Predictive Distribution of the Dirichlet Mixture Model by the Local Variational Inference Method

DEFF Research Database (Denmark)

Ma, Zhanyu; Leijon, Arne; Tan, Zheng-Hua

2014-01-01

the predictive likelihood of the new upcoming data, especially when the amount of training data is small. The Bayesian estimation of a Dirichlet mixture model (DMM) is, in general, not analytically tractable. In our previous work, we have proposed a global variational inference-based method for approximately...... calculating the posterior distributions of the parameters in the DMM analytically. In this paper, we extend our previous study for the DMM and propose an algorithm to calculate the predictive distribution of the DMM with the local variational inference (LVI) method. The true predictive distribution of the DMM...... is analytically intractable. By considering the concave property of the multivariate inverse beta function, we introduce an upper-bound to the true predictive distribution. As the global minimum of this upper-bound exists, the problem is reduced to seek an approximation to the true predictive distribution...

Probabilistic electricity price forecasting with variational heteroscedastic Gaussian process and active learning

International Nuclear Information System (INIS)

Kou, Peng; Liang, Deliang; Gao, Lin; Lou, Jianyong

2015-01-01

Highlights: • A novel active learning model for the probabilistic electricity price forecasting. • Heteroscedastic Gaussian process that captures the local volatility of the electricity price. • Variational Bayesian learning that avoids over-fitting. • Active learning algorithm that reduces the computational efforts. - Abstract: Electricity price forecasting is essential for the market participants in their decision making. Nevertheless, the accuracy of such forecasting cannot be guaranteed due to the high variability of the price data. For this reason, in many cases, rather than merely point forecasting results, market participants are more interested in the probabilistic price forecasting results, i.e., the prediction intervals of the electricity price. Focusing on this issue, this paper proposes a new model for the probabilistic electricity price forecasting. This model is based on the active learning technique and the variational heteroscedastic Gaussian process (VHGP). It provides the heteroscedastic Gaussian prediction intervals, which effectively quantify the heteroscedastic uncertainties associated with the price data. Because the high computational effort of VHGP hinders its application to the large-scale electricity price forecasting tasks, we design an active learning algorithm to select a most informative training subset from the whole available training set. By constructing the forecasting model on this smaller subset, the computational efforts can be significantly reduced. In this way, the practical applicability of the proposed model is enhanced. The forecasting performance and the computational time of the proposed model are evaluated using the real-world electricity price data, which is obtained from the ANEM, PJM, and New England ISO

Latitudinal variation in seasonal activity and mortality in ratsnakes (Elaphe obsoleta).

Science.gov (United States)

Sperry, Jinelle H; Blouin-Demers, Gabriel; Carfagno, Gerardo L F; Weatherhead, Patrick J

2010-06-01

The ecology of ectotherms should be particularly affected by latitude because so much of their biology is temperature dependent. Current latitudinal patterns should also be informative about how ectotherms will have to modify their behavior in response to climate change. We used data from a total of 175 adult black ratsnakes (Elaphe obsoleta) radio-tracked in Ontario, Illinois, and Texas, a latitudinal distance of >1500 km, to test predictions about how seasonal patterns of activity and mortality should vary with latitude. Despite pronounced differences in temperatures among study locations, and despite ratsnakes in Texas not hibernating and switching from diurnal to nocturnal activity in the summer, seasonal patterns of snake activity were remarkably similar during the months that snakes in all populations were active. Rather than being a function of temperature, activity may be driven by the timing of reproduction, which appears similar among populations. Contrary to the prediction that mortality should be highest in the most active population, overall mortality did not follow a clinal pattern. Winter mortality did increase with latitude, however, consistent with temperature limiting the northern distribution of ratsnakes. This result was opposite that found in the only previous study of latitudinal variation in winter mortality in reptiles, which may be a consequence of whether or not the animals exhibit true hibernation. Collectively, these results suggest that, at least in the northern part of their range, ratsnakes should be able to adjust easily to, and may benefit from, a warmer climate, although climate-based changes to the snakes' prey or habitat, for example, could alter that prediction.

Surface Temperature Variation Prediction Model Using Real-Time Weather Forecasts

Science.gov (United States)

Karimi, M.; Vant-Hull, B.; Nazari, R.; Khanbilvardi, R.

2015-12-01

Combination of climate change and urbanization are heating up cities and putting the lives of millions of people in danger. More than half of the world's total population resides in cities and urban centers. Cities are experiencing urban Heat Island (UHI) effect. Hotter days are associated with serious health impacts, heart attaches and respiratory and cardiovascular diseases. Densely populated cities like Manhattan, New York can be affected by UHI impact much more than less populated cities. Even though many studies have been focused on the impact of UHI and temperature changes between urban and rural air temperature, not many look at the temperature variations within a city. These studies mostly use remote sensing data or typical measurements collected by local meteorological station networks. Local meteorological measurements only have local coverage and cannot be used to study the impact of UHI in a city and remote sensing data such as MODIS, LANDSAT and ASTER have with very low resolution which cannot be used for the purpose of this study. Therefore, predicting surface temperature in urban cities using weather data can be useful.Three months of Field campaign in Manhattan were used to measure spatial and temporal temperature variations within an urban setting by placing 10 fixed sensors deployed to measure temperature, relative humidity and sunlight. Fixed instrument shelters containing relative humidity, temperature and illumination sensors were mounted on lampposts in ten different locations in Manhattan (Vant-Hull et al, 2014). The shelters were fixed 3-4 meters above the ground for the period of three months from June 23 to September 20th of 2013 making measurements with the interval of 3 minutes. These high resolution temperature measurements and three months of weather data were used to predict temperature variability from weather forecasts. This study shows that the amplitude of spatial and temporal variation in temperature for each day can be predicted

Modeling and Predicting the Daily Equatorial Plasma Bubble Activity Using the Tiegcm

Science.gov (United States)

Carter, B. A.; Retterer, J. M.; Yizengaw, E.; Wiens, K. C.; Wing, S.; Groves, K. M.; Caton, R. G.; Bridgwood, C.; Francis, M. J.; Terkildsen, M. B.; Norman, R.; Zhang, K.

2014-12-01

Describing and understanding the daily variability of Equatorial Plasma Bubble (EPB) occurrence has remained a significant challenge over recent decades. In this study we use the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM), which is driven by solar (F10.7) and geomagnetic (Kp) activity indices, to study daily variations of the linear Rayleigh-Taylor (R-T) instability growth rate in relation to the measured scintillation strength at five longitudinally distributed stations. For locations characterized by generally favorable conditions for EPB growth (i.e., within the scintillation season for that location) we find that the TIEGCM is capable of identifying days when EPB development, determined from the calculated R-T growth rate, is suppressed as a result of geomagnetic activity. Both observed and modeled upward plasma drift indicate that the pre-reversal enhancement scales linearly with Kp from several hours prior, from which it is concluded that even small Kp changes cause significant variations in daily EPB growth. This control of Kp variations on EPB growth prompted an investigation into the use of predicted Kp values from the Wing Kp model over a 2-month equinoctial campaign in 2014. It is found that both the 1-hr and 4-hr predicted Kp values can be reliably used as inputs into the TIEGCM to forecast the EPB growth conditions during scintillation season, when daily EPB variability is governed by the suppression of EPBs on days with increased, but not necessarily high, geomagnetic activity.

RAPID COMMUNICATION: Improving prediction accuracy of GPS satellite clocks with periodic variation behaviour

Science.gov (United States)

Heo, Youn Jeong; Cho, Jeongho; Heo, Moon Beom

2010-07-01

The broadcast ephemeris and IGS ultra-rapid predicted (IGU-P) products are primarily available for use in real-time GPS applications. The IGU orbit precision has been remarkably improved since late 2007, but its clock products have not shown acceptably high-quality prediction performance. One reason for this fact is that satellite atomic clocks in space can be easily influenced by various factors such as temperature and environment and this leads to complicated aspects like periodic variations, which are not sufficiently described by conventional models. A more reliable prediction model is thus proposed in this paper in order to be utilized particularly in describing the periodic variation behaviour satisfactorily. The proposed prediction model for satellite clocks adds cyclic terms to overcome the periodic effects and adopts delay coordinate embedding, which offers the possibility of accessing linear or nonlinear coupling characteristics like satellite behaviour. The simulation results have shown that the proposed prediction model outperforms the IGU-P solutions at least on a daily basis.

Prediction of galactic cosmic ray intensity variation for a few (up to 10-12 years ahead on the basis of convection-diffusion and drift model

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L. I. Dorman

2005-11-01

Full Text Available We determine the dimension of the Heliosphere (modulation region, radial diffusion coefficient and other parameters of convection-diffusion and drift mechanisms of cosmic ray (CR long-term variation, depending on particle energy, the level of solar activity (SA and general solar magnetic field. This important information we obtain on the basis of CR and SA data in the past, taking into account the theory of convection-diffusion and drift global modulation of galactic CR in the Heliosphere. By using these results and the predictions which are regularly published elsewhere of expected SA variation in the near future and prediction of next future SA cycle, we may make a prediction of the expected in the near future long-term cosmic ray intensity variation. We show that by this method we may make a prediction of the expected in the near future (up to 10-12 years, and may be more, in dependence for what period can be made definite prediction of SA galactic cosmic ray intensity variation in the interplanetary space on different distances from the Sun, in the Earth's magnetosphere, and in the atmosphere at different altitudes and latitudes.

Mapping and predictive variations of soil bacterial richness across France.

Science.gov (United States)

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.

Application of Method of Variation to Analyze and Predict Human Induced Modifications of Water Resource Systems

Science.gov (United States)

Dessu, S. B.; Melesse, A. M.; Mahadev, B.; McClain, M.

2010-12-01

Water resource systems have often used gravitational surface and subsurface flows because of their practicality in hydrological modeling and prediction. Activities such as inter/intra-basin water transfer, the use of small pumps and the construction of micro-ponds challenge the tradition of natural rivers as water resource management unit. On the contrary, precipitation is barely affected by topography and plot harvesting in wet regions can be more manageable than diverting from rivers. Therefore, it is indicative to attend to systems where precipitation drives the dynamics while the internal mechanics constitutes spectrum of human activity and decision in a network of plots. The trade-in volume and path of harvested precipitation depends on water balance, energy balance and the kinematics of supply and demand. Method of variation can be used to understand and predict the implication of local excess precipitation harvest and exchange on the natural water system. A system model was developed using the variational form of Euler-Bernoulli’s equation for the Kenyan Mara River basin. Satellite derived digital elevation models, precipitation estimates, and surface properties such as fractional impervious surface area, are used to estimate the available water resource. Four management conditions are imposed in the model: gravitational flow, open water extraction and high water use investment at upstream and downstream respectively. According to the model, the first management maintains the basin status quo while the open source management could induce externality. The high water market at the upstream in the third management offers more than 50% of the basin-wide total revenue to the upper third section of the basin thus may promote more harvesting. The open source and upstream exploitation suggest potential drop of water availability to downstream. The model exposed the latent potential of economic gradient to reconfigure the flow network along the direction where the

Predicting Variations in Math Performancein Four Countries Using TIMSS

Directory of Open Access Journals (Sweden)

Daniel Koretz

2001-09-01

Full Text Available Although international comparisons of average student performance are a staple of U.S. educational debate, little attention has been paid to cross-national differences in the variability of performance. It is often assumed that the performance of U.S. students is unusually variable or that the distribution of U.S. scores is left-skewed – that is, that it has an unusually long ‘tail' of low-scoring students – but data from international studies are rarely brought to bear on these questions. This study used data from the Third International Mathematics and Science Study (TIMSS to compare the variability of performance in the U.S., Australia, France, Germany, Hong Kong, Korea, and Japan; investigate how this performance variation is distributed within and between classrooms; and explore how well background variables predict performance at both levels. TIMSS shows that the U.S. is not anomalous in terms of the amount, distribution, or prediction of performance variation. Nonetheless, some striking differences appear between countries that are potentially important for both research and policy. In the U.S., Germany, Hong Kong, and Australia, between 42 and 47 percent of score variance was between classrooms. At the other extreme, Japan and Korea both had less than 10 percent of score variance between classrooms. Two-level models (student and classroom were used to explore the prediction of performance by social background variables in four of these countries (the U.S., Hong Kong, France, and Korea. The final models included only a few variables; TIMSS lacked some important background variables, such as income, and other variables were dropped either because of problems revealed by exploratory data analysis or because of a lack of significance in the models. In all four countries, these sparse models predicted most of the between-classroom score variance (from 59 to 94 percent but very little of the within-classroom variance. Korea was the only

Prediction of seasonal climate-induced variations in global food production

Science.gov (United States)

Iizumi, Toshichika; Sakuma, Hirofumi; Yokozawa, Masayuki; Luo, Jing-Jia; Challinor, Andrew J.; Brown, Molly E.; Sakurai, Gen; Yamagata, Toshio

2013-10-01

Consumers, including the poor in many countries, are increasingly dependent on food imports and are thus exposed to variations in yields, production and export prices in the major food-producing regions of the world. National governments and commercial entities are therefore paying increased attention to the cropping forecasts of important food-exporting countries as well as to their own domestic food production. Given the increased volatility of food markets and the rising incidence of climatic extremes affecting food production, food price spikes may increase in prevalence in future years. Here we present a global assessment of the reliability of crop failure hindcasts for major crops at two lead times derived by linking ensemble seasonal climatic forecasts with statistical crop models. We found that moderate-to-marked yield loss over a substantial percentage (26-33%) of the harvested area of these crops is reliably predictable if climatic forecasts are near perfect. However, only rice and wheat production are reliably predictable at three months before the harvest using within-season hindcasts. The reliabilities of estimates varied substantially by crop--rice and wheat yields were the most predictable, followed by soybean and maize. The reasons for variation in the reliability of the estimates included the differences in crop sensitivity to the climate and the technology used by the crop-producing regions. Our findings reveal that the use of seasonal climatic forecasts to predict crop failures will be useful for monitoring global food production and will encourage the adaptation of food systems toclimatic extremes.

T2 map signal variation predicts symptomatic osteoarthritis progression: data from the Osteoarthritis Initiative

Energy Technology Data Exchange (ETDEWEB)

Zhong, Haoti; Miller, David J. [The Pennsylvania State University, Department of Electrical Engineering, University Park, PA (United States); Urish, Kenneth L. [Magee Womens Hospital of the University of Pittsburgh Medical Center, The Bone and Joint Center, Pittsburgh, PA (United States); University of Pittsburgh School of Medicine, Department of Orthopaedic Surgery, Pittsburgh, PA (United States)

2016-07-15

The aim of this work is to use quantitative magnetic resonance imaging (MRI) to identify patients at risk for symptomatic osteoarthritis (OA) progression. We hypothesized that classification of signal variation on T2 maps might predict symptomatic OA progression. Patients were selected from the Osteoarthritis Initiative (OAI), a prospective cohort. Two groups were identified: a symptomatic OA progression group and a control group. At baseline, both groups were asymptomatic (Western Ontario and McMaster Universities Arthritis [WOMAC] pain score total <10) with no radiographic evidence of OA (Kellgren-Lawrence [KL] score ≤ 1). The OA progression group (n = 103) had a change in total WOMAC score greater than 10 by the 3-year follow-up. The control group (n = 79) remained asymptomatic, with a change in total WOMAC score less than 10 at the 3-year follow-up. A classifier was designed to predict OA progression in an independent population based on T2 map cartilage signal variation. The classifier was designed using a nearest neighbor classification based on a Gaussian Mixture Model log-likelihood fit of T2 map cartilage voxel intensities. The use of T2 map signal variation to predict symptomatic OA progression in asymptomatic individuals achieved a specificity of 89.3 %, a sensitivity of 77.2 %, and an overall accuracy rate of 84.2 %. T2 map signal variation can predict symptomatic knee OA progression in asymptomatic individuals, serving as a possible early OA imaging biomarker. (orig.)

Mapping and predictive variations of soil bacterial richness across France.

Directory of Open Access Journals (Sweden)

Sébastien Terrat

Full Text Available 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.

Prediction of Navigation Satellite Clock Bias Considering Clock's Stochastic Variation Behavior with Robust Least Square Collocation

Directory of Open Access Journals (Sweden)

WANG Yupu

2016-06-01

Full Text Available In order to better express the characteristic of satellite clock bias (SCB and further improve its prediction precision, a new SCB prediction model is proposed, which can take the physical feature, cyclic variation and stochastic variation behaviors of the space-borne atomic clock into consideration by using a robust least square collocation (LSC method. The proposed model firstly uses a quadratic polynomial model with periodic terms to fit and abstract the trend term and cyclic terms of SCB. Then for the residual stochastic variation part and possible gross errors hidden in SCB data, the model employs a robust LSC method to process them. The covariance function of the LSC is determined by selecting an empirical function and combining SCB prediction tests. Using the final precise IGS SCB products to conduct prediction tests, the results show that the proposed model can get better prediction performance. Specifically, the results' prediction accuracy can enhance 0.457 ns and 0.948 ns respectively, and the corresponding prediction stability can improve 0.445 ns and 1.233 ns, compared with the results of quadratic polynomial model and grey model. In addition, the results also show that the proposed covariance function corresponding to the new model is reasonable.

Intraspecific morphological and genetic variation of common species predicts ranges of threatened ones

Science.gov (United States)

Fuller, Trevon L.; Thomassen, Henri A.; Peralvo, Manuel; Buermann, Wolfgang; Milá, Borja; Kieswetter, Charles M.; Jarrín-V, Pablo; Devitt, Susan E. Cameron; Mason, Eliza; Schweizer, Rena M.; Schlunegger, Jasmin; Chan, Janice; Wang, Ophelia; Schneider, Christopher J.; Pollinger, John P.; Saatchi, Sassan; Graham, Catherine H.; Wayne, Robert K.; Smith, Thomas B.

2013-01-01

Predicting where threatened species occur is useful for making informed conservation decisions. However, because they are usually rare, surveying threatened species is often expensive and time intensive. Here, we show how regions where common species exhibit high genetic and morphological divergence among populations can be used to predict the occurrence of species of conservation concern. Intraspecific variation of common species of birds, bats and frogs from Ecuador were found to be a significantly better predictor for the occurrence of threatened species than suites of environmental variables or the occurrence of amphibians and birds. Fully 93 per cent of the threatened species analysed had their range adequately represented by the geographical distribution of the morphological and genetic variation found in seven common species. Both higher numbers of threatened species and greater genetic and morphological variation of common species occurred along elevation gradients. Higher levels of intraspecific divergence may be the result of disruptive selection and/or introgression along gradients. We suggest that collecting data on genetic and morphological variation in common species can be a cost effective tool for conservation planning, and that future biodiversity inventories include surveying genetic and morphological data of common species whenever feasible. PMID:23595273

Who Punishes? Personality Traits Predict Individual Variation in Punitive Sentiment

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S. Craig Roberts

2013-01-01

Full Text Available Cross-culturally, participants in public goods games reward participants and punish defectors to a degree beyond that warranted by rational, profit-maximizing considerations. Costly punishment, where individuals impose costs on defectors at a cost to themselves, is thought to promote the maintenance of cooperation. However, despite substantial variation in the extent to which people punish, little is known about why some individuals, and not others, choose to pay these costs. Here, we test whether personality traits might contribute to variation in helping and punishment behavior. We first replicate a previous study using public goods scenarios to investigate effects of sex, relatedness and likelihood of future interaction on willingness to help a group member or to punish a transgressor. As in the previous study, we find that individuals are more willing to help related than unrelated needy others and that women are more likely to express desire to help than men. Desire to help was higher if the probability of future interaction is high, at least among women. In contrast, among these variables, only participant sex predicted some measures of punitive sentiment. Extending the replication, we found that punitive sentiment, but not willingness to help, was predicted by personality traits. Most notably, participants scoring lower on Agreeableness expressed more anger towards and greater desire to punish a transgressor, and were more willing to engage in costly punishment, at least in our scenario. Our results suggest that some personality traits may contribute to underpinning individual variation in social enforcement of cooperation.

Geomagnetic imprinting predicts spatio-temporal variation in homing migration of pink and sockeye salmon

Science.gov (United States)

Putman, Nathan F.; Jenkins, Erica S.; Michielsens, Catherine G. J.; Noakes, David L. G.

2014-01-01

Animals navigate using a variety of sensory cues, but how each is weighted during different phases of movement (e.g. dispersal, foraging, homing) is controversial. Here, we examine the geomagnetic and olfactory imprinting hypotheses of natal homing with datasets that recorded variation in the migratory routes of sockeye (Oncorhynchus nerka) and pink (Oncorhynchus gorbuscha) salmon returning from the Pacific Ocean to the Fraser River, British Columbia. Drift of the magnetic field (i.e. geomagnetic imprinting) uniquely accounted for 23.2% and 44.0% of the variation in migration routes for sockeye and pink salmon, respectively. Ocean circulation (i.e. olfactory imprinting) predicted 6.1% and 0.1% of the variation in sockeye and pink migration routes, respectively. Sea surface temperature (a variable influencing salmon distribution but not navigation, directly) accounted for 13.0% of the variation in sockeye migration but was unrelated to pink migration. These findings suggest that geomagnetic navigation plays an important role in long-distance homing in salmon and that consideration of navigation mechanisms can aid in the management of migratory fishes by better predicting movement patterns. Finally, given the diversity of animals that use the Earth's magnetic field for navigation, geomagnetic drift may provide a unifying explanation for spatio-temporal variation in the movement patterns of many species. PMID:25056214

Ionospheric F2-Layer Semi-Annual Variation in Middle Latitude by Solar Activity

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Yoon-Kyung Park

2010-12-01

Full Text Available We examine the ionospheric F2-layer electron density variation by solar activity in middle latitude by using foF2 observed at the Kokubunji ionosonde station in Japan for the period from 1997 to 2008. The semi-annual variation of foF2 shows obviously in high solar activity (2000-2002 than low solar activity (2006-2008. It seems that variation of geomagnetic activity by solar activity influences on the semi-annual variation of the ionospheric F2-layer electron density. According to the Lomb-Scargle periodogram analysis of foF2 and Ap index, interplanetary magnetic field (IMF Bs (IMF Bz <0 component, solar wind speed, solar wind number density and flow pressure which influence the geomagnetic activity, we examine how the geomagnetic activity affects the ionospheric F2-layer electron density variation. We find that the semi-annual variation of daily foF2, Ap index and IMF Bs appear clearly during the high solar activity. It suggests that the semi-annual variation of geomagnetic activity, caused by Russell-McPherron effect, contributes greatly to the ionospheric F2-layer semi-annual electron density variation, except dynamical effects in the thermosphere.

Phenotypic variation in metabolism and morphology correlating with animal swimming activity in the wild: relevance for the OCLTT (oxygen- and capacity-limitation of thermal tolerance), allocation and performance models.

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Baktoft, Henrik; Jacobsen, Lene; Skov, Christian; Koed, Anders; Jepsen, Niels; Berg, Søren; Boel, Mikkel; Aarestrup, Kim; Svendsen, Jon C

2016-01-01

Ongoing climate change is affecting animal physiology in many parts of the world. Using metabolism, the oxygen- and capacity-limitation of thermal tolerance (OCLTT) hypothesis provides a tool to predict the responses of ectothermic animals to variation in temperature, oxygen availability and pH in the aquatic environment. The hypothesis remains controversial, however, and has been questioned in several studies. A positive relationship between aerobic metabolic scope and animal activity would be consistent with the OCLTT but has rarely been tested. Moreover, the performance model and the allocation model predict positive and negative relationships, respectively, between standard metabolic rate and activity. Finally, animal activity could be affected by individual morphology because of covariation with cost of transport. Therefore, we hypothesized that individual variation in activity is correlated with variation in metabolism and morphology. To test this prediction, we captured 23 wild European perch (Perca fluviatilis) in a lake, tagged them with telemetry transmitters, measured standard and maximal metabolic rates, aerobic metabolic scope and fineness ratio and returned the fish to the lake to quantify individual in situ activity levels. Metabolic rates were measured using intermittent flow respirometry, whereas the activity assay involved high-resolution telemetry providing positions every 30 s over 12 days. We found no correlation between individual metabolic traits and activity, whereas individual fineness ratio correlated with activity. Independent of body length, and consistent with physics theory, slender fish maintained faster mean and maximal swimming speeds, but this variation did not result in a larger area (in square metres) explored per 24 h. Testing assumptions and predictions of recent conceptual models, our study indicates that individual metabolism is not a strong determinant of animal activity, in contrast to individual morphology, which is

Geomagnetic imprinting predicts spatio-temporal variation in homing migration of pink and sockeye salmon.

Science.gov (United States)

Putman, Nathan F; Jenkins, Erica S; Michielsens, Catherine G J; Noakes, David L G

2014-10-06

Animals navigate using a variety of sensory cues, but how each is weighted during different phases of movement (e.g. dispersal, foraging, homing) is controversial. Here, we examine the geomagnetic and olfactory imprinting hypotheses of natal homing with datasets that recorded variation in the migratory routes of sockeye (Oncorhynchus nerka) and pink (Oncorhynchus gorbuscha) salmon returning from the Pacific Ocean to the Fraser River, British Columbia. Drift of the magnetic field (i.e. geomagnetic imprinting) uniquely accounted for 23.2% and 44.0% of the variation in migration routes for sockeye and pink salmon, respectively. Ocean circulation (i.e. olfactory imprinting) predicted 6.1% and 0.1% of the variation in sockeye and pink migration routes, respectively. Sea surface temperature (a variable influencing salmon distribution but not navigation, directly) accounted for 13.0% of the variation in sockeye migration but was unrelated to pink migration. These findings suggest that geomagnetic navigation plays an important role in long-distance homing in salmon and that consideration of navigation mechanisms can aid in the management of migratory fishes by better predicting movement patterns. Finally, given the diversity of animals that use the Earth's magnetic field for navigation, geomagnetic drift may provide a unifying explanation for spatio-temporal variation in the movement patterns of many species. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Long-term trends of foE and geomagnetic activity variations

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A. V. Mikhailov

2003-03-01

Full Text Available A relationship between foE trends and geomagnetic activity long-term variations has been revealed for the first time. By analogy with earlier obtained results on the foF2 trends it is possible to speak about the geomagnetic control of the foE long-term trends as well. Periods of increasing geomagnetic activity correspond to negative foE trends, while these trends are positive for the decreasing phase of geomagnetic activity. This "natural" relationship breaks down around 1970 (on some stations later when pronounced positive foE trends have appeared on most of the stations considered. The dependence of foE trends on geomagnetic activity can be related with nitric oxide variations at the E-layer heights. The positive foE trends that appeared after the "break down" effect may also be explained by the [NO] decrease which is not related to geomagnetic activity variations. But negative trends or irregular foE variations on some stations for the same time period require some different mechanism. Chemical pollution of the lower thermosphere due to the anthropogenic activity may be responsible for such abnormal foE behavior after the end of the 1960s.Key words. Ionosphere (ionosphere-atmosphere interactions; ionospheric disturbances

Linear filters as a method of real-time prediction of geomagnetic activity

International Nuclear Information System (INIS)

McPherron, R.L.; Baker, D.N.; Bargatze, L.F.

1985-01-01

Important factors controlling geomagnetic activity include the solar wind velocity, the strength of the interplanetary magnetic field (IMF), and the field orientation. Because these quantities change so much in transit through the solar wind, real-time monitoring immediately upstream of the earth provides the best input for any technique of real-time prediction. One such technique is linear prediction filtering which utilizes past histories of the input and output of a linear system to create a time-invariant filter characterizing the system. Problems of nonlinearity or temporal changes of the system can be handled by appropriate choice of input parameters and piecewise approximation in various ranges of the input. We have created prediction filters for all the standard magnetic indices and tested their efficiency. The filters show that the initial response of the magnetosphere to a southward turning of the IMF peaks in 20 minutes and then again in 55 minutes. After a northward turning, auroral zone indices and the midlatitude ASYM index return to background within 2 hours, while Dst decays exponentially with a time constant of about 8 hours. This paper describes a simple, real-time system utilizing these filters which could predict a substantial fraction of the variation in magnetic activity indices 20 to 50 minutes in advance

Predictive models for radial sap flux variation in coniferous, diffuse-porous and ring-porous temperate trees.

Science.gov (United States)

Berdanier, Aaron B; Miniat, Chelcy F; Clark, James S

2016-08-01

Accurately scaling sap flux observations to tree or stand levels requires accounting for variation in sap flux between wood types and by depth into the tree. However, existing models for radial variation in axial sap flux are rarely used because they are difficult to implement, there is uncertainty about their predictive ability and calibration measurements are often unavailable. Here we compare different models with a diverse sap flux data set to test the hypotheses that radial profiles differ by wood type and tree size. We show that radial variation in sap flux is dependent on wood type but independent of tree size for a range of temperate trees. The best-fitting model predicted out-of-sample sap flux observations and independent estimates of sapwood area with small errors, suggesting robustness in the new settings. We develop a method for predicting whole-tree water use with this model and include computer code for simple implementation in other studies. Published by Oxford University Press 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Diurnal changes of earthquake activity and geomagnetic Sq-variations

Directory of Open Access Journals (Sweden)

G. Duma

2003-01-01

Full Text Available Statistic analyses demonstrate that the probability of earthquake occurrence in many earthquake regions strongly depends on the time of day, that is on Local Time (e.g. Conrad, 1909, 1932; Shimshoni, 1971; Duma, 1997; Duma and Vilardo, 1998. This also applies to strong earthquake activity. Moreover, recent observations reveal an involvement of the regular diurnal variations of the Earth’s magnetic field, commonly known as Sq-variations, in this geodynamic process of changing earthquake activity with the time of day (Duma, 1996, 1999. In the article it is attempted to quantify the forces which result from the interaction between the induced Sq-variation currents in the Earth’s lithosphere and the regional Earth’s magnetic field, in order to assess the influence on the tectonic stress field and on seismic activity. A reliable model is obtained, which indicates a high energy involved in this process. The effect of Sq-induction is compared with the results of the large scale electromagnetic experiment "Khibiny" (Velikhov, 1989, where a giant artificial current loop was activated in the Barents Sea.

Characteristics of seasonal variation and solar activity dependence of the geomagnetic solar quiet daily variation

Science.gov (United States)

Shinbori, A.; Koyama, Y.; Nose, M.; Hori, T.

2017-12-01

Characteristics of seasonal variation and solar activity dependence of the X- and Y-components of the geomagnetic solar quiet (Sq) daily variation at Memanbetsu in mid-latitudes and Guam near the equator have been investigated using long-term geomagnetic field data with 1-h time resolution from 1957 to 2016. In this analysis, we defined the quiet day when the maximum value of the Kp index is less than 3 for that day. In this analysis, we used the monthly average of the adjusted daily F10.7 corresponding to geomagnetically quiet days. For identification of the monthly mean Sq variation in the X and Y components (Sq-X and Sq-Y), we first determined the baseline of the X and Y components from the average value from 22 to 2 h (LT: local time) for each quiet day. Next, we calculated a deviation from the baseline of the X- and Y-components of the geomagnetic field for each quiet day, and computed the monthly mean value of the deviation for each local time. As a result, Sq-X and Sq-Y shows a clear seasonal variation and solar activity dependence. The amplitude of seasonal variation increases significantly during high solar activities, and is proportional to the solar F10.7 index. The pattern of the seasonal variation is quite different between Sq-X and Sq-Y. The result of the correlation analysis between the solar F10.7 index and Sq-X and Sq-Y shows almost the linear relationship, but the slope and intercept of the linear fitted line varies as function of local time and month. This implies that the sensitivity of Sq-X and Sq-Y to the solar activity is different for different local times and seasons. The local time dependence of the offset value of Sq-Y at Guam and its seasonal variation suggest a magnetic field produced by inter-hemispheric field-aligned currents (FACs). From the sign of the offset value of Sq-Y, it is infer that the inter-hemispheric FACs flow from the summer to winter hemispheres in the dawn and dusk sectors and from the winter to summer hemispheres in

Genetically determined measures of striatal D2 signaling predict prefrontal activity during working memory performance.

Science.gov (United States)

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.

Directory of Open Access Journals (Sweden)

Alessandro Bertolino

2010-02-01

Full Text Available 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.

Phenotypic variation in metabolism and morphology correlating with animal swimming activity in the wild: relevance for the OCLTT (oxygen- and capacity-limitation of thermal tolerance), allocation and performance models

DEFF Research Database (Denmark)

Baktoft, Henrik; Jacobsen, Lene; Skov, Christian

2016-01-01

Ongoing climate change is affecting animal physiology in many parts of the world. Using metabolism, the oxygen- and capacitylimitation of thermal tolerance (OCLTT) hypothesis provides a tool to predict the responses of ectothermic animals to variation in temperature, oxygen availability and p......H in the aquatic environment. The hypothesis remains controversial, however, and has been questioned in several studies. A positive relationship between aerobic metabolic scope and animal activity would be consistent with the OCLTT but has rarely been tested. Moreover, the performance model and the allocation...... model predict positive and negative relationships, respectively, between standard metabolic rate and activity. Finally, animal activity could be affected by individual morphology because of covariation with cost of transport. Therefore, we hypothesized that individual variation in activity is correlated...

Melanopsin gene variations interact with season to predict sleep onset and chronotype.

Science.gov (United States)

Roecklein, Kathryn A; Wong, Patricia M; Franzen, Peter L; Hasler, Brant P; Wood-Vasey, W Michael; Nimgaonkar, Vishwajit L; Miller, Megan A; Kepreos, Kyle M; Ferrell, Robert E; Manuck, Stephen B

2012-10-01

The human melanopsin gene has been reported to mediate risk for seasonal affective disorder (SAD), which is hypothesized to be caused by decreased photic input during winter when light levels fall below threshold, resulting in differences in circadian phase and/or sleep. However, it is unclear if melanopsin increases risk of SAD by causing differences in sleep or circadian phase, or if those differences are symptoms of the mood disorder. To determine if melanopsin sequence variations are associated with differences in sleep-wake behavior among those not suffering from a mood disorder, the authors tested associations between melanopsin gene polymorphisms and self-reported sleep timing (sleep onset and wake time) in a community sample (N = 234) of non-Hispanic Caucasian participants (age 30-54 yrs) with no history of psychological, neurological, or sleep disorders. The authors also tested the effect of melanopsin variations on differences in preferred sleep and activity timing (i.e., chronotype), which may reflect differences in circadian phase, sleep homeostasis, or both. Daylength on the day of assessment was measured and included in analyses. DNA samples were genotyped for melanopsin gene polymorphisms using fluorescence polarization. P10L genotype interacted with daylength to predict self-reported sleep onset (interaction p sleep onset among those with the TT genotype was later in the day when individuals were assessed on longer days and earlier in the day on shorter days, whereas individuals in the other genotype groups (i.e., CC and CT) did not show this interaction effect. P10L genotype also interacted in an analogous way with daylength to predict self-reported morningness (interaction p sleep onset and chronotype as a function of daylength, whereas other genotypes at P10L do not seem to have effects that vary by daylength. A better understanding of how melanopsin confers heightened responsivity to daylength may improve our understanding of a broad range of

Semi-annual Sq-variation in solar activity cycle

Science.gov (United States)

Pogrebnoy, V.; Malosiev, T.

The peculiarities of semi-annual variation in solar activity cycle have been studied. The data from observatories having long observational series and located in different latitude zones were used. The following observatories were selected: Huancayo (magnetic equator), from 1922 to 1959; Apia (low latitudes), from 1912 to 1961; Moscow (middle latitudes), from 1947 to 1965. Based on the hourly values of H-components, the average monthly diurnal amplitudes (a difference between midday and midnight values), according to five international quiet days, were computed. Obtained results were compared with R (relative sunspot numbers) in the ranges of 0-30R, 40-100R, and 140-190R. It was shown, that the amplitude of semi-annual variation increases with R, from minimum to maximum values, on average by 45%. At equatorial Huancayo observatory, the semi-annual Sq(H)-variation appears especially clearly: its maximums take place at periods of equinoxes (March-April, September-October), and minimums -- at periods of solstices (June-July, December-January). At low (Apia observatory) and middle (Moscow observatory) latitudes, the character of semi-annual variation is somewhat different: it appears during the periods of equinoxes, but considerably less than at equator. Besides, with the growth of R, semi-annual variation appears against a background of annual variation, in the form of second peaks (maximum in June). At observatories located in low and middle latitudes, second peaks become more appreciable with an increase of R (March-April and September-October). During the periods of low solar activity, they are insignificant. This work has been carried out with the support from International Scientific and Technology Center (Project #KR-214).

Measured and Predicted Variations in Fast Neutron Spectrum in Massive Shields of Water and Concrete

Energy Technology Data Exchange (ETDEWEB)

Aalto, E; Sandlin, R; Fraeki, R

1965-09-15

The absolute magnitude, and the variations in form, of the fast neutron spectrum during deep penetration (0.8 - 1.1 metre) in massive shields of water, ordinary and magnetite concrete have been studied by using threshold detectors (In (n, h'), S(n,p), Al(n, {alpha})). The results have been compared with predictions by two rigorous (NIOBE, Moments method) and two non-rigorous (multigroup removal-diffusion) shielding codes (NRN, RASH D). The absolute results predicted were in general within 50% of the measured ones, i. e. showed as good or better accuracy than thermal and epithermal flux predictions in the same small-reactor configurations. No difference in accuracy was found between the rigorous and non-rigorous methods. The changes in the relative form of the spectrum (indicated by variations in the (Al/S) and (In/S) reaction rate ratios and amounting to factors up to 3 - 4 during a one metre penetration in water) were rather accurately (within 10 - 30%) predicted by all of the methods. The photonuclear excitation of the 335 keV level used for detecting the In(n, n') reaction was found to distort completely the In results in water at penetrations > 50 cm.

Respiratory variation in peak aortic velocity accurately predicts fluid responsiveness in children undergoing neurosurgery under general anesthesia.

Science.gov (United States)

Morparia, Kavita G; Reddy, Srijaya K; Olivieri, Laura J; Spaeder, Michael C; Schuette, Jennifer J

2018-04-01

The determination of fluid responsiveness in the critically ill child is of vital importance, more so as fluid overload becomes increasingly associated with worse outcomes. Dynamic markers of volume responsiveness have shown some promise in the pediatric population, but more research is needed before they can be adopted for widespread use. Our aim was to investigate effectiveness of respiratory variation in peak aortic velocity and pulse pressure variation to predict fluid responsiveness, and determine their optimal cutoff values. We performed a prospective, observational study at a single tertiary care pediatric center. Twenty-one children with normal cardiorespiratory status undergoing general anesthesia for neurosurgery were enrolled. Respiratory variation in peak aortic velocity (ΔVpeak ao) was measured both before and after volume expansion using a bedside ultrasound device. Pulse pressure variation (PPV) value was obtained from the bedside monitor. All patients received a 10 ml/kg fluid bolus as volume expansion, and were qualified as responders if stroke volume increased >15% as a result. Utility of ΔVpeak ao and PPV and to predict responsiveness to volume expansion was investigated. A baseline ΔVpeak ao value of greater than or equal to 12.3% best predicted a positive response to volume expansion, with a sensitivity of 77%, specificity of 89% and area under receiver operating characteristic curve of 0.90. PPV failed to demonstrate utility in this patient population. Respiratory variation in peak aortic velocity is a promising marker for optimization of perioperative fluid therapy in the pediatric population and can be accurately measured using bedside ultrasonography. More research is needed to evaluate the lack of effectiveness of pulse pressure variation for this purpose.

CERAPP: Collaborative estrogen receptor activity prediction project

DEFF Research Database (Denmark)

Mansouri, Kamel; Abdelaziz, Ahmed; Rybacka, Aleksandra

2016-01-01

). Risk assessors need tools to prioritize chemicals for evaluation in costly in vivo tests, for instance, within the U.S. EPA Endocrine Disruptor Screening Program. oBjectives: We describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project...... States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure-activity relationship models and docking approaches were employed, mostly using a common training set of 1,677 chemical structures provided by the U.S. EPA, to build a total of 40 categorical......: Individual model scores ranged from 0.69 to 0.85, showing high prediction reliabilities. Out of the 32,464 chemicals, the consensus model predicted 4,001 chemicals (12.3%) as high priority actives and 6,742 potential actives (20.8%) to be considered for further testing. conclusion: This project demonstrated...

Peripheral lymphocyte subset variation predicts prostate cancer carbon ion radiotherapy outcomes

Science.gov (United States)

Shi, Ze-Liang; Li, Bing-Xin; Wu, Xian-Wei; Li, Ping; Zhang, Qing; Wei, Xun-Bin; Fu, Shen

2016-01-01

The immune system plays a complementary role in the cytotoxic activity of radiotherapy. Here, we examined changes in immune cell subsets after heavy ion therapy for prostate cancer. The lymphocyte counts were compared with acute radiotherapy-related toxicity, defined according to the Common Terminology Criteria for Adverse Events, and short-term local efficacy, defined based on prostate-specific antigen concentrations. Confirmed prostate cancer patients who had not received previous radiotherapy were administered carbon ion radiotherapy (CIR) in daily fractions of 2.74 GyE with a total dose of 63-66 GyE. Lymphocyte subset counts were investigated before, during and after radiotherapy, and at a 1 month follow-up. Most notable among our findings, the CD4/CD8 ratio and CD19+ cell counts were consistently higher in patients with a complete response (CR) or partial response (PR) to CIR than in those classified in the stable disease (SD) group (P<0.05 for both). But CD3+ and CD8+ cell counts were lower in the CR and PR groups than in the SD group. These results indicate that variations in peripheral lymphocyte subpopulations are predictive of outcome after CIR for prostate cancer. PMID:27029063

Only 7% of the variation in feed efficiency in veal calves can be predicted from variation in feeding motivation, digestion, metabolism, immunology, and behavioral traits in early life

NARCIS (Netherlands)

Gilbert, M.S.; Borne, van den J.J.G.C.; Reenen, van C.G.; Gerrits, W.J.J.

2017-01-01

High interindividual variation in growth performance is commonly observed in veal calf production and appears to depend on milk replacer (MR) composition. Our first objective was to examine whether variation in growth performance in healthy veal calves can be predicted from early life

LONG-TERM VARIATION IN THE SUN’S ACTIVITY CAUSED BY MAGNETIC ROSSBY WAVES IN THE TACHOCLINE

Energy Technology Data Exchange (ETDEWEB)

Zaqarashvili, Teimuraz V. [Space Research Institute, Austrian Academy of Sciences, Schmiedlstrasse 6, 8042 Graz (Austria); Oliver, Ramon; Ballester, Jose Luis [Departament de Física, Universitat de les Illes Balears, E-07122 Palma de Mallorca (Spain); Hanslmeier, Arnold [Institute für Physik, Geophysik Astrophysik und Meteorologie, University of Graz, Univ.-Platz 5, 8010 Graz (Austria); Carbonell, Marc [Departament de Matemàtiques i Informàtica, Universitat de les Illes Balears, E-07122 Palma de Mallorca (Spain); Gachechiladze, Tamar [Abastumani Astrophysical Observatory at Ilia State University, Tbilisi, Georgia (United States); Usoskin, Ilya G., E-mail: teimuraz.zaqarashvili@oeaw.ac.at [Sodankylä Geophysical Observatory and ReSoLVE Centre of Excellence, University of Oulu, FI-90014 Oulo (Finland)

2015-06-01

Long-term records of sunspot number and concentrations of cosmogenic radionuclides (10Be and 14C) on the Earth reveal the variation of the Sun's magnetic activity over hundreds and thousands of years. We identify several clear periods in sunspot, 10Be, and 14C data as 1000, 500, 350, 200, and 100 years. We found that the periods of the first five spherical harmonics of the slow magnetic Rossby mode in the presence of a steady toroidal magnetic field of 1200–1300 G in the lower tachocline are in perfect agreement with the timescales of observed variations. The steady toroidal magnetic field can be generated in the lower tachocline either due to the steady dynamo magnetic field for low magnetic diffusivity or due to the action of the latitudinal differential rotation on the weak poloidal primordial magnetic field, which penetrates from the radiative interior. The slow magnetic Rossby waves lead to variations of the steady toroidal magnetic field in the lower tachocline, which modulate the dynamo magnetic field and consequently the solar cycle strength. This result constitutes a key point for long-term prediction of the cycle strength. According to our model, the next deep minimum in solar activity is expected during the first half of this century.

LONG-TERM VARIATION IN THE SUN’S ACTIVITY CAUSED BY MAGNETIC ROSSBY WAVES IN THE TACHOCLINE

International Nuclear Information System (INIS)

Zaqarashvili, Teimuraz V.; Oliver, Ramon; Ballester, Jose Luis; Hanslmeier, Arnold; Carbonell, Marc; Gachechiladze, Tamar; Usoskin, Ilya G.

2015-01-01

Long-term records of sunspot number and concentrations of cosmogenic radionuclides (10Be and 14C) on the Earth reveal the variation of the Sun's magnetic activity over hundreds and thousands of years. We identify several clear periods in sunspot, 10Be, and 14C data as 1000, 500, 350, 200, and 100 years. We found that the periods of the first five spherical harmonics of the slow magnetic Rossby mode in the presence of a steady toroidal magnetic field of 1200–1300 G in the lower tachocline are in perfect agreement with the timescales of observed variations. The steady toroidal magnetic field can be generated in the lower tachocline either due to the steady dynamo magnetic field for low magnetic diffusivity or due to the action of the latitudinal differential rotation on the weak poloidal primordial magnetic field, which penetrates from the radiative interior. The slow magnetic Rossby waves lead to variations of the steady toroidal magnetic field in the lower tachocline, which modulate the dynamo magnetic field and consequently the solar cycle strength. This result constitutes a key point for long-term prediction of the cycle strength. According to our model, the next deep minimum in solar activity is expected during the first half of this century

Daily and seasonal variations of outdoor alpha-activity concentration in Salzburg city/Austria

International Nuclear Information System (INIS)

Lettner, H.; Hubmer, A.K.; Rolle, R.; Winkler, R.; Steinhaeusler, F.

1996-01-01

Long-term continuous measurements of the atmospheric outdoor alpha-activity concentration have been performed by using a radioaerosol-monitor, roof-mounted 20 m above ground. The alpha-activity concentration was identified to be predominantly attributed to radon progeny. The total alpha-activity covers a range of two orders of magnitude. Three different components of variations could be identified with regard to temporal variations: Short-term diurnal component (daily variation), mid-term component (days to weeks) and long-term component (seasonal variation). Continuous measurements have been recorded since the end of 1993. The results of continuous measurements of the outdoor alpha-activity concentration over a time span from January 1994 to June 1995 are presented. (author)

Predicting Variation of Folk Songs: A Corpus Analysis Study on the Memorability of Melodies

Directory of Open Access Journals (Sweden)

Berit Janssen

2017-04-01

Full Text Available We present a hypothesis-driven study on the variation of melody phrases in a collection of Dutch folk songs. We investigate the variation of phrases within the folk songs through a pattern matching method which detects occurrences of these phrases within folk song variants, and ask the question: do the phrases which show less variation have different properties than those which do? We hypothesize that theories on melody recall may predict variation, and as such, investigate phrase length, the position and number of repetitions of a given phrase in the melody in which it occurs, as well as expectancy and motif repetivity. We show that all of these predictors account for the observed variation to a moderate degree, and that, as hypothesized, those phrases vary less which are rather short, contain highly expected melodic material, occur relatively early in the melody, and contain small pitch intervals. A large portion of the variance is left unexplained by the current model, however, which leads us to a discussion of future approaches to study memorability of melodies.

TH-A-9A-01: Active Optical Flow Model: Predicting Voxel-Level Dose Prediction in Spine SBRT

Energy Technology Data Exchange (ETDEWEB)

Liu, J; Wu, Q.J.; Yin, F; Kirkpatrick, J; Cabrera, A [Duke University Medical Center, Durham, NC (United States); Ge, Y [University of North Carolina at Charlotte, Charlotte, NC (United States)

2014-06-15

Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into five groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH

TH-A-9A-01: Active Optical Flow Model: Predicting Voxel-Level Dose Prediction in Spine SBRT

International Nuclear Information System (INIS)

Liu, J; Wu, Q.J.; Yin, F; Kirkpatrick, J; Cabrera, A; Ge, Y

2014-01-01

Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into five groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH

Isomorph theory prediction for the dielectric loss variation along an isochrone

DEFF Research Database (Denmark)

Xiao, Wence; Tofteskov, Jon; Dyre, J. C.

2015-01-01

This paper derives a prediction for the variation of the amplitude of the dielectric loss from isomorph theory, and presents an experimental test of the prediction performed by measuring the dielectric relaxation behavior of the van der Waals liquid 5-phenyl-4-ether (5PPE). The liquid is studied...... isomorph-invariant terms, one of which is used in analyzing our data. It is the frequency-dependent term χe(f)ργ − 1, with electric susceptibility χe, density ρ, and density-scaling factor γ. Due to the unique design of our experimental setup, we obtain dielectric loss data where the amplitude...... is reproducible ± 0.1 %. We moreover find that the empty capacitance of the capacitor cell is stable within ± 0.3 % in our measuring range and can be assumed to be constant. Using this we predict for two isomorph states there is C2″(f) = C1″(f)(ρ1/ρ2)γ−1 to scale the imaginary capacitance, where C1...

Neural activity patterns in response to interspecific and intraspecific variation in mating calls in the túngara frog.

Directory of Open Access Journals (Sweden)

Mukta Chakraborty

2010-09-01

Full Text Available During mate choice, individuals must classify potential mates according to species identity and relative attractiveness. In many species, females do so by evaluating variation in the signals produced by males. Male túngara frogs (Physalaemus pustulosus can produce single note calls (whines and multi-note calls (whine-chucks. While the whine alone is sufficient for species recognition, females greatly prefer the whine-chuck when given a choice.To better understand how the brain responds to variation in male mating signals, we mapped neural activity patterns evoked by interspecific and intraspecific variation in mating calls in túngara frogs by measuring expression of egr-1. We predicted that egr-1 responses to conspecific calls would identify brain regions that are potentially important for species recognition and that at least some of those brain regions would vary in their egr-1 responses to mating calls that vary in attractiveness. We measured egr-1 in the auditory brainstem and its forebrain targets and found that conspecific whine-chucks elicited greater egr-1 expression than heterospecific whines in all but three regions. We found no evidence that preferred whine-chuck calls elicited greater egr-1 expression than conspecific whines in any of eleven brain regions examined, in contrast to predictions that mating preferences in túngara frogs emerge from greater responses in the auditory system.Although selectivity for species-specific signals is apparent throughout the túngara frog brain, further studies are necessary to elucidate how neural activity patterns vary with the attractiveness of conspecific mating calls.

Prediction of Human Activity by Discovering Temporal Sequence Patterns.

Science.gov (United States)

Li, Kang; Fu, Yun

2014-08-01

Early prediction of ongoing human activity has become more valuable in a large variety of time-critical applications. To build an effective representation for prediction, human activities can be characterized by a complex temporal composition of constituent simple actions and interacting objects. Different from early detection on short-duration simple actions, we propose a novel framework for long -duration complex activity prediction by discovering three key aspects of activity: Causality, Context-cue, and Predictability. The major contributions of our work include: (1) a general framework is proposed to systematically address the problem of complex activity prediction by mining temporal sequence patterns; (2) probabilistic suffix tree (PST) is introduced to model causal relationships between constituent actions, where both large and small order Markov dependencies between action units are captured; (3) the context-cue, especially interactive objects information, is modeled through sequential pattern mining (SPM), where a series of action and object co-occurrence are encoded as a complex symbolic sequence; (4) we also present a predictive accumulative function (PAF) to depict the predictability of each kind of activity. The effectiveness of our approach is evaluated on two experimental scenarios with two data sets for each: action-only prediction and context-aware prediction. Our method achieves superior performance for predicting global activity classes and local action units.

Final Scientific/Technical Report for Subseasonal to Seasonal Prediction of Extratropical Storm Track Activity over the U.S. using NMME data

Energy Technology Data Exchange (ETDEWEB)

Chang, Edmund Kar-Man [Stony Brook Univ., NY (United States)

2017-10-30

The goals of the project are: 1) To develop and assess subseasonal to seasonal prediction products for storm track activity derived from NMME data; 2) Assess how much of the predictable signal can be associated with ENSO and other modes of large scale low frequency atmosphere-ocean variability; and 3) Further explore the link between storm track variations and extreme weather statistics. Significant findings of this project include the followings: 1) Our assessment of NMME reforecasts of storm track variability has demonstrated that NMME models have substantial skill in predicting storm track activity in the vicinity of North America - Subseasonal skill is high only for leads of less than 1 month. However, seasonal (winter) prediction skill near North America is high even out to 4 to 5 months lead - Much of the skill for leads of 1 month or longer is related to the influence of ENSO - Nevertheless, lead 0 NMME predictions are significantly more skillful than those based on ENSO influence 2) Our results have demonstrated that storm track variations highly modulate the frequency of occurrence of weather extremes - Extreme cold, high wind, and extreme precipitation events in winter - Extreme heat events in summer - These results suggest that NMME storm track predictions can be developed to serve as a useful guidance to assist the formulation of monthly/seasonal outlooks

Toward Meaningful Manufacturing Variation Data in Design - Feature Based Description of Variation in Manufacturing Processes

DEFF Research Database (Denmark)

Eifler, Tobias; Boorla, Srinivasa Murthy; Howard, Thomas J.

2016-01-01

The need to mitigate the effects of manufacturing variation already in design is nowadays commonly acknowledged and has led to a wide use of predictive modeling techniques, tolerancing approaches, etc. in industry. The trustworthiness of corresponding variation analyses is, however, not ensured...... by the availability of sophisticated methods and tools alone, but does evidently also depend on the accuracy of the input information used. As existing approaches for the description of manufacturing variation focus however, almost exclusively, on monitoring and controlling production processes, there is frequently...... a lack of objective variation data in design. As a result, variation analyses and tolerancing activities rely on numerous assumptions made to fill the gaps of missing or incomplete data. To overcome this hidden subjectivity, a schema for a consistent and standardised description of manufacturing...

Study of variations of radon emanations from soil in Morocco using solid state nuclear track detectors. Correlations with atmospheric parameters and seismic activities

International Nuclear Information System (INIS)

Boukhal, H.

1993-01-01

This study investigates the quantity variations of radon emanating from soil in accordance with time. It aims to verify the possibility of the radon sign use in earthquake prediction. Regular measures of radon concentration in soil have been carried out over the two years 1991 and 1992 in five towns of Morocco: Rabat, Tetouan, Ifrane and Khouribga, and in geophysic observatory of Ibn Rochd (Berchid region). The measuring method is based on the solid state nuclear track detectors technique. The obtained results have shown an influence of the atmospheric effects on the radon emanation. The experiment proved that, on one hand, the variations of the aforesaid influence are correlated to variations of the pluviometry and the atmospheric temperature and, on the other hand, there is no notable effect of atmospheric pressure or atmospheric humidity. The good correlations between the different seismic activities and the variations of radon emanation rate in the five measurement stations, have shown the interest of radon use in the earthquake prediction field. 81 refs., 100 figs., 17 tabs.(F. M.)

Only 7% of the variation in feed efficiency in veal calves can be predicted from variation in feeding motivation, digestion, metabolism, immunology, and behavioral traits in early life.

Science.gov (United States)

Gilbert, M S; van den Borne, J J G C; van Reenen, C G; Gerrits, W J J

2017-10-01

High interindividual variation in growth performance is commonly observed in veal calf production and appears to depend on milk replacer (MR) composition. Our first objective was to examine whether variation in growth performance in healthy veal calves can be predicted from early life characterization of these calves. Our second objective was to determine whether these predictions differ between calves that are fed a high- or low-lactose MR in later life. A total of 180 male Holstein-Friesian calves arrived at the facilities at 17 ± 3.4 d of age, and blood samples were collected before the first feeding. Subsequently, calves were characterized in the following 9 wk (period 1) using targeted challenges related to traits within each of 5 categories: feeding motivation, digestion, postabsorptive metabolism, behavior and stress, and immunology. In period 2 (wk 10-26), 130 calves were equally divided over 2 MR treatments: a control MR that contained lactose as the only carbohydrate source and a low-lactose MR in which 51% of the lactose was isocalorically replaced by glucose, fructose, and glycerol (2:1:2 ratio). Relations between early life characteristics and growth performance in later life were assessed in 117 clinically healthy calves. Average daily gain (ADG) in period 2 tended to be greater for control calves (1,292 ± 111 g/d) than for calves receiving the low-lactose MR (1,267 ± 103 g/d). Observations in period 1 were clustered per category using principal component analysis, and the resulting principal components were used to predict performance in period 2 using multiple regression procedures. Variation in observations in period 1 predicted 17% of variation in ADG in period 2. However, this was mainly related to variation in solid feed refusals. When ADG was adjusted to equal solid feed intake, only 7% of the variation in standardized ADG in period 2, in fact reflecting feed efficiency, could be explained by early life measurements. This indicates that >90

Prediction of interannual climate variations

International Nuclear Information System (INIS)

Shukla, J.

1993-01-01

It has been known for some time that the behavior of the short-term fluctuations of the earth's atmosphere resembles that of a chaotic non-linear dynamical system, and that the day-to-day weather cannot be predicted beyond a few weeks. However, it has also been found that the interactions of the atmosphere with the underlying oceans and the land surfaces can produce fluctuations whose time scales are much longer than the limits of deterministic prediction of weather. It is, therefore, natural to ask whether it is possible that the seasonal and longer time averages of climate fluctuations can be predicted with sufficient skill to be beneficial for social and economic applications, even though the details of day-to-day weather cannot be predicted beyond a few weeks. The main objective of the workshop was to address this question by assessing the current state of knowledge on predictability of seasonal and interannual climate variability and to investigate various possibilities for its prediction. (orig./KW)

Bi-directional SIFT predicts a subset of activating mutations.

Directory of Open Access Journals (Sweden)

William Lee

Full Text Available Advancements in sequencing technologies have empowered recent efforts to identify polymorphisms and mutations on a global scale. The large number of variations and mutations found in these projects requires high-throughput tools to identify those that are most likely to have an impact on function. Numerous computational tools exist for predicting which mutations are likely to be functional, but none that specifically attempt to identify mutations that result in hyperactivation or gain-of-function. Here we present a modified version of the SIFT (Sorting Intolerant from Tolerant algorithm that utilizes protein sequence alignments with homologous sequences to identify functional mutations based on evolutionary fitness. We show that this bi-directional SIFT (B-SIFT is capable of identifying experimentally verified activating mutants from multiple datasets. B-SIFT analysis of large-scale cancer genotyping data identified potential activating mutations, some of which we have provided detailed structural evidence to support. B-SIFT could prove to be a valuable tool for efforts in protein engineering as well as in identification of functional mutations in cancer.

Variations of plasmaspheric field-aligned electron and ion densities (90-4000 km) during quiet to moderately active (Kp < 4) geomagnetic conditions

Science.gov (United States)

Sonwalkar, V. S.; Reddy, A.

2017-12-01

Variation in field-aligned electron and ion densities as a function of geomagnetic activity are important parameters in the physics of the thermosphere-ionosphere-magnetosphere coupling. Using whistler mode sounding from IMAGE, we report variations in field-aligned electron density and O+/H+ transition height (HT) during two periods (16-23 Aug 2005; 24 Sep-06 Oct 2005) when geomagnetic conditions were quiet (maximum Kp in the past 24 hours, Kpmax,24 ≤ 2) to moderately active (2 quiet time, during moderate geomagnetic activity: (1) O+/H+ transition height was roughly same; (2) electron density variations below HT showed no trend; (3) electron density above HT increased ( 10-40 %). The measured electron density is in agreement with in situ measurements from CHAMP (350 km) and DMSP (850 km) and past space borne (e. g., ISIS) measurements but the F2 peak density is a factor of 2 lower relative to that measured by ground ionosondes and that predicted by IRI-2012 empirical model. The measured transition height is consistent with OGO 4, Explorer 31, and C/NOFS measurements but is lower than that from IRI-2012. The observed variations in electron density at F2 peak are consistent with past work and are attributed to solar, geomagnetic, and meteorological causes [e. g. Risibeth and Mendillo, 2001; Forbes et al., 2000]. To the best of our knowledge, variations in field-aligned electron density above transition height at mid-latitudes during quiet to moderately active periods have not been reported in the past. Further investigation using physics based models (e. g., SAMI3) is required to explain the observed variations.

Variations of Solar Non-axisymmetric Activity

Science.gov (United States)

Gyenge, N.; Baranyi, T.; Ludmány, A.

The temporal behaviour of solar active longitudes has been examined by using two sunspot catalogues, the Greenwich Photoheliographic Results (GPR) and the Debrecen Photoheliographic Data (DPD). The time-longitude diagrams of the activity distribution reveal the preferred longitudinal zones and their migration with respect to the Carrington frame. The migration paths outline a set of patterns in which the activity zone has alternating prograde/retrograde angular velocities with respect to the Carrington rotation rate. The time profiles of these variations can be described by a set of successive parabolae. Two similar migration paths have been selected from these datasets, one northern path during cycles 21 - 22 and one southern path during cycles 13 - 14, for closer examination and comparison of their dynamical behaviours. The rates of sunspot emergence exhibited in both migration paths similar periodicities, close to 1.3 years. This behaviour may imply that the active longitude is connected to the bottom of convection zone.

Variation in GYS1 interacts with exercise and gender to predict cardiovascular mortality.

Directory of Open Access Journals (Sweden)

Jenny Fredriksson

Full Text Available BACKGROUND: The muscle glycogen synthase gene (GYS1 has been associated with type 2 diabetes (T2D, the metabolic syndrome (MetS, male myocardial infarction and a defective increase in muscle glycogen synthase protein in response to exercise. We addressed the questions whether polymorphism in GYS1 can predict cardiovascular (CV mortality in a high-risk population, if this risk is influenced by gender or physical activity, and if the association is independent of genetic variation in nearby apolipoprotein E gene (APOE. METHODOLOGY/PRINCIPAL FINDINGS: Polymorphisms in GYS1 (XbaIC>T and APOE (-219G>T, epsilon2/epsilon3/epsilon4 were genotyped in 4,654 subjects participating in the Botnia T2D-family study and followed for a median of eight years. Mortality analyses were performed using Cox proportional-hazards regression. During the follow-up period, 749 individuals died, 409 due to CV causes. In males the GYS1 XbaI T-allele (hazard ratio (HR 1.9 [1.2-2.9], T2D (2.5 [1.7-3.8], earlier CV events (1.7 [1.2-2.5], physical inactivity (1.9 [1.2-2.9] and smoking (1.5 [1.0-2.3] predicted CV mortality. The GYS1 XbaI T-allele predicted CV mortality particularly in physically active males (HR 1.7 [1.3-2.0]. Association of GYS1 with CV mortality was independent of APOE (219TT/epsilon4, which by its own exerted an effect on CV mortality risk in females (2.9 [1.9-4.4]. Other independent predictors of CV mortality in females were fasting plasma glucose (1.2 [1.1-1.2], high body mass index (BMI (1.0 [1.0-1.1], hypertension (1.9 [1.2-3.1], earlier CV events (1.9 [1.3-2.8] and physical inactivity (1.9 [1.2-2.8]. CONCLUSIONS/SIGNIFICANCE: Polymorphisms in GYS1 and APOE predict CV mortality in T2D families in a gender-specific fashion and independently of each other. Physical exercise seems to unmask the effect associated with the GYS1 polymorphism, rendering carriers of the variant allele less susceptible to the protective effect of exercise on the risk of CV death

Rare copy number deletions predict individual variation in intelligence.

Directory of Open Access Journals (Sweden)

Ronald A Yeo

2011-01-01

Full Text Available Phenotypic variation in human intellectual functioning shows substantial heritability, as demonstrated by a long history of behavior genetic studies. Many recent molecular genetic studies have attempted to uncover specific genetic variations responsible for this heritability, but identified effects capture little variance and have proven difficult to replicate. The present study, motivated an interest in "mutation load" emerging from evolutionary perspectives, examined the importance of the number of rare (or infrequent copy number variations (CNVs, and the total number of base pairs included in such deletions, for psychometric intelligence. Genetic data was collected using the Illumina 1MDuoBeadChip Array from a sample of 202 adult individuals with alcohol dependence, and a subset of these (N = 77 had been administered the Wechsler Abbreviated Scale of Intelligence (WASI. After removing CNV outliers, the impact of rare genetic deletions on psychometric intelligence was investigated in 74 individuals. The total length of the rare deletions significantly and negatively predicted intelligence (r = -.30, p = .01. As prior studies have indicated greater heritability in individuals with relatively higher parental socioeconomic status (SES, we also examined the impact of ethnicity (Anglo/White vs. Other, as a proxy measure of SES; these groups did not differ on any genetic variable. This categorical variable significantly moderated the effect of length of deletions on intelligence, with larger effects being noted in the Anglo/White group. Overall, these results suggest that rare deletions (between 5% and 1% population frequency or less adversely affect intellectual functioning, and that pleotropic effects might partly account for the association of intelligence with health and mental health status. Significant limitations of this research, including issues of generalizability and CNV measurement, are discussed.

Rare Copy Number Deletions Predict Individual Variation in Intelligence

Science.gov (United States)

Yeo, Ronald A.; Gangestad, Steven W.; Liu, Jingyu; Calhoun, Vince D.; Hutchison, Kent E.

2011-01-01

Phenotypic variation in human intellectual functioning shows substantial heritability, as demonstrated by a long history of behavior genetic studies. Many recent molecular genetic studies have attempted to uncover specific genetic variations responsible for this heritability, but identified effects capture little variance and have proven difficult to replicate. The present study, motivated an interest in “mutation load” emerging from evolutionary perspectives, examined the importance of the number of rare (or infrequent) copy number variations (CNVs), and the total number of base pairs included in such deletions, for psychometric intelligence. Genetic data was collected using the Illumina 1MDuoBeadChip Array from a sample of 202 adult individuals with alcohol dependence, and a subset of these (N = 77) had been administered the Wechsler Abbreviated Scale of Intelligence (WASI). After removing CNV outliers, the impact of rare genetic deletions on psychometric intelligence was investigated in 74 individuals. The total length of the rare deletions significantly and negatively predicted intelligence (r = −.30, p = .01). As prior studies have indicated greater heritability in individuals with relatively higher parental socioeconomic status (SES), we also examined the impact of ethnicity (Anglo/White vs. Other), as a proxy measure of SES; these groups did not differ on any genetic variable. This categorical variable significantly moderated the effect of length of deletions on intelligence, with larger effects being noted in the Anglo/White group. Overall, these results suggest that rare deletions (between 5% and 1% population frequency or less) adversely affect intellectual functioning, and that pleotropic effects might partly account for the association of intelligence with health and mental health status. Significant limitations of this research, including issues of generalizability and CNV measurement, are discussed. PMID:21298096

Common Variation in the DOPA Decarboxylase (DDC) Gene and Human Striatal DDC Activity In Vivo.

Science.gov (United States)

Eisenberg, Daniel P; Kohn, Philip D; Hegarty, Catherine E; Ianni, Angela M; Kolachana, Bhaskar; Gregory, Michael D; Masdeu, Joseph C; Berman, Karen F

2016-08-01

The synthesis of multiple amine neurotransmitters, such as dopamine, norepinephrine, serotonin, and trace amines, relies in part on DOPA decarboxylase (DDC, AADC), an enzyme that is required for normative neural operations. Because rare, loss-of-function mutations in the DDC gene result in severe enzymatic deficiency and devastating autonomic, motor, and cognitive impairment, DDC common genetic polymorphisms have been proposed as a source of more moderate, but clinically important, alterations in DDC function that may contribute to risk, course, or treatment response in complex, heritable neuropsychiatric illnesses. However, a direct link between common genetic variation in DDC and DDC activity in the living human brain has never been established. We therefore tested for this association by conducting extensive genotyping across the DDC gene in a large cohort of 120 healthy individuals, for whom DDC activity was then quantified with [(18)F]-FDOPA positron emission tomography (PET). The specific uptake constant, Ki, a measure of DDC activity, was estimated for striatal regions of interest and found to be predicted by one of five tested haplotypes, particularly in the ventral striatum. These data provide evidence for cis-acting, functional common polymorphisms in the DDC gene and support future work to determine whether such variation might meaningfully contribute to DDC-mediated neural processes relevant to neuropsychiatric illness and treatment.

Patient-ventilator asynchrony affects pulse pressure variation prediction of fluid responsiveness.

Science.gov (United States)

Messina, Antonio; Colombo, Davide; Cammarota, Gianmaria; De Lucia, Marta; Cecconi, Maurizio; Antonelli, Massimo; Corte, Francesco Della; Navalesi, Paolo

2015-10-01

During partial ventilatory support, pulse pressure variation (PPV) fails to adequately predict fluid responsiveness. This prospective study aims to investigate whether patient-ventilator asynchrony affects PPV prediction of fluid responsiveness during pressure support ventilation (PSV). This is an observational physiological study evaluating the response to a 500-mL fluid challenge in 54 patients receiving PSV, 27 without (Synch) and 27 with asynchronies (Asynch), as assessed by visual inspection of ventilator waveforms by 2 skilled blinded physicians. The area under the curve was 0.71 (confidence interval, 0.57-0.83) for the overall population, 0.86 (confidence interval, 0.68-0.96) in the Synch group, and 0.53 (confidence interval, 0.33-0.73) in the Asynch group (P = .018). Sensitivity and specificity of PPV were 78% and 89% in the Synch group and 36% and 46% in the Asynch group. Logistic regression showed that the PPV prediction was influenced by patient-ventilator asynchrony (odds ratio, 8.8 [2.0-38.0]; P < .003). Of the 27 patients without asynchronies, 12 had a tidal volume greater than or equal to 8 mL/kg; in this subgroup, the rate of correct classification was 100%. Patient-ventilator asynchrony affects PPV performance during partial ventilatory support influencing its efficacy in predicting fluid responsiveness. Copyright © 2015 Elsevier Inc. All rights reserved.

Thermospheric mass density variations during geomagnetic storms and a prediction model based on the merging electric field

Science.gov (United States)

Liu, R.; Lühr, H.; Doornbos, E.; Ma, S.-Y.

2010-09-01

With the help of four years (2002-2005) of CHAMP accelerometer data we have investigated the dependence of low and mid latitude thermospheric density on the merging electric field, Em, during major magnetic storms. Altogether 30 intensive storm events (Dstmineffect in order to obtain good results for magnetic storms of all activity levels. The memory effect of the thermosphere is accounted for by a weighted integration of Em over the past 3 h. In addition, a lag time of the mass density response to solar wind input of 0 to 4.5 h depending on latitude and local time is considered. A linear model using the preconditioned color: #000;">Em as main controlling parameter for predicting mass density changes during magnetic storms is developed: ρ=0.5 color: #000;">Em + ρamb, where ρamb is based on the mean density during the quiet day before the storm. We show that this simple relation predicts all storm-induced mass density variations at CHAMP altitude fairly well especially if orbital averages are considered.

Between-school variation in physical activity, aerobic fitness, and organized sports participation

DEFF Research Database (Denmark)

Kristensen, Peter L; Olesen, Line G; Ried-Larsen, Mathias

2013-01-01

Abstract A large proportion of a child's day is spent at school interacting with certain physical surroundings, teachers, and school friends. Thus, schools could have a marked impact on establishing physical activity habits. The aim of the present study was to assess between-school variation...... between-school variation in physical activity provides information about the extent to which children adjust their physical activity habits according to the social and environmental circumstances that they share, and helps to plan future school-based physical activity studies, especially in terms...... of sample size and power calculation....

Combined Active and Reactive Power Control of Wind Farms based on Model Predictive Control

DEFF Research Database (Denmark)

Zhao, Haoran; Wu, Qiuwei; Wang, Jianhui

2017-01-01

This paper proposes a combined wind farm controller based on Model Predictive Control (MPC). Compared with the conventional decoupled active and reactive power control, the proposed control scheme considers the significant impact of active power on voltage variations due to the low X=R ratio...... of wind farm collector systems. The voltage control is improved. Besides, by coordination of active and reactive power, the Var capacity is optimized to prevent potential failures due to Var shortage, especially when the wind farm operates close to its full load. An analytical method is used to calculate...... the sensitivity coefficients to improve the computation efficiency and overcome the convergence problem. Two control modes are designed for both normal and emergency conditions. A wind farm with 20 wind turbines was used to verify the proposed combined control scheme....

CERAPP: Collaborative Estrogen Receptor Activity Prediction Project

Data.gov (United States)

U.S. Environmental Protection Agency — Data from a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) demonstrating using predictive computational...

Explained variation and predictive accuracy in general parametric statistical models: the role of model misspecification

DEFF Research Database (Denmark)

Rosthøj, Susanne; Keiding, Niels

2004-01-01

When studying a regression model measures of explained variation are used to assess the degree to which the covariates determine the outcome of interest. Measures of predictive accuracy are used to assess the accuracy of the predictions based on the covariates and the regression model. We give a ...... a detailed and general introduction to the two measures and the estimation procedures. The framework we set up allows for a study of the effect of misspecification on the quantities estimated. We also introduce a generalization to survival analysis....

Prediction of Commuter’s Daily Time Allocation

Directory of Open Access Journals (Sweden)

Fang Zong

2013-10-01

Full Text Available This paper presents a model system to predict the time allocation in commuters’ daily activity-travel pattern. The departure time and the arrival time are estimated with Ordered Probit model and Support Vector Regression is introduced for travel time and activity duration prediction. Applied in a real-world time allocation prediction experiment, the model system shows a satisfactory level of prediction accuracy. This study provides useful insights into commuters’ activity-travel time allocation decision by identifying the important influences, and the results are readily applied to a wide range of transportation practice, such as travel information system, by providing reliable forecast for variations in travel demand over time. By introducing the Support Vector Regression, it also makes a methodological contribution in enhancing prediction accuracy of travel time and activity duration prediction.

On temporal variation of Ceasium isotopes activities in airborne and fallout

International Nuclear Information System (INIS)

Hien, P.D.; Binh, N.T.; Y, T.; Bac, V.T.; Ngo, N.T.; Luyen, T.V.

1992-01-01

Monthly variations of Cs-137 and Cs-134 activities in airborne and fallout collected in Dalat from 1986 to 1991 are presented. The variations exhibit distinct maxima in December-January, when dry fallout was predominant. The observed peaks are explained by the intrusion of cold air masses with higher radioactivity from temperate latitudes during the development of large-scale anticyclones frequently observed in the most active winter monsoon period. Very high dry fallout velocity (about 10 cm/s) determined from the airborne and fallout activities clearly demonstrates one of the most relevant characteristics of cold air masses: behind the cold front vertical air motion is descending.(Authors) (1 Fig. 2 Tables)

Nonlinear dynamical modeling and prediction of the terrestrial magnetospheric activity

International Nuclear Information System (INIS)

Vassiliadis, D.

1992-01-01

The irregular activity of the magnetosphere results from its complex internal dynamics as well as the external influence of the solar wind. The dominating self-organization of the magnetospheric plasma gives rise to repetitive, large-scale coherent behavior manifested in phenomena such as the magnetic substorm. Based on the nonlinearity of the global dynamics this dissertation examines the magnetosphere as a nonlinear dynamical system using time series analysis techniques. Initially the magnetospheric activity is modeled in terms of an autonomous system. A dimension study shows that its observed time series is self-similar, but the correlation dimension is high. The implication of a large number of degrees of freedom is confirmed by other state space techniques such as Poincare sections and search for unstable periodic orbits. At the same time a stability study of the time series in terms of Lyapunov exponents suggests that the series is not chaotic. The absence of deterministic chaos is supported by the low predictive capability of the autonomous model. Rather than chaos, it is an external input which is largely responsible for the irregularity of the magnetospheric activity. In fact, the external driving is so strong that the above state space techniques give results for magnetospheric and solar wind time series that are at least qualitatively similar. Therefore the solar wind input has to be included in a low-dimensional nonautonomous model. Indeed it is shown that such a model can reproduce the observed magnetospheric behavior up to 80-90 percent. The characteristic coefficients of the model show little variation depending on the external disturbance. The impulse response is consistent with earlier results of linear prediction filters. The model can be easily extended to contain nonlinear features of the magnetospheric activity and in particular the loading-unloading behavior of substorms

Using an expiratory resistor, arterial pulse pressure variations predict fluid responsiveness during spontaneous breathing: an experimental porcine study.

Science.gov (United States)

Dahl, Michael K; Vistisen, Simon T; Koefoed-Nielsen, Jacob; Larsson, Anders

2009-01-01

Fluid responsiveness prediction is difficult in spontaneously breathing patients. Because the swings in intrathoracic pressure are minor during spontaneous breathing, dynamic parameters like pulse pressure variation (PPV) and systolic pressure variation (SPV) are usually small. We hypothesized that during spontaneous breathing, inspiratory and/or expiratory resistors could induce high arterial pressure variations at hypovolemia and low variations at normovolemia and hypervolemia. Furthermore, we hypothesized that SPV and PPV could predict fluid responsiveness under these conditions. Eight prone, anesthetized and spontaneously breathing pigs (20 to 25 kg) were subjected to a sequence of 30% hypovolemia, normovolemia, and 20% and 40% hypervolemia. At each volemic level, the pigs breathed in a randomized order either through an inspiratory and/or an expiratory threshold resistor (7.5 cmH2O) or only through the tracheal tube without any resistor. Hemodynamic and respiratory variables were measured during the breathing modes. Fluid responsiveness was defined as a 15% increase in stroke volume (DeltaSV) following fluid loading. Stroke volume was significantly lower at hypovolemia compared with normovolemia, but no differences were found between normovolemia and 20% or 40% hypervolemia. Compared with breathing through no resistor, SPV was magnified by all resistors at hypovolemia whereas there were no changes at normovolemia and hypervolemia. PPV was magnified by the inspiratory resistor and the combined inspiratory and expiratory resistor. Regression analysis of SPV or PPV versus DeltaSV showed the highest R2 (0.83 for SPV and 0.52 for PPV) when the expiratory resistor was applied. The corresponding sensitivity and specificity for prediction of fluid responsiveness were 100% and 100%, respectively, for SPV and 100% and 81%, respectively, for PPV. Inspiratory and/or expiratory threshold resistors magnified SPV and PPV in spontaneously breathing pigs during hypovolemia

Accounting for medical variation: the case of prescribing activity in a New Zealand general practice sample.

Science.gov (United States)

Davis, P B; Yee, R L; Millar, J

1994-08-01

Medical practice variation is extensive and well documented, particularly for surgical interventions, and raises important questions for health policy. To date, however, little work has been carried out on interpractitioner variation in prescribing activity in the primary care setting. An analytical model of medical variation is derived from the literature and relevant indicators are identified from a study of New Zealand general practice. The data are based on nearly 9,500 completed patient encounter records drawn from over a hundred practitioners in the Waikato region of the North Island, New Zealand. The data set represents a 1% sample of all weekday general practice office encounters in the Hamilton Health District recorded over a 12-month period. Overall levels of prescribing, and the distribution of drug mentions across diagnostic groupings, are broadly comparable to results drawn from international benchmark data. A multivariate analysis is carried out on seven measures of activity in the areas of prescribing volume, script detail, and therapeutic choice. The analysis indicates that patient, practitioner and practice attributes exert little systematic influence on the prescribing task. The principal influences are diagnosis, followed by practitioner identity. The pattern of findings suggests also that the prescribing task cannot be viewed as an undifferentiated activity. It is more usefully considered as a process of decision-making in which 'core' judgements--such as the decision to prescribe and the choice of drug--are highly predictable and strongly influenced by diagnosis, while 'peripheral' features of the task--such as choosing a combination drug or prescribing generically--are less determinate and more subject to the exercise of clinical discretion.(ABSTRACT TRUNCATED AT 250 WORDS)

Spatial variation and prediction of forest biomass in a heterogeneous landscape

Institute of Scientific and Technical Information of China (English)

S.Lamsal; D.M.Rizzo; R.K.Meentemeyer

2012-01-01

Large areas assessments of forest biomass distribution are a challenge in heterogeneous landscapes,where variations in tree growth and species composition occur over short distances.In this study,we use statistical and geospatial modeling on densely sampled forest biomass data to analyze the relative importance of ecological and physiographic variables as determinants of spatial variation of forest biomass in the environmentally heterogeneous region of the Big Sur,California.We estimated biomass in 280 forest plots (one plot per 2.85 km2) and measured an array of ecological (vegetation community type,distance to edge,amount of surrounding non-forest vegetation,soil properties,fire history) and physiographic drivers (elevation,potential soil moisture and solar radiation,proximity to the coast) of tree growth at each plot location.Our geostatistical analyses revealed that biomass distribution is spatially structured and autocorrelated up to 3.1 km.Regression tree (RT) models showed that both physiographic and ecological factors influenced biomass distribution.Across randomly selected sample densities (sample size 112 to 280),ecological effects of vegetation community type and distance to forest edge,and physiographic effects of elevation,potentialsoil moisture and solar radiation were the most consistent predictors of biomass.Topographic moisture index and potential solar radiation had a positive effect on biomass,indicating the importance of topographicallymediated energy and moisture on plant growth and biomass accumulation.RT model explained 35% of the variation in biomass and spatially autocorrelated variation were retained in regession residuals.Regression kriging model,developed from RT combined with kriging of regression residuals,was used to map biomass across the Big Sur.This study demonstrates how statistical and geospatial modeling can be used to discriminate the relative importance of physiographic and ecologic effects on forest biomass and develop

Analysis of substructural variation in families of enzymatic proteins with applications to protein function prediction

Directory of Open Access Journals (Sweden)

Fofanov Viacheslav Y

2010-05-01

Full Text Available Abstract Background Structural variations caused by a wide range of physico-chemical and biological sources directly influence the function of a protein. For enzymatic proteins, the structure and chemistry of the catalytic binding site residues can be loosely defined as a substructure of the protein. Comparative analysis of drug-receptor substructures across and within species has been used for lead evaluation. Substructure-level similarity between the binding sites of functionally similar proteins has also been used to identify instances of convergent evolution among proteins. In functionally homologous protein families, shared chemistry and geometry at catalytic sites provide a common, local point of comparison among proteins that may differ significantly at the sequence, fold, or domain topology levels. Results This paper describes two key results that can be used separately or in combination for protein function analysis. The Family-wise Analysis of SubStructural Templates (FASST method uses all-against-all substructure comparison to determine Substructural Clusters (SCs. SCs characterize the binding site substructural variation within a protein family. In this paper we focus on examples of automatically determined SCs that can be linked to phylogenetic distance between family members, segregation by conformation, and organization by homology among convergent protein lineages. The Motif Ensemble Statistical Hypothesis (MESH framework constructs a representative motif for each protein cluster among the SCs determined by FASST to build motif ensembles that are shown through a series of function prediction experiments to improve the function prediction power of existing motifs. Conclusions FASST contributes a critical feedback and assessment step to existing binding site substructure identification methods and can be used for the thorough investigation of structure-function relationships. The application of MESH allows for an automated

Climatic controls of the interannual to decadal variability in Saudi Arabian dust activity: Towards the development of a seasonal prediction tool

Science.gov (United States)

Yu, Y.; Notaro, M.; Liu, Z.; Alkolibi, F.; Fadda, E.; Bakhrjy, F.

2013-12-01

Atmospheric dust significantly influences the climate system, as well as human life in Saudi Arabia. Skillful seasonal prediction of dust activity with climatic variables will help prevent some negative social impacts of dust storms. Yet, the climatic regulators on Saudi Arabian dust activity remain largely unaddressed. Remote sensing and station observations show consistent seasonal cycles in Saudi Arabian dust activity, which peaks in spring and summer. The climatic controls on springtime and summertime Saudi Arabian dust activity during 1975-2010 are studied using observational and reanalysis data. Empirical Orthogonal Function (EOF) of the observed Saudi Arabian dust storm frequency shows a dominant homogeneous pattern across the country, which has distinct interannual and decadal variations, as revealed by the power spectrum. Regression and correlation analyses reveal that Saudi Arabian dust activity is largely tied to precipitation on the Arabian Peninsula in spring and northwesterly (Shamal) wind in summer. On the seasonal-interannual time scale, warm El Niño-Southern Oscillation (ENSO) phase (El Niño) in winter-to-spring inhibits spring dust activity by increasing the precipitation over the Rub'al Khali Desert, a major dust source region on the southern Arabian Peninsula; warm ENSO and warm Indian Ocean Basin Mode (IOBM) in winter-to-spring favor less summer dust activity by producing anomalously low sea-level pressure over eastern north Africa and Arabian Peninsula, which leads to the reduced Shamal wind speed. The decadal variation in dust activity is likely associated with the Atlantic Multidecadal Oscillation (AMO), which impacts Sahel rainfall and North African dust, and likely dust transport to Saudi Arabia. The Pacific Decadal Oscillation (PDO) and tropical Indian Ocean SST also have influence on the decadal variation in Saudi Arabian dust activity, by altering precipitation over the Arabian Peninsula and summer Shamal wind speed. Using eastern

Genomic Features That Predict Allelic Imbalance in Humans Suggest Patterns of Constraint on Gene Expression Variation

Science.gov (United States)

Fédrigo, Olivier; Haygood, Ralph; Mukherjee, Sayan; Wray, Gregory A.

2009-01-01

Variation in gene expression is an important contributor to phenotypic diversity within and between species. Although this variation often has a genetic component, identification of the genetic variants driving this relationship remains challenging. In particular, measurements of gene expression usually do not reveal whether the genetic basis for any observed variation lies in cis or in trans to the gene, a distinction that has direct relevance to the physical location of the underlying genetic variant, and which may also impact its evolutionary trajectory. Allelic imbalance measurements identify cis-acting genetic effects by assaying the relative contribution of the two alleles of a cis-regulatory region to gene expression within individuals. Identification of patterns that predict commonly imbalanced genes could therefore serve as a useful tool and also shed light on the evolution of cis-regulatory variation itself. Here, we show that sequence motifs, polymorphism levels, and divergence levels around a gene can be used to predict commonly imbalanced genes in a human data set. Reduction of this feature set to four factors revealed that only one factor significantly differentiated between commonly imbalanced and nonimbalanced genes. We demonstrate that these results are consistent between the original data set and a second published data set in humans obtained using different technical and statistical methods. Finally, we show that variation in the single allelic imbalance-associated factor is partially explained by the density of genes in the region of a target gene (allelic imbalance is less probable for genes in gene-dense regions), and, to a lesser extent, the evenness of expression of the gene across tissues and the magnitude of negative selection on putative regulatory regions of the gene. These results suggest that the genomic distribution of functional cis-regulatory variants in the human genome is nonrandom, perhaps due to local differences in evolutionary

Activity, exposure rate and spectrum prediction with Java programming

International Nuclear Information System (INIS)

Sahin, D.; Uenlue, K.

2009-01-01

In order to envision the radiation exposure during Neutron Activation Analysis (NAA) experiments, a software called Activity Predictor is developed using Java TM programming language. The Activity Predictor calculates activities, exposure rates and gamma spectra of activated samples for NAA experiments performed at Radiation Science and Engineering Center (RSEC), Penn State Breazeale Reactor (PSBR). The calculation procedure for predictions involves both analytical and Monte Carlo methods. The Activity Predictor software is validated with a series of activation experiments. It has been found that Activity Predictor software calculates the activities and exposure rates precisely. The software also predicts gamma spectrum for each measurement. The predicted spectra agreed partially with measured spectra. The error in net photo peak areas varied from 4.8 to 51.29%, which is considered to be due to simplistic modeling, statistical fluctuations and unknown contaminants in the samples. (author)

Features and prospects of juridical predicting of entrepreneurial activity

Directory of Open Access Journals (Sweden)

Natalya V. Rubtsova

2017-03-01

Full Text Available Objective to identify characteristics and prospects of predicting the business activity. Methods historical sociological logical systematicstructural formallegal comparativelegal legal modeling method. Results in article suggests the legal definition of prediction of business activity as a scientific and practical study aimed at the determination of the future state and prospects of development of business activity consisting of the evaluation of legal regulation and analysis of the prospectsof further socioeconomic development which aims to select the optimal solution for the further development of entrepreneurship through legal regulators. The work proves the necessity of achieving a balanced legal regulation of social relations by changing the legislation in the field of business agreements investment and innovation. Scientific novelty the article for the first time formulates the concept characteristics and features of legal prediction of business activity substantiates the impact of predicting on the development of legal regulation of social relations. Practical significance the main provisions and conclusions of the article can be used in research and teaching while considering the issues of predicting both the socioeconomic processes in general and business activity in particular.

A Bayesian method and its variational approximation for prediction of genomic breeding values in multiple traits

Directory of Open Access Journals (Sweden)

Hayashi Takeshi

2013-01-01

Full Text Available Abstract Background Genomic selection is an effective tool for animal and plant breeding, allowing effective individual selection without phenotypic records through the prediction of genomic breeding value (GBV. To date, genomic selection has focused on a single trait. However, actual breeding often targets multiple correlated traits, and, therefore, joint analysis taking into consideration the correlation between traits, which might result in more accurate GBV prediction than analyzing each trait separately, is suitable for multi-trait genomic selection. This would require an extension of the prediction model for single-trait GBV to multi-trait case. As the computational burden of multi-trait analysis is even higher than that of single-trait analysis, an effective computational method for constructing a multi-trait prediction model is also needed. Results We described a Bayesian regression model incorporating variable selection for jointly predicting GBVs of multiple traits and devised both an MCMC iteration and variational approximation for Bayesian estimation of parameters in this multi-trait model. The proposed Bayesian procedures with MCMC iteration and variational approximation were referred to as MCBayes and varBayes, respectively. Using simulated datasets of SNP genotypes and phenotypes for three traits with high and low heritabilities, we compared the accuracy in predicting GBVs between multi-trait and single-trait analyses as well as between MCBayes and varBayes. The results showed that, compared to single-trait analysis, multi-trait analysis enabled much more accurate GBV prediction for low-heritability traits correlated with high-heritability traits, by utilizing the correlation structure between traits, while the prediction accuracy for uncorrelated low-heritability traits was comparable or less with multi-trait analysis in comparison with single-trait analysis depending on the setting for prior probability that a SNP has zero

Compound Structure-Independent Activity Prediction in High-Dimensional Target Space.

Science.gov (United States)

Balfer, Jenny; Hu, Ye; Bajorath, Jürgen

2014-08-01

Profiling of compound libraries against arrays of targets has become an important approach in pharmaceutical research. The prediction of multi-target compound activities also represents an attractive task for machine learning with potential for drug discovery applications. Herein, we have explored activity prediction in high-dimensional target space. Different types of models were derived to predict multi-target activities. The models included naïve Bayesian (NB) and support vector machine (SVM) classifiers based upon compound structure information and NB models derived on the basis of activity profiles, without considering compound structure. Because the latter approach can be applied to incomplete training data and principally depends on the feature independence assumption, SVM modeling was not applicable in this case. Furthermore, iterative hybrid NB models making use of both activity profiles and compound structure information were built. In high-dimensional target space, NB models utilizing activity profile data were found to yield more accurate activity predictions than structure-based NB and SVM models or hybrid models. An in-depth analysis of activity profile-based models revealed the presence of correlation effects across different targets and rationalized prediction accuracy. Taken together, the results indicate that activity profile information can be effectively used to predict the activity of test compounds against novel targets. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Predicting Solar Activity Using Machine-Learning Methods

Science.gov (United States)

Bobra, M.

2017-12-01

Of all the activity observed on the Sun, two of the most energetic events are flares and coronal mass ejections. However, we do not, as of yet, fully understand the physical mechanism that triggers solar eruptions. A machine-learning algorithm, which is favorable in cases where the amount of data is large, is one way to [1] empirically determine the signatures of this mechanism in solar image data and [2] use them to predict solar activity. In this talk, we discuss the application of various machine learning algorithms - specifically, a Support Vector Machine, a sparse linear regression (Lasso), and Convolutional Neural Network - to image data from the photosphere, chromosphere, transition region, and corona taken by instruments aboard the Solar Dynamics Observatory in order to predict solar activity on a variety of time scales. Such an approach may be useful since, at the present time, there are no physical models of flares available for real-time prediction. We discuss our results (Bobra and Couvidat, 2015; Bobra and Ilonidis, 2016; Jonas et al., 2017) as well as other attempts to predict flares using machine-learning (e.g. Ahmed et al., 2013; Nishizuka et al. 2017) and compare these results with the more traditional techniques used by the NOAA Space Weather Prediction Center (Crown, 2012). We also discuss some of the challenges in using machine-learning algorithms for space science applications.

From field to region yield predictions in response to pedo-climatic variations in Eastern Canada

Science.gov (United States)

JÉGO, G.; Pattey, E.; Liu, J.

2013-12-01

The increase in global population coupled with new pressures to produce energy and bioproducts from agricultural land requires an increase in crop productivity. However, the influence of climate and soil variations on crop production and environmental performance is not fully understood and accounted for to define more sustainable and economical management strategies. Regional crop modeling can be a great tool for understanding the impact of climate variations on crop production, for planning grain handling and for assessing the impact of agriculture on the environment, but it is often limited by the availability of input data. The STICS ("Simulateur mulTIdisciplinaire pour les Cultures Standard") crop model, developed by INRA (France) is a functional crop model which has a built-in module to optimize several input parameters by minimizing the difference between calculated and measured output variables, such as Leaf Area Index (LAI). STICS crop model was adapted to the short growing season of the Mixedwood Plains Ecozone using field experiments results, to predict biomass and yield of soybean, spring wheat and corn. To minimize the numbers of inference required for regional applications, 'generic' cultivars rather than specific ones have been calibrated in STICS. After the calibration of several model parameters, the root mean square error (RMSE) of yield and biomass predictions ranged from 10% to 30% for the three crops. A bit more scattering was obtained for LAI (20%prediction to climate variations. Using RS data to re-initialize input parameters that are not readily available (e.g. seeding date) is considered an effective way

ATHENS SEASONAL VARIATION OF GROUND RESISTANCE PREDICTION USING NEURAL NETWORKS

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S. Anbazhagan

2015-10-01

Full Text Available The objective in ground resistance is to attain the most minimal ground safety esteem conceivable that bodes well monetarily and physically. An application of artificial neural networks (ANN to presage and relegation has been growing rapidly due to sundry unique characteristics of ANN models. A decent forecast is able to capture the dubiousness associated with those ground resistance. A portion of the key instabilities are soil composition, moisture content, temperature, ground electrodes and spacing of the electrodes. Propelled by this need, this paper endeavors to develop a generalized regression neural network (GRNN to predict the ground resistance. The GRNN has a single design parameter and expeditious learning and efficacious modeling for nonlinear time series. The precision of the forecast is applied to the Athens seasonal variation of ground resistance that shows the efficacy of the proposed approach.

Model and scenario variations in predicted number of generations of Spodoptera litura Fab. on peanut during future climate change scenario.

Directory of Open Access Journals (Sweden)

Mathukumalli Srinivasa Rao

Full Text Available The present study features the estimation of number of generations of tobacco caterpillar, Spodoptera litura. Fab. on peanut crop at six locations in India using MarkSim, which provides General Circulation Model (GCM of future data on daily maximum (T.max, minimum (T.min air temperatures from six models viz., BCCR-BCM2.0, CNRM-CM3, CSIRO-Mk3.5, ECHams5, INCM-CM3.0 and MIROC3.2 along with an ensemble of the six from three emission scenarios (A2, A1B and B1. This data was used to predict the future pest scenarios following the growing degree days approach in four different climate periods viz., Baseline-1975, Near future (NF -2020, Distant future (DF-2050 and Very Distant future (VDF-2080. It is predicted that more generations would occur during the three future climate periods with significant variation among scenarios and models. Among the seven models, 1-2 additional generations were predicted during DF and VDF due to higher future temperatures in CNRM-CM3, ECHams5 & CSIRO-Mk3.5 models. The temperature projections of these models indicated that the generation time would decrease by 18-22% over baseline. Analysis of variance (ANOVA was used to partition the variation in the predicted number of generations and generation time of S. litura on peanut during crop season. Geographical location explained 34% of the total variation in number of generations, followed by time period (26%, model (1.74% and scenario (0.74%. The remaining 14% of the variation was explained by interactions. Increased number of generations and reduction of generation time across the six peanut growing locations of India suggest that the incidence of S. litura may increase due to projected increase in temperatures in future climate change periods.

Thermospheric mass density variations during geomagnetic storms and a prediction model based on the merging electric field

Directory of Open Access Journals (Sweden)

R. Liu

2010-09-01

Full Text Available With the help of four years (2002–2005 of CHAMP accelerometer data we have investigated the dependence of low and mid latitude thermospheric density on the merging electric field, Em, during major magnetic storms. Altogether 30 intensive storm events (Dstmin<−100 nT are chosen for a statistical study. In order to achieve a good correlation Em is preconditioned. Contrary to general opinion, Em has to be applied without saturation effect in order to obtain good results for magnetic storms of all activity levels. The memory effect of the thermosphere is accounted for by a weighted integration of Em over the past 3 h. In addition, a lag time of the mass density response to solar wind input of 0 to 4.5 h depending on latitude and local time is considered. A linear model using the preconditioned Em as main controlling parameter for predicting mass density changes during magnetic storms is developed: ρ=0.5 Em + ρamb, where ρamb is based on the mean density during the quiet day before the storm. We show that this simple relation predicts all storm-induced mass density variations at CHAMP altitude fairly well especially if orbital averages are considered.

Decadal variation of ocean heat content and tropical cyclone activity ...

Indian Academy of Sciences (India)

The upper ocean heat content up to 700 m depth (OHC700) is an important ... made to examine the inter-decadal variations of tropical cyclone (TC) activity and OHC700 over the ..... In: Climate change 2007: The physical science basis (eds).

Comparison of Regression Techniques to Predict Response of Oilseed Rape Yield to Variation in Climatic Conditions in Denmark

DEFF Research Database (Denmark)

Sharif, Behzad; Makowski, David; Plauborg, Finn

2017-01-01

Statistical regression models represent alternatives to process-based dynamic models for predicting the response of crop yields to variation in climatic conditions. Regression models can be used to quantify the effect of change in temperature and precipitation on yields. However, it is difficult ...

Fundamental Frequency Variation of Neonatal Spontaneous Crying Predicts Language Acquisition in Preterm and Term Infants.

Science.gov (United States)

Shinya, Yuta; Kawai, Masahiko; Niwa, Fusako; Imafuku, Masahiro; Myowa, Masako

2017-01-01

Spontaneous cries of infants exhibit rich melodic features (i.e., time variation of fundamental frequency [ F 0 ]) even during the neonatal period, and the development of these characteristics might provide an essential base for later expressive prosody in language. However, little is known about the melodic features of spontaneous cries in preterm infants, who have a higher risk of later language-related problems. Thus, the present study investigated how preterm birth influenced melodic features of spontaneous crying at term-equivalent age as well as how these melodic features related to language outcomes at 18 months of corrected age in preterm and term infants. At term, moderate-to-late preterm (MLP) infants showed spontaneous cries with significantly higher F 0 variation and melody complexity than term infants, while there were no significant differences between very preterm (VP) and term infants. Furthermore, larger F 0 variation within cry series at term was significantly related to better language and cognitive outcomes, particularly expressive language skills, at 18 months. On the other hand, no other melodic features at term predicted any developmental outcomes at 18 months. The present results suggest that the additional postnatal vocal experience of MLP preterm infants increased F 0 variation and the complexity of spontaneous cries at term. Additionally, the increases in F 0 variation may partly reflect the development of voluntary vocal control, which, in turn, contributes to expressive language in infancy.

Intraspecific variation in social organization by genetic variation, developmental plasticity, social flexibility or entirely extrinsic factors.

Science.gov (United States)

Schradin, Carsten

2013-05-19

Previously, it was widely believed that each species has a specific social organization, but we know now that many species show intraspecific variation in their social organization. Four different processes can lead to intraspecific variation in social organization: (i) genetic variation between individuals owing to local adaptation (between populations) or evolutionarily stable strategies within populations; (ii) developmental plasticity evolved in long-term (more than one generation) unpredictable and short-term (one generation) predictable environments, which is mediated by organizational physiological effects during early ontogeny; (iii) social flexibility evolved in highly unpredictable environments, which is mediated by activational physiological effects in adults; (iv) entirely extrinsic factors such as the death of a dominant breeder. Variation in social behaviour occurs between individuals in the case of genetic variation and developmental plasticity, but within individuals in the case of social flexibility. It is important to study intraspecific variation in social organization to understand the social systems of species because it reveals the mechanisms by which species can adapt to changing environments, offers a useful tool to study the ultimate and proximate causes of sociality, and is an interesting phenomenon by itself that needs scientific explanation.

Predicting seasonal variations in coastal seabird habitats in the English Channel and the Bay of Biscay

Science.gov (United States)

Virgili, A.; Lambert, C.; Pettex, E.; Dorémus, G.; Van Canneyt, O.; Ridoux, V.

2017-07-01

Seabirds, like all animals, have to live in suitable habitats to fulfil their energetic needs for both somatic and reproductive growth and maintenance. Apart from migration trips, all coastal seabirds are linked to the coast, because they need to return daily to land for resting or breeding. Their use of marine habitats strongly depends on their biology, but also on environmental conditions, and can be described using habitat models. This study aimed to: (1) identify the processes that mostly influence seabird distributions along the coasts of the English Channel and the Bay of Biscay; (2) determine seasonal variations of these processes, (3) provide prediction maps that describe the species distributions. We collected data of coastal seabird sightings from aerial surveys carried out in the English Channel and the eastern North Atlantic in the winter 2011-2012 and summer 2012. We classified seabirds into morphological groups and described their habitats using physiographic and oceanographic variables in Generalised Additive Models (GAMs). Finally, we produced maps of predicted distributions by season for each group. The distributions of coastal seabirds were essentially determined by the distance to the nearest coast, with a weaker influence of oceanographic variables. The nature of the substrate, sand or rock, combined with the timing of reproduction, also contributed to determine seasonal at-sea distributions for some species. The highest densities were predicted near the coast, particularly in bays and estuaries for strictly coastal species with possible variations depending on the season. From this study, we were able to predict the seasonal distribution of the studied species according to varying environmental parameters that changed over time, allowing us to understand better their behaviour and ecology.

Variations in roughness predictions (flume experiments)

NARCIS (Netherlands)

Noordam, Daniëlle; Blom, Astrid; van der Klis, H.; Hulscher, Suzanne J.M.H.; Makaske, A.; Wolfert, H.P.; van Os, A.G.

2005-01-01

Data of flume experiments with bed forms are used to analyze and compare different roughness predictors. In this study, the hydraulic roughness consists of grain roughness and form roughness. We predict the grain roughness by means of the size of the sediment. The form roughness is predicted by

Time variations of geomagnetic activity indices Kp and Ap: an update

Directory of Open Access Journals (Sweden)

G. K. Rangarajan

1997-10-01

Full Text Available Kp and Ap indices covering the period 1932 to 1995 are analysed in a fashion similar to that attempted by Bartels for the 1932–1961 epoch to examine the time variations in their characteristics. Modern analysis techniques on the extended data base are used for further insight. The relative frequencies of occurrence of Kp with different magnitudes and the seasonal and solar cycle dependences are seen to be remarkably consistent despite the addition of 35 years of observations. Many of the earlier features seen in the indices and special intervals are shown to be replicated in the present analysis. Time variations in the occurrence of prolonged periods of geomagnetic calm or of enhanced activity are presented and their relation to solar activity highlighted. It is shown that in the declining phase the occurrence frequencies of Kp = 4–5 (consecutively over 4 intervals can be used as a precursor for the maximum sunspot number to be expected in the next cycle. The semi-annual variation in geomagnetic activity is re-examined utilising not only the Ap index but also the occurrence frequencies of Kp index with different magnitudes. Lack of dependence of the amplitude of semi-annual variation on sunspot number is emphasised. Singular spectrum analysis of the mean monthly Ap index shows some distinct periodic components. The temporal evolution of ~44 month, ~21 month and ~16 month oscillations are examined and it is postulated that while QBO and the 16 month oscillations could be attributed to solar wind and IMF oscillations with analogous periodicity, the 44 month variation is associated with a similar periodicity in recurrent high speed stream caused by sector boundary passage. It is reconfirmed that there could have been only one epoch around 1940 when solar wind speed could have exhibited a 1.3-year periodicity comparable to that seen during the post-1986 period.

Time variations of geomagnetic activity indices Kp and Ap: an update

Directory of Open Access Journals (Sweden)

G. K. Rangarajan

Full Text Available Kp and Ap indices covering the period 1932 to 1995 are analysed in a fashion similar to that attempted by Bartels for the 1932–1961 epoch to examine the time variations in their characteristics. Modern analysis techniques on the extended data base are used for further insight. The relative frequencies of occurrence of Kp with different magnitudes and the seasonal and solar cycle dependences are seen to be remarkably consistent despite the addition of 35 years of observations. Many of the earlier features seen in the indices and special intervals are shown to be replicated in the present analysis. Time variations in the occurrence of prolonged periods of geomagnetic calm or of enhanced activity are presented and their relation to solar activity highlighted. It is shown that in the declining phase the occurrence frequencies of Kp = 4–5 (consecutively over 4 intervals can be used as a precursor for the maximum sunspot number to be expected in the next cycle. The semi-annual variation in geomagnetic activity is re-examined utilising not only the Ap index but also the occurrence frequencies of Kp index with different magnitudes. Lack of dependence of the amplitude of semi-annual variation on sunspot number is emphasised. Singular spectrum analysis of the mean monthly Ap index shows some distinct periodic components. The temporal evolution of ~44 month, ~21 month and ~16 month oscillations are examined and it is postulated that while QBO and the 16 month oscillations could be attributed to solar wind and IMF oscillations with analogous periodicity, the 44 month variation is associated with a similar periodicity in recurrent high speed stream caused by sector boundary passage. It is reconfirmed that there could have been only one epoch around 1940 when solar wind speed could have exhibited a 1.3-year periodicity comparable to that seen during the post-1986 period.

Remaining useful life prediction based on variation coefficient consistency test of a Wiener process

Directory of Open Access Journals (Sweden)

Juan LI

2018-01-01

Full Text Available High-cost equipment is often reused after maintenance, and whether the information before the maintenance can be used for the Remaining Useful Life (RUL prediction after the maintenance is directly determined by the consistency of the degradation pattern before and after the maintenance. Aiming at this problem, an RUL prediction method based on the consistency test of a Wiener process is proposed. Firstly, the parameters of the Wiener process estimated by Maximum Likelihood Estimation (MLE are proved to be biased, and a modified unbiased estimation method is proposed and verified by derivation and simulations. Then, the h statistic is constructed according to the reciprocal of the variation coefficient of the Wiener process, and the sampling distribution is derived. Meanwhile, a universal method for the consistency test is proposed based on the sampling distribution theorem, which is verified by simulation data and classical crack degradation data. Finally, based on the consistency test of the degradation model, a weighted fusion RUL prediction method is presented for the fuel pump of an airplane, and the validity of the presented method is verified by accurate computation results of real data, which provides a theoretical and practical guidance for engineers to predict the RUL of equipment after maintenance.

Activity-induced radial velocity variation of M dwarf stars

DEFF Research Database (Denmark)

Andersen, Jan Marie; Korhonen, Heidi Helena

2012-01-01

that can drown out a planetary signature. Cool, low-mass M dwarf stars can be highly active, which can make detection of potentially habitable planets around these stars difficult. We investigate radial velocity variations caused by different activity (spot) patterns on M dwarf stars in order to determine...... the limits of detectability for small planets orbiting active M dwarfs. We report on our progress toward the aim of answering the following questions: What types of spot patterns are realistic for M dwarf stars? What effect will spots have on M dwarf RV measurements? Can jitter from M dwarf spots mimic...... planetary signals? What is the ideal observing wavelength to reduce M dwarf jitter?...

Recent and Past Musical Activity Predicts Cognitive Aging Variability: Direct Comparison with Leisure Activities

Directory of Open Access Journals (Sweden)

Brenda eHanna-Pladdy

2012-07-01

Full Text Available Studies evaluating the impact of modifiable lifestyle factors on cognition offer potential insights into sources of cognitive aging variability. Recently, we reported an association between extent of musical instrumental practice throughout the life span (greater than 10 years on preserved cognitive functioning in advanced age . These findings raise the question of whether there are training-induced brain changes in musicians that can transfer to nonmusical cognitive abilities to allow for compensation of age-related cognitive declines. However, because of the relationship between engagement in lifestyle activities and preserved cognition, it remains unclear whether these findings are specifically driven by musical training or the types of individuals likely to engage in greater activities in general. The current study examined the type of leisure activity (musical versus other as well as the timing of engagement (age of acquisition, past versus recent in predictive models of successful cognitive aging. Seventy age and education matched older musicians (> 10 years and nonmusicians (ages 59-80 were evaluated on neuropsychological tests and life-style activities (AAP. Partition analyses were conducted on significant cognitive measures to explain performance variance in musicians. Musicians scored higher on tests of phonemic fluency, verbal immediate recall, judgment of line orientation (JLO, and Letter Number Sequencing (LNS, but not the AAP. The first partition analysis revealed education best predicted JLO in musicians, followed by recent musical engagement which offset low education. In the second partition analysis, early age of musical acquisition (< 9 years predicted enhanced LNS in musicians, while analyses for AAP, verbal recall and fluency were not predictive. Recent and past musical activity, but not leisure activity, predicted variability across verbal and visuospatial domains in aging. Early musical acquisition predicted auditory

Variation and Grey GM(1, 1) Prediction of Melting Peak Temperature of Polypropylene During Ultraviolet Radiation Aging

Science.gov (United States)

Chen, K.; Y Zhang, T.; Zhang, F.; Zhang, Z. R.

2017-12-01

Grey system theory regards uncertain system in which information is known partly and unknown partly as research object, extracts useful information from part known, and thereby revealing the potential variation rule of the system. In order to research the applicability of data-driven modelling method in melting peak temperature (T m) fitting and prediction of polypropylene (PP) during ultraviolet radiation aging, the T m of homo-polypropylene after different ultraviolet radiation exposure time investigated by differential scanning calorimeter was fitted and predicted by grey GM(1, 1) model based on grey system theory. The results show that the T m of PP declines with the prolong of aging time, and fitting and prediction equation obtained by grey GM(1, 1) model is T m = 166.567472exp(-0.00012t). Fitting effect of the above equation is excellent and the maximum relative error between prediction value and actual value of T m is 0.32%. Grey system theory needs less original data, has high prediction accuracy, and can be used to predict aging behaviour of PP.

Predicting human activities in sequences of actions in RGB-D videos

Science.gov (United States)

Jardim, David; Nunes, Luís.; Dias, Miguel

2017-03-01

In our daily activities we perform prediction or anticipation when interacting with other humans or with objects. Prediction of human activity made by computers has several potential applications: surveillance systems, human computer interfaces, sports video analysis, human-robot-collaboration, games and health-care. We propose a system capable of recognizing and predicting human actions using supervised classifiers trained with automatically labeled data evaluated in our human activity RGB-D dataset (recorded with a Kinect sensor) and using only the position of the main skeleton joints to extract features. Using conditional random fields (CRFs) to model the sequential nature of actions in a sequence has been used before, but where other approaches try to predict an outcome or anticipate ahead in time (seconds), we try to predict what will be the next action of a subject. Our results show an activity prediction accuracy of 89.9% using an automatically labeled dataset.

The effect of gender on eye colour variation in European populations and an evaluation of the IrisPlex prediction model

DEFF Research Database (Denmark)

Pietroni, Carlotta; Andersen, Jeppe D.; Johansen, Peter

2014-01-01

In two recent studies of Spanish individuals [1,2], gender was suggested as a factor that contributes to human eye colour variation. However, gender did not improve the predictive accuracy on blue, intermediate and brown eye colours when gender was included in the IrisPlex model [3]. In this stud...... and their corresponding predictive values using the IrisPlex prediction model [4]. The results suggested that maximum three (rs12913832, rs1800407, rs16891982) of the six IrisPlex SNPs are useful in practical forensic genetic casework.......In two recent studies of Spanish individuals [1,2], gender was suggested as a factor that contributes to human eye colour variation. However, gender did not improve the predictive accuracy on blue, intermediate and brown eye colours when gender was included in the IrisPlex model [3]. In this study......12203592). A quantitative eye colour score (Pixel Index of the Eye: PIE-score) was calculated based on digital eye images using the custom made DIAT software. The results were compared with those of Danish and Swedish population samples. As expected, we found HERC2 rs12913832 as the main predictor of human...

Deterministic and probabilistic interval prediction for short-term wind power generation based on variational mode decomposition and machine learning methods

International Nuclear Information System (INIS)

Zhang, Yachao; Liu, Kaipei; Qin, Liang; An, Xueli

2016-01-01

Highlights: • Variational mode decomposition is adopted to process original wind power series. • A novel combined model based on machine learning methods is established. • An improved differential evolution algorithm is proposed for weight adjustment. • Probabilistic interval prediction is performed by quantile regression averaging. - Abstract: Due to the increasingly significant energy crisis nowadays, the exploitation and utilization of new clean energy gains more and more attention. As an important category of renewable energy, wind power generation has become the most rapidly growing renewable energy in China. However, the intermittency and volatility of wind power has restricted the large-scale integration of wind turbines into power systems. High-precision wind power forecasting is an effective measure to alleviate the negative influence of wind power generation on the power systems. In this paper, a novel combined model is proposed to improve the prediction performance for the short-term wind power forecasting. Variational mode decomposition is firstly adopted to handle the instability of the raw wind power series, and the subseries can be reconstructed by measuring sample entropy of the decomposed modes. Then the base models can be established for each subseries respectively. On this basis, the combined model is developed based on the optimal virtual prediction scheme, the weight matrix of which is dynamically adjusted by a self-adaptive multi-strategy differential evolution algorithm. Besides, a probabilistic interval prediction model based on quantile regression averaging and variational mode decomposition-based hybrid models is presented to quantify the potential risks of the wind power series. The simulation results indicate that: (1) the normalized mean absolute errors of the proposed combined model from one-step to three-step forecasting are 4.34%, 6.49% and 7.76%, respectively, which are much lower than those of the base models and the hybrid

Causes and consequences of chromatin variation between inbred mice.

Directory of Open Access Journals (Sweden)

Mona Hosseini

2013-06-01

Full Text Available Variation at regulatory elements, identified through hypersensitivity to digestion by DNase I, is believed to contribute to variation in complex traits, but the extent and consequences of this variation are poorly characterized. Analysis of terminally differentiated erythroblasts in eight inbred strains of mice identified reproducible variation at approximately 6% of DNase I hypersensitive sites (DHS. Only 30% of such variable DHS contain a sequence variant predictive of site variation. Nevertheless, sequence variants within variable DHS are more likely to be associated with complex traits than those in non-variant DHS, and variants associated with complex traits preferentially occur in variable DHS. Changes at a small proportion (less than 10% of variable DHS are associated with changes in nearby transcriptional activity. Our results show that whilst DNA sequence variation is not the major determinant of variation in open chromatin, where such variants exist they are likely to be causal for complex traits.

On the relation of Hsub(α) plage brightness variations in solar active regions

International Nuclear Information System (INIS)

Ogir', M.B.

1980-01-01

The variations of hydrogen plage brightnesses in seven spot groups belonging to five active regions are discussed. The observations were made on the Crimean observatory coronograph in 1974 and 1977. The correlation in brightness variations of plages situated in the regions of growing magnetic field was obtained. This was observed in the plages on one spot group as well as in the different groups removing on about 27x10 4 km. In developed groups correlations are mainly seen within a spot group and they are expressed better during flares. The correlations of brightnesses are changing during the active region evolution. Three days observations showed good brightness correlations of all plages in the growing magnetic field region and their decrease that can be explained by the field weakening during natural active region evolution or by the strong flare influence. The existence of the simultaneous variations of brightness in the regions with the growing magnetic field speaks in favour of the simultaneous carring-out of magnetic field or its disturbances into the chromosphere [ru

Human medial frontal cortex activity predicts learning from errors.

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Hester, Robert; Barre, Natalie; Murphy, Kevin; Silk, Tim J; Mattingley, Jason B

2008-08-01

Learning from errors is a critical feature of human cognition. It underlies our ability to adapt to changing environmental demands and to tune behavior for optimal performance. The posterior medial frontal cortex (pMFC) has been implicated in the evaluation of errors to control behavior, although it has not previously been shown that activity in this region predicts learning from errors. Using functional magnetic resonance imaging, we examined activity in the pMFC during an associative learning task in which participants had to recall the spatial locations of 2-digit targets and were provided with immediate feedback regarding accuracy. Activity within the pMFC was significantly greater for errors that were subsequently corrected than for errors that were repeated. Moreover, pMFC activity during recall errors predicted future responses (correct vs. incorrect), despite a sizeable interval (on average 70 s) between an error and the next presentation of the same recall probe. Activity within the hippocampus also predicted future performance and correlated with error-feedback-related pMFC activity. A relationship between performance expectations and pMFC activity, in the absence of differing reinforcement value for errors, is consistent with the idea that error-related pMFC activity reflects the extent to which an outcome is "worse than expected."

Prediction of Positions of Active Compounds Makes It Possible To Increase Activity in Fragment-Based Drug Development

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Yoshifumi Fukunishi

2011-05-01

Full Text Available We have developed a computational method that predicts the positions of active compounds, making it possible to increase activity as a fragment evolution strategy. We refer to the positions of these compounds as the active position. When an active fragment compound is found, the following lead generation process is performed, primarily to increase activity. In the current method, to predict the location of the active position, hydrogen atoms are replaced by small side chains, generating virtual compounds. These virtual compounds are docked to a target protein, and the docking scores (affinities are examined. The hydrogen atom that gives the virtual compound with good affinity should correspond to the active position and it should be replaced to generate a lead compound. This method was found to work well, with the prediction of the active position being 2 times more efficient than random synthesis. In the current study, 15 examples of lead generation were examined. The probability of finding active positions among all hydrogen atoms was 26%, and the current method accurately predicted 60% of the active positions.

Prediction of temperature variation in a rotating spacecraft in space environment

International Nuclear Information System (INIS)

Gadalla, Mohamed A.

2005-01-01

This paper presents a closed-form prediction model for the temperature distribution of a thick-walled cylindrical space vehicle subjected to solar heating in deep space. The model is based on the coupling between dynamics and solar radiation. Since solar radiation is, in general, incident from a fixed direction, one side of the space vehicle will be shone bright, and the other side dark. Thus the space astronauts, instruments, and cryogenic-fuel tanks are gaining heat on the bright side and losing heat from the dark side. This radiative heat gain and loss become equally significant as the conductive heat transfer through the interior of the space vehicle. Thermal analysis is carried out to predict the effect of the spinning speed and angular position on the temperature variation and gradients attained by speed vehicles outside the Earth's atmosphere. This analysis is based on the non-linearity of the radiative heat dissipation, the significant conductive heat transfer role, and combined boundary conditions that involve the temperature and angular position of the vehicle. An exact analytical solution is obtained inspite of the non-linearity and non-homogeneity in the boundary conditions. The results indicate that the temperature distribution on the outer surface of the space vehicle is nearly independent of the angular position; at sub-cylindrical surface, this independence is achieved at low angular velocity

Ventromedial Prefrontal Cortex Activation Is Associated with Memory Formation for Predictable Rewards

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Bialleck, Katharina A.; Schaal, Hans-Peter; Kranz, Thorsten A.; Fell, Juergen; Elger, Christian E.; Axmacher, Nikolai

2011-01-01

During reinforcement learning, dopamine release shifts from the moment of reward consumption to the time point when the reward can be predicted. Previous studies provide consistent evidence that reward-predicting cues enhance long-term memory (LTM) formation of these items via dopaminergic projections to the ventral striatum. However, it is less clear whether memory for items that do not precede a reward but are directly associated with reward consumption is also facilitated. Here, we investigated this question in an fMRI paradigm in which LTM for reward-predicting and neutral cues was compared to LTM for items presented during consumption of reliably predictable as compared to less predictable rewards. We observed activation of the ventral striatum and enhanced memory formation during reward anticipation. During processing of less predictable as compared to reliably predictable rewards, the ventral striatum was activated as well, but items associated with less predictable outcomes were remembered worse than items associated with reliably predictable outcomes. Processing of reliably predictable rewards activated the ventromedial prefrontal cortex (vmPFC), and vmPFC BOLD responses were associated with successful memory formation of these items. Taken together, these findings show that consumption of reliably predictable rewards facilitates LTM formation and is associated with activation of the vmPFC. PMID:21326612

Prediction of ppm level electrical failure by using physical variation analysis

Science.gov (United States)

Hou, Hsin-Ming; Kung, Ji-Fu; Hsu, Y.-B.; Yamazaki, Y.; Maruyama, Kotaro; Toyoshima, Yuya; Chen, Chu-en

2016-03-01

their spatial correlation distance. For local variations (LV) there is no correlation, whereas for global variations (GV) the correlation distance is very large [7]-[9]. This is the first time to certificate the validation of spatial distribution from the affordable bias contour big data fundamental infrastructures. And then apply statistical techniques to dig out the variation sources. The GV come from systematic issue, which could be compensated by adaptive LT condition or OPC correction. But LV comes from random issue, which being considered as intrinsic problem such as structure, material, tool capability… etc. In this paper studying, we can find out the advanced technology node SRAM contact CD local variation (LV) dominates in total variation, about 70%. It often plays significant in-line real time catching WP-DPMO role of the product yield loss, especially for wafer edge is the worst loss within wafer distribution and causes serious reliability concern. The major root cause of variations comes from the PR material induced burr defect (LV), the second one comes from GV enhanced wafer edge short opportunity, which being attributed to three factors, first one factor is wafer edge CD deliberated enlargement for yield improvement as shown in Fig. 10. Second factor is overlaps/AA shifts due to tool capability dealing with incoming wafer's war page issue and optical periphery layout dependent working pitch issue as shown in Fig. 9 (1)., the last factor comes from wafer edge burr enhanced by wafer edge larger Photo Resistance (PR) spin centrifugal force. After implementing KPIs such as GV related AA/CD indexes as shown in Fig. 9 (1) and 10, respectively, and LV related burr index as shown in Fig. 11., we can construct the parts per million (PPM) level short probability model via multi-variables regression, canonical correlation analysis and logistic transformation. The model provides prediction of PPM level electrical failure by using in-line real time physical

Predicting forest insect flight activity: A Bayesian network approach.

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Stephen M Pawson

Full Text Available Daily flight activity patterns of forest insects are influenced by temporal and meteorological conditions. Temperature and time of day are frequently cited as key drivers of activity; however, complex interactions between multiple contributing factors have also been proposed. Here, we report individual Bayesian network models to assess the probability of flight activity of three exotic insects, Hylurgus ligniperda, Hylastes ater, and Arhopalus ferus in a managed plantation forest context. Models were built from 7,144 individual hours of insect sampling, temperature, wind speed, relative humidity, photon flux density, and temporal data. Discretized meteorological and temporal variables were used to build naïve Bayes tree augmented networks. Calibration results suggested that the H. ater and A. ferus Bayesian network models had the best fit for low Type I and overall errors, and H. ligniperda had the best fit for low Type II errors. Maximum hourly temperature and time since sunrise had the largest influence on H. ligniperda flight activity predictions, whereas time of day and year had the greatest influence on H. ater and A. ferus activity. Type II model errors for the prediction of no flight activity is improved by increasing the model's predictive threshold. Improvements in model performance can be made by further sampling, increasing the sensitivity of the flight intercept traps, and replicating sampling in other regions. Predicting insect flight informs an assessment of the potential phytosanitary risks of wood exports. Quantifying this risk allows mitigation treatments to be targeted to prevent the spread of invasive species via international trade pathways.

Origins of the semiannual variation of geomagnetic activity in 1954 and 1996

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L. Svalgaard

Full Text Available We investigate the cause of the unusually strong semiannual variation of geomagnetic activity observed in the solar minimum years of 1954 and 1996. For 1996 we separate the contributions of the three classical modulation mechanisms (axial, equinoctial, and Russell-McPherron to the six-month wave in the aam index and find that all three contribute about equally. This is in contrast to the longer run of geomagnetic activity (1868-1998 over which the equinoctial effect accounts for ∼70% of the semiannual variation. For both 1954 and 1996, we show that the Russell-McPherron effect was enhanced by the Rosenberg-Coleman effect (an axial polarity effect which increased the amount of the negative (toward Sun [positive (away from Sun] polarity field observed during the first [second] half of the year; such fields yield a southward component in GSM coordinates. Because this favourable condition occurs only for alternate solar cycles, the marked semiannual variation in 1954 and 1996 is a manifestation of the 22-year cycle of geomagnetic activity. The 11-year evolution of the heliospheric current sheet (HCS also contributes to the strong six-month wave during these years. At solar minimum, the streamer belt at the base of the HCS is located near the solar equator, permitting easier access to high speed streams from polar coronal holes when the Earth is at its highest heliographic latitudes in March and September. Such an axial variation in solar wind speed was observed for 1996 and is inferred for 1954. Key words. Magnetosphere (solar wind – magnetosphere interactions; storms and substorms

Origins of the semiannual variation of geomagnetic activity in 1954 and 1996

Directory of Open Access Journals (Sweden)

E. W. Cliver

2004-01-01

Full Text Available We investigate the cause of the unusually strong semiannual variation of geomagnetic activity observed in the solar minimum years of 1954 and 1996. For 1996 we separate the contributions of the three classical modulation mechanisms (axial, equinoctial, and Russell-McPherron to the six-month wave in the aam index and find that all three contribute about equally. This is in contrast to the longer run of geomagnetic activity (1868-1998 over which the equinoctial effect accounts for ∼70% of the semiannual variation. For both 1954 and 1996, we show that the Russell-McPherron effect was enhanced by the Rosenberg-Coleman effect (an axial polarity effect which increased the amount of the negative (toward Sun [positive (away from Sun] polarity field observed during the first [second] half of the year; such fields yield a southward component in GSM coordinates. Because this favourable condition occurs only for alternate solar cycles, the marked semiannual variation in 1954 and 1996 is a manifestation of the 22-year cycle of geomagnetic activity. The 11-year evolution of the heliospheric current sheet (HCS also contributes to the strong six-month wave during these years. At solar minimum, the streamer belt at the base of the HCS is located near the solar equator, permitting easier access to high speed streams from polar coronal holes when the Earth is at its highest heliographic latitudes in March and September. Such an axial variation in solar wind speed was observed for 1996 and is inferred for 1954. Key words. Magnetosphere (solar wind – magnetosphere interactions; storms and substorms

Chernobyl derived activity in sheep: variation within a single flock and with time

International Nuclear Information System (INIS)

Walters, B.

1988-01-01

The continuous monitoring of the caesium contents of sheep grazing a high fell in Cumbria, UK, is described. The technique of in-vivo monitoring, using portable NaI crystal detectors, is shown to be robust and capable of producing accurate quantitative data. Results are presented from the monitoring of 100 sheep at fortnightly intervals over a period of 13 weeks. The peak average activity (1300 Bq kg -1 ) was reached five weeks after introduction of the sheep to grazing land with up to 2000 Bq kg -1 in herbage. Activity had fallen, on average, to 68% of the peak value after eight weeks. The variation in activity between individual sheep is large and usually symmetrically distributed. The temporal trend of activity in the whole flock is a combination of the many disparate individual trends. The technique has allowed the variation between animals and individual time trends to be followed. (author)

Predicting environmental restoration activities through static simulation

International Nuclear Information System (INIS)

Ross, T.L.; King, D.A.; Wilkins, M.L.; Forward, M.F.

1994-12-01

This paper discusses a static simulation model that predicts several performance measures of environmental restoration activities over different remedial strategies. Basic model operation consists of manipulating and processing waste streams via selecting and applying remedial technologies according to the strategy. Performance measure prediction is possible for contaminated soil, solid waste, surface water, groundwater, storage tank, and facility sites. Simulations are performed for the U.S. Department of Energy in support of its Programmatic Environmental Impact Statement

On the Nature of Extraversion: Variation in Conditioned Contextual Activation of Dopamine-Facilitated Affective, Cognitive, and Motor Processes

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Richard allen Depue

2013-06-01

Full Text Available Research supports an association between extraversion and dopamine (DA functioning. DA facilitates incentive motivation and the conditioning and incentive encoding of contexts that predict reward. Therefore, we assessed whether extraversion is related to the efficacy of acquiring conditioned contextual facilitation of three processes that are dependent on DA: motor velocity, positive affect, and visuospatial working memory. We exposed high and low extraverts to three days of association of drug reward (methylphenidate, MP with a particular laboratory context (Paired group, a test day of conditioning, and three days of extinction in the same laboratory. A Placebo group and an Unpaired group (that had MP in a different laboratory context served as controls. Conditioned contextual facilitation was assessed by (i presenting video clips that varied in their pairing with drug and laboratory context and in inherent incentive value, and (ii measuring increases from day 1 to Test day on the three processes above. Results showed acquisition of conditioned contextual facilitation across all measures to video clips that had been paired with drug and laboratory context in the Paired high extraverts, but no conditioning in the Paired low extraverts (nor in either of the control groups. Increases in the Paired high extraverts were correlated across the three measures. Also, conditioned facilitation was evident on the first day of extinction in Paired high extraverts, despite the absence of the unconditioned effects of MP. By the last day of extinction, responding returned to day 1 levels. The findings suggest that extraversion is associated with variation in the acquisition of contexts that predict reward. Over time, this variation may lead to differences in the breadth of networks of conditioned contexts. Thus, individual differences in extraversion may be maintained by activation of differentially encoded central representations of incentive contexts that

Seasonal variation of wave activities near the mesopause region observed at King Sejong Station (62.22°S, 58.78°W), Antarctica

Science.gov (United States)

Lee, Changsup; Kim, Yong Ha; Kim, Jeong-Han; Jee, Geonhwa; Won, Young-In; Wu, Dong L.

2013-12-01

We analyzed the neutral wind data at altitudes of 80-100 km obtained from a VHF meteor radar at King Sejong Station (KSS, 62.22°S, 58.78°W), a key location to study wave activities above the stratospheric vortex near the Antarctic Peninsula. The seasonal behavior of the semidiurnal tides is generally consistent with the prediction of Global Scale Wave Model (GSWM02) except in the altitude region above ~96 km. Gravity wave (GW) activities inferred from the neutral wind variances show a seasonal variation very similar to the semidiurnal tide amplitudes, suggesting a strong interaction between gravity waves and the tide. Despite the consistent seasonal variations of the GW wind variances observed at the adjacent Rothera station, the magnitudes of the wind variance obtained at KSS are much larger than those at Rothera, especially during May-September. The enhanced GW activity at KSS is also observed by Aura Microwave Limb Sounder (MLS) from space in its temperature variance. The observed large wind variances at KSS imply that the Antarctic vortex in the stratosphere may act as an effective filter and source for the GWs in the upper atmosphere.

Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction

Science.gov (United States)

Li, Zhijin; Chao, Yi; Li, P. Peggy

2012-01-01

A multi-scale three-dimensional variational data assimilation system (MS-3DVAR) has been formulated and the associated software system has been developed for improving high-resolution coastal ocean prediction. This system helps improve coastal ocean prediction skill, and has been used in support of operational coastal ocean forecasting systems and field experiments. The system has been developed to improve the capability of data assimilation for assimilating, simultaneously and effectively, sparse vertical profiles and high-resolution remote sensing surface measurements into coastal ocean models, as well as constraining model biases. In this system, the cost function is decomposed into two separate units for the large- and small-scale components, respectively. As such, data assimilation is implemented sequentially from large to small scales, the background error covariance is constructed to be scale-dependent, and a scale-dependent dynamic balance is incorporated. This scheme then allows effective constraining large scales and model bias through assimilating sparse vertical profiles, and small scales through assimilating high-resolution surface measurements. This MS-3DVAR enhances the capability of the traditional 3DVAR for assimilating highly heterogeneously distributed observations, such as along-track satellite altimetry data, and particularly maximizing the extraction of information from limited numbers of vertical profile observations.

Autonomous Motivation Predicts 7-Day Physical Activity in Hong Kong Students.

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Ha, Amy S; Ng, Johan Y Y

2015-07-01

Autonomous motivation predicts positive health behaviors such as physical activity. However, few studies have examined the relation between motivational regulations and objectively measured physical activity and sedentary behaviors. Thus, we investigated whether different motivational regulations (autonomous motivation, controlled motivation, and amotivation) predicted 7-day physical activity, sedentary behaviors, and health-related quality of life (HRQoL) of students. A total of 115 students (mean age = 11.6 years, 55.7% female) self-reported their motivational regulations and health-related quality of life. Physical activity and sedentary behaviors were measured using accelerometers for seven days. Using multilevel modeling, we found that autonomous motivation predicted higher levels of moderate-to-vigorous physical activity, less sedentary behaviors, and better HRQoL. Controlled motivation and amotivation each only negatively predicted one facet of HRQoL. Results suggested that autonomous motivation could be an important predictor of physical activity behaviors in Hong Kong students. Promotion of this form of motivational regulation may also increase HRQoL. © 2015 The International Association of Applied Psychology.

Application of Avco data analysis and prediction techniques (ADAPT) to prediction of sunspot activity

Science.gov (United States)

Hunter, H. E.; Amato, R. A.

1972-01-01

The results are presented of the application of Avco Data Analysis and Prediction Techniques (ADAPT) to derivation of new algorithms for the prediction of future sunspot activity. The ADAPT derived algorithms show a factor of 2 to 3 reduction in the expected 2-sigma errors in the estimates of the 81-day running average of the Zurich sunspot numbers. The report presents: (1) the best estimates for sunspot cycles 20 and 21, (2) a comparison of the ADAPT performance with conventional techniques, and (3) specific approaches to further reduction in the errors of estimated sunspot activity and to recovery of earlier sunspot historical data. The ADAPT programs are used both to derive regression algorithm for prediction of the entire 11-year sunspot cycle from the preceding two cycles and to derive extrapolation algorithms for extrapolating a given sunspot cycle based on any available portion of the cycle.

Metabolic Model-Based Integration of Microbiome Taxonomic and Metabolomic Profiles Elucidates Mechanistic Links between Ecological and Metabolic Variation

Energy Technology Data Exchange (ETDEWEB)

Noecker, Cecilia; Eng, Alexander; Srinivasan, Sujatha; Theriot, Casey M.; Young, Vincent B.; Jansson, Janet K.; Fredricks, David N.; Borenstein, Elhanan; Sanchez, Laura M.

2015-12-22

Multiple molecular assays now enable high-throughput profiling of the ecology, metabolic capacity, and activity of the human microbiome. However, to date, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms linking these various facets of the microbiome. Here, we introduce a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, we integrate available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community. Our framework then compares variation in predicted metabolic potential with variation in measured metabolites’ abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts. Focusing on two independent vaginal microbiome data sets, each pairing 16S community profiling with large-scale metabolomics, we demonstrate that our framework successfully recapitulates observed variation in 37% of metabolites. Well-predicted metabolite variation tends to result from disease-associated metabolism. We further identify several disease-enriched species that contribute significantly to these predictions. Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism. Applying this framework to gut microbiome data sets reveals similar trends, including prediction of bile acid metabolite shifts. This framework is an important first step toward a system-level multi-omic integration and an improved mechanistic understanding of the microbiome activity and dynamics in

Intrinsic resting-state activity predicts working memory brain activation and behavioral performance.

Science.gov (United States)

Zou, Qihong; Ross, Thomas J; Gu, Hong; Geng, Xiujuan; Zuo, Xi-Nian; Hong, L Elliot; Gao, Jia-Hong; Stein, Elliot A; Zang, Yu-Feng; Yang, Yihong

2013-12-01

Although resting-state brain activity has been demonstrated to correspond with task-evoked brain activation, the relationship between intrinsic and evoked brain activity has not been fully characterized. For example, it is unclear whether intrinsic activity can also predict task-evoked deactivation and whether the rest-task relationship is dependent on task load. In this study, we addressed these issues on 40 healthy control subjects using resting-state and task-driven [N-back working memory (WM) task] functional magnetic resonance imaging data collected in the same session. Using amplitude of low-frequency fluctuation (ALFF) as an index of intrinsic resting-state activity, we found that ALFF in the middle frontal gyrus and inferior/superior parietal lobules was positively correlated with WM task-evoked activation, while ALFF in the medial prefrontal cortex, posterior cingulate cortex, superior frontal gyrus, superior temporal gyrus, and fusiform gyrus was negatively correlated with WM task-evoked deactivation. Further, the relationship between the intrinsic resting-state activity and task-evoked activation in lateral/superior frontal gyri, inferior/superior parietal lobules, superior temporal gyrus, and midline regions was stronger at higher WM task loads. In addition, both resting-state activity and the task-evoked activation in the superior parietal lobule/precuneus were significantly correlated with the WM task behavioral performance, explaining similar portions of intersubject performance variance. Together, these findings suggest that intrinsic resting-state activity facilitates or is permissive of specific brain circuit engagement to perform a cognitive task, and that resting activity can predict subsequent task-evoked brain responses and behavioral performance. Copyright © 2012 Wiley Periodicals, Inc.

Historical precipitation predictably alters the shape and magnitude of microbial functional response to soil moisture.

Science.gov (United States)

Averill, Colin; Waring, Bonnie G; Hawkes, Christine V

2016-05-01

Soil moisture constrains the activity of decomposer soil microorganisms, and in turn the rate at which soil carbon returns to the atmosphere. While increases in soil moisture are generally associated with increased microbial activity, historical climate may constrain current microbial responses to moisture. However, it is not known if variation in the shape and magnitude of microbial functional responses to soil moisture can be predicted from historical climate at regional scales. To address this problem, we measured soil enzyme activity at 12 sites across a broad climate gradient spanning 442-887 mm mean annual precipitation. Measurements were made eight times over 21 months to maximize sampling during different moisture conditions. We then fit saturating functions of enzyme activity to soil moisture and extracted half saturation and maximum activity parameter values from model fits. We found that 50% of the variation in maximum activity parameters across sites could be predicted by 30-year mean annual precipitation, an indicator of historical climate, and that the effect is independent of variation in temperature, soil texture, or soil carbon concentration. Based on this finding, we suggest that variation in the shape and magnitude of soil microbial response to soil moisture due to historical climate may be remarkably predictable at regional scales, and this approach may extend to other systems. If historical contingencies on microbial activities prove to be persistent in the face of environmental change, this approach also provides a framework for incorporating historical climate effects into biogeochemical models simulating future global change scenarios. © 2016 John Wiley & Sons Ltd.

Striatal Activation Predicts Differential Therapeutic Responses to Methylphenidate and Atomoxetine.

Science.gov (United States)

Schulz, Kurt P; Bédard, Anne-Claude V; Fan, Jin; Hildebrandt, Thomas B; Stein, Mark A; Ivanov, Iliyan; Halperin, Jeffrey M; Newcorn, Jeffrey H

2017-07-01

Methylphenidate has prominent effects in the dopamine-rich striatum that are absent for the selective norepinephrine transporter inhibitor atomoxetine. This study tested whether baseline striatal activation would predict differential response to the two medications in youth with attention-deficit/hyperactivity disorder (ADHD). A total of 36 youth with ADHD performed a Go/No-Go test during functional magnetic resonance imaging at baseline and were treated with methylphenidate and atomoxetine using a randomized cross-over design. Whole-brain task-related activation was regressed on clinical response. Task-related activation in right caudate nucleus was predicted by an interaction of clinical responses to methylphenidate and atomoxetine (F 1,30  = 17.00; p atomoxetine. The rate of robust response was higher for methylphenidate than for atomoxetine in youth with high (94.4% vs. 38.8%; p = .003; number needed to treat = 2, 95% CI = 1.31-3.73) but not low (33.3% vs. 50.0%; p = .375) caudate activation. Furthermore, response to atomoxetine predicted motor cortex activation (F 1,30  = 14.99; p atomoxetine in youth with ADHD, purportedly reflecting the dopaminergic effects of methylphenidate but not atomoxetine in the striatum, whereas motor cortex activation may predict response to atomoxetine. These data do not yet translate directly to the clinical setting, but the approach is potentially important for informing future research and illustrates that it may be possible to predict differential treatment response using a biomarker-driven approach. Stimulant Versus Nonstimulant Medication for Attention Deficit Hyperactivity Disorder in Children; https://clinicaltrials.gov/; NCT00183391. Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Structural Variation within the Amygdala and Ventromedial Prefrontal Cortex Predict Memory for Impressions in Older Adults

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Brittany Shane Cassidy

2012-08-01

Full Text Available Research has shown that lesions to regions involved in social and emotional cognition disrupt socioemotional processing and memory. We investigated how structural variation of regions involved in socioemotional memory (ventromedial prefrontal cortex [vmPFC], amygdala, as opposed to a region implicated in explicit memory (hippocampus, affected memory for impressions in young and older adults. Anatomical MRI scans for fifteen young and fifteen older adults were obtained and reconstructed to gather information about cortical thickness and subcortical volume. Young adults had greater amygdala and hippocampus volumes than old, and thicker left vmPFC than old, although right vmPFC thickness did not differ across the age groups. Participants formed behavior-based impressions and responded to interpersonally meaningful, social but interpersonally irrelevant, or non-social prompts, and completed a memory test. Results showed that greater left amygdala volume predicted enhanced overall memory for impressions in older but not younger adults. Increased right vmPFC thickness in older, but not younger, adults correlated with enhanced memory for impressions formed in the interpersonally meaningful context. Hippocampal volume was not predictive of social memory in young or older adults. These findings demonstrate the importance of structural variation in regions linked to socioemotional processing in the retention of impressions with age, and suggest that the amygdala and vmPFC play an integral role when encoding and retrieving social information.

Resonant activation in 2D and 3D systems driven by multi-variate Lévy noise

International Nuclear Information System (INIS)

Szczepaniec, Krzysztof; Dybiec, Bartłomiej

2014-01-01

Resonant activation is one of the classical effects demonstrating the constructive role of noise. In resonant activation, the cooperative action of a barrier modulation process and noise lead to the optimal escape kinetics as measured by the mean first passage time. Resonant activation has been observed in versatile systems for various types of barrier modulation process and noise type. Here, we show that resonant activation is also observed in 2D and 3D systems driven by bi-variate and tri-variate α-stable noise. The strength of resonant activation is sensitive to the exact value of the noise parameters. In particular, the decrease in the stability index α results in the disappearance of the resonant activation. (paper)

Prediction of interindividual variation in drug plasma levels in vivo from individual enzyme kinetic data and physiologically based pharmacokinetic modeling

NARCIS (Netherlands)

Bogaards, J.J.P.; Hissink, E.M.; Briggs, M.; Weaver, R.; Jochemsen, R.; Jackson, P.; Bertrand, M.; Bladeren, P. van

2000-01-01

A strategy is presented to predict interindividual variation in drug plasma levels in vivo by the use of physiologically based pharmacokinetic modeling and human in vitro metabolic parameters, obtained through the combined use of microsomes containing single cytochrome P450 enzymes and a human liver

Why Does Working Memory Capacity Predict Variation in Reading Comprehension? On the Influence of Mind Wandering and Executive Attention

Science.gov (United States)

McVay, Jennifer C.; Kane, Michael J.

2012-01-01

Some people are better readers than others, and this variation in comprehension ability is predicted by measures of working memory capacity (WMC). The primary goal of this study was to investigate the mediating role of mind-wandering experiences in the association between WMC and normal individual differences in reading comprehension, as predicted…

Inhibition and Updating, but Not Switching, Predict Developmental Dyslexia and Individual Variation in Reading Ability

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Caoilainn Doyle

2018-05-01

Full Text Available To elucidate the core executive function profile (strengths and weaknesses in inhibition, updating, and switching associated with dyslexia, this study explored executive function in 27 children with dyslexia and 29 age matched controls using sensitive z-mean measures of each ability and controlled for individual differences in processing speed. This study found that developmental dyslexia is associated with inhibition and updating, but not switching impairments, at the error z-mean composite level, whilst controlling for processing speed. Inhibition and updating (but not switching error composites predicted both dyslexia likelihood and reading ability across the full range of variation from typical to atypical. The predictive relationships were such that those with poorer performance on inhibition and updating measures were significantly more likely to have a diagnosis of developmental dyslexia and also demonstrate poorer reading ability. These findings suggest that inhibition and updating abilities are associated with developmental dyslexia and predict reading ability. Future studies should explore executive function training as an intervention for children with dyslexia as core executive functions appear to be modifiable with training and may transfer to improved reading ability.

Nonlinear Predictive Sliding Mode Control for Active Suspension System

Directory of Open Access Journals (Sweden)

Dazhuang Wang

2018-01-01

Full Text Available An active suspension system is important in meeting the requirements of the ride comfort and handling stability for vehicles. In this work, a nonlinear model of active suspension system and a corresponding nonlinear robust predictive sliding mode control are established for the control problem of active suspension. Firstly, a seven-degree-of-freedom active suspension model is established considering the nonlinear effects of springs and dampers; and secondly, the dynamic model is expanded in the time domain, and the corresponding predictive sliding mode control is established. The uncertainties in the controller are approximated by the fuzzy logic system, and the adaptive controller reduces the approximation error to increase the robustness of the control system. Finally, the simulation results show that the ride comfort and handling stability performance of the active suspension system is better than that of the passive suspension system and the Skyhook active suspension. Thus, the system can obviously improve the shock absorption performance of vehicles.

Online communication predicts Belgian adolescents' initiation of romantic and sexual activity.

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Vandenbosch, Laura; Beyens, Ine; Vangeel, Laurens; Eggermont, Steven

2016-04-01

Online communication is associated with offline romantic and sexual activity among college students. Yet, it is unknown whether online communication is associated with the initiation of romantic and sexual activity among adolescents. This two-wave panel study investigated whether chatting, visiting dating websites, and visiting erotic contact websites predicted adolescents' initiation of romantic and sexual activity. We analyzed two-wave panel data from 1163 Belgian adolescents who participated in the MORES Study. We investigated the longitudinal impact of online communication on the initiation of romantic relationships and sexual intercourse using logistic regression analyses. The odds ratios of initiating a romantic relationship among romantically inexperienced adolescents who frequently used chat rooms, dating websites, or erotic contact websites were two to three times larger than those of non-users. Among sexually inexperienced adolescents who frequently used chat rooms, dating websites, or erotic contact websites, the odds ratios of initiating sexual intercourse were two to five times larger than that among non-users, even after a number of other relevant factors were introduced. This is the first study to demonstrate that online communication predicts the initiation of offline sexual and romantic activity as early as adolescence. Practitioners and parents need to consider the role of online communication in adolescents' developing sexuality. • Adolescents increasingly communicate online with peers. • Online communication predicts romantic and sexual activity among college students. What is New: • Online communication predicts adolescents' offline romantic activity over time. • Online communication predicts adolescents' offline sexual activity over time.

Recent and past musical activity predicts cognitive aging variability: direct comparison with general lifestyle activities.

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Hanna-Pladdy, Brenda; Gajewski, Byron

2012-01-01

Studies evaluating the impact of modifiable lifestyle factors on cognition offer potential insights into sources of cognitive aging variability. Recently, we reported an association between extent of musical instrumental practice throughout the life span (greater than 10 years) on preserved cognitive functioning in advanced age. These findings raise the question of whether there are training-induced brain changes in musicians that can transfer to non-musical cognitive abilities to allow for compensation of age-related cognitive declines. However, because of the relationship between engagement in general lifestyle activities and preserved cognition, it remains unclear whether these findings are specifically driven by musical training or the types of individuals likely to engage in greater activities in general. The current study controlled for general activity level in evaluating cognition between musicians and nomusicians. Also, the timing of engagement (age of acquisition, past versus recent) was assessed in predictive models of successful cognitive aging. Seventy age and education matched older musicians (>10 years) and non-musicians (ages 59-80) were evaluated on neuropsychological tests and general lifestyle activities. Musicians scored higher on tests of phonemic fluency, verbal working memory, verbal immediate recall, visuospatial judgment, and motor dexterity, but did not differ in other general leisure activities. Partition analyses were conducted on significant cognitive measures to determine aspects of musical training predictive of enhanced cognition. The first partition analysis revealed education best predicted visuospatial functions in musicians, followed by recent musical engagement which offset low education. In the second partition analysis, early age of musical acquisition (memory in musicians, while analyses for other measures were not predictive. Recent and past musical activity, but not general lifestyle activities, predicted variability

The circadian variation of premature atrial contractions

DEFF Research Database (Denmark)

Larsen, Bjørn Strøier; Kumarathurai, Preman; Nielsen, Olav W

2016-01-01

AIMS: The aim of the study was to assess a possible circadian variation of premature atrial contractions (PACs) in a community-based population and to determine if the daily variation could be used to assess a more vulnerable period of PACs in predicting later incidence of atrial fibrillation (AF...... variation in heart rate. After adjusting for relevant risk factors, the risk of AF was equal in all time intervals throughout the day. CONCLUSION: Premature atrial contractions showed a circadian variation in subjects with frequent PACs. No specific time interval of the day was more predictive of AF than...

Variation in Annual Volume at a University Hospital Does Not Predict Mortality for Pancreatic Resections

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Rita A. Mukhtar

2008-01-01

Full Text Available Annual volume of pancreatic resections has been shown to affect mortality rates, prompting recommendations to regionalize these procedures to high-volume hospitals. Implementation has been difficult, given the paucity of high-volume centers and the logistical hardships facing patients. Some studies have shown that low-volume hospitals achieve good outcomes as well, suggesting that other factors are involved. We sought to determine whether variations in annual volume affected patient outcomes in 511 patients who underwent pancreatic resections at the University of California, San Francisco between 1990 and 2005. We compared postoperative mortality and complication rates between low, medium, or high volume years, designated by the number of resections performed, adjusting for patient characteristics. Postoperative mortality rates did not differ between high volume years and medium/low volume years. As annual hospital volume of pancreatic resections may not predict outcome, identification of actual predictive factors may allow low-volume centers to achieve excellent outcomes.

Prediction of adolescents doing physical activity after completing secondary education.

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Moreno-Murcia, Juan Antonio; Huéscar, Elisa; Cervelló, Eduardo

2012-03-01

The purpose of this study, based on the self-determination theory (Ryan & Deci, 2000) was to test the prediction power of student's responsibility, psychological mediators, intrinsic motivation and the importance attached to physical education in the intention to continue to practice some form of physical activity and/or sport, and the possible relationships that exist between these variables. We used a sample of 482 adolescent students in physical education classes, with a mean age of 14.3 years, which were measured for responsibility, psychological mediators, sports motivation, the importance of physical education and intention to be physically active. We completed an analysis of structural equations modelling. The results showed that the responsibility positively predicted psychological mediators, and this predicted intrinsic motivation, which positively predicted the importance students attach to physical education, and this, finally, positively predicted the intention of the student to continue doing sport. Results are discussed in relation to the promotion of student's responsibility towards a greater commitment to the practice of physical exercise.

Seasonal variation in population density and heterotrophic activity of attached and free-living bacteria in coastal waters

International Nuclear Information System (INIS)

Iriberri, J.; Unanue, M.; Barcina, I.; Egea, L.

1987-01-01

The abundance and heterotrophic activity of attached and free-living bacteria was examined seasonally in coastal water. Heterotrophic activity was determined by the uptake of [ 14 C]glucose. The density of attached bacteria was always minor, not showing a seasonal variation, whereas the free-living bacteria were more numerous and showed a marked seasonal variation, their density being higher under warmer conditions. The contribution of the attached bacteria to the total assimilation of [ 14 C]glucose was lower than that of the free-living bacteria, neither of them showing a seasonal variation. On a cellular basis, attached bacteria were more active, since they assimilated more [ 14 C]glucose and showed, under warmer conditions, a higher cellular volume. The authors consider that the factors responsible for these observations were the amount and quality of the particulate material, the different availability of organic matter for the two types of bacteria, and in a fundamental way, the variation in water temperature

Canonical variate regression.

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Luo, Chongliang; Liu, Jin; Dey, Dipak K; Chen, Kun

2016-07-01

In many fields, multi-view datasets, measuring multiple distinct but interrelated sets of characteristics on the same set of subjects, together with data on certain outcomes or phenotypes, are routinely collected. The objective in such a problem is often two-fold: both to explore the association structures of multiple sets of measurements and to develop a parsimonious model for predicting the future outcomes. We study a unified canonical variate regression framework to tackle the two problems simultaneously. The proposed criterion integrates multiple canonical correlation analysis with predictive modeling, balancing between the association strength of the canonical variates and their joint predictive power on the outcomes. Moreover, the proposed criterion seeks multiple sets of canonical variates simultaneously to enable the examination of their joint effects on the outcomes, and is able to handle multivariate and non-Gaussian outcomes. An efficient algorithm based on variable splitting and Lagrangian multipliers is proposed. Simulation studies show the superior performance of the proposed approach. We demonstrate the effectiveness of the proposed approach in an [Formula: see text] intercross mice study and an alcohol dependence study. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Cognitive emotion regulation enhances aversive prediction error activity while reducing emotional responses.

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Mulej Bratec, Satja; Xie, Xiyao; Schmid, Gabriele; Doll, Anselm; Schilbach, Leonhard; Zimmer, Claus; Wohlschläger, Afra; Riedl, Valentin; Sorg, Christian

2015-12-01

Cognitive emotion regulation is a powerful way of modulating emotional responses. However, despite the vital role of emotions in learning, it is unknown whether the effect of cognitive emotion regulation also extends to the modulation of learning. Computational models indicate prediction error activity, typically observed in the striatum and ventral tegmental area, as a critical neural mechanism involved in associative learning. We used model-based fMRI during aversive conditioning with and without cognitive emotion regulation to test the hypothesis that emotion regulation would affect prediction error-related neural activity in the striatum and ventral tegmental area, reflecting an emotion regulation-related modulation of learning. Our results show that cognitive emotion regulation reduced emotion-related brain activity, but increased prediction error-related activity in a network involving ventral tegmental area, hippocampus, insula and ventral striatum. While the reduction of response activity was related to behavioral measures of emotion regulation success, the enhancement of prediction error-related neural activity was related to learning performance. Furthermore, functional connectivity between the ventral tegmental area and ventrolateral prefrontal cortex, an area involved in regulation, was specifically increased during emotion regulation and likewise related to learning performance. Our data, therefore, provide first-time evidence that beyond reducing emotional responses, cognitive emotion regulation affects learning by enhancing prediction error-related activity, potentially via tegmental dopaminergic pathways. Copyright © 2015 Elsevier Inc. All rights reserved.

Using the amplitude variation of a reverberation chamber channel to predict the synchronization of a wireless digital communication test system

NARCIS (Netherlands)

Tanuhardja, Ray R.; Gonzalez, Luis A.; Wang, Chih-Ming; Young, William F.; Remley, Kate A.; Ladbury, John M.

2015-01-01

We discuss the use of a metric based on the amplitude variation of a channel in the signal bandwidth to predict whether or not a digital wireless communication test system receiver will be able to demodulate a test signal. This metric is compared to another method consisting of the correlation

Genetic Programming for Sea Level Predictions in an Island Environment

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M.A. Ghorbani

2010-03-01

Full Text Available Accurate predictions of sea-level are important for geodetic applications, navigation, coastal, industrial and tourist activities. In the current work, the Genetic Programming (GP and artificial neural networks (ANNs were applied to forecast half-daily and daily sea-level variations from 12 hours to 5 days ahead. The measurements at the Cocos (Keeling Islands in the Indian Ocean were used for training and testing of the employed artificial intelligence techniques. A comparison was performed of the predictions from the GP model and the ANN simulations. Based on the comparison outcomes, it was found that the Genetic Programming approach can be successfully employed in forecasting of sea level variations.

Individual variation in baseline and stress-induced corticosterone and prolactin levels predicts parental effort by nesting mourning doves

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Miller, David A.; Vleck, Carol M.; Otis, David L.

2009-01-01

Endocrine systems have an important mechanistic role in structuring life-history trade-offs. During breeding, individual variation in prolactin (PRL) and corticosterone (CORT) levels affects behavioral and physiological processes that drive trade-offs between reproduction and self-maintenance. We examined patterns in baseline (BL) and stress induced (SI; level following a standard capture-restraint protocol) levels of PRL and CORT for breeding mourning doves (Zenaida macroura). We determined whether the relationship of adult condition and parental effort to hormone levels in wild birds was consistent with life-history predictions. Both BL PRL and BL CORT level in adults were positively related to nestling weight at early nestling ages, consistent with the prediction of a positive relationship of hormone levels to current parental effort of adults and associated increased energy demand. Results are consistent with the two hormones acting together at baseline levels to limit negative effects of CORT on reproduction while maintaining beneficial effects such as increased foraging for nestling feeding. Our data did not support predictions that SI responses would vary in response to nestling or adult condition. The magnitude of CORT response in the parents to our capture-restraint protocol was negatively correlated with subsequent parental effort. Average nestling weights for adults with the highest SI CORT response were on average 10–15% lighter than expected for their age in follow-up visits after the stress event. Our results demonstrated a relationship between individual hormone levels and within population variation in parental effort and suggested that hormonal control plays an important role in structuring reproductive decisions for mourning doves.

Validation of Quantitative Structure-Activity Relationship (QSAR Model for Photosensitizer Activity Prediction

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Sharifuddin M. Zain

2011-11-01

Full Text Available Photodynamic therapy is a relatively new treatment method for cancer which utilizes a combination of oxygen, a photosensitizer and light to generate reactive singlet oxygen that eradicates tumors via direct cell-killing, vasculature damage and engagement of the immune system. Most of photosensitizers that are in clinical and pre-clinical assessments, or those that are already approved for clinical use, are mainly based on cyclic tetrapyrroles. In an attempt to discover new effective photosensitizers, we report the use of the quantitative structure-activity relationship (QSAR method to develop a model that could correlate the structural features of cyclic tetrapyrrole-based compounds with their photodynamic therapy (PDT activity. In this study, a set of 36 porphyrin derivatives was used in the model development where 24 of these compounds were in the training set and the remaining 12 compounds were in the test set. The development of the QSAR model involved the use of the multiple linear regression analysis (MLRA method. Based on the method, r2 value, r2 (CV value and r2 prediction value of 0.87, 0.71 and 0.70 were obtained. The QSAR model was also employed to predict the experimental compounds in an external test set. This external test set comprises 20 porphyrin-based compounds with experimental IC50 values ranging from 0.39 µM to 7.04 µM. Thus the model showed good correlative and predictive ability, with a predictive correlation coefficient (r2 prediction for external test set of 0.52. The developed QSAR model was used to discover some compounds as new lead photosensitizers from this external test set.

Vigorous physical activity predicts higher heart rate variability among younger adults.

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May, Richard; McBerty, Victoria; Zaky, Adam; Gianotti, Melino

2017-06-14

Baseline heart rate variability (HRV) is linked to prospective cardiovascular health. We tested intensity and duration of weekly physical activity as predictors of heart rate variability in young adults. Time and frequency domain indices of HRV were calculated based on 5-min resting electrocardiograms collected from 82 undergraduate students. Hours per week of both moderate and vigorous activity were estimated using the International Physical Activity Questionnaire. In regression analyses, hours of vigorous physical activity, but not moderate activity, significantly predicted greater time domain and frequency domain indices of heart rate variability. Adjusted for weekly frequency, greater daily duration of vigorous activity failed to predict HRV indices. Future studies should test direct measurements of vigorous activity patterns as predictors of autonomic function in young adulthood.

A multi-scale modeling framework for individualized, spatiotemporal prediction of drug effects and toxicological risk

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Juan Guillermo eDiaz Ochoa

2013-01-01

Full Text Available In this study, we focus on a novel multi-scale modeling approach for spatiotemporal prediction of the distribution of substances and resulting hepatotoxicity by combining cellular models, a 2D liver model, and whole-body model. As a case study, we focused on predicting human hepatotoxicity upon treatment with acetaminophen based on in vitro toxicity data and potential inter-individual variability in gene expression and enzyme activities. By aggregating mechanistic, genome-based in silico cells to a novel 2D liver model and eventually to a whole body model, we predicted pharmacokinetic properties, metabolism, and the onset of hepatotoxicity in an in silico patient. Depending on the concentration of acetaminophen in the liver and the accumulation of toxic metabolites, cell integrity in the liver as a function of space and time as well as changes in the elimination rate of substances were estimated. We show that the variations in elimination rates also influence the distribution of acetaminophen and its metabolites in the whole body. Our results are in agreement with experimental results. What is more, the integrated model also predicted variations in drug toxicity depending on alterations of metabolic enzyme activities. Variations in enzyme activity, in turn, reflect genetic characteristics or diseases of individuals. In conclusion, this framework presents an important basis for efficiently integrating inter-individual variability data into models, paving the way for personalized or stratified predictions of drug toxicity and efficacy.

Age-dependent variations of somatomedin-A activity in the rabbit

International Nuclear Information System (INIS)

Charrier, J.

1978-01-01

Somatomedin-A (SM-A) was assayed by Hall's method using chick embryo pelvis. The relatively high inorganic SO 4 concentration of rabbit sera (1.5 mM) interfered with the estimation of the relative potency R of SM activity. Separation of the serum stimulation period from radioactive sulfate incorporation (post-incubation system) thus permitted this inconvenience to be eliminated. Using this technique rabbit SM-A activity from birth to 180 days of age was estimated. The sera from 0 to 2-day old newborn rabbits inhibited 35 SO 4 uptake by chick pelvis cartilage. A transition period between 3 and 5 days of age after which the sera obtained became stimulant was observed. SM-A activity increased slowly from 0.5 to about 1 U/ml in the age period between 10 and 180 days, but there was considerable individual variation

Evaluation of stroke volume variation obtained by arterial pulse contour analysis to predict fluid responsiveness intraoperatively.

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Lahner, D; Kabon, B; Marschalek, C; Chiari, A; Pestel, G; Kaider, A; Fleischmann, E; Hetz, H

2009-09-01

Fluid management guided by oesophageal Doppler monitor has been reported to improve perioperative outcome. Stroke volume variation (SVV) is considered a reliable clinical predictor of fluid responsiveness. Consequently, the aim of the present trial was to evaluate the accuracy of SVV determined by arterial pulse contour (APCO) analysis, using the FloTrac/Vigileo system, to predict fluid responsiveness as measured by the oesophageal Doppler. Patients undergoing major abdominal surgery received intraoperative fluid management guided by oesophageal Doppler monitoring. Fluid boluses of 250 ml each were administered in case of a decrease in corrected flow time (FTc) to 10%. The ability of SVV to predict fluid responsiveness was assessed by calculation of the area under the receiver operating characteristic (ROC) curve. Twenty patients received 67 fluid boluses. Fifty-two of the 67 fluid boluses administered resulted in fluid responsiveness. SVV achieved an area under the ROC curve of 0.512 [confidence interval (CI) 0.32-0.70]. A cut-off point for fluid responsiveness was found for SVV > or =8.5% (sensitivity: 77%; specificity: 43%; positive predictive value: 84%; and negative predictive value: 33%). This prospective, interventional observer-blinded study demonstrates that SVV obtained by APCO, using the FloTrac/Vigileo system, is not a reliable predictor of fluid responsiveness in the setting of major abdominal surgery.

Variation in radon exhalation from the ground on the active fault in Kobe

Energy Technology Data Exchange (ETDEWEB)

Yasuoka, Y.; Shinogi, M. [Kobe Pharmaceutical Univ., Kobe, Hyogo (Japan)

1998-12-31

Since 27 January 1997, the measurements of radon (Rn-222) exhaled from the ground have been made continuously by the use of PICO-RAD detector (Packard instrument Co.) at monitoring stations on Ashiya active fault. The fault may have been slipped by the Kobe earthquake (magnitude 7.2, 17 January 1995). The variation of relative radon exhalation on the fault was large. We guessed the large variation of relative radon exhalation on the fault was caused by not only the influence of meteorology but also the influence of other factors. (author)

On-chip active gate bias circuit for MMIC amplifier applications with 100% threshold voltage variation compensation

NARCIS (Netherlands)

Hek, A.P. de; Busking, E.B.

2006-01-01

In this paper the design and performance of an on-chip active gate bias circuit for application in MMIC amplifiers, which gives 100% compensation for threshold variation and at the same time is insensitive to supply voltage variations, is discussed. Design equations have been given. In addition, the

Short communication: Variations in major mineral contents of Mediterranean buffalo milk and application of Fourier-transform infrared spectroscopy for their prediction.

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Stocco, G; Cipolat-Gotet, C; Bonfatti, V; Schiavon, S; Bittante, G; Cecchinato, A

2016-11-01

The aims of this study were (1) to assess variability in the major mineral components of buffalo milk, (2) to estimate the effect of certain environmental sources of variation on the major minerals during lactation, and (3) to investigate the possibility of using Fourier-transform infrared (FTIR) spectroscopy as an indirect, noninvasive tool for routine prediction of the mineral content of buffalo milk. A total of 173 buffaloes reared in 5 herds were sampled once during the morning milking. Milk samples were analyzed for Ca, P, K, and Mg contents within 3h of sample collection using inductively coupled plasma optical emission spectrometry. A Milkoscan FT2 (Foss, Hillerød, Denmark) was used to acquire milk spectra over the spectral range from 5,000 to 900 wavenumber/cm. Prediction models were built using a partial least square approach, and cross-validation was used to assess the prediction accuracy of FTIR. Prediction models were validated using a 4-fold random cross-validation, thus dividing the calibration-test set in 4 folds, using one of them to check the results (prediction models) and the remaining 3 to develop the calibration models. Buffalo milk minerals averaged 162, 117, 86, and 14.4mg/dL of milk for Ca, P, K, and Mg, respectively. Herd and days in milk were the most important sources of variation in the traits investigated. Parity slightly affected only Ca content. Coefficients of determination of cross-validation between the FTIR-predicted and the measured values were 0.71, 0.70, and 0.72 for Ca, Mg, and P, respectively, whereas prediction accuracy was lower for K (0.55). Our findings reveal FTIR to be an unsuitable tool when milk mineral content needs to be predicted with high accuracy. Predictions may play a role as indicator traits in selective breeding (if the additive genetic correlation between FTIR predictions and measures of milk minerals is high enough) or in monitoring the milk of buffalo populations for dairy industry purposes. Copyright �

Model variations in predicting incidence of Plasmodium falciparum malaria using 1998-2007 morbidity and meteorological data from south Ethiopia

OpenAIRE

Loha, Eskindir; Lindtj?rn, Bernt

2010-01-01

Abstract Background Malaria transmission is complex and is believed to be associated with local climate changes. However, simple attempts to extrapolate malaria incidence rates from averaged regional meteorological conditions have proven unsuccessful. Therefore, the objective of this study was to determine if variations in specific meteorological factors are able to consistently predict P. falciparum malaria incidence at different locations in south Ethiopia. Methods Retrospective data from 4...

Self-reported Physical Activity Predicts Pain Inhibitory and Facilitatory Function

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Naugle, Kelly M.; Riley, Joseph L.

2013-01-01

Considerable evidence suggests regular physical activity can reduce chronic pain symptoms. Dysfunction of endogenous facilitatory and inhibitory systems has been implicated in multiple chronic pain conditions. However, few studies have investigated the relationship between levels of physical activity and descending pain modulatory function. Purpose This study’s purpose was to determine whether self-reported levels of physical activity in healthy adults predicted 1) pain sensitivity to heat and cold stimuli, 2) pain facilitatory function as tested by temporal summation of pain (TS), and 3) pain inhibitory function as tested by conditioned pain modulation (CPM) and offset analgesia. Methods Forty-eight healthy adults (age range 18–76) completed the International Physical Activity Questionnaire (IPAQ) and the following pain tests: heat pain thresholds (HPT), heat pain suprathresholds, cold pressor pain (CPP), temporal summation of heat pain, conditioned pain modulation, and offset analgesia. The IPAQ measured levels of walking, moderate, vigorous and total physical activity over the past seven days. Hierarchical linear regressions were conducted to determine the relationship between each pain test and self-reported levels of physical activity, while controlling for age, sex and psychological variables. Results Self-reported total and vigorous physical activity predicted TS and CPM (p’s pain and greater CPM. The IPAQ measures did not predict any of the other pain measures. Conclusion Thus, these results suggest that healthy older and younger adults who self-report greater levels of vigorous and total physical activity exhibit enhanced descending pain modulatory function. Improved descending pain modulation may be a mechanism through which exercise reduces or prevents chronic pain symptoms. PMID:23899890

Diurnal variation in glycogen phosphorylase activity in rat liver. A quantitative histochemical study

NARCIS (Netherlands)

Frederiks, W. M.; Marx, F.; Bosch, K. S.

1987-01-01

The diurnal variations of the glycogen content and of glycogen phosphorylase activity in periportal and pericentral areas of rat liver parenchyma have been analyzed in periodic acid Schiff (PAS)-stained cryostat sections using quantitative microdensitometry. Glycogen content and phosphorylase

Stock price change rate prediction by utilizing social network activities.

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Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

2014-01-01

Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

Stock Price Change Rate Prediction by Utilizing Social Network Activities

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Shangkun Deng

2014-01-01

Full Text Available Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL and genetic algorithm (GA. MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.

Seasonal variation of daily physical activity in individuals with heart failure

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Michael J. Shoemaker

2016-09-01

Full Text Available BackgroundPrevious studies indicate that seasonal variation affects daily physical activity (PA, but none have investigated this relationship in individuals with heart failure (HF who also have implanted cardioverter defibrillators and cardiac resynchronization therapy (ICD/CRT devices. The purpose of the present study was to determine if seasonal variation in temperature affects daily PA in patients with HF and ICD/CRTs.Patients and methodsSecondary analysis of data from 16 subjects with HF and Medtronic® ICD/CRT devices enrolled in a randomized trial investigating interventions to improve daily PA. Due to the rolling study enrollment, daily PA data for all subjects were not available for the entire time frame and were divided into two groups. Determination of seasonal variation of daily PA was determined using visual analysis of daily PA plotted with average temperature, autocorrelation, visual analysis of seasonal subseries plots and boxplot analysis, as well as Wilcoxon signed-rank tests.ResultsSubjects 1-8 demonstrated the greatest differences in daily PA during periods of seasonal transition whereas subjects 9-16 demonstrated the greatest variation in daily PA with greatest seasonal temperature difference. Wilcoxon signed-rank testing of the lowest and highest months for daily PA revealed median differences of 0.30 (p = 0.050 and 0.36 hours (p = 0.036 for subjects 1-8 and 9-16, with effect sizes of 0.69 and 0.74, respectively.ConclusionsSeasonal variation in mean temperature appears to affect daily PA in individuals with HF and ICD/CRT devices by a magnitude of 0.30-0.36 hours, which may need to be accounted for in future research investigating interventions to improve daily PA.

Variation in circulating testosterone during mating predicts reproductive success in a wild songbird.

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Beate Apfelbeck

2016-08-01

Full Text Available Testosterone is an important sex hormone and mediates reproduction in male vertebrates. There is ample evidence that testosterone coordinates the expression of physiological, morphological and behavioural traits during reproduction and many of these traits are under sexual selection. However, only few studies so far have examined if individual variation in testosterone is correlated with reproductive success. Because socially monogamous bird species pass through different phases within a breeding cycle and each of these phases requires the expression of different behaviours, the relation between testosterone and reproductive success could vary with breeding stage. Here we investigate the link between reproductive success and testosterone in European stonechats – a socially monogamous songbird with biparental care. Previous studies found that territorial aggression in breeding stonechats depends on testosterone and that testosterone levels peak during the mating phase. Thus, high testosterone levels during mating may influence reproductive success by promoting territorial aggression and mate guarding. We found that males with two breeding attempts produced a similar number of fledglings as males with three breeding attempts. However, males with two breeding attempts expressed higher levels of testosterone than males with just one or those with three breeding attempts, regardless of whether testosterone was measured during the mating or the parental phase of the first brood. Furthermore, testosterone levels during mating, but not during parenting correlated with the total annual number of fledglings. Thus, individual variation in levels of plasma testosterone predicted reproductive success in stonechats.

Development of Preparatory Activity Indexed by the Contingent Negative Variation in Children

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Flores, Angelica B.; Digiacomo, Marcia R.; Meneres, Susana; Trigo, Eva; Gomez, Carlos M.

2009-01-01

Objectives: The present study investigated the effect of age on task-specific preparatory activation induced by a spatial cue using the central cue Posner's paradigm. The behavioral responses and the contingent negative variation (CNV) generated between S1 (the warning stimulus) and S2 (the imperative stimulus) were compared between 16 healthy…

Causal Genetic Variation Underlying Metabolome Differences.

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Swain-Lenz, Devjanee; Nikolskiy, Igor; Cheng, Jiye; Sudarsanam, Priya; Nayler, Darcy; Staller, Max V; Cohen, Barak A

2017-08-01

An ongoing challenge in biology is to predict the phenotypes of individuals from their genotypes. Genetic variants that cause disease often change an individual's total metabolite profile, or metabolome. In light of our extensive knowledge of metabolic pathways, genetic variants that alter the metabolome may help predict novel phenotypes. To link genetic variants to changes in the metabolome, we studied natural variation in the yeast Saccharomyces cerevisiae We used an untargeted mass spectrometry method to identify dozens of metabolite Quantitative Trait Loci (mQTL), genomic regions containing genetic variation that control differences in metabolite levels between individuals. We mapped differences in urea cycle metabolites to genetic variation in specific genes known to regulate amino acid biosynthesis. Our functional assays reveal that genetic variation in two genes, AUA1 and ARG81 , cause the differences in the abundance of several urea cycle metabolites. Based on knowledge of the urea cycle, we predicted and then validated a new phenotype: sensitivity to a particular class of amino acid isomers. Our results are a proof-of-concept that untargeted mass spectrometry can reveal links between natural genetic variants and metabolome diversity. The interpretability of our results demonstrates the promise of using genetic variants underlying natural differences in the metabolome to predict novel phenotypes from genotype. Copyright © 2017 by the Genetics Society of America.

Evolutionary rate variation and RNA secondary structure prediction

DEFF Research Database (Denmark)

Knudsen, B.; Andersen, E.S.; Damgaard, C.

2004-01-01

Predicting RNA secondary structure using evolutionary history can be carried out by using an alignment of related RNA sequences with conserved structure. Accurately determining evolutionary substitution rates for base pairs and single stranded nucleotides is a concern for methods based on this type...... by applying rates derived from tRNA and rRNA to the prediction of the much more rapidly evolving 5'-region of HIV-1. We find that the HIV-1 prediction is in agreement with experimental data, even though the relative evolutionary rate between A and G is significantly increased, both in stem and loop regions...

D2 receptor genotype and striatal dopamine signaling predict motor cortical activity and behavior in humans.

Science.gov (United States)

Fazio, Leonardo; Blasi, Giuseppe; Taurisano, Paolo; Papazacharias, Apostolos; Romano, Raffaella; Gelao, Barbara; Ursini, Gianluca; Quarto, Tiziana; Lo Bianco, Luciana; Di Giorgio, Annabella; Mancini, Marina; Popolizio, Teresa; Rubini, Giuseppe; Bertolino, Alessandro

2011-02-14

Pre-synaptic D2 receptors regulate striatal dopamine release and DAT activity, key factors for modulation of motor pathways. A functional SNP of DRD2 (rs1076560 G>T) is associated with alternative splicing such that the relative expression of D2S (mainly pre-synaptic) vs. D2L (mainly post-synaptic) receptor isoforms is decreased in subjects with the T allele with a putative increase of striatal dopamine levels. To evaluate how DRD2 genotype and striatal dopamine signaling predict motor cortical activity and behavior in humans, we have investigated the association of rs1076560 with BOLD fMRI activity during a motor task. To further evaluate the relationship of this circuitry with dopamine signaling, we also explored the correlation between genotype based differences in motor brain activity and pre-synaptic striatal DAT binding measured with [(123)I] FP-CIT SPECT. Fifty healthy subjects, genotyped for DRD2 rs1076560 were studied with BOLD-fMRI at 3T while performing a visually paced motor task with their right hand; eleven of these subjects also underwent [(123)I]FP-CIT SPECT. SPM5 random-effects models were used for statistical analyses. Subjects carrying the T allele had greater BOLD responses in left basal ganglia, thalamus, supplementary motor area, and primary motor cortex, whose activity was also negatively correlated with reaction time at the task. Moreover, left striatal DAT binding and activity of left supplementary motor area were negatively correlated. The present results suggest that DRD2 genetic variation was associated with focusing of responses in the whole motor network, in which activity of predictable nodes was correlated with reaction time and with striatal pre-synaptic dopamine signaling. Our results in humans may help shed light on genetic risk for neurobiological mechanisms involved in the pathophysiology of disorders with dysregulation of striatal dopamine like Parkinson's disease. Copyright © 2010 Elsevier Inc. All rights reserved.

Predicting space climate change

Science.gov (United States)

Balcerak, Ernie

2011-10-01

Galactic cosmic rays and solar energetic particles can be hazardous to humans in space, damage spacecraft and satellites, pose threats to aircraft electronics, and expose aircrew and passengers to radiation. A new study shows that these threats are likely to increase in coming years as the Sun approaches the end of the period of high solar activity known as “grand solar maximum,” which has persisted through the past several decades. High solar activity can help protect the Earth by repelling incoming galactic cosmic rays. Understanding the past record can help scientists predict future conditions. Barnard et al. analyzed a 9300-year record of galactic cosmic ray and solar activity based on cosmogenic isotopes in ice cores as well as on neutron monitor data. They used this to predict future variations in galactic cosmic ray flux, near-Earth interplanetary magnetic field, sunspot number, and probability of large solar energetic particle events. The researchers found that the risk of space weather radiation events will likely increase noticeably over the next century compared with recent decades and that lower solar activity will lead to increased galactic cosmic ray levels. (Geophysical Research Letters, doi:10.1029/2011GL048489, 2011)

Predicting activities after stroke : what is clinically relevant?

NARCIS (Netherlands)

Kwakkel, G.; Kollen, B. J.

Knowledge about factors that determine the final outcome after stroke is important for early stroke management, rehabilitation goals, and discharge planning. This narrative review provides an overview of current knowledge about the prediction of activities after stroke. We reviewed the pattern of

The contact binary VW Cephei revisited: surface activity and period variation

Science.gov (United States)

Mitnyan, T.; Bódi, A.; Szalai, T.; Vinkó, J.; Szatmáry, K.; Borkovits, T.; Bíró, B. I.; Hegedüs, T.; Vida, K.; Pál, A.

2018-05-01

Context. Despite the fact that VW Cephei is one of the most well-studied contact binaries in the literature, there is no fully consistent model available that can explain every observed property of this system. Aims: Our aims are to obtain new spectra along with photometric measurements, to analyze what kind of changes may have happened in the system in the past two decades, and to propose new ideas for explaining them. Methods: For the period analysis we determined ten new times of minima from our light curves, and constructed a new O-C diagram of the system. Radial velocities of the components were determined using the cross-correlation technique. The light curves and radial velocities were modeled simultaneously with the PHOEBE code. All observed spectra were compared to synthetic spectra and equivalent widths (EWs) of the Hα line were measured on their differences. Results: We re-determine the physical parameters of the system according to our new light curve and spectral models. We confirm that the primary component is more active than the secondary, and there is a correlation between spottedness and the chromospheric activity. We propose that the flip-flop phenomenon occurring on the primary component could be a possible explanation of the observed nature of the activity. To explain the period variation of VW Cep, we test two previously suggested scenarios: the presence of a fourth body in the system, and the Applegate-mechanism caused by periodic magnetic activity. We conclude that although none of these mechanisms can be ruled out entirely, the available data suggest that mass transfer with a slowly decreasing rate provides the most likely explanation for the period variation of VW Cep.

In normal human fibroblasts variation in DSB repair capacity cannot be ascribed to radiation-induced changes in the localisation, expression or activity of major NHEJ proteins

DEFF Research Database (Denmark)

Kasten-Pisula, Ulla; Vronskaja, Svetlana; Overgaard, Jens

2008-01-01

in the activity of the DNA-PK complex induced upon irradiation. CONCLUSIONS: For normal human fibroblasts, the level or activity of NHEJ proteins measured prior to or after irradiation cannot be used to predict the DSB repair capacity or cellular radiosensitivity. Udgivelsesdato: 2008-Mar......BACKGROUND AND PURPOSE: The aim of the present study was to test whether for normal human fibroblasts the variation in double-strand break (DSB) repair capacity results from radiation-induced differences in localisation, expression or activity of major non-homologous end-joining (NHEJ) proteins....... MATERIALS AND METHODS: Experiments were performed with 11 normal human fibroblast strains AF01-11. NHEJ proteins were determined by Western blot and DNA-PK activity by pulldown-assay. RESULTS: The four NHEJ proteins tested (Ku70, Ku80, XRCC4 and DNA-PKcs) were found to be localised almost exclusively...

Statistical analysis of activation and reaction energies with quasi-variational coupled-cluster theory

Science.gov (United States)

Black, Joshua A.; Knowles, Peter J.

2018-06-01

The performance of quasi-variational coupled-cluster (QV) theory applied to the calculation of activation and reaction energies has been investigated. A statistical analysis of results obtained for six different sets of reactions has been carried out, and the results have been compared to those from standard single-reference methods. In general, the QV methods lead to increased activation energies and larger absolute reaction energies compared to those obtained with traditional coupled-cluster theory.

Ladder variational autoencoders

DEFF Research Database (Denmark)

Sønderby, Casper Kaae; Raiko, Tapani; Maaløe, Lars

2016-01-01

Variational autoencoders are powerful models for unsupervised learning. However deep models with several layers of dependent stochastic variables are difficult to train which limits the improvements obtained using these highly expressive models. We propose a new inference model, the Ladder...... Variational Autoencoder, that recursively corrects the generative distribution by a data dependent approximate likelihood in a process resembling the recently proposed Ladder Network. We show that this model provides state of the art predictive log-likelihood and tighter log-likelihood lower bound compared...

Ladder Variational Autoencoder

DEFF Research Database (Denmark)

Sønderby, Casper Kaae; Raiko, Tapani; Maaløe, Lars

2016-01-01

Variational autoencoders are powerful models for unsupervised learning. However deep models with several layers of dependent stochastic variables are difficult to train which limits the improvements obtained using these highly expressive models. We propose a new inference model, the Ladder...... Variational Autoencoder, that recursively corrects the generative distribution by a data dependent approximate likelihood in a process resembling the recently proposed Ladder Network. We show that this model provides state of the art predictive log-likelihood and tighter log-likelihood lower bound compared...

Solar activity influence on climatic variations of stratosphere and mesosphere in mid-latitudes

International Nuclear Information System (INIS)

Taubenheim, J.; Entzian, G.; Voncossart, G.

1989-01-01

The direct modulation of temperature of the mid-latitude mesosphere by the solar-cycle EUV variation, which leads to greater heat input at higher solar activity, is well established. Middle atmosphere temperature modulation by the solar cycle is independently confirmed by the variation of reflection heights of low frequency radio waves in the lower ionosphere, which are regularly monitored over about 30 years. As explained elsewhere in detail, these reflection heights depend on the geometric altitude of a certain isobaric surface (near 80 k), and on the solar ionizing Lyman-alpha radiation flux. Knowing the solar cycle variation of Lyman-alpha how much the measured reflection heights would be lowered with the transition from solar minimum to maximum can be calculated, if the vertical baric structure of the neutral atmosphere would remain unchanged. Any discrepancy between expected and observed height change must be explained by an uplifting of the isobaric level from solar minimum to maximum, caused by the temperature rise in the mesosphere. By integrating the solar cycle temperature changes over the height region of the middle atmosphere, and assuming that the lower boundary (tropopause) has no solar cycle variation, the magnitude of this uplifting can be estimated. It is given for the Lidar-derived and for the rocket-measured temperature variations. Comparison suggests that the real amplitude of the solar cycle temperature variation in the mesosphere is underestimated when using the rocket data, but probably overestimated with the Lidar data

Single-Nucleotide Variations in Cardiac Arrhythmias: Prospects for Genomics and Proteomics Based Biomarker Discovery and Diagnostics

Directory of Open Access Journals (Sweden)

Ayman Abunimer

2014-03-01

Full Text Available Cardiovascular diseases are a large contributor to causes of early death in developed countries. Some of these conditions, such as sudden cardiac death and atrial fibrillation, stem from arrhythmias—a spectrum of conditions with abnormal electrical activity in the heart. Genome-wide association studies can identify single nucleotide variations (SNVs that may predispose individuals to developing acquired forms of arrhythmias. Through manual curation of published genome-wide association studies, we have collected a comprehensive list of 75 SNVs associated with cardiac arrhythmias. Ten of the SNVs result in amino acid changes and can be used in proteomic-based detection methods. In an effort to identify additional non-synonymous mutations that affect the proteome, we analyzed the post-translational modification S-nitrosylation, which is known to affect cardiac arrhythmias. We identified loss of seven known S-nitrosylation sites due to non-synonymous single nucleotide variations (nsSNVs. For predicted nitrosylation sites we found 1429 proteins where the sites are modified due to nsSNV. Analysis of the predicted S-nitrosylation dataset for over- or under-representation (compared to the complete human proteome of pathways and functional elements shows significant statistical over-representation of the blood coagulation pathway. Gene Ontology (GO analysis displays statistically over-represented terms related to muscle contraction, receptor activity, motor activity, cystoskeleton components, and microtubule activity. Through the genomic and proteomic context of SNVs and S-nitrosylation sites presented in this study, researchers can look for variation that can predispose individuals to cardiac arrhythmias. Such attempts to elucidate mechanisms of arrhythmia thereby add yet another useful parameter in predicting susceptibility for cardiac diseases.

Resting alpha activity predicts learning ability in alpha neurofeedback

Directory of Open Access Journals (Sweden)

Wenya eNan

2014-07-01

Full Text Available Individuals differ in their ability to learn how to regulate the alpha activity by neurofeedback. This study aimed to investigate whether the resting alpha activity is related to the learning ability of alpha enhancement in neurofeedback and could be used as a predictor. A total of 25 subjects performed 20 sessions of individualized alpha neurofeedback in order to learn how to enhance activity in the alpha frequency band. The learning ability was assessed by three indices respectively: the training parameter changes between two periods, within a short period and across the whole training time. It was found that the resting alpha amplitude measured before training had significant positive correlations with all learning indices and could be used as a predictor for the learning ability prediction. This finding would help the researchers in not only predicting the training efficacy in individuals but also gaining further insight into the mechanisms of alpha neurofeedback.

Activation of AMP-activated protein kinase in response to temperature elevation shows seasonal variation in the zebra mussel, Dreissena polymorpha.

Science.gov (United States)

Jost, Jennifer A; Keshwani, Sarah S; Abou-Hanna, Jacob J

2015-04-01

Global climate change is affecting ectothermic species, and a variety of studies are needed on thermal tolerances, especially from cellular and physiological perspectives. This study utilized AMP-activated protein kinase (AMPK), a key regulator of cellular energy levels, to examine the effects of high water temperatures on zebra mussel (Dreissena polymorpha) physiology. During heating, AMPK activity increased as water temperature increased to a point, and maximum AMPK activity was detected at high, but sublethal, water temperatures. This pattern varied with season, suggesting that cellular mechanisms of seasonal thermal acclimatization affect basic metabolic processes during sublethal heat stress. There was a greater seasonal variation in the water temperature at which maximum AMPK activity was measured than in lethal water temperature. Furthermore, baseline AMPK activity varied significantly across seasons, most likely reflecting altered metabolic states during times of growth and reproduction. In addition, when summer-collected mussels were lab-acclimated to winter and spring water temperatures, patterns of heat stress mirrored those of field-collected animals. These data suggest that water temperature is the main driver of the seasonal variation in physiology. This study concluded that AMPK activity, which reflects changes in energy supply and demand during heat stress, can serve as a sensitive and early indicator of temperature stress in mussels. Copyright © 2014 Elsevier Inc. All rights reserved.

Genetic Variations Involved in Vitamin E Status

Directory of Open Access Journals (Sweden)

Patrick Borel

2016-12-01

Full Text Available Vitamin E (VE is the generic term for four tocopherols and four tocotrienols that exhibit the biological activity of α-tocopherol. VE status, which is usually estimated by measuring fasting blood VE concentration, is affected by numerous factors, such as dietary VE intake, VE absorption efficiency, and VE catabolism. Several of these factors are in turn modulated by genetic variations in genes encoding proteins involved in these factors. To identify these genetic variations, two strategies have been used: genome-wide association studies and candidate gene association studies. Each of these strategies has its advantages and its drawbacks, nevertheless they have allowed us to identify a list of single nucleotide polymorphisms associated with fasting blood VE concentration and α-tocopherol bioavailability. However, much work remains to be done to identify, and to replicate in different populations, all the single nucleotide polymorphisms involved, to assess the possible involvement of other kind of genetic variations, e.g., copy number variants and epigenetic modifications, in order to establish a reliable list of genetic variations that will allow us to predict the VE status of an individual by knowing their genotype in these genetic variations. Yet, the potential usefulness of this area of research is exciting with regard to personalized nutrition and for future clinical trials dedicated to assessing the biological effects of the various isoforms of VE.

Impulsive approach tendencies towards physical activity and sedentary behaviors, but not reflective intentions, prospectively predict non-exercise activity thermogenesis.

Science.gov (United States)

Cheval, Boris; Sarrazin, Philippe; Pelletier, Luc

2014-01-01

Understanding the determinants of non-exercise activity thermogenesis (NEAT) is crucial, given its extensive health benefits. Some scholars have assumed that a proneness to react differently to environmental cues promoting sedentary versus active behaviors could be responsible for inter-individual differences in NEAT. In line with this reflection and grounded on the Reflective-Impulsive Model, we test the assumption that impulsive processes related to sedentary and physical activity behaviors can prospectively predict NEAT, operationalized as spontaneous effort exerted to maintain low intensity muscle contractions within the release phases of an intermittent maximal isometric contraction task. Participants (n = 91) completed a questionnaire assessing their intentions to adopt physical activity behaviors and a manikin task to assess impulsive approach tendencies towards physical activity behaviors (IAPA) and sedentary behaviors (IASB). Participants were then instructed to perform a maximal handgrip strength task and an intermittent maximal isometric contraction task. As hypothesized, multilevel regression analyses revealed that spontaneous effort was (a) positively predicted by IAPA, (b) negatively predicted by IASB, and (c) was not predicted by physical activity intentions, after controlling for some confounding variables such as age, sex, usual PA level and average force provided during the maximal-contraction phases of the task. These effects remained constant throughout all the phases of the task. This study demonstrated that impulsive processes may play a unique role in predicting spontaneous physical activity behaviors. Theoretically, this finding reinforces the utility of a motivational approach based on dual-process models to explain inter-individual differences in NEAT. Implications for health behavior theories and behavior change interventions are outlined.

The effect of gender on eye colour variation in European populations and an evaluation of the IrisPlex prediction model.

Science.gov (United States)

Pietroni, Carlotta; Andersen, Jeppe D; Johansen, Peter; Andersen, Mikkel M; Harder, Stine; Paulsen, Rasmus; Børsting, Claus; Morling, Niels

2014-07-01

In two recent studies of Spanish individuals, gender was suggested as a factor that contributes to human eye colour variation. However, gender did not improve the predictive accuracy on blue, intermediate and brown eye colours when gender was included in the IrisPlex model. In this study, we investigate the role of gender as a factor that contributes to eye colour variation and suggest that the gender effect on eye colour is population specific. A total of 230 Italian individuals were typed for the six IrisPlex SNPs (rs12913832, rs1800407, rs12896399, rs1393350, rs16891982 and rs12203592). A quantitative eye colour score (Pixel Index of the Eye: PIE-score) was calculated based on digital eye images using the custom made DIAT software. The results were compared with those of Danish and Swedish population samples. As expected, we found HERC2 rs12913832 as the main predictor of human eye colour independently of ancestry. Furthermore, we found gender to be significantly associated with quantitative eye colour measurements in the Italian population sample. We found that the association was statistically significant only among Italian individuals typed as heterozygote GA for HERC2 rs12913832. Interestingly, we did not observe the same association in the Danish and Swedish population. This indicated that the gender effect on eye colour is population specific. We estimated the effect of gender on quantitative eye colour in the Italian population sample to be 4.9%. Among gender and the IrisPlex SNPs, gender ranked as the second most important predictor of human eye colour variation in Italians after HERC2 rs12913832. We, furthermore, tested the five lower ranked IrisPlex predictors, and evaluated all possible 3(6) (729) genotype combinations of the IrisPlex assay and their corresponding predictive values using the IrisPlex prediction model [4]. The results suggested that maximum three (rs12913832, rs1800407, rs16891982) of the six IrisPlex SNPs are useful in practical

Generation of diurnal variation for influent data for dynamic simulation.

Science.gov (United States)

Langergraber, G; Alex, J; Weissenbacher, N; Woerner, D; Ahnert, M; Frehmann, T; Halft, N; Hobus, I; Plattes, M; Spering, V; Winkler, S

2008-01-01

When using dynamic simulation for fine tuning of the design of activated sludge (AS) plants diurnal variations of influent data are required. For this application usually only data from the design process and no measured data are available. In this paper a simple method to generate diurnal variations of wastewater flow and concentrations is described. The aim is to generate realistic influent data in terms of flow, concentrations and TKN/COD ratios and not to predict the influent of the AS plant in detail. The work has been prepared within the framework of HSG-Sim (Hochschulgruppe Simulation, http://www.hsgsim.org), a group of researchers from Germany, Austria, Luxembourg, Poland, the Netherlands and Switzerland. (c) IWA Publishing 2008.

Fuzzy-predictive direct power control implementation of a grid connected photovoltaic system, associated with an active power filter

International Nuclear Information System (INIS)

Ouchen, Sabir; Betka, Achour; Abdeddaim, Sabrina; Menadi, Abdelkrim

2016-01-01

Highlights: • An implementation on dSPACE 1104 of a double stage grid connected photovoltaic system, associated with an active power filter. • A fuzzy logic controller for maximum power point tracking of photovoltaic generator using a boost converter. • Predictive direct power control almost eliminates the effect of harmonics under a unite power factor. • The robustness of control strategies was examined in different irradiance level conditions. - Abstract: The present paper proposes a real time implementation of an optimal operation of a double stage grid connected photovoltaic system, associated with a shunt active power filter. On the photovoltaic side, a fuzzy logic based maximum power point taking control is proposed to track permanently the optimum point through an adequate tuning of a boost converter regardless the solar irradiance variations; whereas, on the grid side, a model predictive direct power control is applied, to ensure both supplying a part of the load demand with the extracted photovoltaic power, and a compensation of undesirable harmonic contents of the grid current, under a unity power factor operation. The implementation of the control strategies is conducted on a small scale photovoltaic system, controlled via a dSPACE 1104 single card. The obtained experimental results show on one hand, that the proposed Fuzzy logic based maximum power taking point technique provides fast and high performances under different irradiance levels while compared with a sliding mode control, and ensures 1.57% more in efficiency. On the other hand, the predictive power control ensures a flexible settlement of active power amounts exchanges with the grid, under a unity power functioning. Furthermore, the grid current presents a sinusoidal shape with a tolerable total harmonic distortion coefficient 4.71%.

Measured and Predicted Variations in Fast Neutron Spectrum when Penetrating Laminated Fe-D2O

International Nuclear Information System (INIS)

Aalto, E.; Sandlin, R.; Fraeki, R.

1965-09-01

Variations of the fast neutron spectrum in thin regions of alternating Fe and D O have been studied using threshold detectors (ln(n, n' ), S(n, p), Al(n, α)). The results have been compared to those calculated by two shielding codes (NRN and RASH D) of multigroup removal-diffusion type. The absolute fast spectrum calculated in our rather complicated configurations was found to agree with measurements within the same accuracy (a factor of two) as did the thermal flux. The calculated spectrum is slightly harder than the measured one, but the detailed variations (covering the range 1:5) in the form of the spectrum when penetrating Fe agree with observations to within 15-20 %. In and Al activities were found to be proportional to the integrated flux over 1 MeV throughout the whole configuration, while S showed the least proportionality

Variations in creatine kinase activity and reactive oxygen species levels are involved in capacitation of bovine spermatozoa.

Science.gov (United States)

Córdoba, M; Pintos, L; Beconi, M T

2008-12-01

The generation of reactive oxygen species (ROS) is associated with some factors such as oxidative substrate sources, mitochondrial function and NAD(P)H oxidase activity. In bovine spermatozoa, heparin capacitation produces a respiratory burst sensitive to diphenyleneiodonium (DPI). Creatine kinase (CK) is related to extramitochondrial ATP disponibility. Our purpose was to determine the variation in ROS level and its relation with NAD(P)H oxidase sensitive to DPI and CK participation, as factors involved in redox state and energy generation in capacitation. The chlortetracycline technique was used to evaluate capacitation. CK activity and ROS level were measured by spectrophotometry and spectrofluorometry respectively. The capacitation percentage was increased by heparin or quercetin treatment (P level as control (238.62 +/- 23.47 arbitrary units per 10(8) spermatozoa) (P > 0.05). CK activity decreased by 50% with heparin or quercetin (P level variations were observed in heparin- or quercetin-treated samples (P bovine spermatozoa, capacitation requires equilibrium between oxidative damage susceptibility and ROS levels. CK activity is associated with redox state variation and energy sources. In conclusion, capacitation induction depends on NADPH oxidase and the shuttle creatine-creatine phosphate, both sensitive to DPI.

Rate of antioxidant degradation and color variations in dehydrated apples as related to water activity.

Science.gov (United States)

Lavelli, Vera; Vantaggi, Claudia

2009-06-10

Dehydrated apples were studied to evaluate the effects of water activity on the stability of their antioxidants and color. Apples were freeze-dried, ground, then equilibrated, and stored at eight water activity levels, ranging from 0.058 to 0.747, at 40 degrees C. Their contents of hydroxycinnamic acids, dihydrochalcones, catechin, epicatechin, polymeric flavan-3-ols, and hydroxymethylfurfural, their antioxidant activity values, and their Hunter colorimetric parameters were analyzed at different storage times. Antioxidant degradation followed pseudo-first-order kinetics and was accelerated by increasing the water activity. The order of antioxidant stability in the products at water activity levels below 0.316 was catechin, epicatechin, and ascorbic acid acid acid; however, in the products at water activity levels above 0.316, the degradation of all antioxidants was very fast. The hydroxymethylfurfural formation rate increased exponentially during storage, especially at high water activity levels. The antioxidant activity of the dehydrated apples decreased during storage, consistent with antioxidant loss. The variations of the colorimetric parameters, namely, lightness (L*), redness (a*), and yellowness (b*), followed pseudo-zero-order kinetics and were accelerated by increasing water activity. All analytical indices indicated that the dehydrated apples were stable at water activity levels below 0.316, with the degradation rate accelerating upon exposure to higher relative humidities. Above 0.316, a small increase in water activity of the product would sharply increase the degradation rate constants for both antioxidant and color variations.

Analysis of longitudinal variations in North Pacific alkalinity to improve predictive algorithms

Science.gov (United States)

Fry, Claudia H.; Tyrrell, Toby; Achterberg, Eric P.

2016-10-01

The causes of natural variation in alkalinity in the North Pacific surface ocean need to be investigated to understand the carbon cycle and to improve predictive algorithms. We used GLODAPv2 to test hypotheses on the causes of three longitudinal phenomena in Alk*, a tracer of calcium carbonate cycling. These phenomena are (a) an increase from east to west between 45°N and 55°N, (b) an increase from west to east between 25°N and 40°N, and (c) a minor increase from west to east in the equatorial upwelling region. Between 45°N and 55°N, Alk* is higher on the western than on the eastern side, and this is associated with denser isopycnals with higher Alk* lying at shallower depths. Between 25°N and 40°N, upwelling along the North American continental shelf causes higher Alk* in the east. Along the equator, a strong east-west trend was not observed, even though the upwelling on the eastern side of the basin is more intense, because the water brought to the surface is not high in Alk*. We created two algorithms to predict alkalinity, one for the entire Pacific Ocean north of 30°S and one for the eastern margin. The Pacific Ocean algorithm is more accurate than the commonly used algorithm published by Lee et al. (2006), of similar accuracy to the best previously published algorithm by Sasse et al. (2013), and is less biased with longitude than other algorithms in the subpolar North Pacific. Our eastern margin algorithm is more accurate than previously published algorithms.

Prediction signatures in the brain: Semantic pre-activation during language comprehension

Directory of Open Access Journals (Sweden)

Burkhard Maess

2016-11-01

Full Text Available There is broad agreement that context-based predictions facilitate lexical-semantic processing. A robust index of semantic prediction during language comprehension is an evoked response, known as the N400, whose amplitude is modulated as a function of semantic context. However, the underlying neural mechanisms that utilize relations of the prior context and the embedded word within it are largely unknown. We measured magnetoencephalography (MEG data while participants were listening to simple German sentences in which the verbs were either highly predictive for the occurrence of a particular noun (i.e., provided context or not. The identical set of nouns was presented in both conditions. Hence, differences for the evoked responses of the nouns can only be due to differences in the earlier context. We observed a reduction of the N400 response for highly predicted nouns. Interestingly, the opposite pattern was observed for the preceding verbs: Highly predictive (that is more informative verbs yielded stronger neural magnitude compared to less predictive verbs. A negative correlation between the N400 effect of the verb and that of the noun was found in a distributed brain network, indicating an integral relation between the predictive power of the verb and the processing of the subsequent noun. This network consisted of left hemispheric superior and middle temporal areas and a subcortical area; the parahippocampus. Enhanced activity for highly predictive relative to less predictive verbs, likely reflects establishing semantic features associated with the expected nouns, that is a pre-activation of the expected nouns.

Impulsive approach tendencies towards physical activity and sedentary behaviors, but not reflective intentions, prospectively predict non-exercise activity thermogenesis.

Directory of Open Access Journals (Sweden)

Boris Cheval

Full Text Available Understanding the determinants of non-exercise activity thermogenesis (NEAT is crucial, given its extensive health benefits. Some scholars have assumed that a proneness to react differently to environmental cues promoting sedentary versus active behaviors could be responsible for inter-individual differences in NEAT. In line with this reflection and grounded on the Reflective-Impulsive Model, we test the assumption that impulsive processes related to sedentary and physical activity behaviors can prospectively predict NEAT, operationalized as spontaneous effort exerted to maintain low intensity muscle contractions within the release phases of an intermittent maximal isometric contraction task. Participants (n = 91 completed a questionnaire assessing their intentions to adopt physical activity behaviors and a manikin task to assess impulsive approach tendencies towards physical activity behaviors (IAPA and sedentary behaviors (IASB. Participants were then instructed to perform a maximal handgrip strength task and an intermittent maximal isometric contraction task. As hypothesized, multilevel regression analyses revealed that spontaneous effort was (a positively predicted by IAPA, (b negatively predicted by IASB, and (c was not predicted by physical activity intentions, after controlling for some confounding variables such as age, sex, usual PA level and average force provided during the maximal-contraction phases of the task. These effects remained constant throughout all the phases of the task. This study demonstrated that impulsive processes may play a unique role in predicting spontaneous physical activity behaviors. Theoretically, this finding reinforces the utility of a motivational approach based on dual-process models to explain inter-individual differences in NEAT. Implications for health behavior theories and behavior change interventions are outlined.

VARIATIONS IN ELECTROPHYSICAL PARAMETERS ESTIMATED FROM ELECTROMAGNETIC MONITORING DATA AS AN INDICATOR OF FAULT ACTIVITY

Directory of Open Access Journals (Sweden)

A. E. Shalaginov

2018-01-01

Full Text Available In the regions of high seismic activity, investigations of fault zones are of paramount importance as such zones can generate seismicity. A top task in the regional studies is determining the rates of activity from the data obtained by geoelectrical methods, especially considering the data on the faults covered by sediments. From a practical standpoint, the results of these studies are important for seismic zoning and forecasting of natural and anthropogenic geodynamic phenomena that may potentially occur in the populated areas and zones allocated for construction of industrial and civil objects, pipelines, roads, bridges, etc. Seismic activity in Gorny Altai is regularly monitored after the destructive 2003 Chuya earthquake (M=7.3 by the non-stationary electromagnetic sounding with galvanic and inductive sources of three modifications. From the long-term measurements that started in 2007 and continue in the present, electrical resistivity and electrical anisotropy are determined. Our study aimed to estimate the variations of these electrophysical parameters in the zone influenced by the fault, consider the intensity of the variations in comparison with seismicity indicators, and attempt at determining the degree of activity of the faults. Based on the results of our research, we propose a technique for measuring and interpreting the data sets obtained by a complex of non-stationary sounding modifications. The technique ensures a more precise evaluation of the electrophysical parameters. It is concluded that the electric anisotropy coefficient can be effectively used to characterize the current seismicity, and its maximum variations, being observed in the zone influenced by the fault, are characteristic of the fault activity. The use of two electrophysical parameters enhances the informativeness of the study.

Variational predictions of transition energies and electron affinities: He and Li ground states and Li, Be, and Mg core-excited states

International Nuclear Information System (INIS)

Fischer, C.F.

1990-01-01

Variational procedures for predicting energy differences of many-electron systems are investigated. Several different calculations for few-electron systems are considered that illustrate the problems encountered when a many-electron system is modeled as a core plus outer electrons. It is shown that sequences of increasingly more accurate calculations for outer correlation may converge yielding wrong transition energies. At the same time, accurate core-polarization calculations overestimate the binding energy, requiring a core-valence correction. For the high-spin, core-excited states of Li, it was found that outer correlation only predicted electron affinities as accurately as full-correlation studies. This observation suggested a prediction of the core-excited 4 P endash 4 S transition in Be - , based on observed 3 P 0 endash 3 P transition energies of the neutral species, predicted electron affinities including only outer correlation, and a core-valence correction, that is shown to be in good agreement with experiment. A similar calculation for Mg - predicts a wavelength of 2895.1 A for this transition

Predictive modeling and reducing cyclic variability in autoignition engines

Science.gov (United States)

Hellstrom, Erik; Stefanopoulou, Anna; Jiang, Li; Larimore, Jacob

2016-08-30

Methods and systems are provided for controlling a vehicle engine to reduce cycle-to-cycle combustion variation. A predictive model is applied to predict cycle-to-cycle combustion behavior of an engine based on observed engine performance variables. Conditions are identified, based on the predicted cycle-to-cycle combustion behavior, that indicate high cycle-to-cycle combustion variation. Corrective measures are then applied to prevent the predicted high cycle-to-cycle combustion variation.

Seasonal Variation, Chemical Composition and Antioxidant Activity of Brazilian Propolis Samples

Directory of Open Access Journals (Sweden)

Érica Weinstein Teixeira

2010-01-01

Full Text Available Total phenolic contents, antioxidant activity and chemical composition of propolis samples from three localities of Minas Gerais state (southeast Brazil were determined. Total phenolic contents were determined by the Folin–Ciocalteau method, antioxidant activity was evaluated by DPPH, using BHT as reference, and chemical composition was analyzed by GC/MS. Propolis from Itapecerica and Paula Cândido municipalities were found to have high phenolic contents and pronounced antioxidant activity. From these extracts, 40 substances were identified, among them were simple phenylpropanoids, prenylated phenylpropanoids, sesqui- and diterpenoids. Quantitatively, the main constituent of both samples was allyl-3-prenylcinnamic acid. A sample from Virginópolis municipality had no detectable phenolic substances and contained mainly triterpenoids, the main constituents being α- and β-amyrins. Methanolic extracts from Itapecerica and Paula Cândido exhibited pronounced scavenging activity towards DPPH, indistinguishable from BHT activity. However, extracts from Virginópolis sample exhibited no antioxidant activity. Total phenolic substances, GC/MS analyses and antioxidant activity of samples from Itapecerica collected monthly over a period of 1 year revealed considerable variation. No correlation was observed between antioxidant activity and either total phenolic contents or contents of artepillin C and other phenolic substances, as assayed by CG/MS analysis.

Topology of membrane proteins-predictions, limitations and variations.

Science.gov (United States)

Tsirigos, Konstantinos D; Govindarajan, Sudha; Bassot, Claudio; Västermark, Åke; Lamb, John; Shu, Nanjiang; Elofsson, Arne

2017-10-26

Transmembrane proteins perform a variety of important biological functions necessary for the survival and growth of the cells. Membrane proteins are built up by transmembrane segments that span the lipid bilayer. The segments can either be in the form of hydrophobic alpha-helices or beta-sheets which create a barrel. A fundamental aspect of the structure of transmembrane proteins is the membrane topology, that is, the number of transmembrane segments, their position in the protein sequence and their orientation in the membrane. Along these lines, many predictive algorithms for the prediction of the topology of alpha-helical and beta-barrel transmembrane proteins exist. The newest algorithms obtain an accuracy close to 80% both for alpha-helical and beta-barrel transmembrane proteins. However, lately it has been shown that the simplified picture presented when describing a protein family by its topology is limited. To demonstrate this, we highlight examples where the topology is either not conserved in a protein superfamily or where the structure cannot be described solely by the topology of a protein. The prediction of these non-standard features from sequence alone was not successful until the recent revolutionary progress in 3D-structure prediction of proteins. Copyright © 2017 Elsevier Ltd. All rights reserved.

Copy number variation of human AMY1 is a minor contributor to variation in salivary amylase expression and activity.

Science.gov (United States)

Carpenter, Danielle; Mitchell, Laura M; Armour, John A L

2017-02-20

Salivary amylase in humans is encoded by the copy variable gene AMY1 in the amylase gene cluster on chromosome 1. Although the role of salivary amylase is well established, the consequences of the copy number variation (CNV) at AMY1 on salivary amylase protein production are less well understood. The amylase gene cluster is highly structured with a fundamental difference between odd and even AMY1 copy number haplotypes. In this study, we aimed to explore, in samples from 119 unrelated individuals, not only the effects of AMY1 CNV on salivary amylase protein expression and amylase enzyme activity but also whether there is any evidence for underlying difference between the common haplotypes containing odd numbers of AMY1 and even copy number haplotypes. AMY1 copy number was significantly correlated with the variation observed in salivary amylase production (11.7% of variance, P structure may affect expression, but this was not significant in our data.

Variation effect on the insecticide activity of DDT analogues. A chemometric approach

Science.gov (United States)

Itoh, S.; Nagashima, U.

2002-08-01

We investigated a variation effect on the insecticide activity of DDT analogues by using the first principles electronic structure calculations and the neural network analysis. It has been found that the charge distribution at the specific atomic sites in the DDT molecule is related to their toxicity. This approach can contribute to designing a new insecticide and a new harmlessness process of the DDT analogues.

Global Distribution and Variations of NO Infrared Radiative Flux and Its Responses to Solar Activity and Geomagnetic Activity in the Thermosphere

Science.gov (United States)

Tang, Chaoli; Wei, Yuanyuan; Liu, Dong; Luo, Tao; Dai, Congming; Wei, Heli

2017-12-01

The global distribution and variations of NO infrared radiative flux (NO-IRF) are presented during 2002-2016 in the thermosphere covering 100-280 km altitude based on Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) data set. For investigating the spatial variations of the mutual relationship between NO-IRF and solar activity, the altitude ranges from 100 km to 280 km are divided into 90 altitude bins, and the latitude regions of 83°S-83°N are divided into 16 latitude bins. By processing about 1.8E9 NO-IRF observation values from about 5E6 vertical nighttime profiles recorded in SABER data set, we obtained more than 4.1E8 samples of NO-IRF. The annual-mean values of NO-IRF are then calculated by all available NO-IRF samples within each latitude and altitude bin. Local latitudinal maxima in NO-IRF are found between 120 and 145 km altitude, and the maximum NO-IRF located at polar regions are 3 times more than that of the minimum at equatorial region. The influences of solar and geomagnetic activity on the spatial variations of NO-IRF are investigated. Both the NO-IRF and its response to solar and geomagnetic activity show nearly symmetric distribution between the two hemispheres. It is demonstrated that the observed changes in NO-IRF at altitudes between 100 and 225 km correlate well with the changes in solar activity. The NO-IRF at solar maximum is about 4 times than that at solar minimum, and the current maximum of NO-IRF in 2014 is less than 70% of the prior maximum in 2001. For the first time, the response ranges of the NO-IRF to solar and geomagnetic activity at different altitudes and latitudes are reported.

Fiscal 1997 report on the verification survey of geothermal exploration technology. 5-1. Development of the reservoir variation survey method (technology of prediction of reservoir variation); 1997 nendo chinetsu tansa gijutsu nado kensho chosa. Choryuso hendo tansaho kaihatsu (choryuso hendo yosoku gijutsu) hokokusho

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-03-01

For the reservoir evaluation at an initial developmental stage and stabilization/maintenance of power after the start of operation, the fiscal 1997 result was described of the study of technology of prediction of reservoir variation. Using the conventional post processor, feasibilities were computed of reservoir models and behavior after the development, and gravity/self potential/resistivity variation. Variation in the seismic wave speed structure was large in travel time change distribution. The measuring accuracy of 1m sec is required to get enough detection resolving power. A conceptual design of the post processor development was conducted to study a system operated on Windows. Based on the reservoir numerical simulation technology, by taking in variation parameters such as gravity and self potentials as new model constraint conditions, the reservoir modeling technology which increased in accuracy by history matching was trially developed. Using the conventional reservoir model in the Oguni area, predictably computed were reservoir behaviors during 50 years which simulated a 20 MW development. Effectiveness of the post processor were able to be shown though influenced by characteristics such as permeability and resistivity. 74 refs., 95 refs., 12 tabs.

A rapid method of predicting radiocaesium concentrations in sheep from activity levels in faeces

International Nuclear Information System (INIS)

McGee, E.J.; Synnott, H.J.; Colgan, P.A.; Keatinge, M.J.

1994-01-01

The use of faecal samples taken from sheep flocks as a means of predicting radiocaesium concentrations in live animals was studied. Radiocaesium levels in 1726 sheep from 29 flocks were measured using in vivo techniques and a single faecal sample taken from each flock was also analysed. A highly significant relationship was found to exist between mean flock activity and activity in the corresponding faecal samples. Least-square regression yielded a simple model for predicting mean flock radiocaesium concentrations based on activity levels in faecal samples. A similar analysis of flock maxima and activity levels in faeces provides an alternative model for predicting the expected within-flock maximum radiocaesium concentration. (Author)

Predicting global variation in infectious disease severity

DEFF Research Database (Denmark)

Jensen, Per Moestrup; de Fine Licht, Henrik Hjarvard

2016-01-01

demographic and population data. Results: Birth rates were the best predictor for mumps and malaria CFR. For tuberculosis CFR death rates were the best predictor and for leptospirosis population density was a significant predictor. Conclusions and implications: CFR predictors differed among diseases according...... and leptospirosis and assessed these for association with a range of population characteristics, such as crude birth and death rates, median age of the population, mean body mass index, proportion living in urban areas and tuberculosis vaccine coverage. We then tested this predictive model on Danish his- torical...... have the opposite effect. Accordingly changes in CFR may occur in parallel with demographic transitions. Methodology: We explored the predictability of CFR using data obtained from the World Health Organization (WHO) disease databases for four human diseases: mumps, malaria, tuberculosis...

Application of Artificial Intelligence to the Prediction of the Antimicrobial Activity of Essential Oils.

Science.gov (United States)

Daynac, Mathieu; Cortes-Cabrera, Alvaro; Prieto, Jose M

2015-01-01

Essential oils (EOs) are vastly used as natural antibiotics in Complementary and Alternative Medicine (CAM). Their intrinsic chemical variability and synergisms/antagonisms between its components make difficult to ensure consistent effects through different batches. Our aim is to evaluate the use of artificial neural networks (ANNs) for the prediction of their antimicrobial activity. Methods. The chemical composition and antimicrobial activity of 49 EOs, extracts, and/or fractions was extracted from NCCLS compliant works. The fast artificial neural networks (FANN) software was used and the output data reflected the antimicrobial activity of these EOs against four common pathogens: Staphylococcus aureus, Escherichia coli, Candida albicans, and Clostridium perfringens as measured by standardised disk diffusion assays. Results. ANNs were able to predict >70% of the antimicrobial activities within a 10 mm maximum error range. Similarly, ANNs were able to predict 2 or 3 different bioactivities at the same time. The accuracy of the prediction was only limited by the inherent errors of the popular antimicrobial disk susceptibility test and the nature of the pathogens. Conclusions. ANNs can be reliable, fast, and cheap tools for the prediction of the antimicrobial activity of EOs thus improving their use in CAM.

Variations of starting conditions contribution to cooling tower plume predictions; Uticaj promene polaznih uslova na predvidjanje rasprostiranja perjanica rashladnih tornjeva nuklearne elektrane

Energy Technology Data Exchange (ETDEWEB)

Vehauc, A; Zaric, Z [Boris Kidric Institute of nuclear sciences, Vinca, Belgrade (Yugoslavia)

1977-07-01

The paper deals with quantitative contribution of variations of starting conditions to cooling tower plume predictions. The starting conditions are: plume velocity and temperature and concentration of water drops in the plume at the cooling tower outlet. For the same thermal discharge and meteorological conditions, starting conditions are given by characteristics of cooling towers. (author)

On the Relationship between Variational Level Set-Based and SOM-Based Active Contours

Science.gov (United States)

Abdelsamea, Mohammed M.; Gnecco, Giorgio; Gaber, Mohamed Medhat; Elyan, Eyad

2015-01-01

Most Active Contour Models (ACMs) deal with the image segmentation problem as a functional optimization problem, as they work on dividing an image into several regions by optimizing a suitable functional. Among ACMs, variational level set methods have been used to build an active contour with the aim of modeling arbitrarily complex shapes. Moreover, they can handle also topological changes of the contours. Self-Organizing Maps (SOMs) have attracted the attention of many computer vision scientists, particularly in modeling an active contour based on the idea of utilizing the prototypes (weights) of a SOM to control the evolution of the contour. SOM-based models have been proposed in general with the aim of exploiting the specific ability of SOMs to learn the edge-map information via their topology preservation property and overcoming some drawbacks of other ACMs, such as trapping into local minima of the image energy functional to be minimized in such models. In this survey, we illustrate the main concepts of variational level set-based ACMs, SOM-based ACMs, and their relationship and review in a comprehensive fashion the development of their state-of-the-art models from a machine learning perspective, with a focus on their strengths and weaknesses. PMID:25960736

Predictable variation of range-sizes across an extreme environmental gradient in a lizard adaptive radiation: evolutionary and ecological inferences.

Directory of Open Access Journals (Sweden)

Daniel Pincheira-Donoso

Full Text Available Large-scale patterns of current species geographic range-size variation reflect historical dynamics of dispersal and provide insights into future consequences under changing environments. Evidence suggests that climate warming exerts major damage on high latitude and elevation organisms, where changes are more severe and available space to disperse tracking historical niches is more limited. Species with longer generations (slower adaptive responses, such as vertebrates, and with restricted distributions (lower genetic diversity, higher inbreeding in these environments are expected to be particularly threatened by warming crises. However, a well-known macroecological generalization (Rapoport's rule predicts that species range-sizes increase with increasing latitude-elevation, thus counterbalancing the impact of climate change. Here, I investigate geographic range-size variation across an extreme environmental gradient and as a function of body size, in the prominent Liolaemus lizard adaptive radiation. Conventional and phylogenetic analyses revealed that latitudinal (but not elevational ranges significantly decrease with increasing latitude-elevation, while body size was unrelated to range-size. Evolutionarily, these results are insightful as they suggest a link between spatial environmental gradients and range-size evolution. However, ecologically, these results suggest that Liolaemus might be increasingly threatened if, as predicted by theory, ranges retract and contract continuously under persisting climate warming, potentially increasing extinction risks at high latitudes and elevations.

Predictive value of pulse pressure variation for fluid responsiveness in septic patients using lung-protective ventilation strategies.

Science.gov (United States)

Freitas, F G R; Bafi, A T; Nascente, A P M; Assunção, M; Mazza, B; Azevedo, L C P; Machado, F R

2013-03-01

The applicability of pulse pressure variation (ΔPP) to predict fluid responsiveness using lung-protective ventilation strategies is uncertain in clinical practice. We designed this study to evaluate the accuracy of this parameter in predicting the fluid responsiveness of septic patients ventilated with low tidal volumes (TV) (6 ml kg(-1)). Forty patients after the resuscitation phase of severe sepsis and septic shock who were mechanically ventilated with 6 ml kg(-1) were included. The ΔPP was obtained automatically at baseline and after a standardized fluid challenge (7 ml kg(-1)). Patients whose cardiac output increased by more than 15% were considered fluid responders. The predictive values of ΔPP and static variables [right atrial pressure (RAP) and pulmonary artery occlusion pressure (PAOP)] were evaluated through a receiver operating characteristic (ROC) curve analysis. Thirty-four patients had characteristics consistent with acute lung injury or acute respiratory distress syndrome and were ventilated with high levels of PEEP [median (inter-quartile range) 10.0 (10.0-13.5)]. Nineteen patients were considered fluid responders. The RAP and PAOP significantly increased, and ΔPP significantly decreased after volume expansion. The ΔPP performance [ROC curve area: 0.91 (0.82-1.0)] was better than that of the RAP [ROC curve area: 0.73 (0.59-0.90)] and pulmonary artery occlusion pressure [ROC curve area: 0.58 (0.40-0.76)]. The ROC curve analysis revealed that the best cut-off for ΔPP was 6.5%, with a sensitivity of 0.89, specificity of 0.90, positive predictive value of 0.89, and negative predictive value of 0.90. Automatized ΔPP accurately predicted fluid responsiveness in septic patients ventilated with low TV.

Neural activity to a partner's facial expression predicts self-regulation after conflict

Science.gov (United States)

Hooker, Christine I.; Gyurak, Anett; Verosky, Sara; Miyakawa, Asako; Ayduk, Özlem

2009-01-01

Introduction Failure to self-regulate after an interpersonal conflict can result in persistent negative mood and maladaptive behaviors. Research indicates that lateral prefrontal cortex (LPFC) activity is related to the regulation of emotional experience in response to lab-based affective challenges, such as viewing emotional pictures. This suggests that compromised LPFC function may be a risk-factor for mood and behavior problems after an interpersonal stressor. However, it remains unclear whether LPFC activity to a lab-based affective challenge predicts self-regulation in real-life. Method We investigated whether LPFC activity to a lab-based affective challenge (negative facial expressions of a partner) predicts self-regulation after a real-life affective challenge (interpersonal conflict). During an fMRI scan, healthy, adult participants in committed, dating relationships (N = 27) viewed positive, negative, and neutral facial expressions of their partners. In an online daily-diary, participants reported conflict occurrence, level of negative mood, rumination, and substance-use. Results LPFC activity in response to the lab-based affective challenge predicted self-regulation after an interpersonal conflict in daily life. When there was no interpersonal conflict, LPFC activity was not related to the change in mood or behavior the next day. However, when an interpersonal conflict did occur, ventral LPFC (VLPFC) activity predicted the change in mood and behavior the next day, such that lower VLPFC activity was related to higher levels of negative mood, rumination, and substance-use. Conclusions Low LPFC function may be a vulnerability and high LPFC function may be a protective factor for the development of mood and behavior problems after an interpersonal stressor. PMID:20004365

Neural activity to a partner's facial expression predicts self-regulation after conflict.

Science.gov (United States)

Hooker, Christine I; Gyurak, Anett; Verosky, Sara C; Miyakawa, Asako; Ayduk, Ozlem

2010-03-01

Failure to self-regulate after an interpersonal conflict can result in persistent negative mood and maladaptive behaviors. Research indicates that lateral prefrontal cortex (LPFC) activity is related to emotion regulation in response to laboratory-based affective challenges, such as viewing emotional pictures. This suggests that compromised LPFC function may be a risk factor for mood and behavior problems after an interpersonal conflict. However, it remains unclear whether LPFC activity to a laboratory-based affective challenge predicts self-regulation in real life. We investigated whether LPFC activity to a laboratory-based affective challenge (negative facial expressions of a partner) predicts self-regulation after a real-life affective challenge (interpersonal conflict). During a functional magnetic resonance imaging scan, healthy, adult participants in committed relationships (n = 27) viewed positive, negative, and neutral facial expressions of their partners. In a three-week online daily diary, participants reported conflict occurrence, level of negative mood, rumination, and substance use. LPFC activity in response to the laboratory-based affective challenge predicted self-regulation after an interpersonal conflict in daily life. When there was no interpersonal conflict, LPFC activity was not related to mood or behavior the next day. However, when an interpersonal conflict did occur, ventral LPFC (VLPFC) activity predicted mood and behavior the next day, such that lower VLPFC activity was related to higher levels of negative mood, rumination, and substance use. Low LPFC function may be a vulnerability and high LPFC function may be a protective factor for the development of mood and behavior problems after an interpersonal stressor. Copyright 2010 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Temporal variations in microbial biomass C and cellulolytic enzyme activity in arable soils: effects of organic matter input

DEFF Research Database (Denmark)

Debosz, K.; Rasmussen, Peter Have; Pedersen, A. R.

1999-01-01

Temporal variations in soil microbial biomass C concentration and in activity of extracellular enzymes of the cellulolytic complex were investigated in a field experiment after eight years of cultivation with either low organic matter input (low-OM) or high organic matter input (high-OM). The cul......Temporal variations in soil microbial biomass C concentration and in activity of extracellular enzymes of the cellulolytic complex were investigated in a field experiment after eight years of cultivation with either low organic matter input (low-OM) or high organic matter input (high......-OM). The cultivation systems differed in whether their source of fertiliser was mainly mineral or organic, in whether a winter cover crop was grown, and whether straw was mulched or removed. Sampling occurred at approximately monthly intervals, over a period of two years. Distinct temporal variations in microbial......) and an endocellulase activity of 44.2 +/- 1.1 nmol g(-1) h(-1). (C) 1999 Elsevier Science B.V. All rights reserved....

A Local Stable Bootstrap for Power Variations of Pure-Jump Semimartingales and Activity Index Estimation

DEFF Research Database (Denmark)

Hounyo, Ulrich; Varneskov, Rasmus T.

We provide a new resampling procedure - the local stable bootstrap - that is able to mimic the dependence properties of realized power variations for pure-jump semimartingales observed at different frequencies. This allows us to propose a bootstrap estimator and inference procedure for the activity...... index of the underlying process, β, as well as a bootstrap test for whether it obeys a jump-diffusion or a pure-jump process, that is, of the null hypothesis H₀: β=2 against the alternative H₁: βbootstrap power variations, activity index...... estimator, and diffusion test for H0. Moreover, the finite sample size and power properties of the proposed diffusion test are compared to those of benchmark tests using Monte Carlo simulations. Unlike existing procedures, our bootstrap test is correctly sized in general settings. Finally, we illustrate use...

Active diagnosis of hybrid systems - A model predictive approach

DEFF Research Database (Denmark)

Tabatabaeipour, Seyed Mojtaba; Ravn, Anders P.; Izadi-Zamanabadi, Roozbeh

2009-01-01

A method for active diagnosis of hybrid systems is proposed. The main idea is to predict the future output of both normal and faulty model of the system; then at each time step an optimization problem is solved with the objective of maximizing the difference between the predicted normal and fault...... can be used as a test signal for sanity check at the commissioning or for detection of faults hidden by regulatory actions of the controller. The method is tested on the two tank benchmark example. ©2009 IEEE....

The role of ecosystem memory in predicting inter-annual variations of the tropical carbon balance.

Science.gov (United States)

Bloom, A. A.; Liu, J.; Bowman, K. W.; Konings, A. G.; Saatchi, S.; Worden, J. R.; Worden, H. M.; Jiang, Z.; Parazoo, N.; Williams, M. D.; Schimel, D.

2017-12-01

Understanding the trajectory of the tropical carbon balance remains challenging, in part due to large uncertainties in the integrated response of carbon cycle processes to climate variability. Satellite observations atmospheric CO2 from GOSAT and OCO-2, together with ancillary satellite measurements, provide crucial constraints on continental-scale terrestrial carbon fluxes. However, an integrated understanding of both climate forcings and legacy effects (or "ecosystem memory") on the terrestrial carbon balance is ultimately needed to reduce uncertainty on its future trajectory. Here we use the CARbon DAta-MOdel fraMework (CARDAMOM) diagnostic model-data fusion approach - constrained by an array of C cycle satellite surface observations, including MODIS leaf area, biomass, GOSAT solar-induced fluorescence, as well as "top-down" atmospheric inversion estimates of CO2 and CO surface fluxes from the NASA Carbon Monitoring System Flux (CMS-Flux) - to constrain and predict spatially-explicit tropical carbon state variables during 2010-2015. We find that the combined assimilation of land surface and atmospheric datasets places key constraints on the temperature sensitivity and first order carbon-water feedbacks throughout the tropics and combustion factors within biomass burning regions. By varying the duration of the assimilation period, we find that the prediction skill on inter-annual net biospheric exchange is primarily limited by record length rather than model structure and process representation. We show that across all tropical biomes, quantitative knowledge of memory effects - which account for 30-50% of interannual variations across the tropics - is critical for understanding and ultimately predicting the inter-annual tropical carbon balance.

Latitudinal variation of the topside electron temperature at different levels of solar activity

Czech Academy of Sciences Publication Activity Database

Truhlík, Vladimír; Bilitza, D.; Třísková, Ludmila

2009-01-01

Roč. 44, č. 6 (2009), s. 693-700 ISSN 0273-1177 R&D Projects: GA AV ČR IAA300420603 Grant - others: NASA (US) NNH06CD17C Institutional research plan: CEZ:AV0Z30420517 Keywords : Electron temperature * Solar activity variation * Latitudinal dependence Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.079, year: 2009

Leaf nitrogen from first principles: field evidence for adaptive variation with climate

Science.gov (United States)

Dong, Ning; Prentice, Iain Colin; Evans, Bradley J.; Caddy-Retalic, Stefan; Lowe, Andrew J.; Wright, Ian J.

2017-01-01

Nitrogen content per unit leaf area (Narea) is a key variable in plant functional ecology and biogeochemistry. Narea comprises a structural component, which scales with leaf mass per area (LMA), and a metabolic component, which scales with Rubisco capacity. The co-ordination hypothesis, as implemented in LPJ and related global vegetation models, predicts that Rubisco capacity should be directly proportional to irradiance but should decrease with increases in ci : ca and temperature because the amount of Rubisco required to achieve a given assimilation rate declines with increases in both. We tested these predictions using LMA, leaf δ13C, and leaf N measurements on complete species assemblages sampled at sites on a north-south transect from tropical to temperate Australia. Partial effects of mean canopy irradiance, mean annual temperature, and ci : ca (from δ13C) on Narea were all significant and their directions and magnitudes were in line with predictions. Over 80 % of the variance in community-mean (ln) Narea was accounted for by these predictors plus LMA. Moreover, Narea could be decomposed into two components, one proportional to LMA (slightly steeper in N-fixers), and the other to Rubisco capacity as predicted by the co-ordination hypothesis. Trait gradient analysis revealed ci : ca to be perfectly plastic, while species turnover contributed about half the variation in LMA and Narea. Interest has surged in methods to predict continuous leaf-trait variation from environmental factors, in order to improve ecosystem models. Coupled carbon-nitrogen models require a method to predict Narea that is more realistic than the widespread assumptions that Narea is proportional to photosynthetic capacity, and/or that Narea (and photosynthetic capacity) are determined by N supply from the soil. Our results indicate that Narea has a useful degree of predictability, from a combination of LMA and ci : ca - themselves in part environmentally determined - with Rubisco activity

Variation in predicted internal concentrations in relation to PBPK model complexity for rainbow trout

Energy Technology Data Exchange (ETDEWEB)

Salmina, E.S.; Wondrousch, D. [UFZ Department of Ecological Chemistry, Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig (Germany); Institute for Organic Chemistry, Technical University Bergakademie Freiberg, Leipziger Str. 29, 09596 Freiberg (Germany); Kühne, R. [UFZ Department of Ecological Chemistry, Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig (Germany); Potemkin, V.A. [Department of Chemistry, South Ural State Medical University, Vorovskogo 64, 454048, Chelyabinsk (Russian Federation); Schüürmann, G. [UFZ Department of Ecological Chemistry, Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig (Germany); Institute for Organic Chemistry, Technical University Bergakademie Freiberg, Leipziger Str. 29, 09596 Freiberg (Germany)

2016-04-15

The present study is motivated by the increasing demand to consider internal partitioning into tissues instead of exposure concentrations for the environmental toxicity assessment. To this end, physiologically based pharmacokinetic (PBPK) models can be applied. We evaluated the variation in accuracy of PBPK model outcomes depending on tissue constituents modeled as sorptive phases and chemical distribution tendencies addressed by molecular descriptors. The model performance was examined using data from 150 experiments for 28 chemicals collected from US EPA databases. The simplest PBPK model is based on the “K{sub ow}-lipid content” approach as being traditional for environmental toxicology. The most elaborated one considers five biological sorptive phases (polar and non-polar lipids, water, albumin and the remaining proteins) and makes use of LSER (linear solvation energy relationship) parameters to describe the compound partitioning behavior. The “K{sub ow}-lipid content”-based PBPK model shows more than one order of magnitude difference in predicted and measured values for 37% of the studied exposure experiments while for the most elaborated model this happens only for 7%. It is shown that further improvements could be achieved by introducing corrections for metabolic biotransformation and compound transmission hindrance through a cellular membrane. The analysis of the interface distribution tendencies shows that polar tissue constituents, namely water, polar lipids and proteins, play an important role in the accumulation behavior of polar compounds with H-bond donating functional groups. For compounds without H-bond donating fragments preferable accumulation phases are storage lipids and water depending on compound polarity. - Highlights: • For reliable predictions, models of a certain complexity should be compared. • For reliable predictions non-lipid fish tissue constituents should be considered. • H-donor compounds preferably accumulate in water

Variation in predicted internal concentrations in relation to PBPK model complexity for rainbow trout

International Nuclear Information System (INIS)

Salmina, E.S.; Wondrousch, D.; Kühne, R.; Potemkin, V.A.; Schüürmann, G.

2016-01-01

The present study is motivated by the increasing demand to consider internal partitioning into tissues instead of exposure concentrations for the environmental toxicity assessment. To this end, physiologically based pharmacokinetic (PBPK) models can be applied. We evaluated the variation in accuracy of PBPK model outcomes depending on tissue constituents modeled as sorptive phases and chemical distribution tendencies addressed by molecular descriptors. The model performance was examined using data from 150 experiments for 28 chemicals collected from US EPA databases. The simplest PBPK model is based on the “K_o_w-lipid content” approach as being traditional for environmental toxicology. The most elaborated one considers five biological sorptive phases (polar and non-polar lipids, water, albumin and the remaining proteins) and makes use of LSER (linear solvation energy relationship) parameters to describe the compound partitioning behavior. The “K_o_w-lipid content”-based PBPK model shows more than one order of magnitude difference in predicted and measured values for 37% of the studied exposure experiments while for the most elaborated model this happens only for 7%. It is shown that further improvements could be achieved by introducing corrections for metabolic biotransformation and compound transmission hindrance through a cellular membrane. The analysis of the interface distribution tendencies shows that polar tissue constituents, namely water, polar lipids and proteins, play an important role in the accumulation behavior of polar compounds with H-bond donating functional groups. For compounds without H-bond donating fragments preferable accumulation phases are storage lipids and water depending on compound polarity. - Highlights: • For reliable predictions, models of a certain complexity should be compared. • For reliable predictions non-lipid fish tissue constituents should be considered. • H-donor compounds preferably accumulate in water, polar

Prediction of Active Site and Distal Residues in E. coli DNA Polymerase III alpha Polymerase Activity.

Science.gov (United States)

Parasuram, Ramya; Coulther, Timothy A; Hollander, Judith M; Keston-Smith, Elise; Ondrechen, Mary Jo; Beuning, Penny J

2018-02-20

The process of DNA replication is carried out with high efficiency and accuracy by DNA polymerases. The replicative polymerase in E. coli is DNA Pol III, which is a complex of 10 different subunits that coordinates simultaneous replication on the leading and lagging strands. The 1160-residue Pol III alpha subunit is responsible for the polymerase activity and copies DNA accurately, making one error per 10 5 nucleotide incorporations. The goal of this research is to determine the residues that contribute to the activity of the polymerase subunit. Homology modeling and the computational methods of THEMATICS and POOL were used to predict functionally important amino acid residues through their computed chemical properties. Site-directed mutagenesis and biochemical assays were used to validate these predictions. Primer extension, steady-state single-nucleotide incorporation kinetics, and thermal denaturation assays were performed to understand the contribution of these residues to the function of the polymerase. This work shows that the top 15 residues predicted by POOL, a set that includes the three previously known catalytic aspartate residues, seven remote residues, plus five previously unexplored first-layer residues, are important for function. Six previously unidentified residues, R362, D405, K553, Y686, E688, and H760, are each essential to Pol III activity; three additional residues, Y340, R390, and K758, play important roles in activity.

Predicting flow at work: investigating the activities and job characteristics that predict flow states at work.

Science.gov (United States)

Nielsen, Karina; Cleal, Bryan

2010-04-01

Flow (a state of consciousness where people become totally immersed in an activity and enjoy it intensely) has been identified as a desirable state with positive effects for employee well-being and innovation at work. Flow has been studied using both questionnaires and Experience Sampling Method (ESM). In this study, we used a newly developed 9-item flow scale in an ESM study combined with a questionnaire to examine the predictors of flow at two levels: the activities (brainstorming, planning, problem solving and evaluation) associated with transient flow states and the more stable job characteristics (role clarity, influence and cognitive demands). Participants were 58 line managers from two companies in Denmark; a private accountancy firm and a public elder care organization. We found that line managers in elder care experienced flow more often than accountancy line managers, and activities such as planning, problem solving, and evaluation predicted transient flow states. The more stable job characteristics included in this study were not, however, found to predict flow at work. Copyright 2010 APA, all rights reserved.

Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks.

Science.gov (United States)

Zhu, Junxing; Zhang, Jiawei; Wu, Quanyuan; Jia, Yan; Zhou, Bin; Wei, Xiaokai; Yu, Philip S

2017-08-03

Nowadays, people are usually involved in multiple heterogeneous social networks simultaneously. Discovering the anchor links between the accounts owned by the same users across different social networks is crucial for many important inter-network applications, e.g., cross-network link transfer and cross-network recommendation. Many different supervised models have been proposed to predict anchor links so far, but they are effective only when the labeled anchor links are abundant. However, in real scenarios, such a requirement can hardly be met and most anchor links are unlabeled, since manually labeling the inter-network anchor links is quite costly and tedious. To overcome such a problem and utilize the numerous unlabeled anchor links in model building, in this paper, we introduce the active learning based anchor link prediction problem. Different from the traditional active learning problems, due to the one-to-one constraint on anchor links, if an unlabeled anchor link a = ( u , v ) is identified as positive (i.e., existing), all the other unlabeled anchor links incident to account u or account v will be negative (i.e., non-existing) automatically. Viewed in such a perspective, asking for the labels of potential positive anchor links in the unlabeled set will be rewarding in the active anchor link prediction problem. Various novel anchor link information gain measures are defined in this paper, based on which several constraint active anchor link prediction methods are introduced. Extensive experiments have been done on real-world social network datasets to compare the performance of these methods with state-of-art anchor link prediction methods. The experimental results show that the proposed Mean-entropy-based Constrained Active Learning (MC) method can outperform other methods with significant advantages.

Influence of accelerometer type and placement on physical activity energy expenditure prediction in manual wheelchair users.

Directory of Open Access Journals (Sweden)

Tom Edward Nightingale

Full Text Available To assess the validity of two accelerometer devices, at two different anatomical locations, for the prediction of physical activity energy expenditure (PAEE in manual wheelchair users (MWUs.Seventeen MWUs (36 ± 10 yrs, 72 ± 11 kg completed ten activities; resting, folding clothes, propulsion on a 1% gradient (3,4,5,6 and 7 km·hr-1 and propulsion at 4km·hr-1 (with an additional 8% body mass, 2% and 3% gradient on a motorised wheelchair treadmill. GT3X+ and GENEActiv accelerometers were worn on the right wrist (W and upper arm (UA. Linear regression analysis was conducted between outputs from each accelerometer and criterion PAEE, measured using indirect calorimetry. Subsequent error statistics were calculated for the derived regression equations for all four device/location combinations, using a leave-one-out cross-validation analysis.Accelerometer outputs at each anatomical location were significantly (p < .01 associated with PAEE (GT3X+-UA; r = 0.68 and GT3X+-W; r = 0.82. GENEActiv-UA; r = 0.87 and GENEActiv-W; r = 0.88. Mean ± SD PAEE estimation errors for all activities combined were 15 ± 45%, 14 ± 50%, 3 ± 25% and 4 ± 26% for GT3X+-UA, GT3X+-W, GENEActiv-UA and GENEActiv-W, respectively. Absolute PAEE estimation errors for devices varied, 19 to 66% for GT3X+-UA, 17 to 122% for GT3X+-W, 15 to 26% for GENEActiv-UA and from 17.0 to 32% for the GENEActiv-W.The results indicate that the GENEActiv device worn on either the upper arm or wrist provides the most valid prediction of PAEE in MWUs. Variation in error statistics between the two devices is a result of inherent differences in internal components, on-board filtering processes and outputs of each device.

Influence of accelerometer type and placement on physical activity energy expenditure prediction in manual wheelchair users.

Science.gov (United States)

Nightingale, Tom Edward; Walhin, Jean-Philippe; Thompson, Dylan; Bilzon, James Lee John

2015-01-01

To assess the validity of two accelerometer devices, at two different anatomical locations, for the prediction of physical activity energy expenditure (PAEE) in manual wheelchair users (MWUs). Seventeen MWUs (36 ± 10 yrs, 72 ± 11 kg) completed ten activities; resting, folding clothes, propulsion on a 1% gradient (3,4,5,6 and 7 km·hr-1) and propulsion at 4km·hr-1 (with an additional 8% body mass, 2% and 3% gradient) on a motorised wheelchair treadmill. GT3X+ and GENEActiv accelerometers were worn on the right wrist (W) and upper arm (UA). Linear regression analysis was conducted between outputs from each accelerometer and criterion PAEE, measured using indirect calorimetry. Subsequent error statistics were calculated for the derived regression equations for all four device/location combinations, using a leave-one-out cross-validation analysis. Accelerometer outputs at each anatomical location were significantly (p < .01) associated with PAEE (GT3X+-UA; r = 0.68 and GT3X+-W; r = 0.82. GENEActiv-UA; r = 0.87 and GENEActiv-W; r = 0.88). Mean ± SD PAEE estimation errors for all activities combined were 15 ± 45%, 14 ± 50%, 3 ± 25% and 4 ± 26% for GT3X+-UA, GT3X+-W, GENEActiv-UA and GENEActiv-W, respectively. Absolute PAEE estimation errors for devices varied, 19 to 66% for GT3X+-UA, 17 to 122% for GT3X+-W, 15 to 26% for GENEActiv-UA and from 17.0 to 32% for the GENEActiv-W. The results indicate that the GENEActiv device worn on either the upper arm or wrist provides the most valid prediction of PAEE in MWUs. Variation in error statistics between the two devices is a result of inherent differences in internal components, on-board filtering processes and outputs of each device.

PRDM9 variation strongly influences recombination hot-spot activity and meiotic instability in humans.

Science.gov (United States)

Berg, Ingrid L; Neumann, Rita; Lam, Kwan-Wood G; Sarbajna, Shriparna; Odenthal-Hesse, Linda; May, Celia A; Jeffreys, Alec J

2010-10-01

PRDM9 has recently been identified as a likely trans regulator of meiotic recombination hot spots in humans and mice. PRDM9 contains a zinc finger array that, in humans, can recognize a short sequence motif associated with hot spots, with binding to this motif possibly triggering hot-spot activity via chromatin remodeling. We now report that human genetic variation at the PRDM9 locus has a strong effect on sperm hot-spot activity, even at hot spots lacking the sequence motif. Subtle changes within the zinc finger array can create hot-spot nonactivating or enhancing variants and can even trigger the appearance of a new hot spot, suggesting that PRDM9 is a major global regulator of hot spots in humans. Variation at the PRDM9 locus also influences aspects of genome instability-specifically, a megabase-scale rearrangement underlying two genomic disorders as well as minisatellite instability-implicating PRDM9 as a risk factor for some pathological genome rearrangements.

Using Volcanic Lightning Measurements to Discern Variations in Explosive Volcanic Activity

Science.gov (United States)

Behnke, S. A.; Thomas, R. J.; McNutt, S. R.; Edens, H. E.; Krehbiel, P. R.; Rison, W.

2013-12-01

VHF observations of volcanic lightning have been made during the recent eruptions of Augustine Volcano (2006, Alaska, USA), Redoubt Volcano (2009, Alaska, USA), and Eyjafjallajökull (2010, Iceland). These show that electrical activity occurs both on small scales at the vent of the volcano, concurrent with an eruptive event and on large scales throughout the eruption column during and subsequent to an eruptive event. The small-scale discharges at the vent of the volcano are often referred to as 'vent discharges' and are on the order of 10-100 meters in length and occur at rates on the order of 1000 per second. The high rate of vent discharges produces a distinct VHF signature that is sometimes referred to as 'continuous RF' radiation. VHF radiation from vent discharges has been observed at sensors placed as far as 100 km from the volcano. VHF and infrasound measurements have shown that vent discharges occur simultaneously with the onset of eruption, making their detection an unambiguous indicator of explosive volcanic activity. The fact that vent discharges are observed concurrent with explosive volcanic activity indicates that volcanic ejecta are charged upon eruption. VHF observations have shown that the intensity of vent discharges varies between eruptive events, suggesting that fluctuations in eruptive processes affect the electrification processes giving rise to vent discharges. These fluctuations may be variations in eruptive vigor or variations in the type of eruption; however, the data obtained so far do not show a clear relationship between eruption parameters and the intensity or occurrence of vent discharges. Further study is needed to clarify the link between vent discharges and eruptive behavior, such as more detailed lightning observations concurrent with tephra measurements and other measures of eruptive strength. Observations of vent discharges, and volcanic lightning observations in general, are a valuable tool for volcano monitoring, providing a

Variation in aerodynamic coefficients with altitude

Science.gov (United States)

Shahid, Faiza; Hussain, Mukkarum; Baig, Mirza Mehmood; Haq, Ihtram ul

Precise aerodynamics performance prediction plays key role for a flying vehicle to get its mission completed within desired accuracy. Aerodynamic coefficients for same Mach number can be different at different altitude due to difference in Reynolds number. Prediction of these aerodynamics coefficients can be made through experiments, analytical solution or Computational Fluid Dynamics (CFD). Advancements in computational power have generated the concept of using CFD as a virtual Wind Tunnel (WT), hence aerodynamic performance prediction in present study is based upon CFD (numerical test rig). Simulations at different altitudes for a range of Mach numbers with zero angle of attack are performed to predict axial force coefficient behavior with altitude (Reynolds number). Similar simulations for a fixed Mach number '3' and a range of angle of attacks are also carried out to envisage the variation in normal force and pitching moment coefficients with altitude (Reynolds number). Results clearly depict that the axial force coefficient is a function of altitude (Reynolds number) and increase as altitude increases, especially for subsonic region. Variation in axial force coefficient with altitude (Reynolds number) slightly increases for larger values of angle of attacks. Normal force and pitching moment coefficients do not depend on altitude (Reynolds number) at smaller values of angle of attacks but show slight decrease as altitude increases. Present study suggests that variation of normal force and pitching moment coefficients with altitude can be neglected but the variation of axial force coefficient with altitude should be considered for vehicle fly in dense atmosphere. It is recommended to continue this study to more complex configurations for various Mach numbers with side slip and real gas effects.

Predicting the activity coefficients of free-solvent for concentrated globular protein solutions using independently determined physical parameters.

Directory of Open Access Journals (Sweden)

Devin W McBride

Full Text Available The activity coefficient is largely considered an empirical parameter that was traditionally introduced to correct the non-ideality observed in thermodynamic systems such as osmotic pressure. Here, the activity coefficient of free-solvent is related to physically realistic parameters and a mathematical expression is developed to directly predict the activity coefficients of free-solvent, for aqueous protein solutions up to near-saturation concentrations. The model is based on the free-solvent model, which has previously been shown to provide excellent prediction of the osmotic pressure of concentrated and crowded globular proteins in aqueous solutions up to near-saturation concentrations. Thus, this model uses only the independently determined, physically realizable quantities: mole fraction, solvent accessible surface area, and ion binding, in its prediction. Predictions are presented for the activity coefficients of free-solvent for near-saturated protein solutions containing either bovine serum albumin or hemoglobin. As a verification step, the predictability of the model for the activity coefficient of sucrose solutions was evaluated. The predicted activity coefficients of free-solvent are compared to the calculated activity coefficients of free-solvent based on osmotic pressure data. It is observed that the predicted activity coefficients are increasingly dependent on the solute-solvent parameters as the protein concentration increases to near-saturation concentrations.

Measured and Predicted Variations in Fast Neutron Spectrum when Penetrating Laminated Fe-D{sub 2}O

Energy Technology Data Exchange (ETDEWEB)

Aalto, E; Sandlin, R; Fraeki, R

1965-09-15

Variations of the fast neutron spectrum in thin regions of alternating Fe and D{sub O} have been studied using threshold detectors (ln(n, n' ), S(n, p), Al(n, {alpha})). The results have been compared to those calculated by two shielding codes (NRN and RASH D) of multigroup removal-diffusion type. The absolute fast spectrum calculated in our rather complicated configurations was found to agree with measurements within the same accuracy (a factor of two) as did the thermal flux. The calculated spectrum is slightly harder than the measured one, but the detailed variations (covering the range 1:5) in the form of the spectrum when penetrating Fe agree with observations to within 15-20 %. In and Al activities were found to be proportional to the integrated flux over 1 MeV throughout the whole configuration, while S showed the least proportionality.

Distortion of the activation energy of high temperature internal friction background due to temperature dependence frequency variations

International Nuclear Information System (INIS)

Lambri, O.; Povolo, F.; Molinas, B.

1991-01-01

In this work, a study is made of how the variation of frequency with temperature affects an activation enthalpy. This effect is usually neglected, but in some cases like Cu-Au or Zry-4 (an alloy of nuclear interest base or Zr alloyed with Sn, Fe and Cr) such variation can rise up to as much as 16%/4/ and 37%/5/. (Author) [es

Changes in monthly unemployment rates may predict changes in the number of psychiatric presentations to emergency services in South Australia.

Science.gov (United States)

Bidargaddi, Niranjan; Bastiampillai, Tarun; Schrader, Geoffrey; Adams, Robert; Piantadosi, Cynthia; Strobel, Jörg; Tucker, Graeme; Allison, Stephen

2015-07-24

To determine the extent to which variations in monthly Mental Health Emergency Department (MHED) presentations in South Australian Public Hospitals are associated with the Australian Bureau of Statistics (ABS) monthly unemployment rates. Times series modelling of relationships between monthly MHED presentations to South Australian Public Hospitals derived from the Integrated South Australian Activity Collection (ISAAC) data base and the ABS monthly unemployment rates in South Australia between January 2004-June 2011. Time series modelling using monthly unemployment rates from ABS as a predictor variable explains 69% of the variation in monthly MHED presentations across public hospitals in South Australia. Thirty-two percent of the variation in current month's male MHED presentations can be predicted by using the 2 months' prior male unemployment rate. Over 63% of the variation in monthly female MHED presentations can be predicted by either male or female prior monthly unemployment rates. The findings of this study highlight that even with the relatively favourable economic conditions, small shifts in monthly unemployment rates can predict variations in monthly MHED presentations, particularly for women. Monthly ABS unemployment rates may be a useful metric for predicting demand for emergency mental health services.

Genetic variation of the ghrelin activator gene ghrelin O-acyltransferase (GOAT) is associated with anorexia nervosa.

Science.gov (United States)

Müller, Timo D; Tschöp, Matthias H; Jarick, Ivonne; Ehrlich, Stefan; Scherag, Susann; Herpertz-Dahlmann, Beate; Zipfel, Stefan; Herzog, Wolfgang; de Zwaan, Martina; Burghardt, Roland; Fleischhaker, Christian; Klampfl, Karin; Wewetzer, Christoph; Herpertz, Stephan; Zeeck, Almut; Tagay, Sefik; Burgmer, Markus; Pfluger, Paul T; Scherag, André; Hebebrand, Johannes; Hinney, Anke

2011-05-01

The gastrointestinal peptide hormone ghrelin promotes food intake and increases body weight and adiposity through activation of the growth hormone secretagogue receptor (GHSR1a). To promote its biological action ghrelin is acylated at its serine 3 residue by the recently discovered ghrelin O-acyltransferase (GOAT, a.k.a. membrane-bound O-acyltransferase 4, MBOAT4). Plasma levels of total and acyl-ghrelin are negatively correlated with body-mass-index (BMI); as lower the BMI as higher plasma levels of total and acylated ghrelin and vice versa. Accordingly, plasma levels of total and acyl-ghrelin are elevated in patients with anorexia nervosa (AN) and decline upon weight regain. The importance of the endogenous Goat/ghrelin system in the neuroendocrine adaptation to fasting was recently highlighted by the observation that acyl-ghrelin mediated elevation of growth hormone (GH) release prevents starvation induced hypoglycemia in Goat(-/-) mice. The aim of this study was to test if genetic variation of GOAT is implicated in the etiology of AN. We therefore assessed association of 6 tagging single nucleotide polymorphisms (tagSNPs), which were predicted to cover 96% the common genetic variability of GOAT plus 50 kb of the 5' and 3' flanking region, in 543 German patients with AN and 612 German normal and underweight healthy controls. Based on a recessive mode of inheritance we observed some evidence for association of the G/G genotype at SNP rs10096097 with AN (nominal two-sided p = 0.031). Based on our results we conclude that genetic variation in GOAT might be implicated in the etiology of AN. Copyright © 2010 Elsevier Ltd. All rights reserved.

Intraspecific variation in flight metabolic rate in the bumblebee Bombus impatiens: repeatability and functional determinants in workers and drones.

Science.gov (United States)

Darveau, Charles-A; Billardon, Fannie; Bélanger, Kasandra

2014-02-15

The evolution of flight energetics requires that phenotypes be variable, repeatable and heritable. We studied intraspecific variation in flight energetics in order to assess the repeatability of flight metabolic rate and wingbeat frequency, as well as the functional basis of phenotypic variation in workers and drones of the bumblebee species Bombus impatiens. We showed that flight metabolic rate and wingbeat frequency were highly repeatable in workers, even when controlling for body mass variation using residual analysis. We did not detect significant repeatability in drones, but a smaller range of variation might have prevented us from finding significant values in our sample. Based on our results and previous findings, we associated the high repeatability of flight phenotypes in workers to the functional links between body mass, thorax mass, wing size, wingbeat frequency and metabolic rate. Moreover, differences between workers and drones were as predicted from these functional associations, where drones had larger wings for their size, lower wingbeat frequency and lower flight metabolic rate. We also investigated thoracic muscle metabolic phenotypes by measuring the activity of carbohydrate metabolism enzymes, and we found positive correlations between mass-independent metabolic rate and the activity of all enzymes measured, but in workers only. When comparing workers and drones that differ in flight metabolic rate, only the activity of the enzymes hexokinase and trehalase showed the predicted differences. Overall, our study indicates that there should be correlated evolution among physiological phenotypes at multiple levels of organization and morphological traits associated with flight.

Predictive capabilities of the specific activity hypothesis for Cs and Zn in freshwater systems

International Nuclear Information System (INIS)

Seelye, J.G.

1975-01-01

Predictions of radioisotope concentrations in components of aquatic systems have been attempted using the specific activity concept, an approach that seems theoretically sound. A comprehensive examination of the specific activities of 134 Cs and 65 Zn in the components of a freshwater system, over a 10 month period, was conducted to evaluate the specific activity hypothesis under applied conditions. This study was designed to provide comparisons of predicted and observed specific activities and to test the equivalence of specific activities between all components of the system. One dose of radioisotopes was added to the system in this study and even after 10 months these radioisotopes were not distributed similarly to the stable isotopes. This suggests that the time necessary to reach a specific activity equilibrium might be a matter of years rather than months. More importantly, in natural systems, where the radioisotope addition is continuous a specific activity equilibrium may never be achieved. These things plus the non-conservative nature of the 134 Cs and 65 Zn predicted concentrations indicates that the use of the specific activity concept for predicting radioisotope concentrations of Cs and Zn in freshwater systems is questionable. A more rigorous approach must be used, considering isotope transfer rates between components and the complexity of the system. Problems with statistical comparisons of derived variables, such as specific activities, are discussed and were considered in interpreting the results of this study

A cluster expansion model for predicting activation barrier of atomic processes

International Nuclear Information System (INIS)

Rehman, Tafizur; Jaipal, M.; Chatterjee, Abhijit

2013-01-01

We introduce a procedure based on cluster expansion models for predicting the activation barrier of atomic processes encountered while studying the dynamics of a material system using the kinetic Monte Carlo (KMC) method. Starting with an interatomic potential description, a mathematical derivation is presented to show that the local environment dependence of the activation barrier can be captured using cluster interaction models. Next, we develop a systematic procedure for training the cluster interaction model on-the-fly, which involves: (i) obtaining activation barriers for handful local environments using nudged elastic band (NEB) calculations, (ii) identifying the local environment by analyzing the NEB results, and (iii) estimating the cluster interaction model parameters from the activation barrier data. Once a cluster expansion model has been trained, it is used to predict activation barriers without requiring any additional NEB calculations. Numerical studies are performed to validate the cluster expansion model by studying hop processes in Ag/Ag(100). We show that the use of cluster expansion model with KMC enables efficient generation of an accurate process rate catalog

Development of METAL-ACTIVE SITE and ZINCCLUSTER tool to predict active site pockets.

Science.gov (United States)

Ajitha, M; Sundar, K; Arul Mugilan, S; Arumugam, S

2018-03-01

The advent of whole genome sequencing leads to increasing number of proteins with known amino acid sequences. Despite many efforts, the number of proteins with resolved three dimensional structures is still low. One of the challenging tasks the structural biologists face is the prediction of the interaction of metal ion with any protein for which the structure is unknown. Based on the information available in Protein Data Bank, a site (METALACTIVE INTERACTION) has been generated which displays information for significant high preferential and low-preferential combination of endogenous ligands for 49 metal ions. User can also gain information about the residues present in the first and second coordination sphere as it plays a major role in maintaining the structure and function of metalloproteins in biological system. In this paper, a novel computational tool (ZINCCLUSTER) is developed, which can predict the zinc metal binding sites of proteins even if only the primary sequence is known. The purpose of this tool is to predict the active site cluster of an uncharacterized protein based on its primary sequence or a 3D structure. The tool can predict amino acids interacting with a metal or vice versa. This tool is based on the occurrence of significant triplets and it is tested to have higher prediction accuracy when compared to that of other available techniques. © 2017 Wiley Periodicals, Inc.

Predicting active school travel: The role of planned behavior and habit strength

Science.gov (United States)

2012-01-01

Background Despite strong support for predictive validity of the theory of planned behavior (TPB) substantial variance in both intention and behavior is unaccounted for by the model’s predictors. The present study tested the extent to which habit strength augments the predictive validity of the TPB in relation to a currently under-researched behavior that has important health implications, namely children’s active school travel. Method Participants (N = 126 children aged 8–9 years; 59 % males) were sampled from five elementary schools in the west of Scotland and completed questionnaire measures of all TPB constructs in relation to walking to school and both walking and car/bus use habit. Over the subsequent week, commuting steps on school journeys were measured objectively using an accelerometer. Hierarchical multiple regressions were used to test the predictive utility of the TPB and habit strength in relation to both intention and subsequent behavior. Results The TPB accounted for 41 % and 10 % of the variance in intention and objectively measured behavior, respectively. Together, walking habit and car/bus habit significantly increased the proportion of explained variance in both intention and behavior by 6 %. Perceived behavioral control and both walking and car/bus habit independently predicted intention. Intention and car/bus habit independently predicted behavior. Conclusions The TPB significantly predicts children’s active school travel. However, habit strength augments the predictive validity of the model. The results indicate that school travel is controlled by both intentional and habitual processes. In practice, interventions could usefully decrease the habitual use of motorized transport for travel to school and increase children’s intention to walk (via increases in perceived behavioral control and walking habit, and decreases in car/bus habit). Further research is needed to identify effective strategies for changing these

Predicting Variation of DNA Shape Preferences in Protein-DNA Interaction in Cancer Cells with a New Biophysical Model.

Science.gov (United States)

Batmanov, Kirill; Wang, Junbai

2017-09-18

DNA shape readout is an important mechanism of transcription factor target site recognition, in addition to the sequence readout. Several machine learning-based models of transcription factor-DNA interactions, considering DNA shape features, have been developed in recent years. Here, we present a new biophysical model of protein-DNA interactions by integrating the DNA shape properties. It is based on the neighbor dinucleotide dependency model BayesPI2, where new parameters are restricted to a subspace spanned by the dinucleotide form of DNA shape features. This allows a biophysical interpretation of the new parameters as a position-dependent preference towards specific DNA shape features. Using the new model, we explore the variation of DNA shape preferences in several transcription factors across various cancer cell lines and cellular conditions. The results reveal that there are DNA shape variations at FOXA1 (Forkhead Box Protein A1) binding sites in steroid-treated MCF7 cells. The new biophysical model is useful for elucidating the finer details of transcription factor-DNA interaction, as well as for predicting cancer mutation effects in the future.

Merlin : microsimulation system for predicting leisure activity-travel patterns

NARCIS (Netherlands)

Middelkoop, van M.; Borgers, A.W.J.; Timmermans, H.J.P.

2004-01-01

Development of a model of annual activity-travel patterns of leisure and vacation travel is reported. The simulation system, called Merlin, is a hybrid model system consisting of discrete choice models and rule-based models. It predicts the annual number of day trips and vacations, and the profile

Tail Risk Premia and Return Predictability

DEFF Research Database (Denmark)

Bollerslev, Tim; Todorov, Viktor; Xu, Lai

The variance risk premium, defined as the difference between actual and risk-neutralized expectations of the forward aggregate market variation, helps predict future market returns. Relying on new essentially model-free estimation procedure, we show that much of this predictability may be attribu......The variance risk premium, defined as the difference between actual and risk-neutralized expectations of the forward aggregate market variation, helps predict future market returns. Relying on new essentially model-free estimation procedure, we show that much of this predictability may......-varying economic uncertainty and changes in risk aversion, or market fears, respectively....

Circulating Biologically Active Adrenomedullin (bio-ADM) Predicts Hemodynamic Support Requirement and Mortality During Sepsis.

Science.gov (United States)

Caironi, Pietro; Latini, Roberto; Struck, Joachim; Hartmann, Oliver; Bergmann, Andreas; Maggio, Giuseppe; Cavana, Marco; Tognoni, Gianni; Pesenti, Antonio; Gattinoni, Luciano; Masson, Serge

2017-08-01

The biological role of adrenomedullin (ADM), a hormone involved in hemodynamic homeostasis, is controversial in sepsis because administration of either the peptide or an antibody against it may be beneficial. Plasma biologically active ADM (bio-ADM) was assessed on days 1, 2, and 7 after randomization of 956 patients with sepsis or septic shock to albumin or crystalloids for fluid resuscitation in the multicenter Albumin Italian Outcome Sepsis trial. We tested the association of bio-ADM and its time-dependent variation with fluid therapy, vasopressor administration, organ failures, and mortality. Plasma bio-ADM on day 1 (median [Q1-Q3], 110 [59-198] pg/mL) was higher in patients with septic shock, associated with 90-day mortality, multiple organ failures and the average extent of hemodynamic support therapy (fluids and vasopressors), and serum lactate time course over the first week. Moreover, it predicted incident cardiovascular dysfunction in patients without shock at enrollment (OR [95% CI], 1.9 [1.4-2.5]; P sepsis, the circulating, biologically active form of ADM may help individualizing hemodynamic support therapy, while avoiding harmful effects. Its possible pathophysiologic role makes bio-ADM a potential candidate for future targeted therapies. ClinicalTrials.gov; No.: NCT00707122. Copyright © 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Jensen's Inequality Predicts Effects of Environmental Variation

Science.gov (United States)

Jonathan J. Ruel; Matthew P. Ayres

1999-01-01

Many biologists now recognize that environmental variance can exert important effects on patterns and processes in nature that are independent of average conditions. Jenson's inequality is a mathematical proof that is seldom mentioned in the ecological literature but which provides a powerful tool for predicting some direct effects of environmental variance in...

In silico detection of sequence variations modifying transcriptional regulation.

Directory of Open Access Journals (Sweden)

Malin C Andersen

2008-01-01

Full Text Available Identification of functional genetic variation associated with increased susceptibility to complex diseases can elucidate genes and underlying biochemical mechanisms linked to disease onset and progression. For genes linked to genetic diseases, most identified causal mutations alter an encoded protein sequence. Technological advances for measuring RNA abundance suggest that a significant number of undiscovered causal mutations may alter the regulation of gene transcription. However, it remains a challenge to separate causal genetic variations from linked neutral variations. Here we present an in silico driven approach to identify possible genetic variation in regulatory sequences. The approach combines phylogenetic footprinting and transcription factor binding site prediction to identify variation in candidate cis-regulatory elements. The bioinformatics approach has been tested on a set of SNPs that are reported to have a regulatory function, as well as background SNPs. In the absence of additional information about an analyzed gene, the poor specificity of binding site prediction is prohibitive to its application. However, when additional data is available that can give guidance on which transcription factor is involved in the regulation of the gene, the in silico binding site prediction improves the selection of candidate regulatory polymorphisms for further analyses. The bioinformatics software generated for the analysis has been implemented as a Web-based application system entitled RAVEN (regulatory analysis of variation in enhancers. The RAVEN system is available at http://www.cisreg.ca for all researchers interested in the detection and characterization of regulatory sequence variation.

In Silico Detection of Sequence Variations Modifying Transcriptional Regulation

Science.gov (United States)

Andersen, Malin C; Engström, Pär G; Lithwick, Stuart; Arenillas, David; Eriksson, Per; Lenhard, Boris; Wasserman, Wyeth W; Odeberg, Jacob

2008-01-01

Identification of functional genetic variation associated with increased susceptibility to complex diseases can elucidate genes and underlying biochemical mechanisms linked to disease onset and progression. For genes linked to genetic diseases, most identified causal mutations alter an encoded protein sequence. Technological advances for measuring RNA abundance suggest that a significant number of undiscovered causal mutations may alter the regulation of gene transcription. However, it remains a challenge to separate causal genetic variations from linked neutral variations. Here we present an in silico driven approach to identify possible genetic variation in regulatory sequences. The approach combines phylogenetic footprinting and transcription factor binding site prediction to identify variation in candidate cis-regulatory elements. The bioinformatics approach has been tested on a set of SNPs that are reported to have a regulatory function, as well as background SNPs. In the absence of additional information about an analyzed gene, the poor specificity of binding site prediction is prohibitive to its application. However, when additional data is available that can give guidance on which transcription factor is involved in the regulation of the gene, the in silico binding site prediction improves the selection of candidate regulatory polymorphisms for further analyses. The bioinformatics software generated for the analysis has been implemented as a Web-based application system entitled RAVEN (regulatory analysis of variation in enhancers). The RAVEN system is available at http://www.cisreg.ca for all researchers interested in the detection and characterization of regulatory sequence variation. PMID:18208319

Chaos in balance: non-linear measures of postural control predict individual variations in visual illusions of motion.

Directory of Open Access Journals (Sweden)

Deborah Apthorp

Full Text Available Visually-induced illusions of self-motion (vection can be compelling for some people, but they are subject to large individual variations in strength. Do these variations depend, at least in part, on the extent to which people rely on vision to maintain their postural stability? We investigated by comparing physical posture measures to subjective vection ratings. Using a Bertec balance plate in a brightly-lit room, we measured 13 participants' excursions of the centre of foot pressure (CoP over a 60-second period with eyes open and with eyes closed during quiet stance. Subsequently, we collected vection strength ratings for large optic flow displays while seated, using both verbal ratings and online throttle measures. We also collected measures of postural sway (changes in anterior-posterior CoP in response to the same visual motion stimuli while standing on the plate. The magnitude of standing sway in response to expanding optic flow (in comparison to blank fixation periods was predictive of both verbal and throttle measures for seated vection. In addition, the ratio between eyes-open and eyes-closed CoP excursions during quiet stance (using the area of postural sway significantly predicted seated vection for both measures. Interestingly, these relationships were weaker for contracting optic flow displays, though these produced both stronger vection and more sway. Next we used a non-linear analysis (recurrence quantification analysis, RQA of the fluctuations in anterior-posterior position during quiet stance (both with eyes closed and eyes open; this was a much stronger predictor of seated vection for both expanding and contracting stimuli. Given the complex multisensory integration involved in postural control, our study adds to the growing evidence that non-linear measures drawn from complexity theory may provide a more informative measure of postural sway than the conventional linear measures.

NESmapper: accurate prediction of leucine-rich nuclear export signals using activity-based profiles.

Directory of Open Access Journals (Sweden)

Shunichi Kosugi

2014-09-01

Full Text Available The nuclear export of proteins is regulated largely through the exportin/CRM1 pathway, which involves the specific recognition of leucine-rich nuclear export signals (NESs in the cargo proteins, and modulates nuclear-cytoplasmic protein shuttling by antagonizing the nuclear import activity mediated by importins and the nuclear import signal (NLS. Although the prediction of NESs can help to define proteins that undergo regulated nuclear export, current methods of predicting NESs, including computational tools and consensus-sequence-based searches, have limited accuracy, especially in terms of their specificity. We found that each residue within an NES largely contributes independently and additively to the entire nuclear export activity. We created activity-based profiles of all classes of NESs with a comprehensive mutational analysis in mammalian cells. The profiles highlight a number of specific activity-affecting residues not only at the conserved hydrophobic positions but also in the linker and flanking regions. We then developed a computational tool, NESmapper, to predict NESs by using profiles that had been further optimized by training and combining the amino acid properties of the NES-flanking regions. This tool successfully reduced the considerable number of false positives, and the overall prediction accuracy was higher than that of other methods, including NESsential and Wregex. This profile-based prediction strategy is a reliable way to identify functional protein motifs. NESmapper is available at http://sourceforge.net/projects/nesmapper.

Quantitative structure-activity relationship (QSAR) for insecticides: development of predictive in vivo insecticide activity models.

Science.gov (United States)

Naik, P K; Singh, T; Singh, H

2009-07-01

Quantitative structure-activity relationship (QSAR) analyses were performed independently on data sets belonging to two groups of insecticides, namely the organophosphates and carbamates. Several types of descriptors including topological, spatial, thermodynamic, information content, lead likeness and E-state indices were used to derive quantitative relationships between insecticide activities and structural properties of chemicals. A systematic search approach based on missing value, zero value, simple correlation and multi-collinearity tests as well as the use of a genetic algorithm allowed the optimal selection of the descriptors used to generate the models. The QSAR models developed for both organophosphate and carbamate groups revealed good predictability with r(2) values of 0.949 and 0.838 as well as [image omitted] values of 0.890 and 0.765, respectively. In addition, a linear correlation was observed between the predicted and experimental LD(50) values for the test set data with r(2) of 0.871 and 0.788 for both the organophosphate and carbamate groups, indicating that the prediction accuracy of the QSAR models was acceptable. The models were also tested successfully from external validation criteria. QSAR models developed in this study should help further design of novel potent insecticides.

Anthropometry and physical activity level in the prediction of metabolic syndrome in children.

Science.gov (United States)

Andaki, Alynne Christian Ribeiro; Tinôco, Adelson Luiz Araújo; Mendes, Edmar Lacerda; Andaki Júnior, Roberto; Hills, Andrew P; Amorim, Paulo Roberto S

2014-10-01

To evaluate the effectiveness of anthropometric measures and physical activity level in the prediction of metabolic syndrome (MetS) in children. Cross-sectional study with children from public and private schools. Children underwent an anthropometric assessment, blood pressure measurement and biochemical evaluation of serum for determination of TAG, HDL-cholesterol and glucose. Physical activity level was calculated and number of steps per day obtained using a pedometer for seven consecutive days. Viçosa, south-eastern Brazil. Boys and girls (n 187), mean age 9·90 (SD 0·7) years. Conicity index, sum of four skinfolds, physical activity level and number of steps per day were accurate in predicting MetS in boys. Anthropometric indicators were accurate in predicting MetS for girls, specifically BMI, waist circumference measured at the narrowest point and at the level of the umbilicus, four skinfold thickness measures evaluated separately, the sum of subscapular and triceps skinfold thickness, the sum of four skinfolds and body fat percentage. The sum of four skinfolds was the most accurate method in predicting MetS in both genders.

Analysis of the variation of the activity of a "9"9"mTc sample after dilution with saline solution

International Nuclear Information System (INIS)

Kuahara, L.T.; Correa, E.L.; Potiens, M.P.A.

2016-01-01

The activity meter is essential equipment in nuclear medicine services.To ensure its good operation and know the factors which may influence its readings is vital for the activity administered to the patient be correct. Many factors may influence the activity meter accuracy, such as the type of container, geometry, and radioactive material volume. The aim of this study was to analyze the measurements variations in 0.5 ml and 1.0 ml of "9"9"mTc pure and diluted in 2.5 ml of saline solution, in containers used in nuclear medicine. Variations of up to 4 % in measured values were found. (author)

Predicting Neural Activity Patterns Associated with Sentences Using a Neurobiologically Motivated Model of Semantic Representation.

Science.gov (United States)

Anderson, Andrew James; Binder, Jeffrey R; Fernandino, Leonardo; Humphries, Colin J; Conant, Lisa L; Aguilar, Mario; Wang, Xixi; Doko, Donias; Raizada, Rajeev D S

2017-09-01

We introduce an approach that predicts neural representations of word meanings contained in sentences then superposes these to predict neural representations of new sentences. A neurobiological semantic model based on sensory, motor, social, emotional, and cognitive attributes was used as a foundation to define semantic content. Previous studies have predominantly predicted neural patterns for isolated words, using models that lack neurobiological interpretation. Fourteen participants read 240 sentences describing everyday situations while undergoing fMRI. To connect sentence-level fMRI activation patterns to the word-level semantic model, we devised methods to decompose the fMRI data into individual words. Activation patterns associated with each attribute in the model were then estimated using multiple-regression. This enabled synthesis of activation patterns for trained and new words, which were subsequently averaged to predict new sentences. Region-of-interest analyses revealed that prediction accuracy was highest using voxels in the left temporal and inferior parietal cortex, although a broad range of regions returned statistically significant results, showing that semantic information is widely distributed across the brain. The results show how a neurobiologically motivated semantic model can decompose sentence-level fMRI data into activation features for component words, which can be recombined to predict activation patterns for new sentences. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Regional variation in the predictive validity of self-rated health for mortality

Directory of Open Access Journals (Sweden)

Edward R. Berchick

2017-12-01

Full Text Available Self-rated health (SRH is a commonly used measure for assessing general health in surveys in the United States. However, individuals from different parts of the United States may vary in how they assess their health. Geographic differences in health care access and in the prevalence of illnesses may make it difficult to discern true regional differences in health when using SRH as a health measure. In this article, we use data from the 1986 and 1989–2006 National Health Interview Survey Linked Mortality Files and estimate Cox regression models to examine whether the relationship between SRH and five-year all-cause mortality differs by Census region. Contrary to hypotheses, there is no evidence of regional variation in the predictive validity of SRH for mortality. At all levels of SRH, and for both non-Hispanic white and non-Hispanic black respondents, SRH is equally and strongly associated with five-year mortality across regions. Our results suggest that differences in SRH across regions are not solely due to differences in how respondents assess their health across regions, but reflect true differences in health. Future research can, therefore, employ this common measure to investigate the geographic patterning of health in the United States.

Spontaneous brain activity predicts learning ability of foreign sounds.

Science.gov (United States)

Ventura-Campos, Noelia; Sanjuán, Ana; González, Julio; Palomar-García, María-Ángeles; Rodríguez-Pujadas, Aina; Sebastián-Gallés, Núria; Deco, Gustavo; Ávila, César

2013-05-29

Can learning capacity of the human brain be predicted from initial spontaneous functional connectivity (FC) between brain areas involved in a task? We combined task-related functional magnetic resonance imaging (fMRI) and resting-state fMRI (rs-fMRI) before and after training with a Hindi dental-retroflex nonnative contrast. Previous fMRI results were replicated, demonstrating that this learning recruited the left insula/frontal operculum and the left superior parietal lobe, among other areas of the brain. Crucially, resting-state FC (rs-FC) between these two areas at pretraining predicted individual differences in learning outcomes after distributed (Experiment 1) and intensive training (Experiment 2). Furthermore, this rs-FC was reduced at posttraining, a change that may also account for learning. Finally, resting-state network analyses showed that the mechanism underlying this reduction of rs-FC was mainly a transfer in intrinsic activity of the left frontal operculum/anterior insula from the left frontoparietal network to the salience network. Thus, rs-FC may contribute to predict learning ability and to understand how learning modifies the functioning of the brain. The discovery of this correspondence between initial spontaneous brain activity in task-related areas and posttraining performance opens new avenues to find predictors of learning capacities in the brain using task-related fMRI and rs-fMRI combined.

Prediction of tire/wet road friction and its variation with speed from road macro- and microtexture, and tire-related properties

OpenAIRE

Do , Minh Tan; Delanne , Yves

2004-01-01

In this paper, validation of a model for the speed dependency of friction is presented. Based on the shape of the friction – speed curve, the model assumes that calculation of friction at any speed would need an estimate of friction at very low speed, and the knowledge of its variation with speed described by the Stribeck curve. Two existing models developed at LCPC are then coupled to predict friction versus speed from the following characteristics: road surface macro and microtexture,...

Prediction of Tire/Wet Road Friction and its Variation with speed from Road Macro- and Microtexture, and Tire-Related Properties

OpenAIRE

DO, MT; DELANNE, Y

2004-01-01

In this paper, validation of a model for the speed dependency of friction is presented. Based on the shape of the friction - speed curve, the model assumes that calculation of friction at any speed would need an estimate of friction at very slow speed, and the knowledge of its variation with speed described by the Stribeck curve. Two existing models developed at LCPC are then coupled to predict friction versus speed from the following characteristics road surface macro and microtexture, rubbe...

A prediction model of short-term ionospheric foF2 based on AdaBoost

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Zhao, Xiukuan; Ning, Baiqi; Liu, Libo; Song, Gangbing

2014-02-01

In this paper, the AdaBoost-BP algorithm is used to construct a new model to predict the critical frequency of the ionospheric F2-layer (foF2) one hour ahead. Different indices were used to characterize ionospheric diurnal and seasonal variations and their dependence on solar and geomagnetic activity. These indices, together with the current observed foF2 value, were input into the prediction model and the foF2 value at one hour ahead was output. We analyzed twenty-two years' foF2 data from nine ionosonde stations in the East-Asian sector in this work. The first eleven years' data were used as a training dataset and the second eleven years' data were used as a testing dataset. The results show that the performance of AdaBoost-BP is better than those of BP Neural Network (BPNN), Support Vector Regression (SVR) and the IRI model. For example, the AdaBoost-BP prediction absolute error of foF2 at Irkutsk station (a middle latitude station) is 0.32 MHz, which is better than 0.34 MHz from BPNN, 0.35 MHz from SVR and also significantly outperforms the IRI model whose absolute error is 0.64 MHz. Meanwhile, AdaBoost-BP prediction absolute error at Taipei station from the low latitude is 0.78 MHz, which is better than 0.81 MHz from BPNN, 0.81 MHz from SVR and 1.37 MHz from the IRI model. Finally, the variety characteristics of the AdaBoost-BP prediction error along with seasonal variation, solar activity and latitude variation were also discussed in the paper.

Match-to-match variation in physical activity and technical skill measures in professional Australian Football.

Science.gov (United States)

Kempton, Thomas; Sullivan, Courtney; Bilsborough, Johann C; Cordy, Justin; Coutts, Aaron J

2015-01-01

To determine the match-to-match variability in physical activity and technical performance measures in Australian Football, and examine the influence of playing position, time of season, and different seasons on these measures of variability. Longitudinal observational study. Global positioning system, accelerometer and technical performance measures (total kicks, handballs, possessions and Champion Data rank) were collected from 33 players competing in the Australian Football League over 31 matches during 2011-2012 (N=511 observations). The global positioning system data were categorised into total distance, mean speed (mmin(-1)), high-speed running (>14.4 kmh(-1)), very high-speed running (>19.9 kmh(-1)), and sprint (>23.0 kmh(-1)) distance while player load was collected from the accelerometer. The data were log transformed to provide coefficient of variation and the between subject standard deviation (expressed as percentages). Match-to-match variability was increased for higher speed activities (high-speed running, very high-speed running, sprint distance, coefficient of variation %: 13.3-28.6%) compared to global measures (speed, total distance, player load, coefficient of variation %: 5.3-9.2%). The between-match variability was relativity stable for all measures between and within AFL seasons, with only few differences between positions. Higher speed activities (high-speed running, very high-speed running, sprint distance), but excluding mean speed, total distance and player load, were all higher in the final third phase of the season compared to the start of the season. While global measures of physical performance are relatively stable, higher-speed activities and technical measures exhibit a large degree of between-match variability in Australian Football. However, these measures remain relatively stable between positions, and within and between Australian Football League seasons. Copyright © 2013 Sports Medicine Australia. Published by Elsevier Ltd

Methodology for dimensional variation analysis of ITER integrated systems

International Nuclear Information System (INIS)

Fuentes, F. Javier; Trouvé, Vincent; Cordier, Jean-Jacques; Reich, Jens

2016-01-01

Highlights: • Tokamak dimensional management methodology, based on 3D variation analysis, is presented. • Dimensional Variation Model implementation workflow is described. • Methodology phases are described in detail. The application of this methodology to the tolerance analysis of ITER Vacuum Vessel is presented. • Dimensional studies are a valuable tool for the assessment of Tokamak PCR (Project Change Requests), DR (Deviation Requests) and NCR (Non-Conformance Reports). - Abstract: The ITER machine consists of a large number of complex systems highly integrated, with critical functional requirements and reduced design clearances to minimize the impact in cost and performances. Tolerances and assembly accuracies in critical areas could have a serious impact in the final performances, compromising the machine assembly and plasma operation. The management of tolerances allocated to part manufacture and assembly processes, as well as the control of potential deviations and early mitigation of non-compliances with the technical requirements, is a critical activity on the project life cycle. A 3D tolerance simulation analysis of ITER Tokamak machine has been developed based on 3DCS dedicated software. This integrated dimensional variation model is representative of Tokamak manufacturing functional tolerances and assembly processes, predicting accurate values for the amount of variation on critical areas. This paper describes the detailed methodology to implement and update the Tokamak Dimensional Variation Model. The model is managed at system level. The methodology phases are illustrated by its application to the Vacuum Vessel (VV), considering the status of maturity of VV dimensional variation model. The following topics are described in this paper: • Model description and constraints. • Model implementation workflow. • Management of input and output data. • Statistical analysis and risk assessment. The management of the integration studies based on

Methodology for dimensional variation analysis of ITER integrated systems

Energy Technology Data Exchange (ETDEWEB)

Fuentes, F. Javier, E-mail: FranciscoJavier.Fuentes@iter.org [ITER Organization, Route de Vinon-sur-Verdon—CS 90046, 13067 St Paul-lez-Durance (France); Trouvé, Vincent [Assystem Engineering & Operation Services, rue J-M Jacquard CS 60117, 84120 Pertuis (France); Cordier, Jean-Jacques; Reich, Jens [ITER Organization, Route de Vinon-sur-Verdon—CS 90046, 13067 St Paul-lez-Durance (France)

2016-11-01

Highlights: • Tokamak dimensional management methodology, based on 3D variation analysis, is presented. • Dimensional Variation Model implementation workflow is described. • Methodology phases are described in detail. The application of this methodology to the tolerance analysis of ITER Vacuum Vessel is presented. • Dimensional studies are a valuable tool for the assessment of Tokamak PCR (Project Change Requests), DR (Deviation Requests) and NCR (Non-Conformance Reports). - Abstract: The ITER machine consists of a large number of complex systems highly integrated, with critical functional requirements and reduced design clearances to minimize the impact in cost and performances. Tolerances and assembly accuracies in critical areas could have a serious impact in the final performances, compromising the machine assembly and plasma operation. The management of tolerances allocated to part manufacture and assembly processes, as well as the control of potential deviations and early mitigation of non-compliances with the technical requirements, is a critical activity on the project life cycle. A 3D tolerance simulation analysis of ITER Tokamak machine has been developed based on 3DCS dedicated software. This integrated dimensional variation model is representative of Tokamak manufacturing functional tolerances and assembly processes, predicting accurate values for the amount of variation on critical areas. This paper describes the detailed methodology to implement and update the Tokamak Dimensional Variation Model. The model is managed at system level. The methodology phases are illustrated by its application to the Vacuum Vessel (VV), considering the status of maturity of VV dimensional variation model. The following topics are described in this paper: • Model description and constraints. • Model implementation workflow. • Management of input and output data. • Statistical analysis and risk assessment. The management of the integration studies based on

Variation in aerodynamic coefficients with altitude

Directory of Open Access Journals (Sweden)

Faiza Shahid

Full Text Available Precise aerodynamics performance prediction plays key role for a flying vehicle to get its mission completed within desired accuracy. Aerodynamic coefficients for same Mach number can be different at different altitude due to difference in Reynolds number. Prediction of these aerodynamics coefficients can be made through experiments, analytical solution or Computational Fluid Dynamics (CFD. Advancements in computational power have generated the concept of using CFD as a virtual Wind Tunnel (WT, hence aerodynamic performance prediction in present study is based upon CFD (numerical test rig. Simulations at different altitudes for a range of Mach numbers with zero angle of attack are performed to predict axial force coefficient behavior with altitude (Reynolds number. Similar simulations for a fixed Mach number ‘3’ and a range of angle of attacks are also carried out to envisage the variation in normal force and pitching moment coefficients with altitude (Reynolds number. Results clearly depict that the axial force coefficient is a function of altitude (Reynolds number and increase as altitude increases, especially for subsonic region. Variation in axial force coefficient with altitude (Reynolds number slightly increases for larger values of angle of attacks. Normal force and pitching moment coefficients do not depend on altitude (Reynolds number at smaller values of angle of attacks but show slight decrease as altitude increases. Present study suggests that variation of normal force and pitching moment coefficients with altitude can be neglected but the variation of axial force coefficient with altitude should be considered for vehicle fly in dense atmosphere. It is recommended to continue this study to more complex configurations for various Mach numbers with side slip and real gas effects. Keywords: Mach number, Reynolds number, Blunt body, Altitude effect, Angle of attacks

Solar ultraviolet irradiance variations: a review

International Nuclear Information System (INIS)

Lean, J.

1987-01-01

Despite the geophysical importance of solar ultraviolet radiation, specific aspects of its temporal variations have not yet been adequately determined experimentally, nor are the mechanisms for the variability completely understood. Satellite observations have verified the reality of solar ultraviolet irradiance variations over time scales of days and months, and model calculations have confirmed the association of these short-term variations with the evolution and rotation of regions of enhanced magnetic activity on the solar disc. However, neither rocket nor satellite measurements have yet been made with sufficient accuracy and regularity to establish unequivocally the nature of the variability over the longer time of the 11-year solar cycle. The comparative importance for the long-term variations of local regions of enhanced magnetic activity and global scale activity perturbations is still being investigated. Solar ultraviolet irradiance variations over both short and long time scales are reviewed, with emphasis on their connection to solar magnetic activity. Correlations with ground-based measures of solar variability are examined because of the importance of the ground-based observations as historical proxies of ultraviolet irradiance variations. Current problems in understanding solar ultraviolet irradiance variations are discussed, and the measurements planned for solar cycle 22, which may resolve these problems, are briefly described. copyright American Geophysical Union 1987

Seasonal variation and solar activity dependence of the quiet-time ionospheric trough

Science.gov (United States)

Ishida, T.; Ogawa, Y.; Kadokura, A.; Hiraki, Y.; Häggström, I.

2014-08-01

We have conducted a statistical analysis of the ionospheric F region trough, focusing on its seasonal variation and solar activity dependence under geomagnetically quiet and moderate conditions, using plasma parameter data obtained via Common Program 3 observations performed by the European Incoherent Scatter (EISCAT) radar between 1982 and 2011. We have confirmed that there is a major difference in frictional heating between the high- and low-latitude sides of the EISCAT field of view (FOV) at ~73°0'N-60°5'N (geomagnetic latitude) at an altitude of 325 km, which is associated with trough formation. Our statistical results show that the high-latitude and midlatitude troughs occur on the high- and low-latitude sides of the FOV, respectively. Seasonal variations indicate that dissociative recombination accompanied by frictional heating is a main cause of trough formation in sunlit regions. During summer, therefore, the occurrence rate is maintained at 80-90% in the postmidnight high-latitude region owing to frictional heating by eastward return flow. Solar activity dependence on trough formation indicates that field-aligned currents modulate the occurrence rate of the trough during the winter and equinox seasons. In addition, the trough becomes deeper via dissociative recombination caused by an increased ion temperature with F10.7, at least in the equinox and summer seasons but not in winter.

Population genetic variation in gene expression is associated withphenotypic variation in Saccharomyces cerevisiae

Energy Technology Data Exchange (ETDEWEB)

Fay, Justin C.; McCullough, Heather L.; Sniegowski, Paul D.; Eisen, Michael B.

2004-02-25

The relationship between genetic variation in gene expression and phenotypic variation observable in nature is not well understood. Identifying how many phenotypes are associated with differences in gene expression and how many gene-expression differences are associated with a phenotype is important to understanding the molecular basis and evolution of complex traits. Results: We compared levels of gene expression among nine natural isolates of Saccharomyces cerevisiae grown either in the presence or absence of copper sulfate. Of the nine strains, two show a reduced growth rate and two others are rust colored in the presence of copper sulfate. We identified 633 genes that show significant differences in expression among strains. Of these genes,20 were correlated with resistance to copper sulfate and 24 were correlated with rust coloration. The function of these genes in combination with their expression pattern suggests the presence of both correlative and causative expression differences. But the majority of differentially expressed genes were not correlated with either phenotype and showed the same expression pattern both in the presence and absence of copper sulfate. To determine whether these expression differences may contribute to phenotypic variation under other environmental conditions, we examined one phenotype, freeze tolerance, predicted by the differential expression of the aquaporin gene AQY2. We found freeze tolerance is associated with the expression of AQY2. Conclusions: Gene expression differences provide substantial insight into the molecular basis of naturally occurring traits and can be used to predict environment dependent phenotypic variation.

ChIP-seq Accurately Predicts Tissue-Specific Activity of Enhancers

Energy Technology Data Exchange (ETDEWEB)

Visel, Axel; Blow, Matthew J.; Li, Zirong; Zhang, Tao; Akiyama, Jennifer A.; Holt, Amy; Plajzer-Frick, Ingrid; Shoukry, Malak; Wright, Crystal; Chen, Feng; Afzal, Veena; Ren, Bing; Rubin, Edward M.; Pennacchio, Len A.

2009-02-01

A major yet unresolved quest in decoding the human genome is the identification of the regulatory sequences that control the spatial and temporal expression of genes. Distant-acting transcriptional enhancers are particularly challenging to uncover since they are scattered amongst the vast non-coding portion of the genome. Evolutionary sequence constraint can facilitate the discovery of enhancers, but fails to predict when and where they are active in vivo. Here, we performed chromatin immunoprecipitation with the enhancer-associated protein p300, followed by massively-parallel sequencing, to map several thousand in vivo binding sites of p300 in mouse embryonic forebrain, midbrain, and limb tissue. We tested 86 of these sequences in a transgenic mouse assay, which in nearly all cases revealed reproducible enhancer activity in those tissues predicted by p300 binding. Our results indicate that in vivo mapping of p300 binding is a highly accurate means for identifying enhancers and their associated activities and suggest that such datasets will be useful to study the role of tissue-specific enhancers in human biology and disease on a genome-wide scale.

Variations in 137Cs activity concentrations in individual fruitbodies in clusters of Cantharellus tubaeformis

International Nuclear Information System (INIS)

Nikolova, I.; Johanson, K.J.

1999-01-01

Fruitbodies of Cantharellus tubaeformis grown in clusters were collected from a normal Swedish coniferous forest. In the laboratory, individual fruitbodies were transferred into plastic vials and the 137 Cs activity concentrations were determined and expressed as Bq kg -1 fresh weight. After drying at 55 o , the 137 CS levels were recalculated and expressed as Bq kg -1 dry weight. Large variations of 137 Cs activity concentrations between individual fruitbodies within the clusters were observed. In 1995, the range in the 137 CS levels of individual fruitbodies in one cluster were from 9,194 to 164,811 and in another cluster from 2,338 to 38,377 Bq kg -1 . The mean values for these two clusters were 90,294 and 13,556 Bq kg -1 respectively. In 1998, the mean value for eight clusters showed a range from 26,373 to 67,281 Bq kg -1 . The largest variations between individual fruitbodies within a cluster were from 11,875 to 107,160 Bq kg -1 . Refs. 10 (author)

Solar cycle variations of geocoronal balmer α emission

International Nuclear Information System (INIS)

Nossal, S.; Reynolds, R.J.; Roesler, F.L.; Scherb, F.

1993-01-01

Observations of the geocoronal Balmer in nightglow have been made from Wisconsin for more than a solar cycle with an internally consistent intensity reference to standard astronomical nebulae. These measurements were made with a double etalon, pressure-scanned, 15-cm aperture Fabry-Perot interferometer. The resulting long time data provides an opportunity to examine solar cycle influence on the mid-latitude exosphere and to address accompanying questions concerning the degree to which the exosphere is locally static or changing. The exospheric Balmer α absolute intensity measurements reported here show no statistically significant variations throughout the solar cycle when the variation with viewing geometry is removed by normalizing the data to reference exospheric model predictions by Anderson et al. However, the relative intensity dependence on solar depression angle does show a solar cycle variation. This variation suggests a possible related variation in the exospheric hydrogen density profile, although other interpretations are also possible. The results suggest that additional well-calibrated data taken over a longer time span could probe low-amplitude variations over the solar cycle and test predictions of a slow monotonic increase in exospheric hydrogen arising from greenhouse gases. 21 refs., 9 figs., 2 tabs

Predicting the unpredictable: Critical analysis and practical implications of predictive anticipatory activity

Directory of Open Access Journals (Sweden)

Julia eMossbridge

2014-03-01

Full Text Available A recent meta-analysis of experiments from seven independent laboratories (n=26 published since 1978 indicates that the human body can apparently detect randomly delivered stimuli occurring 1-10 seconds in the future (Mossbridge, Tressoldi, & Utts, 2012. The key observation in these studies is that human physiology appears to be able to distinguish between unpredictable dichotomous future stimuli, such as emotional vs. neutral images or sound vs. silence. This phenomenon has been called presentiment (as in feeling the future. In this paper we call it predictive anticipatory activity or PAA. The phenomenon is predictive because it can distinguish between upcoming stimuli; it is anticipatory because the physiological changes occur before a future event; and it is an activity because it involves changes in the cardiopulmonary, skin, and/or nervous systems. PAA is an unconscious phenomenon that seems to be a time-reversed reflection of the usual physiological response to a stimulus. It appears to resemble precognition (consciously knowing something is going to happen before it does, but PAA specifically refers to unconscious physiological reactions as opposed to conscious premonitions. Though it is possible that PAA underlies the conscious experience of precognition, experiments testing this idea have not produced clear results. The first part of this paper reviews the evidence for PAA and examines the two most difficult challenges for obtaining valid evidence for it: expectation bias and multiple analyses. The second part speculates on possible mechanisms and the theoretical implications of PAA for understanding physiology and consciousness. The third part examines potential practical applications.

Uncertainty in Predicting CCN Activity of Aged and Primary Aerosols

Science.gov (United States)

Zhang, Fang; Wang, Yuying; Peng, Jianfei; Ren, Jingye; Collins, Don; Zhang, Renyi; Sun, Yele; Yang, Xin; Li, Zhanqing

2017-11-01

Understanding particle CCN activity in diverse atmospheres is crucial when evaluating aerosol indirect effects. Here aerosols measured at three sites in China were categorized as different types for attributing uncertainties in CCN prediction in terms of a comprehensive data set including size-resolved CCN activity, size-resolved hygroscopic growth factor, and chemical composition. We show that CCN activity for aged aerosols is unexpectedly underestimated 22% at a supersaturation (S) of 0.2% when using κ-Kohler theory with an assumption of an internal mixture with measured bulk composition that has typically resulted in an overestimate of the CCN activity in previous studies. We conclude that the underestimation stems from neglect of the effect of aging/coating on particle hygroscopicity, which is not considered properly in most current models. This effect enhanced the hygroscopicity parameter (κ) by between 11% (polluted conditions) and 30% (clean days), as indicated in diurnal cycles of κ based on measurements by different instruments. In the urban Beijing atmosphere heavily influenced by fresh emissions, the CCN activity was overestimated by 45% at S = 0.2%, likely because of inaccurate assumptions of particle mixing state and because of variability of chemical composition over the particle size range. For both fresh and aged aerosols, CCN prediction exhibits very limited sensitivity to κSOA, implying a critical role of other factors like mixing of aerosol components within and between particles in regulating CCN activity. Our findings could help improving CCN parameterization in climate models.

Comment on ``Annual variation of geomagnetic activity'' by Alicia L. Clúa de Gonzales et al.

Science.gov (United States)

Sonnemann, G. R.

2002-10-01

Clúa de Gonzales et al. (J. Atmos. Terr. Phys. 63 (2001) 367) analyzed the monthly means of the geomagnetic /aa-index available since 1868 and found enhanced geomagnetic activity in July outside of the known seasonal course of semiannual variation. They pointed out that this behavior is mainly caused by the high values of the geomagnetic activity. Their analysis confirmed results obtained from an analysis of Ap-values nearly 30 years ago but widely unknown to the scientific community. At that time the entire year was analyzed using running means of the activity values averaged to the same date. Aside from the July period, the calculations revealed distinct deviations from the seasonal course-called geomagnetic singularities. The most marked singularity occurs from the middle of March to the end of March characterized by a strong increase from, on average, relatively calm values to the actually strongest ones during the entire year. Some typical time patterns around and after equinox are repeated half a year later. An analysis in 1998 on the basis of the available /aa-values confirmed the findings derived from Ap-values and the local activity index Ak from Niemegk, Germany available since 1890. The new results will be presented and discussed. Special attention is paid to the statistical problem of the persistence of geomagnetic perturbations. The main problem under consideration is that the variation of the mean activity is not caused by an accidental accumulation of strong perturbations occurring within certain intervals of days. We assume that the most marked variations of the mean value are not accidental and result from internal processes within the earth's atmosphere but different, particularly small-scale features, are most probably accidental.

Finite element predictions of active buckling control of stiffened panels

Science.gov (United States)

Thompson, Danniella M.; Griffin, O. H., Jr.

1993-04-01

Materials systems and structures that can respond 'intelligently' to their environment are currently being proposed and investigated. A series of finite element analyses was performed to investigate the potential for active buckling control of two different stiffened panels by embedded shape memory alloy (SMA) rods. Changes in the predicted buckling load increased with the magnitude of the actuation level for a given structural concept. Increasing the number of actuators for a given concept yielded greater predicted increases in buckling load. Considerable control authority was generated with a small number of actuators, with greater authority demonstrated for those structural concepts where the activated SMA rods could develop greater forces and moments on the structure. Relatively simple and inexpensive analyses were performed with standard finite elements to determine such information, indicating the viability of these types of models for design purposes.

Relation of geomagnetic activity index variations with parameters of interplanetary scintillations

International Nuclear Information System (INIS)

Vlasov, V.I.; Shishov, V.I.; Shishova, T.D.

1985-01-01

A correlation between the Asub(p)-index of geomagnetic activity, index of interplanetary scintillations and solar wind velocity, has been considered depending on the spatial position of the interplanetary plasma (IPP) regions under study. It is shown, that the scintillation index can be used to forecast the geomagnetic activity, whereas the solar wind velocity can not be used for the purpose. Heliolongitudinal dependence of geoeffectiveness of IPP sreading perturbations agrees well with their structure in the heliolongitudinal cross section (and, on the whole, with the angular structure and direction of IPP perturbation spread). To use interplanetary scintillations in forecasting the geomagnetic activity (on the level of correlation not below 0.5), the angular distance of the investigated IPP regions relative to the Sun-Earth line on the average should not exceed 30-40 deg. The time of delay between the moments of observation of variations in the scintillation index the time of passage of the corresponding heliocentric distances at an average rate of the interplanetary perturbation spread approximately 500 km/s

Spatio-Temporal Variation and Prediction of Ischemic Heart Disease Hospitalizations in Shenzhen, China

Directory of Open Access Journals (Sweden)

Yanxia Wang

2014-05-01

Full Text Available Ischemic heart disease (IHD is a leading cause of death worldwide. Urban public health and medical management in Shenzhen, an international city in the developing country of China, is challenged by an increasing burden of IHD. This study analyzed the spatio-temporal variation of IHD hospital admissions from 2003 to 2012 utilizing spatial statistics, spatial analysis, and space-time scan statistics. The spatial statistics and spatial analysis measured the incidence rate (hospital admissions per 1,000 residents and the standardized rate (the observed cases standardized by the expected cases of IHD at the district level to determine the spatio-temporal distribution and identify patterns of change. The space-time scan statistics was used to identify spatio-temporal clusters of IHD hospital admissions at the district level. The other objective of this study was to forecast the IHD hospital admissions over the next three years (2013–2015 to predict the IHD incidence rates and the varying burdens of IHD-related medical services among the districts in Shenzhen. The results show that the highest hospital admissions, incidence rates, and standardized rates of IHD are in Futian. From 2003 to 2012, the IHD hospital admissions exhibited similar mean centers and directional distributions, with a slight increase in admissions toward the north in accordance with the movement of the total population. The incidence rates of IHD exhibited a gradual increase from 2003 to 2012 for all districts in Shenzhen, which may be the result of the rapid development of the economy and the increasing traffic pollution. In addition, some neighboring areas exhibited similar temporal change patterns, which were also detected by the spatio-temporal cluster analysis. Futian and Dapeng would have the highest and the lowest hospital admissions, respectively, although these districts have the highest incidence rates among all of the districts from 2013 to 2015 based on the prediction

A prediction model of short-term ionospheric foF2 Based on AdaBoost

Science.gov (United States)

Zhao, Xiukuan; Liu, Libo; Ning, Baiqi

Accurate specifications of spatial and temporal variations of the ionosphere during geomagnetic quiet and disturbed conditions are critical for applications, such as HF communications, satellite positioning and navigation, power grids, pipelines, etc. Therefore, developing empirical models to forecast the ionospheric perturbations is of high priority in real applications. The critical frequency of the F2 layer, foF2, is an important ionospheric parameter, especially for radio wave propagation applications. In this paper, the AdaBoost-BP algorithm is used to construct a new model to predict the critical frequency of the ionospheric F2-layer one hour ahead. Different indices were used to characterize ionospheric diurnal and seasonal variations and their dependence on solar and geomagnetic activity. These indices, together with the current observed foF2 value, were input into the prediction model and the foF2 value at one hour ahead was output. We analyzed twenty-two years’ foF2 data from nine ionosonde stations in the East-Asian sector in this work. The first eleven years’ data were used as a training dataset and the second eleven years’ data were used as a testing dataset. The results show that the performance of AdaBoost-BP is better than those of BP Neural Network (BPNN), Support Vector Regression (SVR) and the IRI model. For example, the AdaBoost-BP prediction absolute error of foF2 at Irkutsk station (a middle latitude station) is 0.32 MHz, which is better than 0.34 MHz from BPNN, 0.35 MHz from SVR and also significantly outperforms the IRI model whose absolute error is 0.64 MHz. Meanwhile, AdaBoost-BP prediction absolute error at Taipei station from the low latitude is 0.78 MHz, which is better than 0.81 MHz from BPNN, 0.81 MHz from SVR and 1.37 MHz from the IRI model. Finally, the variety characteristics of the AdaBoost-BP prediction error along with seasonal variation, solar activity and latitude variation were also discussed in the paper.

Prediction Study on Anti-Slide Control of Railway Vehicle Based on RBF Neural Networks

Science.gov (United States)

Yang, Lijun; Zhang, Jimin

While railway vehicle braking, Anti-slide control system will detect operating status of each wheel-sets e.g. speed difference and deceleration etc. Once the detected value on some wheel-set is over pre-defined threshold, brake effort on such wheel-set will be adjusted automatically to avoid blocking. Such method takes effect on guarantee safety operation of vehicle and avoid wheel-set flatness, however it cannot adapt itself to the rail adhesion variation. While wheel-sets slide, the operating status is chaotic time series with certain law, and can be predicted with the law and experiment data in certain time. The predicted values can be used as the input reference signals of vehicle anti-slide control system, to judge and control the slide status of wheel-sets. In this article, the RBF neural networks is taken to predict wheel-set slide status in multi-step with weight vector adjusted based on online self-adaptive algorithm, and the center & normalizing parameters of active function of the hidden unit of RBF neural networks' hidden layer computed with K-means clustering algorithm. With multi-step prediction simulation, the predicted signal with appropriate precision can be used by anti-slide system to trace actively and adjust wheel-set slide tendency, so as to adapt to wheel-rail adhesion variation and reduce the risk of wheel-set blocking.

Experience during development triggers between-individual variation in behavioural plasticity.

Science.gov (United States)

Urszán, Tamás János; Garamszegi, László Zsolt; Nagy, Gergely; Hettyey, Attila; Török, János; Herczeg, Gábor

2018-05-12

1.Behavioural consistency within and across behaviours (animal personality and behavioural syndrome, respectively) have been vigorously studied in the last decade, leading to the emergence of 'animal personality' research. It has been proposed recently that not only mean behaviour (behavioural type), but the environmentally induced behavioural change (behavioural plasticity) might also differ between individuals within populations. 2.While case studies presenting between-individual variation in behavioural plasticity have started to accumulate, the mechanisms behind its emergence are virtually unknown. We have recently demonstrated that ecologically relevant environmental stimuli during ontogeny are necessary for the development of animal personality and behavioural syndromes. However, it is unknown whether between-individual variation in behavioural plasticity is hard-wired or induced. 3.Here, we tested whether experience with predation during development affected predator-induced behavioural plasticity in Rana dalmatina tadpoles. We ran a common garden experiment with two ontogenetic predation treatments: tadpoles developed from hatching in either the presence or absence of olfactory predator stimuli. Then, we assayed all tadpoles repeatedly for activity and risk-taking both in the absence and presence of olfactory predator stimuli. 4. We found that (i) between-individual variation in predator-induced behavioural plasticity was present only in the group that developed in the presence of olfactory stimuli from predators and (ii) previous experience with predatory stimuli resulted in lower plastic response at the group-level. The latter pattern resulted from increased between-individual variation and not from universally lower individual responses. We also found that experience with predation during development increased the predictability (i.e. decreased the within-individual variation unrelated to environmental change) of activity, but not risk-taking. In line

Colony-level behavioural variation correlates with differences in expression of the foraging gene in red imported fire ants.

Science.gov (United States)

Bockoven, Alison A; Coates, Craig J; Eubanks, Micky D

2017-11-01

Among social insects, colony-level variation is likely to be widespread and has significant ecological consequences. Very few studies, however, have documented how genetic factors relate to behaviour at the colony level. Differences in expression of the foraging gene have been associated with differences in foraging and activity of a wide variety of organisms. We quantified expression of the red imported fire ant foraging gene (sifor) in workers from 21 colonies collected across the natural range of Texas fire ant populations, but maintained under standardized, environmentally controlled conditions. Colonies varied significantly in their behaviour. The most active colonies had up to 10 times more active foragers than the least active colony and more than 16 times as many workers outside the nest. Expression differences among colonies correlated with this colony-level behavioural variation. Colonies with higher sifor expression in foragers had, on average, significantly higher foraging activity, exploratory activity and recruitment to nectar than colonies with lower expression. Expression of sifor was also strongly correlated with worker task (foraging vs. working in the interior of the nest). These results provide insight into the genetic and physiological processes underlying collective differences in social behaviour. Quantifying variation in expression of the foraging gene may provide an important tool for understanding and predicting the ecological consequences of colony-level behavioural variation. © 2017 John Wiley & Sons Ltd.

Causes of seasonal variations of Cs-134/137 activity concentrations in surface air

International Nuclear Information System (INIS)

Hoetzl, H.; Winkler, R.

1993-01-01

In winter months maxima of Cs-134/137 activity concentrations in air are observed at several locations in Europe. To clarify this phenomenon, from October 1991 to November 1992 we performed a program for aerosol collection on a short-term scale based on collecting intervals of 48-72 hours. The local meteorological parameters were determined simultaneously. Statistical analysis of these observations reveiled a highly significant positive correlation between Cs-137 activity concentration and the so-called 'Stagnationsindex'. Based on this relationship the seasonal variations of Cs-134/137 concentrations in ground-level air can be explained by atmospheric inversion conditions frequently occurring during fall- and wintermonths. (orig.) [de

Individual diet variation in a marine fish assemblage: Optimal Foraging Theory, Niche Variation Hypothesis and functional identity

Science.gov (United States)

Cachera, M.; Ernande, B.; Villanueva, M. C.; Lefebvre, S.

2017-02-01

Individual diet variation (i.e. diet variation among individuals) impacts intra- and inter-specific interactions. Investigating its sources and relationship with species trophic niche organization is important for understanding community structure and dynamics. Individual diet variation may increase with intra-specific phenotypic (or "individual state") variation and habitat variability, according to Optimal Foraging Theory (OFT), and with species trophic niche width, according to the Niche Variation Hypothesis (NVH). OFT proposes "proximate sources" of individual diet variation such as variations in habitat or size whereas NVH relies on "ultimate sources" related to the competitive balance between intra- and inter-specific competitions. The latter implies as a corollary that species trophic niche overlap, taken as inter-specific competition measure, decreases as species niche width and individual niche variation increase. We tested the complementary predictions of OFT and NVH in a marine fish assemblage using stomach content data and associated trophic niche metrics. The NVH predictions were tested between species of the assemblage and decomposed into a between- and a within-functional group component to assess the potential influence of species' ecological function. For most species, individual diet variation and niche overlap were consistently larger than expected. Individual diet variation increased with intra-specific variability in individual state and habitat, as expected from OFT. It also increased with species niche width but in compliance with the null expectation, thus not supporting the NVH. In contrast, species niche overlap increased significantly less than null expectation with both species niche width and individual diet variation, supporting NVH corollary. The between- and within-functional group components of the NVH relationships were consistent with those between species at the assemblage level. Changing the number of prey categories used to

Variation in dietary intake and physical activity pattern as predictors of change in body mass index (BMI) Z-score among Brazilian adolescents.

Science.gov (United States)

Enes, Carla C; Slater, Betzabeth

2013-06-01

To assess whether changes in dietary intake and physical activity pattern are associated with the annual body mass index (BMI) z-score change among adolescents. The study was conducted in public schools in the city of Piracicaba, Sao Paulo, Brazil, with a probabilistic sample of 431 adolescents participating in wave I (2004) (hereafter, baseline) and 299 in wave II (2005) (hereafter, follow-up). BMI, usual food intake, physical activity, screen time, sexual maturation and demographic variables were assessed twice. The association between annual change in food intake, physical activity, screen time, and annual BMI z-score changes were assessed by multiple regression. The study showed a positive variation in BMI z-score over one-year. Among variables related to physical activity pattern only playing videogame and using computer increased over the year. The intake of fruits and vegetables and sugar-sweetened beverages increased over one year, while the others variables showed a reduction. An increased consumption of fatty foods (β = 0.04, p = 0.04) and sweetened natural fruit juices (β = 0.05, p = 0.03) was positively associated with the rise in BMI z-score. Unhealthy dietary habits can predict the BMI z-score gain more than the physical activity pattern. The intake of fatty foods and sweetened fruit juices is associated with the BMI z-score over one year.

Variation in dietary intake and physical activity pattern as predictors of change in body mass index (BMI Z-score among Brazilian adolescents*

Directory of Open Access Journals (Sweden)

Carla C. Enes

2013-06-01

Full Text Available Objective: To assess whether changes in dietary intake and physical activity pattern are associated with the annual body mass index (BMI z-score change among adolescents. Methods: The study was conducted in public schools in the city of Piracicaba, Sao Paulo, Brazil, with a probabilistic sample of 431 adolescents participating in wave I (2004 (hereafter, baseline and 299 in wave II (2005 (hereafter, follow-up. BMI, usual food intake, physical activity, screen time, sexual maturation and demographic variables were assessed twice. The association between annual change in food intake, physical activity, screen time, and annual BMI z-score changes were assessed by multiple regression. Results: The study showed a positive variation in BMI z-score over one-year. Among variables related to physical activity pattern only playing videogame and using computer increased over the year. The intake of fruits and vegetables and sugar-sweetened beverages increased over one year, while the others variables showed a reduction. An increased consumption of fatty foods (β = 0.04, p = 0.04 and sweetened natural fruit juices (β = 0.05, p = 0.03 was positively associated with the rise in BMI z-score. Conclusions: Unhealthy dietary habits can predict the BMI z-score gain more than the physical activity pattern. The intake of fatty foods and sweetened fruit juices is associated with the BMI z-score over one year.

Predicting Indian Summer Monsoon onset through variations of surface air temperature and relative humidity

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Stolbova, Veronika; Surovyatkina, Elena; Kurths, Jurgen

2015-04-01

Indian Summer Monsoon (ISM) rainfall has an enormous effect on Indian agriculture, economy, and, as a consequence, life and prosperity of more than one billion people. Variability of the monsoonal rainfall and its onset have a huge influence on food production, agricultural planning and GDP of the country, which on 22% is determined by agriculture. Consequently, successful forecasting of the ISM onset is a big challenge and large efforts are being put into it. Here, we propose a novel approach for predictability of the ISM onset, based on critical transition theory. The ISM onset is defined as an abrupt transition from sporadious rainfall to spatially organized and temporally sustained rainfall. Taking this into account, we consider the ISM onset as is a critical transition from pre-monsoon to monsoon, which take place in time and also in space. It allows us to suggest that before the onset of ISM on the Indian subcontinent should be areas of critical behavior where indicators of the critical transitions can be detected through an analysis of observational data. First, we identify areas with such critical behavior. Second, we use detected areas as reference points for observation locations for the ISM onset prediction. Third, we derive a precursor for the ISM onset based on the analysis of surface air temperature and relative humidity variations in these reference points. Finally, we demonstrate the performance of this precursor on two observational data sets. The proposed approach allows to determine ISM onset in advance in 67% of all considered years. Our proposed approach is less effective during the anomalous years, which are associated with weak/strong monsoons, e.g. El-Nino, La-Nina or positive Indian Ocean Dipole events. The ISM onset is predicted for 23 out of 27 normal monsoon years (85%) during the past 6 decades. In the anomalous years, we show that time series analysis in both areas during the pre-monsoon period reveals indicators whether the

Kinetics of Hydrogen Radical Reactions with Toluene Including Chemical Activation Theory Employing System-Specific Quantum RRK Theory Calibrated by Variational Transition State Theory.

Science.gov (United States)

Bao, Junwei Lucas; Zheng, Jingjing; Truhlar, Donald G

2016-03-02

Pressure-dependent reactions are ubiquitous in combustion and atmospheric chemistry. We employ a new calibration procedure for quantum Rice-Ramsperger-Kassel (QRRK) unimolecular rate theory within a chemical activation mechanism to calculate the pressure-falloff effect of a radical association with an aromatic ring. The new theoretical framework is applied to the reaction of H with toluene, which is a prototypical reaction in the combustion chemistry of aromatic hydrocarbons present in most fuels. Both the hydrogen abstraction reactions and the hydrogen addition reactions are calculated. Our system-specific (SS) QRRK approach is adjusted with SS parameters to agree with multistructural canonical variational transition state theory with multidimensional tunneling (MS-CVT/SCT) at the high-pressure limit. The new method avoids the need for the usual empirical estimations of the QRRK parameters, and it eliminates the need for variational transition state theory calculations as a function of energy, although in this first application we do validate the falloff curves by comparing SS-QRRK results without tunneling to multistructural microcanonical variational transition state theory (MS-μVT) rate constants without tunneling. At low temperatures, the two approaches agree well with each other, but at high temperatures, SS-QRRK tends to overestimate falloff slightly. We also show that the variational effect is important in computing the energy-resolved rate constants. Multiple-structure anharmonicity, torsional-potential anharmonicity, and high-frequency-mode vibrational anharmonicity are all included in the rate computations, and torsional anharmonicity effects on the density of states are investigated. Branching fractions, which are both temperature- and pressure-dependent (and for which only limited data is available from experiment), are predicted as a function of pressure.

Estimation of physical activity levels using cell phone questionnaires: a comparison with accelerometry for evaluation of between-subject and within-subject variations.

Science.gov (United States)

Bexelius, Christin; Sandin, Sven; Trolle Lagerros, Ylva; Litton, Jan-Eric; Löf, Marie

2011-09-25

Physical activity promotes health and longevity. Further elaboration of the role of physical activity for human health in epidemiological studies on large samples requires accurate methods that are easy to use, cheap, and possible to repeat. The use of telecommunication technologies such as cell phones is highly interesting in this respect. In an earlier report, we showed that physical activity level (PAL) assessed using a cell phone procedure agreed well with corresponding estimates obtained using the doubly labeled water method. However, our earlier study indicated high within-subject variation in relation to between-subject variations in PAL using cell phones, but we could not assess if this was a true variation of PAL or an artifact of the cell phone technique. Our objective was to compare within- and between-subject variations in PAL by means of cell phones with corresponding estimates using an accelerometer. In addition, we compared the agreement of daily PAL values obtained using the cell phone questionnaire with corresponding data obtained using an accelerometer. PAL was measured both with the cell phone questionnaire and with a triaxial accelerometer daily during a 2-week study period in 21 healthy Swedish women (20 to 45 years of age and BMI from 17.7 kg/m² to 33.6 kg/m²). The results were evaluated by fitting linear mixed effect models and descriptive statistics and graphs. With the accelerometer, 57% (95% confidence interval [CI] 40%-66%) of the variation was within subjects, while with the cell phone, within-subject variation was 76% (95% CI 59%-83%). The day-to-day variations in PAL observed using the cell phone questions agreed well with the corresponding accelerometer results. Both the cell phone questionnaire and the accelerometer showed high within-subject variations. Furthermore, day-to-day variations in PAL within subjects assessed using the cell phone agreed well with corresponding accelerometer values. Consequently, our cell phone

Neural activity predicts attitude change in cognitive dissonance.

Science.gov (United States)

van Veen, Vincent; Krug, Marie K; Schooler, Jonathan W; Carter, Cameron S

2009-11-01

When our actions conflict with our prior attitudes, we often change our attitudes to be more consistent with our actions. This phenomenon, known as cognitive dissonance, is considered to be one of the most influential theories in psychology. However, the neural basis of this phenomenon is unknown. Using a Solomon four-group design, we scanned participants with functional MRI while they argued that the uncomfortable scanner environment was nevertheless a pleasant experience. We found that cognitive dissonance engaged the dorsal anterior cingulate cortex and anterior insula; furthermore, we found that the activation of these regions tightly predicted participants' subsequent attitude change. These effects were not observed in a control group. Our findings elucidate the neural representation of cognitive dissonance, and support the role of the anterior cingulate cortex in detecting cognitive conflict and the neural prediction of attitude change.

Temperature variation in pulp chamber during dental bleaching in presence or absence of light activation

OpenAIRE

Mollica, Fernanda Brandão; Rocha, Daniel Maranha da; Travassos, Alessandro Caldas; Valera, Marcia Carneiro; Araujo, Maria Amélia Maximo de

2010-01-01

PURPOSE: In addition to the chemical damage due to bleaching gels penetration into the pulp during pulp vitality dental bleaching, another possible aggressive factor could be the heat generated by the exothermal oxidation reaction of the bleaching gel, which may also be aggravated by the use of light activation. This study assessed the temperature variation in the pulp chamber in human teeth, using three different bleaching gels with or without LED light activation. METHODS: Thirty human pre-...

Longitudinal variation in adolescent physical activity patterns and the emergence of tobacco use.

Science.gov (United States)

Audrain-McGovern, Janet; Rodriguez, Daniel; Rodgers, Kelli; Cuevas, Jocelyn; Sass, Joseph

2012-07-01

The objective of this investigation was to examine how variation in adolescent physical activity is related to smoking and alternative tobacco use. Adolescents (N = 1,384) completed a self-report survey every 6 months from ages 14- to 18-years old in a prospective study of health behaviors. The 8 waves of data were analyzed using General Growth Mixture Modeling (GGMM) RESULTS: GGMM identified five physical activity trajectories including stable higher (SHPA), decreased (DPA), stable regular (SRPA), curvilinear (CPA), and stable low (SLPA). Across 4 years, the likelihood of smoking was greater among adolescents in the DPA, SLPA and SRPA trajectories compared to adolescents belonging to the SHPA trajectory. Alternative tobacco use was greatest among adolescents in the DPA and SRPA trajectories. Adolescents with decreasing physical activity and even adolescents averaging an hour of physical activity a day (SRPA) are important groups to target for tobacco use prevention and intervention efforts.

Latitudinal variation rate of geomagnetic cutoff rigidity in the active Chilean convergent margin

Science.gov (United States)

Cordaro, Enrique G.; Venegas, Patricio; Laroze, David

2018-03-01

We present a different view of secular variation of the Earth's magnetic field, through the variations in the threshold rigidity known as the variation rate of geomagnetic cutoff rigidity (VRc). As the geomagnetic cutoff rigidity (Rc) lets us differentiate between charged particle trajectories arriving at the Earth and the Earth's magnetic field, we used the VRc to look for internal variations in the latter, close to the 70° south meridian. Due to the fact that the empirical data of total magnetic field BF and vertical magnetic field Bz obtained at Putre (OP) and Los Cerrillos (OLC) stations are consistent with the displacement of the South Atlantic magnetic anomaly (SAMA), we detected that the VRc does not fully correlate to SAMA in central Chile. Besides, the lower section of VRc seems to correlate perfectly with important geological features, like the flat slab in the active Chilean convergent margin. Based on this, we next focused our attention on the empirical variations of the vertical component of the magnetic field Bz, recorded in OP prior to the Maule earthquake in 2010, which occurred in the middle of the Chilean flat slab. We found a jump in Bz values and main frequencies from 3.510 to 5.860 µHz, in the second derivative of Bz, which corresponds to similar magnetic behavior found by other research groups, but at lower frequency ranges. Then, we extended this analysis to other relevant subduction seismic events, like Sumatra in 2004 and Tohoku in 2011, using data from the Guam station. Similar records and the main frequencies before each event were found. Thus, these results seem to show that magnetic anomalies recorded on different timescales, as VRc (decades) and Bz (days), may correlate with some geological events, as the lithosphere-atmosphere-ionosphere coupling (LAIC).

Inter-fraction variations in respiratory motion models

Energy Technology Data Exchange (ETDEWEB)

McClelland, J R; Modat, M; Ourselin, S; Hawkes, D J [Centre for Medical Image Computing, University College London (United Kingdom); Hughes, S; Qureshi, A; Ahmad, S; Landau, D B, E-mail: j.mcclelland@cs.ucl.ac.uk [Department of Oncology, Guy' s and St Thomas' s Hospitals NHS Trust, London (United Kingdom)

2011-01-07

Respiratory motion can vary dramatically between the planning stage and the different fractions of radiotherapy treatment. Motion predictions used when constructing the radiotherapy plan may be unsuitable for later fractions of treatment. This paper presents a methodology for constructing patient-specific respiratory motion models and uses these models to evaluate and analyse the inter-fraction variations in the respiratory motion. The internal respiratory motion is determined from the deformable registration of Cine CT data and related to a respiratory surrogate signal derived from 3D skin surface data. Three different models for relating the internal motion to the surrogate signal have been investigated in this work. Data were acquired from six lung cancer patients. Two full datasets were acquired for each patient, one before the course of radiotherapy treatment and one at the end (approximately 6 weeks later). Separate models were built for each dataset. All models could accurately predict the respiratory motion in the same dataset, but had large errors when predicting the motion in the other dataset. Analysis of the inter-fraction variations revealed that most variations were spatially varying base-line shifts, but changes to the anatomy and the motion trajectories were also observed.

Uncertainties in container failure time predictions

International Nuclear Information System (INIS)

Williford, R.E.

1990-01-01

Stochastic variations in the local chemical environment of a geologic waste repository can cause corresponding variations in container corrosion rates and failure times, and thus in radionuclide release rates. This paper addresses how well the future variations in repository chemistries must be known in order to predict container failure times that are bounded by a finite time period within the repository lifetime. Preliminary results indicate that a 5000 year scatter in predicted container failure times requires that repository chemistries be known to within ±10% over the repository lifetime. These are small uncertainties compared to current estimates. 9 refs., 3 figs

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

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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.

Investigation of a connection of variations of atmospheric radiocarbon activity with some geophysical and astrophysical phenomena

International Nuclear Information System (INIS)

Kocharov, G.E.; Chernov, S.B.

1980-01-01

Relation of the radiocarbon concentration is dendrochronologically dated wood samples to solar activity, geomagnetic field variations and changes of global temperature near the earth surface for the last 500 years is studied. It is found that averaged 10-year Δ 14 C fluctuations of radiocarbon content in annual rings of trees experience noticeable variations with the 0.5% amplitude. To reveal the effect in the best way the Δ 14 C values averaged in the intervals equal to 11-year solar activity cycles and with a 4-year shift in relation to the latter, are obtained. It is shown that in the 1700-1805 period of time the Δ 14 C averaged values corresponding to peak values of the even 11-year solar activity cycles are mainly lower than the Δ 14 C averaged values corresponding to the odd cycle maximum values. In the 1835-1900 period the 14 C averaged values corresponding to the odd solar cycle maximum values are lesser than the Δ 14 C averaged values corresponding to the even cycle peaks [ru

Sources of variation and genetic profile of spontaneous, out-of-season ovulatory activity in the Chios sheep

Directory of Open Access Journals (Sweden)

Kouttos Athanasios

2003-01-01

Full Text Available Abstract Organising the breeding plan of a seasonally breeding species, such as sheep, presents a challenge to farmers and the industry as a whole, since both economical and biological considerations need to be carefully balanced. Understanding the breeding activity of individual animals becomes a prerequisite for a successful breeding program. This study set out to investigate the sources of variation and the genetic profile of the spontaneous, out-of-season ovulatory activity of ewes of the Chios dairy sheep breed in Greece. The definition of the trait was based on blood progesterone levels, measured before exposing the ewes to rams, which marks the onset of the usual breeding season. Data were 707 records, taken over two consecutive years, of 435 ewes kept at the Agricultural Research Station of Chalkidiki in northern Greece. When all available pedigree was included, the total number of animals involved was 1068. On average, 29% of all ewes exhibited spontaneous, out-of-season ovulatory activity, with no substantial variation between the years. Significant sources of systematic variation were the ewe age and live weight, and the month of previous lambing. Older, heavier ewes, that had lambed early the previous autumn, exhibited more frequent activity. Heritability estimates were 0.216 (± 0.084 with a linear and 0.291 with a threshold model. The latter better accounts for the categorical nature of the trait. The linear model repeatability was 0.230 (± 0.095. The results obtained in this study support the notion that spontaneous out-of-season ovulatory activity can be considered in the development of a breeding plan for the Chios sheep breed.

New active drugs against liver stages of Plasmodium predicted by molecular topology.

NARCIS (Netherlands)

Mahmoudi, N.; Garcia-Domenech, R.; Galvez, J.; Farhati, K.; Franetich, J.F.; Sauerwein, R.W.; Hannoun, L.; Derouin, F.; Danis, M.; Mazier, D.

2008-01-01

We conducted a quantitative structure-activity relationship (QSAR) study based on a database of 127 compounds previously tested against the liver stage of Plasmodium yoelii in order to develop a model capable of predicting the in vitro antimalarial activities of new compounds. Topological indices

Evidence from northwest European bogs shows ‘Little Ice Age’ climatic changes driven by variations in solar activity

NARCIS (Netherlands)

Mauquoy, D; van Geel, B; Blaauw, Maarten; van der Plicht, J

2002-01-01

Fluctuations in Holocene atmospheric radiocarbon concentrations have been shown to be due to variations in solar activity. Analyses of both Be-10 and C-14 nuclides confirm that production-rate changes during the Holocene were largely modulated by solar activity. Analyses of peat samples from two

Study on the Seismic Active Earth Pressure by Variational Limit Equilibrium Method

Directory of Open Access Journals (Sweden)

Jiangong Chen

2016-01-01

Full Text Available In the framework of limit equilibrium theory, the isoperimetric model of functional extremum regarding the seismic active earth pressure is deduced according to the variational method. On this basis, Lagrange multipliers are introduced to convert the problem of seismic active earth pressure into the problem on the functional extremum of two undetermined function arguments. Based on the necessary conditions required for the existence of functional extremum, the function of the slip surface and the normal stress distribution on the slip surface is obtained, and the functional extremum problem is further converted into a function optimization problem with two undetermined Lagrange multipliers. The calculated results show that the slip surface is a plane and the seismic active earth pressure is minimal when the action point is at the lower limit position. As the action point moves upward, the slip surface becomes a logarithmic spiral and the corresponding value of seismic active earth pressure increases in a nonlinear manner. And the seismic active earth pressure is maximal at the upper limit position. The interval estimation constructed by the minimum and maximum values of seismic active earth pressure can provide a reference for the aseismic design of gravity retaining walls.

Which nerve conduction parameters can predict spontaneous electromyographic activity in carpal tunnel syndrome?

Science.gov (United States)

Chang, Chia-Wei; Lee, Wei-Ju; Liao, Yi-Chu; Chang, Ming-Hong

2013-11-01

We investigate electrodiagnostic markers to determine which parameters are the best predictors of spontaneous electromyographic (EMG) activity in carpal tunnel syndrome (CTS). We enrolled 229 patients with clinically proven and nerve conduction study (NCS)-proven CTS, as well as 100 normal control subjects. All subjects were evaluated using electrodiagnostic techniques, including median distal sensory latencies (DSLs), sensory nerve action potentials (SNAPs), distal motor latencies (DMLs), compound muscle action potentials (CMAPs), forearm median nerve conduction velocities (FMCVs) and wrist-palm motor conduction velocities (W-P MCVs). All CTS patients underwent EMG examination of the abductor pollicis brevis (APB) muscle, and the presence or absence of spontaneous EMG activities was recorded. Normal limits were determined by calculating the means ± 2 standard deviations from the control data. Associations between parameters from the NCS and EMG findings were investigated. In patients with clinically diagnosed CTS, abnormal median CMAP amplitudes were the best predictors of spontaneous activity during EMG examination (p95% (positive predictive rate >95%). If the median CMAP amplitude was higher than the normal limit (>4.9 mV), the rate of no spontaneous EMG activity was >94% (negative predictive rate >94%). An abnormal SNAP amplitude was the second best predictor of spontaneous EMG activity (p<0.001; OR 4.13; 95% CI 2.16-7.90), and an abnormal FMCV was the third best predictor (p=0.01; OR 2.10; 95% CI 1.20-3.67). No other nerve conduction parameters had significant power to predict spontaneous activity upon EMG examination. The CMAP amplitudes of the APB are the most powerful predictors of the occurrence of spontaneous EMG activity. Low CMAP amplitudes are strongly associated with spontaneous activity, whereas high CMAP amplitude are less associated with spontaneous activity, implying that needle EMG examination should be recommended for the detection of

Prokaryotic Argonautes - variations on the RNA interference theme

Science.gov (United States)

van der Oost, John; Swarts, Daan C.; Jore, Matthijs M.

2014-01-01

The discovery of RNA interference (RNAi) has been a major scientific breakthrough. This RNA-guided RNA interference system plays a crucial role in a wide range of regulatory and defense mechanisms in eukaryotes. The key enzyme of the RNAi system is Argonaute (Ago), an endo-ribonuclease that uses a small RNA guide molecule to specifically target a complementary RNA transcript. Two functional classes of eukaryotic Ago have been described: catalytically active Ago that cleaves RNA targets complementary to its guide, and inactive Ago that uses its guide to bind target RNA to down-regulate translation efficiency. A recent comparative genomics study has revealed that Argonaute-like proteins are also encoded by prokaryotic genomes. Interestingly, there is a lot of variation among these prokaryotic Argonaute (pAgo) proteins with respect to domain architecture: some resemble the eukaryotic Ago (long pAgo) containing a complete or disrupted catalytic site, while others are truncated versions (short pAgo) that generally contain an incomplete catalytic site. Prokaryotic Agos with an incomplete catalytic site often co-occur with (predicted) nucleases. Based on this diversity, and on the fact that homologs of other RNAi-related protein components (such as Dicer nucleases) have never been identified in prokaryotes, it has been predicted that variations on the eukaryotic RNAi theme may occur in prokaryotes. PMID:28357239

In-Season Yield Prediction of Cabbage with a Hand-Held Active Canopy Sensor.

Science.gov (United States)

Ji, Rongting; Min, Ju; Wang, Yuan; Cheng, Hu; Zhang, Hailin; Shi, Weiming

2017-10-08

Efficient and precise yield prediction is critical to optimize cabbage yields and guide fertilizer application. A two-year field experiment was conducted to establish a yield prediction model for cabbage by using the Greenseeker hand-held optical sensor. Two cabbage cultivars (Jianbao and Pingbao) were used and Jianbao cultivar was grown for 2 consecutive seasons but Pingbao was only grown in the second season. Four chemical nitrogen application rates were implemented: 0, 80, 140, and 200 kg·N·ha -1 . Normalized difference vegetation index (NDVI) was collected 20, 50, 70, 80, 90, 100, 110, 120, 130, and 140 days after transplanting (DAT). Pearson correlation analysis and regression analysis were performed to identify the relationship between the NDVI measurements and harvested yields of cabbage. NDVI measurements obtained at 110 DAT were significantly correlated to yield and explained 87-89% and 75-82% of the cabbage yield variation of Jianbao cultivar over the two-year experiment and 77-81% of the yield variability of Pingbao cultivar. Adjusting the yield prediction models with CGDD (cumulative growing degree days) could make remarkable improvement to the accuracy of the prediction model and increase the determination coefficient to 0.82, while the modification with DFP (days from transplanting when GDD > 0) values did not. The integrated exponential yield prediction equation was better than linear or quadratic functions and could accurately make in-season estimation of cabbage yields with different cultivars between years.

Physical Activity Participation: Social Cognitive Theory versus the Theories of Reasoned Action and Planned Behavior.

Science.gov (United States)

Dzewaltowski, David A; Noble, John M; Shaw, Jeff M

1990-12-01

Social cognitive theory and the theories of reasoned action and planned behavior were examined in the prediction of 4 weeks of physical activity participation. The theories of reasoned action and planned behavior were supported. Attitude and perceived control predicted intention, and intention predicted physical activity participation. The social cognitive theory variables significantly predicted physical activity participation, with self-efficacy and self-evaluation of the behavior significantly contributing to the prediction. The greater the confidence in participating in physical activity and the greater the satisfaction with present physical activity, the more physical activity performed. Hierarchical regression analyses indicated that perceived control and intentions did not account for any unique variation in physical activity participation over self-efficacy. Therefore the social cognitive theory constructs were better predictors of physical activity than those from the theories of reasoned action and planned behavior.

Consensus Modeling for Prediction of Estrogenic Activity of Ingredients Commonly Used in Sunscreen Products

Directory of Open Access Journals (Sweden)

Huixiao Hong

2016-09-01

Full Text Available Sunscreen products are predominantly regulated as over-the-counter (OTC drugs by the US FDA. The “active” ingredients function as ultraviolet filters. Once a sunscreen product is generally recognized as safe and effective (GRASE via an OTC drug review process, new formulations using these ingredients do not require FDA review and approval, however, the majority of ingredients have never been tested to uncover any potential endocrine activity and their ability to interact with the estrogen receptor (ER is unknown, despite the fact that this is a very extensively studied target related to endocrine activity. Consequently, we have developed an in silico model to prioritize single ingredient estrogen receptor activity for use when actual animal data are inadequate, equivocal, or absent. It relies on consensus modeling to qualitatively and quantitatively predict ER binding activity. As proof of concept, the model was applied to ingredients commonly used in sunscreen products worldwide and a few reference chemicals. Of the 32 chemicals with unknown ER binding activity that were evaluated, seven were predicted to be active estrogenic compounds. Five of the seven were confirmed by the published data. Further experimental data is needed to confirm the other two predictions.

The sequential structure of brain activation predicts skill.

Science.gov (United States)

Anderson, John R; Bothell, Daniel; Fincham, Jon M; Moon, Jungaa

2016-01-29

In an fMRI study, participants were trained to play a complex video game. They were scanned early and then again after substantial practice. While better players showed greater activation in one region (right dorsal striatum) their relative skill was better diagnosed by considering the sequential structure of whole brain activation. Using a cognitive model that played this game, we extracted a characterization of the mental states that are involved in playing a game and the statistical structure of the transitions among these states. There was a strong correspondence between this measure of sequential structure and the skill of different players. Using multi-voxel pattern analysis, it was possible to recognize, with relatively high accuracy, the cognitive states participants were in during particular scans. We used the sequential structure of these activation-recognized states to predict the skill of individual players. These findings indicate that important features about information-processing strategies can be identified from a model-based analysis of the sequential structure of brain activation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Design and implementation of predictive filtering system for current reference generation of active power filter

Energy Technology Data Exchange (ETDEWEB)

Kilic, Tomislav; Milun, Stanko; Petrovic, Goran [FESB University of Split, Faculty of Electrical Engineering, Machine Engineering and Naval Architecture, R. Boskovica bb, 21000, Split (Croatia)

2007-02-15

The shunt active power filters are used to attenuate the harmonic currents in power systems by injecting equal but opposite compensating currents. Successful control of the active filters requires an accurate current reference. In this paper the current reference determination based on predictive filtering structure is presented. Current reference was obtained by taking the difference of load current and its fundamental harmonic. For fundamental harmonic determination with no time delay a combination of digital predictive filter and low pass filter is used. The proposed method was implemented on a laboratory prototype of a three-phase active power filter. The algorithm for current reference determination was adapted and implemented on DSP controller. Simulation and experimental results show that the active power filter with implemented predictive filtering structure gives satisfactory performance in power system harmonic attenuation. (author)

Indo-Pacific Warm Pool Area Expansion, Modoki Activity, and Tropical Cold-Point Tropopause Temperature Variations

Science.gov (United States)

Xie, Fei; Li, Jianping; Tian, Wenshou; Li, Yanjie; Feng, Juan

2014-01-01

The tropical cold-point tropopause temperature (CPTT), a potentially important indicator of global climate change, is of particular importance for understanding changes in stratospheric water vapor levels. Since the 1980s, the tropical CPTT has shown not only interannual variations, but also a decreasing trend. However, the factors controlling the variations in the tropical CPTT since the 1980s remain elusive. The present study reveals that the continuous expansion of the area of the Indo-Pacific warm pool (IPWP) since the 1980s represents an increase in the total heat energy of the IPWP available to heat the tropospheric air, which is likely to expand as a result. This process lifts the tropical cold-point tropopause height (CPTH) and leads to the observed long-term cooling trend of the tropical CPTT. In addition, our analysis shows that Modoki activity is an important factor in modulating the interannual variations of the tropical CPTT through significant effects on overshooting convection. PMID:24686481

Bet hedging in a warming ocean: predictability of maternal environment shapes offspring size variation in marine sticklebacks.

Science.gov (United States)

Shama, Lisa N S

2015-12-01

Bet hedging at reproduction is expected to evolve when mothers are exposed to unpredictable cues for future environmental conditions, whereas transgenerational plasticity (TGP) should be favoured when cues reliably predict the environment offspring will experience. Since climate predictions forecast an increase in both temperature and climate variability, both TGP and bet hedging are likely to become important strategies to mediate climate change effects. Here, the potential to produce variably sized offspring in both warming and unpredictable environments was tested by investigating whether stickleback (Gasterosteus aculeatus) mothers adjusted mean offspring size and within-clutch variation in offspring size in response to experimental manipulation of maternal thermal environment and predictability (alternating between ambient and elevated water temperatures). Reproductive output traits of F1 females were influenced by both temperature and environmental predictability. Mothers that developed at ambient temperature (17 °C) produced larger, but fewer eggs than mothers that developed at elevated temperature (21 °C), implying selection for different-sized offspring in different environments. Mothers in unpredictable environments had smaller mean egg sizes and tended to have greater within-female egg size variability, especially at 21 °C, suggesting that mothers may have dynamically modified the variance in offspring size to spread the risk of incorrectly predicting future environmental conditions. Both TGP and diversification influenced F2 offspring body size. F2 offspring reared at 21 °C had larger mean body sizes if their mother developed at 21 °C, but this TGP benefit was not present for offspring of 17 °C mothers reared at 17 °C, indicating that maternal TGP will be highly relevant for ocean warming scenarios in this system. Offspring of variable environment mothers were smaller but more variable in size than offspring from constant environment

High responders and low responders: factors associated with individual variation in response to standardized training.

Science.gov (United States)

Mann, Theresa N; Lamberts, Robert P; Lambert, Michael I

2014-08-01

The response to an exercise intervention is often described in general terms, with the assumption that the group average represents a typical response for most individuals. In reality, however, it is more common for individuals to show a wide range of responses to an intervention rather than a similar response. This phenomenon of 'high responders' and 'low responders' following a standardized training intervention may provide helpful insights into mechanisms of training adaptation and methods of training prescription. Therefore, the aim of this review was to discuss factors associated with inter-individual variation in response to standardized, endurance-type training. It is well-known that genetic influences make an important contribution to individual variation in certain training responses. The association between genotype and training response has often been supported using heritability estimates; however, recent studies have been able to link variation in some training responses to specific single nucleotide polymorphisms. It would appear that hereditary influences are often expressed through hereditary influences on the pre-training phenotype, with some parameters showing a hereditary influence in the pre-training phenotype but not in the subsequent training response. In most cases, the pre-training phenotype appears to predict only a small amount of variation in the subsequent training response of that phenotype. However, the relationship between pre-training autonomic activity and subsequent maximal oxygen uptake response appears to show relatively stronger predictive potential. Individual variation in response to standardized training that cannot be explained by genetic influences may be related to the characteristics of the training program or lifestyle factors. Although standardized programs usually involve training prescribed by relative intensity and duration, some methods of relative exercise intensity prescription may be more successful in creating

Predicting spatial variations of tree species richness in tropical forests from high-resolution remote sensing.

Science.gov (United States)

Fricker, Geoffrey A; Wolf, Jeffrey A; Saatchi, Sassan S; Gillespie, Thomas W

2015-10-01

There is an increasing interest in identifying theories, empirical data sets, and remote-sensing metrics that can quantify tropical forest alpha diversity at a landscape scale. Quantifying patterns of tree species richness in the field is time consuming, especially in regions with over 100 tree species/ha. We examine species richness in a 50-ha plot in Barro Colorado Island in Panama and test if biophysical measurements of canopy reflectance from high-resolution satellite imagery and detailed vertical forest structure and topography from light detection and ranging (lidar) are associated with species richness across four tree size classes (>1, 1-10, >10, and >20 cm dbh) and three spatial scales (1, 0.25, and 0.04 ha). We use the 2010 tree inventory, including 204,757 individuals belonging to 301 species of freestanding woody plants or 166 ± 1.5 species/ha (mean ± SE), to compare with remote-sensing data. All remote-sensing metrics became less correlated with species richness as spatial resolution decreased from 1.0 ha to 0.04 ha and tree size increased from 1 cm to 20 cm dbh. When all stems with dbh > 1 cm in 1-ha plots were compared to remote-sensing metrics, standard deviation in canopy reflectance explained 13% of the variance in species richness. The standard deviations of canopy height and the topographic wetness index (TWI) derived from lidar were the best metrics to explain the spatial variance in species richness (15% and 24%, respectively). Using multiple regression models, we made predictions of species richness across Barro Colorado Island (BCI) at the 1-ha spatial scale for different tree size classes. We predicted variation in tree species richness among all plants (adjusted r² = 0.35) and trees with dbh > 10 cm (adjusted r² = 0.25). However, the best model results were for understory trees and shrubs (dbh 1-10 cm) (adjusted r² = 0.52) that comprise the majority of species richness in tropical forests. Our results indicate that high

Variation in population exposure in China as a result of differing human activities

Energy Technology Data Exchange (ETDEWEB)

Pan, Z.Q. [China Atomic Energy Authority, Beijing (China). Bureau of Safety, Protection and Health; Guo, M.Q. [China Nuclear Industry Huaqing Company, Beijing (China)

1995-08-01

The necessity of studying the variations in radiation levels dispassionately is discussed. Human activities may increase, but can also decrease, radiation dose to the population. Travel by air may cause a rise in population collective dose by 3.6 x 10 man.Sv, and travel by ship, train and vehicle may lead to a drop of 5.36 x 10{sup 2} man.Sv. Dwellings of coal cinder brick may increase collective dose by 3.5 x 10{sup 3} man.Sv, and buildings of reinforced concrete may decrease collective dose by 3.7 x 10{sup 3} man.Sv. It is inadequate to study only those activities which may increase radiation levels. (author).

Surface tensions of multi-component mixed inorganic/organic aqueous systems of atmospheric significance: measurements, model predictions and importance for cloud activation predictions

Directory of Open Access Journals (Sweden)

D. O. Topping

2007-01-01

Full Text Available In order to predict the physical properties of aerosol particles, it is necessary to adequately capture the behaviour of the ubiquitous complex organic components. One of the key properties which may affect this behaviour is the contribution of the organic components to the surface tension of aqueous particles in the moist atmosphere. Whilst the qualitative effect of organic compounds on solution surface tensions has been widely reported, our quantitative understanding on mixed organic and mixed inorganic/organic systems is limited. Furthermore, it is unclear whether models that exist in the literature can reproduce the surface tension variability for binary and higher order multi-component organic and mixed inorganic/organic systems of atmospheric significance. The current study aims to resolve both issues to some extent. Surface tensions of single and multiple solute aqueous solutions were measured and compared with predictions from a number of model treatments. On comparison with binary organic systems, two predictive models found in the literature provided a range of values resulting from sensitivity to calculations of pure component surface tensions. Results indicate that a fitted model can capture the variability of the measured data very well, producing the lowest average percentage deviation for all compounds studied. The performance of the other models varies with compound and choice of model parameters. The behaviour of ternary mixed inorganic/organic systems was unreliably captured by using a predictive scheme and this was dependent on the composition of the solutes present. For more atmospherically representative higher order systems, entirely predictive schemes performed poorly. It was found that use of the binary data in a relatively simple mixing rule, or modification of an existing thermodynamic model with parameters derived from binary data, was able to accurately capture the surface tension variation with concentration. Thus

Diverse models for the prediction of CDK4 inhibitory activity of ...

Indian Academy of Sciences (India)

employed for development of models for the prediction of CDK4 inhibitory activity using a dataset comprising of 52 analogues of ... index; molecular connectivity index; connective eccentricity topochemical index. 1. ... 80% of human cancers.

Activity Prediction of Schiff Base Compounds using Improved QSAR Models of Cinnamaldehyde Analogues and Derivatives

Directory of Open Access Journals (Sweden)

Hui Wang

2015-10-01

Full Text Available In past work, QSAR (quantitative structure-activity relationship models of cinnamaldehyde analogues and derivatives (CADs have been used to predict the activities of new chemicals based on their mass concentrations, but these approaches are not without shortcomings. Therefore, molar concentrations were used instead of mass concentrations to determine antifungal activity. New QSAR models of CADs against Aspergillus niger and Penicillium citrinum were established, and the molecular design of new CADs was performed. The antifungal properties of the designed CADs were tested, and the experimental Log AR values were in agreement with the predicted Log AR values. The results indicate that the improved QSAR models are more reliable and can be effectively used for CADs molecular design and prediction of the activity of CADs. These findings provide new insight into the development and utilization of cinnamaldehyde compounds.

Prediction of LDEF exposure to the ionizing radiation environment

Science.gov (United States)

Watts, J. W.; Armstrong, T. W.; Colborn, B. L.

1996-01-01

Predictions of the LDEF mission's trapped proton and electron and galactic cosmic ray proton exposures have been made using the currently accepted models with improved resolution near mission end and better modeling of solar cycle effects. An extension of previous calculations, to provide a more definitive description of the LDEF exposure to ionizing radiation, is represented by trapped proton and electron flux as a function of mission time, presented considering altitude and solar activity variation during the mission and the change in galactic cosmic ray proton flux over the mission. Modifications of the AP8MAX and AP8MIN fluence led to a reduction of fluence by 20%. A modified interpolation model developed by Daly and Evans resulted in 30% higher dose and activation levels, which better agreed with measured values than results predicted using the Vette model.

Variations in CT determination of target volume with active breath co-ordinate in radiotherapy for post-operative gastric cancer.

Science.gov (United States)

Li, Gui-Chao; Zhang, Zhen; Ma, Xue-Jun; Yu, Xiao-Li; Hu, Wei-Gang; Wang, Jia-Zhou; Li, Qi-Wen; Liang, Li-Ping; Shen, Li-Jun; Zhang, Hui; Fan, Ming

2016-01-01

To investigate interobserver and inter-CT variations in using the active breath co-ordinate technique in the determination of clinical tumour volume (CTV) and normal organs in post-operative gastric cancer radiotherapy. Ten gastric cancer patients were enrolled in our study, and four radiation oncologists independently determined the CTVs and organs at risk based on the CT simulation data. To determine interobserver and inter-CT variation, we evaluated the maximum dimensions, derived volume and distance between the centres of mass (CMs) of the CTVs. We assessed the reliability in CTV determination among the observers by conformity index (CI). The average volumes ± standard deviation (cm(3)) of the CTV, liver, left kidney and right kidney were 674 ± 138 (range, 332-969), 1000 ± 138 (range, 714-1320), 149 ± 13 (range, 104-183) and 141 ± 21 (range, 110-186) cm(3), respectively. The average inter-CT distances between the CMs of the CTV, liver, left kidney and right kidney were 0.40, 0.56, 0.65 and 0.6 cm, respectively; the interobserver values were 0.98, 0.53, 0.16 and 0.15 cm, respectively. In the volume size of CTV for post-operative gastric cancer, there were significant variations among multiple observers, whereas there was no variation between different CTs. The slices in which variations more likely occur were the slices of the lower verge of the hilum of the spleen and porta hepatis, then the paraoesophageal lymph nodes region and abdominal aorta, and the inferior vena cava, and the variation in the craniocaudal orientation from the interobserver was more predominant than that from inter-CT. First, this is the first study to evaluate the interobserver and inter-CT variations in the determination of the CTV and normal organs in gastric cancer with the use of the active breath co-ordinate technique. Second, we analysed the region where variations most likely occur. Third, we investigated the influence of interobserver variation on

Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.

Science.gov (United States)

Simm, Jaak; Klambauer, Günter; Arany, Adam; Steijaert, Marvin; Wegner, Jörg Kurt; Gustin, Emmanuel; Chupakhin, Vladimir; Chong, Yolanda T; Vialard, Jorge; Buijnsters, Peter; Velter, Ingrid; Vapirev, Alexander; Singh, Shantanu; Carpenter, Anne E; Wuyts, Roel; Hochreiter, Sepp; Moreau, Yves; Ceulemans, Hugo

2018-05-17

In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, whole organisms, or expensive or rare reagents. We hypothesized that data from a single high-throughput imaging assay can be repurposed to predict the biological activity of compounds in other assays, even those targeting alternate pathways or biological processes. Indeed, quantitative information extracted from a three-channel microscopy-based screen for glucocorticoid receptor translocation was able to predict assay-specific biological activity in two ongoing drug discovery projects. In these projects, repurposing increased hit rates by 50- to 250-fold over that of the initial project assays while increasing the chemical structure diversity of the hits. Our results suggest that data from high-content screens are a rich source of information that can be used to predict and replace customized biological assays. Copyright © 2018 Elsevier Ltd. All rights reserved.

THE FIRST RESULTS OF STUDIES OF TEMPORARY VARIATIONS IN SOILRADON ACTIVITY OF FAULTS IN WESTERN PRIBAIKALIE

Directory of Open Access Journals (Sweden)

К. Zh. Seminsky

2013-01-01

Full Text Available Radon concentrations in soil air are variable depending on factors that are considered external (planetary and internal (geodynamic relative to the Earth. In active fault zones, variations of gas emanations are most intense. A permanent monitoring station was established near Tyrgan settlement in Western Pribaikalie to study temporal variations of soil radon concentration, Q, in the faults of the Baikal rift, East Siberia. This station is located in the zone of the Primorsky normal fault that is the largest in the region. The station is equipped with radon radiometer PPA01M03 that records Q values every 85 minutes and also monitors a number of meteorological parameters, including atmospheric pressure, humidity, and air temperature.We analysed records of two measurement sessions (148 and 66 days covering a part of the year during which field measurement of Q are possible in the cold climate conditions of the area under study. According to the available monitoring data, variations of radon concentrations in the Primorsky fault zone may vary by more than one order of magnitude through a springsummerautumn period, and such variations are oscillatory. Significant changes of permeability in time occur due to intensive changes in the state of stresses of the rock massives under the impacts of the planetary and geodynamic factors. The influence of the first group of factors, i.e. planetary ones, is manifested by synchronous oscillations of radon concentrations and atmospheric pressure, which phases of occurrence are opposed. Domination of daily and fourday periods gives evidence that the state of stresses of the rock massives is impacted by the lunar tides and cyclonic phenomena associated with the interaction between the Earth and the Sun. The influence of the second group of factors, i.e. geodynamic ones, is suggested by an evident relation between radon emanations and seismic events, including the catastrophic earthquake in Japan (March 11, 2011, M=9

Can Research Design Explain Variation in Head Start Research Results? A Meta-Analysis of Cognitive and Achievement Outcomes

Science.gov (United States)

Shager, Hilary M.; Schindler, Holly S.; Magnuson, Katherine A.; Duncan, Greg J.; Yoshikawa, Hirokazu; Hart, Cassandra M. D.

2013-01-01

This study explores the extent to which differences in research design explain variation in Head Start program impacts. We employ meta-analytic techniques to predict effect sizes for cognitive and achievement outcomes as a function of the type and rigor of research design, quality and type of outcome measure, activity level of control group, and…

Structural maturation and brain activity predict future working memory capacity during childhood development.

Science.gov (United States)

Ullman, Henrik; Almeida, Rita; Klingberg, Torkel

2014-01-29

Human working memory capacity develops during childhood and is a strong predictor of future academic performance, in particular, achievements in mathematics and reading. Predicting working memory development is important for the early identification of children at risk for poor cognitive and academic development. Here we show that structural and functional magnetic resonance imaging data explain variance in children's working memory capacity 2 years later, which was unique variance in addition to that predicted using cognitive tests. While current working memory capacity correlated with frontoparietal cortical activity, the future capacity could be inferred from structure and activity in basal ganglia and thalamus. This gives a novel insight into the neural mechanisms of childhood development and supports the idea that neuroimaging can have a unique role in predicting children's cognitive development.

Length and activation dependent variations in muscle shear wave speed

International Nuclear Information System (INIS)

Chernak, L A; DeWall, R J; Lee, K S; Thelen, D G

2013-01-01

Muscle stiffness is known to vary as a result of a variety of disease states, yet current clinical methods for quantifying muscle stiffness have limitations including cost and availability. We investigated the capability of shear wave elastography (SWE) to measure variations in gastrocnemius shear wave speed induced via active contraction and passive stretch. Ten healthy young adults were tested. Shear wave speeds were measured using a SWE transducer positioned over the medial gastrocnemius at ankle angles ranging from maximum dorsiflexion to maximum plantarflexion. Shear wave speeds were also measured during voluntary plantarflexor contractions at a fixed ankle angle. Average shear wave speed increased significantly from 2.6 to 5.6 m s –1 with passive dorsiflexion and the knee in an extended posture, but did not vary with dorsiflexion when the gastrocnemius was shortened in a flexed knee posture. During active contractions, shear wave speed monotonically varied with the net ankle moment generated, reaching 8.3 m s –1 in the maximally contracted condition. There was a linear correlation between shear wave speed and net ankle moment in both the active and passive conditions; however, the slope of this linear relationship was significantly steeper for the data collected during passive loading conditions. The results show that SWE is a promising approach for quantitatively assessing changes in mechanical muscle loading. However, the differential effect of active and passive loading on shear wave speed makes it important to carefully consider the relevant loading conditions in which to use SWE to characterize in vivo muscle properties. (paper)

High biological variation of serum hyaluronic acid and Hepascore, a biochemical marker model for the prediction of liver fibrosis.

Science.gov (United States)

Rossi, Enrico; Adams, Leon A; Ching, Helena L; Bulsara, Max; MacQuillan, Gerry C; Jeffrey, Gary P

2013-05-01

Serum hyaluronic acid and biochemical models which require hyaluronic acid analysis are commonly used as predictors of liver fibrosis in patients with chronic liver disease, however biological variation data for hyaluronic acid are deficient. Four serial serum samples were obtained at weekly intervals from healthy volunteers and patients with chronic hepatitis B, chronic hepatitis C and non- alcoholic fatty liver disease (NAFLD; 20 in each group). The within-individual week-to-week variation (CVI) and reference change values for hyaluronic acid, α₂-macroglobulin and Hepascore were obtained. Hepascore is calculated from hyaluronic acid, α2-macroglobulin, bilirubin and γ-glutamyltransferase activity. Hyaluronic acid displayed large within-individual variation, the CVI values were 62% in healthy subjects, 38% in hepatitis C, 37% in hepatitis B and 36% in NAFLD patients. Hepascore CVIs were 43% in healthy subjects, 24% in hepatitis C, 28% in hepatitis B and 39% in NAFLD patients. α₂-Macroglobulin was much less variable with CVIs ranging from 4.4% to 7.6%. Bland-Altman plots of week-to-week variations showed rates of significant disagreement for samples collected in any 2 successive weeks varied from 5% in NAFLD patients to 8.3% in healthy subjects. When using non-fasting serum samples, hyaluronic acid and to a lesser extent, the Hepascore model display large within-individual variations in both health and chronic liver disease. This information is critical for interpreting the significance of both single measurements and changes in serial measurements.

Association of GSK-3β genetic variation with GSK-3β expression, prefrontal cortical thickness, prefrontal physiology, and schizophrenia.

Science.gov (United States)

Blasi, Giuseppe; Napolitano, Francesco; Ursini, Gianluca; Di Giorgio, Annabella; Caforio, Grazia; Taurisano, Paolo; Fazio, Leonardo; Gelao, Barbara; Attrotto, Maria Teresa; Colagiorgio, Lucia; Todarello, Giovanna; Piva, Francesco; Papazacharias, Apostolos; Masellis, Rita; Mancini, Marina; Porcelli, Annamaria; Romano, Raffaella; Rampino, Antonio; Quarto, Tiziana; Giulietti, Matteo; Lipska, Barbara K; Kleinman, Joel E; Popolizio, Teresa; Weinberger, Daniel R; Usiello, Alessandro; Bertolino, Alessandro

2013-08-01

OBJECTIVE Glycogen synthase kinase 3β (GSK-3β) is an enzyme implicated in neurodevelopmental processes with a broad range of substrates mediating several canonical signaling pathways in the brain. The authors investigated the association of variation in the GSK-3β gene with a series of progressively more complex phenotypes of relevance to schizophrenia, a neurodevelopmental disorder with strong genetic risk. METHOD Based on computer predictions, the authors investigated in humans the association of GSK-3β functional variation with 1) GSK-3β mRNA expression from postmortem prefrontal cortex, 2) GSK-3β and β-catenin protein expression from peripheral blood mononuclear cells (PBMCs), 3) prefrontal imaging phenotypes, and 4) diagnosis of schizophrenia. RESULTS Consistent with predictions, the TT genotype of a single-nucleotide polymorphism in GSK-3β (rs12630592) was associated with reduced GSK-3β mRNA from postmortem prefrontal cortex. Furthermore, this genotype was associated with GSK-3β protein expression and kinase activity, as well as with downstream effects on β-catenin expression in PBMCs. Finally, the TT genotype was associated with attenuated functional MRI prefrontal activity, reduced prefrontal cortical thickness, and diagnosis of schizophrenia. CONCLUSIONS These results suggest that GSK-3β variation is implicated in multiple phenotypes relevant to schizophrenia.

Cortisol and politics: variance in voting behavior is predicted by baseline cortisol levels.

Science.gov (United States)

French, Jeffrey A; Smith, Kevin B; Alford, John R; Guck, Adam; Birnie, Andrew K; Hibbing, John R

2014-06-22

Participation in electoral politics is affected by a host of social and demographics variables, but there is growing evidence that biological predispositions may also play a role in behavior related to political involvement. We examined the role of individual variation in hypothalamic-pituitary-adrenal (HPA) stress axis parameters in explaining differences in self-reported and actual participation in political activities. Self-reported political activity, religious participation, and verified voting activity in U.S. national elections were collected from 105 participants, who were subsequently exposed to a standardized (nonpolitical) psychosocial stressor. We demonstrated that lower baseline salivary cortisol in the late afternoon was significantly associated with increased actual voting frequency in six national elections, but not with self-reported non-voting political activity. Baseline cortisol predicted significant variation in voting behavior above and beyond variation accounted for by traditional demographic variables (particularly age of participant in our sample). Participation in religious activity was weakly (and negatively) associated with baseline cortisol. Our results suggest that HPA-mediated characteristics of social, cognitive, and emotional processes may exert an influence on a trait as complex as voting behavior, and that cortisol is a better predictor of actual voting behavior, as opposed to self-reported political activity. Copyright © 2014 Elsevier Inc. All rights reserved.

Cortisol and Politics: Variance in Voting Behavior is Predicted by Baseline Cortisol Levels

Science.gov (United States)

French, Jeffrey A.; Smith, Kevin B.; Alford, John R.; Guck, Adam; Birnie, Andrew K.; Hibbing, John R.

2014-01-01

Participation in electoral politics is affected by a host of social and demographics variables, but there is growing evidence that biological predispositions may also play a role in behavior related to political involvement. We examined the role of individual variation in hypothalamic-pituitary-adrenal (HPA) stress axis parameters in explaining differences in self-reported and actual participation in political activities. Self-reported political activity, religious participation, and verified voting activity in U.S. national elections were collected from 105 participants, who were subsequently exposed to a standardized (nonpolitical) psychosocial stressor. We demonstrated that lower baseline salivary cortisol in the late afternoon was significantly associated with increased actual voting frequency in six national elections, but not with self-reported non-voting political activity. Baseline cortisol predicted significant variation in voting behavior above and beyond variation accounted for by traditional demographic variables (particularly age of participant in our sample). Participation in religious activity was weakly (and negatively) associated with baseline cortisol. Our results suggest that HPA-mediated characteristics of social, cognitive, and emotional processes may exert an influence on a trait as complex as voting behavior, and that cortisol is a better predictor of actual voting behavior, as opposed to self-reported political activity. PMID:24835544

Time-specific ecological niche modeling predicts spatial dynamics of vector insects and human dengue cases.

Science.gov (United States)

Peterson, A Townsend; Martínez-Campos, Carmen; Nakazawa, Yoshinori; Martínez-Meyer, Enrique

2005-09-01

Numerous human diseases-malaria, dengue, yellow fever and leishmaniasis, to name a few-are transmitted by insect vectors with brief life cycles and biting activity that varies in both space and time. Although the general geographic distributions of these epidemiologically important species are known, the spatiotemporal variation in their emergence and activity remains poorly understood. We used ecological niche modeling via a genetic algorithm to produce time-specific predictive models of monthly distributions of Aedes aegypti in Mexico in 1995. Significant predictions of monthly mosquito activity and distributions indicate that predicting spatiotemporal dynamics of disease vector species is feasible; significant coincidence with human cases of dengue indicate that these dynamics probably translate directly into transmission of dengue virus to humans. This approach provides new potential for optimizing use of resources for disease prevention and remediation via automated forecasting of disease transmission risk.

Evaluation of the NCEP CFSv2 45-day Forecasts for Predictability of Intraseasonal Tropical Storm Activities

Science.gov (United States)

Schemm, J. E.; Long, L.; Baxter, S.

2013-12-01

Evaluation of the NCEP CFSv2 45-day Forecasts for Predictability of Intraseasonal Tropical Storm Activities Jae-Kyung E. Schemm, Lindsey Long and Stephen Baxter Climate Prediction Center, NCEP/NWS/NOAA Predictability of intraseasonal tropical storm (TS) activities is assessed using the 1999-2010 CFSv2 hindcast suite. Weekly TS activities in the CFSv2 45-day forecasts were determined using the TS detection and tracking method devised by Carmago and Zebiak (2002). The forecast periods are divided into weekly intervals for Week 1 through Week 6, and also the 30-day mean. The TS activities in those intervals are compared to the observed activities based on the NHC HURDAT and JTWC Best Track datasets. The CFSv2 45-day hindcast suite is made of forecast runs initialized at 00, 06, 12 and 18Z every day during the 1999 - 2010 period. For predictability evaluation, forecast TS activities are analyzed based on 20-member ensemble forecasts comprised of 45-day runs made during the most recent 5 days prior to the verification period. The forecast TS activities are evaluated in terms of the number of storms, genesis locations and storm tracks during the weekly periods. The CFSv2 forecasts are shown to have a fair level of skill in predicting the number of storms over the Atlantic Basin with the temporal correlation scores ranging from 0.73 for Week 1 forecasts to 0.63 for Week 6, and the average RMS errors ranging from 0.86 to 1.07 during the 1999-2010 hurricane season. Also, the forecast track density distribution and false alarm statistics are compiled using the hindcast analyses. In real-time applications of the intraseasonal TS activity forecasts, the climatological TS forecast statistics will be used to make the model bias corrections in terms of the storm counts, track distribution and removal of false alarms. An operational implementation of the weekly TS activity prediction is planned for early 2014 to provide an objective input for the CPC's Global Tropical Hazards

Oxytocin receptor gene variation predicts subjective responses to MDMA.

Science.gov (United States)

Bershad, Anya K; Weafer, Jessica J; Kirkpatrick, Matthew G; Wardle, Margaret C; Miller, Melissa A; de Wit, Harriet

2016-12-01

3,4-Methylenedioxymethamphetamine (MDMA, "ecstasy") enhances desire to socialize and feelings of empathy, which are thought to be related to increased oxytocin levels. Thus, variation in the oxytocin receptor gene (OXTR) may influence responses to the drug. Here, we examined the influence of a single OXTR nucleotide polymorphism (SNP) on responses to MDMA in humans. Based on findings that carriers of the A allele at rs53576 exhibit reduced sensitivity to oxytocin-induced social behavior, we hypothesized that these individuals would show reduced subjective responses to MDMA, including sociability. In this three-session, double blind, within-subjects study, healthy volunteers with past MDMA experience (N = 68) received a MDMA (0, 0.75 mg/kg, and 1.5 mg/kg) and provided self-report ratings of sociability, anxiety, and drug effects. These responses were examined in relation to rs53576. MDMA (1.5 mg/kg) did not increase sociability in individuals with the A/A genotype as it did in G allele carriers. The genotypic groups did not differ in responses at the lower MDMA dose, or in cardiovascular or other subjective responses. These findings are consistent with the idea that MDMA-induced sociability is mediated by oxytocin, and that variation in the oxytocin receptor gene may influence responses to the drug.

Inferior frontal gyrus activation predicts individual differences in perceptual learning of cochlear-implant simulations.

Science.gov (United States)

Eisner, Frank; McGettigan, Carolyn; Faulkner, Andrew; Rosen, Stuart; Scott, Sophie K

2010-05-26

This study investigated the neural plasticity associated with perceptual learning of a cochlear implant (CI) simulation. Normal-hearing listeners were trained with vocoded and spectrally shifted speech simulating a CI while cortical responses were measured with functional magnetic resonance imaging (fMRI). A condition in which the vocoded speech was spectrally inverted provided a control for learnability and adaptation. Behavioral measures showed considerable individual variability both in the ability to learn to understand the degraded speech, and in phonological working memory capacity. Neurally, left-lateralized regions in superior temporal sulcus and inferior frontal gyrus (IFG) were sensitive to the learnability of the simulations, but only the activity in prefrontal cortex correlated with interindividual variation in intelligibility scores and phonological working memory. A region in left angular gyrus (AG) showed an activation pattern that reflected learning over the course of the experiment, and covariation of activity in AG and IFG was modulated by the learnability of the stimuli. These results suggest that variation in listeners' ability to adjust to vocoded and spectrally shifted speech is partly reflected in differences in the recruitment of higher-level language processes in prefrontal cortex, and that this variability may further depend on functional links between the left inferior frontal gyrus and angular gyrus. Differences in the engagement of left inferior prefrontal cortex, and its covariation with posterior parietal areas, may thus underlie some of the variation in speech perception skills that have been observed in clinical populations of CI users.

Prediction of in vitro and in vivo oestrogen receptor activity using hierarchical clustering

Science.gov (United States)

In this study, hierarchical clustering classification models were developed to predict in vitro and in vivo oestrogen receptor (ER) activity. Classification models were developed for binding, agonist, and antagonist in vitro ER activity and for mouse in vivo uterotrophic ER bindi...

School and class-level variations and patterns of physical activity: a multilevel analysis of Danish high school students.

Science.gov (United States)

Steenholt, Carina Bjørnskov; Pisinger, Veronica Sofie Clara; Danquah, Ida Høgstedt; Tolstrup, Janne Schurmann

2018-02-14

There is limited knowledge of physical activity (PA) patterns among high school students. High schools plays an important role as context for the students, but it is uncertain to what extent schools influence student participation in PA during leisure time. The purpose of this study is to describe patterns of PA and assess variations between schools and classes in PA, in a large cohort of Danish high school students. Self-reported cross-sectional data came from The Danish National Youth Study, comprising a total of 70,674 students attending 119 different schools and 3213 classes. Multilevel logistic regressions were applied to evaluate the association between socio-demographic variables and patterns of PA, and to assess the impact of schools and classes on PA measures. Students whose parents have achieved a lower level of education, older students and girls of perceived ethnic minority generally participated less in several forms of PA during leisure time. Substantial variations between schools were observed in terms of participation in PA at school during leisure time and in terms of use of active transportation to and from school. The school-level accounted for 9% (intra-class correlation coefficient (ICC) = 0.09 (95% CI: 0.06-0.11)) and 8% (ICC = 0.08 (95% CI: 0.07-0.11)) of the variation for participation in PA during leisure time and active transportation. Overall, students whose parents achieved a lower level of education, older students and girls of perceived ethnic minority represent vulnerable groups in relation to participation in several forms of PA during leisure time. The ICCs indicate that schools, in particular, have the potential to influence participation in PA at school during leisure time and active transportation to and from school. Thus, high schools should encourage and facilitate activities aimed at engaging students in PA during leisure time as well as encourage active transportation.

Mining geographic variations of Plasmodium vivax for active surveillance: a case study in China.

Science.gov (United States)

Shi, Benyun; Tan, Qi; Zhou, Xiao-Nong; Liu, Jiming

2015-05-27

, the proposed space-time model is general and can readily be extended to investigate geographic variations of other diseases. Practically, such a computational model will offer new insights into active surveillance and strategic planning for disease surveillance and control.

Proteomic and biochemical analyses of short-tailed pit viper (Gloydius brevicaudus) venom: age-related variation and composition-activity correlation.

Science.gov (United States)

Gao, Jian-Fang; Wang, Jin; He, Ying; Qu, Yan-Fu; Lin, Long-Hui; Ma, Xiao-Mei; Ji, Xiang

2014-06-13

We conducted an in-depth analysis of the proteomic and biochemical profiles of the venom of neonate and adult short-tailed pit vipers (Gloydius brevicaudus). Identified proteins were assigned to a few main toxin families. Disintegrin, phospholipase A2 (PLA2), serine proteinase, cysteine-rich secretory protein, C-type lectin-like protein, l-amino acid oxidase and snake venom metalloproteinase (SVMP) were detected in both venoms, while 5'-nucleotidase was detected only in the adult venom. SVMP was the predominant protein family in both venoms (neonate: 65.7%; adult: 64.4%), followed by PLA2 (neonate: 13.4%; adult: 25.0%). Antivenomic analysis revealed that commercial G. brevicaudus antivenom almost neutralized the chromatographic peaks with medium and high molecular masses in both venoms, but did not completely recognize peaks with low molecular mass. Toxicological and enzymatic activities show remarkable age-related variation in G. brevicaudus venom, probably resulting from variation in venom composition. Our data demonstrate age-related variation across venomics, antivenomics and biochemical profiles of G. brevicaudus venom, and have implications for the management of G. brevicaudus bites, including improving antivenom preparation by combining both venoms. This study investigates the composition and biochemical activity of neonate and adult Gloydius brevicaudus venoms. We found remarkable age-related variation in venom biological activity, likely the result of variation in venom composition. Antivenomics analysis was used to explore difference in neonate and adult G. brevicaudus venoms. Our findings have implications for the diagnosis and clinical management of G. brevicaudus bites, and the design of venom mixtures that will increase the efficacy of commercial antivenom. This article is part of a Special Issue entitled: Proteomics of non-model organisms. Copyright © 2014 Elsevier B.V. All rights reserved.

[Fluctuations in biophysical measurements as a result of variations in solar activity].

Science.gov (United States)

Peterson, T F

1995-01-01

A theory is proposed to explain variations in the net electrical charge of biological substances at the Earth's surface. These are shown to occur in association with changes in the solar wind and geomagnetic field. It is suggested that a liquid dielectric's net volume charge will imitate pH effects, influence chemical reaction rates, and alter ion transfer mechanisms in biophysical systems. An experiment is described which measures dielectric volume charge, or non-neutrality, to allow correlation of this property with daily, 28-day, and 11-year fluctuation patterns in geophysical and satellite data associated with solar activity and the interplanetary magnetic field.

QSAR classification models for the prediction of endocrine disrupting activity of brominated flame retardants.

Science.gov (United States)

Kovarich, Simona; Papa, Ester; Gramatica, Paola

2011-06-15

The identification of potential endocrine disrupting (ED) chemicals is an important task for the scientific community due to their diffusion in the environment; the production and use of such compounds will be strictly regulated through the authorization process of the REACH regulation. To overcome the problem of insufficient experimental data, the quantitative structure-activity relationship (QSAR) approach is applied to predict the ED activity of new chemicals. In the present study QSAR classification models are developed, according to the OECD principles, to predict the ED potency for a class of emerging ubiquitary pollutants, viz. brominated flame retardants (BFRs). Different endpoints related to ED activity (i.e. aryl hydrocarbon receptor agonism and antagonism, estrogen receptor agonism and antagonism, androgen and progesterone receptor antagonism, T4-TTR competition, E2SULT inhibition) are modeled using the k-NN classification method. The best models are selected by maximizing the sensitivity and external predictive ability. We propose simple QSARs (based on few descriptors) characterized by internal stability, good predictive power and with a verified applicability domain. These models are simple tools that are applicable to screen BFRs in relation to their ED activity, and also to design safer alternatives, in agreement with the requirements of REACH regulation at the authorization step. Copyright © 2011 Elsevier B.V. All rights reserved.

Prediction of flare activity of stellar aggregates. I. Theoretical part

International Nuclear Information System (INIS)

Mnatsakanyan, M.A.; Mirzoyan, A.L.

1989-01-01

The problem is posed of predicting the number n k (t) of flare stars that have exhibited precisely k flares by the time t on the basis of data on these quantities known during the total time T of observations of the aggregate. The problem posed by Ambartsumyan of determining the distribution function f(ν) of the true frequency of stellar flares from known chronology of these data is equivalent to the limiting form of their formulation - prediction in the future over an infinitely long time. An exact analytic solution of the problem obtained without any assumption about the function f(ν) is given. It permits prediction of the steady flare activity of the aggregate into both the future and the (known) past. It follows from this solution that prediction into the future is in principle impossible to times that exceed the doubled time 2T of the available observations (this means that the problem of determining of the function f(ν) cannot be solved). Moreover, because of the unavoidable fluctuations in the observational data n k (T), such prediction is limited to even shorter times, and these are shorter the larger the value of k. Prediction into the past and into the future on the basis of the data n k (T) at the present time and its possible errors due to small fluctuations in these data are illustrated for the examples of the Pleiades and the Orion aggregate

Evaluation of the interindividual human variation in bioactivation of methyleugenol using physiologically based kinetic modeling and Monte Carlo simulations

International Nuclear Information System (INIS)

Al-Subeihi, Ala' A.A.; Alhusainy, Wasma; Kiwamoto, Reiko; Spenkelink, Bert; Bladeren, Peter J. van; Rietjens, Ivonne M.C.M.; Punt, Ans

2015-01-01

The present study aims at predicting the level of formation of the ultimate carcinogenic metabolite of methyleugenol, 1′-sulfooxymethyleugenol, in the human population by taking variability in key bioactivation and detoxification reactions into account using Monte Carlo simulations. Depending on the metabolic route, variation was simulated based on kinetic constants obtained from incubations with a range of individual human liver fractions or by combining kinetic constants obtained for specific isoenzymes with literature reported human variation in the activity of these enzymes. The results of the study indicate that formation of 1′-sulfooxymethyleugenol is predominantly affected by variation in i) P450 1A2-catalyzed bioactivation of methyleugenol to 1′-hydroxymethyleugenol, ii) P450 2B6-catalyzed epoxidation of methyleugenol, iii) the apparent kinetic constants for oxidation of 1′-hydroxymethyleugenol, and iv) the apparent kinetic constants for sulfation of 1′-hydroxymethyleugenol. Based on the Monte Carlo simulations a so-called chemical-specific adjustment factor (CSAF) for intraspecies variation could be derived by dividing different percentiles by the 50th percentile of the predicted population distribution for 1′-sulfooxymethyleugenol formation. The obtained CSAF value at the 90th percentile was 3.2, indicating that the default uncertainty factor of 3.16 for human variability in kinetics may adequately cover the variation within 90% of the population. Covering 99% of the population requires a larger uncertainty factor of 6.4. In conclusion, the results showed that adequate predictions on interindividual human variation can be made with Monte Carlo-based PBK modeling. For methyleugenol this variation was observed to be in line with the default variation generally assumed in risk assessment. - Highlights: • Interindividual human differences in methyleugenol bioactivation were simulated. • This was done using in vitro incubations, PBK modeling

Evaluation of the interindividual human variation in bioactivation of methyleugenol using physiologically based kinetic modeling and Monte Carlo simulations

Energy Technology Data Exchange (ETDEWEB)

Al-Subeihi, Ala' A.A., E-mail: subeihi@yahoo.com [Division of Toxicology, Wageningen University, Tuinlaan 5, 6703 HE Wageningen (Netherlands); BEN-HAYYAN-Aqaba International Laboratories, Aqaba Special Economic Zone Authority (ASEZA), P. O. Box 2565, Aqaba 77110 (Jordan); Alhusainy, Wasma; Kiwamoto, Reiko; Spenkelink, Bert [Division of Toxicology, Wageningen University, Tuinlaan 5, 6703 HE Wageningen (Netherlands); Bladeren, Peter J. van [Division of Toxicology, Wageningen University, Tuinlaan 5, 6703 HE Wageningen (Netherlands); Nestec S.A., Avenue Nestlé 55, 1800 Vevey (Switzerland); Rietjens, Ivonne M.C.M.; Punt, Ans [Division of Toxicology, Wageningen University, Tuinlaan 5, 6703 HE Wageningen (Netherlands)

2015-03-01

The present study aims at predicting the level of formation of the ultimate carcinogenic metabolite of methyleugenol, 1′-sulfooxymethyleugenol, in the human population by taking variability in key bioactivation and detoxification reactions into account using Monte Carlo simulations. Depending on the metabolic route, variation was simulated based on kinetic constants obtained from incubations with a range of individual human liver fractions or by combining kinetic constants obtained for specific isoenzymes with literature reported human variation in the activity of these enzymes. The results of the study indicate that formation of 1′-sulfooxymethyleugenol is predominantly affected by variation in i) P450 1A2-catalyzed bioactivation of methyleugenol to 1′-hydroxymethyleugenol, ii) P450 2B6-catalyzed epoxidation of methyleugenol, iii) the apparent kinetic constants for oxidation of 1′-hydroxymethyleugenol, and iv) the apparent kinetic constants for sulfation of 1′-hydroxymethyleugenol. Based on the Monte Carlo simulations a so-called chemical-specific adjustment factor (CSAF) for intraspecies variation could be derived by dividing different percentiles by the 50th percentile of the predicted population distribution for 1′-sulfooxymethyleugenol formation. The obtained CSAF value at the 90th percentile was 3.2, indicating that the default uncertainty factor of 3.16 for human variability in kinetics may adequately cover the variation within 90% of the population. Covering 99% of the population requires a larger uncertainty factor of 6.4. In conclusion, the results showed that adequate predictions on interindividual human variation can be made with Monte Carlo-based PBK modeling. For methyleugenol this variation was observed to be in line with the default variation generally assumed in risk assessment. - Highlights: • Interindividual human differences in methyleugenol bioactivation were simulated. • This was done using in vitro incubations, PBK modeling

Why Does Working Memory Capacity Predict Variation in Reading Comprehension? On the Influence of Mind Wandering and Executive Attention

Science.gov (United States)

McVay, Jennifer C.; Kane, Michael J.

2012-01-01

Some people are better readers than others, and this variation in comprehension ability is predicted by measures of working memory capacity (WMC). The primary goal of this study was to investigate the mediating role of mind wandering experiences in the association between WMC and normal individual differences in reading comprehension, as predicted by the executive-attention theory of WMC (e.g., Engle & Kane, 2004). We used a latent-variable, structural-equation-model approach, testing skilled adult readers on three WMC span tasks, seven varied reading comprehension tasks, and three attention-control tasks. Mind wandering was assessed using experimenter-scheduled thought probes during four different tasks (two reading, two attention-control tasks). The results support the executive-attention theory of WMC. Mind wandering across the four tasks loaded onto a single latent factor, reflecting a stable individual difference. Most importantly, mind wandering was a significant mediator in the relationship between WMC and reading comprehension, suggesting that the WMC-comprehension correlation is driven, in part, by attention control over intruding thoughts. We discuss implications for theories of WMC, attention control, and reading comprehension. PMID:21875246

Why does working memory capacity predict variation in reading comprehension? On the influence of mind wandering and executive attention.

Science.gov (United States)

McVay, Jennifer C; Kane, Michael J

2012-05-01

Some people are better readers than others, and this variation in comprehension ability is predicted by measures of working memory capacity (WMC). The primary goal of this study was to investigate the mediating role of mind-wandering experiences in the association between WMC and normal individual differences in reading comprehension, as predicted by the executive-attention theory of WMC (e.g., Engle & Kane, 2004). We used a latent-variable, structural-equation-model approach, testing skilled adult readers on 3 WMC span tasks, 7 varied reading-comprehension tasks, and 3 attention-control tasks. Mind wandering was assessed using experimenter-scheduled thought probes during 4 different tasks (2 reading, 2 attention-control). The results support the executive-attention theory of WMC. Mind wandering across the 4 tasks loaded onto a single latent factor, reflecting a stable individual difference. Most important, mind wandering was a significant mediator in the relationship between WMC and reading comprehension, suggesting that the WMC-comprehension correlation is driven, in part, by attention control over intruding thoughts. We discuss implications for theories of WMC, attention control, and reading comprehension.

Predicting facial characteristics from complex polygenic variations

DEFF Research Database (Denmark)

Fagertun, Jens; Wolffhechel, Karin Marie Brandt; Pers, Tune

2015-01-01

Research into the importance of the human genome in the context of facial appearance is receiving increasing attention and has led to the detection of several Single Nucleotide Polymorphisms (SNPs) of importance. In this work we attempt a holistic approach predicting facial characteristics from...... genetic principal components across a population of 1,266 individuals. For this we perform a genome-wide association analysis to select a large number of SNPs linked to specific facial traits, recode these to genetic principal components and then use these principal components as predictors for facial...

Individual variation in social aggression and the probability of inheritance: theory and a field test.

Science.gov (United States)

Cant, Michael A; Llop, Justine B; Field, Jeremy

2006-06-01

Recent theory suggests that much of the wide variation in individual behavior that exists within cooperative animal societies can be explained by variation in the future direct component of fitness, or the probability of inheritance. Here we develop two models to explore the effect of variation in future fitness on social aggression. The models predict that rates of aggression will be highest toward the front of the queue to inherit and will be higher in larger, more productive groups. A third prediction is that, in seasonal animals, aggression will increase as the time available to inherit the breeding position runs out. We tested these predictions using a model social species, the paper wasp Polistes dominulus. We found that rates of both aggressive "displays" (aimed at individuals of lower rank) and aggressive "tests" (aimed at individuals of higher rank) decreased down the hierarchy, as predicted by our models. The only other significant factor affecting aggression rates was date, with more aggression observed later in the season, also as predicted. Variation in future fitness due to inheritance rank is the hidden factor accounting for much of the variation in aggressiveness among apparently equivalent individuals in this species.

A Trap Motion in Validating Muscle Activity Prediction from Musculoskeletal Model using EMG

NARCIS (Netherlands)

Wibawa, A. D.; Verdonschot, N.; Halbertsma, J.P.K.; Burgerhof, J.G.M.; Diercks, R.L.; Verkerke, G. J.

2016-01-01

Musculoskeletal modeling nowadays is becoming the most common tool for studying and analyzing human motion. Besides its potential in predicting muscle activity and muscle force during active motion, musculoskeletal modeling can also calculate many important kinetic data that are difficult to measure

Intraspecific variation in 137Cs activity concentration in sporocarps of Suillus variegatus in seven Swedish populations

International Nuclear Information System (INIS)

Dahlberg, Anders; Nikolova, Ivanka; Johanson, K.-J.

1997-01-01

Following the Chernobyl accident in 1986, sporocarps of Suillus variegatus in Sweden showed a large amount of individual variation in concentration of 137 Cs activity. Our aim was to determine the degrees to which this variability in sporocarp 137 Cs levels could be explained by differences between (i) local populations, (ii) fungal genets and (iii) locations within genets. Five populations in a 100-yr-old Scots pine forest, located within a 1 km 2 area, and two populations in Scots pine/Norway spruce forest, located 40 km north-west of Uppsala, were investigated. In total, 154 sporocarps were analysed to determine their 137 Cs content. Of these, the genetic affiliations of 86 were successfully characterized using somatic incompatibility reactions. Twenty-six genets were found which, on average, consisted of 6.5 sporocarps. The genets averaged 7.5 m in size, measured as the length between the most distant sporocarps. The mean sporocarp 137 Cs level was 67.1 ± 2.8 kBq kgsup(-1) D.W. (range between 13.6 and 182). According to analyses of variance, within-population variation accounted for 60% of the total variation in 137 Cs levels, while 40% was ascribed to variation among populations. Within a population, 137 Cs levels did not generally differ significantly between genets. Plausible reasons for intraspecific variation in radiocaesium content in sporocarps are discussed. (author)

School and class-level variations and patterns of physical activity

DEFF Research Database (Denmark)

Steenholt, Carina Bjørnskov; Pisinger, Veronica Sofie Clara; Danquah, Ida Høgstedt

2018-01-01

is to describe patterns of PA and assess variations between schools and classes in PA, in a large cohort of Danish high school students. METHODS: Self-reported cross-sectional data came from The Danish National Youth Study, comprising a total of 70,674 students attending 119 different schools and 3213 classes....... Multilevel logistic regressions were applied to evaluate the association between socio-demographic variables and patterns of PA, and to assess the impact of schools and classes on PA measures. RESULTS: Students whose parents have achieved a lower level of education, older students and girls of perceived......BACKGROUND: There is limited knowledge of physical activity (PA) patterns among high school students. High schools plays an important role as context for the students, but it is uncertain to what extent schools influence student participation in PA during leisure time. The purpose of this study...

Spontaneous and UV-induced variations in the activity of biomass synthesis in Candida utilis haploid and diploid strains

International Nuclear Information System (INIS)

Kondrat'eva, T.F.; Lin'kova, M.A.; Lobacheva, N.A.

1988-01-01

Candida utilis diploid strains have greater variations induced by UV irradiation in the activity of biomass synthesis as compared with the parent haploid culture. Clones with an activity of the synthesis greater that the mean population one appear more frequently in the diploid strains. Mathematical analysis has confirmed the significance of the results and the hypothesis according to which the frequency of variants more active in biomass synthesis rises after the action of UV

Predictive Duty Cycle Control of Three-Phase Active-Front-End Rectifiers

DEFF Research Database (Denmark)

Song, Zhanfeng; Tian, Yanjun; Chen, Wei

2016-01-01

This paper proposed an on-line optimizing duty cycle control approach for three-phase active-front-end rectifiers, aiming to obtain the optimal control actions under different operating conditions. Similar to finite control set model predictive control strategy, a cost function previously...

Active Mirror Predictive and Requirements Verification Software (AMP-ReVS)

Science.gov (United States)

Basinger, Scott A.

2012-01-01

This software is designed to predict large active mirror performance at various stages in the fabrication lifecycle of the mirror. It was developed for 1-meter class powered mirrors for astronomical purposes, but is extensible to other geometries. The package accepts finite element model (FEM) inputs and laboratory measured data for large optical-quality mirrors with active figure control. It computes phenomenological contributions to the surface figure error using several built-in optimization techniques. These phenomena include stresses induced in the mirror by the manufacturing process and the support structure, the test procedure, high spatial frequency errors introduced by the polishing process, and other process-dependent deleterious effects due to light-weighting of the mirror. Then, depending on the maturity of the mirror, it either predicts the best surface figure error that the mirror will attain, or it verifies that the requirements for the error sources have been met once the best surface figure error has been measured. The unique feature of this software is that it ties together physical phenomenology with wavefront sensing and control techniques and various optimization methods including convex optimization, Kalman filtering, and quadratic programming to both generate predictive models and to do requirements verification. This software combines three distinct disciplines: wavefront control, predictive models based on FEM, and requirements verification using measured data in a robust, reusable code that is applicable to any large optics for ground and space telescopes. The software also includes state-of-the-art wavefront control algorithms that allow closed-loop performance to be computed. It allows for quantitative trade studies to be performed for optical systems engineering, including computing the best surface figure error under various testing and operating conditions. After the mirror manufacturing process and testing have been completed, the

Predicting the variation in Echinogammarus marinus at its southernmost limits under global warming scenarios: can the sex-ratio make a difference?

Science.gov (United States)

Guerra, Alexandra; Leite, Nuno; Marques, João Carlos; Ford, Alex T; Martins, Irene

2014-01-01

Understanding the environmental parameters that constrain the distribution of a species at its latitudinal extremes is critical for predicting how ecosystems react to climate change. Our first aim was to predict the variation in the amphipod populations of Echinogammarus marinus from the southernmost limit of its distribution under global warming scenarios. Our second aim was to test whether sex-ratio fluctuations - a mechanism frequently displayed by amphipods - respond to the variations in populations under altered climate conditions. To achieve these aims, scenarios were run with a validated model of E. marinus populations. Simulations were divided into: phase I - simulation of the effect of climate change on amphipod populations, and phase II - simulation of the effect of climate change on populations with male and female proportions. In both phases, temperature (T), salinity (S) and temperature and salinity (T-S) were tested. Results showed that E. marinus populations are highly sensitive to increases in temperature (>2 °C), which has adverse effects on amphipod recruitment and growth. Results from the climate change scenarios coupled with the sex-ratio fluctuations depended largely on the degree of female bias within population. Temperature increase of 2 °C had less impact on female-biased populations, particularly when conjugated with increases in salinity. Male-biased populations were highly sensitive to any variation in temperature and/or salinity; these populations exhibited a long-term decline in density. Simulations in which temperature increased more than 4 °C led to a continuous decline in the E. marinus population. According to this work, E. marinus populations at their southernmost limit are vulnerable to global warming. We anticipate that in Europe, temperature increases of 2 °C will incite a withdrawal of the population of 5°N from the amphipod species located at southernmost geographical borders. This effect is discussed in relation to the

Long-term radial-velocity variations of the Sun as a star: The HARPS view

Science.gov (United States)

Lanza, A. F.; Molaro, P.; Monaco, L.; Haywood, R. D.

2016-03-01

Context. Stellar radial velocities play a fundamental role in the discovery of extrasolar planets and the measurement of their physical parameters as well as in the study of stellar physical properties. Aims: We investigate the impact of the solar activity on the radial velocity of the Sun using the HARPS spectrograph to obtain measurements that can be directly compared with those acquired in the extrasolar planet search programmes. Methods: We used the Moon, the Galilean satellites, and several asteroids as reflectors to measure the radial velocity of the Sun as a star and correlated this velocity with disc-integrated chromospheric and magnetic indexes of solar activity that are similar to stellar activity indexes. We discuss in detail the systematic effects that affect our measurements and the methods to account for them. Results: We find that the radial velocity of the Sun as a star is positively correlated with the level of its chromospheric activity at ~95 percent significance level. The amplitude of the long-term variation measured in the 2006-2014 period is 4.98 ± 1.44 m/s, which is in good agreement with model predictions. The standard deviation of the residuals obtained by subtracting a linear best fit is 2.82 m/s and is due to the rotation of the reflecting bodies and the intrinsic variability of the Sun on timescales shorter than the activity cycle. A correlation with a lower significance is detected between the radial velocity and the mean absolute value of the line-of-sight photospheric magnetic field flux density. Conclusions: Our results confirm similar correlations found in other late-type main-sequence stars and provide support to the predictions of radial velocity variations induced by stellar activity based on current models.

Predicting Antitumor Activity of Peptides by Consensus of Regression Models Trained on a Small Data Sample

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Ivanka Jerić

2011-11-01

Full Text Available Predicting antitumor activity of compounds using regression models trained on a small number of compounds with measured biological activity is an ill-posed inverse problem. Yet, it occurs very often within the academic community. To counteract, up to some extent, overfitting problems caused by a small training data, we propose to use consensus of six regression models for prediction of biological activity of virtual library of compounds. The QSAR descriptors of 22 compounds related to the opioid growth factor (OGF, Tyr-Gly-Gly-Phe-Met with known antitumor activity were used to train regression models: the feed-forward artificial neural network, the k-nearest neighbor, sparseness constrained linear regression, the linear and nonlinear (with polynomial and Gaussian kernel support vector machine. Regression models were applied on a virtual library of 429 compounds that resulted in six lists with candidate compounds ranked by predicted antitumor activity. The highly ranked candidate compounds were synthesized, characterized and tested for an antiproliferative activity. Some of prepared peptides showed more pronounced activity compared with the native OGF; however, they were less active than highly ranked compounds selected previously by the radial basis function support vector machine (RBF SVM regression model. The ill-posedness of the related inverse problem causes unstable behavior of trained regression models on test data. These results point to high complexity of prediction based on the regression models trained on a small data sample.

The seasonal variations of allelopathic activity and allelopathic substances in Brachiaria brizantha.

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Kobayashi, Ai; Kato-Noguchi, Hisashi

2015-12-01

Controlling weeds through allelopathy is one strategy to reduce dependency on synthetic herbicides. The plant shoots of the grass Brachiaria brizantha incorporated into the field soil were found to inhibit the growth of several plant species. We investigated the variations of allelopathic activity and allelopathic substances in B. brizantha harvested in June, October and January. All extracts of B. brizantha obtained from June, October and January inhibited the root and shoot growth of cress, lettuce, Phleum pretense and Lolium multiflorum in a concentration dependent manner. However, the inhibitory activity of B. brizantha of June and October was greater than that of B. brizantha of January. Concentrations of three potent allelopathic active substances, (6R,9S)-3-oxo-α-ionol, (6R,9R)-3-oxo-α-ionol and 4-ketopinoresinol were also greater in B. brizantha of June and October than those in B. brizantha of January. The results suggest that the allelopathic activity and the levels of those allelopathic active substances are greater in B. brizantha of June and October than those in B. brizantha of January. It is possible that B. brizantha could be useful for a weed suppressive residue or soil additive materials in the variety of agricultural settings to develop sustainable agriculture options. The effectiveness of B. brizantha of June and October as a weed suppressive agent may be greater than that of January.

Variational methods in molecular modeling

CERN Document Server

2017-01-01

This book presents tutorial overviews for many applications of variational methods to molecular modeling. Topics discussed include the Gibbs-Bogoliubov-Feynman variational principle, square-gradient models, classical density functional theories, self-consistent-field theories, phase-field methods, Ginzburg-Landau and Helfrich-type phenomenological models, dynamical density functional theory, and variational Monte Carlo methods. Illustrative examples are given to facilitate understanding of the basic concepts and quantitative prediction of the properties and rich behavior of diverse many-body systems ranging from inhomogeneous fluids, electrolytes and ionic liquids in micropores, colloidal dispersions, liquid crystals, polymer blends, lipid membranes, microemulsions, magnetic materials and high-temperature superconductors. All chapters are written by leading experts in the field and illustrated with tutorial examples for their practical applications to specific subjects. With emphasis placed on physical unders...

Do Urinary Cystine Parameters Predict Clinical Stone Activity?

Science.gov (United States)

Friedlander, Justin I; Antonelli, Jodi A; Canvasser, Noah E; Morgan, Monica S C; Mollengarden, Daniel; Best, Sara; Pearle, Margaret S

2018-02-01

An accurate urinary predictor of stone recurrence would be clinically advantageous for patients with cystinuria. A proprietary assay (Litholink, Chicago, Illinois) measures cystine capacity as a potentially more reliable estimate of stone forming propensity. The recommended capacity level to prevent stone formation, which is greater than 150 mg/l, has not been directly correlated with clinical stone activity. We investigated the relationship between urinary cystine parameters and clinical stone activity. We prospectively followed 48 patients with cystinuria using 24-hour urine collections and serial imaging, and recorded stone activity. We compared cystine urinary parameters at times of stone activity with those obtained during periods of stone quiescence. We then performed correlation and ROC analysis to evaluate the performance of cystine parameters to predict stone activity. During a median followup of 70.6 months (range 2.2 to 274.6) 85 stone events occurred which could be linked to a recent urine collection. Cystine capacity was significantly greater for quiescent urine than for stone event urine (mean ± SD 48 ± 107 vs -38 ± 163 mg/l, p stone activity (r = -0.29, p r = -0.88, p r = -0.87, p stone quiescence. Decreasing the cutoff to 90 mg/l or greater improved sensitivity to 25.2% while maintaining specificity at 90.9%. Our results suggest that the target for capacity should be lower than previously advised. Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Predicting the initial freezing point and water activity of meat products from composition data

NARCIS (Netherlands)

Sman, van der R.G.M.; Boer, E.P.J.

2005-01-01

In this paper we predict the water activity and initial freezing point of food products (meat and fish) based on their composition. The prediction is based on thermodynamics (the Clausius-Clapeyron equation, the Ross equation and an approximation of the Pitzer equation). Furthermore, we have taken

Signaling Network Assessment of Mutations and Copy Number Variations Predict Breast Cancer Subtype-Specific Drug Targets

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Naif Zaman

2013-10-01

Full Text Available Individual cancer cells carry a bewildering number of distinct genomic alterations (e.g., copy number variations and mutations, making it a challenge to uncover genomic-driven mechanisms governing tumorigenesis. Here, we performed exome sequencing on several breast cancer cell lines that represent two subtypes, luminal and basal. We integrated these sequencing data and functional RNAi screening data (for the identification of genes that are essential for cell proliferation and survival onto a human signaling network. Two subtype-specific networks that potentially represent core-signaling mechanisms underlying tumorigenesis were identified. Within both networks, we found that genes were differentially affected in different cell lines; i.e., in some cell lines a gene was identified through RNAi screening, whereas in others it was genomically altered. Interestingly, we found that highly connected network genes could be used to correctly classify breast tumors into subtypes on the basis of genomic alterations. Further, the networks effectively predicted subtype-specific drug targets, which were experimentally validated.

CLASP/SJ Observations of Rapid Time Variations in the Ly α Emission in a Solar Active Region

Energy Technology Data Exchange (ETDEWEB)

Ishikawa, Shin-nosuke [Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, 3-1-1 Yoshinodai, Chuo-ku, Sagamihara, Kanagawa 252–5210 (Japan); Kubo, Masahito; Katsukawa, Yukio; Kano, Ryouhei; Narukage, Noriyuki; Ishikawa, Ryohko; Bando, Takamasa [National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo 181-8588 (Japan); Winebarger, Amy; Kobayashi, Ken [NASA Marshall Space Flight Center, Huntsville, AL 35812 (United States); Trujillo Bueno, Javier [Instituto de Astrofísica de Canarias, E-38205 La Laguna, Tenerife (Spain); Auchère, Frédéric, E-mail: s.ishikawa@solar.isas.jaxa.jp [Institut d’Astrophysique Spatiale, CNRS/Univ. Paris-Sud 11, Bätiment 121, F-91405 Orsay (France)

2017-09-10

The Chromospheric Ly α SpectroPolarimeter (CLASP) is a sounding rocket experiment launched on 2015 September 3 to investigate the solar chromosphere and transition region. The slit-jaw (SJ) optical system captured Ly α images with a high time cadence of 0.6 s. From the CLASP/SJ observations, many variations in the solar chromosphere and transition region emission with a timescale of <1 minute were discovered. In this paper, we focus on the active region within the SJ field of view and investigate the relationship between short (<30 s) temporal variations in the Ly α emission and the coronal structures observed by Solar Dynamics Observatory/Atmospheric Imaging Assembly (AIA). We compare the Ly α temporal variations at the coronal loop footpoints observed in the AIA 211 Å (≈2 MK) and AIA 171 Å (≈0.6 MK) channels with those in the regions with bright Ly α features without a clear association with the coronal loop footpoints. We find more short (<30 s) temporal variations in the Ly α intensity in the footpoint regions. Those variations did not depend on the temperature of the coronal loops. Therefore, the temporal variations in the Ly α intensity at this timescale range could be related to the heating of the coronal structures up to temperatures around the sensitivity peak of 171 Å. No signature was found to support the scenario that these Ly α intensity variations were related to the nanoflares. Waves or jets from the lower layers (lower chromosphere or photosphere) are possible causes for this phenomenon.

Constraining slip rates and spacings for active normal faults

Science.gov (United States)

Cowie, Patience A.; Roberts, Gerald P.

2001-12-01

Numerous observations of extensional provinces indicate that neighbouring faults commonly slip at different rates and, moreover, may be active over different time intervals. These published observations include variations in slip rate measured along-strike of a fault array or fault zone, as well as significant across-strike differences in the timing and rates of movement on faults that have a similar orientation with respect to the regional stress field. Here we review published examples from the western USA, the North Sea, and central Greece, and present new data from the Italian Apennines that support the idea that such variations are systematic and thus to some extent predictable. The basis for the prediction is that: (1) the way in which a fault grows is fundamentally controlled by the ratio of maximum displacement to length, and (2) the regional strain rate must remain approximately constant through time. We show how data on fault lengths and displacements can be used to model the observed patterns of long-term slip rate where measured values are sparse. Specifically, we estimate the magnitude of spatial variation in slip rate along-strike and relate it to the across-strike spacing between active faults.

Variation across mitochondrial gene trees provides evidence for systematic error: How much gene tree variation is biological?

Science.gov (United States)

Richards, Emilie J; Brown, Jeremy M; Barley, Anthony J; Chong, Rebecca A; Thomson, Robert C

2018-02-19

The use of large genomic datasets in phylogenetics has highlighted extensive topological variation across genes. Much of this discordance is assumed to result from biological processes. However, variation among gene trees can also be a consequence of systematic error driven by poor model fit, and the relative importance of biological versus methodological factors in explaining gene tree variation is a major unresolved question. Using mitochondrial genomes to control for biological causes of gene tree variation, we estimate the extent of gene tree discordance driven by systematic error and employ posterior prediction to highlight the role of model fit in producing this discordance. We find that the amount of discordance among mitochondrial gene trees is similar to the amount of discordance found in other studies that assume only biological causes of variation. This similarity suggests that the role of systematic error in generating gene tree variation is underappreciated and critical evaluation of fit between assumed models and the data used for inference is important for the resolution of unresolved phylogenetic questions.

Role of spontaneous physical activity in prediction of susceptibility to activity based anorexia in male and female rats.

Science.gov (United States)

Perez-Leighton, Claudio E; Grace, Martha; Billington, Charles J; Kotz, Catherine M

2014-08-01

Anorexia nervosa (AN) is a chronic eating disorder affecting females and males, defined by body weight loss, higher physical activity levels and restricted food intake. Currently, the commonalities and differences between genders in etiology of AN are not well understood. Animal models of AN, such as activity-based anorexia (ABA), can be helpful in identifying factors determining individual susceptibility to AN. In ABA, rodents are given an access to a running wheel while food restricted, resulting in paradoxical increased physical activity levels and weight loss. Recent studies suggest that different behavioral traits, including voluntary exercise, can predict individual weight loss in ABA. A higher inherent drive for movement may promote development and severity of AN, but this hypothesis remains untested. In rodents and humans, drive for movement is defined as spontaneous physical activity (SPA), which is time spent in low-intensity, non-volitional movements. In this paper, we show that a profile of body weight history and behavioral traits, including SPA, can predict individual weight loss caused by ABA in male and female rats with high accuracy. Analysis of the influence of SPA on ABA susceptibility in males and females rats suggests that either high or low levels of SPA increase the probability of high weight loss in ABA, but with larger effects in males compared to females. These results suggest that the same behavioral profile can identify individuals at-risk of AN for both male and female populations and that SPA has predictive value for susceptibility to AN. Copyright © 2014 Elsevier Inc. All rights reserved.

Comparison of semantic and episodic memory BOLD fMRI activation in predicting cognitive decline in older adults.

Science.gov (United States)

Hantke, Nathan; Nielson, Kristy A; Woodard, John L; Breting, Leslie M Guidotti; Butts, Alissa; Seidenberg, Michael; Carson Smith, J; Durgerian, Sally; Lancaster, Melissa; Matthews, Monica; Sugarman, Michael A; Rao, Stephen M

2013-01-01

Previous studies suggest that task-activated functional magnetic resonance imaging (fMRI) can predict future cognitive decline among healthy older adults. The present fMRI study examined the relative sensitivity of semantic memory (SM) versus episodic memory (EM) activation tasks for predicting cognitive decline. Seventy-eight cognitively intact elders underwent neuropsychological testing at entry and after an 18-month interval, with participants classified as cognitively "Stable" or "Declining" based on ≥ 1.0 SD decline in performance. Baseline fMRI scanning involved SM (famous name discrimination) and EM (name recognition) tasks. SM and EM fMRI activation, along with Apolipoprotein E (APOE) ε4 status, served as predictors of cognitive outcome using a logistic regression analysis. Twenty-seven (34.6%) participants were classified as Declining and 51 (65.4%) as Stable. APOE ε4 status alone significantly predicted cognitive decline (R(2) = .106; C index = .642). Addition of SM activation significantly improved prediction accuracy (R(2) = .285; C index = .787), whereas the addition of EM did not (R(2) = .212; C index = .711). In combination with APOE status, SM task activation predicts future cognitive decline better than EM activation. These results have implications for use of fMRI in prevention clinical trials involving the identification of persons at-risk for age-associated memory loss and Alzheimer's disease.

Planning for subacute care: predicting demand using acute activity data.

Science.gov (United States)

Green, Janette P; McNamee, Jennifer P; Kobel, Conrad; Seraji, Md Habibur R; Lawrence, Suanne J

2016-01-01

Objective The aim of the present study was to develop a robust model that uses the concept of 'rehabilitation-sensitive' Diagnosis Related Groups (DRGs) in predicting demand for rehabilitation and geriatric evaluation and management (GEM) care following acute in-patient episodes provided in Australian hospitals. Methods The model was developed using statistical analyses of national datasets, informed by a panel of expert clinicians and jurisdictional advice. Logistic regression analysis was undertaken using acute in-patient data, published national hospital statistics and data from the Australasian Rehabilitation Outcomes Centre. Results The predictive model comprises tables of probabilities that patients will require rehabilitation or GEM care after an acute episode, with columns defined by age group and rows defined by grouped Australian Refined (AR)-DRGs. Conclusions The existing concept of rehabilitation-sensitive DRGs was revised and extended. When applied to national data, the model provided a conservative estimate of 83% of the activity actually provided. An example demonstrates the application of the model for service planning. What is known about the topic? Health service planning is core business for jurisdictions and local areas. With populations ageing and an acknowledgement of the underservicing of subacute care, it is timely to find improved methods of estimating demand for this type of care. Traditionally, age-sex standardised utilisation rates for individual DRGs have been applied to Australian Bureau of Statistics (ABS) population projections to predict the future need for subacute services. Improved predictions became possible when some AR-DRGs were designated 'rehabilitation-sensitive'. This improved methodology has been used in several Australian jurisdictions. What does this paper add? This paper presents a new tool, or model, to predict demand for rehabilitation and GEM services based on in-patient acute activity. In this model, the

Variational transition state theory for multidimensional activated rate processes in the presence of anisotropic friction

Science.gov (United States)

Berezhkovskii, Alexander M.; Frishman, Anatoli M.; Pollak, Eli

1994-09-01

Variational transition state theory (VTST) is applied to the study of the activated escape of a particle trapped in a multidimensional potential well and coupled to a heat bath. Special attention is given to the dependence of the rate constant on the friction coefficients in the case of anisotropic friction. It is demonstrated explicitly that both the traditional as well as the nontraditional scenarios for the particle escape are recovered uniformly within the framework of VTST. Effects such as saddle point avoidance and friction dependence of the activation energy are derived from VTST using optimized planar dividing surfaces.

Development of a predictive model to determine micropollutant removal using granular activated carbon

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D. J. de Ridder

2009-12-01

Full Text Available The occurrence of organic micropollutants in drinking water and its sources has opened up a field of study related to monitoring concentration levels in water sources, evaluating their toxicity and estimating their removal in drinking water treatment processes. Because a large number of organic micropollutants is currently present (although in relatively low concentrations in drinking water sources, a method should be developed to select which micropollutants has to be evaluated with priority. In this paper, a screening model is presented that can predict solute removal by activated carbon, in ultrapure water and in natural water. Solute removal prediction is based on a combination of solute hydrophobicity (expressed as log D, the pH corrected log K_ow, solute charge and the carbon dose. Solute molecular weight was also considered as model input parameter, but this solute property appeared to relate insufficiently to solute removal.

Removal of negatively charged solutes by preloaded activated carbon was reduced while the removal of positively charged solutes was increased, compared with freshly regenerated activated carbon. Differences in charged solute removal by freshly regenerated activated carbon were small, indicating that charge interactions are an important mechanism in adsorption onto preloaded carbon. The predicted solute removal was within 20 removal-% deviation of experimentally measured values for most solutes.

Sound induced activity in voice sensitive cortex predicts voice memory ability

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Rebecca eWatson

2012-04-01

Full Text Available The ‘temporal voice areas’ (TVAs (Belin et al., 2000 of the human brain show greater neuronal activity in response to human voices than to other categories of nonvocal sounds. However, a direct link between TVA activity and voice perceptionbehaviour has not yet been established. Here we show that a functional magnetic resonance imaging (fMRI measure of activity in the TVAs predicts individual performance at a separately administered voice memory test. This relation holds whengeneral sound memory ability is taken into account. These findings provide the first evidence that the TVAs are specifically involved in voice cognition.

PASS assisted prediction and pharmacological evaluation of novel nicotinic analogs for nootropic activity in mice.

Science.gov (United States)

Khurana, Navneet; Ishar, Mohan Pal Singh; Gajbhiye, Asmita; Goel, Rajesh Kumar

2011-07-15

The aim of present study is to predict the probable nootropic activity of novel nicotine analogues with the help of computer program, PASS (prediction of activity spectra for substances) and evaluate the same. Two compounds from differently substituted pyridines were selected for synthesis and evaluation of nootropic activity based on their high probable activity (Pa) value predicted by PASS computer program. Evaluation of nootropic activity of compounds after acute and chronic treatment was done with transfer latency (TL) and step down latency (SDL) methods which showed significant nootropic activity. The effect on scopolamine induced amnesia was also observed along with their acetylcholine esterase inhibitory activity which also showed positive results which strengthened their efficacy as nootropic agents through involvement of cholinergic system. This nootropic effect was similar to the effect of nicotine and donepezil used as standard drugs. Muscle coordination and locomotor activity along with their addiction liability, safety and tolerability studies were also evaluated. These studies showed that these compounds are well tolerable and safe over a wide range of doses tested along with the absence of withdrawal effect which is present in nicotine due to its addiction liability. The study showed that these compounds are true nicotine analogs with desirable efficacy and safety profile for their use as effective nootropic agents. Copyright © 2011 Elsevier B.V. All rights reserved.

Predictive Factors of Clinical Response of Infliximab Therapy in Active Nonradiographic Axial Spondyloarthritis Patients

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Zhiming Lin

2015-01-01

Full Text Available Objectives. To evaluate the efficiency and the predictive factors of clinical response of infliximab in active nonradiographic axial spondyloarthritis patients. Methods. Active nonradiographic patients fulfilling ESSG criteria for SpA but not fulfilling modified New York criteria were included. All patients received infliximab treatment for 24 weeks. The primary endpoint was ASAS20 response at weeks 12 and 24. The abilities of baseline parameters and response at week 2 to predict ASAS20 response at weeks 12 and 24 were assessed using ROC curve and logistic regression analysis, respectively. Results. Of 70 axial SpA patients included, the proportions of patients achieving an ASAS20 response at weeks 2, 6, 12, and 24 were 85.7%, 88.6%, 87.1%, and 84.3%, respectively. Baseline MRI sacroiliitis score (AUC = 0.791; P=0.005, CRP (AUC = 0.75; P=0.017, and ASDAS (AUC = 0.778, P=0.007 significantly predicted ASAS20 response at week 12. However, only ASDAS (AUC = 0.696, P=0.040 significantly predicted ASAS20 response at week 24. Achievement of ASAS20 response after the first infliximab infusion was a significant predictor of subsequent ASAS20 response at weeks 12 and 24 (wald χ2=6.87, P=0.009, and wald χ2=5.171, P=0.023. Conclusions. Infliximab shows efficiency in active nonradiographic axial spondyloarthritis patients. ASDAS score and first-dose response could help predicting clinical efficacy of infliximab therapy in these patients.

Application of genetic algorithm - multiple linear regressions to predict the activity of RSK inhibitors

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Avval Zhila Mohajeri

2015-01-01

Full Text Available This paper deals with developing a linear quantitative structure-activity relationship (QSAR model for predicting the RSK inhibition activity of some new compounds. A dataset consisting of 62 pyrazino [1,2-α] indole, diazepino [1,2-α] indole, and imidazole derivatives with known inhibitory activities was used. Multiple linear regressions (MLR technique combined with the stepwise (SW and the genetic algorithm (GA methods as variable selection tools was employed. For more checking stability, robustness and predictability of the proposed models, internal and external validation techniques were used. Comparison of the results obtained, indicate that the GA-MLR model is superior to the SW-MLR model and that it isapplicable for designing novel RSK inhibitors.

Parietal operculum and motor cortex activities predict motor recovery in moderate to severe stroke

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Firdaus Fabrice Hannanu

2017-01-01

In subacute stroke, fMRI brain activity related to passive movement measured in a sensorimotor network defined by activity during voluntary movement predicted motor recovery better than baseline motor-FMS alone. Furthermore, fMRI sensorimotor network activity measures considered alone allowed excellent clinical recovery prediction and may provide reliable biomarkers for assessing new therapies in clinical trial contexts. Our findings suggest that neural reorganization related to motor recovery from moderate to severe stroke results from balanced changes in ipsilesional MI (BA4a and a set of phylogenetically more archaic sensorimotor regions in the ventral sensorimotor trend, in which OP1 and OP4 processes may complement the ipsilesional dorsal motor cortex in achieving compensatory sensorimotor recovery.

Quantitative structure activity relationship for the computational prediction of nitrocompounds carcinogenicity

International Nuclear Information System (INIS)

Morales, Aliuska Helguera; Perez, Miguel Angel Cabrera; Combes, Robert D.; Gonzalez, Maykel Perez

2006-01-01

Several nitrocompounds have been screened for carcinogenicity in rodents, but this is a lengthy and expensive process, taking two years and typically costing 2.5 million dollars, and uses large numbers of animals. There is, therefore, much impetus to develop suitable alternative methods. One possible way of predicting carcinogenicity is to use quantitative structure-activity relationships (QSARs). QSARs have been widely utilized for toxicity testing, thereby contributing to a reduction in the need for experimental animals. This paper describes the results of applying a TOPological substructural molecular design (TOPS-MODE) approach for predicting the rodent carcinogenicity of nitrocompounds. The model described 79.10% of the experimental variance, with a standard deviation of 0.424. The predictive power of the model was validated by leave-one-out validation, with a determination coefficient of 0.666. In addition, this approach enabled the contribution of different fragments to carcinogenic potency to be assessed, thereby making the relationships between structure and carcinogenicity to be transparent. It was found that the carcinogenic activity of the chemicals analysed was increased by the presence of a primary amine group bonded to the aromatic ring, a manner that was proportional to the ring aromaticity. The nitro group bonded to an aromatic carbon atom is a more important determinant of carcinogenicity than the nitro group bonded to an aliphatic carbon. Finally, the TOPS-MODE approach was compared with four other predictive models, but none of these could explain more than 66% of the variance in the carcinogenic potency with the same number of variables

Preparatory neural activity predicts performance on a conflict task.

Science.gov (United States)

Stern, Emily R; Wager, Tor D; Egner, Tobias; Hirsch, Joy; Mangels, Jennifer A

2007-10-24

Advance preparation has been shown to improve the efficiency of conflict resolution. Yet, with little empirical work directly linking preparatory neural activity to the performance benefits of advance cueing, it is not clear whether this relationship results from preparatory activation of task-specific networks, or from activity associated with general alerting processes. Here, fMRI data were acquired during a spatial Stroop task in which advance cues either informed subjects of the upcoming relevant feature of conflict stimuli (spatial or semantic) or were neutral. Informative cues decreased reaction time (RT) relative to neutral cues, and cues indicating that spatial information would be task-relevant elicited greater activity than neutral cues in multiple areas, including right anterior prefrontal and bilateral parietal cortex. Additionally, preparatory activation in bilateral parietal cortex and right dorsolateral prefrontal cortex predicted faster RT when subjects responded to spatial location. No regions were found to be specific to semantic cues at conventional thresholds, and lowering the threshold further revealed little overlap between activity associated with spatial and semantic cueing effects, thereby demonstrating a single dissociation between activations related to preparing a spatial versus semantic task-set. This relationship between preparatory activation of spatial processing networks and efficient conflict resolution suggests that advance information can benefit performance by leading to domain-specific biasing of task-relevant information.

Early prediction of outcome of activities of daily living after stroke: a systematic review

OpenAIRE

Veerbeek, J.M.; Kwakkel, G.; Wegen, van, E.E.H.; Ket, J.C.F.; Heijmans, M.W.

2011-01-01

BACKGROUND AND PURPOSE-Knowledge about robust and unbiased factors that predict outcome of activities of daily living (ADL) is paramount in stroke management. This review investigates the methodological quality of prognostic studies in the early poststroke phase for final ADL to identify variables that are predictive or not predictive for outcome of ADL after stroke. METHODS-PubMed, Ebsco/Cinahl and Embase were systematically searched for prognostic studies in which stroke patients were inclu...

The Ecology of Exercise: Mechanisms Underlying Individual Variation in Behavior, Activity, and Performance: An Introduction to Symposium.

Science.gov (United States)

Killen, Shaun S; Calsbeek, Ryan; Williams, Tony D

2017-08-01

Wild animals often engage in intense physical activity while performing tasks vital for their survival and reproduction associated with foraging, avoiding predators, fighting, providing parental care, and migrating. In this theme issue we consider how viewing these tasks as "exercise"-analogous to that performed by human athletes-may help provide insight into the mechanisms underlying individual variation in these types of behaviors and the importance of physical activity in an ecological context. In this article and throughout this issue, we focus on four key questions relevant to the study of behavioral ecology that may be addressed by studying wild animal behavior from the perspective of exercise physiology: (1) How hard do individual animals work in response to ecological (or evolutionary) demands?; (2) Do lab-based studies of activity provide good models for understanding activity in free-living animals and individual variation in traits?; (3) Can animals work too hard during "routine" activities?; and (4) Can paradigms of "exercise" and "training" be applied to free-living animals? Attempts to address these issues are currently being facilitated by rapid technological developments associated with physiological measurements and the remote tracking of wild animals, to provide mechanistic insights into the behavior of free-ranging animals at spatial and temporal scales that were previously impossible. We further suggest that viewing the behaviors of non-human animals in terms of the physical exercise performed will allow us to fully take advantage of these technological advances, draw from knowledge and conceptual frameworks already in use by human exercise physiologists, and identify key traits that constrain performance and generate variation in performance among individuals. It is our hope that, by highlighting mechanisms of behavior and performance, the articles in this issue will spur on further synergies between physiologists and ecologists, to take

Integrated Detection and Prediction of Influenza Activity for Real-Time Surveillance: Algorithm Design.

Science.gov (United States)

Spreco, Armin; Eriksson, Olle; Dahlström, Örjan; Cowling, Benjamin John; Timpka, Toomas

2017-06-15

Influenza is a viral respiratory disease capable of causing epidemics that represent a threat to communities worldwide. The rapidly growing availability of electronic "big data" from diagnostic and prediagnostic sources in health care and public health settings permits advance of a new generation of methods for local detection and prediction of winter influenza seasons and influenza pandemics. The aim of this study was to present a method for integrated detection and prediction of influenza virus activity in local settings using electronically available surveillance data and to evaluate its performance by retrospective application on authentic data from a Swedish county. An integrated detection and prediction method was formally defined based on a design rationale for influenza detection and prediction methods adapted for local surveillance. The novel method was retrospectively applied on data from the winter influenza season 2008-09 in a Swedish county (population 445,000). Outcome data represented individuals who met a clinical case definition for influenza (based on International Classification of Diseases version 10 [ICD-10] codes) from an electronic health data repository. Information from calls to a telenursing service in the county was used as syndromic data source. The novel integrated detection and prediction method is based on nonmechanistic statistical models and is designed for integration in local health information systems. The method is divided into separate modules for detection and prediction of local influenza virus activity. The function of the detection module is to alert for an upcoming period of increased load of influenza cases on local health care (using influenza-diagnosis data), whereas the function of the prediction module is to predict the timing of the activity peak (using syndromic data) and its intensity (using influenza-diagnosis data). For detection modeling, exponential regression was used based on the assumption that the beginning

Solar UV radiation variations and their stratospheric and climatic effects

Science.gov (United States)

Donnelly, R. F.; Heath, D. F.

1985-01-01

Nimbus-7 SBUV measurements of the short-term solar UV variations caused by solar rotation and active-region evolution have determined the amplitude and wavelength dependence for the active-region component of solar UV variations. Intermediate-term variations lasting several months are associated with rounds of major new active regions. The UV flux stays near the peak value during the current solar cycle variation for more than two years and peaks about two years later than the sunspot number. Nimbus-7 measurements have observed the concurrent stratospheric ozone variations caused by solar UV variations. There is now no doubt that solar UV variations are an important cause of short- and long-term stratospheric variations, but the strength of the coupling to the troposphere and to climate has not yet been proven.

Improving model predictions for RNA interference activities that use support vector machine regression by combining and filtering features

Directory of Open Access Journals (Sweden)

Peek Andrew S

2007-06-01

Full Text Available Abstract Background RNA interference (RNAi is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathways. To dissect the factors that result in effective siRNA sequences a regression kernel Support Vector Machine (SVM approach was used to quantitatively model RNA interference activities. Results Eight overall feature mapping methods were compared in their abilities to build SVM regression models that predict published siRNA activities. The primary factors in predictive SVM models are position specific nucleotide compositions. The secondary factors are position independent sequence motifs (N-grams and guide strand to passenger strand sequence thermodynamics. Finally, the factors that are least contributory but are still predictive of efficacy are measures of intramolecular guide strand secondary structure and target strand secondary structure. Of these, the site of the 5' most base of the guide strand is the most informative. Conclusion The capacity of specific feature mapping methods and their ability to build predictive models of RNAi activity suggests a relative biological importance of these features. Some feature mapping methods are more informative in building predictive models and overall t-test filtering provides a method to remove some noisy features or make comparisons among datasets. Together, these features can yield predictive SVM regression models with increased predictive accuracy between predicted and observed activities both within datasets by cross validation, and between independently collected RNAi activity datasets. Feature filtering to remove features should be approached carefully in that it is possible to reduce feature set size without substantially reducing predictive models, but the features retained in the candidate models become increasingly distinct. Software to perform feature prediction and SVM training and testing on nucleic acid

Lake nutrient stoichiometry is less predictable than nutrient concentrations at regional and sub-continental scales.

Science.gov (United States)

Collins, Sarah M; Oliver, Samantha K; Lapierre, Jean-Francois; Stanley, Emily H; Jones, John R; Wagner, Tyler; Soranno, Patricia A

2017-07-01

Production in many ecosystems is co-limited by multiple elements. While a known suite of drivers associated with nutrient sources, nutrient transport, and internal processing controls concentrations of phosphorus (P) and nitrogen (N) in lakes, much less is known about whether the drivers of single nutrient concentrations can also explain spatial or temporal variation in lake N:P stoichiometry. Predicting stoichiometry might be more complex than predicting concentrations of individual elements because some drivers have similar relationships with N and P, leading to a weak relationship with their ratio. Further, the dominant controls on elemental concentrations likely vary across regions, resulting in context dependent relationships between drivers, lake nutrients and their ratios. Here, we examine whether known drivers of N and P concentrations can explain variation in N:P stoichiometry, and whether explaining variation in stoichiometry differs across regions. We examined drivers of N:P in ~2,700 lakes at a sub-continental scale and two large regions nested within the sub-continental study area that have contrasting ecological context, including differences in the dominant type of land cover (agriculture vs. forest). At the sub-continental scale, lake nutrient concentrations were correlated with nutrient loading and lake internal processing, but stoichiometry was only weakly correlated to drivers of lake nutrients. At the regional scale, drivers that explained variation in nutrients and stoichiometry differed between regions. In the Midwestern U.S. region, dominated by agricultural land use, lake depth and the percentage of row crop agriculture were strong predictors of stoichiometry because only phosphorus was related to lake depth and only nitrogen was related to the percentage of row crop agriculture. In contrast, all drivers were related to N and P in similar ways in the Northeastern U.S. region, leading to weak relationships between drivers and stoichiometry

Accurate cut-offs for predicting endoscopic activity and mucosal healing in Crohn's disease with fecal calprotectin

Directory of Open Access Journals (Sweden)

Juan María Vázquez-Morón

Full Text Available Background: Fecal biomarkers, especially fecal calprotectin, are useful for predicting endoscopic activity in Crohn's disease; however, the cut-off point remains unclear. The aim of this paper was to analyze whether faecal calprotectin and M2 pyruvate kinase are good tools for generating highly accurate scores for the prediction of the state of endoscopic activity and mucosal healing. Methods: The simple endoscopic score for Crohn's disease and the Crohn's disease activity index was calculated for 71 patients diagnosed with Crohn's. Fecal calprotectin and M2-PK were measured by the enzyme-linked immunosorbent assay test. Results: A fecal calprotectin cut-off concentration of ≥ 170 µg/g (sensitivity 77.6%, specificity 95.5% and likelihood ratio +17.06 predicts a high probability of endoscopic activity, and a fecal calprotectin cut-off of ≤ 71 µg/g (sensitivity 95.9%, specificity 52.3% and likelihood ratio -0.08 predicts a high probability of mucosal healing. Three clinical groups were identified according to the data obtained: endoscopic activity (calprotectin ≥ 170, mucosal healing (calprotectin ≤ 71 and uncertainty (71 > calprotectin < 170, with significant differences in endoscopic values (F = 26.407, p < 0.01. Clinical activity or remission modified the probabilities of presenting endoscopic activity (100% vs 89% or mucosal healing (75% vs 87% in the diagnostic scores generated. M2-PK was insufficiently accurate to determine scores. Conclusions: The highly accurate scores for fecal calprotectin provide a useful tool for interpreting the probabilities of presenting endoscopic activity or mucosal healing, and are valuable in the specific clinical context.

Joint reconstruction of dynamic PET activity and kinetic parametric images using total variation constrained dictionary sparse coding

Science.gov (United States)

Yu, Haiqing; Chen, Shuhang; Chen, Yunmei; Liu, Huafeng

2017-05-01

Dynamic positron emission tomography (PET) is capable of providing both spatial and temporal information of radio tracers in vivo. In this paper, we present a novel joint estimation framework to reconstruct temporal sequences of dynamic PET images and the coefficients characterizing the system impulse response function, from which the associated parametric images of the system macro parameters for tracer kinetics can be estimated. The proposed algorithm, which combines statistical data measurement and tracer kinetic models, integrates a dictionary sparse coding (DSC) into a total variational minimization based algorithm for simultaneous reconstruction of the activity distribution and parametric map from measured emission sinograms. DSC, based on the compartmental theory, provides biologically meaningful regularization, and total variation regularization is incorporated to provide edge-preserving guidance. We rely on techniques from minimization algorithms (the alternating direction method of multipliers) to first generate the estimated activity distributions with sub-optimal kinetic parameter estimates, and then recover the parametric maps given these activity estimates. These coupled iterative steps are repeated as necessary until convergence. Experiments with synthetic, Monte Carlo generated data, and real patient data have been conducted, and the results are very promising.

PASS-Predicted Hepatoprotective Activity of Caesalpinia sappan in Thioacetamide-Induced Liver Fibrosis in Rats

Directory of Open Access Journals (Sweden)

Farkaad A. Kadir

2014-01-01

Full Text Available The antifibrotic effects of traditional medicinal herb Caesalpinia sappan (CS extract on liver fibrosis induced by thioacetamide (TAA and the expression of transforming growth factor β1 (TGF-β1, α-smooth muscle actin (αSMA, and proliferating cell nuclear antigen (PCNA in rats were studied. A computer-aided prediction of antioxidant and hepatoprotective activities was primarily performed with the Prediction Activity Spectra of the Substance (PASS Program. Liver fibrosis was induced in male Sprague Dawley rats by TAA administration (0.03% w/v in drinking water for a period of 12 weeks. Rats were divided into seven groups: control, TAA, Silymarin (SY, and CS 300 mg/kg body weight and 100 mg/kg groups. The effect of CS on liver fibrogenesis was determined by Masson’s trichrome staining, immunohistochemical analysis, and western blotting. In vivo determination of hepatic antioxidant activities, cytochrome P450 2E1 (CYP2E1, and matrix metalloproteinases (MPPS was employed. CS treatment had significantly increased hepatic antioxidant enzymes activity in the TAA-treated rats. Liver fibrosis was greatly alleviated in rats when treated with CS extract. CS treatment was noted to normalize the expression of TGF-β1, αSMA, PCNA, MMPs, and TIMP1 proteins. PASS-predicted plant activity could efficiently guide in selecting a promising pharmaceutical lead with high accuracy and required antioxidant and hepatoprotective properties.

Predictive value of European Scleroderma Group Activity Index in an early scleroderma cohort.

Science.gov (United States)

Nevskaya, Tatiana; Baron, Murray; Pope, Janet E

2017-07-01

To estimate the effect of disease activity, as measured by the European Scleroderma Research Group Activity Index (EScSG-AI), on the risk of subsequent organ damage in a large systemic sclerosis (SSc) cohort. Of 421 SSc patients from the Canadian Scleroderma Research Group database with disease duration of ⩽ 3 years, 197 who had no evidence of end-stage organ damage initially and available 3 year follow-up were included. Disease activity was assessed by the EScSG-AI with two variability measures: the adjusted mean EScSG-AI (the area under the curve of the EScSG-AI over the observation period) and persistently active disease/flare. Outcomes were based on the Medsger severity scale and included accrual of a new severity score (Δ ⩾ 1) overall and within organ systems or reaching a significant level of deterioration in health status. After adjustment for covariates, the adjusted mean EScSG-AI was the most consistent predictor of risk across the study outcomes over 3 years in dcSSc: disease progression defined as Δ ⩾ 1 in any major internal organ, significant decline in forced vital capacity and diffusing capacity of carbon monoxide, severity of visceral disease and HAQ Disability Index worsening. In multivariate analysis, progression of lung disease was predicted solely by adjusted mean EScSG-AI, while the severity of lung disease was predicted the adjusted mean EScSG-AI, older age, modified Rodnan skin score (mRSS) and initial severity. The EScSG-AI was associated with patient- and physician-assessed measures of health status and overpowered the mRSS in predicting disease outcomes. Disease activity burden quantified with the adjusted mean EScSG-AI predicted the risk of deterioration in health status and severe organ involvement in dcSSc. The EScSG-AI is more responsive when done repeatedly and averaged. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email

Extensive Variation in Chromatin States Across Humans

KAUST Repository

Kasowski, M.

2013-10-17

The majority of disease-associated variants lie outside protein-coding regions, suggesting a link between variation in regulatory regions and disease predisposition. We studied differences in chromatin states using five histone modifications, cohesin, and CTCF in lymphoblastoid lines from 19 individuals of diverse ancestry. We found extensive signal variation in regulatory regions, which often switch between active and repressed states across individuals. Enhancer activity is particularly diverse among individuals, whereas gene expression remains relatively stable. Chromatin variability shows genetic inheritance in trios, correlates with genetic variation and population divergence, and is associated with disruptions of transcription factor binding motifs. Overall, our results provide insights into chromatin variation among humans.

Extensive Variation in Chromatin States Across Humans

KAUST Repository

Kasowski, M.; Kyriazopoulou-Panagiotopoulou, S.; Grubert, F.; Zaugg, J. B.; Kundaje, A.; Liu, Y.; Boyle, A. P.; Zhang, Q. C.; Zakharia, F.; Spacek, D. V.; Li, J.; Xie, D.; Olarerin-George, A.; Steinmetz, L. M.; Hogenesch, J. B.; Kellis, M.; Batzoglou, S.; Snyder, M.

2013-01-01

The majority of disease-associated variants lie outside protein-coding regions, suggesting a link between variation in regulatory regions and disease predisposition. We studied differences in chromatin states using five histone modifications, cohesin, and CTCF in lymphoblastoid lines from 19 individuals of diverse ancestry. We found extensive signal variation in regulatory regions, which often switch between active and repressed states across individuals. Enhancer activity is particularly diverse among individuals, whereas gene expression remains relatively stable. Chromatin variability shows genetic inheritance in trios, correlates with genetic variation and population divergence, and is associated with disruptions of transcription factor binding motifs. Overall, our results provide insights into chromatin variation among humans.

The influence of active region information on the prediction of solar flares: an empirical model using data mining

Directory of Open Access Journals (Sweden)

M. Núñez

2005-11-01

Full Text Available Predicting the occurrence of solar flares is a challenge of great importance for many space weather scientists and users. We introduce a data mining approach, called Behavior Pattern Learning (BPL, for automatically discovering correlations between solar flares and active region data, in order to predict the former. The goal of BPL is to predict the interval of time to the next solar flare and provide a confidence value for the associated prediction. The discovered correlations are described in terms of easy-to-read rules. The results indicate that active region dynamics is essential for predicting solar flares.

Bayesian Predictive Models for Rayleigh Wind Speed

DEFF Research Database (Denmark)

Shahirinia, Amir; Hajizadeh, Amin; Yu, David C

2017-01-01

predictive model of the wind speed aggregates the non-homogeneous distributions into a single continuous distribution. Therefore, the result is able to capture the variation among the probability distributions of the wind speeds at the turbines’ locations in a wind farm. More specifically, instead of using...... a wind speed distribution whose parameters are known or estimated, the parameters are considered as random whose variations are according to probability distributions. The Bayesian predictive model for a Rayleigh which only has a single model scale parameter has been proposed. Also closed-form posterior...... and predictive inferences under different reasonable choices of prior distribution in sensitivity analysis have been presented....

M-ficolin levels reflect disease activity and predict remission in early rheumatoid arthritis

DEFF Research Database (Denmark)

Ammitzbøll, Christian Gytz; Thiel, Steffen; Jensenius, Jens Christian

2013-01-01

To assess plasma M-ficolin concentrations in disease-modifying antirheumatic drug (DMARD)-naive patients with early rheumatoid arthritis (RA), to investigate the correlation of M-ficolin concentrations with disease activity markers, and to determine the predictive value of M-ficolin with respect...... to the Disease Activity Score in 28 joints (DAS28)....

Knee and Hip Joint Kinematics Predict Quadriceps and Hamstrings Neuromuscular Activation Patterns in Drop Jump Landings.

Science.gov (United States)

Malfait, Bart; Dingenen, Bart; Smeets, Annemie; Staes, Filip; Pataky, Todd; Robinson, Mark A; Vanrenterghem, Jos; Verschueren, Sabine

2016-01-01

The purpose was to assess if variation in sagittal plane landing kinematics is associated with variation in neuromuscular activation patterns of the quadriceps-hamstrings muscle groups during drop vertical jumps (DVJ). Fifty female athletes performed three DVJ. The relationship between peak knee and hip flexion angles and the amplitude of four EMG vectors was investigated with trajectory-level canonical correlation analyses over the entire time period of the landing phase. EMG vectors consisted of the {vastus medialis(VM),vastus lateralis(VL)}, {vastus medialis(VM),hamstring medialis(HM)}, {hamstring medialis(HM),hamstring lateralis(HL)} and the {vastus lateralis(VL),hamstring lateralis(HL)}. To estimate the contribution of each individual muscle, linear regressions were also conducted using one-dimensional statistical parametric mapping. The peak knee flexion angle was significantly positively associated with the amplitudes of the {VM,HM} and {HM,HL} during the preparatory and initial contact phase and with the {VL,HL} vector during the peak loading phase (phamstrings medialis activity) during the preparatory and initial contact phase and an increased lateral neuromuscular activation (dominant vastus lateralis activity) during the peak loading phase.

Genetic variations in multiple myeloma II

DEFF Research Database (Denmark)

Vangsted, A.; Klausen, T.W.; Vogel, U.

2012-01-01

Association studies on genetic variation to treatment effect may serve as a predictive marker for effect of treatment and can also uncover biological pathways behind drug effect. Single-nucleotide polymorphisms (SNPs) have been studied in relation to high-dose treatment (HDT), thalidomide- and bo...

Early functional MRI activation predicts motor outcome after ischemic stroke: a longitudinal, multimodal study.

Science.gov (United States)

Du, Juan; Yang, Fang; Zhang, Zhiqiang; Hu, Jingze; Xu, Qiang; Hu, Jianping; Zeng, Fanyong; Lu, Guangming; Liu, Xinfeng

2018-05-15

An accurate prediction of long term outcome after stroke is urgently required to provide early individualized neurorehabilitation. This study aimed to examine the added value of early neuroimaging measures and identify the best approaches for predicting motor outcome after stroke. This prospective study involved 34 first-ever ischemic stroke patients (time since stroke: 1-14 days) with upper limb impairment. All patients underwent baseline multimodal assessments that included clinical (age, motor impairment), neurophysiological (motor-evoked potentials, MEP) and neuroimaging (diffusion tensor imaging and motor task-based fMRI) measures, and also underwent reassessment 3 months after stroke. Bivariate analysis and multivariate linear regression models were used to predict the motor scores (Fugl-Meyer assessment, FMA) at 3 months post-stroke. With bivariate analysis, better motor outcome significantly correlated with (1) less initial motor impairment and disability, (2) less corticospinal tract injury, (3) the initial presence of MEPs, (4) stronger baseline motor fMRI activations. In multivariate analysis, incorporating neuroimaging data improved the predictive accuracy relative to only clinical and neurophysiological assessments. Baseline fMRI activation in SMA was an independent predictor of motor outcome after stroke. A multimodal model incorporating fMRI and clinical measures best predicted the motor outcome following stroke. fMRI measures obtained early after stroke provided independent prediction of long-term motor outcome.

Flood Prediction using Rainfall – Runoff Spatial Variation: An ...

African Journals Online (AJOL)

Ethiopian Journal of Environmental Studies and Management ... and especially those based on the use of Artificial Neural Network (ANN), provide a ... in the flood forecasting accuracy in comparison to the use of simple prediction approaches, ...

An experimental test of fitness variation across a hydrologic gradient predicts willow and poplar species distributions.

Science.gov (United States)

Wei, Xiaojing; Savage, Jessica A; Riggs, Charlotte E; Cavender-Bares, Jeannine

2017-05-01

Environmental filtering is an important community assembly process influencing species distributions. Contrasting species abundance patterns along environmental gradients are commonly used to provide evidence for environmental filtering. However, the same abundance patterns may result from alternative or concurrent assembly processes. Experimental tests are an important means to decipher whether species fitness varies with environment, in the absence of dispersal constraints and biotic interactions, and to draw conclusions about the importance of environmental filtering in community assembly. We performed an experimental test of environmental filtering in 14 closely related willow and poplar species (family Salicaceae) by transplanting cuttings of each species into 40 common gardens established along a natural hydrologic gradient in the field, where competition was minimized and herbivory was controlled. We analyzed species fitness responses to the hydrologic environment based on cumulative growth and survival over two years using aster fitness models. We also examined variation in nine drought and flooding tolerance traits expected to contribute to performance based on a priori understanding of plant function in relation to water availability and stress. We found substantial evidence that environmental filtering along the hydrologic gradient played a critical role in determining species distributions. Fitness variation of each species in the field experiment was used to model their water table depth optima. These optima predicted 68% of the variation in species realized hydrologic niches based on peak abundance in naturally assembled communities in the surrounding region. Multiple traits associated with water transport efficiency and water stress tolerance were correlated with species hydrologic niches, but they did not necessarily covary with each other. As a consequence, species occupying similar hydrologic niches had different combinations of trait values

Radon variations in active volcanoes and in regions with high seismicity: internal and external factors

International Nuclear Information System (INIS)

Segovia, N.; Cruz-Reyna, S. De la; Mena, M.

1986-01-01

The results of 4 years of observations of radon concentrations in soils of active volcanoes of Costa Rica and a highly seismic region in Mexico are discussed. A distinction is made between the influences of external (mostly meteorological) and internal (magmatic or tectonic) factors on the variation in radon levels. The geological meaning of the radon data can be thus enhanced if the external factors are excluded. (author)

Quantum variational calculus

CERN Document Server

Malinowska, Agnieszka B

2014-01-01

This Brief puts together two subjects, quantum and variational calculi by considering variational problems involving Hahn quantum operators. The main advantage of its results is that they are able to deal with nondifferentiable (even discontinuous) functions, which are important in applications. Possible applications in economics are discussed. Economists model time as continuous or discrete. Although individual economic decisions are generally made at discrete time intervals, they may well be less than perfectly synchronized in ways discrete models postulate. On the other hand, the usual assumption that economic activity takes place continuously, is nothing else than a convenient abstraction that in many applications is far from reality. The Hahn quantum calculus helps to bridge the gap between the two families of models: continuous and discrete. Quantum Variational Calculus is self-contained and unified in presentation. It provides an opportunity for an introduction to the quantum calculus of variations fo...

Prediction of objectively measured physical activity and sedentariness among blue-collar workers using survey questionnaires

DEFF Research Database (Denmark)

Gupta, Nidhi; Heiden, Marina; Mathiassen, Svend Erik

2016-01-01

responded to a questionnaire containing information about personal and work related variables, available in most large epidemiological studies and surveys. Workers also wore accelerometers for 1-4 days measuring time spent sedentary and in physical activity, defined as non-sedentary time. Least......-squares linear regression models were developed, predicting objectively measured exposures from selected predictors in the questionnaire. RESULTS: A full prediction model based on age, gender, body mass index, job group, self-reported occupational physical activity (OPA), and self-reported occupational sedentary...

GRIND2-based 3D-QSAR and prediction of activity spectra for symmetrical bis-pyridinium salts with promastigote antileishmanial activity.

Science.gov (United States)

Diniz, Evelyn Mirella Lopes Pina; Tomich de Paula da Silva, Carlos Henrique; Gómez-Perez, Verónica; Federico, Leonardo Bruno; Campos Rosa, Joaquín María

2017-08-01

Leishmaniasis is a major group of neglected tropical diseases caused by the protozoan parasite Leishmania. About 12 million people are affected in 98 countries and 350 million people worldwide are at risk of infection. Current leishmaniasis treatments rely on a relatively small arsenal of drugs, including amphotericin B, pentamidine and others, which in general have some type of inconvenience. Recently, we have synthesized antileishmanial bis-pyridinium derivatives and symmetrical bis-pyridinium cyclophanes. These compounds are considered structural analogues of pentamidine, where the amidino moiety, protonated at physiological pH, is replaced by a positively charged nitrogen atom as a pyridinium ring. In this work, a statistically significant GRIND2-based 3D-QSAR model was built and biological activity predictions were in silico carried out allowing rationalization of the different activities recently obtained against Leishmania donovani (in L. donovani promastigotes) for a data set of 19 bis-pyridinium compounds. We will emphasize the most important structural requirements to improve the biological activity and probable interactions with the biological receptor as a guide for lead and prototype optimization. In addition, since no information about the actual biological target for this series of active compounds is provided, we have used Prediction of Activity Spectra for Biologically Active Substances to propose our compounds as potential nicotinic α6β3β4α5 receptor antagonists. This proposal is reinforced by the high structural similarity observed between our compounds and several anthelmintic drugs in current clinical use, which have the same drug action mechanism here predicted. Such new findings would be confirmed with further and additional experimental assays.

The Heart´s rhythm 'n' blues: Sex differences in circadian variation patterns of vagal activity vary by depressive symptoms in predominantly healthy employees.

Science.gov (United States)

Jarczok, Marc N; Aguilar-Raab, Corina; Koenig, Julian; Kaess, Michael; Borniger, Jeremy C; Nelson, Randy J; Hall, Martica; Ditzen, Beate; Thayer, Julian F; Fischer, Joachim E

2018-03-15

Successful regulation of emotional states is positively associated to mental health, while difficulties in regulating emotions are negatively associated to overall mental health and in particular associated with anxiety or depression symptoms. A key structure associated to socio-emotional regulatory processes is the central autonomic network. Activity in this structure is associated to vagal activity can be indexed noninvasively and simply by measures of peripheral cardiac autonomic modulations such as heart rate variability. Vagal activity exhibits a circadian variation pattern, with a maximum during nighttime. Depression is known to affect chronobiology. Also, depressive symptoms are known to be associated with decreased resting state vagal activity, but studies investigating the association between circadian variation pattern of vagal activity and depressive symptoms are scarce. We aim to examine these patterns in association to symptom severity of depression using chronobiologic methods. Data from the Manheim Industrial Cohort Studies (MICS) were used. A total of 3,030 predominantly healthy working adults underwent, among others, ambulatory 24-h hear rate-recordings, detailed health examination and online questionnaires and were available for this analysis. The root mean sum of successive differences (RMSSD) was used as an indicator of vagally mediated heart rate variability. Three individual-level cosine function parameters (MESOR, amplitude, acrophase) were estimated to quantify circadian variation pattern. Multivariate linear regression models including important covariates such as age, sex, and lifestyle factors as well as an interaction effect of sex with depressive symptoms were used to estimate the association of circadian variation pattern of vagal activity with depressive symptoms simultaneously. The analysis sample consisted of 20.2% females and an average age 41 with standard deviation of 11 years. Nonparametric bivariate analysis revealed

A random forest classifier for the prediction of energy expenditure and type of physical activity from wrist and hip accelerometers

International Nuclear Information System (INIS)

Ellis, Katherine; Lanckriet, Gert; Kerr, Jacqueline; Godbole, Suneeta; Wing, David; Marshall, Simon

2014-01-01

Wrist accelerometers are being used in population level surveillance of physical activity (PA) but more research is needed to evaluate their validity for correctly classifying types of PA behavior and predicting energy expenditure (EE). In this study we compare accelerometers worn on the wrist and hip, and the added value of heart rate (HR) data, for predicting PA type and EE using machine learning. Forty adults performed locomotion and household activities in a lab setting while wearing three ActiGraph GT3X+ accelerometers (left hip, right hip, non-dominant wrist) and a HR monitor (Polar RS400). Participants also wore a portable indirect calorimeter (COSMED K4b2), from which EE and metabolic equivalents (METs) were computed for each minute. We developed two predictive models: a random forest classifier to predict activity type and a random forest of regression trees to estimate METs. Predictions were evaluated using leave-one-user-out cross-validation. The hip accelerometer obtained an average accuracy of 92.3% in predicting four activity types (household, stairs, walking, running), while the wrist accelerometer obtained an average accuracy of 87.5%. Across all 8 activities combined (laundry, window washing, dusting, dishes, sweeping, stairs, walking, running), the hip and wrist accelerometers obtained average accuracies of 70.2% and 80.2% respectively. Predicting METs using the hip or wrist devices alone obtained root mean square errors (rMSE) of 1.09 and 1.00 METs per 6 min bout, respectively. Including HR data improved MET estimation, but did not significantly improve activity type classification. These results demonstrate the validity of random forest classification and regression forests for PA type and MET prediction using accelerometers. The wrist accelerometer proved more useful in predicting activities with significant arm movement, while the hip accelerometer was superior for predicting locomotion and estimating EE. (paper)

A random forest classifier for the prediction of energy expenditure and type of physical activity from wrist and hip accelerometers.

Science.gov (United States)

Ellis, Katherine; Kerr, Jacqueline; Godbole, Suneeta; Lanckriet, Gert; Wing, David; Marshall, Simon

2014-11-01

Wrist accelerometers are being used in population level surveillance of physical activity (PA) but more research is needed to evaluate their validity for correctly classifying types of PA behavior and predicting energy expenditure (EE). In this study we compare accelerometers worn on the wrist and hip, and the added value of heart rate (HR) data, for predicting PA type and EE using machine learning. Forty adults performed locomotion and household activities in a lab setting while wearing three ActiGraph GT3X+ accelerometers (left hip, right hip, non-dominant wrist) and a HR monitor (Polar RS400). Participants also wore a portable indirect calorimeter (COSMED K4b2), from which EE and metabolic equivalents (METs) were computed for each minute. We developed two predictive models: a random forest classifier to predict activity type and a random forest of regression trees to estimate METs. Predictions were evaluated using leave-one-user-out cross-validation. The hip accelerometer obtained an average accuracy of 92.3% in predicting four activity types (household, stairs, walking, running), while the wrist accelerometer obtained an average accuracy of 87.5%. Across all 8 activities combined (laundry, window washing, dusting, dishes, sweeping, stairs, walking, running), the hip and wrist accelerometers obtained average accuracies of 70.2% and 80.2% respectively. Predicting METs using the hip or wrist devices alone obtained root mean square errors (rMSE) of 1.09 and 1.00 METs per 6 min bout, respectively. Including HR data improved MET estimation, but did not significantly improve activity type classification. These results demonstrate the validity of random forest classification and regression forests for PA type and MET prediction using accelerometers. The wrist accelerometer proved more useful in predicting activities with significant arm movement, while the hip accelerometer was superior for predicting locomotion and estimating EE.

Learning-based prediction of gestational age from ultrasound images of the fetal brain.

Science.gov (United States)

Namburete, Ana I L; Stebbing, Richard V; Kemp, Bryn; Yaqub, Mohammad; Papageorghiou, Aris T; Alison Noble, J

2015-04-01

We propose an automated framework for predicting gestational age (GA) and neurodevelopmental maturation of a fetus based on 3D ultrasound (US) brain image appearance. Our method capitalizes on age-related sonographic image patterns in conjunction with clinical measurements to develop, for the first time, a predictive age model which improves on the GA-prediction potential of US images. The framework benefits from a manifold surface representation of the fetal head which delineates the inner skull boundary and serves as a common coordinate system based on cranial position. This allows for fast and efficient sampling of anatomically-corresponding brain regions to achieve like-for-like structural comparison of different developmental stages. We develop bespoke features which capture neurosonographic patterns in 3D images, and using a regression forest classifier, we characterize structural brain development both spatially and temporally to capture the natural variation existing in a healthy population (N=447) over an age range of active brain maturation (18-34weeks). On a routine clinical dataset (N=187) our age prediction results strongly correlate with true GA (r=0.98,accurate within±6.10days), confirming the link between maturational progression and neurosonographic activity observable across gestation. Our model also outperforms current clinical methods by ±4.57 days in the third trimester-a period complicated by biological variations in the fetal population. Through feature selection, the model successfully identified the most age-discriminating anatomies over this age range as being the Sylvian fissure, cingulate, and callosal sulci. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Generalized Predictive Control for Non-Stationary Systems

DEFF Research Database (Denmark)

Palsson, Olafur Petur; Madsen, Henrik; Søgaard, Henning Tangen

1994-01-01

This paper shows how the generalized predictive control (GPC) can be extended to non-stationary (time-varying) systems. If the time-variation is slow, then the classical GPC can be used in context with an adaptive estimation procedure of a time-invariant ARIMAX model. However, in this paper prior...... knowledge concerning the nature of the parameter variations is assumed available. The GPC is based on the assumption that the prediction of the system output can be expressed as a linear combination of present and future controls. Since the Diophantine equation cannot be used due to the time......-variation of the parameters, the optimal prediction is found as the general conditional expectation of the system output. The underlying model is of an ARMAX-type instead of an ARIMAX-type as in the original version of the GPC (Clarke, D. W., C. Mohtadi and P. S. Tuffs (1987). Automatica, 23, 137-148) and almost all later...

Seasonal and spatial variations in microbial activity at various phylogenetic resolutions at a groundwater – surface water interface

DEFF Research Database (Denmark)

Yu, Ran; Smets, Barth F.; Gan, Ping

2014-01-01

analysis. Consistently higher microbial activities with less variation in depth were measured in the AIMC traps than in the ambient sediments. Flood disturbance appeared to control AIMC activity distributions at the gradually elevated GSI. The highest AIMC activities were generally obtained from locations...... closest to the free surface water boundary except during the dry season when microbial activities were similar across the entire GSI. A clone library of AIMC 16S rRNA genes was constructed, and it confirmed the predominant role of the targeted alphaproteobacterial group in AIMC activity and composition...... phylogenetically related to putative IOB, supporting the occurrence and persistence of active microbial iron oxidation across the studied iron-rich GSI ecosystem....

Decreased dopamine activity predicts relapse in methamphetamine abusers

Energy Technology Data Exchange (ETDEWEB)

Wang G. J.; Wang, G.-J.; Smith, L.; Volkow, N.D.; Telang, F.; Logan, J.; Tomasi, D.; Wong, C.T.; Hoffman, W.; Jayne, M.; Alia-Klein, N.; Thanos, P.; Fowler, J.S.

2011-01-20

Studies in methamphetamine (METH) abusers showed that the decreases in brain dopamine (DA) function might recover with protracted detoxification. However, the extent to which striatal DA function in METH predicts recovery has not been evaluated. Here we assessed whether striatal DA activity in METH abusers is associated with clinical outcomes. Brain DA D2 receptor (D2R) availability was measured with positron emission tomography and [{sup 11}C]raclopride in 16 METH abusers, both after placebo and after challenge with 60 mg oral methylphenidate (MPH) (to measure DA release) to assess whether it predicted clinical outcomes. For this purpose, METH abusers were tested within 6 months of last METH use and then followed up for 9 months of abstinence. In parallel, 15 healthy controls were tested. METH abusers had lower D2R availability in caudate than in controls. Both METH abusers and controls showed decreased striatal D2R availability after MPH and these decreases were smaller in METH than in controls in left putamen. The six METH abusers who relapsed during the follow-up period had lower D2R availability in dorsal striatum than in controls, and had no D2R changes after MPH challenge. The 10 METH abusers who completed detoxification did not differ from controls neither in striatal D2R availability nor in MPH-induced striatal DA changes. These results provide preliminary evidence that low striatal DA function in METH abusers is associated with a greater likelihood of relapse during treatment. Detection of the extent of DA dysfunction may be helpful in predicting therapeutic outcomes.

Decreased dopamine activity predicts relapse in methamphetamine abusers

International Nuclear Information System (INIS)

Wang, G.J.; Smith, L.; Volkow, N.D.; Telang, F.; Logan, J.; Tomasi, D.; Wong, C.T.; Hoffman, W.; Jayne, M.; Alia-Klein, N.; Thanos, P.; Fowler, J.S.

2011-01-01

Studies in methamphetamine (METH) abusers showed that the decreases in brain dopamine (DA) function might recover with protracted detoxification. However, the extent to which striatal DA function in METH predicts recovery has not been evaluated. Here we assessed whether striatal DA activity in METH abusers is associated with clinical outcomes. Brain DA D2 receptor (D2R) availability was measured with positron emission tomography and ( 11 C)raclopride in 16 METH abusers, both after placebo and after challenge with 60 mg oral methylphenidate (MPH) (to measure DA release) to assess whether it predicted clinical outcomes. For this purpose, METH abusers were tested within 6 months of last METH use and then followed up for 9 months of abstinence. In parallel, 15 healthy controls were tested. METH abusers had lower D2R availability in caudate than in controls. Both METH abusers and controls showed decreased striatal D2R availability after MPH and these decreases were smaller in METH than in controls in left putamen. The six METH abusers who relapsed during the follow-up period had lower D2R availability in dorsal striatum than in controls, and had no D2R changes after MPH challenge. The 10 METH abusers who completed detoxification did not differ from controls neither in striatal D2R availability nor in MPH-induced striatal DA changes. These results provide preliminary evidence that low striatal DA function in METH abusers is associated with a greater likelihood of relapse during treatment. Detection of the extent of DA dysfunction may be helpful in predicting therapeutic outcomes.

SU-E-T-326: The Oxygen Saturation (SO2) and Breath-Holding Time Variation Applied Active Breathing Control (ABC)

Energy Technology Data Exchange (ETDEWEB)

Gong, G; Yin, Y [Shandong Cancer Hospital, Jinan, Shandong (China)

2014-06-01

Purpose: To study the oxygen saturation (SO2) and breath-holding time variation applied active breathing control (ABC) in radiotherapy of tumor. Methods: 24 volunteers were involved in our trials, and they all did breath-holding motion assisted by ELEKTA Active Breathing Coordinator 2.0 for 10 times respectively. And the patient monitor was used to observe the oxygen saturation (SO2) variation. The variation of SO2, and length of breath-holding time and the time for recovering to the initial value of SO2 were recorded and analyzed. Results: (1) The volunteers were divided into two groups according to the SO2 variation in breath-holding: A group, 14 cases whose SO2 reduction were more than 2% (initial value was 97% to 99%, while termination value was 91% to 96%); B group, 10 cases were less than 2% in breath-holding without inhaling oxygen. (2) The interfraction breath holding time varied from 8 to 20s for A group compared to the first breath-holding time, and for B group varied from 4 to 14s. (3) The breathing holding time of B group prolonged mean 8s, compared to A group. (4) The time for restoring to the initial value of SO2 was from 10s to 30s. And the breath-holding time shortened obviously for patients whose SO2 did not recover to normal. Conclusion: It is very obvious that the SO2 reduction in breath-holding associated with ABC for partial people. It is necessary to check the SO2 variation in breath training, and enough time should be given to recover SO2.

Analysis and prediction of daily physical activity level data using autoregressive integrated moving average models

NARCIS (Netherlands)

Long, Xi; Pauws, S.C.; Pijl, M.; Lacroix, J.; Goris, A.H.C.; Aarts, R.M.

2009-01-01

Results are provided on predicting daily physical activity level (PAL) data from past data of participants of a physical activity lifestyle program aimed at promoting a healthier lifestyle consisting of more physical exercise. The PAL data quantifies the level of a person’s daily physical activity

Predicting variation in subject thermal response during transcranial magnetic resonance guided focused ultrasound surgery: Comparison in seventeen subject datasets

Energy Technology Data Exchange (ETDEWEB)

Vyas, Urvi, E-mail: urvi.vyas@gmail.com; Ghanouni, Pejman; Halpern, Casey H.; Pauly, Kim Butts [Department of Radiology, Stanford University, Stanford, California 94305 (United States); Elias, Jeff [Department of Neurological Surgery, University of Virginia, Charlottesville, Virginia 22908 (United States)

2016-09-15

Purpose: In transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) treatments, the acoustic and spatial heterogeneity of the skull cause reflection, absorption, and scattering of the acoustic beams. These effects depend on skull-specific parameters and can lead to patient-specific thermal responses to the same transducer power. In this work, the authors develop a simulation tool to help predict these different experimental responses using 3D heterogeneous tissue models based on the subject CT images. The authors then validate and compare the predicted skull efficiencies to an experimental metric based on the subject thermal responses during tcMRgFUS treatments in a dataset of seventeen human subjects. Methods: Seventeen human head CT scans were used to create tissue acoustic models, simulating the effects of reflection, absorption, and scattering of the acoustic beam as it propagates through a heterogeneous skull. The hybrid angular spectrum technique was used to model the acoustic beam propagation of the InSightec ExAblate 4000 head transducer for each subject, yielding maps of the specific absorption rate (SAR). The simulation assumed the transducer was geometrically focused to the thalamus of each subject, and the focal SAR at the target was used as a measure of the simulated skull efficiency. Experimental skull efficiency for each subject was calculated using the thermal temperature maps from the tcMRgFUS treatments. Axial temperature images (with no artifacts) were reconstructed with a single baseline, corrected using a referenceless algorithm. The experimental skull efficiency was calculated by dividing the reconstructed temperature rise 8.8 s after sonication by the applied acoustic power. Results: The simulated skull efficiency using individual-specific heterogeneous models predicts well (R{sup 2} = 0.84) the experimental energy efficiency. Conclusions: This paper presents a simulation model to predict the variation in thermal responses

Short- and long-term variations in non-linear dynamics of heart rate variability

DEFF Research Database (Denmark)

Kanters, J K; Højgaard, M V; Agner, E

1996-01-01

OBJECTIVES: The purpose of the study was to investigate the short- and long-term variations in the non-linear dynamics of heart rate variability, and to determine the relationships between conventional time and frequency domain methods and the newer non-linear methods of characterizing heart rate...... rate and describes mainly linear correlations. Non-linear predictability is correlated with heart rate variability measured as the standard deviation of the R-R intervals and the respiratory activity expressed as power of the high-frequency band. The dynamics of heart rate variability changes suddenly...

A novel method for predicting activity of cis-regulatory modules, based on a diverse training set.

Science.gov (United States)

Yang, Wei; Sinha, Saurabh

2017-01-01

With the rapid emergence of technologies for locating cis-regulatory modules (CRMs) genome-wide, the next pressing challenge is to assign precise functions to each CRM, i.e. to determine the spatiotemporal domains or cell-types where it drives expression. A popular approach to this task is to model the typical k-mer composition of a set of CRMs known to drive a common expression pattern, and assign that pattern to other CRMs exhibiting a similar k-mer composition. This approach does not rely on prior knowledge of transcription factors relevant to the CRM or their binding motifs, and is thus more widely applicable than motif-based methods for predicting CRM activity, but is also prone to false positive predictions. We present a novel strategy to improve the above-mentioned approach: to predict if a CRM drives a specific gene expression pattern, assess not only how similar the CRM is to other CRMs with similar activity but also to CRMs with distinct activities. We use a state-of-the-art statistical method to quantify a CRM's sequence similarity to many different training sets of CRMs, and employ a classification algorithm to integrate these similarity scores into a single prediction of the CRM's activity. This strategy is shown to significantly improve CRM activity prediction over current approaches. Our implementation of the new method, called IMMBoost, is freely available as source code, at https://github.com/weiyangedward/IMMBoost CONTACT: sinhas@illinois.eduSupplementary information: 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.

Predicting physical activity energy expenditure in wheelchair users with a multisensor device.

Science.gov (United States)

Nightingale, T E; Walhin, J P; Thompson, D; Bilzon, J L J

2015-01-01

To assess the error in predicting physical activity energy expenditure (PAEE), using a multisensor device in wheelchair users, and to examine the efficacy of using an individual heart rate calibration (IC) method. 15 manual wheelchair users (36±10 years, 72±11 kg) completed 10 activities: resting, folding clothes, wheelchair propulsion on a 1% gradient (3456 and 7 km/h) and propulsion at 4 km/h (with an additional 8% of body mass, 2% and 3% gradient) on a motorised wheelchair treadmill. Criterion PAEE was measured using a computerised indirect calorimetry system. Participants wore a combined accelerometer and heart rate monitor (Actiheart). They also performed an incremental arm crank ergometry test to exhaustion which permitted retrospective individual calibration of the Actiheart for the activity protocol. Linear regression analysis was conducted between criterion (indirect calorimetry) and estimated PAEE from the Actiheart using the manufacturer's proprietary algorithms (group calibration, GC) or IC. Bland-Altman plots were used and mean absolute error was calculated to assess the agreement between criterion values and estimated PAEE. Predicted PAEE was significantly (p<0.01) correlated with criterion PAEE (GC, r=0.76 and IC, r=0.95). The absolute bias ±95% limits of agreement were 0.51±3.75 and -0.22±0.96 kcal/min for GC and IC, respectively. Mean absolute errors across the activity protocol were 51.4±38.9% using GC and 16.8±15.8% using IC. PAEE can be accurately and precisely estimated using a combined accelerometer and heart rate monitor device, with integration of an IC. Interindividual variance in cardiovascular function and response to exercise is high in this population. Therefore, in manual wheelchair users, we advocate the use of an IC when using the Actiheart to predict PAEE.

Theoretical prediction of thermodynamic activities of liquid Au-Sn-X (X=Bi, Sb, Zn) solder systems

Energy Technology Data Exchange (ETDEWEB)

Awe, O.E., E-mail: draweoe2004@yahoo.com [Department of Physics, University of Ibadan, Ibadan (Nigeria); Department of Physics and Engineering Physics, Obafemi Awolowo University, Ile-Ife (Nigeria); Oshakuade, O.M. [Department of Physics, University of Ibadan, Ibadan (Nigeria)

2017-02-15

Molecular interaction volume model has been theoretically used to predict the thermodynamic activities of tin in Au-Sn-Bi and Au-Sn-Sb and the thermodynamic activity of zinc in Au-Sn-Zn at experimental temperatures 800 K, 873 K and 973 K, respectively. On the premise of agreement between the predicted and experimental values, we predicted the activities of the remaining two components in each of the three systems. This prediction was extended from three cross-sections to five cross-sections, and to temperature range 400–600 K, relevant for applications. Iso-activities were plotted. Results show that addition of tin reduces the tendency for chemical short range order in both Au-Sb and Au-Zn systems, while addition of gold and bismuth, respectively, reduce the tendency for chemical short range order in Sn-Sb and Au-Sn systems. Also, we found that, in the desired high-temperature region for applications, while a combination of chemical order and miscibility of components exist in both Au-Sn-Bi and Au-Sn-Zn systems, only chemical order exist in the Au-Sn-Sb system. Results, further show that increase in temperature reduces the phase separation tendency in Au-Sn-Bi system.