated they were nonsmokers (n = 44,968, main sample) and (2) a subset of the main sample who screened positive for PTSD (n = 1622). Participants were military service members who completed triennial comprehensive surveys that included assessments of smoking and PTSD symptoms. Complementary log-log models were fit to estimate the relative risk for subsequent smoking initiation associated with each of the 17 symptoms that comprise the PTSD Checklist and 5 symptom clusters. Models were adjusted for demographics, military factors, comorbid conditions, and other PTSD symptoms or clusters. In the main sample, no individual symptoms or clusters predicted smoking initiation. However, in the subset with PTSD, the symptoms "feeling irritable or having angry outbursts" (relative risk [RR] 1.41, 95% confidence interval [CI] 1.13-1.76) and "feeling as though your future will somehow be cut short" (RR 1.19, 95% CI 1.02-1.40) were associated with increased risk for subsequent smoking initiation. Certain PTSD symptoms were associated with higher risk for smoking initiation among current and former service members with PTSD. These results may help identify individuals who might benefit from more intensive smoking prevention efforts included with PTSD treatment.

Long bunch trains measured using a prototype cavity beam position monitor for the Compact Linear Collider

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

Cullinan, F. J.; Boogert, S. T.; Farabolini, W.

2015-11-19

The Compact Linear Collider (CLIC) requires beam position monitors (BPMs) with 50 nm spatial resolution for alignment of the beam line elements in the main linac and beam delivery system. Furthermore, the BPMs must be able to make multiple independent measurements within a single 156 ns long bunch train. A prototype cavity BPM for CLIC has been manufactured and tested on the probe beam line at the 3rd CLIC Test Facility (CTF3) at CERN. The transverse beam position is determined from the electromagnetic resonant modes excited by the beam in the two cavities of the pickup, the position cavity and the referencemore » cavity. The mode that is measured in each cavity resonates at 15 GHz and has a loaded quality factor that is below 200. Analytical expressions for the amplitude, phase and total energy of signals from long trains of bunches have been derived and the main conclusions are discussed. The results of the beam tests are presented. The variable gain of the receiver electronics has been characterized using beam excited signals and the form of the signals for different beam pulse lengths with the 2/3 ns bunch spacing has been observed. The sensitivity of the reference cavity signal to charge and the horizontal position signal to beam offset have been measured and are compared with theoretical predictions based on laboratory measurements of the BPM pickup and the form of the resonant cavity modes as determined by numerical simulation. Lastly, the BPM was calibrated so that the beam position jitter at the BPM location could be measured. It is expected that the beam jitter scales linearly with the beam size and so the results are compared to predicted values for the latter.« less

Auscultation versus Point-of-care Ultrasound to Determine Endotracheal versus Bronchial Intubation: A Diagnostic Accuracy Study.

PubMed

Ramsingh, Davinder; Frank, Ethan; Haughton, Robert; Schilling, John; Gimenez, Kimberly M; Banh, Esther; Rinehart, Joseph; Cannesson, Maxime

2016-05-01

Unrecognized malposition of the endotracheal tube (ETT) can lead to severe complications in patients under general anesthesia. The focus of this double-blinded randomized study was to assess the accuracy of point-of-care ultrasound in verifying the correct position of the ETT and to compare it with the accuracy of auscultation. Forty-two adult patients requiring general anesthesia with ETT were consented. Patients were randomized to right main bronchus, left main bronchus, or tracheal intubation. After randomization, the ETT was placed via fiber-optic visualization. Next, the location of the ETT was assessed using auscultation by a separate blinded anesthesiologist, followed by an ultrasound performed by a third blinded anesthesiologist. Ultrasound examination included assessment of tracheal dilation via cuff inflation with air and evaluation of pleural lung sliding. Statistical analysis included sensitivity, specificity, positive predictive value, negative predictive value, and interobserver agreement for the ultrasound examination (95% CI). In differentiating tracheal versus bronchial intubations, auscultation showed a sensitivity of 66% (0.39 to 0.87) and a specificity of 59% (0.39 to 0.77), whereas ultrasound showed a sensitivity of 93% (0.66 to 0.99) and specificity of 96% (0.79 to 1). Identification of tracheal versus bronchial intubation was 62% (26 of 42) in the auscultation group and 95% (40 of 42) in the ultrasound group (P = 0.0005) (CI for difference, 0.15 to 0.52), and the McNemar comparison showed statistically significant improvement with ultrasound (P < 0.0001). Interobserver agreement of ultrasound findings was 100%. Assessment of trachea and pleura via point-of-care ultrasound is superior to auscultation in determining the location of ETT.

In vitro assessment of competitive and time-dependent inhibition of the nevirapine metabolism by nortriptyline in rats.

PubMed

Usach, Iris; Ferrer, José-Maria; Peris, José-Esteban

2018-04-17

Nevirapine (NVP) is a non-nucleoside reverse transcriptase inhibitor of human immunodeficiency virus type 1 (HIV-1) widely used as a component of High Active Antiretroviral Therapy (HAART) since it is inexpensive, readily absorbed after oral administration and non-teratogenic. In the present work, the mechanism of a previously described pharmacokinetic interaction between NVP and the antidepressant drug nortriptyline (NT) was studied using rat hepatic microsomes. The obtained results showed a competitive inhibition of the NVP metabolism by NT. The three main NVP metabolites (2-OH-NVP, 3-OH-NVP and 12-OH-NVP) where competitively inhibited with similar inhibitory constant values (K i  = 4.01, 3.97 and 4.40 μM, respectively). Time-dependent inhibition of the NVP metabolism was also detected, with a 2.5-fold reduction in the IC 50 values of NT for 2-, 3-, and 12-OH-NVP formation when NT was preincubated with the microsomal suspension in the presence of an NADPH-generating system. A concentration-dependent inhibition of the formation of NVP metabolites by the main NT metabolite (10-OH-NT) was also observed, however, the inhibitory potency of 10-OH-NT was much lower than that of the parent drug. The apparent hepatic intrinsic clearance of NVP determined in these in vitro experiments was used to predict the in vivo clearance of NVP using the "well-stirred" and the "parallel-tube" models, resulting in values close to those previously observed in vivo clearance. Finally, a good prediction of the increase in the plasma concentrations of NVP when co-administered with NT was obtained employing the inhibitory constant of NT determined in vitro and the estimated plasma concentration of NT entering the liver. Copyright © 2018. Published by Elsevier Inc.

Long bunch trains measured using a prototype cavity beam position monitor for the Compact Linear Collider

NASA Astrophysics Data System (ADS)

Cullinan, F. J.; Boogert, S. T.; Farabolini, W.; Lefevre, T.; Lunin, A.; Lyapin, A.; Søby, L.; Towler, J.; Wendt, M.

2015-11-01

The Compact Linear Collider (CLIC) requires beam position monitors (BPMs) with 50 nm spatial resolution for alignment of the beam line elements in the main linac and beam delivery system. Furthermore, the BPMs must be able to make multiple independent measurements within a single 156 ns long bunch train. A prototype cavity BPM for CLIC has been manufactured and tested on the probe beam line at the 3rd CLIC Test Facility (CTF3) at CERN. The transverse beam position is determined from the electromagnetic resonant modes excited by the beam in the two cavities of the pickup, the position cavity and the reference cavity. The mode that is measured in each cavity resonates at 15 GHz and has a loaded quality factor that is below 200. Analytical expressions for the amplitude, phase and total energy of signals from long trains of bunches have been derived and the main conclusions are discussed. The results of the beam tests are presented. The variable gain of the receiver electronics has been characterized using beam excited signals and the form of the signals for different beam pulse lengths with the 2 /3 ns bunch spacing has been observed. The sensitivity of the reference cavity signal to charge and the horizontal position signal to beam offset have been measured and are compared with theoretical predictions based on laboratory measurements of the BPM pickup and the form of the resonant cavity modes as determined by numerical simulation. Finally, the BPM was calibrated so that the beam position jitter at the BPM location could be measured. It is expected that the beam jitter scales linearly with the beam size and so the results are compared to predicted values for the latter.

Application of Multispectral Imaging to Determine Quality Attributes and Ripeness Stage in Strawberry Fruit

PubMed Central

Liu, Changhong; Liu, Wei; Lu, Xuzhong; Ma, Fei; Chen, Wei; Yang, Jianbo; Zheng, Lei

2014-01-01

Multispectral imaging with 19 wavelengths in the range of 405–970 nm has been evaluated for nondestructive determination of firmness, total soluble solids (TSS) content and ripeness stage in strawberry fruit. Several analysis approaches, including partial least squares (PLS), support vector machine (SVM) and back propagation neural network (BPNN), were applied to develop theoretical models for predicting the firmness and TSS of intact strawberry fruit. Compared with PLS and SVM, BPNN considerably improved the performance of multispectral imaging for predicting firmness and total soluble solids content with the correlation coefficient (r) of 0.94 and 0.83, SEP of 0.375 and 0.573, and bias of 0.035 and 0.056, respectively. Subsequently, the ability of multispectral imaging technology to classify fruit based on ripeness stage was tested using SVM and principal component analysis-back propagation neural network (PCA-BPNN) models. The higher classification accuracy of 100% was achieved using SVM model. Moreover, the results of all these models demonstrated that the VIS parts of the spectra were the main contributor to the determination of firmness, TSS content estimation and classification of ripeness stage in strawberry fruit. These results suggest that multispectral imaging, together with suitable analysis model, is a promising technology for rapid estimation of quality attributes and classification of ripeness stage in strawberry fruit. PMID:24505317

Analysis of the origin of predictability in human communications

NASA Astrophysics Data System (ADS)

Zhang, Lin; Liu, Yani; Wu, Ye; Xiao, Jinghua

2014-01-01

Human behaviors in daily life can be traced by their communications via electronic devices. E-mails, short messages and cell-phone calls can be used to investigate the predictability of communication partners’ patterns, because these three are the most representative and common behaviors in daily communications. In this paper, we show that all the three manners have apparent predictability in partners’ patterns, and moreover, the short message users’ sequences have the highest predictability among the three. We also reveal that people with fewer communication partners have higher predictability. Finally, we investigate the origin of predictability, which comes from two aspects: one is the intrinsic pattern in the partners sequence, that is, people have the preference of communicating with a fixed partner after another fixed one. The other aspect is the burst, which is communicating with the same partner several times in a row. The high burst in short message communication pattern is one of the main reasons for its high predictability, the intrinsic pattern in e-mail partners sequence is the main reason for its predictability, and the predictability of cell-phone call partners sequence comes from both aspects.

Predicting turns in proteins with a unified model.

PubMed

Song, Qi; Li, Tonghua; Cong, Peisheng; Sun, Jiangming; Li, Dapeng; Tang, Shengnan

2012-01-01

Turns are a critical element of the structure of a protein; turns play a crucial role in loops, folds, and interactions. Current prediction methods are well developed for the prediction of individual turn types, including α-turn, β-turn, and γ-turn, etc. However, for further protein structure and function prediction it is necessary to develop a uniform model that can accurately predict all types of turns simultaneously. In this study, we present a novel approach, TurnP, which offers the ability to investigate all the turns in a protein based on a unified model. The main characteristics of TurnP are: (i) using newly exploited features of structural evolution information (secondary structure and shape string of protein) based on structure homologies, (ii) considering all types of turns in a unified model, and (iii) practical capability of accurate prediction of all turns simultaneously for a query. TurnP utilizes predicted secondary structures and predicted shape strings, both of which have greater accuracy, based on innovative technologies which were both developed by our group. Then, sequence and structural evolution features, which are profile of sequence, profile of secondary structures and profile of shape strings are generated by sequence and structure alignment. When TurnP was validated on a non-redundant dataset (4,107 entries) by five-fold cross-validation, we achieved an accuracy of 88.8% and a sensitivity of 71.8%, which exceeded the most state-of-the-art predictors of certain type of turn. Newly determined sequences, the EVA and CASP9 datasets were used as independent tests and the results we achieved were outstanding for turn predictions and confirmed the good performance of TurnP for practical applications.

Predicting Turns in Proteins with a Unified Model

PubMed Central

Song, Qi; Li, Tonghua; Cong, Peisheng; Sun, Jiangming; Li, Dapeng; Tang, Shengnan

2012-01-01

Motivation Turns are a critical element of the structure of a protein; turns play a crucial role in loops, folds, and interactions. Current prediction methods are well developed for the prediction of individual turn types, including α-turn, β-turn, and γ-turn, etc. However, for further protein structure and function prediction it is necessary to develop a uniform model that can accurately predict all types of turns simultaneously. Results In this study, we present a novel approach, TurnP, which offers the ability to investigate all the turns in a protein based on a unified model. The main characteristics of TurnP are: (i) using newly exploited features of structural evolution information (secondary structure and shape string of protein) based on structure homologies, (ii) considering all types of turns in a unified model, and (iii) practical capability of accurate prediction of all turns simultaneously for a query. TurnP utilizes predicted secondary structures and predicted shape strings, both of which have greater accuracy, based on innovative technologies which were both developed by our group. Then, sequence and structural evolution features, which are profile of sequence, profile of secondary structures and profile of shape strings are generated by sequence and structure alignment. When TurnP was validated on a non-redundant dataset (4,107 entries) by five-fold cross-validation, we achieved an accuracy of 88.8% and a sensitivity of 71.8%, which exceeded the most state-of-the-art predictors of certain type of turn. Newly determined sequences, the EVA and CASP9 datasets were used as independent tests and the results we achieved were outstanding for turn predictions and confirmed the good performance of TurnP for practical applications. PMID:23144872

Mapping the EORTC QLQ-C30 onto the EQ-5D-3L: assessing the external validity of existing mapping algorithms.

PubMed

Doble, Brett; Lorgelly, Paula

2016-04-01

To determine the external validity of existing mapping algorithms for predicting EQ-5D-3L utility values from EORTC QLQ-C30 responses and to establish their generalizability in different types of cancer. A main analysis (pooled) sample of 3560 observations (1727 patients) and two disease severity patient samples (496 and 93 patients) with repeated observations over time from Cancer 2015 were used to validate the existing algorithms. Errors were calculated between observed and predicted EQ-5D-3L utility values using a single pooled sample and ten pooled tumour type-specific samples. Predictive accuracy was assessed using mean absolute error (MAE) and standardized root-mean-squared error (RMSE). The association between observed and predicted EQ-5D utility values and other covariates across the distribution was tested using quantile regression. Quality-adjusted life years (QALYs) were calculated using observed and predicted values to test responsiveness. Ten 'preferred' mapping algorithms were identified. Two algorithms estimated via response mapping and ordinary least-squares regression using dummy variables performed well on number of validation criteria, including accurate prediction of the best and worst QLQ-C30 health states, predicted values within the EQ-5D tariff range, relatively small MAEs and RMSEs, and minimal differences between estimated QALYs. Comparison of predictive accuracy across ten tumour type-specific samples highlighted that algorithms are relatively insensitive to grouping by tumour type and affected more by differences in disease severity. Two of the 'preferred' mapping algorithms suggest more accurate predictions, but limitations exist. We recommend extensive scenario analyses if mapped utilities are used in cost-utility analyses.

[The new preschool examination in Baden-Wuerttemberg: what determinants influence the school medical evaluation special need for language promotion in childhood development?].

PubMed

Spannenkrebs, M; Crispin, A; Krämer, D

2013-12-01

The new examination before primary school enrollment in Baden-Wuerttemberg aims at detecting problems in infant development with regard to later school success in time to initiate supporting measures, especially to improve the language skills of children with other native languages. By a 2-level process composed of a screening of language skills (HASE and KVS) and an additional test (SETK 3-5) of children who did not pass the screening, the school physicians attested special needs for language promotion in the kindergarten. This study looked for associated risks of children with special needs for language promotion. The degree of test quality of the 2-level process for identifying special needs for language promotion was determined. This cross-sectional analysis explored findings of n=80,781 children in the new examination before primary school enrollment of the data-set of Baden-Wuerttemberg (children with school enrollment 2011). 56,352 children (69.8%) were speaking German, 24,429 children (30.2%) had other family languages. 20,461 children (25.3%) had special needs for language promotion in the kindergarten. A logistic regression model to determine main risks of special needs for language promotion was developed. Main effects were other native languages (OR 5.1 [4.8; 5.2]), problems in subitising (OR 2.8 [2.7; 3.0]) and language development lags in the questionnaire of the nursery school teachers (OR 3.5 [3.3; 3.7]). Protective effects were an elevated graduation of the mother (OR 0.7 [0.7; 0.7]) or the father (OR 0.8 [0.7; 0.8]). Risk scores of the effects were defined. The corresponding predictive probability to different levels of risk scores was calculated. The true positive rate of the screening of language skills (HASE/KVS) in regard to special needs for language promotion was 0.95, the true negative rate was 0.72 and the -positive predictive value was 0.53. The school physician's findings of special needs for language promotion acted as gold standard. With the additional test (SETK 3-5) the positive predictive value improved to 0.9, if at least one of the subtests of the SETK 3-5 was not passed. The risk score-level corresponded with the pretest-probability and the consecutive positive predictive value of the screening of language skills. This study showed an adequate degree of test quality of the 2-level process in the new examination before primary school enrollment in Baden-Wuerttemberg (screening of language skills and additional test, if the screening is not passed). In addition children with special needs for language promotion had associated risks. Risk scores, that have been defined, offer an information tool to the school physicians concerning the positive predictive value of the screening of language skills without additional testing. © Georg Thieme Verlag KG Stuttgart · New York.

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

PubMed

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

2015-09-01

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

Bioenergetic and pharmacokinetic model for exposure of common loon (Gavia immer) chicks to methylmercury

USGS Publications Warehouse

Karasov, W.H.; Kenow, K.P.; Meyer, M.W.; Fournier, F.

2007-01-01

A bioenergetics model was used to predict food intake of common loon (Gavia immer) chicks as a function of body mass during development, and a pharmacokinetics model, based on first-order kinetics in a single compartment, was used to predict blood Hg level as a function of food intake rate, food Hg content, body mass, and Hg absorption and elimination. Predictions were tested in captive growing chicks fed trout (Salmo gairdneri) with average MeHg concentrations of 0.02 (control), 0.4, and 1.2 ??g/g wet mass (delivered as CH3HgCl). Predicted food intake matched observed intake through 50 d of age but then exceeded observed intake by an amount that grew progressively larger with age, reaching a significant overestimate of 28% by the end of the trial. Respiration in older, nongrowing birds probably was overestimated by using rates measured in younger, growing birds. Close agreement was found between simulations and measured blood Hg, which varied significantly with dietary Hg and age. Although chicks may hatch with different blood Hg levels, their blood level is determined mainly by dietary Hg level beyond approximately two weeks of age. The model also may be useful for predicting Hg levels in adults and in the eggs that they lay, but its accuracy in both chicks and adults needs to be tested in free-living birds. ?? 2007 SETAC.

The prediction of resting energy expenditure in type 2 diabetes mellitus is improved by factoring for glycemia.

PubMed

Gougeon, R; Lamarche, M; Yale, J-F; Venuta, T

2002-12-01

Predictive equations have been reported to overestimate resting energy expenditure (REE) for obese persons. The presence of hyperglycemia results in elevated REE in obese persons with type 2 diabetes, and its effect on the validity of these equations is unknown. We tested whether (1) indicators of diabetes control were independent associates of REE in type 2 diabetes and (2) their inclusion would improve predictive equations. A cross-sectional study of 65 (25 men, 40 women) obese type 2 diabetic subjects. Variables measured were: REE by ventilated-hood indirect calorimetry, body composition by bioimpedance analysis, body circumferences, fasting plasma glucose (FPG) and hemoglobin A(1c). Data were analyzed using stepwise multiple linear regression. REE, corrected for weight, fat-free mass, age and gender, was significantly greater with FPG>10 mmol/l (P=0.017) and correlated with FPG (P=0.013) and hemoglobin A(1c) as percentage upper limit of normal (P=0.02). Weight was the main determinant of REE. Together with hip circumference and FPG, it explained 81% of the variation. FPG improved the predictability of the equation by >3%. With poor glycemic control, it can represent an increase in REE of up to 8%. Our data indicate that in a population of obese subjects with type 2 diabetes mellitus, REE is better predicted when fasting plasma glucose is included as a variable.

Development of GP and GEP models to estimate an environmental issue induced by blasting operation.

PubMed

Faradonbeh, Roohollah Shirani; Hasanipanah, Mahdi; Amnieh, Hassan Bakhshandeh; Armaghani, Danial Jahed; Monjezi, Masoud

2018-05-21

Air overpressure (AOp) is one of the most adverse effects induced by blasting in the surface mines and civil projects. So, proper evaluation and estimation of the AOp is important for minimizing the environmental problems resulting from blasting. The main aim of this study is to estimate AOp produced by blasting operation in Miduk copper mine, Iran, developing two artificial intelligence models, i.e., genetic programming (GP) and gene expression programming (GEP). Then, the accuracy of the GP and GEP models has been compared to multiple linear regression (MLR) and three empirical models. For this purpose, 92 blasting events were investigated, and subsequently, the AOp values were carefully measured. Moreover, in each operation, the values of maximum charge per delay and distance from blast points, as two effective parameters on the AOp, were measured. After predicting by the predictive models, their performance prediction was checked in terms of variance account for (VAF), coefficient of determination (CoD), and root mean square error (RMSE). Finally, it was found that the GEP with VAF of 94.12%, CoD of 0.941, and RMSE of 0.06 is a more precise model than other predictive models for the AOp prediction in the Miduk copper mine, and it can be introduced as a new powerful tool for estimating the AOp resulting from blasting.

Discussion of New Approaches to Medium-Short-Term Earthquake Forecast in Practice of The Earthquake Prediction in Yunnan

NASA Astrophysics Data System (ADS)

Hong, F.

2017-12-01

After retrospection of years of practice of the earthquake prediction in Yunnan area, it is widely considered that the fixed-point earthquake precursory anomalies mainly reflect the field information. The increase of amplitude and number of precursory anomalies could help to determine the original time of earthquakes, however it is difficult to obtain the spatial relevance between earthquakes and precursory anomalies, thus we can hardly predict the spatial locations of earthquakes using precursory anomalies. The past practices have shown that the seismic activities are superior to the precursory anomalies in predicting earthquakes locations, resulting from the increased seismicity were observed before 80% M=6.0 earthquakes in Yunnan area. While the mobile geomagnetic anomalies are turned out to be helpful in predicting earthquakes locations in recent year, for instance, the forecasted earthquakes occurring time and area derived form the 1-year-scale geomagnetic anomalies before the M6.5 Ludian earthquake in 2014 are shorter and smaller than which derived from the seismicity enhancement region. According to the past works, the author believes that the medium-short-term earthquake forecast level, as well as objective understanding of the seismogenic mechanisms, could be substantially improved by the densely laying observation array and capturing the dynamic process of physical property changes in the enhancement region of medium to small earthquakes.

Full-scale wind-tunnel test of the aeroelastic stability of a bearingless main rotor

NASA Technical Reports Server (NTRS)

Warmbrodt, W.; Mccloud, J., III; Sheffler, M.; Staley, J.

1981-01-01

The rotor studied in the wind tunnel had previously been flight tested on a BO-105 helicopter. The investigation was conducted to determine the rotor's aeroelastic stability characteristics in hover and at airspeeds up to 143 knots. These characteristics are compared with those obtained from whirl-tower and flight tests and predictions from a digital computer simulation. It was found that the rotor was stable for all conditions tested. At constant tip speed, shaft angle, and airspeed, stability increases with blade collective pitch setting. No significant change in system damping occurred that was attributable to frequency coalescence between the rotor inplane regressing mode and the support modes. Stability levels determined in the wind tunnel were of the same magnitude and yielded the same trends as data obtained from whirl-tower and flight tests.

Determination of NMR chemical shifts for cholesterol crystals from first-principles

NASA Astrophysics Data System (ADS)

Kucukbenli, Emine; de Gironcoli, Stefano

2011-03-01

Solid State Nuclear Magnetic Resonance (NMR) is a powerful tool in crystallography when combined with theoretical predictions. So far, empirical calculations of spectra have been employed for an unambiguous identification. However, many complex systems are outside the scope of these methods. Our implementation of ultrasoft and projector augmented wave pseudopotentials within ab initio gauge including projector augmented plane wave (GIPAW) method in Quantum Espresso simulation package allows affordable calculations of NMR spectra for systems of thousands of electrons. We report here the first ab initio determination of NMR spectra for several crystal structures of cholesterol. Cholesterol crystals, the main component of human gallstones, are of interest to medical research as their structural properties can shed light on the pathologies of gallbladder. With our application we show that ab initio calculations can be employed to aid NMR crystallography.

Performance evaluation of Space Shuttle SRB parachutes from air drop and scaled model wind tunnel tests. [Solid Rocket Booster recovery system

NASA Technical Reports Server (NTRS)

Moog, R. D.; Bacchus, D. L.; Utreja, L. R.

1979-01-01

The aerodynamic performance characteristics have been determined for the Space Shuttle Solid Rocket Booster drogue, main, and pilot parachutes. The performance evaluation on the 20-degree conical ribbon parachutes is based primarily on air drop tests of full scale prototype parachutes. In addition, parametric wind tunnel tests were performed and used in parachute configuration development and preliminary performance assessments. The wind tunnel test data are compared to the drop test results and both sets of data are used to determine the predicted performance of the Solid Rocket Booster flight parachutes. Data from other drop tests of large ribbon parachutes are also compared with the Solid Rocket Booster parachute performance characteristics. Parameters assessed include full open terminal drag coefficients, reefed drag area, opening characteristics, clustering effects, and forebody interference.

Prediction of human dietary δ15N intake from standardised food records: validity and precision of single meal and 24-h diet data.

PubMed

Hülsemann, Frank; Koehler, Karsten; Wittsiepe, Jürgen; Wilhelm, Michael; Hilbig, Annett; Kersting, Mathilde; Braun, Hans; Flenker, Ulrich; Schänzer, Wilhelm

2017-08-01

Natural stable isotope ratios (δ 15 N) of humans can be used for nutritional analyses and dietary reconstruction of modern and historic individuals and populations. Information about an individual's metabolic state can be obtained by comparison of tissue and dietary δ 15 N. Different methods have been used to estimate dietary δ 15 N in the past; however, the validity of such predictions has not been compared to experimental values. For a total of 56 meals and 21 samples of 24-h diets, predicted and experimental δ 15 N values were compared. The δ 15 N values were predicted from self-recorded food intake and compared with experimental δ 15 N values. Predicted and experimental δ 15 N values were in good agreement for meals and preparations (r = 0.89, p < .001) as well as for the 24-h diets (r = 0.76, p < .001). Dietary δ 15 N was mainly determined by the amount of fish, whereas the contribution of meat to dietary δ 15 N values was less pronounced. Prediction of human dietary δ 15 N values using standardised food records and representative δ 15 N data sets yields reliable data for dietary δ 15 N intake. A differentiated analysis of the primary protein sources is necessary when relating the proportion of animal-derived protein in the diet by δ 15 N analysis.

Mechanistic modeling to predict the transporter- and enzyme-mediated drug-drug interactions of repaglinide.

PubMed

Varma, Manthena V S; Lai, Yurong; Kimoto, Emi; Goosen, Theunis C; El-Kattan, Ayman F; Kumar, Vikas

2013-04-01

Quantitative prediction of complex drug-drug interactions (DDIs) is challenging. Repaglinide is mainly metabolized by cytochrome-P-450 (CYP)2C8 and CYP3A4, and is also a substrate of organic anion transporting polypeptide (OATP)1B1. The purpose is to develop a physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics and DDIs of repaglinide. In vitro hepatic transport of repaglinide, gemfibrozil and gemfibrozil 1-O-β-glucuronide was characterized using sandwich-culture human hepatocytes. A PBPK model, implemented in Simcyp (Sheffield, UK), was developed utilizing in vitro transport and metabolic clearance data. In vitro studies suggested significant active hepatic uptake of repaglinide. Mechanistic model adequately described repaglinide pharmacokinetics, and successfully predicted DDIs with several OATP1B1 and CYP3A4 inhibitors (<10% error). Furthermore, repaglinide-gemfibrozil interaction at therapeutic dose was closely predicted using in vitro fraction metabolism for CYP2C8 (0.71), when primarily considering reversible inhibition of OATP1B1 and mechanism-based inactivation of CYP2C8 by gemfibrozil and gemfibrozil 1-O-β-glucuronide. This study demonstrated that hepatic uptake is rate-determining in the systemic clearance of repaglinide. The model quantitatively predicted several repaglinide DDIs, including the complex interactions with gemfibrozil. Both OATP1B1 and CYP2C8 inhibition contribute significantly to repaglinide-gemfibrozil interaction, and need to be considered for quantitative rationalization of DDIs with either drug.

New Approach For Prediction Groundwater Depletion

NASA Astrophysics Data System (ADS)

Moustafa, Mahmoud

2017-01-01

Current approaches to quantify groundwater depletion involve water balance and satellite gravity. However, the water balance technique includes uncertain estimation of parameters such as evapotranspiration and runoff. The satellite method consumes time and effort. The work reported in this paper proposes using failure theory in a novel way to predict groundwater saturated thickness depletion. An important issue in the failure theory proposed is to determine the failure point (depletion case). The proposed technique uses depth of water as the net result of recharge/discharge processes in the aquifer to calculate remaining saturated thickness resulting from the applied pumping rates in an area to evaluate the groundwater depletion. Two parameters, the Weibull function and Bayes analysis were used to model and analyze collected data from 1962 to 2009. The proposed methodology was tested in a nonrenewable aquifer, with no recharge. Consequently, the continuous decline in water depth has been the main criterion used to estimate the depletion. The value of the proposed approach is to predict the probable effect of the current applied pumping rates on the saturated thickness based on the remaining saturated thickness data. The limitation of the suggested approach is that it assumes the applied management practices are constant during the prediction period. The study predicted that after 300 years there would be an 80% probability of the saturated aquifer which would be expected to be depleted. Lifetime or failure theory can give a simple alternative way to predict the remaining saturated thickness depletion with no time-consuming processes such as the sophisticated software required.

Predictive power of theoretical modelling of the nuclear mean field: examples of improving predictive capacities

NASA Astrophysics Data System (ADS)

Dedes, I.; Dudek, J.

2018-03-01

We examine the effects of the parametric correlations on the predictive capacities of the theoretical modelling keeping in mind the nuclear structure applications. The main purpose of this work is to illustrate the method of establishing the presence and determining the form of parametric correlations within a model as well as an algorithm of elimination by substitution (see text) of parametric correlations. We examine the effects of the elimination of the parametric correlations on the stabilisation of the model predictions further and further away from the fitting zone. It follows that the choice of the physics case and the selection of the associated model are of secondary importance in this case. Under these circumstances we give priority to the relative simplicity of the underlying mathematical algorithm, provided the model is realistic. Following such criteria, we focus specifically on an important but relatively simple case of doubly magic spherical nuclei. To profit from the algorithmic simplicity we chose working with the phenomenological spherically symmetric Woods–Saxon mean-field. We employ two variants of the underlying Hamiltonian, the traditional one involving both the central and the spin orbit potential in the Woods–Saxon form and the more advanced version with the self-consistent density-dependent spin–orbit interaction. We compare the effects of eliminating of various types of correlations and discuss the improvement of the quality of predictions (‘predictive power’) under realistic parameter adjustment conditions.

Association of insulin resistance with cerebral glucose uptake in late middle-aged adults at risk for Alzheimer’s disease

PubMed Central

Willette, Auriel A.; Bendlin, Barbara B.; Starks, Erika J.; Birdsill, Alex C.; Johnson, Sterling C.; Christian, Bradley T.; Okonkwo, Ozioma C.; La Rue, Asenath; Hermann, Bruce P.; Koscik, Rebecca L.; Jonaitis, Erin M.; Sager, Mark A.; Asthana, Sanjay

2015-01-01

Importance Converging evidence suggests that Alzheimer’s disease (AD) involves insulin signaling impairment. AD patients and people at risk for AD show reduced glucose metabolism, as indexed by F18-fluorodeoxyglucose positron emission tomography ([F18]FDG-PET). Objective To determine if insulin resistance (IR) predicts AD-like global and regional glucose metabolism deficits in late middle-aged participants at risk for AD. A secondary objective was to examine if IR-predicted variation in regional glucose metabolism was associated with worse cognitive performance. Setting A general community sample enriched for AD family history. Participants Population-based, cross-sectional study of 150 cognitively normal, late middle-aged (mean=60.67 years) adults from the Wisconsin Registry for Alzheimer’s Prevention. Design Participants underwent cognitive testing, fasting blood draw, and an [F18]FDG-PET scan at baseline. The Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) was used to assess peripheral insulin resistance. Regression analysis tested the statistical effect of HOMA-IR on global glucose metabolism. A voxel-wise analysis was used to determine if HOMA-IR predicted regional glucose metabolism. Finally, predicted variation in regional glucose metabolism was regressed against cognitive factors. Covariates included age, sex, body mass index, Apolipoprotein E genotype, AD family history status, and a reference region used to normalize regional uptake. Main Outcome Measures Regional glucose uptake determined using [F18]FDG-PET, and neuropsychological factors. Results Higher HOMA-IR was associated with lower global glucose metabolism (β=−0.29, p<.01) and lower regional glucose metabolism across large portions of frontal, lateral parietal, lateral temporal, and medial temporal lobe (MTL; p<.05, family-wise error corrected). The association was especially robust in left MTL (R2=0.178). Lower left MTL glucose metabolism predicted by HOMA-IR was significantly related to worse immediate memory (β=0.317, p<.001) and delayed memory (β=0.305, p<.001) performance. Conclusions Our results show that IR, a prevalent and increasingly common condition in developed countries, is associated with significantly lower regional cerebral glucose metabolism, which in turn may predict worse memory performance. Midlife may be a critical period for initiating treatments to lower peripheral IR in order to maintain neural metabolism and cognitive function. PMID:26214150

Dependence of the aftershock flow on the main shock magnitude

NASA Astrophysics Data System (ADS)

Guglielmi, A. V.; Zavyalov, A. D.; Zotov, O. D.; Lavrov, I. P.

2017-01-01

Previously, we predicted and then observed in practice the property of aftershocks which consists in the statistically regular clustering of events in time during the first hours after the main shock. The characteristic quasi-period of clustering is three hours. This property is associated with the cumulative action of the surface waves converging to the epicenter, whereas the quasi-period is mainly determined by the time delay of the round-the-world seismic echo. The quasi-period varies from case to case. In the attempt to find the cause of this variability, we have statistically explored the probable dependence of quasi-period on the magnitude of the main shock. In this paper, we present the corresponding result of analyzing global seismicity from the USGS/NEIC earthquake catalog. We succeeded in finding a significant reduction in the quasiperiod of the strong earthquakes clustering with growth in the magnitude of the main shock. We suggest the interpretation of this regularity from the standpoint of the phenomenological theory of explosive instability. It is noted that the phenomenon of explosive instability is fairly common in the geophysical media. The examples of explosive instability in the radiation belt and magnetospheric tail are presented. The search for the parallels in the evolution of explosive instability in the lithosphere and magnetosphere of the Earth will enrich both the physics of the earthquakes and physics of the magnetospheric pulsations.

Predictability of the Indian Ocean Dipole in the coupled models

NASA Astrophysics Data System (ADS)

Liu, Huafeng; Tang, Youmin; Chen, Dake; Lian, Tao

2017-03-01

In this study, the Indian Ocean Dipole (IOD) predictability, measured by the Indian Dipole Mode Index (DMI), is comprehensively examined at the seasonal time scale, including its actual prediction skill and potential predictability, using the ENSEMBLES multiple model ensembles and the recently developed information-based theoretical framework of predictability. It was found that all model predictions have useful skill, which is normally defined by the anomaly correlation coefficient larger than 0.5, only at around 2-3 month leads. This is mainly because there are more false alarms in predictions as leading time increases. The DMI predictability has significant seasonal variation, and the predictions whose target seasons are boreal summer (JJA) and autumn (SON) are more reliable than that for other seasons. All of models fail to predict the IOD onset before May and suffer from the winter (DJF) predictability barrier. The potential predictability study indicates that, with the model development and initialization improvement, the prediction of IOD onset is likely to be improved but the winter barrier cannot be overcome. The IOD predictability also has decadal variation, with a high skill during the 1960s and the early 1990s, and a low skill during the early 1970s and early 1980s, which is very consistent with the potential predictability. The main factors controlling the IOD predictability, including its seasonal and decadal variations, are also analyzed in this study.

Investigating Clinically and Scientifically Useful Cut Points on the Compulsive Sexual Behavior Inventory

PubMed Central

Miner, Michael H.; Raymond, Nancy; Coleman, Eli; Romine, Rebecca Swinburne

2017-01-01

Introduction One of the major obstacles to conducting epidemiological research and determining the incidence and prevalence of compulsive sexual behavior has been the lack of relevant, empirically derived cut points on the various instruments that have been used to measure the concept. Aim To further develop the Compulsive Sexual Behavior Inventory (CSBI) through exploring predictive validity and developing an empirically determined and clinically useful cut point for defining CSB. Methods A sample of 242 men who have sex with men was recruited from various sites in a moderate-size Midwestern city. Participants were assigned to a CSB group or a control group using an interview for the diagnosis that was patterned after the Structured Clinical Interview for the Diagnostic and Statistical Manual for Mental Disorders, Fourth Edition. The 22-item CSBI was administered as part of a larger battery of self-report inventories. Main Outcome Measures ROC analyses were used to compute AUC measures to ascertain predictive validity of the total scale, the control subscale and the violence subscale. Cut-points were determined through consensus of experts balancing sensitivity and specificity as determined by ROC curves. Results Analyses indicated that the 22-item CSBI was a good predictor of group membership, as was the 13-item control subscale. The Violence subscale added little to the predictive accuracy of the instrument and thus, it likely measures something other than CSB. Two relevant cut points were found, one that minimized false negatives and another, more conservative cut-point that minimized false positives. Conclusion The CSBI as currently configured measures two different constructions and only the Control subscale is helpful in diagnosing CSB. We have, therefore, decided to eliminate the Violence subscale and move forward with a 13-item scale that we have named the CSBI-13. Two cut points were developed from this revised scale, one which is useful as a clinical screening and the other, more conservative measure useful for etiological and epidemiological research. PMID:28499521

A Subjective Test of Modulated Blade Spacing for Helicopter Main Rotors

NASA Technical Reports Server (NTRS)

Sullivan, Brenda M.; Edwards, Bryan D.; Brentner, Kenneth S.; Booth, Earl R., Jr.

2002-01-01

Analytically, uneven (modulated) spacing of main rotor blades was found to reduce helicopter noise. A study was performed to see if these reductions transferred to improvements in subjective response. Using a predictive computer code, sounds produced by six main rotor configurations: 4 blades evenly spaced, 5 blades evenly spaced and four configurations with 5 blades with modulated spacing of varying amounts, were predicted. These predictions were converted to audible sounds corresponding to the level flyover, takeoff and approach flight conditions. Subjects who heard the simulations were asked to assess the overflight sounds in terms of noisiness on a scale of 0 to 10. In general the evenly spaced configurations were found less noisy than the modulated spacings, possibly because the uneven spacings produced a perceptible pulsating sound due to the very low fundamental frequency.

Direct CFD Predictions of Low Frequency Sounds Generated by a Helicopter Main Rotor

NASA Technical Reports Server (NTRS)

Sim, Ben W.; Potsdam, Mark A.; Conner, Dave A.; Conner, Dave A.; Watts, Michael E.

2010-01-01

The use of CFD to directly predict helicopter main rotor noise is shown to be quite promising as an alternative mean for low frequency source noise evaluation. Results using existing state-of-the-art grid structures and finite-difference schemes demonstrated that small perturbation pressures, associated with acoustics radiation, can be extracted with some degree of fidelity. Accuracy of the predictions are demonstrated via comparing to predictions from conventional acoustic analogy-based models, and with measurements obtained from wind tunnel and flight tests for the MD-902 helicopter at several operating conditions. Findings show that the direct CFD approach is quite successfully in yielding low frequency results due to thickness and steady loading noise mechanisms. Mid-to-high frequency contents, due to blade-vortex interactions, are not predicted due to CFD modeling and grid constraints.

Decision making for pancreatic resection in patients with intraductal papillary mucinous neoplasms.

PubMed

Xu, Bin; Ding, Wei-Xing; Jin, Da-Yong; Wang, Dan-Song; Lou, Wen-Hui

2013-03-07

To identify a practical approach for preoperative decision-making in patients with intraductal papillary mucinous neoplasms (IPMNs) of the pancreas. Between March 1999 and November 2006, the clinical characteristics, pathological data and computed tomography/magnetic resonance imaging (CT/MRI) of 54 IPMNs cases were retrieved and analyzed. The relationships between the above data and decision-making for pancreatic resection were analyzed using SPSS 13.0 software. Univariate analysis of risk factors for malignant or invasive IPMNs was performed with regard to the following variables: carcinoembryonic antigen, carbohydrate antigen 19-9 (CA19-9) and the characteristics from CT/MRI images. Receiver operating characteristic (ROC) curve analysis for pancreatic resection was performed using significant factors from the univariate analysis. CT/MRI images, including main and mixed duct IPMNs, tumor size > 30 mm or a solid component appearance in the lesion, and preoperative serum CA19-9 > 37 U/mL had good predictive value for determining pancreatic resection (P < 0.05), but with limitations. Combining the above factors (CT/MRI images and CA19-9) improved the accuracy and sensitivity for determining pancreatic resection in IPMNs. Using ROC analysis, the area under the curve reached 0.893 (P < 0.01, 95%CI: 0.763-1.023), with a sensitivity, specificity, positive predictive value and negative predictive value of 95.2%, 83.3%, 95.2% and 83.3%, respectively. Combining preoperative CT/MRI images and CA19-9 level may provide useful information for surgical decision-making in IPMNs.

Executive function moderates the role of muscular fitness in determining functional mobility in older adults.

PubMed

Forte, Roberta; Pesce, Caterina; Leite, Joao Costa; De Vito, Giuseppe; Gibney, Eileen R; Tomporowski, Phillip D; Boreham, Colin A G

2013-06-01

Both physical and cognitive factors are known to independently predict functional mobility in older people. However, the combined predictive value of both physical fitness and cognitive factors on functional mobility has been less investigated. The aim of the present study was to assess if cognitive executive functions moderate the role of physical fitness in determining functional mobility of older individuals. Fifty-seven 65- to 75-year-old healthy participants performed tests of functional mobility (habitual and maximal walking speed, maximal walking speed while picking up objects/stepping over obstacles), physical fitness (peak power, knee extensors torque, back/lower limb flexibility, aerobic fitness), and executive function (inhibition and cognitive flexibility). Maximal walking speeds were predicted by physical fitness parameters and their interaction with cognitive factors. Knee extensor torque emerged as the main predictor of all tested locomotor performances at maximal speed. The effect of peak power and back/lower limb flexibility was moderated by executive functions. In particular, inhibition and cognitive flexibility differed in the way in which they moderate the role of fitness. High levels of cognitive flexibility seem necessary to take advantage of leg power for walking at maximal speed. In contrast, high levels of inhibitory capacity seem to compensate for low levels of back/lower limb flexibility when picking up movements are added to a locomotor task. These findings may have important practical implications for the design and implementation of multi-component training programs aimed at optimizing functional abilities in older adults.

Prediction of unsaturated flow and water backfill during infiltration in layered soils

NASA Astrophysics Data System (ADS)

Cui, Guotao; Zhu, Jianting

2018-02-01

We develop a new analytical infiltration model to determine water flow dynamics around layer interfaces during infiltration process in layered soils. The model mainly involves the analytical solutions to quadratic equations to determine the flux rates around the interfaces. Active water content profile behind the wetting front is developed based on the solution of steady state flow to dynamically update active parameters in sharp wetting front infiltration equations and to predict unsaturated flow in coarse layers before the front reaches an impeding fine layer. The effect of water backfill to saturate the coarse layers after the wetting front encounters the impeding fine layer is analytically expressed based on the active water content profiles. Comparison to the numerical solutions of the Richards equation shows that the new model can well capture water dynamics in relation to the arrangement of soil layers. The steady state active water content profile can be used to predict the saturation state of all layers when the wetting front first passes through these layers during the unsteady infiltration process. Water backfill effect may occur when the unsaturated wetting front encounters a fine layer underlying a coarse layer. Sensitivity analysis shows that saturated hydraulic conductivity is the parameter dictating the occurrence of unsaturated flow and water backfill and can be used to represent the coarseness of soil layers. Water backfill effect occurs in coarse layers between upper and lower fine layers when the lower layer is not significantly coarser than the upper layer.

Predicting the emissive power of hydrocarbon pool fires.

PubMed

Muñoz, Miguel; Planas, Eulàlia; Ferrero, Fabio; Casal, Joaquim

2007-06-18

The emissive power (E) of a flame depends on the size of the fire and the type of fuel. In fact, it changes significantly over the flame surface: the zones of luminous flame have high emittance, while those covered by smoke have low E values. The emissive power of each zone (that is, the luminous or clear flame and the non-luminous or smoky flame) and the portion of total flame area they occupy must be assessed when a two-zone model is used. In this study, data obtained from an experimental set-up were used to estimate the emissive power of fires and its behaviour as a function of pool size. The experiments were performed using gasoline and diesel oil as fuel. Five concentric circular pools (1.5, 3, 4, 5 and 6m in diameter) were used. Appropriate instruments were employed to determine the main features of the fires. By superimposing IR and VHS images it was possible to accurately identify the luminous and non-luminous zones of the fire. Mathematical expressions were obtained that give a more accurate prediction of E(lum), E(soot) and the average emissive power of a fire as a function of its luminous and smoky zones. These expressions can be used in a two-zone model to obtain a better prediction of the thermal radiation. The value of the radiative fraction was determined from the thermal flux measured with radiometers. An expression is also proposed for estimating the radiative fraction.

OCT-measured plaque free wall angle is indicative for plaque burden: overcoming the main limitation of OCT?

PubMed

Hoogendoorn, Ayla; Gnanadesigan, Muthukaruppan; Zahnd, Guillaume; van Ditzhuijzen, Nienke S; Schuurbiers, Johan C H; van Soest, Gijs; Regar, Evelyn; Wentzel, Jolanda J

2016-10-01

The aim of this study was to investigate the relationship between the plaque free wall (PFW) measured by optical coherence tomography (OCT) and the plaque burden (PB) measured by intravascular ultrasound (IVUS). We hypothesize that measurement of the PFW could help to estimate the PB, thereby overcoming the limited ability of OCT to visualize the external elastic membrane in the presence of plaque. This could enable selection of the optimal stent-landing zone by OCT, which is traditionally defined by IVUS as a region with a PB < 40 %. PB (IVUS) and PFW angle (OCT and IVUS) were measured in 18 matched IVUS and OCT pullbacks acquired in the same coronary artery. We determined the relationship between OCT measured PFW (PFWOCT) and IVUS PB (PBIVUS) by non-linear regression analysis. An ROC-curve analysis was used to determine the optimal cut-off value of PFW angle for the detection of PB < 40 %. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated. There is a significant correlation between PFWOCT and PBIVUS (r(2) = 0.59). The optimal cut-off value of the PFWOCT for the prediction of a PBIVUS < 40 % is ≥220° with a PPV of 78 % and an NPV of 84 %. This study shows that PFWOCT can be considered as a surrogate marker for PBIVUS, which is currently a common criterion to select an optimal stent-landing zone.

Environmental determinants of tropical forest and savanna distribution: A quantitative model evaluation and its implication

NASA Astrophysics Data System (ADS)

Zeng, Zhenzhong; Chen, Anping; Piao, Shilong; Rabin, Sam; Shen, Zehao

2014-07-01

The distributions of tropical ecosystems are rapidly being altered by climate change and anthropogenic activities. One possible trend—the loss of tropical forests and replacement by savannas—could result in significant shifts in ecosystem services and biodiversity loss. However, the influence and the relative importance of environmental factors in regulating the distribution of tropical forest and savanna biomes are still poorly understood, which makes it difficult to predict future tropical forest and savanna distributions in the context of climate change. Here we use boosted regression trees to quantitatively evaluate the importance of environmental predictors—mainly climatic, edaphic, and fire factors—for the tropical forest-savanna distribution at a mesoscale across the tropics (between 15°N and 35°S). Our results demonstrate that climate alone can explain most of the distribution of tropical forest and savanna at the scale considered; dry season average precipitation is the single most important determinant across tropical Asia-Australia, Africa, and South America. Given the strong tendency of increased seasonality and decreased dry season precipitation predicted by global climate models, we estimate that about 28% of what is now tropical forest would likely be lost to savanna by the late 21st century under the future scenario considered. This study highlights the importance of climate seasonality and interannual variability in predicting the distribution of tropical forest and savanna, supporting the climate as the primary driver in the savanna biogeography.

[EVALUATION OF THE BODY ADIPOSITY INDEX IN PREDICTING PERCENTAGE BODY FAT AMONG COLOMBIAN ADULTS].

PubMed

González-Ruíz, Katherine; Correa-Bautista, Jorge Enrique; Ramírez-Vélez, Robinson

2015-07-01

the body adiposity index (BAI) is a new simplistic method for predicting body fat percentage (BF%) via a simple equation of hip circumference to height. Up to now, few studies have evaluated the performance of BAI in determining excess fat in Colombians. The aim of this study was to evaluate the usefulness of BAI as a predictor of body fat in among Colombian adults. cross-sectional study carried out in a sample of 204 male belonging to the education sector from Bogotá, Colombia. BAI was calculated based on the equation reported in the Bergman et al. %BF determined by tetrapolar bioimpedance analysis (BIA) was used as the reference measure of adiposity. Bland-Altman analysis was used to assess the agreement between the two methods: BAI and BIA. Associations between anthropometric measures of adiposity were investigated by Pearson correlation analysis. in general pupulation, the BAI overestimates %BF (mean difference: 12.5 % [95%CI = -4.04 % to -21.02 %]), mainly at lower levels of adiposity (mean difference: 10.2 ± 3.3). Significant correlations were found between BAI and all measurements, being the strongest-moderate correlation with %BF (r = 0.777, p < 0.001), waist to height ratio (r = 0.557, p < 0.001) and BMI (r = 0.480, p < 0.001). the results of this investigation indicate that BAI results in large individual errors when predicting BF% among Colombian adults and has a tendency to provide overestimated values as BF% decreases. Therefore, this method can be a useful tool to predict %BF in Colombian adults, although it has some limitations. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Self-Reported Menopausal Symptoms, Coronary Artery Calcification and Carotid Intima-Media Thickness in Recently Menopausal Women Screened for the Kronos Early Estrogen Prevention Study (KEEPS)

PubMed Central

Wolff, Erin Foran; He, Yunxiao; Black, Dennis M.; Brinton, Eliot A.; Budoff, Mathew J.; Cedars, Marcelle I.; Hodis, Howard N.; Lobo, Rogerio A.; Manson, JoAnn E.; Merriam, George R.; Miller, Virginia M.; Naftolin, Fredrick; Pal, Lubna; Santoro, Nanette; Zhang, Heping; Harman, S. Mitchell; Taylor, Hugh S.

2012-01-01

Objective To determine whether self-reported menopausal symptoms are associated with measures of subclinical atherosclerosis. Setting Multi-center, randomized controlled trial. Patients Recently menopausal women (n=868) screened for the Kronos Early Estrogen Prevention Study (KEEPS). Design Cross sectional analysis. Interventions None Main Outcome Measures Baseline menopausal symptoms (hot flashes, dyspareunia, vaginal dryness, night sweats, palpitations, mood swings, depression, insomnia, irritability), serum estradiol (E2) levels and measures of atherosclerosis were assessed. Atherosclerosis was quantified using Coronary Artery Calcium (CAC) Agatston scores (n=771) and Carotid Intima-Media Thickness (CIMT). Logistic regression model of menopausal symptoms and E2 was used to predict CAC. Linear regression model of menopausal symptoms and E2 was used to predict CIMT. Correlation between length of time in menopause with menopausal symptoms, estradiol (E2), CAC, and CIMT were assessed. Results In early menopausal women screened for KEEPS, neither E2 nor climacteric symptoms predicted the extent of subclinical atherosclerosis. Palpitations (p=0.09) and depression (p=0.07) approached significance as predictors of CAC. Other symptoms of insomnia, irritability, dyspareunia, hot flashes, mood swings, night sweats, and vaginal dryness were not associated with CAC. Women with significantly elevated CAC scores were excluded from further participation in KEEPS; in women meeting inclusion criteria, neither baseline menopausal symptoms nor E2 predicted CIMT. Years since menopause onset correlated with CIMT, dyspareunia, vaginal dryness and E2. Conclusions Self-reported symptoms in recently menopausal women are not strong predictors of subclinical atherosclerosis. Continued follow-up of this population will be performed to determine if baseline or persistent symptoms in the early menopause are associated with progression of cardiovascular disease. PMID:23312232

Can pre-season fitness measures predict time to injury in varsity athletes?: a retrospective case control study

PubMed Central

2012-01-01

Background The ability to determine athletic performance in varsity athletes using preseason measures has been established. The ability of pre-season performance measures and athlete’s exposure to predict the incidence of injuries is unclear. Thus our purpose was to determine the ability of pre-season measures of athletic performance to predict time to injury in varsity athletes. Methods Male and female varsity athletes competing in basketball, volleyball and ice hockey participated in this study. The main outcome measures were injury prevalence, time to injury (based on calculated exposure) and pre-season fitness measures as predictors of time to injury. Fitness measures were Apley’s range of motion, push-up, curl-ups, vertical jump, modified Illinois agility, and sit-and-reach. Cox regression models were used to identify which baseline fitness measures were predictors of time to injury. Results Seventy-six percent of the athletes reported 1 or more injuries. Mean times to initial injury were significantly different for females and males (40.6% and 66.1% of the total season (p < 0.05), respectively). A significant univariate correlation was observed between push-up performance and time to injury (Pearson’s r = 0.332, p < 0.01). No preseason fitness measure impacted the hazard of injury. Regardless of sport, female athletes had significantly shorter time to injury than males (Hazard Ratio = 2.2, p < 0.01). Athletes playing volleyball had significantly shorter time to injury (Hazard Ratio = 4.2, p < 0.01) compared to those playing hockey or basketball. Conclusions When accounting for exposure, gender, sport and fitness measures, prediction of time to injury was influenced most heavily by gender and sport. PMID:22824555

Prediction of clathrate structure type and guest position by molecular mechanics.

PubMed

Fleischer, Everly B; Janda, Kenneth C

2013-05-16

The clathrate hydrates occur in various types in which the number, size, and shape of the various cages differ. Usually the clathrate type of a specific guest is predicted by the size and shape of the molecular guest. We have developed a methodology to determine the clathrate type employing molecular mechanics with the MMFF force field employing a strategy to calculate the energy of formation of the clathrate from the sum of the guest/cage energies. The clathrate type with the most negative (most stable) energy of formation would be the type predicted (we mainly focused on type I, type II, or bromine type). This strategy allows for a calculation to predict the clathrate type for any cage guest in a few minutes on a laptop computer. It proved successful in predicting the clathrate structure for 46 out of 47 guest molecules. The molecular mechanics calculations also provide a prediction of the guest position within the cage and clathrate structure. These predictions are generally consistent with the X-ray and neutron diffraction studies. By supplementing the diffraction study with molecular mechanics, we gain a more detailed insight regarding the details of the structure. We have also compared MM calculations to studies of the multiple occupancy of the cages. Finally, we present a density functional calculation that demonstrates that the inside of the clathrates cages have a relatively uniform and low electrostatic potential in comparison with the outside oxygen and hydrogen atoms. This implies that van der Waals forces will usually be dominant in the guest-cage interactions.

Hazardous Alcohol Drinking as Predictor of Smoking Relapse (3-, 6-, and 12-Months Follow-Up) by Gender.

PubMed

Rodríguez-Cano, Rubén; López-Durán, Ana; Martínez-Vispo, Carmela; Martínez, Úrsula; Fernández Del Río, Elena; Becoña, Elisardo

2016-12-01

Diverse studies have found a relation between alcohol consumption and smoking relapse. Few studies have analyzed the relation of smoking relapse with pretreatment alcohol consumption and gender differences. The main purpose of this study is to analyze the influence of alcohol consumption in smoking relapse over 12 months (3-, 6-, and 12-months follow-up) and to determine possible gender differences. The sample included 374 smokers who quit smoking by participating in a psychological smoking cessation treatment. We assessed hazardous pretreatment alcohol drinking (AUDIT), cigarette consumption (FTND; number of cigarettes) and sociodemographic variables. Higher scores on hazardous pretreatment alcohol drinking predict smoking relapse at 3-, 6-, and 12-months after smoking cessation. In males, higher scores on hazardous pretreatment alcohol drinking predict relapse at 6 and at 12 months. In females, higher scores on hazardous pretreatment alcohol drinking predict tobacco relapse at 3 months. Hazardous pretreatment alcohol drinking predicts relapse at all intervals after smoking cessation (3-, 6-, and 12-months follow-up). However, the influence of hazardous pretreatment alcohol drinking on smoking relapse differs as a function of gender, as it is a short-term predictor in women (3 months) and a long-term predictor in men (6 and 12 months). Copyright © 2016 Elsevier Inc. All rights reserved.

Parent-child mediated learning interactions as determinants of cognitive modifiability: recent research and future directions.

PubMed

Tzuriel, D

1999-05-01

The main objectives of this article are to describe the effects of mediated learning experience (MLE) strategies in mother-child interactions on the child's cognitive modifiability, the effects of distal factors (e.g., socioeconomic status, mother's intelligence, child's personality) on MLE interactions, and the effects of situational variables on MLE processes. Methodological aspects of measurement of MLE interactions and of cognitive modifiability, using a dynamic assessment approach, are discussed. Studies with infants showed that the quality of mother-infant MLE interactions predict later cognitive functioning and that MLE patterns and children's cognitive performance change as a result of intervention programs. Studies with preschool and school-aged children showed that MLE interactions predict cognitive modifiability and that distal factors predict MLE interactions but not the child's cognitive modifiability. The child's cognitive modifiability was predicted by MLE interactions in a structured but not in a free-play situation. Mediation for transcendence (e.g., teaching rules and generalizations) appeared to be the strongest predictor of children's cognitive modifiability. Discussion of future research includes the consideration of a holistic transactional approach, which refers to MLE processes, personality, and motivational-affective factors, the cultural context of mediation, perception of the whole family as a mediational unit, and the "mediational normative scripts."

Inferences of drug responses in cancer cells from cancer genomic features and compound chemical and therapeutic properties

PubMed Central

Wang, Yongcui; Fang, Jianwen; Chen, Shilong

2016-01-01

Accurately predicting the response of a cancer patient to a therapeutic agent is a core goal of precision medicine. Existing approaches were mainly relied primarily on genomic alterations in cancer cells that have been treated with different drugs. Here we focus on predicting drug response based on integration of the heterogeneously pharmacogenomics data from both cell and drug sides. Through a systematical approach, named as PDRCC (Predict Drug Response in Cancer Cells), the cancer genomic alterations and compound chemical and therapeutic properties were incorporated to determine the chemotherapeutic response in cancer patients. Using the Cancer Cell Line Encyclopedia (CCLE) study as the benchmark dataset, all pharmacogenomics data exhibited their roles in inferring the relationships between cancer cells and drugs. When integrating both genomic resources and compound information, the prediction coverage was significantly increased. The validity of PDRCC was also supported by its effective in uncovering the unknown cell-drug associations with database and literature evidences. It set the stage for clinical testing of novel therapeutic strategies, such as the sensitive association between cancer cell ‘A549_LUNG’ and compound ‘Topotecan’. In conclusion, PDRCC offers the possibility for faster, safer, and cheaper the development of novel anti-cancer therapeutics in the early-stage clinical trails. PMID:27645580

Nurses' intention to leave: critically analyse the theory of reasoned action and organizational commitment model.

PubMed

Liou, Shwu-Ru

2009-01-01

To systematically analyse the Organizational Commitment model and Theory of Reasoned Action and determine concepts that can better explain nurses' intention to leave their job. The Organizational Commitment model and Theory of Reasoned Action have been proposed and applied to understand intention to leave and turnover behaviour, which are major contributors to nursing shortage. However, the appropriateness of applying these two models in nursing was not analysed. Three main criteria of a useful model were used for the analysis: consistency in the use of concepts, testability and predictability. Both theories use concepts consistently. Concepts in the Theory of Reasoned Action are defined broadly whereas they are operationally defined in the Organizational Commitment model. Predictability of the Theory of Reasoned Action is questionable whereas the Organizational Commitment model can be applied to predict intention to leave. A model was proposed based on this analysis. Organizational commitment, intention to leave, work experiences, job characteristics and personal characteristics can be concepts for predicting nurses' intention to leave. Nursing managers may consider nurses' personal characteristics and experiences to increase their organizational commitment and enhance their intention to stay. Empirical studies are needed to test and cross-validate the re-synthesized model for nurses' intention to leave their job.

Inferences of drug responses in cancer cells from cancer genomic features and compound chemical and therapeutic properties

NASA Astrophysics Data System (ADS)

Wang, Yongcui; Fang, Jianwen; Chen, Shilong

2016-09-01

Accurately predicting the response of a cancer patient to a therapeutic agent is a core goal of precision medicine. Existing approaches were mainly relied primarily on genomic alterations in cancer cells that have been treated with different drugs. Here we focus on predicting drug response based on integration of the heterogeneously pharmacogenomics data from both cell and drug sides. Through a systematical approach, named as PDRCC (Predict Drug Response in Cancer Cells), the cancer genomic alterations and compound chemical and therapeutic properties were incorporated to determine the chemotherapeutic response in cancer patients. Using the Cancer Cell Line Encyclopedia (CCLE) study as the benchmark dataset, all pharmacogenomics data exhibited their roles in inferring the relationships between cancer cells and drugs. When integrating both genomic resources and compound information, the prediction coverage was significantly increased. The validity of PDRCC was also supported by its effective in uncovering the unknown cell-drug associations with database and literature evidences. It set the stage for clinical testing of novel therapeutic strategies, such as the sensitive association between cancer cell ‘A549_LUNG’ and compound ‘Topotecan’. In conclusion, PDRCC offers the possibility for faster, safer, and cheaper the development of novel anti-cancer therapeutics in the early-stage clinical trails.

Development of Artificial Neural Network Model for Diesel Fuel Properties Prediction using Vibrational Spectroscopy.

PubMed

Bolanča, Tomislav; Marinović, Slavica; Ukić, Sime; Jukić, Ante; Rukavina, Vinko

2012-06-01

This paper describes development of artificial neural network models which can be used to correlate and predict diesel fuel properties from several FTIR-ATR absorbances and Raman intensities as input variables. Multilayer feed forward and radial basis function neural networks have been used to rapid and simultaneous prediction of cetane number, cetane index, density, viscosity, distillation temperatures at 10% (T10), 50% (T50) and 90% (T90) recovery, contents of total aromatics and polycyclic aromatic hydrocarbons of commercial diesel fuels. In this study two-phase training procedures for multilayer feed forward networks were applied. While first phase training algorithm was constantly the back propagation one, two second phase training algorithms were varied and compared, namely: conjugate gradient and quasi Newton. In case of radial basis function network, radial layer was trained using K-means radial assignment algorithm and three different radial spread algorithms: explicit, isotropic and K-nearest neighbour. The number of hidden layer neurons and experimental data points used for the training set have been optimized for both neural networks in order to insure good predictive ability by reducing unnecessary experimental work. This work shows that developed artificial neural network models can determine main properties of diesel fuels simultaneously based on a single and fast IR or Raman measurement.

Things Are Not as Bad as They Seem: Physicians' Ability to Predict Their Clinical Practice When a New Vaccine Becomes Available

PubMed Central

Hurley, Laura; Crane, Lori A.; Dong, Fran; Stokley, Shannon; Daley, Matthew F.; Barrow, Jennifer; Babbel, Christine; Dickinson, L. Miriam; Kempe, Allison

2013-01-01

Survey results regarding primary care physicians' likelihood of recommending a new vaccine were compared before and after the vaccine was licensed by the Food and Drug Administration for three new vaccines: herpes zoster (HZ), human papillomavirus (HPV) and rotavirus (RV), using physician networks representative of United States physicians. The main purpose of this study was to determine (a) how accurately physicians predict their eventual vaccine recommendations and the barriers they will experience in delivering the new vaccine and (b) whether physicians shift towards more or less strongly recommending a new vaccine from pre- to post-licensure. Responses from 284, 152 and 184 physicians were analyzed for the three vaccines, respectively. For all vaccines, there was a significant association between physicians' pre- and post-licensure recommendations (p<0.05). When responses changed from pre- to post-licensure, physicians tended to recommend a given vaccine more strongly than they had anticipated pre-licensure. Before vaccine availability, physicians tended to predict greater barriers to vaccine delivery than they eventually experienced. Surveys are useful for predicting physician practices, but may provide a slightly pessimistic view of physician adoption of new vaccines. Such data can be helpful in devising strategies to encourage vaccine delivery by physicians. PMID:23968639

Inferences of drug responses in cancer cells from cancer genomic features and compound chemical and therapeutic properties.

PubMed

Wang, Yongcui; Fang, Jianwen; Chen, Shilong

2016-09-20

Accurately predicting the response of a cancer patient to a therapeutic agent is a core goal of precision medicine. Existing approaches were mainly relied primarily on genomic alterations in cancer cells that have been treated with different drugs. Here we focus on predicting drug response based on integration of the heterogeneously pharmacogenomics data from both cell and drug sides. Through a systematical approach, named as PDRCC (Predict Drug Response in Cancer Cells), the cancer genomic alterations and compound chemical and therapeutic properties were incorporated to determine the chemotherapeutic response in cancer patients. Using the Cancer Cell Line Encyclopedia (CCLE) study as the benchmark dataset, all pharmacogenomics data exhibited their roles in inferring the relationships between cancer cells and drugs. When integrating both genomic resources and compound information, the prediction coverage was significantly increased. The validity of PDRCC was also supported by its effective in uncovering the unknown cell-drug associations with database and literature evidences. It set the stage for clinical testing of novel therapeutic strategies, such as the sensitive association between cancer cell 'A549_LUNG' and compound 'Topotecan'. In conclusion, PDRCC offers the possibility for faster, safer, and cheaper the development of novel anti-cancer therapeutics in the early-stage clinical trails.

A Study of Impairing Injuries in Real World Crashes Using the Injury Impairment Scale (IIS) and the Predicted Functional Capacity Index (PFCI-AIS)

PubMed Central

Barnes, Jo; Morris, Andrew

2009-01-01

The ability to predict impairment outcomes in large databases using a simplified technique allows researchers to focus attention on preventing costly impairing injuries. The dilemma that exists for researchers is to determine which method is the most reliable and valid. This study examines available methods to predict impairment and explores the differences between the IIS and pFCI applied to real world crash injury data. Occupant injury data from the UK Co-operative Crash Injury Study (CCIS) database have been coded using AIS 1990 and AIS 2005. The data have subsequently been recoded using the associated impairment scales namely the Injury Impairment Scale (IIS) and the predicted Functional Capacity Index (pFCI) to determine the predicted impairment levels of injuries at one year post crash. Comparisons between the levels of impairment were made and any differences further explored. Injury data for the period February 2006 to September 2008 from the CCIS database were used in the analysis which involved a dataset of 2,437 occcupants who sustained over 8000 injuries. This study found some differences between the impairment scales for injuries coded to the AIS 1990 and AIS 2005 coding dictionaries. The pFCI predicts 31.5% of injuries to be impairing in AIS 2005, less than the IIS (38.5%) using AIS 1990. Using CCIS data the pFCI predicted that only 6% of the occupants with a coded injury would have an impairing injury compared to 24% of occupants using the IIS. The main body regions identified as having the major differences between the two impairment scales for car occupants were the head and spine. Follow up data were then used for a small number of cases (n=31, lower extremity and whiplash injuries) to examine any differences in predicted impairment versus perceived impairment. These data were selected from a previous study conducted between 2003 and 2006 and identified the discrepancy between predicted impairment and actual perceived impairment as defined by the participant. Overall the work highlights the variaton between the pFCI and IIS and emphasises the importance and need for a single validated impairment scale that can be universally applied. This would allow emphasis to be directed towards preventing injuries that are associated with the most significant impairment outcomes. PMID:20184844

A study of impairing injuries in real world crashes using the Injury Impairment Scale (IIS) and the predicted Functional Capacity Index (PFCI-AIS).

PubMed

Barnes, Jo; Morris, Andrew

2009-10-01

The ability to predict impairment outcomes in large databases using a simplified technique allows researchers to focus attention on preventing costly impairing injuries. The dilemma that exists for researchers is to determine which method is the most reliable and valid. This study examines available methods to predict impairment and explores the differences between the IIS and pFCI applied to real world crash injury data. Occupant injury data from the UK Co-operative Crash Injury Study (CCIS) database have been coded using AIS 1990 and AIS 2005. The data have subsequently been recoded using the associated impairment scales namely the Injury Impairment Scale (IIS) and the predicted Functional Capacity Index (pFCI) to determine the predicted impairment levels of injuries at one year post crash. Comparisons between the levels of impairment were made and any differences further explored. Injury data for the period February 2006 to September 2008 from the CCIS database were used in the analysis which involved a dataset of 2,437 occcupants who sustained over 8000 injuries. This study found some differences between the impairment scales for injuries coded to the AIS 1990 and AIS 2005 coding dictionaries. The pFCI predicts 31.5% of injuries to be impairing in AIS 2005, less than the IIS (38.5%) using AIS 1990. Using CCIS data the pFCI predicted that only 6% of the occupants with a coded injury would have an impairing injury compared to 24% of occupants using the IIS. The main body regions identified as having the major differences between the two impairment scales for car occupants were the head and spine. Follow up data were then used for a small number of cases (n=31, lower extremity and whiplash injuries) to examine any differences in predicted impairment versus perceived impairment. These data were selected from a previous study conducted between 2003 and 2006 and identified the discrepancy between predicted impairment and actual perceived impairment as defined by the participant. Overall the work highlights the variation between the pFCI and IIS and emphasises the importance and need for a single validated impairment scale that can be universally applied. This would allow emphasis to be directed towards preventing injuries that are associated with the most significant impairment outcomes.

Carcinogenesis of urethane: simulation versus experiment.

PubMed

Lajovic, Andrej; Nagy, Leslie D; Guengerich, F Peter; Bren, Urban

2015-04-20

The carcinogenesis of urethane (ethyl carbamate), a byproduct of fermentation that is consistently found in various food products, was investigated with a combination of kinetic experiments and quantum chemical calculations. The main objective of the study was to find ΔG(⧧), the activation free energy for the rate-limiting step of the SN2 reaction among the ultimate carcinogen of urethane, vinyl carbamate epoxide (VCE), and different nucleobases of the DNA. In the experimental part, the second-order reaction rate constants for the formation of the main 7-(2-oxoethyl)guanine adduct in aqueous solutions of deoxyguanosine and in DNA were determined. A series of ab initio, density functional theory (DFT), and semiempirical molecular orbital (MO) calculations was then performed to determine the activation barriers for the reaction between VCE and nucleobases methylguanine, methyladenine, and methylcytosine. Effects of hydration were incorporated with the use of the solvent reaction field method of Tomasi and co-workers and the Langevine dipoles model of Florian and Warshel. The computational results for the main adduct were found to be in good agreement with the experiment, thus presenting strong evidence for the validity of the proposed SN2 mechanism. This allowed us to predict the activation barriers of reactions leading to side products for which kinetic experiments have not yet been performed. Our calculations have shown that the main 7-(2-oxoethyl)deoxyguanosine adduct indeed forms preferentially because the emergence of other adducts either proceeds across a significantly higher activation barrier or the geometry of the reaction requires the Watson-Crick pairs of the DNA to be broken. The computational study also considered the questions of stereoselectivity, the ease of the elimination of the leaving group, and the relative contributions of the two possible reaction paths for the formation of the 1,N(2)-ethenodeoxyguanosine adduct.

Computational Evaluation of Airframe Noise Reduction Concepts at Full Scale

NASA Technical Reports Server (NTRS)

Khorrami, Mehdi R.; Duda, Benjamin; Hazir, Andreas; Fares, Ehab

2016-01-01

High-fidelity simulations focused on full-scale evaluation of new technologies for mitigating flap and landing gear noise are presented. These noise reduction concepts were selected because of their superior acoustic performance, as demonstrated during NASA wind tunnel tests of an 18%-scale, semi-span model of a Gulfstream aircraft. The full-scale, full-aircraft, time-accurate simulations were performed with the lattice Boltzmann PowerFLOW(Registered Trademark) solver for free air at a Mach number of 0.2. Three aircraft configurations (flaps deflected at 39? without and with main gear deployed, and 0? flaps with main gear extended) were used to determine the aero-acoustic performance of the concepts on component-level (individually) and system-level (concurrent applica-tion) bases. Farfield noise spectra were obtained using a Ffowcs-Williams and Hawkings acoustic analogy approach. Comparison of the predicted spectra without (baseline) and with the noise treatments applied showed that noise reduction benefits between 2-3 dB for the flap and 1.3-1.7 dB for the main landing gear are obtained. It was also found that the full extent of the benefits is being masked by the noise generated from the flap brackets and main gear cavities, which act as prominent secondary sources.

Improve SSME power balance model

NASA Technical Reports Server (NTRS)

Karr, Gerald R.

1992-01-01

Effort was dedicated to development and testing of a formal strategy for reconciling uncertain test data with physically limited computational prediction. Specific weaknesses in the logical structure of the current Power Balance Model (PBM) version are described with emphasis given to the main routing subroutines BAL and DATRED. Selected results from a variational analysis of PBM predictions are compared to Technology Test Bed (TTB) variational study results to assess PBM predictive capability. The motivation for systematic integration of uncertain test data with computational predictions based on limited physical models is provided. The theoretical foundation for the reconciliation strategy developed in this effort is presented, and results of a reconciliation analysis of the Space Shuttle Main Engine (SSME) high pressure fuel side turbopump subsystem are examined.

PSA: A program to streamline orbit determination for launch support operations

NASA Technical Reports Server (NTRS)

Legerton, V. N.; Mottinger, N. A.

1988-01-01

An interactive, menu driven computer program was written to streamline the orbit determination process during the critical launch support phase of a mission. Residing on a virtual memory minicomputer, this program retains the quantities in-core needed to obtain a least squares estimate of the spacecraft trajectory with interactive displays to assist in rapid radio metric data evaluation. Menu-driven displays allow real time filter and data strategy development. Graphical and tabular displays can be sent to a laser printer for analysis without exiting the program. Products generated by this program feed back to the main orbit determination program in order to further refine the estimate of the trajectory. The final estimate provides a spacecraft ephemeris which is transmitted to the mission control center and used for antenna pointing and frequency predict generation by the Deep Space Network. The development and implementation process of this program differs from that used for most other navigation software by allowing the users to check important operating features during development and have changes made as needed.

Characterizing air quality data from complex network perspective.

PubMed

Fan, Xinghua; Wang, Li; Xu, Huihui; Li, Shasha; Tian, Lixin

2016-02-01

Air quality depends mainly on changes in emission of pollutants and their precursors. Understanding its characteristics is the key to predicting and controlling air quality. In this study, complex networks were built to analyze topological characteristics of air quality data by correlation coefficient method. Firstly, PM2.5 (particulate matter with aerodynamic diameter less than 2.5 μm) indexes of eight monitoring sites in Beijing were selected as samples from January 2013 to December 2014. Secondly, the C-C method was applied to determine the structure of phase space. Points in the reconstructed phase space were considered to be nodes of the network mapped. Then, edges were determined by nodes having the correlation greater than a critical threshold. Three properties of the constructed networks, degree distribution, clustering coefficient, and modularity, were used to determine the optimal value of the critical threshold. Finally, by analyzing and comparing topological properties, we pointed out that similarities and difference in the constructed complex networks revealed influence factors and their different roles on real air quality system.

High-resolution estimates of Nubia-Somalia plate motion since 20 Ma from reconstructions of the Southwest Indian Ridge, Red Sea and Gulf of Aden

NASA Astrophysics Data System (ADS)

DeMets, C.; Merkouriev, S.

2016-10-01

Large gaps and inconsistencies remain in published estimates of Nubia-Somalia plate motion based on reconstructions of seafloor spreading data around Africa. Herein, we use newly available reconstructions of the Southwest Indian Ridge at ˜1-Myr intervals since 20 Ma to estimate Nubia-Somalia plate motion farther back in time than previously achieved and with an unprecedented degree of temporal resolution. At the northern end of the East African rift, our new estimates of Nubia-Somalia motion for six times from 0.78 Ma to 5.2 Ma differ by only 2 per cent from the rift-normal component of motion that is extrapolated from a recently estimated GPS angular velocity. The rate of rift-normal extension thus appears to have remained steady since at least 5.2 Ma. Our new rotations indicate that the two plates have moved relative to each other since at least 16 Ma and possibly longer. Motion has either been steady since at least 16 Ma or accelerated modestly between 6 and 5.2 Ma. Our Nubia-Somalia rotations predict 42.5 ± 3.8 km of rift-normal extension since 10.6 Ma across the well-studied, northern segment of the Main Ethiopian Rift, consistent with 40-50 km estimates for extension since 10.6 Myr based on seismological surveys of this narrow part of the plate boundary. Nubia-Somalia rotations are also derived by combining newly estimated Somalia-Arabia rotations that reconstruct the post-20-Ma opening of the Gulf of Aden with Nubia-Arabia rotations estimated via a probabilistic analysis of plausible opening scenarios for the Red Sea. These rotations predict Nubia-Somalia motion since 5.2 Myr that is consistent with that determined from Southwest Indian Ridge data and also predict 40 ± 3 km of rift-normal extension since 10.6 Ma across the Main Ethiopian Rift, consistent with our 42.5 ± 3.8 km Southwest Indian Ridge estimate. Our new rotations exclude at high confidence level previous estimates of 12 ± 13 and 123 ± 14 km for rift-normal extensions across the Main Ethiopian Rift since 10.6 Ma based on reconstructions of Chron 5n.2 along the Southwest Indian Ridge. Sparse coverage of magnetic reversals older than 16 Ma along the western third of the Southwest Indian Ridge precludes reliable determinations of Nubia-Somalia plate motion before 16 Ma, leaving unanswered the key question of when the motion between the two plates began.

Determination of the hydrodynamic friction matrix for various anisotropic particles

NASA Astrophysics Data System (ADS)

Kraft, Daniela; Wittkowksi, Raphael; Löwen, Hartmut; Pine, David

2013-03-01

The relationship between the shape of a colloidal particle and its Brownian motion can be captured by the hydrodynamic friction matrix. It fully describes the translational and rotational diffusion along the particle's main axes as well as the coupling between rotational and translational diffusion. We observed a wide variety of anisotropic colloidal particles with confocal microscopy and calculated the hydrodynamic friction matrix from the particle trajectories. We find that symmetries in the particle shape are reflected in the entries of the friction matrix. We compare our experimentally obtained results with numerical simulations and theoretical predictions. Financial support through a Rubicon grant by the Netherlands Organisation for Scientific Research.

High negative charge of a dust particle in a hot cathode discharge.

PubMed

Arnas, C; Mikikian, M; Doveil, F

1999-12-01

Dust particle levitation experiments in a plasma produced by a hot filament discharge, operating at low argon pressure, are presented. The basic characteristics of a dust grain trapped in a plate sheath edge in these experimental conditions are reported. Taking into account the sheath potential profiles measured with a differential emissive probe diagnostic, the forces applied to an isolated dust grain can be determined. Two different experimental methods yield approximately the same value for the dust charge. The observed high negative charge is mainly due to the contribution of the primary electrons emitted by the filaments as predicted by a simple model.

Vibrations and structureborne noise in space station

NASA Technical Reports Server (NTRS)

Vaicaitis, R.

1985-01-01

Theoretical models were developed capable of predicting structural response and noise transmission to random point mechanical loads. Fiber reinforced composite and aluminum materials were considered. Cylindrical shells and circular plates were taken as typical representatives of structural components for space station habitability modules. Analytical formulations include double wall and single wall constructions. Pressurized and unpressurized models were considered. Parametric studies were conducted to determine the effect on structural response and noise transmission due to fiber orientation, point load location, damping in the core and the main load carrying structure, pressurization, interior acoustic absorption, etc. These analytical models could serve as preliminary tools for assessing noise related problems, for space station applications.

The self-propulsion of a helix in granular matter

NASA Astrophysics Data System (ADS)

Valdes, Rogelio; Angeles, Veronica; de La Calleja, Elsa; Zenit, Roberto

2017-11-01

The effect of the shape of helicoidal on the displacement of magnetic robots in granular media is studied experimentally. We quantify the influences of three main parameters of the shape of the helicoidal swimmers: body diameter, step, and the angle. We compare the experimental measurements with an empirically modified resistive force theory prediction that accounts for the static friction coefficient of the particles of the granular material, leading to good agreement. Comparisons are also made with the granular resistive force theory proposed by Goldman and collaborators. We found an optimal helix angle to produce movement and determined a relationship between the swimmer size and speed.

Composition of pyrolysis gas from oil shale at various stages of heating

NASA Astrophysics Data System (ADS)

Martemyanov, S. M.; Bukharkin, A. A.; Koryashov, I. A.; Ivanov, A. A.

2017-05-01

Underground, the pyrolytic conversion of an oil shale in the nearest future may become an alternative source of a fuel gas and a synthetic oil. The main scientific problem in designing this technology is to provide a methodology for determination of the optimal mode of heating the subterranean formation. Such a methodology must allow predicting the composition of the pyrolysis products and the energy consumption at a given heating rate of the subterranean formation. The paper describes the results of heating of the oil shale fragments in conditions similar to the underground. The dynamics of composition of the gaseous products of pyrolysis are presented and analyzed.

Dynamic evolutions of electron properties: A theoretical study for condensed-phase β-HMX under shock loading

NASA Astrophysics Data System (ADS)

He, Zheng-Hua; Chen, Jun; Wu, Qiang; Ji, Guang-Fu

2017-11-01

We present the density functional theory (DFT) calculations for microscopic electron properties of β-HMX under shock loading. The metallization pressure is determined to be within 30-55 GPa. The frontier molecular orbitals mainly localize on N-NO2 groups initially and disperse with pressure increase, while HOMO and LUMO orbitals trend to aggregate with each other. The deformation of N-NO2 groups and enhanced hydrogen-bonding interactions cause the electron delocalization and lower the band gap, inducing the reaction initiation finally. Our results show that using the electron properties can reliably predict the initial decomposition of energetic materials under shock loading.

[The Use of FTIR Coupled with Partial Least Square for Quantitative Analysis of the Main Composition of Bamboo/Polypropylene Composites].

PubMed

Lao, Wan-li; He, Yu-chan; Li, Gai-yun; Zhou, Qun

2016-01-01

The biomass to plastic ratio in wood plastic composites (WPCs) greatly affects the physical and mechanical properties and price. Fast and accurate evaluation of the biomass to plastic ratio is important for the further development of WPCs. Quantitative analysis of the WPC main composition currently relies primarily on thermo-analytical methods. However, these methods have some inherent disadvantages, including time-consuming, high analytical errors and sophisticated, which severely limits the applications of these techniques. Therefore, in this study, Fourier Transform Infrared (FTIR) spectroscopy in combination with partial least square (PLS) has been used for rapid prediction of bamboo and polypropylene (PP) content in bamboo/PP composites. The bamboo powders were used as filler after being dried at 105 degrees C for 24 h. PP was used as matrix materials, and some chemical regents were used as additives. Then 42 WPC samples with different ratios of bamboo and PP were prepared by the methods of extrusion. FTIR spectral data of 42 WPC samples were collected by means of KBr pellets technique. The model for bamboo and PP content prediction was developed by PLS-2 and full cross validation. Results of internal cross validation showed that the first derivative spectra in the range of 1 800-800 cm(-1) corrected by standard normal variate (SNV) yielded the optimal model. For both bamboo and PP calibration, the coefficients of determination (R2) were 0.955. The standard errors of calibration (SEC) were 1.872 for bamboo content and 1.848 for PP content, respectively. For both bamboo and PP validation, the R2 values were 0.950. The standard errors of cross validation (SECV) were 1.927 for bamboo content and 1.950 for PP content, respectively. And the ratios of performance to deviation (RPD) were 4.45 for both biomass and PP examinations. The results of external validation showed that the relative prediction deviations for both biomass and PP contents were lower than ± 6%. FTIR combined with PLS can be used for rapid and accurate determination of bamboo and PP content in bamboo/PP composites.

An Observational Study of Accretion Dynamics in Short-Period Pre-Main Sequence Binaries

NASA Astrophysics Data System (ADS)

Tofflemire, Benjamin; Mathieu, Robert; Herczeg, Greg; Johns-Krull, Christopher; Akeson, Rachel; Ciardi, David

2018-01-01

Over the past thirty years, a detailed picture of star formation has emerged that highlights the importance of the interaction between a pre-main sequence (pre-MS) star and its protoplanetary disk. The properties of an emergent star, the lifetime of a protoplanetary disk, and the formation of planets are all, in part, determined by this star-disk interaction. Many stars, however, form in binary or higher-order systems where orbital dynamics are capable of fundamentally altering this star-disk interaction. Orbital resonances, especially in short-period systems, are capable of clearing the central region of a protoplanetary disk, leaving the possibility for three stable accretion disks: a circumstellar disk around each star and a circumbinary disk. In this model, accretion onto the stars is predicted to proceed in periodic streams that form at the inner edge of the circumbinary disk, cross the dynamically cleared gap, and feed circumstellar disks or accrete directly onto the stars themselves. This pulsed-accretion paradigm predicts bursts of accretion that are periodic with the orbital period, where the duration, amplitude, location in orbital phase, and which star if preferentially fed, all depend on the orbital parameters. To test these predictions, we have carried out intensive observational campaigns combining time-series, optical and near-infrared photometry with time-series, optical spectroscopy. These data are capable of monitoring the stellar accretion rate, the properties of warm circumstellar dust, and the kinematics of accretion flows, all as a function of orbital phase. In our sample of 9 pre-MS binaries with diverse orbital parameters, we search for evidence of periodic accretion events and seek to determine the role orbital parameters have on the characteristics of accretion events. Two results from our campaign will be highlighted: 1) the detection of periodic pulsed accretion events in DQ Tau and TWA 3A, and 2) evidence that the TWA 3A primary is the dominant accretor in the system. We compare these findings to the results of numerical simulations and comment on the role of magnetospheric accretion in pre-MS binaries.

Global Risk Score and Clinical SYNTAX Score as Predictors of Clinical Outcomes of Patients Undergoing Unprotected Left Main Percutaneous Catheter Intervention

PubMed Central

Cuenza, Lucky; Collado, Marianne P.; Ho Khe Sui, James

2017-01-01

Background Risk stratification is an important component of left main percutaneous catheter intervention (PCI) which has emerged as a feasible alternative to cardiac surgery. We sought to compare the clinical SYNTAX score and the global risk score in predicting outcomes of patients undergoing unprotected left main PCI in our institution. Methods Clinical, angiographic and procedural characteristics of 92 patients who underwent unprotected left main PCI (mean age 62 ± 12.1 years) were analyzed. Patients were risk stratified into tertiles of high, intermediate and low risk using the global risk score (GRS) and the clinical SYNTAX score (CSS) and were prospectively followed up at 1 year for the occurrence of major adverse cardiovascular events (MACEs), defined as a composite of all cause mortality, cardiac mortality, non-fatal myocardial infarction, stroke, coronary artery bypass, and target vessel revascularization. Results There were 26 (28.2%) who experienced MACEs, of which 10 (10.8%) patients died. Multivariable hazards analysis showed that the GRS (hazard ratio (HR) = 5.5, P = 0.001) and CSS (HR = 4.3, P = 0.001) were both independent predictors of MACEs. Kaplan-Meier analysis showed higher incidence of MACEs with the intermediate and higher risk categories compared to those classified as low risk. Receiver-operator characteristic analysis showed that the GRS has better discriminatory ability than the CSS in the prediction of 1 year MACEs (0.891 vs. 0.743, P = 0.007). Conclusion The GRS and CSS are predictive of outcomes after left main PCI. The GRS appears to have superior predictive and prognostic utility compared to the CSS. This study emphasizes the importance of combining both anatomic and clinical variables for optimum prognostication and management decisions in left main PCI. PMID:29317974

Making fate and exposure models for freshwater ecotoxicity in life cycle assessment suitable for organic acids and bases.

PubMed

van Zelm, Rosalie; Stam, Gea; Huijbregts, Mark A J; van de Meent, Dik

2013-01-01

Freshwater fate and exposure factors were determined for organic acids and bases, making use of the knowledge on electrical interaction of ionizing chemicals and their sorption to particles. The fate factor represents the residence time in the environment whereas exposure factors equal the dissolved fraction of a chemical. Multimedia fate, exposure, and effect model USES-LCA was updated to take into account the influence of ionization, based upon the acid dissociation constant (pK(a)) of a chemical, and the environmental pH. Freshwater fate (FF) and exposure (XF) factors were determined for 415 acids and 496 bases emitted to freshwater, air, and soil. The relevance of taking account of the degree of ionization of chemicals was tested by determining the ratio (R) of the new vs. fate and exposure factors determined with USES-LCA suitable for neutral chemicals only. Our results show that the majority of freshwater fate and exposure factors of chemicals that are largely ionized in the environment are larger with the ionics model compared to the factors determined with the neutrals model version. R(FF) ranged from 2.4×10(-1) to 1.6×10(1) for freshwater emissions, from 1.2×10(-2) to 2.0×10(4) for soil emissions and from 5.8×10(-2) to 6.0×10(3) for air emissions, and R(XF) from 5.3×10(-1) to 2.2×10(1). Prediction of changed solid-water partitioning, implying a change in runoff and in removal via sedimentation, and prediction of negligible air-water partition coefficient, leading to negligible volatilization were the main contributors to the changes in freshwater fate factors. Copyright © 2012 Elsevier Ltd. All rights reserved.

Predictability and prediction of the total number of winter extremely cold days over China

NASA Astrophysics Data System (ADS)

Luo, Xiao; Wang, Bin

2018-03-01

The current dynamical climate models have limited skills in predicting winter temperature in China. The present study uses physics-based empirical models (PEMs) to explore the sources and limits of the seasonal predictability in the total number of extremely cold days (NECD) over China. A combined cluster-rotated EOF analysis reveals two sub-regions of homogeneous variability among hundreds of stations, namely the Northeast China (NE) and Main China (MC). This reduces the large-number of predictands to only two indices, the NCED-NE and NCED-MC, which facilitates detection of the common sources of predictability for all stations. The circulation anomalies associated with the NECD-NE exhibit a zonally symmetric Arctic Oscillation-like pattern, whereas those associated with the NECD-MC feature a North-South dipolar pattern over Asia. The predictability of the NECD originates from SST and snow cover anomalies in the preceding September and October. However, the two regions have different SST predictors: The NE predictor is in the western Eurasian Arctic while the MC predictor is over the tropical-North Pacific. The October snow cover predictors also differ: The NE predictor primarily resides in the central Eurasia while the MC predictor is over the western and eastern Eurasia. The PEM prediction results suggest that about 60% (55%) of the total variance of winter NECD over the NE (Main) China are likely predictable 1 month in advance. The NECD at each station can also be predicted by using the four predictors that were detected for the two indices. The cross-validated temporal correlation skills exceed 0.70 at most stations. The physical mechanisms by which the autumn Arctic sea ice, snow cover, and tropical-North Pacific SST anomalies affect winter NECD over the NE and Main China are discussed.

Small UAS-Based Wind Feature Identification System Part 1: Integration and Validation

PubMed Central

Rodriguez Salazar, Leopoldo; Cobano, Jose A.; Ollero, Anibal

2016-01-01

This paper presents a system for identification of wind features, such as gusts and wind shear. These are of particular interest in the context of energy-efficient navigation of Small Unmanned Aerial Systems (UAS). The proposed system generates real-time wind vector estimates and a novel algorithm to generate wind field predictions. Estimations are based on the integration of an off-the-shelf navigation system and airspeed readings in a so-called direct approach. Wind predictions use atmospheric models to characterize the wind field with different statistical analyses. During the prediction stage, the system is able to incorporate, in a big-data approach, wind measurements from previous flights in order to enhance the approximations. Wind estimates are classified and fitted into a Weibull probability density function. A Genetic Algorithm (GA) is utilized to determine the shaping and scale parameters of the distribution, which are employed to determine the most probable wind speed at a certain position. The system uses this information to characterize a wind shear or a discrete gust and also utilizes a Gaussian Process regression to characterize continuous gusts. The knowledge of the wind features is crucial for computing energy-efficient trajectories with low cost and payload. Therefore, the system provides a solution that does not require any additional sensors. The system architecture presents a modular decentralized approach, in which the main parts of the system are separated in modules and the exchange of information is managed by a communication handler to enhance upgradeability and maintainability. Validation is done providing preliminary results of both simulations and Software-In-The-Loop testing. Telemetry data collected from real flights, performed in the Seville Metropolitan Area in Andalusia (Spain), was used for testing. Results show that wind estimation and predictions can be calculated at 1 Hz and a wind map can be updated at 0.4 Hz. Predictions show a convergence time with a 95% confidence interval of approximately 30 s. PMID:28025531

Small UAS-Based Wind Feature Identification System Part 1: Integration and Validation.

PubMed

Rodriguez Salazar, Leopoldo; Cobano, Jose A; Ollero, Anibal

2016-12-23

This paper presents a system for identification of wind features, such as gusts and wind shear. These are of particular interest in the context of energy-efficient navigation of Small Unmanned Aerial Systems (UAS). The proposed system generates real-time wind vector estimates and a novel algorithm to generate wind field predictions. Estimations are based on the integration of an off-the-shelf navigation system and airspeed readings in a so-called direct approach. Wind predictions use atmospheric models to characterize the wind field with different statistical analyses. During the prediction stage, the system is able to incorporate, in a big-data approach, wind measurements from previous flights in order to enhance the approximations. Wind estimates are classified and fitted into a Weibull probability density function. A Genetic Algorithm (GA) is utilized to determine the shaping and scale parameters of the distribution, which are employed to determine the most probable wind speed at a certain position. The system uses this information to characterize a wind shear or a discrete gust and also utilizes a Gaussian Process regression to characterize continuous gusts. The knowledge of the wind features is crucial for computing energy-efficient trajectories with low cost and payload. Therefore, the system provides a solution that does not require any additional sensors. The system architecture presents a modular decentralized approach, in which the main parts of the system are separated in modules and the exchange of information is managed by a communication handler to enhance upgradeability and maintainability. Validation is done providing preliminary results of both simulations and Software-In-The-Loop testing. Telemetry data collected from real flights, performed in the Seville Metropolitan Area in Andalusia (Spain), was used for testing. Results show that wind estimation and predictions can be calculated at 1 Hz and a wind map can be updated at 0.4 Hz . Predictions show a convergence time with a 95% confidence interval of approximately 30 s .

Trajectory Orientation: A Technology-Enabled Concept Requiring a Shift in Controller Roles and Responsibilities

NASA Technical Reports Server (NTRS)

Leiden, Ken; Green, Steven

2000-01-01

The development of a decision support tool (DST) for the en-route domain with accurate conflict prediction time horizons of 20 minutes has introduced an interesting problem. A 20 minute time horizon for conflict prediction often results in the predicted conflict occurring one or more sectors downstream from the sector controller who "owns" (i-e., is responsible for the safe separation of aircraft) one or both of the aircraft in the conflict pair. Based on current roles and responsibilities of today's en route controllers, the upstream controller would not resolve this conflict. In most cases, the downstream controller would wait until the conflicting aircraft entered higher sector before resolving the conflict. This results in a delay of several minutes from the time when the conflict was initially predicted. This delay is inefficient from both a controller workload and user's cost of operations perspective. Trajectory orientation, a new concept for facilitating an efficient, conflict-free flight path across several sectors while conforming to metering or miles-in-trail spacing, is proposed as an alternative to today's sector-oriented method. This concept necessitates a fundamental shift in thinking about inter-sector coordination. Instead of operating independently, with the main focus on protecting their internal airspace, controllers would work cooperatively, depending on each other for well-planned, conflict-free flow of aircraft. To support the trajectory orientation concept, a long time horizon (15 to 20 minutes) for conflict prediction and resolution would most likely be a primary requirement. In addition, new tools, such as controller-pilot data link will be identified to determine their necessity and applicability for trajectory orientation. Finally, with significant controller participation from selected Air Route Traffic Control Centers, potential shifts in R-side/D-side roles and responsibilities as well as the creation of a new controller position for multi-sector planning will be examined to determine the most viable solutions.

Predictable Phenotypes of Antibiotic Resistance Mutations.

PubMed

Knopp, M; Andersson, D I

2018-05-15

Antibiotic-resistant bacteria represent a major threat to our ability to treat bacterial infections. Two factors that determine the evolutionary success of antibiotic resistance mutations are their impact on resistance level and the fitness cost. Recent studies suggest that resistance mutations commonly show epistatic interactions, which would complicate predictions of their stability in bacterial populations. We analyzed 13 different chromosomal resistance mutations and 10 host strains of Salmonella enterica and Escherichia coli to address two main questions. (i) Are there epistatic interactions between different chromosomal resistance mutations? (ii) How does the strain background and genetic distance influence the effect of chromosomal resistance mutations on resistance and fitness? Our results show that the effects of combined resistance mutations on resistance and fitness are largely predictable and that epistasis remains rare even when up to four mutations were combined. Furthermore, a majority of the mutations, especially target alteration mutations, demonstrate strain-independent phenotypes across different species. This study extends our understanding of epistasis among resistance mutations and shows that interactions between different resistance mutations are often predictable from the characteristics of the individual mutations. IMPORTANCE The spread of antibiotic-resistant bacteria imposes an urgent threat to public health. The ability to forecast the evolutionary success of resistant mutants would help to combat dissemination of antibiotic resistance. Previous studies have shown that the phenotypic effects (fitness and resistance level) of resistance mutations can vary substantially depending on the genetic context in which they occur. We conducted a broad screen using many different resistance mutations and host strains to identify potential epistatic interactions between various types of resistance mutations and to determine the effect of strain background on resistance phenotypes. Combinations of several different mutations showed a large amount of phenotypic predictability, and the majority of the mutations displayed strain-independent phenotypes. However, we also identified a few outliers from these patterns, illustrating that the choice of host organism can be critically important when studying antibiotic resistance mutations. Copyright © 2018 Knopp and Andersson.

Predicting invasiveness of species in trade: Climate match, trophic guild and fecundity influence establishment and impact of non-native freshwater fishes

USGS Publications Warehouse

Howeth, Jennifer G.; Gantz, Crysta A.; Angermeier, Paul; Frimpong, Emmanuel A.; Hoff, Michael H.; Keller, Reuben P.; Mandrak, Nicholas E.; Marchetti, Michael P.; Olden, Julian D.; Romagosa, Christina M.; Lodge, David M.

2016-01-01

AimImpacts of non-native species have motivated development of risk assessment tools for identifying introduced species likely to become invasive. Here, we develop trait-based models for the establishment and impact stages of freshwater fish invasion, and use them to screen non-native species common in international trade. We also determine which species in the aquarium, biological supply, live bait, live food and water garden trades are likely to become invasive. Results are compared to historical patterns of non-native fish establishment to assess the relative importance over time of pathways in causing invasions.LocationLaurentian Great Lakes region.MethodsTrait-based classification trees for the establishment and impact stages of invasion were developed from data on freshwater fish species that established or failed to establish in the Great Lakes. Fishes in trade were determined from import data from Canadian and United States regulatory agencies, assigned to specific trades and screened through the developed models.ResultsClimate match between a species’ native range and the Great Lakes region predicted establishment success with 75–81% accuracy. Trophic guild and fecundity predicted potential harmful impacts of established non-native fishes with 75–83% accuracy. Screening outcomes suggest the water garden trade poses the greatest risk of introducing new invasive species, followed by the live food and aquarium trades. Analysis of historical patterns of introduction pathways demonstrates the increasing importance of these trades relative to other pathways. Comparisons among trades reveal that model predictions parallel historical patterns; all fishes previously introduced from the water garden trade have established. The live bait, biological supply, aquarium and live food trades have also contributed established non-native fishes.Main conclusionsOur models predict invasion risk of potential fish invaders to the Great Lakes region and could help managers prioritize efforts among species and pathways to minimize such risk. Similar approaches could be applied to other taxonomic groups and geographic regions.

Identification of residue pairing in interacting β-strands from a predicted residue contact map.

PubMed

Mao, Wenzhi; Wang, Tong; Zhang, Wenxuan; Gong, Haipeng

2018-04-19

Despite the rapid progress of protein residue contact prediction, predicted residue contact maps frequently contain many errors. However, information of residue pairing in β strands could be extracted from a noisy contact map, due to the presence of characteristic contact patterns in β-β interactions. This information may benefit the tertiary structure prediction of mainly β proteins. In this work, we propose a novel ridge-detection-based β-β contact predictor to identify residue pairing in β strands from any predicted residue contact map. Our algorithm RDb 2 C adopts ridge detection, a well-developed technique in computer image processing, to capture consecutive residue contacts, and then utilizes a novel multi-stage random forest framework to integrate the ridge information and additional features for prediction. Starting from the predicted contact map of CCMpred, RDb 2 C remarkably outperforms all state-of-the-art methods on two conventional test sets of β proteins (BetaSheet916 and BetaSheet1452), and achieves F1-scores of ~ 62% and ~ 76% at the residue level and strand level, respectively. Taking the prediction of the more advanced RaptorX-Contact as input, RDb 2 C achieves impressively higher performance, with F1-scores reaching ~ 76% and ~ 86% at the residue level and strand level, respectively. In a test of structural modeling using the top 1 L predicted contacts as constraints, for 61 mainly β proteins, the average TM-score achieves 0.442 when using the raw RaptorX-Contact prediction, but increases to 0.506 when using the improved prediction by RDb 2 C. Our method can significantly improve the prediction of β-β contacts from any predicted residue contact maps. Prediction results of our algorithm could be directly applied to effectively facilitate the practical structure prediction of mainly β proteins. All source data and codes are available at http://166.111.152.91/Downloads.html or the GitHub address of https://github.com/wzmao/RDb2C .

The implementation of rare events logistic regression to predict the distribution of mesophotic hard corals across the main Hawaiian Islands.

PubMed

Veazey, Lindsay M; Franklin, Erik C; Kelley, Christopher; Rooney, John; Frazer, L Neil; Toonen, Robert J

2016-01-01

Predictive habitat suitability models are powerful tools for cost-effective, statistically robust assessment of the environmental drivers of species distributions. The aim of this study was to develop predictive habitat suitability models for two genera of scleractinian corals (Leptoserisand Montipora) found within the mesophotic zone across the main Hawaiian Islands. The mesophotic zone (30-180 m) is challenging to reach, and therefore historically understudied, because it falls between the maximum limit of SCUBA divers and the minimum typical working depth of submersible vehicles. Here, we implement a logistic regression with rare events corrections to account for the scarcity of presence observations within the dataset. These corrections reduced the coefficient error and improved overall prediction success (73.6% and 74.3%) for both original regression models. The final models included depth, rugosity, slope, mean current velocity, and wave height as the best environmental covariates for predicting the occurrence of the two genera in the mesophotic zone. Using an objectively selected theta ("presence") threshold, the predicted presence probability values (average of 0.051 for Leptoseris and 0.040 for Montipora) were translated to spatially-explicit habitat suitability maps of the main Hawaiian Islands at 25 m grid cell resolution. Our maps are the first of their kind to use extant presence and absence data to examine the habitat preferences of these two dominant mesophotic coral genera across Hawai'i.

Prediction of protein post-translational modifications: main trends and methods

NASA Astrophysics Data System (ADS)

Sobolev, B. N.; Veselovsky, A. V.; Poroikov, V. V.

2014-02-01

The review summarizes main trends in the development of methods for the prediction of protein post-translational modifications (PTMs) by considering the three most common types of PTMs — phosphorylation, acetylation and glycosylation. Considerable attention is given to general characteristics of regulatory interactions associated with PTMs. Different approaches to the prediction of PTMs are analyzed. Most of the methods are based only on the analysis of the neighbouring environment of modification sites. The related software is characterized by relatively low accuracy of PTM predictions, which may be due both to the incompleteness of training data and the features of PTM regulation. Advantages and limitations of the phylogenetic approach are considered. The prediction of PTMs using data on regulatory interactions, including the modular organization of interacting proteins, is a promising field, provided that a more carefully selected training data will be used. The bibliography includes 145 references.

Genetically determined measures of striatal D2 signaling predict prefrontal activity during working memory performance.

PubMed

Bertolino, Alessandro; Taurisano, Paolo; Pisciotta, Nicola Marco; Blasi, Giuseppe; Fazio, Leonardo; Romano, Raffaella; Gelao, Barbara; Lo Bianco, Luciana; Lozupone, Madia; Di Giorgio, Annabella; Caforio, Grazia; Sambataro, Fabio; Niccoli-Asabella, Artor; Papp, Audrey; Ursini, Gianluca; Sinibaldi, Lorenzo; Popolizio, Teresa; Sadee, Wolfgang; Rubini, Giuseppe

2010-02-22

Variation of the gene coding for D2 receptors (DRD2) has been associated with risk for schizophrenia and with working memory deficits. A functional intronic SNP (rs1076560) predicts relative expression of the two D2 receptors isoforms, D2S (mainly pre-synaptic) and D2L (mainly post-synaptic). However, the effect of functional genetic variation of DRD2 on striatal dopamine D2 signaling and on its correlation with prefrontal activity during working memory in humans is not known. Thirty-seven healthy subjects were genotyped for rs1076560 (G>T) and underwent SPECT with [123I]IBZM (which binds primarily to post-synaptic D2 receptors) and with [123I]FP-CIT (which binds to pre-synaptic dopamine transporters, whose activity and density is also regulated by pre-synaptic D2 receptors), as well as BOLD fMRI during N-Back working memory. Subjects carrying the T allele (previously associated with reduced D2S expression) had striatal reductions of [123I]IBZM and of [123I]FP-CIT binding. DRD2 genotype also differentially predicted the correlation between striatal dopamine D2 signaling (as identified with factor analysis of the two radiotracers) and activity of the prefrontal cortex during working memory as measured with BOLD fMRI, which was positive in GG subjects and negative in GT. Our results demonstrate that this functional SNP within DRD2 predicts striatal binding of the two radiotracers to dopamine transporters and D2 receptors as well as the correlation between striatal D2 signaling with prefrontal cortex activity during performance of a working memory task. These data are consistent with the possibility that the balance of excitatory/inhibitory modulation of striatal neurons may also affect striatal outputs in relationship with prefrontal activity during working memory performance within the cortico-striatal-thalamic-cortical pathway.

Genetically Determined Measures of Striatal D2 Signaling Predict Prefrontal Activity during Working Memory Performance

PubMed Central

Bertolino, Alessandro; Taurisano, Paolo; Pisciotta, Nicola Marco; Blasi, Giuseppe; Fazio, Leonardo; Romano, Raffaella; Gelao, Barbara; Bianco, Luciana Lo; Lozupone, Madia; Di Giorgio, Annabella; Caforio, Grazia; Sambataro, Fabio; Niccoli-Asabella, Artor; Papp, Audrey; Ursini, Gianluca; Sinibaldi, Lorenzo; Popolizio, Teresa; Sadee, Wolfgang; Rubini, Giuseppe

2010-01-01

Background Variation of the gene coding for D2 receptors (DRD2) has been associated with risk for schizophrenia and with working memory deficits. A functional intronic SNP (rs1076560) predicts relative expression of the two D2 receptors isoforms, D2S (mainly pre-synaptic) and D2L (mainly post-synaptic). However, the effect of functional genetic variation of DRD2 on striatal dopamine D2 signaling and on its correlation with prefrontal activity during working memory in humans is not known. Methods Thirty-seven healthy subjects were genotyped for rs1076560 (G>T) and underwent SPECT with [123I]IBZM (which binds primarily to post-synaptic D2 receptors) and with [123I]FP-CIT (which binds to pre-synaptic dopamine transporters, whose activity and density is also regulated by pre-synaptic D2 receptors), as well as BOLD fMRI during N-Back working memory. Results Subjects carrying the T allele (previously associated with reduced D2S expression) had striatal reductions of [123I]IBZM and of [123I]FP-CIT binding. DRD2 genotype also differentially predicted the correlation between striatal dopamine D2 signaling (as identified with factor analysis of the two radiotracers) and activity of the prefrontal cortex during working memory as measured with BOLD fMRI, which was positive in GG subjects and negative in GT. Conclusions Our results demonstrate that this functional SNP within DRD2 predicts striatal binding of the two radiotracers to dopamine transporters and D2 receptors as well as the correlation between striatal D2 signaling with prefrontal cortex activity during performance of a working memory task. These data are consistent with the possibility that the balance of excitatory/inhibitory modulation of striatal neurons may also affect striatal outputs in relationship with prefrontal activity during working memory performance within the cortico-striatal-thalamic-cortical pathway. PMID:20179754

Thoracic Trauma Severity score on admission allows to determine the risk of delayed ARDS in trauma patients with pulmonary contusion.

PubMed

Daurat, Aurélien; Millet, Ingrid; Roustan, Jean-Paul; Maury, Camille; Taourel, Patrice; Jaber, Samir; Capdevila, Xavier; Charbit, Jonathan

2016-01-01

Pulmonary contusion is a major risk factor of acute respiratory distress syndrome (ARDS) in trauma patients. As this complication may appear after a free interval of 24-48 h, detection of patients at risk is essential. The main objective of this study was to assess the performance of the Thoracic Trauma Severity (TTS) score upon admission in predicting delayed ARDS in blunt trauma patients with pulmonary contusion. All blunt thoracic trauma patients admitted consecutively to our trauma centre between January 2005 and December 2009 were retrospectively included if they presented a pulmonary contusion on the admission chest computed tomography scan. Main outcome measure was the presence of moderate or severe ARDS (PaO2/FiO2 ratio≤200) for 48 h or more. The global ability of the TTS score to predict ARDS was studied by ROC curves with a threshold analysis using a grey zone approach. Of 329 patients studied (75% men, mean age 36.9 years [SD 17.8 years], mean Injury Severity Score 21.7 [SD 16.0]), 82 (25%) presented with ARDS (mean lowest PaO2/FiO2 ratio of 131 [SD 34]). The area under the ROC curves for the TTS score in predicting ARDS was 0.82 (95% CI 0.78-0.86) in the overall population. TTS scores between 8 and 12 belonged to the inconclusive grey zone. A TTS score of 13-25 was found to be independent risk factors of ARDS (OR 25.8 [95% CI 6.7-99.6] P<0.001). An extreme TTS score on admission accurately predicts the occurrence of delayed ARDS in blunt thoracic trauma patients affected by pulmonary contusion. This simple score could guide early decision making and management for a non-negligible proportion of this specific population. Copyright © 2015. Published by Elsevier Ltd.

Sizes, Shapes, and Satellites of Asteroids from Occultations

NASA Astrophysics Data System (ADS)

Waring Dunham, David; Herald, David Russell; Preston, Steve; Timerson, Bradley; Maley, Paul; Frappa, Eric; Hayamizu, Tsutomu; Talbot, John; Poro, Atila

2015-08-01

For 40 years, the sizes and shapes of dozens of asteroids have been determined from observations of asteroidal occultations. Some of the first evidence for satellites of asteroids was obtained from the early efforts; now, the orbits and sizes of some satellites discovered by other means have been refined from occultation observations. Also, several close binary stars have been discovered, and the angular diameters of some stars have been measured from analysis of these observations. The International Occultation Timing Association (IOTA) coordinates this activity worldwide, from predicting and publicizing the events, to accurately timing the occultations from as many stations as possible, and publishing and archiving the observations.The release of the Hipparcos and Tycho catalogs in 1997, from ESA’s Hipparcos space mission, revolutionized asteroidal occultation work, increasing the routine accuracy of the predictions and the annual number of observations by an order of magnitude. IOTA developed an efficient procedure for predicting the occultations using a combination of new star catalogs, based on Hipparcos and new star catalogs, generated mainly at the U. S. Naval Observatory (USNO), and new observations of asteroids relative to the improved astrometric nets mainly from USNO’s Flagstaff Astrometric Scanning Transit Telescope and JPL’s Table Mountain Observatory. In addition, many IOTA observers now use inexpensive low-light-level video cameras and specially built GPS video time inserters to accurately time the events. This automation has also allowed some observers to deploy multiple remote video stations across occultation paths. Then, one observer can record several “chords” across the asteroid. The cameras are sensitive enough that easily-hidden telescopes, many of which can be packed in standard air travel suitcases, can be used for many of the predicted occultations. IOTA’s network of regional coordinators collect and reduce the observations, which are deposited annually in Asteroid Occultations V12.0. EAR-A-3-RDR-OCCULTATIONS-V12.0. NASA Planetary Data System, 2014, where they are available to researchers worldwide.

Shear wave prediction using committee fuzzy model constrained by lithofacies, Zagros basin, SW Iran

NASA Astrophysics Data System (ADS)

Shiroodi, Sadjad Kazem; Ghafoori, Mohammad; Ansari, Hamid Reza; Lashkaripour, Golamreza; Ghanadian, Mostafa

2017-02-01

The main purpose of this study is to introduce the geological controlling factors in improving an intelligence-based model to estimate shear wave velocity from seismic attributes. The proposed method includes three main steps in the framework of geological events in a complex sedimentary succession located in the Persian Gulf. First, the best attributes were selected from extracted seismic data. Second, these attributes were transformed into shear wave velocity using fuzzy inference systems (FIS) such as Sugeno's fuzzy inference (SFIS), adaptive neuro-fuzzy inference (ANFIS) and optimized fuzzy inference (OFIS). Finally, a committee fuzzy machine (CFM) based on bat-inspired algorithm (BA) optimization was applied to combine previous predictions into an enhanced solution. In order to show the geological effect on improving the prediction, the main classes of predominate lithofacies in the reservoir of interest including shale, sand, and carbonate were selected and then the proposed algorithm was performed with and without lithofacies constraint. The results showed a good agreement between real and predicted shear wave velocity in the lithofacies-based model compared to the model without lithofacies especially in sand and carbonate.

Automated assessment of aortic and main pulmonary arterial diameters using model-based blood vessel segmentation for predicting chronic thromboembolic pulmonary hypertension in low-dose CT lung screening

NASA Astrophysics Data System (ADS)

Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Sugiura, Toshihiko; Tanabe, Nobuhiro; Kusumoto, Masahiko; Eguchi, Kenji; Kaneko, Masahiro

2018-02-01

Chronic thromboembolic pulmonary hypertension (CTEPH) is characterized by obstruction of the pulmonary vasculature by residual organized thrombi. A morphological abnormality inside mediastinum of CTEPH patient is enlargement of pulmonary artery. This paper presents an automated assessment of aortic and main pulmonary arterial diameters for predicting CTEPH in low-dose CT lung screening. The distinctive feature of our method is to segment aorta and main pulmonary artery using both of prior probability and vascular direction which were estimated from mediastinal vascular region using principal curvatures of four-dimensional hyper surface. The method was applied to two datasets, 64 lowdose CT scans of lung cancer screening and 19 normal-dose CT scans of CTEPH patients through the training phase with 121 low-dose CT scans. This paper demonstrates effectiveness of our method for predicting CTEPH in low-dose CT screening.

Based on BP Neural Network Stock Prediction

ERIC Educational Resources Information Center

Liu, Xiangwei; Ma, Xin

2012-01-01

The stock market has a high profit and high risk features, on the stock market analysis and prediction research has been paid attention to by people. Stock price trend is a complex nonlinear function, so the price has certain predictability. This article mainly with improved BP neural network (BPNN) to set up the stock market prediction model, and…

Electrical Generation for More-Electric Aircraft Using Solid Oxide Fuel Cells

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

Whyatt, Greg A.; Chick, Lawrence A.

This report examines the potential for Solid-Oxide Fuel Cells (SOFC) to provide electrical generation on-board commercial aircraft. Unlike a turbine-based auxiliary power unit (APU) a solid oxide fuel cell power unit (SOFCPU) would be more efficient than using the main engine generators to generate electricity and would operate continuously during flight. The focus of this study is on more-electric aircraft which minimize bleed air extraction from the engines and instead use electrical power obtained from generators driven by the main engines to satisfy all major loads. The increased electrical generation increases the potential fuel savings obtainable through more efficient electricalmore » generation using a SOFCPU. However, the weight added to the aircraft by the SOFCPU impacts the main engine fuel consumption which reduces the potential fuel savings. To investigate these relationships the Boeing 787­8 was used as a case study. The potential performance of the SOFCPU was determined by coupling flowsheet modeling using ChemCAD software with a stack performance algorithm. For a given stack operating condition (cell voltage, anode utilization, stack pressure, target cell exit temperature), ChemCAD software was used to determine the cathode air rate to provide stack thermal balance, the heat exchanger duties, the gross power output for a given fuel rate, the parasitic power for the anode recycle blower and net power obtained from (or required by) the compressor/expander. The SOFC is based on the Gen4 Delphi planar SOFC with assumed modifications to tailor it to this application. The size of the stack needed to satisfy the specified condition was assessed using an empirically-based algorithm. The algorithm predicts stack power density based on the pressure, inlet temperature, cell voltage and anode and cathode inlet flows and compositions. The algorithm was developed by enhancing a model for a well-established material set operating at atmospheric pressure to reflect the effect of elevated pressure and to represent the expected enhancement obtained using a promising cell material set which has been tested in button cells but not yet used to produce full-scale stacks. The predictions for the effect of pressure on stack performance were based on literature. As part of this study, additional data were obtained on button cells at elevated pressure to confirm the validity of the predictions. The impact of adding weight to the 787-8 fuel consumption was determined as a function of flight distance using a PianoX model. A conceptual design for a SOFC power system for the Boeing 787 is developed and the weight estimated. The results indicate that the power density of the stacks must increase by at least a factor of 2 to begin saving fuel on the 787 aircraft. However, the conceptual design of the power system may still be useful for other applications which are less weight sensitive.« less

Development of a questionnaire for assessing factors predicting blood donation among university students: a pilot study.

PubMed

Jalalian, Mehrdad; Latiff, Latiffah; Hassan, Syed Tajuddin Syed; Hanachi, Parichehr; Othman, Mohamed

2010-05-01

University students are a target group for blood donor programs. To develop a blood donation culture among university students, it is important to identify factors used to predict their intent to donate blood. This study attempted to develop a valid and reliable measurement tool to be employed in assessing variables in a blood donation behavior model based on the Theory of Planned Behavior (TPB), a commonly used theoretical foundation for social psychology studies. We employed an elicitation study, in which we determined the commonly held behavioral and normative beliefs about blood donation. We used the results of the elicitation study and a standard format for creating questionnaire items for all constructs of the TPB model to prepare the first draft of the measurement tool. After piloting the questionnaire, we prepared the final draft of the questionnaire to be used in our main study. Examination of internal consistency using Chronbach's alpha coefficient and item-total statistics indicated the constructs "Intention" and "Self efficacy" had the highest reliability. Removing one item from each of the constructs, "Attitude," "Subjective norm," "Self efficacy," or "Behavioral beliefs", can considerably increase the reliability of the measurement tool, however, such action is controversial, especially for the variables "attitude" and "subjective norm." We consider all the items of our first draft questionnaire in our main study to make it a reliable measurement tool.

Water insecurity in 3 dimensions: An anthropological perspective on water and women's psychosocial distress in Ethiopia

PubMed Central

Stevenson, Edward G. J.; Greene, Leslie E.; Maes, Kenneth C.; Ambelu, Argaw; Tesfaye, Yihenew Alemu; Rheingans, Richard; Hadley, Craig

2012-01-01

Water insecurity is a primary underlying determinant of global health disparities. While public health research on water insecurity has focused mainly on two dimensions, water access and adequacy, an anthropological perspective highlights the cultural or lifestyle dimension of water insecurity, and its implications for access / adequacy and for the phenomenology of water insecurity. Recent work in Bolivia has shown that scores on a water insecurity scale derived from ethnographic observations are associated with emotional distress. We extend this line of research by assessing the utility of a locally developed water insecurity scale, compared with standard measures of water access and adequacy, in predicting women's psychosocial distress in Ethiopia. In 2009-2010 we conducted two phases of research. Phase I was mainly qualitative and designed to identify locally relevant experiences of water insecurity, and Phase II used a quantitative survey to test the association between women's reported water insecurity and the Falk Self-Reporting Questionnaire (SRQ-F), a measure of psychosocial distress. In multiple regression models controlling for food insecurity and reported quantity of water used, women's water insecurity scores were significantly associated with psychosocial distress. Including controls for time required to collect water and whether water sources were protected did not further predict psychosocial distress. This approach highlights the social dimension of water insecurity, and may be useful for informing and evaluating interventions to improve water supplies. PMID:22575697

The Impact of Maternal Obesity and Excessive Gestational Weight Gain on Maternal and Infant Outcomes in Maine: Analysis of Pregnancy Risk Assessment Monitoring System Results from 2000 to 2010

PubMed Central

Sarton, Cheryl; Lichter, Erika

2016-01-01

The objective of this study is to understand the relationships between prepregnancy obesity and excessive gestational weight gain (GWG) and adverse maternal and fetal outcomes. Pregnancy risk assessment monitoring system (PRAMS) data from Maine for 2000–2010 were used to determine associations between demographic, socioeconomic, and health behavioral variables and maternal and infant outcomes. Multivariate logistic regression analysis was performed on the independent variables of age, race, smoking, previous live births, marital status, education, BMI, income, rurality, alcohol use, and GWG. Dependent variables included maternal hypertension, premature birth, birth weight, infant admission to the intensive care unit (ICU), and length of hospital stay of the infant. Excessive prepregnancy BMI and excessive GWG independently predicted maternal hypertension. A high prepregnancy BMI increased the risk of the infant being born prematurely, having a longer hospital stay, and having an excessive birth weight. Excessive GWG predicted a longer infant hospital stay and excessive birth weight. A low pregnancy BMI and a lower than recommended GWG were also associated with poor outcomes: prematurity, low birth weight, and an increased risk of the infant admitted to ICU. These findings support the importance of preconception care that promotes achievement of a healthy weight to enhance optimal reproductive outcomes. PMID:27747104

Hard breakup of the deuteron into two Δ isobars

NASA Astrophysics Data System (ADS)

Granados, Carlos G.; Sargsian, Misak M.

2011-05-01

We study high-energy photodisintegration of the deuteron into two Δ isobars at large center of mass angles within the QCD hard rescattering model (HRM). According to the HRM, the process develops in three main steps: the photon knocks a quark from one of the nucleons in the deuteron; the struck quark rescatters off a quark from the other nucleon sharing the high energy of the photon; then the energetic quarks recombine into two outgoing baryons which have large transverse momenta. Within the HRM, the cross section is expressed through the amplitude of pn→ΔΔ scattering which we evaluated based on the quark-interchange model of hard hadronic scattering. Calculations show that the angular distribution and the strength of the photodisintegration is mainly determined by the properties of the pn→ΔΔ scattering. We predict that the cross section of the deuteron breakup to Δ++Δ- is 4-5 times larger than that of the breakup to the Δ+Δ0 channel. Also, the angular distributions for these two channels are markedly different. These can be compared with the predictions based on the assumption that two hard Δ isobars are the result of the disintegration of the preexisting ΔΔ components of the deuteron wave function. In this case, one expects the angular distributions and cross sections of the breakup in both Δ++Δ- and Δ+Δ0 channels to be similar.

Mixing with applications to inertial-confinement-fusion implosions

NASA Astrophysics Data System (ADS)

Rana, V.; Lim, H.; Melvin, J.; Glimm, J.; Cheng, B.; Sharp, D. H.

2017-01-01

Approximate one-dimensional (1D) as well as 2D and 3D simulations are playing an important supporting role in the design and analysis of future experiments at National Ignition Facility. This paper is mainly concerned with 1D simulations, used extensively in design and optimization. We couple a 1D buoyancy-drag mix model for the mixing zone edges with a 1D inertial confinement fusion simulation code. This analysis predicts that National Ignition Campaign (NIC) designs are located close to a performance cliff, so modeling errors, design features (fill tube and tent) and additional, unmodeled instabilities could lead to significant levels of mix. The performance cliff we identify is associated with multimode plastic ablator (CH) mix into the hot-spot deuterium and tritium (DT). The buoyancy-drag mix model is mode number independent and selects implicitly a range of maximum growth modes. Our main conclusion is that single effect instabilities are predicted not to lead to hot-spot mix, while combined mode mixing effects are predicted to affect hot-spot thermodynamics and possibly hot-spot mix. Combined with the stagnation Rayleigh-Taylor instability, we find the potential for mix effects in combination with the ice-to-gas DT boundary, numerical effects of Eulerian species CH concentration diffusion, and ablation-driven instabilities. With the help of a convenient package of plasma transport parameters developed here, we give an approximate determination of these quantities in the regime relevant to the NIC experiments, while ruling out a variety of mix possibilities. Plasma transport parameters affect the 1D buoyancy-drag mix model primarily through its phenomenological drag coefficient as well as the 1D hydro model to which the buoyancy-drag equation is coupled.

Mixing with applications to inertial-confinement-fusion implosions.

PubMed

Rana, V; Lim, H; Melvin, J; Glimm, J; Cheng, B; Sharp, D H

2017-01-01

Approximate one-dimensional (1D) as well as 2D and 3D simulations are playing an important supporting role in the design and analysis of future experiments at National Ignition Facility. This paper is mainly concerned with 1D simulations, used extensively in design and optimization. We couple a 1D buoyancy-drag mix model for the mixing zone edges with a 1D inertial confinement fusion simulation code. This analysis predicts that National Ignition Campaign (NIC) designs are located close to a performance cliff, so modeling errors, design features (fill tube and tent) and additional, unmodeled instabilities could lead to significant levels of mix. The performance cliff we identify is associated with multimode plastic ablator (CH) mix into the hot-spot deuterium and tritium (DT). The buoyancy-drag mix model is mode number independent and selects implicitly a range of maximum growth modes. Our main conclusion is that single effect instabilities are predicted not to lead to hot-spot mix, while combined mode mixing effects are predicted to affect hot-spot thermodynamics and possibly hot-spot mix. Combined with the stagnation Rayleigh-Taylor instability, we find the potential for mix effects in combination with the ice-to-gas DT boundary, numerical effects of Eulerian species CH concentration diffusion, and ablation-driven instabilities. With the help of a convenient package of plasma transport parameters developed here, we give an approximate determination of these quantities in the regime relevant to the NIC experiments, while ruling out a variety of mix possibilities. Plasma transport parameters affect the 1D buoyancy-drag mix model primarily through its phenomenological drag coefficient as well as the 1D hydro model to which the buoyancy-drag equation is coupled.

Indoor determinants of dustborne allergens in Mexican homes

PubMed Central

Hernández-Cadena, Leticia; Zeldin, Darryl C.; Sever, Michelle L.; Sly, Peter D.; London, Stephanie J.; Escamilla-Nuñez, María Consuelo; Romieu, Isabelle

2015-01-01

Exposure to indoor allergens represents a significant risk factor for allergies and asthma in several parts of the world. In Mexico, few studies have evaluated indoor allergens, including cat, dog, and mouse allergens and the factors that predict their presence. This study evaluates the main environmental and household predictors of high prenatal allergen levels and multiple allergen exposures in a birth cohort from Mexico City. A cross-sectional study was conducted as part of a birth cohort study of 1094 infants recruited during pregnancy and followed until delivery. We collected dust samples in a subset of 264 homes and assessed environmental factors. Der p 1, Der f 1, dust mite group 2, Fel d 1, Can f 1, Rat n 1, Mus m 1, and Bla g 2 concentrations in dust samples were measured using immunoassays. To define detectable allergen levels, the lowest limits of detection for each allergen were taken as cutoff points. Overall allergen exposure was considered high when four or more allergens exceeded detectable levels in the same household. Logistic regression was used for predictive models. Eighty-five percent of homes had at least one allergen in dust over the detection limit, 52.1% had high exposure (four or more allergens above detectable limits), and 11.7% of homes had detectable levels for more than eight allergens. Der p 1, Der p 2, Mus m 1, and Fel d 1 were the most frequent allergens detected. Each allergen had both common and distinct predictors. The main predictors of a high multiple allergen index were the size of the home, pesticide use, mother's age, mother as homemaker, and season. Increased indoor environmental allergen exposure is mainly related to sociodemographic factors and household cleaning. PMID:25715241

Discrimination of wine from grape cultivated in Japan, imported wine, and others by multi-elemental analysis.

PubMed

Shimizu, Hideaki; Akamatsu, Fumikazu; Kamada, Aya; Koyama, Kazuya; Okuda, Masaki; Fukuda, Hisashi; Iwashita, Kazuhiro; Goto-Yamamoto, Nami

2018-04-01

Differences in mineral concentrations were examined among three types of wine in the Japanese market place: Japan wine, imported wine, and domestically produced wine mainly from foreign ingredients (DWF), where Japan wine has been recently defined by the National Tax Agency as domestically produced wine from grapes cultivated in Japan. The main objective of this study was to examine the possibility of controlling the authenticity of Japan wine. The concentrations of 18 minerals (Li, B, Na, Mg, Si, P, S, K, Ca, Mn, Co, Ni, Ga, Rb, Sr, Mo, Ba, and Pb) in 214 wine samples were determined by inductively coupled-plasma mass spectrometry (ICP-MS) and ICP-atomic emission spectrometry (ICP-AES). In general, Japan wine had a higher concentration of potassium and lower concentrations of eight elements (Li, B, Na, Si, S, Co, Sr, and Pb) as compared with the other two groups of wine. Linear discriminant analysis (LDA) models based on concentrations of the 18 minerals facilitated the identification of three wine groups: Japan wine, imported wine, and DWF with a 91.1% classification score and 87.9% prediction score. In addition, an LDA model for discrimination of wine from four domestic geographic origins (Yamanashi, Nagano, Hokkaido, and Yamagata Prefectures) using 18 elements gave a classification score of 93.1% and a prediction score of 76.4%. In summary, we have shown that an LDA model based on mineral concentrations is useful for distinguishing Japan wine from other wine groups, and can contribute to classification of the four main domestic wine-producing regions of Japan. Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Characterization of Volatiles Loss from Soil Samples at Lunar Environments

NASA Technical Reports Server (NTRS)

Kleinhenz, Julie; Smith, Jim; Roush, Ted; Colaprete, Anthony; Zacny, Kris; Paulsen, Gale; Wang, Alex; Paz, Aaron

2017-01-01

Resource Prospector Integrated Thermal Vacuum Test Program A series of ground based dirty thermal vacuum tests are being conducted to better understand the subsurface sampling operations for RP Volatiles loss during sampling operations Hardware performance Sample removal and transfer Concept of operationsInstrumentation5 test campaigns over 5 years have been conducted with RP hardware with advancing hardware designs and additional RP subsystems Volatiles sampling 4 years Using flight-forward regolith sampling hardware, empirically determine volatile retention at lunar-relevant conditions Use data to improve theoretical predictions Determine driving variables for retention Bound water loss potential to define measurement uncertainties. The main goal of this talk is to introduce you to our approach to characterizing volatiles loss for RP. Introduce the facility and its capabilities Overview of the RP hardware used in integrated testing (most recent iteration) Summarize the test variables used thus farReview a sample of the results.

Correlation measurements in nuclear {beta}-decay using traps and polarized low energy beams

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

Naviliat-Cuncic, Oscar

2013-05-06

Precision measurements in nuclear {beta}-decay provide sensitive means to test discrete symmetries in the weak interaction and to determine some of the fundamental constants in semi-leptonic decays, like the coupling of the lightest quarks to charged weak bosons. The main motivation of such measurements is to find deviations from Standard Model predictions as possible indications of new physics. In this contribution I will focus on two topics related to precision measurements in nuclear {beta}-decay: i) the determination of the V{sub ud} element of the Cabibbo-Kobayashi-Maskawa quark mixing matrix from nuclear mirror transitions and ii) the search for exotic scalar ormore » tensor contributions from {beta}{nu} angular correlations. The purpose is to underline the role being played by experimental techniques based on the confinement of radioactive species with atom and ion traps as well as the plans to use low energy polarized beams.« less

Thermal fatigue behaviour for a 316 L type steel

NASA Astrophysics Data System (ADS)

Fissolo, A.; Marini, B.; Nais, G.; Wident, P.

1996-10-01

This paper deals with initiation and growth of cracks produced by thermal fatigue loadings on 316 L steel, which is a reference material for the first wall of the next fusion reactor ITER. Two types of facilities have been built. As for true components, thermal cycles have been repeatedly applied on the surface of the specimen. The first is mainly concerned with initiation, which is detected with a light microscope. The second allows one to determine the propagation of a single crack. Crack initiation is analyzed using the French RCC-MR code procedure, and the strain-controlled isothermal fatigue curves. To predict crack growth, a model previously proposed by Haigh and Skelton is applied. This is based on determination of effective stress intensity factors, which takes into account both plastic strain and crack closure phenomena. It is shown that estimations obtained with such methodologies are in good agreement with experimental data.

NIR technology for on-line determination of superficial a(w) and moisture content during the drying process of fermented sausages.

PubMed

Collell, Carles; Gou, Pere; Arnau, Jacint; Muñoz, Israel; Comaposada, Josep

2012-12-01

Three different NIR equipment were evaluated based on their ability to predict superficial water activity (a(w)) and moisture content in two types of fermented sausages (with and without moulds on surface), using partial least squares (PLS) regression models. The instruments differed mainly in wavelength range, resolution and measurement configuration. The most accurate equipment was used in a new experiment to achieve robust models in sausages with different salt contents and submitted to different drying conditions. The models developed showed determination coefficients (R(2)(P)) values of 0.990, 0.910 and 0.984, and RMSEP values of 1.560%, 0.220% and 0.007% for moisture, salt and a(w) respectively. It was demonstrated that NIR spectroscopy could be a suitable non-destructive method for on-line monitoring and control of the drying process in fermented sausages. Copyright © 2012 Elsevier Ltd. All rights reserved.

Clinical stage I carcinoma of the cervix. Value of MR imaging in determining invasion into the parametrium.

PubMed

Lien, H H; Blomlie, V; Iversen, T; Tropé, C; Sundfør, K; Abeler, V M

1993-03-01

Using MR imaging with a body coil parametrial invasion was determined prospectively in 169 consecutive patients considered on the basis of clinical examination to have carcinoma confined to the cervix. After radical hysterectomy correlation with histologic examination was performed for the left and right parametrium separately. The criterion for parametrial invasion was a high-signal-intensity lesion with disruption of the full thickness of the cervical stroma combined with areas of abnormal signal intensity within the parametrial region on T2-weighted images. Histologic examination showed that 18 parametria in 13 patients were invaded by tumor. MR had an overall accuracy of 93%, a sensitivity of 89%, and a specificity of 93% in demonstrating parametrial involvement. Positive and negative predictive values were 43% and 99%. The main weakness of MR was 21 false-positive tests. This represents a limitation when MR is performed with a body coil.

Quantitative imaging of carbon dimer precursor for nanomaterial synthesis in the carbon arc

DOE PAGES

Vekselman, V.; Khrabry, A.; Kaganovich, I.; ...

2018-02-06

Delineating the dominant processes responsible for nanomaterial synthesis in a plasma environment requires measurements of the precursor species contributing to the growth of nanostructures. Here, we performed comprehensive measurements of spatial and temporal profiles of carbon dimers (C 2) in sub-atmospheric-pressure carbon arc by laser-induced fluorescence. Measured spatial profiles of C 2 coincide with the growth region of carbon nanotubes (Fang et al 2016 Carbon 107 273–80) and vary depending on the arc operation mode, which is determined by the discharge current and the ablation rate of the graphite anode. The C 2 density profile exhibits large spatial and timemore » variations due to motion of the arc core. A comparison of the experimental data with the 2D simulation results of self-consistent arc modeling shows good agreement. The model predicts well the main processes determining spatial profiles of carbon dimers (C 2).« less

Short-Arc Orbit Determination Results and Space Debris Test Observation of the OWL-Net

NASA Astrophysics Data System (ADS)

Choi, J.; Jo, J.; Yim, H.

Korea Astronomy and Space Science Institute had developed the Optical Wide-field patroL-Network (OWL-Net) for maintaining the domestic Low Earth Orbit satellites’ ephemeris and monitoring Geostationary Earth Orbit region. It also can be used to observe space debris. The orbit determination process was planned with batch least square orbit estimator for every week. The optical tracking window is very narrow, several times per week. Sequentialbatch type estimation strategy was attempted for more reliable orbit prediction. We compared the test operation results with Two Line Elements and CPF files to validate the system. This results can be used to estimate the performance of the OWL-Net operations. And also we had observation of the Astro-H debris. We got the dozens of photometric data of the Astro-H debris main part for a few seconds with the chopper system.

Interpersonal reactivity index: analysis of invariance and gender differences in spanish youths.

PubMed

Holgado Tello, Francisco Pablo; Delgado Egido, Begoña; Carrasco Ortiz, Miguel A; Del Barrio Gandara, M V

2013-04-01

Empathy is understood as a multidimensional construct involving both cognitive and emotional factors for which, traditionally, gender differences have been reported. The Interpersonal Reactivity Index (Davis in Catalog Sel Documents Psychol 10:1-19, 1980) is an instrument made up of four subscales, each measuring a different dimension of the global concept of empathy. Attending to gender differences, the present study's objective is twofold. First, it aims to determine, conceptually speaking, whether or not the model analyzed by this instrument is equivalent for the two sexes. Second, it aims to determine which dimensions involved in empathy most strongly predict gender differences. The results convey that the proposed model is invariant between boys and girls, although the dimensions exhibited significant differences of magnitude as a function of sex. Mainly two variables (Considerate Social Style and Impassiveness) were capable of distinguishing between men and women. Possible reasons for these results are also discussed.

Quantitative imaging of carbon dimer precursor for nanomaterial synthesis in the carbon arc

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

Vekselman, V.; Khrabry, A.; Kaganovich, I.

Delineating the dominant processes responsible for nanomaterial synthesis in a plasma environment requires measurements of the precursor species contributing to the growth of nanostructures. Here, we performed comprehensive measurements of spatial and temporal profiles of carbon dimers (C 2) in sub-atmospheric-pressure carbon arc by laser-induced fluorescence. Measured spatial profiles of C 2 coincide with the growth region of carbon nanotubes (Fang et al 2016 Carbon 107 273–80) and vary depending on the arc operation mode, which is determined by the discharge current and the ablation rate of the graphite anode. The C 2 density profile exhibits large spatial and timemore » variations due to motion of the arc core. A comparison of the experimental data with the 2D simulation results of self-consistent arc modeling shows good agreement. The model predicts well the main processes determining spatial profiles of carbon dimers (C 2).« less

Determinants of mortality in systemic sclerosis: a focused review.

PubMed

Poudel, Dilli Ram; Jayakumar, Divya; Danve, Abhijeet; Sehra, Shiv Tej; Derk, Chris T

2017-11-07

Scleroderma (systemic sclerosis) is an autoimmune rheumatic disorder that is characterized by fibrosis, vascular dysfunction, and autoantibody production that involves most visceral organs. It is characterized by a high morbidity and mortality rate, mainly due to disease-related complications. Epidemiological data describing mortality and survival in this population have been based on both population and observational studies. Multiple clinical and non-clinical factors have been found to predict higher likelihood of death among thepatients. Here, we do an extensive review of the available literature, utilizing the PubMed database, to describe scleroderma and non-scleroderma related determinants of mortality in this population. We found that even though the mortality among the general population has declined, scleroderma continues to carry a very high morbidity and mortality rate, however we have made some slow progress in improving the mortality among scleroderma patients over the last few decades.

Evaluation and Prediction of Water Resources Based on AHP

NASA Astrophysics Data System (ADS)

Li, Shuai; Sun, Anqi

2017-01-01

Nowadays, the shortage of water resources is a threat to us. In order to solve the problem of water resources restricted by varieties of factors, this paper establishes a water resources evaluation index model (WREI), which adopts the fuzzy comprehensive evaluation (FCE) based on analytic hierarchy process (AHP) algorithm. After considering influencing factors of water resources, we ignore secondary factors and then hierarchical approach the main factors according to the class, set up a three-layer structure. The top floor is for WREI. Using analytic hierarchy process (AHP) to determine weight first, and then use fuzzy judgment to judge target, so the comprehensive use of the two algorithms reduce the subjective influence of AHP and overcome the disadvantages of multi-level evaluation. To prove the model, we choose India as a target region. On the basis of water resources evaluation index model, we use Matlab and combine grey prediction with linear prediction to discuss the ability to provide clean water in India and the trend of India’s water resources changing in the next 15 years. The model with theoretical support and practical significance will be of great help to provide reliable data support and reference for us to get plans to improve water quality.

Metazoan parasite infracommunities of Florida pompano (Trachinotus carolinus) from the coast of the Yucatan Peninsula, Mexico.

PubMed

Sánchez-Ramírez, Claudia; Vidal-Martínez, Victor M

2002-12-01

Metazoan parasite infracommunities of the Florida pompano (Trachinotus carolinus) were studied in terms of species composition, species richness, diversity, numerical dominance, and similarity. Seventy-five fishes were collected from 4 localities along the Yucatan Peninsula coast and 24 parasite species recovered. Most were digeneans (8 species) and nematodes (7). Other species were monogeneans (3). aspidogastreans (2), cestodes (1), acanthocephalans (1), and crustaceans (2). Only 4 species were common in at least I locality. Mean values for species richness, abundance, diversity, numerical dominance, and similarity in total (all species in the individual fish), gastrointestinal, and ectoparasite infracommunities were within ranges observed for most helminth infracommunities of marine fishes from temperate and tropical latitudes. These infracommunities had low species richness, abundance, diversity, and predictability (except ectoparasite infracommunities) and high dominance. Within the predictable element (common species), the specialist monogenean Pseudobicotylophora atlantica was the main reason for the increase in predictability because it was the only common species at all 4 localities. Host feeding habits, the distribution of intermediate hosts and infective stages, the local species pool, and a phylogenetic component seem to be determining the characteristics of these metazoan parasite infracommunities.

Determinants of satisfaction with the health state of the facial skin in patients undergoing surgery for facial basal cell carcinoma.

PubMed

Essers, Brigitte A B; Nieman, Fred H M; Prins, Martin H; Krekels, Gertruud A M; Smeets, Nicole W J; Neumann, H A Martino

2006-02-01

The main objective of the study was to assess which health beliefs predict and explain satisfaction with the facial health state of patients undergoing surgery for basal cell carcinoma. Data were collected by administering a newly developed questionnaire pre-operatively and 6 months post-operatively (n = 222). Results show that satisfaction as measured by post-operative worrying, susceptibility and fear of developing a new BCC at other facial sites can be predicted by pre-operative health beliefs. In addition, some patients an increase in perceived susceptibility, fear of recurrence of BCC on the same site or fear of developing a new BCC at other facial sites. Our findings indicate that both pre- and post-operative perceptions predict and explain for a substantial part the extent to which patients are satisfied with their facial health state 6 months after surgery. Administering a short questionnaire at the start of the treatment period will give physicians a better understanding of how patients experience this skin disease. It will also help them to adjust information about BCC and its consequences to the needs of the patient.

Application of Visual Attention in Seismic Attribute Analysis

NASA Astrophysics Data System (ADS)

He, M.; Gu, H.; Wang, F.

2016-12-01

It has been proved that seismic attributes can be used to predict reservoir. The joint of multi-attribute and geological statistics, data mining, artificial intelligence, further promote the development of the seismic attribute analysis. However, the existing methods tend to have multiple solutions and insufficient generalization ability, which is mainly due to the complex relationship between seismic data and geological information, and undoubtedly own partly to the methods applied. Visual attention is a mechanism model of the human visual system which can concentrate on a few significant visual objects rapidly, even in a mixed scene. Actually, the model qualify good ability of target detection and recognition. In our study, the targets to be predicted are treated as visual objects, and an object representation based on well data is made in the attribute dimensions. Then in the same attribute space, the representation is served as a criterion to search the potential targets outside the wells. This method need not predict properties by building up a complicated relation between attributes and reservoir properties, but with reference to the standard determined before. So it has pretty good generalization ability, and the problem of multiple solutions can be weakened by defining the threshold of similarity.

Thermal/Pyrolysis Gas Flow Analysis of Carbon Phenolic Material

NASA Technical Reports Server (NTRS)

Clayton, J. Louie

2001-01-01

Provided in this study are predicted in-depth temperature and pyrolysis gas pressure distributions for carbon phenolic materials that are externally heated with a laser source. Governing equations, numerical techniques and comparisons to measured temperature data are also presented. Surface thermochemical conditions were determined using the Aerotherm Chemical Equilibrium (ACE) program. Surface heating simulation used facility calibrated radiative and convective flux levels. Temperatures and pyrolysis gas pressures are predicted using an upgraded form of the SINDA/CMA program that was developed by NASA during the Solid Propulsion Integrity Program (SPIP). Multispecie mass balance, tracking of condensable vapors, high heat rate kinetics, real gas compressibility and reduced mixture viscosity's have been added to the algorithm. In general, surface and in-depth temperature comparisons are very good. Specie partial pressures calculations show that a saturated water-vapor mixture is the main contributor to peak in-depth total pressure. Further, for most of the cases studied, the water-vapor mixture is driven near the critical point and is believed to significantly increase the local heat capacity of the composite material. This phenomenon if not accounted for in analysis models may lead to an over prediction in temperature response in charring regions of the material.

Comparison between Canadian Canola Harvest and Export Surveys.

PubMed

Barthet, Véronique J

2016-07-20

Parameters, such as oil, protein, glucosinolates, chlorophyll content and fatty acid composition, were determined using reference methods for both harvest survey samples and Canadian Canola exports. Canola harvest survey and export data were assessed to evaluate if canola harvest survey data can be extrapolated to predict the quality of the Canadian canola exports. There were some differences in some measured parameters between harvest and export data, while other parameters showed little difference. Protein content and fatty acid composition showed very similar data for harvest and export averages. Canadian export data showed lower oil content when compared to the oil content of harvest survey was mainly due to a diluting effect of dockage in the export cargoes which remained constant over the years (1.7% to 1.9%). Chlorophyll was the least predictable parameter; dockage quality as well as commingling of the other grades in Canola No. 1 Canada affected the chlorophyll content of the exports. Free fatty acids (FFA) were also different for the export and harvest survey. FFA levels are affected by storage conditions; they increase during the shipping season and, therefore, are difficult to predict from their harvest survey averages.

The prospective relationship between role stressors and new cases of self-reported workplace bullying.

PubMed

Reknes, Iselin; Einarsen, Ståle; Knardahl, Stein; Lau, Bjørn

2014-02-01

In line with the "Work environment hypothesis," role stressors have been proposed as important antecedents of bullying in the workplace. Only a few longitudinal studies on the relationship between role stressors and bullying exist, however, and earlier studies have largely been cross-sectional. The aim of the present prospective study was to determine whether role stressors at baseline predict new cases of workplace bullying at follow-up. A total of 2,835 Norwegian employees participated at both baseline and follow-up, with an interval of two years between the measurements. The study supports the hypotheses that role ambiguity and role conflict, independently, contribute to subsequent new reports of workplace bullying. However, there was a weak reverse effect: reporting being bullied at work at baseline predicted reporting increased levels of role ambiguity and role conflict at follow-up. Even though the results may indicate a circular relationship between the variables at hand, the weak reverse relationship seems to have little practical impact compared to the stronger relationship from role stressors to bullying. Hence, the results mainly support the hypotheses stating that role ambiguity and role conflict, independently, predict subsequent exposure to workplace bullying.

A predictive model for recurrence in patients with glottic cancer implemented in a mobile application for Android.

PubMed

Jover-Esplá, Ana Gabriela; Palazón-Bru, Antonio; Folgado-de la Rosa, David Manuel; Severá-Ferrándiz, Guillermo; Sancho-Mestre, Manuela; de Juan-Herrero, Joaquín; Gil-Guillén, Vicente Francisco

2018-05-01

The existing predictive models of laryngeal cancer recurrence present limitations for clinical practice. Therefore, we constructed, internally validated and implemented in a mobile application (Android) a new model based on a points system taking into account the internationally recommended statistical methodology. This longitudinal prospective study included 189 patients with glottic cancer in 2004-2016 in a Spanish region. The main variable was time-to-recurrence, and its potential predictors were: age, gender, TNM classification, stage, smoking, alcohol consumption, and histology. A points system was developed to predict five-year risk of recurrence based on a Cox model. This was validated internally by bootstrapping, determining discrimination (C-statistics) and calibration (smooth curves). A total of 77 patients presented recurrence (40.7%) in a mean follow-up period of 3.4 ± 3.0 years. The factors in the model were: age, lymph node stage, alcohol consumption and stage. Discrimination and calibration were satisfactory. A points system was developed to obtain the probability of recurrence of laryngeal glottic cancer in five years, using five clinical variables. Our system should be validated externally in other geographical areas. Copyright © 2018 Elsevier Ltd. All rights reserved.

Validation of Shoulder Response of Human Body Finite-Element Model (GHBMC) Under Whole Body Lateral Impact Condition.

PubMed

Park, Gwansik; Kim, Taewung; Panzer, Matthew B; Crandall, Jeff R

2016-08-01

In previous shoulder impact studies, the 50th-percentile male GHBMC human body finite-element model was shown to have good biofidelity regarding impact force, but under-predicted shoulder deflection by 80% compared to those observed in the experiment. The goal of this study was to validate the response of the GHBMC M50 model by focusing on three-dimensional shoulder kinematics under a whole-body lateral impact condition. Five modifications, focused on material properties and modeling techniques, were introduced into the model and a supplementary sensitivity analysis was done to determine the influence of each modification to the biomechanical response of the body. The modified model predicted substantially improved shoulder response and peak shoulder deflection within 10% of the observed experimental data, and showed good correlation in the scapula kinematics on sagittal and transverse planes. The improvement in the biofidelity of the shoulder region was mainly due to the modifications of material properties of muscle, the acromioclavicular joint, and the attachment region between the pectoralis major and ribs. Predictions of rib fracture and chest deflection were also improved because of these modifications.

Development of the statistical ARIMA model: an application for predicting the upcoming of MJO index

NASA Astrophysics Data System (ADS)

Hermawan, Eddy; Nurani Ruchjana, Budi; Setiawan Abdullah, Atje; Gede Nyoman Mindra Jaya, I.; Berliana Sipayung, Sinta; Rustiana, Shailla

2017-10-01

This study is mainly concerned in development one of the most important equatorial atmospheric phenomena that we call as the Madden Julian Oscillation (MJO) which having strong impacts to the extreme rainfall anomalies over the Indonesian Maritime Continent (IMC). In this study, we focused to the big floods over Jakarta and surrounded area that suspecting caused by the impacts of MJO. We concentrated to develop the MJO index using the statistical model that we call as Box-Jenkis (ARIMA) ini 1996, 2002, and 2007, respectively. They are the RMM (Real Multivariate MJO) index as represented by RMM1 and RMM2, respectively. There are some steps to develop that model, starting from identification of data, estimated, determined model, before finally we applied that model for investigation some big floods that occurred at Jakarta in 1996, 2002, and 2007 respectively. We found the best of estimated model for the RMM1 and RMM2 prediction is ARIMA (2,1,2). Detailed steps how that model can be extracted and applying to predict the rainfall anomalies over Jakarta for 3 to 6 months later is discussed at this paper.

Comparison between Canadian Canola Harvest and Export Surveys

PubMed Central

Barthet, Véronique J.

2016-01-01

Parameters, such as oil, protein, glucosinolates, chlorophyll content and fatty acid composition, were determined using reference methods for both harvest survey samples and Canadian Canola exports. Canola harvest survey and export data were assessed to evaluate if canola harvest survey data can be extrapolated to predict the quality of the Canadian canola exports. There were some differences in some measured parameters between harvest and export data, while other parameters showed little difference. Protein content and fatty acid composition showed very similar data for harvest and export averages. Canadian export data showed lower oil content when compared to the oil content of harvest survey was mainly due to a diluting effect of dockage in the export cargoes which remained constant over the years (1.7% to 1.9%). Chlorophyll was the least predictable parameter; dockage quality as well as commingling of the other grades in Canola No. 1 Canada affected the chlorophyll content of the exports. Free fatty acids (FFA) were also different for the export and harvest survey. FFA levels are affected by storage conditions; they increase during the shipping season and, therefore, are difficult to predict from their harvest survey averages. PMID:27447675

Conversion gain and noise of niobium superconducting hot-electron-mixers

NASA Technical Reports Server (NTRS)

Ekstrom, Hans; Karasik, Boris S.; Kollberg, Erik L.; Yngvesson, Sigfrid

1995-01-01

A study has been done of microwave mixing at 20 GHz using the nonlinear (power dependent) resistance of thin niobium strips in the resistive state. Our experiments give evidence that electron-heating is the main cause of the nonlinear phenomenon. Also a detailed phenomenological theory for the determination of conversion properties is presented. This theory is capable of predicting the frequency-conversion loss rather accurately for arbitrary bias by examining the I-V-characteristic. Knowing the electron temperature relaxation time, and using parameters derived from the I-V-characteristic also allows us to predict the -3 dB IF bandwidth. Experimental results are in excellent agreement with the theoretical predictions. The requirements on the mode of operation and on the film parameters for minimizing the conversion loss (and even achieving conversion gain) are discussed in some detail. Our measurements demonstrate an intrinsic conversion loss as low as 1 dB. The maximum IF frequency defined for -3 dB drop in conversion gain, is about 80 MHz. Noise measurements indicate a device output noise temperature of about 50 K and SSB mixer noise temperature below 250 K. This type of mixer is considered very promising for use in low-noise heterodyne receivers at THz frequencies.

Study on the Influence of Building Materials on Indoor Pollutants and Pollution Sources

NASA Astrophysics Data System (ADS)

Wang, Yao

2018-01-01

The paper summarizes the achievements and problems of indoor air quality research at home and abroad. The pollutants and pollution sources in the room are analyzed systematically. The types of building materials and pollutants are also discussed. The physical and chemical properties and health effects of main pollutants were analyzed and studied. According to the principle of mass balance, the basic mathematical model of indoor air quality is established. Considering the release rate of pollutants and indoor ventilation, a mathematical model for predicting the concentration of indoor air pollutants is derived. The model can be used to analyze and describe the variation of pollutant concentration in indoor air, and to predict and calculate the concentration of pollutants in indoor air at a certain time. The results show that the mathematical model established in this study can be used to analyze and predict the variation law of pollutant concentration in indoor air. The evaluation model can be used to evaluate the impact of indoor air quality and evaluation of current situation. Especially in the process of building and interior decoration, through pre-evaluation, it can provide reliable design parameters for selecting building materials and determining ventilation volume.

A spatially distributed model for the dynamic prediction of sediment erosion and transport in mountainous forested watersheds

NASA Astrophysics Data System (ADS)

Doten, Colleen O.; Bowling, Laura C.; Lanini, Jordan S.; Maurer, Edwin P.; Lettenmaier, Dennis P.

2006-04-01

Erosion and sediment transport in a temperate forested watershed are predicted with a new sediment model that represents the main sources of sediment generation in forested environments (mass wasting, hillslope erosion, and road surface erosion) within the distributed hydrology-soil-vegetation model (DHSVM) environment. The model produces slope failures on the basis of a factor-of-safety analysis with the infinite slope model through use of stochastically generated soil and vegetation parameters. Failed material is routed downslope with a rule-based scheme that determines sediment delivery to streams. Sediment from hillslopes and road surfaces is also transported to the channel network. A simple channel routing scheme is implemented to predict basin sediment yield. We demonstrate through an initial application of this model to the Rainy Creek catchment, a tributary of the Wenatchee River, which drains the east slopes of the Cascade Mountains, that the model produces plausible sediment yield and ratios of landsliding and surface erosion when compared to published rates for similar catchments in the Pacific Northwest. A road removal scenario and a basin-wide fire scenario are both evaluated with the model.

23 CFR 772.17 - Traffic noise prediction.

Code of Federal Regulations, 2010 CFR

2010-04-01

..._federal_regulations/ibr_locations.html. These documents are available for copying and inspection at the... URL: http://www.trafficnoisemodel.org/main.html. (b) In predicting noise levels and assessing noise...

ESTIMATING THE RADIUS OF THE CONVECTIVE CORE OF MAIN-SEQUENCE STARS FROM OBSERVED OSCILLATION FREQUENCIES

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

Yang, Wuming, E-mail: yangwuming@bnu.edu.cn, E-mail: yangwuming@ynao.ac.cn

The determination of the size of the convective core of main-sequence stars is usually dependent on the construction of models of stars. Here we introduce a method to estimate the radius of the convective core of main-sequence stars with masses between about 1.1 and 1.5 M {sub ⊙} from observed frequencies of low-degree p -modes. A formula is proposed to achieve the estimation. The values of the radius of the convective core of four known stars are successfully estimated by the formula. The radius of the convective core of KIC 9812850 estimated by the formula is 0.140 ± 0.028 Rmore » {sub ⊙}. In order to confirm this prediction, a grid of evolutionary models was computed. The value of the convective-core radius of the best-fit model of KIC 9812850 is 0.149 R {sub ⊙}, which is in good agreement with that estimated by the formula from observed frequencies. The formula aids in understanding the interior structure of stars directly from observed frequencies. The understanding is not dependent on the construction of models.« less

The influence of meteorological conditions on the progress and dynamics of pollen phenophases of selected species.

NASA Astrophysics Data System (ADS)

Jatczak, K.; Linkowska, J.; Rapiejko, P.

2010-09-01

In Poland phenological data is used mainly as a natural indicator of the influence of climate changes on environment. In relation to the growing interest of phenology in scientific research, we substantially extended observation ranges, concentrating mainly on phenophases of selected species that are important for allergology. Phenological data application in complex analysis together with meteorological and aerobiological data, give an opportunity for drawing conclusions on variability of the starting date of pollen season and its dynamics in a meteorological aspect. Species have their regional phenological characteristics, however the characteristics depends on meteorological conditions in a particular year. Therefore, the calculation of pheno-meteorological parameters is important for pollen release prediction. Availability of phenological database can also be useful in the field of preventive health care, through phenological data application in different atmospheric models (NWP models, phenological models, pollen release models) for numerical forecasting of pollen concentration in the air. Genetic conditions, industrial development, increase of air pollution are regarded as the main determinants of allergic diseases. The results of pheno - aero- meteorological analysis enable the estimation of the influence of natural environmental changes on the increasing prevalence of allergic diseases in Poland.

Gamma glutamyl transferase and oxidative stress in obstructive sleep apnea: a study in 1744 patients.

PubMed

Sánchez-Armengol, A; Villalobos-López, P; Caballero-Eraso, C; Carmona-Bernal, C; Asensio-Cruz, M; Barbé, F; Capote, F

2015-09-01

We analyze a large population of patients to determine whether gamma glutamyl transferase (GGT) levels are increased in sleep apnea-hypopnea syndrome (OSA) and whether these levels are related to clinical characteristics or polygraphic indexes. A cross-sectional study in a population of 1744 patients referred for OSA suspicion was conducted. The following variables were determined: glucose, cholesterol, triglycerides, aspartate aminotransferase (GOT), alanine aminotransferase (GPT), GGT, body mass index, waist-hip ratio (WHR), and overnight sleep study. The 483 patients with GGT ≥40 IU/l were younger and more obese, and had a pattern of more centrally distributed fat than the 1261 with GGT <40 IU/l. Patients with high levels of GGT also consumed more alcohol, had a poorer biochemical profile, and had more respiratory and oximetric alterations during sleep. GGT levels were significantly correlated with AHI, DI, and CT90. In the binary regression test, WHR, glucose, cholesterol, triglycerides, and grams of alcohol consumed per day predicted GGT levels ≥40 IU/l, while none of the polygraphic variables had predictive value. High GGT levels were associated with the severity of OSA. However, this relationship seems to be due to the coexistence of other associated factors, mainly central obesity, rather than to the respiratory disorders found in this disease.

THE STATISTICAL MECHANICS OF PLANET ORBITS

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

Tremaine, Scott, E-mail: tremaine@ias.edu

2015-07-10

The final “giant-impact” phase of terrestrial planet formation is believed to begin with a large number of planetary “embryos” on nearly circular, coplanar orbits. Mutual gravitational interactions gradually excite their eccentricities until their orbits cross and they collide and merge; through this process the number of surviving bodies declines until the system contains a small number of planets on well-separated, stable orbits. In this paper we explore a simple statistical model for the orbit distribution of planets formed by this process, based on the sheared-sheet approximation and the ansatz that the planets explore uniformly all of the stable region ofmore » phase space. The model provides analytic predictions for the distribution of eccentricities and semimajor axis differences, correlations between orbital elements of nearby planets, and the complete N-planet distribution function, in terms of a single parameter, the “dynamical temperature,” that is determined by the planetary masses. The predicted properties are generally consistent with N-body simulations of the giant-impact phase and with the distribution of semimajor axis differences in the Kepler catalog of extrasolar planets. A similar model may apply to the orbits of giant planets if these orbits are determined mainly by dynamical evolution after the planets have formed and the gas disk has disappeared.« less

Indoor noise annoyance due to 3-5 megawatt wind turbines-An exposure-response relationship.

PubMed

Hongisto, Valtteri; Oliva, David; Keränen, Jukka

2017-10-01

The existing exposure-response relationships describing the association between wind turbine sound level and noise annoyance concern turbine sizes of 0.15-3.0 MW. The main purpose of this study was to determine a relationship concerning turbines with nominal power of 3-5 MW. A cross-sectional survey was conducted around three wind power areas in Finland. The survey involved all households within a 2 km distance from the nearest turbine. Altogether, 429 households out of 753 participated. The households were exposed to wind turbine noise having sound levels within 26.7-44.2 dB L Aeq . Standard prediction methods were applied to determine the sound level, L Aeq , in each participant's yard. The measured sound level agreed well with the predicted sound level. The exposure-response relationship was derived between L Aeq outdoors and the indoor noise annoyance. The relationship was in rather good agreement with two previous studies involving much smaller turbines (0.15-1.5 MW) under 40 dB L Aeq . The Community Tolerance Level (CTL), CTL 20  = 50 dB, was 3 dB lower than for two previous studies. Above 40 dB, a small number of participants prevented a reliable comparison to previous studies.

On the use of response surface methodology to predict and interpret the preferred c-axis orientation of sputtered AlN thin films

NASA Astrophysics Data System (ADS)

Adamczyk, J.; Horny, N.; Tricoteaux, A.; Jouan, P.-Y.; Zadam, M.

2008-01-01

This paper deals with experimental design applied to response surface methodology (RSM) in order to determine the influence of the discharge conditions on preferred c-axis orientation of sputtered AlN thin films. The thin films have been deposited by DC reactive magnetron sputtering on Si (1 0 0) substrates. The preferred orientation was evaluated using a conventional Bragg-Brentano X-ray diffractometer ( θ-2 θ) with the CuKα radiation. We have first determined the experimental domain for 3 parameters: sputtering pressure (2-6 mTorr), discharge current (312-438 mA) and nitrogen percentage (17-33%). For the setup of the experimental design we have used a three factors Doehlert matrix which allows the use of the statistical response surface methodology (RSM) in a spherical domain. A four dimensional surface response, which represents the (0 0 0 2) peak height as a function of sputtering pressure, discharge current and nitrogen percentage, was obtained. It has been found that the main interaction affecting the preferential c-axis orientation was the pressure-nitrogen percentage interaction. It has been proved that a Box-Cox transformation is a very useful method to interpret and discuss the experimental results and leads to predictions in good agreement with experiments.

Sensory evaluation and electronic tongue analysis for sweetener recognition in coke drinks

NASA Astrophysics Data System (ADS)

Szöllősi, Dániel; Kovács, Zoltán; Gere, Attila; Sípos, László; Kókai, Zoltán; Fekete, András

2011-09-01

Consumption of beverages with low energy has an increasing role. Furthermore hydrolyzed starch products such as inverted syrup show a wide application in the beverage industry. Therefore the importance of methods which can monitor the usage of natural and artificial sweeteners is increasing. The task was to describe the relevant sensory attributes and to determine the applicability of the electronic tongue to discriminate the coke drink samples with different sweeteners. Furthermore the aim was to find relationship between the taste attributes and measurement results provided by electronic tongue. An Alpha Astree Electronic Tongue and a trained sensory panel were used to evaluate the coke samples. Panelists found significant differences between the samples in 15 cases from the 18 sensory attributes defined previously by the consensus group. Coke drinks containing different kind of sweeteners can be characterized according to these sensory attributes. The samples were definitely distinguished by the electronic tongue. The main difference was found between the samples made with natural and artificial sweeteners. However electronic tongue was able to distinguish samples containing different kind of artificial and different kind of natural sweeteners, as well. Taste attributes of coke drinks determined by sensory panel were predicted by partial least squares regression method based on the results of electronic tongue with close correlation and low prediction error.

[Ecological suitability regionalization for Gastrodia elata in Zhaotong based on Maxent and ArcGIS].

PubMed

Shi, Zi-Wei; Ma, Cong-Ji; Kang, Chuan-Zhi; Wang, Li; Zhang, Zhi-Hui; Chen, Jun-Fei; Zhang, Xiao-Bo; Liu, Da-Hui

2016-09-01

In this paper, the potential distribution information and ecological suitability regionalization for Gastrodia elata in Zhaotong were studied based on the climate, terrain, soil and vegetation factors analysis by Maxent and ArcGIS. The results showed that the highly potential distribution (suitability index>0.6) mainly located in Zhaotong, Yunnan province（Zhenxiong,Yiliang and Daguan county, with an area of 2 872 km²）, and Bijie, Guizhou province （Hezhang,Bijie,Weining county, 1 251 km²）. The AUC of ROC curve was above 0.99, indicating that the predictive results with the Maxent model were highly precise. The main ecological factors determining the potential distribution were the altitude, average rainfall in November, average rainfall in October, vegetation types, average rainfall in March, average rainfall in April,soil types,isothermal characteristic and average rainfall in June. The environmental variables in the highly potential areas were determined as altitude around 1 450-2 200 m,annual average temperature around 18.0-20.4 ℃,annual average precipitation around 900 mm,yellow soil or yellow brown soil,and acid sandy loam or slightly acidic sandy loam.The results will provide valuable references for plantation regionalization and the siting for imitation wild planting of G. elata in Zhaotong. Copyright© by the Chinese Pharmaceutical Association.

Structure of the ordered hydration of amino acids in proteins: analysis of crystal structures

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

Biedermannová, Lada, E-mail: lada.biedermannova@ibt.cas.cz; Schneider, Bohdan

2015-10-27

The hydration of protein crystal structures was studied at the level of individual amino acids. The dependence of the number of water molecules and their preferred spatial localization on various parameters, such as solvent accessibility, secondary structure and side-chain conformation, was determined. Crystallography provides unique information about the arrangement of water molecules near protein surfaces. Using a nonredundant set of 2818 protein crystal structures with a resolution of better than 1.8 Å, the extent and structure of the hydration shell of all 20 standard amino-acid residues were analyzed as function of the residue conformation, secondary structure and solvent accessibility. Themore » results show how hydration depends on the amino-acid conformation and the environment in which it occurs. After conformational clustering of individual residues, the density distribution of water molecules was compiled and the preferred hydration sites were determined as maxima in the pseudo-electron-density representation of water distributions. Many hydration sites interact with both main-chain and side-chain amino-acid atoms, and several occurrences of hydration sites with less canonical contacts, such as carbon–donor hydrogen bonds, OH–π interactions and off-plane interactions with aromatic heteroatoms, are also reported. Information about the location and relative importance of the empirically determined preferred hydration sites in proteins has applications in improving the current methods of hydration-site prediction in molecular replacement, ab initio protein structure prediction and the set-up of molecular-dynamics simulations.« less

Numerical determination of personal aerosol sampler aspiration efficiency.

PubMed

Lo Savio, Simone; Paradisi, Paolo; Tampieri, Francesco; Belosi, Franco; Morigi, Maria Pia; Agostini, Sergio

2003-04-01

In this work the determination of the aspiration efficiency of personal aerosol samplers, commonly used in occupational exposure assessment, is investigated by means of CFD techniques. Specifically, it will be described a code to calculate the particle trajectories in a given flow field. At the present state the code considers only the effects of the mean flow field on the particle motion, whereas the turbulent diffusion effects are neglected. Comparisons with experimental measurements are also given in the framework of a research contract, supported by the European Community, with several experimental contributions from the participants. The main objective of the European research is to develop a new approach to experimentation with airborne particle flows, working on a reduced scale. This methodology has the advantage of allowing real-time aerosol determination and use of small wind tunnels, with a better experimental control. In this article we describe how the methodology has been verified using computational fluid dynamics. Experimental and numerical aspiration efficiencies have been compared and the influence of gravity and turbulence intensity in full and reduced scale has been investigated. The numerical techniques described here are in agreement with previous similar research and allow at least qualitative predictions of aspiration efficiency for real samplers, taking care of orientation from the incoming air flow. The major discrepancies among predicted and experimental results may be a consequence of bounce effects, which are very difficult to eliminate also by greasing the sampler surface.

Parasite infracommunities of a specialized marine fish species in a compound community dominated by generalist parasites.

PubMed

Lanfranchi, A L; Rossin, M A; Timi, J T

2009-12-01

The structure and composition of parasite communities of Mullus argentinae were analysed under two alternative hypotheses in a sample of 75 specimens caught off Mar del Plata, Argentina (38 degrees 27'S, 57 degrees 90'W). The first, based on the dominance of trophically transmitted larval parasites of low host-specificity among fish species in the region, predicts that infracommunities will be random subsets of regionally available species. The second, based on previous studies on other mullids, predicts that infracommunities will be dominated by adult digeneans. The parasite fauna of goatfishes was mainly composed of endoparasites, with metacercariae of Prosorhynchus australis accounting for most individual parasites and greatly affecting infracommunity descriptors. Its importance was reinforced by the low number of trophically transmitted larval parasites. Both hypotheses were refuted; parasite communities were not dominated either by trophically transmitted larval parasites of low host-specificity or by adult digeneans. Prosorhynchus australis was the only species displaying any degree of phylogenetic specificity. Therefore, the influence of phylogenetic factors seems to exceed that of ecological ones in determining the observed structure of infracommunities. However, it is precisely host ecology that allows P. australis to become the determinant of infracommunity structure by constraining the acquisition of other parasites. Studies aiming to determine the relative importance of evolutionary and ecological processes as structuring forces of parasite communities should take into account not only the identity and specificity of their component parasites, but also their availability in the compound community.

Orbit Determination of the SELENE Satellites Using Multi-Satellite Data Types and Evaluation of SELENE Gravity Field Models

NASA Technical Reports Server (NTRS)

Goossens, S.; Matsumoto, K.; Noda, H.; Araki, H.; Rowlands, D. D.; Lemoine, F. G.

2011-01-01

The SELENE mission, consisting of three separate satellites that use different terrestrial-based tracking systems, presents a unique opportunity to evaluate the contribution of these tracking systems to orbit determination precision. The tracking data consist of four-way Doppler between the main orbiter and one of the two sub-satellites while the former is over the far side, and of same-beam differential VLBI tracking between the two sub-satellites. Laser altimeter data are also used for orbit determination. The contribution to orbit precision of these different data types is investigated through orbit overlap analysis. It is shown that using four-way and VLBI data improves orbit consistency for all satellites involved by reducing peak values in orbit overlap differences that exist when only standard two-way Doppler and range data are used. Including laser altimeter data improves the orbit precision of the SELENE main satellite further, resulting in very smooth total orbit errors at an average level of 18m. The multi-satellite data have also resulted in improved lunar gravity field models, which are assessed through orbit overlap analysis using Lunar Prospector tracking data. Improvements over a pre-SELENE model are shown to be mostly in the along-track and cross-track directions. Orbit overlap differences are at a level between 13 and 21 m with the SELENE models, depending on whether l-day data overlaps or I-day predictions are used.

Longitudinal histories as predictors of future diagnoses of domestic abuse: modelling study

PubMed Central

Kohane, Isaac S; Mandl, Kenneth D

2009-01-01

Objective To determine whether longitudinal data in patients’ historical records, commonly available in electronic health record systems, can be used to predict a patient’s future risk of receiving a diagnosis of domestic abuse. Design Bayesian models, known as intelligent histories, used to predict a patient’s risk of receiving a future diagnosis of abuse, based on the patient’s diagnostic history. Retrospective evaluation of the model’s predictions using an independent testing set. Setting A state-wide claims database covering six years of inpatient admissions to hospital, admissions for observation, and encounters in emergency departments. Population All patients aged over 18 who had at least four years between their earliest and latest visits recorded in the database (561 216 patients). Main outcome measures Timeliness of detection, sensitivity, specificity, positive predictive values, and area under the ROC curve. Results 1.04% (5829) of the patients met the narrow case definition for abuse, while 3.44% (19 303) met the broader case definition for abuse. The model achieved sensitive, specific (area under the ROC curve of 0.88), and early (10-30 months in advance, on average) prediction of patients’ future risk of receiving a diagnosis of abuse. Analysis of model parameters showed important differences between sexes in the risks associated with certain diagnoses. Conclusions Commonly available longitudinal diagnostic data can be useful for predicting a patient’s future risk of receiving a diagnosis of abuse. This modelling approach could serve as the basis for an early warning system to help doctors identify high risk patients for further screening. PMID:19789406

Prediction of citation counts for clinical articles at two years using data available within three weeks of publication: retrospective cohort study

PubMed Central

2008-01-01

Objective To determine if citation counts at two years could be predicted for clinical articles that pass basic criteria for critical appraisal using data within three weeks of publication from external sources and an online article rating service. Design Retrospective cohort study. Setting Online rating service, Canada. Participants 1274 articles from 105 journals published from January to June 2005, randomly divided into a 60:40 split to provide derivation and validation datasets. Main outcome measures 20 article and journal features, including ratings of clinical relevance and newsworthiness, routinely collected by the McMaster online rating of evidence system, compared with citation counts at two years. Results The derivation analysis showed that the regression equation accounted for 60% of the variation (R2=0.60, 95% confidence interval 0.538 to 0.629). This model applied to the validation dataset gave a similar prediction (R2=0.56, 0.476 to 0.596, shrinkage 0.04; shrinkage measures how well the derived equation matches data from the validation dataset). Cited articles in the top half and top third were predicted with 83% and 61% sensitivity and 72% and 82% specificity. Higher citations were predicted by indexing in numerous databases; number of authors; abstraction in synoptic journals; clinical relevance scores; number of cited references; and original, multicentred, and therapy articles from journals with a greater proportion of articles abstracted. Conclusion Citation counts can be reliably predicted at two years using data within three weeks of publication. PMID:18292132

Risk score for predicting long-term mortality after coronary artery bypass graft surgery.

PubMed

Wu, Chuntao; Camacho, Fabian T; Wechsler, Andrew S; Lahey, Stephen; Culliford, Alfred T; Jordan, Desmond; Gold, Jeffrey P; Higgins, Robert S D; Smith, Craig R; Hannan, Edward L

2012-05-22

No simplified bedside risk scores have been created to predict long-term mortality after coronary artery bypass graft surgery. The New York State Cardiac Surgery Reporting System was used to identify 8597 patients who underwent isolated coronary artery bypass graft surgery in July through December 2000. The National Death Index was used to ascertain patients' vital statuses through December 31, 2007. A Cox proportional hazards model was fit to predict death after CABG surgery using preprocedural risk factors. Then, points were assigned to significant predictors of death on the basis of the values of their regression coefficients. For each possible point total, the predicted risks of death at years 1, 3, 5, and 7 were calculated. It was found that the 7-year mortality rate was 24.2 in the study population. Significant predictors of death included age, body mass index, ejection fraction, unstable hemodynamic state or shock, left main coronary artery disease, cerebrovascular disease, peripheral arterial disease, congestive heart failure, malignant ventricular arrhythmia, chronic obstructive pulmonary disease, diabetes mellitus, renal failure, and history of open heart surgery. The points assigned to these risk factors ranged from 1 to 7; possible point totals for each patient ranged from 0 to 28. The observed and predicted risks of death at years 1, 3, 5, and 7 across patient groups stratified by point totals were highly correlated. The simplified risk score accurately predicted the risk of mortality after coronary artery bypass graft surgery and can be used for informed consent and as an aid in determining treatment choice.

Global hot-star wind models for stars from Magellanic Clouds

NASA Astrophysics Data System (ADS)

Krtička, J.; Kubát, J.

2018-04-01

We provide mass-loss rate predictions for O stars from Large and Small Magellanic Clouds. We calculate global (unified, hydrodynamic) model atmospheres of main sequence, giant, and supergiant stars for chemical composition corresponding to Magellanic Clouds. The models solve radiative transfer equation in comoving frame, kinetic equilibrium equations (also known as NLTE equations), and hydrodynamical equations from (quasi-)hydrostatic atmosphere to expanding stellar wind. The models allow us to predict wind density, velocity, and temperature (consequently also the terminal wind velocity and the mass-loss rate) just from basic global stellar parameters. As a result of their lower metallicity, the line radiative driving is weaker leading to lower wind mass-loss rates with respect to the Galactic stars. We provide a formula that fits the mass-loss rate predicted by our models as a function of stellar luminosity and metallicity. On average, the mass-loss rate scales with metallicity as Ṁ Z0.59. The predicted mass-loss rates are lower than mass-loss rates derived from Hα diagnostics and can be reconciled with observational results assuming clumping factor Cc = 9. On the other hand, the predicted mass-loss rates either agree or are slightly higher than the mass-loss rates derived from ultraviolet wind line profiles. The calculated P V ionization fractions also agree with values derived from observations for LMC stars with Teff ≤ 40 000 K. Taken together, our theoretical predictions provide reasonable models with consistent mass-loss rate determination, which can be used for quantitative study of stars from Magellanic Clouds.

Identifying dyslexia in adults: an iterative method using the predictive value of item scores and self-report questions.

PubMed

Tamboer, Peter; Vorst, Harrie C M; Oort, Frans J

2014-04-01

Methods for identifying dyslexia in adults vary widely between studies. Researchers have to decide how many tests to use, which tests are considered to be the most reliable, and how to determine cut-off scores. The aim of this study was to develop an objective and powerful method for diagnosing dyslexia. We took various methodological measures, most of which are new compared to previous methods. We used a large sample of Dutch first-year psychology students, we considered several options for exclusion and inclusion criteria, we collected as many cognitive tests as possible, we used six independent sources of biographical information for a criterion of dyslexia, we compared the predictive power of discriminant analyses and logistic regression analyses, we used both sum scores and item scores as predictor variables, we used self-report questions as predictor variables, and we retested the reliability of predictions with repeated prediction analyses using an adjusted criterion. We were able to identify 74 dyslexic and 369 non-dyslexic students. For 37 students, various predictions were too inconsistent for a final classification. The most reliable predictions were acquired with item scores and self-report questions. The main conclusion is that it is possible to identify dyslexia with a high reliability, although the exact nature of dyslexia is still unknown. We therefore believe that this study yielded valuable information for future methods of identifying dyslexia in Dutch as well as in other languages, and that this would be beneficial for comparing studies across countries.

Predicted MHC peptide binding promiscuity explains MHC class I 'hotspots' of antigen presentation defined by mass spectrometry eluted ligand data.

PubMed

Jappe, Emma Christine; Kringelum, Jens; Trolle, Thomas; Nielsen, Morten

2018-02-15

Peptides that bind to and are presented by MHC class I and class II molecules collectively make up the immunopeptidome. In the context of vaccine development, an understanding of the immunopeptidome is essential, and much effort has been dedicated to its accurate and cost-effective identification. Current state-of-the-art methods mainly comprise in silico tools for predicting MHC binding, which is strongly correlated with peptide immunogenicity. However, only a small proportion of the peptides that bind to MHC molecules are, in fact, immunogenic, and substantial work has been dedicated to uncovering additional determinants of peptide immunogenicity. In this context, and in light of recent advancements in mass spectrometry (MS), the existence of immunological hotspots has been given new life, inciting the hypothesis that hotspots are associated with MHC class I peptide immunogenicity. We here introduce a precise terminology for defining these hotspots and carry out a systematic analysis of MS and in silico predicted hotspots. We find that hotspots defined from MS data are largely captured by peptide binding predictions, enabling their replication in silico. This leads us to conclude that hotspots, to a great degree, are simply a result of promiscuous HLA binding, which disproves the hypothesis that the identification of hotspots provides novel information in the context of immunogenic peptide prediction. Furthermore, our analyses demonstrate that the signal of ligand processing, although present in the MS data, has very low predictive power to discriminate between MS and in silico defined hotspots. © 2018 John Wiley & Sons Ltd.

An evaluation of the predictive performance of distributional models for flora and fauna in north-east New South Wales.

PubMed

Pearce, J; Ferrier, S; Scotts, D

2001-06-01

To use models of species distributions effectively in conservation planning, it is important to determine the predictive accuracy of such models. Extensive modelling of the distribution of vascular plant and vertebrate fauna species within north-east New South Wales has been undertaken by linking field survey data to environmental and geographical predictors using logistic regression. These models have been used in the development of a comprehensive and adequate reserve system within the region. We evaluate the predictive accuracy of models for 153 small reptile, arboreal marsupial, diurnal bird and vascular plant species for which independent evaluation data were available. The predictive performance of each model was evaluated using the relative operating characteristic curve to measure discrimination capacity. Good discrimination ability implies that a model's predictions provide an acceptable index of species occurrence. The discrimination capacity of 89% of the models was significantly better than random, with 70% of the models providing high levels of discrimination. Predictions generated by this type of modelling therefore provide a reasonably sound basis for regional conservation planning. The discrimination ability of models was highest for the less mobile biological groups, particularly the vascular plants and small reptiles. In the case of diurnal birds, poor performing models tended to be for species which occur mainly within specific habitats not well sampled by either the model development or evaluation data, highly mobile species, species that are locally nomadic or those that display very broad habitat requirements. Particular care needs to be exercised when employing models for these types of species in conservation planning.

Studies in Bilingual Evaluation, Work Unit I: Bilingual Prediction Project. Final Report.

ERIC Educational Resources Information Center

de Porcel, Antonio; And Others

The final report of the Bilingual Prediction Project presents a review of the project from its inception in 1975 through completion in 1979. The main goal was to predict a student's academic ability in English. A prediction index was constructed in two stages. The first stage was a description of the target population and their school setting, as…

Assessment of coagulation pretreatment of leachate by response surface methodology.

PubMed

Lessoued, Ridha; Souahi, Fatiha; Castrillon Pelaez, Leonor

2017-11-01

Coagulation-flocculation is a relatively simple technique that can be used successfully for the treatment of old leachate by poly-aluminum chloride (PAC). The main objectives of this study are to design the experiments, build models and optimize the operating parameters, dosage m and pH, using the central composite design and response surface method. Developed for chemical organic matter (COD) and turbidity responses, the quadratic polynomial model is suitable for prediction within the range of simulated variables as it showed that the optimum conditions were m of 5.55 g/L at pH 7.05, with a determination coefficient R² at 99.33%, 99.92% and adjusted R² at 98.85% and 99.86% for both COD and turbidity. We confirm that the initial pH and PAC dosage have significant effects on COD and turbidity removal. The experimental data and model predictions agreed well and the removal efficiency of COD, turbidity, Fe, Pb and Cu reached respectively 61%, 96.4%, 97.1%, 99% and 100%.

Odor Discrimination in Drosophila: From Neural Population Codes to Behavior

PubMed Central

Parnas, Moshe; Lin, Andrew C.; Huetteroth, Wolf; Miesenböck, Gero

2013-01-01

Summary Taking advantage of the well-characterized olfactory system of Drosophila, we derive a simple quantitative relationship between patterns of odorant receptor activation, the resulting internal representations of odors, and odor discrimination. Second-order excitatory and inhibitory projection neurons (ePNs and iPNs) convey olfactory information to the lateral horn, a brain region implicated in innate odor-driven behaviors. We show that the distance between ePN activity patterns is the main determinant of a fly’s spontaneous discrimination behavior. Manipulations that silence subsets of ePNs have graded behavioral consequences, and effect sizes are predicted by changes in ePN distances. ePN distances predict only innate, not learned, behavior because the latter engages the mushroom body, which enables differentiated responses to even very similar odors. Inhibition from iPNs, which scales with olfactory stimulus strength, enhances innate discrimination of closely related odors, by imposing a high-pass filter on transmitter release from ePN terminals that increases the distance between odor representations. PMID:24012006

The role of maxillofacial radiologists in gunshot injuries: a hypothesized missile trajectory in two case reports

PubMed Central

Sansare, K; Khanna, V; Karjodkar, F

2011-01-01

Gunshot injuries are an emerging form of trauma that oral radiologists increasingly have to deal with. There are two main types of gunshot injuries: high-velocity and low-velocity bullet injuries. The outcome of high-velocity gunshot injury is usually fatal; however, a non-fatal low-velocity injury to the maxillofacial region is more likely to be encountered by the oral and maxillofacial radiologist. It is therefore important to up-to-date knowledge of ballistic science and its implications in the field of maxillofacial radiology. The ability of oral and maxillofacial radiologists to predict the missile trajectory will aid the assessment and localization of the damage caused by the bullet and its splinters. Predicting the missile trajectory may also be of help to law enforcement agencies and forensic scientists in determining the type of firearm used and direction of fire. This article, which examines two cases, attempts to highlight to the oral radiologist this emerging form of trauma and its implications. PMID:21159916

Comprehensive Study of the Evolution of the Gas-Liquid Partitioning of Acetaldehyde during Wine Alcoholic Fermentation.

PubMed

Aguera, Evelyne; Sire, Yannick; Mouret, Jean-Roch; Sablayrolles, Jean-Marie; Farines, Vincent

2018-06-20

Determining the gas-liquid partitioning ( K i ) of acetaldehyde during alcoholic fermentation is an important step in the optimization of fermentation control with the aim of minimizing the accumulation of this compound, which is responsible for the undesired attributes of green apples and fresh-cut grass in wines. In this work, the effects of the main fermentation parameters on the K i of acetaldehyde were assessed. K i values were found to be dependent on the temperature and composition of the medium. A nonlinear correlation between the evolution of the K i and fermentation progress was observed, attributable to the strong retention effect of ethanol at low concentrations, and it was demonstrated that the partitioning of this specific molecule was not influenced by the CO 2 production rate. A model was developed that quantifies the K i of acetaldehyde with a very accurate prediction, as the difference between the observed and predicted values did not exceed 9%.

Narcissists of a Feather Flock Together: Narcissism and the Similarity of Friends.

PubMed

Maaß, Ulrike; Lämmle, Lena; Bensch, Doreen; Ziegler, Matthias

2016-03-01

Who is willing to expose himself or herself to narcissists on a long-term basis? Studies that address the interactions of narcissists focus mainly on their interactions with strangers. Hence, the aim of the present study was to investigate the extent to which two best friends' similarity in narcissism would influence their similarities in other personality profiles. A total of 290 best friends' dyads filled out measurements of the whole Dark Triad as well as the Big Five. For each personality domain, profile similarity and its dependence on the similarity in the Dark Triad were determined. Results showed that the friends' similarity in narcissism significantly predicted similarity in all Big Five domains. For the general Big Five similarity as well as extraversion, the effect of narcissism similarity was stronger for male than female or mixed friends. Similarity in psychopathy and Machiavellianism significantly predicted all domains except for openness and extraversion, respectively. © 2016 by the Society for Personality and Social Psychology, Inc.

Effect of Wind Speed and Relative Humidity on Atmospheric Dust Concentrations in Semi-Arid Climates

PubMed Central

Csavina, Janae; Field, Jason; Félix, Omar; Corral-Avitia, Alba Y.; Sáez, A. Eduardo; Betterton, Eric A.

2014-01-01

Atmospheric particulate have deleterious impacts on human health. Predicting dust and aerosol emission and transport would be helpful to reduce harmful impacts but, despite numerous studies, prediction of dust events and contaminant transport in dust remains challenging. In this work, we show that relative humidity and wind speed are both determinants in atmospheric dust concentration. Observations of atmospheric dust concentrations in Green Valley, AZ, USA, and Juárez, Chihuahua, México, show that PM10 concentrations are not directly correlated with wind speed or relative humidity separately. However, selecting the data for high wind speeds (> 4 m/s at 10 m elevation), a definite trend is observed between dust concentration and relative humidity: dust concentration increases with relative humidity, reaching a maximum around 25% and it subsequently decreases with relative humidity. Models for dust storm forecasting may be improved by utilizing atmospheric humidity and wind speed as main drivers for dust generation and transport. PMID:24769193

Development of predictive models for total phenolics and free p-coumaric acid contents in barley grain by near-infrared spectroscopy.

PubMed

Han, Zhigang; Cai, Shengguan; Zhang, Xuelei; Qian, Qiufeng; Huang, Yuqing; Dai, Fei; Zhang, Guoping

2017-07-15

Barley grains are rich in phenolic compounds, which are associated with reduced risk of chronic diseases. Development of barley cultivars with high phenolic acid content has become one of the main objectives in breeding programs. A rapid and accurate method for measuring phenolic compounds would be helpful for crop breeding. We developed predictive models for both total phenolics (TPC) and p-coumaric acid (PA), based on near-infrared spectroscopy (NIRS) analysis. Regressions of partial least squares (PLS) and least squares support vector machine (LS-SVM) were compared for improving the models, and Monte Carlo-Uninformative Variable Elimination (MC-UVE) was applied to select informative wavelengths. The optimal calibration models generated high coefficients of correlation (r pre ) and ratio performance deviation (RPD) for TPC and PA. These results indicated the models are suitable for rapid determination of phenolic compounds in barley grains. Copyright © 2017 Elsevier Ltd. All rights reserved.

Medium Suppression of In medium Nucleon-Nucleon Cross Sections Predicted with Various Microscopic Calculations

NASA Astrophysics Data System (ADS)

Xing, Yong-Zhong; Lu, Fei-Ping; Wei, Xiao-Ping; Zheng, Yu-Ming

2014-08-01

The nucleon-nucleon cross sections in the dense nuclear matter are microscopically calculated by using Dirac—Brueckner—Hartree—Fock (DBHF) approximation with different covariant representations of the T-matrix, i.e., complete pseudo-vector (CPV), pseudoscalar (PS) and pseudo-vector (PV) choices. Special attention is paid to the discrepancies among the cross sections calculated with these different T-matrix project choices. The results show that the medium suppression of the cross section given by DBHF in the CPV choice is not only smaller than those obtained in both PS and PV choices, but also smaller than the predictions with a nonrelativistic Brueckner—Hartree—Fock (BHF) method including three body force (3BF). The further analysis reveals that the influence of the different choices on the cross section in the DBHF approximation is mainly determined by the state of smaller total angular momentum due to the medium effect being strongly suppressed in the higher angular momentum.

Predictive value and efficiency of laboratory testing.

PubMed

Galen, R S

1980-11-01

Literature on determining reference values and reference intervals on "normal" or "healthy" individuals is abundant. It is impossible, however, to evaluate a data set of reference values and select a suitable reference interval that will be meaningful for the practice of medicine. The reference interval, no matter how derived statistically, tells us nothing about disease. This is the main reason the concepts of "normal values" have failed us and why "reference values" will prove similarly disappointing. By studying these same constituents in a variety of disease states as well, it will be possible to select "referent values" that will make the test procedure meaningful for diagnostic purposes. In order to obtain meaningful referent values for predicting disease, it is necessary to study not only the "healthy" reference population, but patients with the disease in question, and patients who are free of the disease in question but who have other diseases. Studies of this type are not frequently found for laboratory tests that are in common use today.

A frictionally and hydraulically constrained model of the convectively driven mean flow in partially enclosed seas

NASA Astrophysics Data System (ADS)

Maxworthy, T.

1997-08-01

A simple three-layer model of the dynamics of partially enclosed seas, driven by a surface buoyancy flux, is presented. It contains two major elements, a hydraulic constraint at the exit contraction and friction in the interior of the main body of the sea; both together determine the vertical structure and magnitudes of the interior flow variables, i.e. velocity and density. Application of the model to the large-scale dynamics of the Red Sea gives results that are not in disagreement with observation once the model is applied, also, to predict the dense outflow from the Gulf of Suez. The latter appears to be the agent responsible for the formation of dense bottom water in this system. Also, the model is reasonably successful in predicting the density of the outflow from the Persian Gulf, and can be applied to any number of other examples of convectively driven flow in long, narrow channels, with or without sills and constrictions at their exits.

The role of maxillofacial radiologists in gunshot injuries: a hypothesized missile trajectory in two case reports.

PubMed

Sansare, K; Khanna, V; Karjodkar, F

2011-01-01

Gunshot injuries are an emerging form of trauma that oral radiologists increasingly have to deal with. There are two main types of gunshot injuries: high-velocity and low-velocity bullet injuries. The outcome of high-velocity gunshot injury is usually fatal; however, a non-fatal low-velocity injury to the maxillofacial region is more likely to be encountered by the oral and maxillofacial radiologist. It is therefore important to up-to-date knowledge of ballistic science and its implications in the field of maxillofacial radiology. The ability of oral and maxillofacial radiologists to predict the missile trajectory will aid the assessment and localization of the damage caused by the bullet and its splinters. Predicting the missile trajectory may also be of help to law enforcement agencies and forensic scientists in determining the type of firearm used and direction of fire. This article, which examines two cases, attempts to highlight to the oral radiologist this emerging form of trauma and its implications.