WorldWideScience

Sample records for adaptive branch prediction

  1. Branch prediction in the pentium family

    DEFF Research Database (Denmark)

    Fog, Agner

    1998-01-01

    How the branch prediction mechanism in the Pentium has been uncovered with all its quirks, and the incredibly more effective branch prediction in the later versions.......How the branch prediction mechanism in the Pentium has been uncovered with all its quirks, and the incredibly more effective branch prediction in the later versions....

  2. Adaptive delta management : Roots and branches

    NARCIS (Netherlands)

    Timmermans, J.S.; Haasnoot, M.; Hermans, L.M.; Kwakkel, J.H.; Rutten, M.M.; Thissen, W.A.H.

    2015-01-01

    Deltas are generally recognized as vulnerable to climate change and therefore a salient topic in adaptation science. Deltas are also highly dynamic systems viewed from physical (erosion, sedimentation, subsidence), social (demographic), economic (trade), infrastructures (transport, energy,

  3. Adaptive Delta Management : Roots and Branches

    NARCIS (Netherlands)

    Timmermans, Jos; Haasnoot, Marjolijn; Hermans, Leon; Kwakkel, Jan H.; Rutten, Maarten; Thissen, Wil A.H.; Mynett, Arthur

    2015-01-01

    Deltas are generally recognized as vulnerable to climate change and therefore a salient topic in adaptation science. Deltas are also highly dynamic systems viewed from physical (erosion, sedimentation, subsidence), social (demographic), economic (trade), infrastructures (transport, energy,

  4. BPP: a sequence-based algorithm for branch point prediction.

    Science.gov (United States)

    Zhang, Qing; Fan, Xiaodan; Wang, Yejun; Sun, Ming-An; Shao, Jianlin; Guo, Dianjing

    2017-10-15

    Although high-throughput sequencing methods have been proposed to identify splicing branch points in the human genome, these methods can only detect a small fraction of the branch points subject to the sequencing depth, experimental cost and the expression level of the mRNA. An accurate computational model for branch point prediction is therefore an ongoing objective in human genome research. We here propose a novel branch point prediction algorithm that utilizes information on the branch point sequence and the polypyrimidine tract. Using experimentally validated data, we demonstrate that our proposed method outperforms existing methods. Availability and implementation: https://github.com/zhqingit/BPP. djguo@cuhk.edu.hk. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  5. Adaptive filtering prediction and control

    CERN Document Server

    Goodwin, Graham C

    2009-01-01

    Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary o

  6. Detection of Bundle Branch Block using Adaptive Bacterial Foraging Optimization and Neural Network

    Directory of Open Access Journals (Sweden)

    Padmavthi Kora

    2017-03-01

    Full Text Available The medical practitioners analyze the electrical activity of the human heart so as to predict various ailments by studying the data collected from the Electrocardiogram (ECG. A Bundle Branch Block (BBB is a type of heart disease which occurs when there is an obstruction along the pathway of an electrical impulse. This abnormality makes the heart beat irregular as there is an obstruction in the branches of heart, this results in pulses to travel slower than the usual. Our current study involved is to diagnose this heart problem using Adaptive Bacterial Foraging Optimization (ABFO Algorithm. The Data collected from MIT/BIH arrhythmia BBB database applied to an ABFO Algorithm for obtaining best(important feature from each ECG beat. These features later fed to Levenberg Marquardt Neural Network (LMNN based classifier. The results show the proposed classification using ABFO is better than some recent algorithms reported in the literature.

  7. Prediction Reweighting for Domain Adaptation.

    Science.gov (United States)

    Shuang Li; Shiji Song; Gao Huang

    2017-07-01

    There are plenty of classification methods that perform well when training and testing data are drawn from the same distribution. However, in real applications, this condition may be violated, which causes degradation of classification accuracy. Domain adaptation is an effective approach to address this problem. In this paper, we propose a general domain adaptation framework from the perspective of prediction reweighting, from which a novel approach is derived. Different from the major domain adaptation methods, our idea is to reweight predictions of the training classifier on testing data according to their signed distance to the domain separator, which is a classifier that distinguishes training data (from source domain) and testing data (from target domain). We then propagate the labels of target instances with larger weights to ones with smaller weights by introducing a manifold regularization method. It can be proved that our reweighting scheme effectively brings the source and target domains closer to each other in an appropriate sense, such that classification in target domain becomes easier. The proposed method can be implemented efficiently by a simple two-stage algorithm, and the target classifier has a closed-form solution. The effectiveness of our approach is verified by the experiments on artificial datasets and two standard benchmarks, a visual object recognition task and a cross-domain sentiment analysis of text. Experimental results demonstrate that our method is competitive with the state-of-the-art domain adaptation algorithms.

  8. Modifications of the branch-and-bound algorithm for application in constrained adaptive testing

    NARCIS (Netherlands)

    Veldkamp, Bernard P.

    2000-01-01

    A mathematical programming approach is presented for computer adaptive testing (CAT) with many constraints on the item and test attributes. Because mathematical programming problems have to be solved while the examinee waits for the next item, a fast implementation of the Branch-and-Bound algorithm

  9. A model-based study delineating the roles of the two signaling branches of Saccharomyces cerevisiae, Sho1 and Sln1, during adaptation to osmotic stress

    International Nuclear Information System (INIS)

    Parmar, J H; Bhartiya, Sharad; Venkatesh, K V

    2009-01-01

    Adaptation to osmotic shock in Saccharomyces cerevisiae is brought about by the activation of two independent signaling pathways, Sho1 and Sln1, which in turn trigger the high osmolarity glycerol (HOG) pathway. The HOG pathway thereby activates the transcription of Gpd1p, an enzyme necessary to synthesize glycerol. The production of glycerol brings about a change in the intracellular osmolarity leading to adaptation. We present a detailed mechanistic model for the response of the yeast to hyperosmotic shock. The model integrates the two branches, Sho1 and Sln1, of the HOG pathway and also includes the mitogen-activated protein kinase cascade, gene regulation and metabolism. Model simulations are consistent with known experimental results for wild-type strain, and Ste11Δ and Ssk1Δ mutant strains subjected to osmotic stress. Simulation results predict that both the branches contribute to the overall wild-type response for moderate osmotic shock, while under severe osmotic shock, the cell responds mainly through the Sln1 branch. The analysis shows that the Sln1 branch helps the cell in preventing cross-talk to other signaling pathways by inhibiting ste11ste50 activation and also by increasing the phosphorylation of Ste50. We show that the negative feedbacks to the Sho1 branch must be faster than those to the Sln1 branch to simultaneously achieve pathway specificity and adaptation during hyperosmotic shock. Sensitivity analysis revealed that the presence of both branches imparts robust behavior to the cell under osmoadaptation to perturbations

  10. Adaptive vehicle motion estimation and prediction

    Science.gov (United States)

    Zhao, Liang; Thorpe, Chuck E.

    1999-01-01

    Accurate motion estimation and reliable maneuver prediction enable an automated car to react quickly and correctly to the rapid maneuvers of the other vehicles, and so allow safe and efficient navigation. In this paper, we present a car tracking system which provides motion estimation, maneuver prediction and detection of the tracked car. The three strategies employed - adaptive motion modeling, adaptive data sampling, and adaptive model switching probabilities - result in an adaptive interacting multiple model algorithm (AIMM). The experimental results on simulated and real data demonstrate that our tracking system is reliable, flexible, and robust. The adaptive tracking makes the system intelligent and useful in various autonomous driving tasks.

  11. Adaptive prediction applied to seismic event detection

    International Nuclear Information System (INIS)

    Clark, G.A.; Rodgers, P.W.

    1981-01-01

    Adaptive prediction was applied to the problem of detecting small seismic events in microseismic background noise. The Widrow-Hoff LMS adaptive filter used in a prediction configuration is compared with two standard seismic filters as an onset indicator. Examples demonstrate the technique's usefulness with both synthetic and actual seismic data

  12. Adaptive prediction applied to seismic event detection

    Energy Technology Data Exchange (ETDEWEB)

    Clark, G.A.; Rodgers, P.W.

    1981-09-01

    Adaptive prediction was applied to the problem of detecting small seismic events in microseismic background noise. The Widrow-Hoff LMS adaptive filter used in a prediction configuration is compared with two standard seismic filters as an onset indicator. Examples demonstrate the technique's usefulness with both synthetic and actual seismic data.

  13. Branching-ratio predictions for the iota(1440)

    International Nuclear Information System (INIS)

    Palmer, W.F.; Pinsky, S.S.

    1983-01-01

    A simple pole model is used to predict iota→deltaπ, rho#betta#, #betta##betta#, phi#betta#, rhoππ, and etaππ. The rates iota→etaππ and iota→KK-barπ are examined in detail. In the pole model the rate iota→etaππ is compared to eta'→etaππ and we have the prediction B(iota→etaππ)/B(iota→KK-barπ) = 10%. A direct calculation that takes into account the cancellation between iota→deltaπ→(etaπ)π and iota→etaepsilon→eta(ππ), the KK-bar threshold, and SU(3) violations seen in the decay of the delta, predicts 20%< or =B(iota→etaππ)/B(iota→KK-barπ),< or =110%. Both calculations are consistent with the experimental limit of 50%

  14. Branching-ratio predictions for the iota (1440)

    International Nuclear Information System (INIS)

    Palmer, W.F.; Pinsky, S.S.

    1982-01-01

    A simple pole model is used to predict iota → delta π, rho ν, νν, phi ν, rho ππ, and eta ππ. The rates iota → eta ππ and iota → K anti Kπ are examined in detail. In the pole model the rate iota → eta ππ is compared to eta' → eta ππ and we have the prediction B(iota → eta ππ)/B(iota → K anti Kπ) = 10%. A direct calculation that takes into account the cancellation between iota → delta π → (eta π)π and iota → eta epsilon → eta(ππ), the K anti K threshold and SU(3) violations seen in the decay of the delta, predicts 20% less than or equal to B(iota → eta ππ)/B(iota → K anti Kπ less than or equal to 110%. Both calculations are consistent with the experimental limit of 50%

  15. Predicting life-history adaptations to pollutants

    Energy Technology Data Exchange (ETDEWEB)

    Maltby, L. [Univ. of Sheffield (United Kingdom). Dept. of Animal and Plant Sciences

    1995-12-31

    Animals may adapt to pollutant stress so that individuals from polluted environments are less susceptible than those from unpolluted environments. In addition to such direct adaptations, animals may respond to pollutant stress by life-history modifications; so-called indirect adaptations. This paper will demonstrate how, by combining life-history theory and toxicological data, it is possible to predict stress-induced alterations in reproductive output and offspring size. Pollutant-induced alterations in age-specific survival in favor of adults and reductions in juvenile growth, conditions are predicted to select for reduced investment in reproduction and the allocation of this investment into fewer, larger offspring. Field observations on the freshwater crustaceans, Asellus aquaticus and Gammarus pulex, support these predictions. Females from metal-polluted sites had lower investment in reproduction and produced larger offspring than females of the same species from unpolluted sites. Moreover, interpopulation differences in reproductive biology persisted in laboratory cultures indicating that they had a genetic basis and were therefore due to adaptation rather than acclimation. The general applicability of this approach will be considered.

  16. Adapting Price Predictions in TAC SCM

    Science.gov (United States)

    Pardoe, David; Stone, Peter

    In agent-based markets, adapting to the behavior of other agents is often necessary for success. When it is not possible to directly model individual competitors, an agent may instead model and adapt to the market conditions that result from competitor behavior. Such an agent could still benefit from reasoning about specific competitor strategies by considering how various combinations of these strategies would impact the conditions being modeled. We present an application of such an approach to a specific prediction problem faced by the agent TacTex-06 in the Trading Agent Competition's Supply Chain Management scenario (TAC SCM).

  17. Simulation of branched serial first-order decay of atrazine and metabolites in adapted and nonadapted soils

    Science.gov (United States)

    Webb, Richard M.; Sandstrom, Mark W.; Jason L. Krutz,; Dale L. Shaner,

    2011-01-01

    In the present study a branched serial first-order decay (BSFOD) model is presented and used to derive transformation rates describing the decay of a common herbicide, atrazine, and its metabolites observed in unsaturated soils adapted to previous atrazine applications and in soils with no history of atrazine applications. Calibration of BSFOD models for soils throughout the country can reduce the uncertainty, relative to that of traditional models, in predicting the fate and transport of pesticides and their metabolites and thus support improved agricultural management schemes for reducing threats to the environment. Results from application of the BSFOD model to better understand the degradation of atrazine supports two previously reported conclusions: atrazine (6-chloro-N-ethyl-N′-(1-methylethyl)-1,3,5-triazine-2,4-diamine) and its primary metabolites are less persistent in adapted soils than in nonadapted soils; and hydroxyatrazine was the dominant primary metabolite in most of the soils tested. In addition, a method to simulate BSFOD in a one-dimensional solute-transport unsaturated zone model is also presented.

  18. Becoming Predictably Adaptable in Software Development

    Directory of Open Access Journals (Sweden)

    Michael Vakoc

    2017-10-01

    Full Text Available It’s difficult to state exact timelines in software development and it is even more difficult to say when features that users want will be delivered. We propose changes to current software development methodologies that enable companies to be predictably adaptable and deliver both on time and what customer asked for. We do so through research of current literature, interviews and personal experience working at an international company that builds products for millions of customers and is facing exactly the challenges described above.

  19. Linear zonal atmospheric prediction for adaptive optics

    Science.gov (United States)

    McGuire, Patrick C.; Rhoadarmer, Troy A.; Coy, Hanna A.; Angel, J. Roger P.; Lloyd-Hart, Michael

    2000-07-01

    We compare linear zonal predictors of atmospheric turbulence for adaptive optics. Zonal prediction has the possible advantage of being able to interpret and utilize wind-velocity information from the wavefront sensor better than modal prediction. For simulated open-loop atmospheric data for a 2- meter 16-subaperture AO telescope with 5 millisecond prediction and a lookback of 4 slope-vectors, we find that Widrow-Hoff Delta-Rule training of linear nets and Back- Propagation training of non-linear multilayer neural networks is quite slow, getting stuck on plateaus or in local minima. Recursive Least Squares training of linear predictors is two orders of magnitude faster and it also converges to the solution with global minimum error. We have successfully implemented Amari's Adaptive Natural Gradient Learning (ANGL) technique for a linear zonal predictor, which premultiplies the Delta-Rule gradients with a matrix that orthogonalizes the parameter space and speeds up the training by two orders of magnitude, like the Recursive Least Squares predictor. This shows that the simple Widrow-Hoff Delta-Rule's slow convergence is not a fluke. In the case of bright guidestars, the ANGL, RLS, and standard matrix-inversion least-squares (MILS) algorithms all converge to the same global minimum linear total phase error (approximately 0.18 rad2), which is only approximately 5% higher than the spatial phase error (approximately 0.17 rad2), and is approximately 33% lower than the total 'naive' phase error without prediction (approximately 0.27 rad2). ANGL can, in principle, also be extended to make non-linear neural network training feasible for these large networks, with the potential to lower the predictor error below the linear predictor error. We will soon scale our linear work to the approximately 108-subaperture MMT AO system, both with simulations and real wavefront sensor data from prime focus.

  20. Adaptive MAC-layer protocol for multiservice digital access via tree and branch communication networks

    Science.gov (United States)

    Sriram, Kotikalapudi; Li, Chia-Chang; Magill, Peter; Whitaker, Norman A.; Dail, James E.; Dajer, Miguel A.; Siller, Curtis A.

    1995-11-01

    Described here is an adaptive MAC-layer protocol that supports multiservice (STM and ATM) applications in the context of subscriber access to tree and branch (e.g., fiber-coaxial cable) networks. The protocol adapts to changing demands for a mix of circuit and cell mode applications, and efficiently allocates upstream and downstream bandwidth to a variety of bursty and isochronous traffic sources. In the case of a hybrid fiber-coaxial (HFC) network the protocol resides in customer premises equipment and a common head-end controller. A medium-access control (MAC) processor provides for dividing the time domain for a given digital bitstream into successive frames, each with multiple STM and ATM time slots. Within the STM region of a frame, variable length time slots are allocated to calls (e.g., telephony, video telephony) requiring different amounts of bandwidth. A contention access signaling channel is also provided in this region for call control and set-up requests. Within the ATM region fixed-length time slots accommodate one individual ATM cell. These ATM time slots may be reserved for a user for the duration of a call or burst of successive ATM cells, or shared via a contention process. At least one contention time slot is available for signaling messages related to ATM call control and set-up requests. Further, the fixed-length ATM time slots may be reserved by a user for the duration of a call, or shared through a contention process. This paper describes the MAC-layer protocol, its relation to circuit- and ATM- amenable applications, and its performance with respect to signaling throughput and latency, and bandwidth efficiency for several service scenarios.

  1. Development of Test Method for Simple Shear and Prediction of Hardening Behavior Considering the Branchings Effect

    International Nuclear Information System (INIS)

    Kim, Dongwook; Bang, Sungsik; Kim, Minsoo; Lee, Hyungyil; Kim, Naksoo

    2013-01-01

    In this study we establish a process to predict hardening behavior considering the Branchings effect for zircaloy-4 sheets. When a metal is compressed after tension in forming, the yield strength decreases. For this reason, the Branchings effect should be considered in FE simulations of spring-back. We suggested a suitable specimen size and a method for determining the optimum tightening torque for simple shear tests. Shear stress-strain curves are obtained for five materials. We developed a method to convert the shear load-displacement curve to the effective stress-strain curve with Fea. We simulated the simple shear forward/reverse test using the combined isotropic/kinematic hardening model. We also investigated the change of the load-displacement curve by varying the hardening coefficients. We determined the hardening coefficients so that they follow the hardening behavior of zircaloy-4 in experiments

  2. Development of Test Method for Simple Shear and Prediction of Hardening Behavior Considering the Branchings Effect

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Dongwook; Bang, Sungsik; Kim, Minsoo; Lee, Hyungyil; Kim, Naksoo [Sogang Univ., Seoul (Korea, Republic of)

    2013-10-15

    In this study we establish a process to predict hardening behavior considering the Branchings effect for zircaloy-4 sheets. When a metal is compressed after tension in forming, the yield strength decreases. For this reason, the Branchings effect should be considered in FE simulations of spring-back. We suggested a suitable specimen size and a method for determining the optimum tightening torque for simple shear tests. Shear stress-strain curves are obtained for five materials. We developed a method to convert the shear load-displacement curve to the effective stress-strain curve with Fea. We simulated the simple shear forward/reverse test using the combined isotropic/kinematic hardening model. We also investigated the change of the load-displacement curve by varying the hardening coefficients. We determined the hardening coefficients so that they follow the hardening behavior of zircaloy-4 in experiments.

  3. A heuristic model for computational prediction of human branch point sequence.

    Science.gov (United States)

    Wen, Jia; Wang, Jue; Zhang, Qing; Guo, Dianjing

    2017-10-24

    Pre-mRNA splicing is the removal of introns from precursor mRNAs (pre-mRNAs) and the concurrent ligation of the flanking exons to generate mature mRNA. This process is catalyzed by the spliceosome, where the splicing factor 1 (SF1) specifically recognizes the seven-nucleotide branch point sequence (BPS) and the U2 snRNP later displaces the SF1 and binds to the BPS. In mammals, the degeneracy of BPS motifs together with the lack of a large set of experimentally verified BPSs complicates the task of BPS prediction in silico. In this paper, we develop a simple and yet efficient heuristic model for human BPS prediction based on a novel scoring scheme, which quantifies the splicing strength of putative BPSs. The candidate BPS is restricted exclusively within a defined BPS search region to avoid the influences of other elements in the intron and therefore the prediction accuracy is improved. Moreover, using two types of relative frequencies for human BPS prediction, we demonstrate our model outperformed other current implementations on experimentally verified human introns. We propose that the binding energy contributes to the molecular recognition involved in human pre-mRNA splicing. In addition, a genome-wide human BPS prediction is carried out. The characteristics of predicted BPSs are in accordance with experimentally verified human BPSs, and branch site positions relative to the 3'ss and the 5'end of the shortened AGEZ are consistent with the results of published papers. Meanwhile, a webserver for BPS predictor is freely available at http://biocomputer.bio.cuhk.edu.hk/BPS .

  4. Assessing allometric models to predict vegetative growth of mango (Mangifera indica; Anacardiaceae) at the current-year branch scale.

    Science.gov (United States)

    Normand, Frédéric; Lauri, Pierre-Éric

    2012-03-01

    Accurate and reliable predictive models are necessary to estimate nondestructively key variables for plant growth studies such as leaf area and leaf, stem, and total biomass. Predictive models are lacking at the current-year branch scale despite the importance of this scale in plant science. We calibrated allometric models to estimate leaf area and stem and branch (leaves + stem) mass of current-year branches, i.e., branches several months old studied at the end of the vegetative growth season, of four mango cultivars on the basis of their basal cross-sectional area. The effects of year, site, and cultivar were tested. Models were validated with independent data and prediction accuracy was evaluated with the appropriate statistics. Models revealed a positive allometry between dependent and independent variables, whose y-intercept but not the slope, was affected by the cultivar. The effects of year and site were negligible. For each branch characteristic, cultivar-specific models were more accurate than common models built with pooled data from the four cultivars. Prediction quality was satisfactory but with data dispersion around the models, particularly for large values. Leaf area and stem and branch mass of mango current-year branches could be satisfactorily estimated on the basis of branch basal cross-sectional area with cultivar-specific allometric models. The results suggested that, in addition to the heteroscedastic behavior of the variables studied, model accuracy was probably related to the functional plasticity of branches in relation to the light environment and/or to the number of growth units composing the branches.

  5. New social adaptability index predicts overall mortality.

    Science.gov (United States)

    Goldfarb-Rumyantzev, Alexander; Barenbaum, Anna; Rodrigue, James; Rout, Preeti; Isaacs, Ross; Mukamal, Kenneth

    2011-08-01

    Definitions of underprivileged status based on race, gender and geographic location are neither sensitive nor specific; instead we proposed and validated a composite index of social adaptability (SAI). Index of social adaptability was calculated based on employment, education, income, marital status, and substance abuse, each factor contributing from 0 to 3 points. Index of social adaptability was validated in NHANES-3 by association with all-cause and cause-specific mortality. Weighted analysis of 19,593 subjects demonstrated mean SAI of 8.29 (95% CI 8.17-8.40). Index of social adaptability was higher in Whites, followed by Mexican-Americans and then the African-American population (ANOVA, p adaptability with a strong association with mortality, which can be used to identify underprivileged populations at risk of death.

  6. Performance analysis of joint multi-branch switched diversity and adaptive modulation schemes for spectrum sharing systems

    KAUST Repository

    Bouida, Zied

    2012-12-01

    Under the scenario of an underlay cognitive radio network, we propose in this paper two adaptive schemes using switched transmit diversity and adaptive modulation in order to increase the spectral efficiency of the secondary link and maintain a desired performance for the primary link. The proposed switching efficient scheme (SES) and bandwidth efficient scheme (BES) use the scan and wait combining technique (SWC) where a transmission occurs only when a branch with an acceptable performance is found, otherwise data is buffered. In these schemes, the modulation constellation size and the used transmit branch are determined to minimize the average number of switched branches and to achieve the highest spectral efficiency given the fading channel conditions, the required error rate performance, and a peak interference constraint to the primary receiver (PR). For delay-sensitive applications, we also propose two variations of the SES and BES schemes using power control (SES-PC and BES-PC) where the secondary transmitter (ST) starts sending data using a nominal power level which is selected in order to minimize the average delay introduced by the SWC technique. We demonstrate through numerical examples that the BES scheme increases the capacity of the secondary link when compared to the SES scheme. This spectral efficiency improvement comes at the expense of an increased average number of switched branches and thus an increased average delay. We also show that the SES-PC and the BES-PC schemes minimize the average delay while satisfying the same spectral efficiency as the SES and BES schemes, respectively. © 2012 IEEE.

  7. Learning from sensory and reward prediction errors during motor adaptation.

    Science.gov (United States)

    Izawa, Jun; Shadmehr, Reza

    2011-03-01

    Voluntary motor commands produce two kinds of consequences. Initially, a sensory consequence is observed in terms of activity in our primary sensory organs (e.g., vision, proprioception). Subsequently, the brain evaluates the sensory feedback and produces a subjective measure of utility or usefulness of the motor commands (e.g., reward). As a result, comparisons between predicted and observed consequences of motor commands produce two forms of prediction error. How do these errors contribute to changes in motor commands? Here, we considered a reach adaptation protocol and found that when high quality sensory feedback was available, adaptation of motor commands was driven almost exclusively by sensory prediction errors. This form of learning had a distinct signature: as motor commands adapted, the subjects altered their predictions regarding sensory consequences of motor commands, and generalized this learning broadly to neighboring motor commands. In contrast, as the quality of the sensory feedback degraded, adaptation of motor commands became more dependent on reward prediction errors. Reward prediction errors produced comparable changes in the motor commands, but produced no change in the predicted sensory consequences of motor commands, and generalized only locally. Because we found that there was a within subject correlation between generalization patterns and sensory remapping, it is plausible that during adaptation an individual's relative reliance on sensory vs. reward prediction errors could be inferred. We suggest that while motor commands change because of sensory and reward prediction errors, only sensory prediction errors produce a change in the neural system that predicts sensory consequences of motor commands.

  8. Customizing Countermeasure Prescriptions using Predictive Measures of Sensorimotor Adaptability

    Science.gov (United States)

    Bloomberg, J. J.; Peters, B. T.; Mulavara, A. P.; Miller, C. A.; Batson, C. D.; Wood, S. J.; Guined, J. R.; Cohen, H. S.; Buccello-Stout, R.; DeDios, Y. E.; hide

    2014-01-01

    Astronauts experience sensorimotor disturbances during the initial exposure to microgravity and during the readapation phase following a return to a gravitational environment. These alterations may lead to disruption in the ability to perform mission critical functional tasks during and after these gravitational transitions. Astronauts show significant inter-subject variation in adaptive capability following gravitational transitions. The ability to predict the manner and degree to which each individual astronaut will be affected would improve the effectiveness of a countermeasure comprised of a training program designed to enhance sensorimotor adaptability. Due to this inherent individual variability we need to develop predictive measures of sensorimotor adaptability that will allow us to predict, before actual space flight, which crewmember will experience challenges in adaptive capacity. Thus, obtaining this information will allow us to design and implement better sensorimotor adaptability training countermeasures that will be customized for each crewmember's unique adaptive capabilities. Therefore the goals of this project are to: 1) develop a set of predictive measures capable of identifying individual differences in sensorimotor adaptability, and 2) use this information to design sensorimotor adaptability training countermeasures that are customized for each crewmember's individual sensorimotor adaptive characteristics. To achieve these goals we are currently pursuing the following specific aims: Aim 1: Determine whether behavioral metrics of individual sensory bias predict sensorimotor adaptability. For this aim, subjects perform tests that delineate individual sensory biases in tests of visual, vestibular, and proprioceptive function. Aim 2: Determine if individual capability for strategic and plastic-adaptive responses predicts sensorimotor adaptability. For this aim, each subject's strategic and plastic-adaptive motor learning abilities are assessed using

  9. Conformal prediction for reliable machine learning theory, adaptations and applications

    CERN Document Server

    Balasubramanian, Vineeth; Vovk, Vladimir

    2014-01-01

    The conformal predictions framework is a recent development in machine learning that can associate a reliable measure of confidence with a prediction in any real-world pattern recognition application, including risk-sensitive applications such as medical diagnosis, face recognition, and financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detecti

  10. Model Prediction Control For Water Management Using Adaptive Prediction Accuracy

    NARCIS (Netherlands)

    Tian, X.; Negenborn, R.R.; Van Overloop, P.J.A.T.M.; Mostert, E.

    2014-01-01

    In the field of operational water management, Model Predictive Control (MPC) has gained popularity owing to its versatility and flexibility. The MPC controller, which takes predictions, time delay and uncertainties into account, can be designed for multi-objective management problems and for

  11. Fourier transform wavefront control with adaptive prediction of the atmosphere.

    Science.gov (United States)

    Poyneer, Lisa A; Macintosh, Bruce A; Véran, Jean-Pierre

    2007-09-01

    Predictive Fourier control is a temporal power spectral density-based adaptive method for adaptive optics that predicts the atmosphere under the assumption of frozen flow. The predictive controller is based on Kalman filtering and a Fourier decomposition of atmospheric turbulence using the Fourier transform reconstructor. It provides a stable way to compensate for arbitrary numbers of atmospheric layers. For each Fourier mode, efficient and accurate algorithms estimate the necessary atmospheric parameters from closed-loop telemetry and determine the predictive filter, adjusting as conditions change. This prediction improves atmospheric rejection, leading to significant improvements in system performance. For a 48x48 actuator system operating at 2 kHz, five-layer prediction for all modes is achievable in under 2x10(9) floating-point operations/s.

  12. Predicting mesh density for adaptive modelling of the global atmosphere.

    Science.gov (United States)

    Weller, Hilary

    2009-11-28

    The shallow water equations are solved using a mesh of polygons on the sphere, which adapts infrequently to the predicted future solution. Infrequent mesh adaptation reduces the cost of adaptation and load-balancing and will thus allow for more accurate mapping on adaptation. We simulate the growth of a barotropically unstable jet adapting the mesh every 12 h. Using an adaptation criterion based largely on the gradient of the vorticity leads to a mesh with around 20 per cent of the cells of a uniform mesh that gives equivalent results. This is a similar proportion to previous studies of the same test case with mesh adaptation every 1-20 min. The prediction of the mesh density involves solving the shallow water equations on a coarse mesh in advance of the locally refined mesh in order to estimate where features requiring higher resolution will grow, decay or move to. The adaptation criterion consists of two parts: that resolved on the coarse mesh, and that which is not resolved and so is passively advected on the coarse mesh. This combination leads to a balance between resolving features controlled by the large-scale dynamics and maintaining fine-scale features.

  13. Branching out: Agroforestry as a climate change mitigation and adaptation tool for agriculture

    Science.gov (United States)

    The United States and Canadian agricultural lands are being targeted to provide more environmental and economic services while at the same time their capacity to provide these services under potential climate change (CC) is being questioned. Predictions of future climate conditions include longer gr...

  14. A theoretical adaptive model of thermal comfort - Adaptive Predicted Mean Vote (aPMV)

    Energy Technology Data Exchange (ETDEWEB)

    Yao, Runming [School of Construction Management and Engineering, The University of Reading (United Kingdom); Faculty of Urban Construction and Environmental Engineering, Chongqing University (China); Li, Baizhan [Key Laboratory of the Three Gorges Reservoir Region' s Eco-Environment (Ministry of Education), Chongqing University (China); Faculty of Urban Construction and Environmental Engineering, Chongqing University (China); Liu, Jing [School of Construction Management and Engineering, The University of Reading (United Kingdom)

    2009-10-15

    This paper presents in detail a theoretical adaptive model of thermal comfort based on the ''Black Box'' theory, taking into account factors such as culture, climate, social, psychological and behavioural adaptations, which have an impact on the senses used to detect thermal comfort. The model is called the Adaptive Predicted Mean Vote (aPMV) model. The aPMV model explains, by applying the cybernetics concept, the phenomena that the Predicted Mean Vote (PMV) is greater than the Actual Mean Vote (AMV) in free-running buildings, which has been revealed by many researchers in field studies. An Adaptive coefficient ({lambda}) representing the adaptive factors that affect the sense of thermal comfort has been proposed. The empirical coefficients in warm and cool conditions for the Chongqing area in China have been derived by applying the least square method to the monitored onsite environmental data and the thermal comfort survey results. (author)

  15. An adaptive predictive controller and its applications in power stations

    Energy Technology Data Exchange (ETDEWEB)

    Yang Zhiyuan; Lu Huiming; Zhang Xinggao [North China Electric Power University, Beijing (China); Song Chunping [Tsinghua University, Beijing (China). Dept. of Thermal Energy Engineering

    1999-07-01

    Based on the objective function in the form of integration of generalized model error, a globally convergent model reference adaptive predictive control algorithm (MRAPC) containing inertia-time compensators is presented in this paper. MRAPC has been successfully applied to control important thermal process of more than 20 units in many Chinese power stations. In this paper three representative examples are described. Continual operation results for years demonstrate that MRAPC is a successful attempt for the practical applications of adaptive control techniques. (author)

  16. Adaptive Outlier-tolerant Exponential Smoothing Prediction Algorithms with Applications to Predict the Temperature in Spacecraft

    OpenAIRE

    Hu Shaolin; Zhang Wei; Li Ye; Fan Shunxi

    2011-01-01

    The exponential smoothing prediction algorithm is widely used in spaceflight control and in process monitoring as well as in economical prediction. There are two key conundrums which are open: one is about the selective rule of the parameter in the exponential smoothing prediction, and the other is how to improve the bad influence of outliers on prediction. In this paper a new practical outlier-tolerant algorithm is built to select adaptively proper parameter, and the exponential smoothing pr...

  17. Prediction of fibre architecture and adaptation in diseased carotid bifurcations.

    LENUS (Irish Health Repository)

    Creane, Arthur

    2011-12-01

    Many studies have used patient-specific finite element models to estimate the stress environment in atherosclerotic plaques, attempting to correlate the magnitude of stress to plaque vulnerability. In complex geometries, few studies have incorporated the anisotropic material response of arterial tissue. This paper presents a fibre remodelling algorithm to predict the fibre architecture, and thus anisotropic material response in four patient-specific models of the carotid bifurcation. The change in fibre architecture during disease progression and its affect on the stress environment in the plaque were predicted. The mean fibre directions were assumed to lie at an angle between the two positive principal strain directions. The angle and the degree of dispersion were assumed to depend on the ratio of principal strain values. Results were compared with experimental observations and other numerical studies. In non-branching regions of each model, the typical double helix arterial fibre pattern was predicted while at the bifurcation and in regions of plaque burden, more complex fibre architectures were found. The predicted change in fibre architecture in the arterial tissue during plaque progression was found to alter the stress environment in the plaque. This suggests that the specimen-specific anisotropic response of the tissue should be taken into account to accurately predict stresses in the plaque. Since determination of the fibre architecture in vivo is a difficult task, the system presented here provides a useful method of estimating the fibre architecture in complex arterial geometries.

  18. 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.

  19. Disruption prediction with adaptive neural networks for ASDEX Upgrade

    International Nuclear Information System (INIS)

    Cannas, B.; Fanni, A.; Pautasso, G.; Sias, G.

    2011-01-01

    In this paper, an adaptive neural system has been built to predict the risk of disruption at ASDEX Upgrade. The system contains a Self Organizing Map, which determines the 'novelty' of the input of a Multi Layer Perceptron predictor module. The answer of the MLP predictor will be inhibited whenever a novel sample is detected. Furthermore, it is possible that the predictor produces a wrong answer although it is fed with known samples. In this case, a retraining procedure will be performed to update the MLP predictor in an incremental fashion using data coming from both the novelty detection, and from wrong predictions. In particular, a new update is performed whenever a missed alarm is triggered by the predictor. The performance of the adaptive predictor during the more recent experimental campaigns until November 2009 has been evaluated.

  20. Least-Square Prediction for Backward Adaptive Video Coding

    Directory of Open Access Journals (Sweden)

    Li Xin

    2006-01-01

    Full Text Available Almost all existing approaches towards video coding exploit the temporal redundancy by block-matching-based motion estimation and compensation. Regardless of its popularity, block matching still reflects an ad hoc understanding of the relationship between motion and intensity uncertainty models. In this paper, we present a novel backward adaptive approach, named "least-square prediction" (LSP, and demonstrate its potential in video coding. Motivated by the duality between edge contour in images and motion trajectory in video, we propose to derive the best prediction of the current frame from its causal past using least-square method. It is demonstrated that LSP is particularly effective for modeling video material with slow motion and can be extended to handle fast motion by temporal warping and forward adaptation. For typical QCIF test sequences, LSP often achieves smaller MSE than , full-search, quarter-pel block matching algorithm (BMA without the need of transmitting any overhead.

  1. An adaptive prediction and detection algorithm for multistream syndromic surveillance

    Directory of Open Access Journals (Sweden)

    Magruder Steve F

    2005-10-01

    Full Text Available Abstract Background Surveillance of Over-the-Counter pharmaceutical (OTC sales as a potential early indicator of developing public health conditions, in particular in cases of interest to biosurvellance, has been suggested in the literature. This paper is a continuation of a previous study in which we formulated the problem of estimating clinical data from OTC sales in terms of optimal LMS linear and Finite Impulse Response (FIR filters. In this paper we extend our results to predict clinical data multiple steps ahead using OTC sales as well as the clinical data itself. Methods The OTC data are grouped into a few categories and we predict the clinical data using a multichannel filter that encompasses all the past OTC categories as well as the past clinical data itself. The prediction is performed using FIR (Finite Impulse Response filters and the recursive least squares method in order to adapt rapidly to nonstationary behaviour. In addition, we inject simulated events in both clinical and OTC data streams to evaluate the predictions by computing the Receiver Operating Characteristic curves of a threshold detector based on predicted outputs. Results We present all prediction results showing the effectiveness of the combined filtering operation. In addition, we compute and present the performance of a detector using the prediction output. Conclusion Multichannel adaptive FIR least squares filtering provides a viable method of predicting public health conditions, as represented by clinical data, from OTC sales, and/or the clinical data. The potential value to a biosurveillance system cannot, however, be determined without studying this approach in the presence of transient events (nonstationary events of relatively short duration and fast rise times. Our simulated events superimposed on actual OTC and clinical data allow us to provide an upper bound on that potential value under some restricted conditions. Based on our ROC curves we argue that a

  2. Predicting the scanning branches of hysteretic soil water-retention capacity with use of the method of mathematical modeling

    Science.gov (United States)

    Terleev, V.; Ginevsky, R.; Lazarev, V.; Nikonorov, A.; Togo, I.; Topaj, A.; Moiseev, K.; Abakumov, E.; Melnichuk, A.; Dunaieva, I.

    2017-10-01

    A mathematical model of the hysteresis of the water-retention capacity of the soil is proposed. The parameters of the model are interpreted within the framework of physical concepts of the structure and capillary properties of soil pores. On the basis of the model, a computer program with an interface that allows for dialogue with the user is developed. The program has some of options: visualization of experimental data; identification of the model parameters with use of measured data by means of an optimizing algorithm; graphical presentation of the hysteresis loop with application of the assigned parameters. Using the program, computational experiments were carried out, which consisted in verifying the identifiability of the model parameters from data on the main branches, and also in testing the ability to predict the scanning branches of the hysteresis loop. For the experiments, literature data on two sandy soils were used. The absence of an “artificial pump effect” is proved. A sufficiently high accuracy of the prediction of the scanning branches of the hysteresis loop has been achieved in comparison with the three models of the precursors. The practical importance of the proposed model and computer program, which is developed on its basis, is to ensure the calculation of precision irrigation rates. The application of such rates in irrigation farming will help to prevent excess moisture from flowing beyond the root layer of the soil and, thus, minimize the unproductive loss of irrigation water and agrochemicals, as well as reduce the risk of groundwater contamination and natural water eutrophication.

  3. The Pupillary Orienting Response Predicts Adaptive Behavioral Adjustment after Errors.

    Directory of Open Access Journals (Sweden)

    Peter R Murphy

    Full Text Available Reaction time (RT is commonly observed to slow down after an error. This post-error slowing (PES has been thought to arise from the strategic adoption of a more cautious response mode following deployment of cognitive control. Recently, an alternative account has suggested that PES results from interference due to an error-evoked orienting response. We investigated whether error-related orienting may in fact be a pre-cursor to adaptive post-error behavioral adjustment when the orienting response resolves before subsequent trial onset. We measured pupil dilation, a prototypical measure of autonomic orienting, during performance of a choice RT task with long inter-stimulus intervals, and found that the trial-by-trial magnitude of the error-evoked pupil response positively predicted both PES magnitude and the likelihood that the following response would be correct. These combined findings suggest that the magnitude of the error-related orienting response predicts an adaptive change of response strategy following errors, and thereby promote a reconciliation of the orienting and adaptive control accounts of PES.

  4. A New Adaptive Framework for Collaborative Filtering Prediction.

    Science.gov (United States)

    Almosallam, Ibrahim A; Shang, Yi

    2008-06-01

    Collaborative filtering is one of the most successful techniques for recommendation systems and has been used in many commercial services provided by major companies including Amazon, TiVo and Netflix. In this paper we focus on memory-based collaborative filtering (CF). Existing CF techniques work well on dense data but poorly on sparse data. To address this weakness, we propose to use z-scores instead of explicit ratings and introduce a mechanism that adaptively combines global statistics with item-based values based on data density level. We present a new adaptive framework that encapsulates various CF algorithms and the relationships among them. An adaptive CF predictor is developed that can self adapt from user-based to item-based to hybrid methods based on the amount of available ratings. Our experimental results show that the new predictor consistently obtained more accurate predictions than existing CF methods, with the most significant improvement on sparse data sets. When applied to the Netflix Challenge data set, our method performed better than existing CF and singular value decomposition (SVD) methods and achieved 4.67% improvement over Netflix's system.

  5. Visual Bias Predicts Gait Adaptability in Novel Sensory Discordant Conditions

    Science.gov (United States)

    Brady, Rachel A.; Batson, Crystal D.; Peters, Brian T.; Mulavara, Ajitkumar P.; Bloomberg, Jacob J.

    2010-01-01

    We designed a gait training study that presented combinations of visual flow and support-surface manipulations to investigate the response of healthy adults to novel discordant sensorimotor conditions. We aimed to determine whether a relationship existed between subjects visual dependence and their postural stability and cognitive performance in a new discordant environment presented at the conclusion of training (Transfer Test). Our training system comprised a treadmill placed on a motion base facing a virtual visual scene that provided a variety of sensory challenges. Ten healthy adults completed 3 training sessions during which they walked on a treadmill at 1.1 m/s while receiving discordant support-surface and visual manipulations. At the first visit, in an analysis of normalized torso translation measured in a scene-movement-only condition, 3 of 10 subjects were classified as visually dependent. During the Transfer Test, all participants received a 2-minute novel exposure. In a combined measure of stride frequency and reaction time, the non-visually dependent subjects showed improved adaptation on the Transfer Test compared to their visually dependent counterparts. This finding suggests that individual differences in the ability to adapt to new sensorimotor conditions may be explained by individuals innate sensory biases. An accurate preflight assessment of crewmembers biases for visual dependence could be used to predict their propensities to adapt to novel sensory conditions. It may also facilitate the development of customized training regimens that could expedite adaptation to alternate gravitational environments.

  6. Performance analysis of joint multi-branch switched diversity and adaptive modulation schemes for spectrum sharing systems

    KAUST Repository

    Bouida, Zied; Qaraqe, Khalid A.; Abdallah, Mohamed M.; Alouini, Mohamed-Slim

    2012-01-01

    desired performance for the primary link. The proposed switching efficient scheme (SES) and bandwidth efficient scheme (BES) use the scan and wait combining technique (SWC) where a transmission occurs only when a branch with an acceptable performance

  7. NOAA ESRI Grid - sediment size predictions model in New York offshore planning area from Biogeography Branch

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset represents sediment size predictions from a sediment spatial model developed for the New York offshore spatial planning area. The model also includes...

  8. NOAA ESRI Grid - depth predictions bathymetry model in New York offshore planning area from Biogeography Branch

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset represents depth predictions from a bathymetric model developed for the New York offshore spatial planning area. The model also includes...

  9. NOAA ESRI Shapefile - sediment composition class predictions in New York offshore planning area from Biogeography Branch

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset represents sediment composition class predictions from a sediment spatial model developed for the New York offshore spatial planning area. The...

  10. Background-Modeling-Based Adaptive Prediction for Surveillance Video Coding.

    Science.gov (United States)

    Zhang, Xianguo; Huang, Tiejun; Tian, Yonghong; Gao, Wen

    2014-02-01

    The exponential growth of surveillance videos presents an unprecedented challenge for high-efficiency surveillance video coding technology. Compared with the existing coding standards that were basically developed for generic videos, surveillance video coding should be designed to make the best use of the special characteristics of surveillance videos (e.g., relative static background). To do so, this paper first conducts two analyses on how to improve the background and foreground prediction efficiencies in surveillance video coding. Following the analysis results, we propose a background-modeling-based adaptive prediction (BMAP) method. In this method, all blocks to be encoded are firstly classified into three categories. Then, according to the category of each block, two novel inter predictions are selectively utilized, namely, the background reference prediction (BRP) that uses the background modeled from the original input frames as the long-term reference and the background difference prediction (BDP) that predicts the current data in the background difference domain. For background blocks, the BRP can effectively improve the prediction efficiency using the higher quality background as the reference; whereas for foreground-background-hybrid blocks, the BDP can provide a better reference after subtracting its background pixels. Experimental results show that the BMAP can achieve at least twice the compression ratio on surveillance videos as AVC (MPEG-4 Advanced Video Coding) high profile, yet with a slightly additional encoding complexity. Moreover, for the foreground coding performance, which is crucial to the subjective quality of moving objects in surveillance videos, BMAP also obtains remarkable gains over several state-of-the-art methods.

  11. A Viral Branching Model for Predicting the Spread of Electronic Word-of-Mouth

    NARCIS (Netherlands)

    R.J.A. van der Lans (Ralf); G.H. van Bruggen (Gerrit); J. Eliashberg (Jehoshua); B. Wierenga (Berend)

    2009-01-01

    textabstractIn a viral marketing campaign an organization develops a marketing message, and stimulates customers to forward this message to their contacts. Despite its increasing popularity, there are no models yet that help marketers to predict how many customers a viral marketing campaign will

  12. Adaptive LINE-P: An Adaptive Linear Energy Prediction Model for Wireless Sensor Network Nodes.

    Science.gov (United States)

    Ahmed, Faisal; Tamberg, Gert; Le Moullec, Yannick; Annus, Paul

    2018-04-05

    In the context of wireless sensor networks, energy prediction models are increasingly useful tools that can facilitate the power management of the wireless sensor network (WSN) nodes. However, most of the existing models suffer from the so-called fixed weighting parameter, which limits their applicability when it comes to, e.g., solar energy harvesters with varying characteristics. Thus, in this article we propose the Adaptive LINE-P (all cases) model that calculates adaptive weighting parameters based on the stored energy profiles. Furthermore, we also present a profile compression method to reduce the memory requirements. To determine the performance of our proposed model, we have used real data for the solar and wind energy profiles. The simulation results show that our model achieves 90-94% accuracy and that the compressed method reduces memory overheads by 50% as compared to state-of-the-art models.

  13. The Role of Institutional Dual Embeddedness in the Strategic Local Adaptation of International Branch Campuses: Evidence from Malaysia and Singapore

    Science.gov (United States)

    Shams, Farshid; Huisman, Jeroen

    2016-01-01

    Past research revealed that International Branch Campuses (IBCs) are simultaneously under two types of isomorphic pressures. On the one hand, they are obliged to conform to the institutions of their host countries, which lead them towards homogenising with the local Higher Education Institutions (HEIs), hence deviate from their parent unit's…

  14. Using plural modeling for predicting decisions made by adaptive adversaries

    International Nuclear Information System (INIS)

    Buede, Dennis M.; Mahoney, Suzanne; Ezell, Barry; Lathrop, John

    2012-01-01

    Incorporating an appropriate representation of the likelihood of terrorist decision outcomes into risk assessments associated with weapons of mass destruction attacks has been a significant problem for countries around the world. Developing these likelihoods gets at the heart of the most difficult predictive problems: human decision making, adaptive adversaries, and adversaries about which very little is known. A plural modeling approach is proposed that incorporates estimates of all critical uncertainties: who is the adversary and what skills and resources are available to him, what information is known to the adversary and what perceptions of the important facts are held by this group or individual, what does the adversary know about the countermeasure actions taken by the government in question, what are the adversary's objectives and the priorities of those objectives, what would trigger the adversary to start an attack and what kind of success does the adversary desire, how realistic is the adversary in estimating the success of an attack, how does the adversary make a decision and what type of model best predicts this decision-making process. A computational framework is defined to aggregate the predictions from a suite of models, based on this broad array of uncertainties. A validation approach is described that deals with a significant scarcity of data.

  15. Adaptive learning compressive tracking based on Markov location prediction

    Science.gov (United States)

    Zhou, Xingyu; Fu, Dongmei; Yang, Tao; Shi, Yanan

    2017-03-01

    Object tracking is an interdisciplinary research topic in image processing, pattern recognition, and computer vision which has theoretical and practical application value in video surveillance, virtual reality, and automatic navigation. Compressive tracking (CT) has many advantages, such as efficiency and accuracy. However, when there are object occlusion, abrupt motion and blur, similar objects, and scale changing, the CT has the problem of tracking drift. We propose the Markov object location prediction to get the initial position of the object. Then CT is used to locate the object accurately, and the classifier parameter adaptive updating strategy is given based on the confidence map. At the same time according to the object location, extract the scale features, which is able to deal with object scale variations effectively. Experimental results show that the proposed algorithm has better tracking accuracy and robustness than current advanced algorithms and achieves real-time performance.

  16. Adaptive model predictive process control using neural networks

    Science.gov (United States)

    Buescher, K.L.; Baum, C.C.; Jones, R.D.

    1997-08-19

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

  17. Domain Adaptation for Pedestrian Detection Based on Prediction Consistency

    Directory of Open Access Journals (Sweden)

    Yu Li-ping

    2014-01-01

    Full Text Available Pedestrian detection is an active area of research in computer vision. It remains a quite challenging problem in many applications where many factors cause a mismatch between source dataset used to train the pedestrian detector and samples in the target scene. In this paper, we propose a novel domain adaptation model for merging plentiful source domain samples with scared target domain samples to create a scene-specific pedestrian detector that performs as well as rich target domain simples are present. Our approach combines the boosting-based learning algorithm with an entropy-based transferability, which is derived from the prediction consistency with the source classifications, to selectively choose the samples showing positive transferability in source domains to the target domain. Experimental results show that our approach can improve the detection rate, especially with the insufficient labeled data in target scene.

  18. ANN Model for Predicting the Impact of Submerged Aquatic Weeds Existence on the Hydraulic Performance of Branched Open Channel System Accompanied by Water Structures

    International Nuclear Information System (INIS)

    Abdeen, Mostafa A. M.; Abdin, Alla E.

    2007-01-01

    The existence of hydraulic structures in a branched open channel system urges the need for considering the gradually varied flow criterion in evaluating the different hydraulic characteristics in this type of open channel system. Computations of hydraulic characteristics such as flow rates and water surface profiles in branched open channel system with hydraulic structures require tremendous numerical effort especially when the flow cannot be assumed uniform. In addition, the existence of submerged aquatic weeds in this branched open channel system adds to the complexity of the evaluation of the different hydraulic characteristics for this system. However, this existence of aquatic weeds can not be neglected since it is very common in Egyptian open channel systems. Artificial Neural Network (ANN) has been widely utilized in the past decade in civil engineering applications for the simulation and prediction of the different physical phenomena and has proven its capabilities in the different fields. The present study aims towards introducing the use of ANN technique to model and predict the impact of submerged aquatic weeds existence on the hydraulic performance of branched open channel system. Specifically the current paper investigates a branched open channel system that consists of main channel supplies water to two branch channels that are infested by submerged aquatic weeds and have water structures such as clear over fall weirs and sluice gates. The results of this study showed that ANN technique was capable, with small computational effort and high accuracy, of predicting the impact of different infestation percentage for submerged aquatic weeds on the hydraulic performance of branched open channel system with two different hydraulic structures

  19. A branch point consensus from Arabidopsis found by non-circular analysis allows for better prediction of acceptor sites

    DEFF Research Database (Denmark)

    Tolstrup, Niels; Rouzé, Pierre; Brunak, Søren

    1997-01-01

    Little knowledge exists about branch points in plants; it has even been claimed that plant introns lack conserved branch point sequences similar to those found in vertebrate introns. A putative branch point consensus sequence for Arabidopsis thaliana resembling the well known metazoan consensus s...... in the recognition of true acceptor sites; the false positive rate being reduced by a factor of 2. We take this as an indication that the consensus found here is the genuine one and that the branch point does play a role in the proper recognition of the acceptor site in plants.......Little knowledge exists about branch points in plants; it has even been claimed that plant introns lack conserved branch point sequences similar to those found in vertebrate introns. A putative branch point consensus sequence for Arabidopsis thaliana resembling the well known metazoan consensus...... sequence has been proposed, but this is based on search of sequences similar to those in yeast and metazoa. Here we present a novel consensus sequence found by a non-circular approach. A hidden Markov model with a fixed A nucleotide was trained on sequences upstream of the acceptor site. The consensus...

  20. Adaptation.

    Science.gov (United States)

    Broom, Donald M

    2006-01-01

    The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and

  1. Evaluation of acoustic resonance at branch section in main steam line. Part 2. Proposal of method for predicting resonance frequency in steam flow

    International Nuclear Information System (INIS)

    Uchiyama, Yuta; Morita, Ryo

    2012-01-01

    Flow-induced acoustic resonances of piping system containing closed side-branches are sometimes encountered in power plants. Acoustic standing waves with large amplitude pressure fluctuation in closed side-branches are excited by the unstable shear layer which separates the mean flow in the main piping from the stagnant fluid in the branch. In U.S. NPP, the steam dryer had been damaged by high cycle fatigue due to acoustic-induced vibration under a power uprating condition. Our previous research developed the method for evaluating the acoustic resonance at the branch sections in actual power plants by using CFD. In the method, sound speed in wet steam is evaluated by its theory on the assumption of homogeneous flow, although it may be different from practical sound speed in wet steam. So, it is necessary to consider and introduce the most suitable model of practical sound speed in wet steam. In addition, we tried to develop simplified prediction method of the amplitude and frequency of pressure fluctuation in wet steam flow. Our previous experimental research clarified that resonance amplitude of fluctuating pressure at the top of the branch in wet steam. However, the resonance frequency in steam condition could not be estimated by using theoretical equation as the end correction in steam condition and sound speed in wet steam is not clarified as same reason as CFD. Therefore, in this study, we tried to evaluate the end correction in each dry and wet steam and sound speed of wet steam from experimental results. As a result, method for predicting resonance frequency by using theoretical equation in each wet and dry steam condition was proposed. (author)

  2. Predicting Adaptive Functioning of Mentally Retarded Persons in Community Settings.

    Science.gov (United States)

    Hull, John T.; Thompson, Joy C.

    1980-01-01

    The impact of a variety of individual, residential, and community variables on adaptive functioning of 369 retarded persons (18 to 73 years old) was examined using a multiple regression analysis. Individual characteristics (especially IQ) accounted for 21 percent of the variance, while environmental variables, primarily those related to…

  3. Subjective Technology Adaptivity Predicts Technology Use in Old Age.

    Science.gov (United States)

    Kamin, Stefan T; Lang, Frieder R; Beyer, Anja

    2017-01-01

    To date, not much is known about the psychological and motivational factors underlying technology use in late life. What are the interindividual determinants that lead older adults to invest in using technological innovations despite the age-related physiological changes that impose challenges on behavioral plasticity in everyday life? This research explores interindividual differences in subjective technology adaptivity - a general technology-related motivational resource that accounts for technology use in late life. More specifically, we investigate the influence of this factor relative to demographic characteristics, personality traits, and functional limitations in a longitudinal sample of community-dwelling older adults. We report results from a paper-and-pencil survey with 136 older adults between 59 and 92 years of age (mean = 71.4, SD = 7.4). Of those participants, 77 participated in a 2-year follow-up. We assessed self-reports of technology use, subjective technology adaptivity, functional limitations, and the personality traits openness to new experiences and neuroticism. Higher levels of subjective technology adaptivity were associated with technology use at the first measurement as well as increased use over the course of 2 years. Subjective technology adaptivity is a significant predictor of technology use in old age. Our findings contribute to improving the understanding of interindividual differences when using technological innovation in late life. Moreover, our findings have implications in the context of user involvement and may contribute to the successful development of innovative technology for older adults. © 2017 S. Karger AG, Basel.

  4. Predictive Acoustic Tracking with an Adaptive Neural Mechanism

    DEFF Research Database (Denmark)

    Shaikh, Danish; Manoonpong, Poramate

    2017-01-01

    model of the lizard peripheral auditory system to extract information regarding sound direction. This information is utilised by a neural machinery to learn the acoustic signal’s velocity through fast and unsupervised correlation-based learning adapted from differential Hebbian learning. This approach...

  5. Genomic islands predict functional adaptation in marine actinobacteria

    Energy Technology Data Exchange (ETDEWEB)

    Penn, Kevin; Jenkins, Caroline; Nett, Markus; Udwary, Daniel; Gontang, Erin; McGlinchey, Ryan; Foster, Brian; Lapidus, Alla; Podell, Sheila; Allen, Eric; Moore, Bradley; Jensen, Paul

    2009-04-01

    Linking functional traits to bacterial phylogeny remains a fundamental but elusive goal of microbial ecology 1. Without this information, it becomes impossible to resolve meaningful units of diversity and the mechanisms by which bacteria interact with each other and adapt to environmental change. Ecological adaptations among bacterial populations have been linked to genomic islands, strain-specific regions of DNA that house functionally adaptive traits 2. In the case of environmental bacteria, these traits are largely inferred from bioinformatic or gene expression analyses 2, thus leaving few examples in which the functions of island genes have been experimentally characterized. Here we report the complete genome sequences of Salinispora tropica and S. arenicola, the first cultured, obligate marine Actinobacteria 3. These two species inhabit benthic marine environments and dedicate 8-10percent of their genomes to the biosynthesis of secondary metabolites. Despite a close phylogenetic relationship, 25 of 37 secondary metabolic pathways are species-specific and located within 21 genomic islands, thus providing new evidence linking secondary metabolism to ecological adaptation. Species-specific differences are also observed in CRISPR sequences, suggesting that variations in phage immunity provide fitness advantages that contribute to the cosmopolitan distribution of S. arenicola 4. The two Salinispora genomes have evolved by complex processes that include the duplication and acquisition of secondary metabolite genes, the products of which provide immediate opportunities for molecular diversification and ecological adaptation. Evidence that secondary metabolic pathways are exchanged by Horizontal Gene Transfer (HGT) yet are fixed among globally distributed populations 5 supports a functional role for their products and suggests that pathway acquisition represents a previously unrecognized force driving bacterial diversification

  6. Branching structure and strain hardening of branched metallocene polyethylenes

    International Nuclear Information System (INIS)

    Torres, Enrique; Li, Si-Wan; Costeux, Stéphane; Dealy, John M.

    2015-01-01

    There have been a number of studies of a series of branched metallocene polyethylenes (BMPs) made in a solution, continuous stirred tank reactor (CSTR) polymerization. The materials studied vary in branching level in a systematic way, and the most highly branched members of the series exhibit mild strain hardening. An outstanding question is which types of branched molecules are responsible for strain hardening in extension. This question is explored here by use of polymerization and rheological models along with new data on the extensional flow behavior of the most highly branched members of the set. After reviewing all that is known about the effects of various branching structures in homogeneous polymers and comparing this with the structures predicted to be present in BMPs, it is concluded that in spite of their very low concentration, treelike molecules with branch-on-branch structure provide a large number of deeply buried inner segments that are essential for strain hardening in these polymers

  7. Branching structure and strain hardening of branched metallocene polyethylenes

    Energy Technology Data Exchange (ETDEWEB)

    Torres, Enrique; Li, Si-Wan; Costeux, Stéphane; Dealy, John M., E-mail: john.dealy@mcgill.ca [Department of Chemical Engineering, McGill University, Montreal, Quebec H3A 0C4 (Canada)

    2015-09-15

    There have been a number of studies of a series of branched metallocene polyethylenes (BMPs) made in a solution, continuous stirred tank reactor (CSTR) polymerization. The materials studied vary in branching level in a systematic way, and the most highly branched members of the series exhibit mild strain hardening. An outstanding question is which types of branched molecules are responsible for strain hardening in extension. This question is explored here by use of polymerization and rheological models along with new data on the extensional flow behavior of the most highly branched members of the set. After reviewing all that is known about the effects of various branching structures in homogeneous polymers and comparing this with the structures predicted to be present in BMPs, it is concluded that in spite of their very low concentration, treelike molecules with branch-on-branch structure provide a large number of deeply buried inner segments that are essential for strain hardening in these polymers.

  8. Predictive and Reactive Locomotor Adaptability in Healthy Elderly: A Systematic Review and Meta-Analysis.

    Science.gov (United States)

    Bohm, Sebastian; Mademli, Lida; Mersmann, Falk; Arampatzis, Adamantios

    2015-12-01

    Locomotor adaptability is based on the implementation of error-feedback information from previous perturbations to predictively adapt to expected perturbations (feedforward) and to facilitate reactive responses in recurring unexpected perturbations ('savings'). The effect of aging on predictive and reactive adaptability is yet unclear. However, such understanding is fundamental for the design and application of effective interventions targeting fall prevention. We systematically searched the Web of Science, MEDLINE, Embase and Science Direct databases as well as the reference lists of the eligible articles. A study was included if it addressed an investigation of the locomotor adaptability in response to repeated mechanical movement perturbations of healthy older adults (≥60 years). The weighted average effect size (WAES) of the general adaptability (adaptive motor responses to repeated perturbations) as well as predictive (after-effects) and reactive adaptation (feedback responses to a recurring unexpected perturbation) was calculated and tested for an overall effect. A subgroup analysis was performed regarding the factor age group [i.e., young (≤35 years) vs. older adults]. Furthermore, the methodological study quality was assessed. The review process yielded 18 studies [1009 participants, 613 older adults (70 ± 4 years)], which used various kinds of locomotor tasks and perturbations. The WAES for the general locomotor adaptability was 1.21 [95% confidence interval (CI) 0.68-1.74, n = 11] for the older and 1.39 (95% CI 0.90-1.89, n = 10) for the young adults with a significant (p locomotor adaptability in general and predictive and reactive adaptation in particular remain highly effective in the elderly, showing only minor, not statistically significant age-related deficits. Consequently, interventions which use adaptation and learning paradigms including the application of the mechanisms responsible for an effective predictive and reactive dynamic stability

  9. Analytic Model Predictive Control of Uncertain Nonlinear Systems: A Fuzzy Adaptive Approach

    Directory of Open Access Journals (Sweden)

    Xiuyan Peng

    2015-01-01

    Full Text Available A fuzzy adaptive analytic model predictive control method is proposed in this paper for a class of uncertain nonlinear systems. Specifically, invoking the standard results from the Moore-Penrose inverse of matrix, the unmatched problem which exists commonly in input and output dimensions of systems is firstly solved. Then, recurring to analytic model predictive control law, combined with fuzzy adaptive approach, the fuzzy adaptive predictive controller synthesis for the underlying systems is developed. To further reduce the impact of fuzzy approximation error on the system and improve the robustness of the system, the robust compensation term is introduced. It is shown that by applying the fuzzy adaptive analytic model predictive controller the rudder roll stabilization system is ultimately uniformly bounded stabilized in the H-infinity sense. Finally, simulation results demonstrate the effectiveness of the proposed method.

  10. Beyond Reactive Planning: Self Adaptive Software and Self Modeling Software in Predictive Deliberation Management

    National Research Council Canada - National Science Library

    Lenahan, Jack; Nash, Michael P; Charles, Phil

    2008-01-01

    .... We present the following hypothesis: predictive deliberation management using self-adapting and self-modeling software will be required to provide mission planning adjustments after the start of a mission...

  11. Comprehensive adaptive mesh refinement in wrinkling prediction analysis

    NARCIS (Netherlands)

    Selman, A.; Meinders, Vincent T.; Huetink, Han; van den Boogaard, Antonius H.

    2002-01-01

    Discretisation errors indicator, contact free wrinkling and wrinkling with contact indicators are, in a challenging task, brought together and used in a comprehensive approach to wrinkling prediction analysis in thin sheet metal forming processes.

  12. Predicting Career Adaptability through Self-Esteem and Social Support: A Research on Young Adults

    Science.gov (United States)

    Ataç, Lale Oral; Dirik, Deniz; Tetik, Hilmiye Türesin

    2018-01-01

    The purpose of this study is to investigate the relationship between career adaptability and self-esteem, and analyze the moderating role of social support in this relationship on a sample of 313 young adults. The results of the study confirm that career adaptability is significantly predicted by self-esteem. Moreover, findings suggest that (1)…

  13. Episodic memories predict adaptive value-based decision-making

    Science.gov (United States)

    Murty, Vishnu; FeldmanHall, Oriel; Hunter, Lindsay E.; Phelps, Elizabeth A; Davachi, Lila

    2016-01-01

    Prior research illustrates that memory can guide value-based decision-making. For example, previous work has implicated both working memory and procedural memory (i.e., reinforcement learning) in guiding choice. However, other types of memories, such as episodic memory, may also influence decision-making. Here we test the role for episodic memory—specifically item versus associative memory—in supporting value-based choice. Participants completed a task where they first learned the value associated with trial unique lotteries. After a short delay, they completed a decision-making task where they could choose to re-engage with previously encountered lotteries, or new never before seen lotteries. Finally, participants completed a surprise memory test for the lotteries and their associated values. Results indicate that participants chose to re-engage more often with lotteries that resulted in high versus low rewards. Critically, participants not only formed detailed, associative memories for the reward values coupled with individual lotteries, but also exhibited adaptive decision-making only when they had intact associative memory. We further found that the relationship between adaptive choice and associative memory generalized to more complex, ecologically valid choice behavior, such as social decision-making. However, individuals more strongly encode experiences of social violations—such as being treated unfairly, suggesting a bias for how individuals form associative memories within social contexts. Together, these findings provide an important integration of episodic memory and decision-making literatures to better understand key mechanisms supporting adaptive behavior. PMID:26999046

  14. Performance Prediction of Constrained Waveform Design for Adaptive Radar

    Science.gov (United States)

    2016-11-01

    the famous Woodward quote, having a ubiquitous feeling for all radar waveform design (and performance prediction) researchers , that is found at the end...discuss research that develops performance prediction models to quantify the impact on SINR when an amplitude constraint is placed on a radar waveform...optimize the radar perfor- mance for the particular scenario and tasks. There have also been several survey papers on various topics in waveform design for

  15. Whatever after next? adaptive predictions based on short- and long-term memory in visual search

    OpenAIRE

    Conci, M.; Zellin, M.; Muller, Hermann J.

    2012-01-01

    Generating predictions for task-relevant goals is a fundamental requirement of human information processing, as it ensures adaptive success in our complex natural environment. Clark (in press) proposed a model of hierarchical predictive processing, in which perception, attention, and learning are unified within a coherent framework. In this view, incoming sensory signals are constantly matched with top-down expectations or predictions, with the aim of minimizing the prediction error to genera...

  16. Adaptive plasticity in speech perception: Effects of external information and internal predictions.

    Science.gov (United States)

    Guediche, Sara; Fiez, Julie A; Holt, Lori L

    2016-07-01

    When listeners encounter speech under adverse listening conditions, adaptive adjustments in perception can improve comprehension over time. In some cases, these adaptive changes require the presence of external information that disambiguates the distorted speech signals, whereas in other cases mere exposure is sufficient. Both external (e.g., written feedback) and internal (e.g., prior word knowledge) sources of information can be used to generate predictions about the correct mapping of a distorted speech signal. We hypothesize that these predictions provide a basis for determining the discrepancy between the expected and actual speech signal that can be used to guide adaptive changes in perception. This study provides the first empirical investigation that manipulates external and internal factors through (a) the availability of explicit external disambiguating information via the presence or absence of postresponse orthographic information paired with a repetition of the degraded stimulus, and (b) the accuracy of internally generated predictions; an acoustic distortion is introduced either abruptly or incrementally. The results demonstrate that the impact of external information on adaptive plasticity is contingent upon whether the intelligibility of the stimuli permits accurate internally generated predictions during exposure. External information sources enhance adaptive plasticity only when input signals are severely degraded and cannot reliably access internal predictions. This is consistent with a computational framework for adaptive plasticity in which error-driven supervised learning relies on the ability to compute sensory prediction error signals from both internal and external sources of information. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  17. Branches of the landscape

    International Nuclear Information System (INIS)

    Dine, Michael; O'Neil, Deva; Sun Zheng

    2005-01-01

    With respect to the question of supersymmetry breaking, there are three branches of the flux landscape. On one of these, if one requires small cosmological constant, supersymmetry breaking is predominantly at the fundamental scale; on another, the distribution is roughly flat on a logarithmic scale; on the third, the preponderance of vacua are at very low scale. A priori, as we will explain, one can say little about the first branch. The vast majority of these states are not accessible even to crude, approximate analysis. On the other two branches one can hope to do better. But as a result of the lack of access to branch one, and our poor understanding of cosmology, we can at best conjecture about whether string theory predicts low energy supersymmetry or not. If we hypothesize that are on branch two or three, distinctive predictions may be possible. We comment of the status of naturalness within the landscape, deriving, for example, the statistics of the first branch from simple effective field theory reasoning

  18. Cloud-based adaptive exon prediction for DNA analysis.

    Science.gov (United States)

    Putluri, Srinivasareddy; Zia Ur Rahman, Md; Fathima, Shaik Yasmeen

    2018-02-01

    Cloud computing offers significant research and economic benefits to healthcare organisations. Cloud services provide a safe place for storing and managing large amounts of such sensitive data. Under conventional flow of gene information, gene sequence laboratories send out raw and inferred information via Internet to several sequence libraries. DNA sequencing storage costs will be minimised by use of cloud service. In this study, the authors put forward a novel genomic informatics system using Amazon Cloud Services, where genomic sequence information is stored and accessed for processing. True identification of exon regions in a DNA sequence is a key task in bioinformatics, which helps in disease identification and design drugs. Three base periodicity property of exons forms the basis of all exon identification techniques. Adaptive signal processing techniques found to be promising in comparison with several other methods. Several adaptive exon predictors (AEPs) are developed using variable normalised least mean square and its maximum normalised variants to reduce computational complexity. Finally, performance evaluation of various AEPs is done based on measures such as sensitivity, specificity and precision using various standard genomic datasets taken from National Center for Biotechnology Information genomic sequence database.

  19. Computer prediction of subsurface radionuclide transport: an adaptive numerical method

    International Nuclear Information System (INIS)

    Neuman, S.P.

    1983-01-01

    Radionuclide transport in the subsurface is often modeled with the aid of the advection-dispersion equation. A review of existing computer methods for the solution of this equation shows that there is need for improvement. To answer this need, a new adaptive numerical method is proposed based on an Eulerian-Lagrangian formulation. The method is based on a decomposition of the concentration field into two parts, one advective and one dispersive, in a rigorous manner that does not leave room for ambiguity. The advective component of steep concentration fronts is tracked forward with the aid of moving particles clustered around each front. Away from such fronts the advection problem is handled by an efficient modified method of characteristics called single-step reverse particle tracking. When a front dissipates with time, its forward tracking stops automatically and the corresponding cloud of particles is eliminated. The dispersion problem is solved by an unconventional Lagrangian finite element formulation on a fixed grid which involves only symmetric and diagonal matrices. Preliminary tests against analytical solutions of ne- and two-dimensional dispersion in a uniform steady state velocity field suggest that the proposed adaptive method can handle the entire range of Peclet numbers from 0 to infinity, with Courant numbers well in excess of 1

  20. Adaptation is.... Predicting malaria's changing course in East Africa

    International Development Research Centre (IDRC) Digital Library (Canada)

    IDRC

    Health experts say controlling malaria is crucial if the three East African nations are to achieve the UN Millennium. Development Goal of halving the incidence of infectious diseases such as malaria, tuberculosis, and HIV/AIDS by 2015. Looking ahead:Prevention and treatment. Improved malaria prediction will be an.

  1. A highly accurate predictive-adaptive method for lithium-ion battery remaining discharge energy prediction in electric vehicle applications

    International Nuclear Information System (INIS)

    Liu, Guangming; Ouyang, Minggao; Lu, Languang; Li, Jianqiu; Hua, Jianfeng

    2015-01-01

    Highlights: • An energy prediction (EP) method is introduced for battery E RDE determination. • EP determines E RDE through coupled prediction of future states, parameters, and output. • The PAEP combines parameter adaptation and prediction to update model parameters. • The PAEP provides improved E RDE accuracy compared with DC and other EP methods. - Abstract: In order to estimate the remaining driving range (RDR) in electric vehicles, the remaining discharge energy (E RDE ) of the applied battery system needs to be precisely predicted. Strongly affected by the load profiles, the available E RDE varies largely in real-world applications and requires specific determination. However, the commonly-used direct calculation (DC) method might result in certain energy prediction errors by relating the E RDE directly to the current state of charge (SOC). To enhance the E RDE accuracy, this paper presents a battery energy prediction (EP) method based on the predictive control theory, in which a coupled prediction of future battery state variation, battery model parameter change, and voltage response, is implemented on the E RDE prediction horizon, and the E RDE is subsequently accumulated and real-timely optimized. Three EP approaches with different model parameter updating routes are introduced, and the predictive-adaptive energy prediction (PAEP) method combining the real-time parameter identification and the future parameter prediction offers the best potential. Based on a large-format lithium-ion battery, the performance of different E RDE calculation methods is compared under various dynamic profiles. Results imply that the EP methods provide much better accuracy than the traditional DC method, and the PAEP could reduce the E RDE error by more than 90% and guarantee the relative energy prediction error under 2%, proving as a proper choice in online E RDE prediction. The correlation of SOC estimation and E RDE calculation is then discussed to illustrate the

  2. Genetic algorithm based adaptive neural network ensemble and its application in predicting carbon flux

    Science.gov (United States)

    Xue, Y.; Liu, S.; Hu, Y.; Yang, J.; Chen, Q.

    2007-01-01

    To improve the accuracy in prediction, Genetic Algorithm based Adaptive Neural Network Ensemble (GA-ANNE) is presented. Intersections are allowed between different training sets based on the fuzzy clustering analysis, which ensures the diversity as well as the accuracy of individual Neural Networks (NNs). Moreover, to improve the accuracy of the adaptive weights of individual NNs, GA is used to optimize the cluster centers. Empirical results in predicting carbon flux of Duke Forest reveal that GA-ANNE can predict the carbon flux more accurately than Radial Basis Function Neural Network (RBFNN), Bagging NN ensemble, and ANNE. ?? 2007 IEEE.

  3. Adaptation and Implementation of Predictive Maintenance Technique with Nondestructive Testing for Power Plants

    International Nuclear Information System (INIS)

    Jung, Gye Jo; Jung, Nam Gun

    2010-01-01

    Many forces are pressuring utilities to reduce operating and maintenance costs without cutting back on reliability or availability. Many utility managers are re-evaluating maintenance strategies to meet these demands. To utilities how to reduce maintenance costs and extent the effective operating life of equipment, predictive maintenance technique can be adapted. Predictive maintenance had three types program which are in-house program, engineering company program and mixed program. We can approach successful predictive maintenance program with 'smart trust' concept

  4. Transitional states in marine fisheries: adapting to predicted global change.

    Science.gov (United States)

    MacNeil, M Aaron; Graham, Nicholas A J; Cinner, Joshua E; Dulvy, Nicholas K; Loring, Philip A; Jennings, Simon; Polunin, Nicholas V C; Fisk, Aaron T; McClanahan, Tim R

    2010-11-27

    Global climate change has the potential to substantially alter the production and community structure of marine fisheries and modify the ongoing impacts of fishing. Fish community composition is already changing in some tropical, temperate and polar ecosystems, where local combinations of warming trends and higher environmental variation anticipate the changes likely to occur more widely over coming decades. Using case studies from the Western Indian Ocean, the North Sea and the Bering Sea, we contextualize the direct and indirect effects of climate change on production and biodiversity and, in turn, on the social and economic aspects of marine fisheries. Climate warming is expected to lead to (i) yield and species losses in tropical reef fisheries, driven primarily by habitat loss; (ii) community turnover in temperate fisheries, owing to the arrival and increasing dominance of warm-water species as well as the reduced dominance and departure of cold-water species; and (iii) increased diversity and yield in Arctic fisheries, arising from invasions of southern species and increased primary production resulting from ice-free summer conditions. How societies deal with such changes will depend largely on their capacity to adapt--to plan and implement effective responses to change--a process heavily influenced by social, economic, political and cultural conditions.

  5. Saccadic gain adaptation is predicted by the statistics of natural fluctuations in oculomotor function

    Directory of Open Access Journals (Sweden)

    Mark V Albert

    2012-12-01

    Full Text Available Due to multiple factors such as fatigue, muscle strengthening, and neural plasticity, the responsiveness of the motor apparatus to neural commands changes over time. To enable precise movements the nervous system must adapt to compensate for these changes. Recent models of motor adaptation derive from assumptions about the way the motor apparatus changes. Characterizing these changes is difficult because motor adaptation happens at the same time, masking most of the effects of ongoing changes. Here, we analyze eye movements of monkeys with lesions to the posterior cerebellar vermis that impair adaptation. Their fluctuations better reveal the underlying changes of the motor system over time. When these measured, unadapted changes are used to derive optimal motor adaptation rules the prediction precision significantly improves. Among three models that similarly fit single-day adaptation results, the model that also matches the temporal correlations of the nonadapting saccades most accurately predicts multiple day adaptation. Saccadic gain adaptation is well matched to the natural statistics of fluctuations of the oculomotor plant.

  6. Adaptive DIT-Based Fringe Tracking and Prediction at IOTA

    Science.gov (United States)

    Wilson, Edward; Pedretti, Ettore; Bregman, Jesse; Mah, Robert W.; Traub, Wesley A.

    2004-01-01

    An automatic fringe tracking system has been developed and implemented at the Infrared Optical Telescope Array (IOTA). In testing during May 2002, the system successfully minimized the optical path differences (OPDs) for all three baselines at IOTA. Based on sliding window discrete Fourier transform (DFT) calculations that were optimized for computational efficiency and robustness to atmospheric disturbances, the algorithm has also been tested extensively on off-line data. Implemented in ANSI C on the 266 MHZ PowerPC processor running the VxWorks real-time operating system, the algorithm runs in approximately 2.0 milliseconds per scan (including all three interferograms), using the science camera and piezo scanners to measure and correct the OPDs. Preliminary analysis on an extension of this algorithm indicates a potential for predictive tracking, although at present, real-time implementation of this extension would require significantly more computational capacity.

  7. A Personalized Predictive Framework for Multivariate Clinical Time Series via Adaptive Model Selection.

    Science.gov (United States)

    Liu, Zitao; Hauskrecht, Milos

    2017-11-01

    Building of an accurate predictive model of clinical time series for a patient is critical for understanding of the patient condition, its dynamics, and optimal patient management. Unfortunately, this process is not straightforward. First, patient-specific variations are typically large and population-based models derived or learned from many different patients are often unable to support accurate predictions for each individual patient. Moreover, time series observed for one patient at any point in time may be too short and insufficient to learn a high-quality patient-specific model just from the patient's own data. To address these problems we propose, develop and experiment with a new adaptive forecasting framework for building multivariate clinical time series models for a patient and for supporting patient-specific predictions. The framework relies on the adaptive model switching approach that at any point in time selects the most promising time series model out of the pool of many possible models, and consequently, combines advantages of the population, patient-specific and short-term individualized predictive models. We demonstrate that the adaptive model switching framework is very promising approach to support personalized time series prediction, and that it is able to outperform predictions based on pure population and patient-specific models, as well as, other patient-specific model adaptation strategies.

  8. Predicting respiratory tumor motion with multi-dimensional adaptive filters and support vector regression

    International Nuclear Information System (INIS)

    Riaz, Nadeem; Wiersma, Rodney; Mao Weihua; Xing Lei; Shanker, Piyush; Gudmundsson, Olafur; Widrow, Bernard

    2009-01-01

    Intra-fraction tumor tracking methods can improve radiation delivery during radiotherapy sessions. Image acquisition for tumor tracking and subsequent adjustment of the treatment beam with gating or beam tracking introduces time latency and necessitates predicting the future position of the tumor. This study evaluates the use of multi-dimensional linear adaptive filters and support vector regression to predict the motion of lung tumors tracked at 30 Hz. We expand on the prior work of other groups who have looked at adaptive filters by using a general framework of a multiple-input single-output (MISO) adaptive system that uses multiple correlated signals to predict the motion of a tumor. We compare the performance of these two novel methods to conventional methods like linear regression and single-input, single-output adaptive filters. At 400 ms latency the average root-mean-square-errors (RMSEs) for the 14 treatment sessions studied using no prediction, linear regression, single-output adaptive filter, MISO and support vector regression are 2.58, 1.60, 1.58, 1.71 and 1.26 mm, respectively. At 1 s, the RMSEs are 4.40, 2.61, 3.34, 2.66 and 1.93 mm, respectively. We find that support vector regression most accurately predicts the future tumor position of the methods studied and can provide a RMSE of less than 2 mm at 1 s latency. Also, a multi-dimensional adaptive filter framework provides improved performance over single-dimension adaptive filters. Work is underway to combine these two frameworks to improve performance.

  9. Data Analytics Based Dual-Optimized Adaptive Model Predictive Control for the Power Plant Boiler

    Directory of Open Access Journals (Sweden)

    Zhenhao Tang

    2017-01-01

    Full Text Available To control the furnace temperature of a power plant boiler precisely, a dual-optimized adaptive model predictive control (DoAMPC method is designed based on the data analytics. In the proposed DoAMPC, an accurate predictive model is constructed adaptively by the hybrid algorithm of the least squares support vector machine and differential evolution method. Then, an optimization problem is constructed based on the predictive model and many constraint conditions. To control the boiler furnace temperature, the differential evolution method is utilized to decide the control variables by solving the optimization problem. The proposed method can adapt to the time-varying situation by updating the sample data. The experimental results based on practical data illustrate that the DoAMPC can control the boiler furnace temperature with errors of less than 1.5% which can meet the requirements of the real production process.

  10. NOAA ESRI Grid - seafloor hardbottom occurrence predictions model in New York offshore planning area from Biogeography Branch

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset represents hard bottom occurrence predictions from a spatial model developed for the New York offshore spatial planning area. This model builds upon the...

  11. NOAA ESRI Grid - depth uncertainty predictions in New York offshore planning area from Biogeography Branch bathymetry model

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset represents depth uncertainty predictions from a bathymetric model developed for the New York offshore spatial planning area. The model also includes...

  12. NOAA ESRI Grid - predictions of seabird diversity in the New York offshore planning area made by the NOAA Biogeography Branch

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset represents seabird diversity predictions from spatial models developed for the New York offshore spatial planning area. This raster was derived from...

  13. Dynamic Crack Branching - A Photoelastic Evaluation,

    Science.gov (United States)

    1982-05-01

    0.41 mPai and a 0.18 MPa, and predicted a theoretical kinking angle of 84°whichagreed well with experimentally measured angle. After crack kinking...Consistent crack branching’at KIb = 2.04 MPaI -i- and r = 1.3 mm verified this crack branching criterion. The crack branching angle predicted by--.’ DD

  14. Branched-chain amino acid (BCAA) supplementation enhances adaptability to exercise training of mice with a muscle-specific defect in the control of BCAA catabolism.

    Science.gov (United States)

    Xu, Minjun; Kitaura, Yasuyuki; Shindo, Daichi; Shimomura, Yoshiharu

    2018-03-01

    Branched-chain α-keto acid dehydrogenase (BCKDH) kinase (BDK) suppresses the branched-chain amino acid (BCAA) catabolism by inactivation of the BCKDH complex. The muscle-specific BDK-deficient (BDK-mKO) mice showed accelerated BCAA oxidation in muscle and decreased endurance capacity after training (Xu et al. PLoS One. 12 (2017) e0180989). We here report that BCAA supplementation overcompensated endurance capacity in BDK-mKO mice after training.

  15. DNApi: A De Novo Adapter Prediction Algorithm for Small RNA Sequencing Data.

    Science.gov (United States)

    Tsuji, Junko; Weng, Zhiping

    2016-01-01

    With the rapid accumulation of publicly available small RNA sequencing datasets, third-party meta-analysis across many datasets is becoming increasingly powerful. Although removing the 3´ adapter is an essential step for small RNA sequencing analysis, the adapter sequence information is not always available in the metadata. The information can be also erroneous even when it is available. In this study, we developed DNApi, a lightweight Python software package that predicts the 3´ adapter sequence de novo and provides the user with cleansed small RNA sequences ready for down stream analysis. Tested on 539 publicly available small RNA libraries accompanied with 3´ adapter sequences in their metadata, DNApi shows near-perfect accuracy (98.5%) with fast runtime (~2.85 seconds per library) and efficient memory usage (~43 MB on average). In addition to 3´ adapter prediction, it is also important to classify whether the input small RNA libraries were already processed, i.e. the 3´ adapters were removed. DNApi perfectly judged that given another batch of datasets, 192 publicly available processed libraries were "ready-to-map" small RNA sequence. DNApi is compatible with Python 2 and 3, and is available at https://github.com/jnktsj/DNApi. The 731 small RNA libraries used for DNApi evaluation were from human tissues and were carefully and manually collected. This study also provides readers with the curated datasets that can be integrated into their studies.

  16. Adaptive Disturbance Estimation for Offset-Free SISO Model Predictive Control

    DEFF Research Database (Denmark)

    Huusom, Jakob Kjøbsted; Poulsen, Niels Kjølstad; Jørgensen, Sten Bay

    2011-01-01

    Offset free tracking in Model Predictive Control requires estimation of unmeasured disturbances or the inclusion of an integrator. An algorithm for estimation of an unknown disturbance based on adaptive estimation with time varying forgetting is introduced and benchmarked against the classical...

  17. An Adaptive Handover Prediction Scheme for Seamless Mobility Based Wireless Networks

    Directory of Open Access Journals (Sweden)

    Ali Safa Sadiq

    2014-01-01

    Full Text Available We propose an adaptive handover prediction (AHP scheme for seamless mobility based wireless networks. That is, the AHP scheme incorporates fuzzy logic with AP prediction process in order to lend cognitive capability to handover decision making. Selection metrics, including received signal strength, mobile node relative direction towards the access points in the vicinity, and access point load, are collected and considered inputs of the fuzzy decision making system in order to select the best preferable AP around WLANs. The obtained handover decision which is based on the calculated quality cost using fuzzy inference system is also based on adaptable coefficients instead of fixed coefficients. In other words, the mean and the standard deviation of the normalized network prediction metrics of fuzzy inference system, which are collected from available WLANs are obtained adaptively. Accordingly, they are applied as statistical information to adjust or adapt the coefficients of membership functions. In addition, we propose an adjustable weight vector concept for input metrics in order to cope with the continuous, unpredictable variation in their membership degrees. Furthermore, handover decisions are performed in each MN independently after knowing RSS, direction toward APs, and AP load. Finally, performance evaluation of the proposed scheme shows its superiority compared with representatives of the prediction approaches.

  18. Lossless medical image compression using geometry-adaptive partitioning and least square-based prediction.

    Science.gov (United States)

    Song, Xiaoying; Huang, Qijun; Chang, Sheng; He, Jin; Wang, Hao

    2018-06-01

    To improve the compression rates for lossless compression of medical images, an efficient algorithm, based on irregular segmentation and region-based prediction, is proposed in this paper. Considering that the first step of a region-based compression algorithm is segmentation, this paper proposes a hybrid method by combining geometry-adaptive partitioning and quadtree partitioning to achieve adaptive irregular segmentation for medical images. Then, least square (LS)-based predictors are adaptively designed for each region (regular subblock or irregular subregion). The proposed adaptive algorithm not only exploits spatial correlation between pixels but it utilizes local structure similarity, resulting in efficient compression performance. Experimental results show that the average compression performance of the proposed algorithm is 10.48, 4.86, 3.58, and 0.10% better than that of JPEG 2000, CALIC, EDP, and JPEG-LS, respectively. Graphical abstract ᅟ.

  19. Adaptive neuro fuzzy system for modelling and prediction of distance pantograph catenary in railway transportation

    Science.gov (United States)

    Panoiu, M.; Panoiu, C.; Lihaciu, I. L.

    2018-01-01

    This research presents an adaptive neuro-fuzzy system which is used in the prediction of the distance between the pantograph and contact line of the electrical locomotives used in railway transportation. In railway transportation any incident that occurs in the electrical system can have major negative effects: traffic interrupts, equipment destroying. Therefore, a prediction as good as possible of such situations is very useful. In the paper was analyzing the possibility of modeling and prediction the variation of the distance between the pantograph and the contact line using intelligent techniques

  20. Respiratory motion prediction by using the adaptive neuro fuzzy inference system (ANFIS)

    International Nuclear Information System (INIS)

    Kakar, Manish; Nystroem, Haakan; Aarup, Lasse Rye; Noettrup, Trine Jakobi; Olsen, Dag Rune

    2005-01-01

    The quality of radiation therapy delivered for treating cancer patients is related to set-up errors and organ motion. Due to the margins needed to ensure adequate target coverage, many breast cancer patients have been shown to develop late side effects such as pneumonitis and cardiac damage. Breathing-adapted radiation therapy offers the potential for precise radiation dose delivery to a moving target and thereby reduces the side effects substantially. However, the basic requirement for breathing-adapted radiation therapy is to track and predict the target as precisely as possible. Recent studies have addressed the problem of organ motion prediction by using different methods including artificial neural network and model based approaches. In this study, we propose to use a hybrid intelligent system called ANFIS (the adaptive neuro fuzzy inference system) for predicting respiratory motion in breast cancer patients. In ANFIS, we combine both the learning capabilities of a neural network and reasoning capabilities of fuzzy logic in order to give enhanced prediction capabilities, as compared to using a single methodology alone. After training ANFIS and checking for prediction accuracy on 11 breast cancer patients, it was found that the RMSE (root-mean-square error) can be reduced to sub-millimetre accuracy over a period of 20 s provided the patient is assisted with coaching. The average RMSE for the un-coached patients was 35% of the respiratory amplitude and for the coached patients 6% of the respiratory amplitude

  1. Respiratory motion prediction by using the adaptive neuro fuzzy inference system (ANFIS)

    Energy Technology Data Exchange (ETDEWEB)

    Kakar, Manish [Department of Radiation Biology, Norwegian Radium Hospital, Montebello, 0310 Oslo (Norway); Nystroem, Haakan [Department of Radiation Oncology, The Finsen Centre, Rigshospitalet, Copenhagen (Denmark); Aarup, Lasse Rye [Department of Radiation Oncology, The Finsen Centre, Rigshospitalet, Copenhagen (Denmark); Noettrup, Trine Jakobi [Department of Radiation Oncology, The Finsen Centre, Rigshospitalet, Copenhagen (Denmark); Olsen, Dag Rune [Department of Radiation Biology, Norwegian Radium Hospital, Montebello, 0310 Oslo (Norway); Department of Medical Physics and Technology, Norwegian Radium Hospital, Oslo (Norway); Department of Physics, University of Oslo (Norway)

    2005-10-07

    The quality of radiation therapy delivered for treating cancer patients is related to set-up errors and organ motion. Due to the margins needed to ensure adequate target coverage, many breast cancer patients have been shown to develop late side effects such as pneumonitis and cardiac damage. Breathing-adapted radiation therapy offers the potential for precise radiation dose delivery to a moving target and thereby reduces the side effects substantially. However, the basic requirement for breathing-adapted radiation therapy is to track and predict the target as precisely as possible. Recent studies have addressed the problem of organ motion prediction by using different methods including artificial neural network and model based approaches. In this study, we propose to use a hybrid intelligent system called ANFIS (the adaptive neuro fuzzy inference system) for predicting respiratory motion in breast cancer patients. In ANFIS, we combine both the learning capabilities of a neural network and reasoning capabilities of fuzzy logic in order to give enhanced prediction capabilities, as compared to using a single methodology alone. After training ANFIS and checking for prediction accuracy on 11 breast cancer patients, it was found that the RMSE (root-mean-square error) can be reduced to sub-millimetre accuracy over a period of 20 s provided the patient is assisted with coaching. The average RMSE for the un-coached patients was 35% of the respiratory amplitude and for the coached patients 6% of the respiratory amplitude.

  2. Predictive models for PEM-electrolyzer performance using adaptive neuro-fuzzy inference systems

    Energy Technology Data Exchange (ETDEWEB)

    Becker, Steffen [University of Tasmania, Hobart 7001, Tasmania (Australia); Karri, Vishy [Australian College of Kuwait (Kuwait)

    2010-09-15

    Predictive models were built using neural network based Adaptive Neuro-Fuzzy Inference Systems for hydrogen flow rate, electrolyzer system-efficiency and stack-efficiency respectively. A comprehensive experimental database forms the foundation for the predictive models. It is argued that, due to the high costs associated with the hydrogen measuring equipment; these reliable predictive models can be implemented as virtual sensors. These models can also be used on-line for monitoring and safety of hydrogen equipment. The quantitative accuracy of the predictive models is appraised using statistical techniques. These mathematical models are found to be reliable predictive tools with an excellent accuracy of {+-}3% compared with experimental values. The predictive nature of these models did not show any significant bias to either over prediction or under prediction. These predictive models, built on a sound mathematical and quantitative basis, can be seen as a step towards establishing hydrogen performance prediction models as generic virtual sensors for wider safety and monitoring applications. (author)

  3. Soliciting scientific information and beliefs in predictive modeling and adaptive management

    Science.gov (United States)

    Glynn, P. D.; Voinov, A. A.; Shapiro, C. D.

    2015-12-01

    Post-normal science requires public engagement and adaptive corrections in addressing issues with high complexity and uncertainty. An adaptive management framework is presented for the improved management of natural resources and environments through a public participation process. The framework solicits the gathering and transformation and/or modeling of scientific information but also explicitly solicits the expression of participant beliefs. Beliefs and information are compared, explicitly discussed for alignments or misalignments, and ultimately melded back together as a "knowledge" basis for making decisions. An effort is made to recognize the human or participant biases that may affect the information base and the potential decisions. In a separate step, an attempt is made to recognize and predict the potential "winners" and "losers" (perceived or real) of any decision or action. These "winners" and "losers" include present human communities with different spatial, demographic or socio-economic characteristics as well as more dispersed or more diffusely characterized regional or global communities. "Winners" and "losers" may also include future human communities as well as communities of other biotic species. As in any adaptive management framework, assessment of predictions, iterative follow-through and adaptation of policies or actions is essential, and commonly very difficult or impossible to achieve. Recognizing beforehand the limits of adaptive management is essential. More generally, knowledge of the behavioral and economic sciences and of ethics and sociology will be key to a successful implementation of this adaptive management framework. Knowledge of biogeophysical processes will also be essential, but by definition of the issues being addressed, will always be incomplete and highly uncertain. The human dimensions of the issues addressed and the participatory processes used carry their own complexities and uncertainties. Some ideas and principles are

  4. Heart Motion Prediction in Robotic-Assisted Beating Heart Surgery: A Nonlinear Fast Adaptive Approach

    Directory of Open Access Journals (Sweden)

    Fan Liang

    2013-01-01

    Full Text Available Off-pump Coronary Artery Bypass Graft (CABG surgery outperforms traditional on-pump surgery because the assisted robotic tools can alleviate the relative motion between the beating heart and robotic tools. Therefore, it is possible for the surgeon to operate on the beating heart and thus lessens post surgery complications for the patients. Due to the highly irregular and non-stationary nature of heart motion, it is critical that the beating heart motion is predicted in the model-based track control procedures. It is technically preferable to model heart motion in a nonlinear way because the characteristic analysis of 3D heart motion data through Bi-spectral analysis and Fourier methods demonstrates the involved nonlinearity of heart motion. We propose an adaptive nonlinear heart motion model based on the Volterra Series in this paper. We also design a fast lattice structure to achieve computational-efficiency for real-time online predictions. We argue that the quadratic term of the Volterra Series can improve the prediction accuracy by covering sharp change points and including the motion with sufficient detail. The experiment results indicate that the adaptive nonlinear heart motion prediction algorithm outperforms the autoregressive (AR and the time-varying Fourier-series models in terms of the root mean square of the prediction error and the prediction error in extreme cases.

  5. Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory

    Directory of Open Access Journals (Sweden)

    Haimin Yang

    2017-01-01

    Full Text Available Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam, for long short-term memory (LSTM to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM.

  6. Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory.

    Science.gov (United States)

    Yang, Haimin; Pan, Zhisong; Tao, Qing

    2017-01-01

    Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM.

  7. LPTA: Location Predictive and Time Adaptive Data Gathering Scheme with Mobile Sink for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Chuan Zhu

    2014-01-01

    Full Text Available This paper exploits sink mobility to prolong the lifetime of sensor networks while maintaining the data transmission delay relatively low. A location predictive and time adaptive data gathering scheme is proposed. In this paper, we introduce a sink location prediction principle based on loose time synchronization and deduce the time-location formulas of the mobile sink. According to local clocks and the time-location formulas of the mobile sink, nodes in the network are able to calculate the current location of the mobile sink accurately and route data packets timely toward the mobile sink by multihop relay. Considering that data packets generating from different areas may be different greatly, an adaptive dwelling time adjustment method is also proposed to balance energy consumption among nodes in the network. Simulation results show that our data gathering scheme enables data routing with less data transmission time delay and balance energy consumption among nodes.

  8. LPTA: location predictive and time adaptive data gathering scheme with mobile sink for wireless sensor networks.

    Science.gov (United States)

    Zhu, Chuan; Wang, Yao; Han, Guangjie; Rodrigues, Joel J P C; Lloret, Jaime

    2014-01-01

    This paper exploits sink mobility to prolong the lifetime of sensor networks while maintaining the data transmission delay relatively low. A location predictive and time adaptive data gathering scheme is proposed. In this paper, we introduce a sink location prediction principle based on loose time synchronization and deduce the time-location formulas of the mobile sink. According to local clocks and the time-location formulas of the mobile sink, nodes in the network are able to calculate the current location of the mobile sink accurately and route data packets timely toward the mobile sink by multihop relay. Considering that data packets generating from different areas may be different greatly, an adaptive dwelling time adjustment method is also proposed to balance energy consumption among nodes in the network. Simulation results show that our data gathering scheme enables data routing with less data transmission time delay and balance energy consumption among nodes.

  9. Adaptive Neuro-Fuzzy Inference System Models for Force Prediction of a Mechatronic Flexible Structure

    DEFF Research Database (Denmark)

    Achiche, S.; Shlechtingen, M.; Raison, M.

    2016-01-01

    This paper presents the results obtained from a research work investigating the performance of different Adaptive Neuro-Fuzzy Inference System (ANFIS) models developed to predict excitation forces on a dynamically loaded flexible structure. For this purpose, a flexible structure is equipped...... obtained from applying a random excitation force on the flexible structure. The performance of the developed models is evaluated by analyzing the prediction capabilities based on a normalized prediction error. The frequency domain is considered to analyze the similarity of the frequencies in the predicted...... of the sampling frequency and sensor location on the model performance is investigated. The results obtained in this paper show that ANFIS models can be used to set up reliable force predictors for dynamical loaded flexible structures, when a certain degree of inaccuracy is accepted. Furthermore, the comparison...

  10. An adaptive-order particle filter for remaining useful life prediction of aviation piston pumps

    Directory of Open Access Journals (Sweden)

    Tongyang LI

    2018-05-01

    Full Text Available An accurate estimation of the remaining useful life (RUL not only contributes to an effective application of an aviation piston pump, but also meets the necessity of condition based maintenance (CBM. For the current RUL evaluation methods, a model-based method is inappropriate for the degradation process of an aviation piston pump due to difficulties of modeling, while a data-based method rarely presents high-accuracy prediction in a long period of time. In this work, an adaptive-order particle filter (AOPF prognostic process is proposed aiming at improving long-term prediction accuracy of RUL by combining both kinds of methods. A dynamic model is initialized by a data-driven or empirical method. When a new observation comes, the prior state distribution is approximated by a current model. The order of the current model is updated adaptively by fusing the information of the observation. Monte Carlo simulation is employed for estimating the posterior probability density function of future states of the pump’s degradation. With updating the order number adaptively, the method presents a higher precision in contrast with those of traditional methods. In a case study, the proposed AOPF method is adopted to forecast the degradation status of an aviation piston pump with experimental return oil flow data, and the analytical results show the effectiveness of the proposed AOPF method. Keywords: Adaptive prognosis, Condition based maintenance (CBM, Particle filter (PF, Piston pump, Remaining useful life (RUL

  11. Genetic risk prediction using a spatial autoregressive model with adaptive lasso.

    Science.gov (United States)

    Wen, Yalu; Shen, Xiaoxi; Lu, Qing

    2018-05-31

    With rapidly evolving high-throughput technologies, studies are being initiated to accelerate the process toward precision medicine. The collection of the vast amounts of sequencing data provides us with great opportunities to systematically study the role of a deep catalog of sequencing variants in risk prediction. Nevertheless, the massive amount of noise signals and low frequencies of rare variants in sequencing data pose great analytical challenges on risk prediction modeling. Motivated by the development in spatial statistics, we propose a spatial autoregressive model with adaptive lasso (SARAL) for risk prediction modeling using high-dimensional sequencing data. The SARAL is a set-based approach, and thus, it reduces the data dimension and accumulates genetic effects within a single-nucleotide variant (SNV) set. Moreover, it allows different SNV sets having various magnitudes and directions of effect sizes, which reflects the nature of complex diseases. With the adaptive lasso implemented, SARAL can shrink the effects of noise SNV sets to be zero and, thus, further improve prediction accuracy. Through simulation studies, we demonstrate that, overall, SARAL is comparable to, if not better than, the genomic best linear unbiased prediction method. The method is further illustrated by an application to the sequencing data from the Alzheimer's Disease Neuroimaging Initiative. Copyright © 2018 John Wiley & Sons, Ltd.

  12. French validation and adaptation of the Grobman nomogram for prediction of vaginal birth after cesarean delivery.

    Science.gov (United States)

    Haumonte, J-B; Raylet, M; Christophe, M; Mauviel, F; Bertrand, A; Desbriere, R; d'Ercole, C

    2018-03-01

    To validate Grobman nomogram for predicting vaginal birth after cesarean delivery (VBAC) in a French population and adapt it. Multicenter retrospective study of maternal and obstetric factors associated with VBAC between May 2012 and May 2013 in 6 maternity units. External validation and adaptation of the prenatal and intrapartum Grobman nomograms for vaginal birth prediction after cesarean delivery in a French cohort. The study included 523 women with previous cesarean deliveries; 70% underwent a trial of labor for a subsequent delivery (n=367) with a success rate of 65% (n=240). In the univariate analysis, 5 factors were associated with successful VBAC: previous vaginal delivery before the cesarean (P6 (P=0.03). A potentially recurrent indication (defined as arrest of dilation or descent as the indication for the previous cesarean) (P=0.039), a hypertensive disorder during pregnancy (P=0.05), and labor induction (P=0.017) were each associated with failed VBAC. External validation of the prenatal and intrapartum Grobman nomograms showed an area under the ROC curve of 69% (95% CI: 0.638, 0.736) and 65% (95% CI: 0.599, 0.700) respectively. Adaptation of the nomogram to the French cohort resulted in the inclusion of the following factors: maternal age, body mass index at last prenatal visit, hypertensive disorder, gestational age at delivery, recurring indication, cervical dilatation, and induction of labor. Its area under the curve to predict successful VBAC was 78% (95% CI: 0.738, 0.825). The nomogram to predict VBAC developed by Grobman et al. is validated in the French population. Adaptation to the French population, by excluding ethnicity, appeared to improve its performance. Impact of the nomogram use on the caesarean section rate has to be validated in a randomized control trial. Copyright © 2017. Published by Elsevier Masson SAS.

  13. Model-on-Demand Predictive Control for Nonlinear Hybrid Systems With Application to Adaptive Behavioral Interventions

    Science.gov (United States)

    Nandola, Naresh N.; Rivera, Daniel E.

    2011-01-01

    This paper presents a data-centric modeling and predictive control approach for nonlinear hybrid systems. System identification of hybrid systems represents a challenging problem because model parameters depend on the mode or operating point of the system. The proposed algorithm applies Model-on-Demand (MoD) estimation to generate a local linear approximation of the nonlinear hybrid system at each time step, using a small subset of data selected by an adaptive bandwidth selector. The appeal of the MoD approach lies in the fact that model parameters are estimated based on a current operating point; hence estimation of locations or modes governed by autonomous discrete events is achieved automatically. The local MoD model is then converted into a mixed logical dynamical (MLD) system representation which can be used directly in a model predictive control (MPC) law for hybrid systems using multiple-degree-of-freedom tuning. The effectiveness of the proposed MoD predictive control algorithm for nonlinear hybrid systems is demonstrated on a hypothetical adaptive behavioral intervention problem inspired by Fast Track, a real-life preventive intervention for improving parental function and reducing conduct disorder in at-risk children. Simulation results demonstrate that the proposed algorithm can be useful for adaptive intervention problems exhibiting both nonlinear and hybrid character. PMID:21874087

  14. Predicting adaptive phenotypes from multilocus genotypes in Sitka spruce (Picea sitchensis) using random forest.

    Science.gov (United States)

    Holliday, Jason A; Wang, Tongli; Aitken, Sally

    2012-09-01

    Climate is the primary driver of the distribution of tree species worldwide, and the potential for adaptive evolution will be an important factor determining the response of forests to anthropogenic climate change. Although association mapping has the potential to improve our understanding of the genomic underpinnings of climatically relevant traits, the utility of adaptive polymorphisms uncovered by such studies would be greatly enhanced by the development of integrated models that account for the phenotypic effects of multiple single-nucleotide polymorphisms (SNPs) and their interactions simultaneously. We previously reported the results of association mapping in the widespread conifer Sitka spruce (Picea sitchensis). In the current study we used the recursive partitioning algorithm 'Random Forest' to identify optimized combinations of SNPs to predict adaptive phenotypes. After adjusting for population structure, we were able to explain 37% and 30% of the phenotypic variation, respectively, in two locally adaptive traits--autumn budset timing and cold hardiness. For each trait, the leading five SNPs captured much of the phenotypic variation. To determine the role of epistasis in shaping these phenotypes, we also used a novel approach to quantify the strength and direction of pairwise interactions between SNPs and found such interactions to be common. Our results demonstrate the power of Random Forest to identify subsets of markers that are most important to climatic adaptation, and suggest that interactions among these loci may be widespread.

  15. Spike-threshold adaptation predicted by membrane potential dynamics in vivo.

    Directory of Open Access Journals (Sweden)

    Bertrand Fontaine

    2014-04-01

    Full Text Available Neurons encode information in sequences of spikes, which are triggered when their membrane potential crosses a threshold. In vivo, the spiking threshold displays large variability suggesting that threshold dynamics have a profound influence on how the combined input of a neuron is encoded in the spiking. Threshold variability could be explained by adaptation to the membrane potential. However, it could also be the case that most threshold variability reflects noise and processes other than threshold adaptation. Here, we investigated threshold variation in auditory neurons responses recorded in vivo in barn owls. We found that spike threshold is quantitatively predicted by a model in which the threshold adapts, tracking the membrane potential at a short timescale. As a result, in these neurons, slow voltage fluctuations do not contribute to spiking because they are filtered by threshold adaptation. More importantly, these neurons can only respond to input spikes arriving together on a millisecond timescale. These results demonstrate that fast adaptation to the membrane potential captures spike threshold variability in vivo.

  16. Cognitive and social processes predicting partner psychological adaptation to early stage breast cancer.

    Science.gov (United States)

    Manne, Sharon; Ostroff, Jamie; Fox, Kevin; Grana, Generosa; Winkel, Gary

    2009-02-01

    The diagnosis and subsequent treatment for early stage breast cancer is stressful for partners. Little is known about the role of cognitive and social processes predicting the longitudinal course of partners' psychosocial adaptation. This study evaluated the role of cognitive and social processing in partner psychological adaptation to early stage breast cancer, evaluating both main and moderator effect models. Moderating effects for meaning making, acceptance, and positive reappraisal on the predictive association of searching for meaning, emotional processing, and emotional expression on partner psychological distress were examined. Partners of women diagnosed with early stage breast cancer were evaluated shortly after the ill partner's diagnosis (N=253), 9 (N=167), and 18 months (N=149) later. Partners completed measures of emotional expression, emotional processing, acceptance, meaning making, and general and cancer-specific distress at all time points. Lower satisfaction with partner support predicted greater global distress, and greater use of positive reappraisal was associated with greater distress. The predicted moderator effects for found meaning on the associations between the search for meaning and cancer-specific distress were found and similar moderating effects for positive reappraisal on the associations between emotional expression and global distress and for acceptance on the association between emotional processing and cancer-specific distress were found. Results indicate several cognitive-social processes directly predict partner distress. However, moderator effect models in which the effects of partners' processing depends upon whether these efforts result in changes in perceptions of the cancer experience may add to the understanding of partners' adaptation to cancer.

  17. Data-adaptive Harmonic Decomposition and Real-time Prediction of Arctic Sea Ice Extent

    Science.gov (United States)

    Kondrashov, Dmitri; Chekroun, Mickael; Ghil, Michael

    2017-04-01

    Decline in the Arctic sea ice extent (SIE) has profound socio-economic implications and is a focus of active scientific research. Of particular interest is prediction of SIE on subseasonal time scales, i.e. from early summer into fall, when sea ice coverage in Arctic reaches its minimum. However, subseasonal forecasting of SIE is very challenging due to the high variability of ocean and atmosphere over Arctic in summer, as well as shortness of observational data and inadequacies of the physics-based models to simulate sea-ice dynamics. The Sea Ice Outlook (SIO) by Sea Ice Prediction Network (SIPN, http://www.arcus.org/sipn) is a collaborative effort to facilitate and improve subseasonal prediction of September SIE by physics-based and data-driven statistical models. Data-adaptive Harmonic Decomposition (DAH) and Multilayer Stuart-Landau Models (MSLM) techniques [Chekroun and Kondrashov, 2017], have been successfully applied to the nonlinear stochastic modeling, as well as retrospective and real-time forecasting of Multisensor Analyzed Sea Ice Extent (MASIE) dataset in key four Arctic regions. In particular, DAH-MSLM predictions outperformed most statistical models and physics-based models in real-time 2016 SIO submissions. The key success factors are associated with DAH ability to disentangle complex regional dynamics of MASIE by data-adaptive harmonic spatio-temporal patterns that reduce the data-driven modeling effort to elemental MSLMs stacked per frequency with fixed and small number of model coefficients to estimate.

  18. Adaptive neuro-fuzzy and expert systems for power quality analysis and prediction of abnormal operation

    Science.gov (United States)

    Ibrahim, Wael Refaat Anis

    The present research involves the development of several fuzzy expert systems for power quality analysis and diagnosis. Intelligent systems for the prediction of abnormal system operation were also developed. The performance of all intelligent modules developed was either enhanced or completely produced through adaptive fuzzy learning techniques. Neuro-fuzzy learning is the main adaptive technique utilized. The work presents a novel approach to the interpretation of power quality from the perspective of the continuous operation of a single system. The research includes an extensive literature review pertaining to the applications of intelligent systems to power quality analysis. Basic definitions and signature events related to power quality are introduced. In addition, detailed discussions of various artificial intelligence paradigms as well as wavelet theory are included. A fuzzy-based intelligent system capable of identifying normal from abnormal operation for a given system was developed. Adaptive neuro-fuzzy learning was applied to enhance its performance. A group of fuzzy expert systems that could perform full operational diagnosis were also developed successfully. The developed systems were applied to the operational diagnosis of 3-phase induction motors and rectifier bridges. A novel approach for learning power quality waveforms and trends was developed. The technique, which is adaptive neuro fuzzy-based, learned, compressed, and stored the waveform data. The new technique was successfully tested using a wide variety of power quality signature waveforms, and using real site data. The trend-learning technique was incorporated into a fuzzy expert system that was designed to predict abnormal operation of a monitored system. The intelligent system learns and stores, in compressed format, trends leading to abnormal operation. The system then compares incoming data to the retained trends continuously. If the incoming data matches any of the learned trends, an

  19. Adaptation

    International Development Research Centre (IDRC) Digital Library (Canada)

    building skills, knowledge or networks on adaptation, ... the African partners leading the AfricaAdapt network, together with the UK-based Institute of Development Studies; and ... UNCCD Secretariat, Regional Coordination Unit for Africa, Tunis, Tunisia .... 26 Rural–urban Cooperation on Water Management in the Context of.

  20. The Predictive Utility of Narcissism among Children and Adolescents: Evidence for a Distinction between Adaptive and Maladaptive Narcissism

    Science.gov (United States)

    Barry, Christopher T.; Frick, Paul J.; Adler, Kristy K.; Grafeman, Sarah J.

    2007-01-01

    We examined the predictive utility of narcissism among a community sample of children and adolescents (N=98) longitudinally. Analyses focused on the differential utility between maladaptive and adaptive narcissism for predicting later delinquency. Maladaptive narcissism significantly predicted self-reported delinquency at one-, two-, and…

  1. Adaptability and Prediction of Anticipatory Muscular Activity Parameters to Different Movements in the Sitting Position.

    Science.gov (United States)

    Chikh, Soufien; Watelain, Eric; Faupin, Arnaud; Pinti, Antonio; Jarraya, Mohamed; Garnier, Cyril

    2016-08-01

    Voluntary movement often causes postural perturbation that requires an anticipatory postural adjustment to minimize perturbation and increase the efficiency and coordination during execution. This systematic review focuses specifically on the relationship between the parameters of anticipatory muscular activities and movement finality in sitting position among adults, to study the adaptability and predictability of anticipatory muscular activities parameters to different movements and conditions in sitting position in adults. A systematic literature search was performed using PubMed, Science Direct, Web of Science, Springer-Link, Engineering Village, and EbscoHost. Inclusion and exclusion criteria were applied to retain the most rigorous and specific studies, yielding 76 articles, Seventeen articles were excluded at first reading, and after the application of inclusion and exclusion criteria, 23 were retained. In a sitting position, central nervous system activity precedes movement by diverse anticipatory muscular activities and shows the ability to adapt anticipatory muscular activity parameters to the movement direction, postural stability, or charge weight. In addition, these parameters could be adapted to the speed of execution, as found for the standing position. Parameters of anticipatory muscular activities (duration, order, and amplitude of muscle contractions constituting the anticipatory muscular activity) could be used as a predictive indicator of forthcoming movement. In addition, this systematic review may improve methodology in empirical studies and assistive technology for people with disabilities. © The Author(s) 2016.

  2. Improved Trust Prediction in Business Environments by Adaptive Neuro Fuzzy Inference Systems

    Directory of Open Access Journals (Sweden)

    Ali Azadeh

    2015-06-01

    Full Text Available Trust prediction turns out to be an important challenge when cooperation among intelligent agents with an impression of trust in their mind, is investigated. In other words, predicting trust values for future time slots help partners to identify the probability of continuing a relationship. Another important case to be considered is the context of trust, i.e. the services and business commitments for which a relationship is defined. Hence, intelligent agents should focus on improving trust to provide a stable and confident context. Modelling of trust between collaborating parties seems to be an important component of the business intelligence strategy. In this regard, a set of metrics have been considered by which the value of confidence level for predicted trust values has been estimated. These metrics are maturity, distance and density (MD2. Prediction of trust for future mutual relationships among agents is a problem that is addressed in this study. We introduce a simulation-based model which utilizes linguistic variables to create various scenarios. Then, future trust values among agents are predicted by the concept of adaptive neuro-fuzzy inference system (ANFIS. Mean absolute percentage errors (MAPEs resulted from ANFIS are compared with confidence levels which are determined by applying MD2. Results determine the efficiency of MD2 for forecasting trust values. This is the first study that utilizes the concept of MD2 for improvement of business trust prediction.

  3. Data-adaptive harmonic analysis and prediction of sea level change in North Atlantic region

    Science.gov (United States)

    Kondrashov, D. A.; Chekroun, M.

    2017-12-01

    This study aims to characterize North Atlantic sea level variability across the temporal and spatial scales. We apply recently developed data-adaptive Harmonic Decomposition (DAH) and Multilayer Stuart-Landau Models (MSLM) stochastic modeling techniques [Chekroun and Kondrashov, 2017] to monthly 1993-2017 dataset of Combined TOPEX/Poseidon, Jason-1 and Jason-2/OSTM altimetry fields over North Atlantic region. The key numerical feature of the DAH relies on the eigendecomposition of a matrix constructed from time-lagged spatial cross-correlations. In particular, eigenmodes form an orthogonal set of oscillating data-adaptive harmonic modes (DAHMs) that come in pairs and in exact phase quadrature for a given temporal frequency. Furthermore, the pairs of data-adaptive harmonic coefficients (DAHCs), obtained by projecting the dataset onto associated DAHMs, can be very efficiently modeled by a universal parametric family of simple nonlinear stochastic models - coupled Stuart-Landau oscillators stacked per frequency, and synchronized across different frequencies by the stochastic forcing. Despite the short record of altimetry dataset, developed DAH-MSLM model provides for skillful prediction of key dynamical and statistical features of sea level variability. References M. D. Chekroun and D. Kondrashov, Data-adaptive harmonic spectra and multilayer Stuart-Landau models. HAL preprint, 2017, https://hal.archives-ouvertes.fr/hal-01537797

  4. Assessment of Model Predictive and Adaptive Glucose Control Strategies for People with Type 1 Diabetes

    DEFF Research Database (Denmark)

    Boiroux, Dimitri; Duun-Henriksen, Anne Katrine; Schmidt, Signe

    2014-01-01

    This paper addresses overnight blood glucose stabilization in people with type 1 diabetes using a Model Predictive Controller (MPC). We use a control strategy based on an adaptive ARMAX model in which we use a Recursive Extended Least Squares (RELS) method to estimate parameters of the stochastic...... and reduce the risk of hypoglycemia. We test our control strategies on a virtual clinic of 100 randomly generated patients with a representative inter-subject variability. This virtual clinic is based on the Hovorka model. We consider the case where only half of the meal bolus is administered at mealtime......, and the case where the insulin sensitivity varies during the night. The simulation results demonstrate that the adaptive control strategy can reduce the risks of hypoglycemia and hyperglycemia during the night....

  5. Tolerance and potential for adaptation of a Baltic Sea rockweed under predicted climate change conditions.

    Science.gov (United States)

    Rugiu, Luca; Manninen, Iita; Rothäusler, Eva; Jormalainen, Veijo

    2018-03-01

    Climate change is threating species' persistence worldwide. To predict species responses to climate change we need information not just on their environmental tolerance but also on its adaptive potential. We tested how the foundation species of rocky littoral habitats, Fucus vesiculosus, responds to combined hyposalinity and warming projected to the Baltic Sea by 2070-2099. We quantified responses of replicated populations originating from the entrance, central, and marginal Baltic regions. Using replicated individuals, we tested for the presence of within-population tolerance variation. Future conditions hampered growth and survival of the central and marginal populations whereas the entrance populations fared well. Further, both the among- and within-population variation in responses to climate change indicated existence of genetic variation in tolerance. Such standing genetic variation provides the raw material necessary for adaptation to a changing environment, which may eventually ensure the persistence of the species in the inner Baltic Sea. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Ground-based adaptive optics coronagraphic performance under closed-loop predictive control

    Science.gov (United States)

    Males, Jared R.; Guyon, Olivier

    2018-01-01

    The discovery of the exoplanet Proxima b highlights the potential for the coming generation of giant segmented mirror telescopes (GSMTs) to characterize terrestrial-potentially habitable-planets orbiting nearby stars with direct imaging. This will require continued development and implementation of optimized adaptive optics systems feeding coronagraphs on the GSMTs. Such development should proceed with an understanding of the fundamental limits imposed by atmospheric turbulence. Here, we seek to address this question with a semianalytic framework for calculating the postcoronagraph contrast in a closed-loop adaptive optics system. We do this starting with the temporal power spectra of the Fourier basis calculated assuming frozen flow turbulence, and then apply closed-loop transfer functions. We include the benefits of a simple predictive controller, which we show could provide over a factor of 1400 gain in raw point spread function contrast at 1 λ/D on bright stars, and more than a factor of 30 gain on an I=7.5 mag star such as Proxima. More sophisticated predictive control can be expected to improve this even further. Assuming a photon-noise limited observing technique such as high-dispersion coronagraphy, these gains in raw contrast will decrease integration times by the same large factors. Predictive control of atmospheric turbulence should therefore be seen as one of the key technologies that will enable ground-based telescopes to characterize terrestrial planets.

  7. Adaptive on-line prediction of the available power of lithium-ion batteries

    Science.gov (United States)

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

    2013-11-01

    In this paper a new approach for prediction of the available power of a lithium-ion battery pack is presented. It is based on a nonlinear battery model that includes current dependency of the battery resistance. It results in an accurate power prediction not only at room temperature, but also at lower temperatures at which the current dependency is substantial. The used model parameters are fully adaptable on-line to the given state of the battery (state of charge, state of health, temperature). This on-line adaption in combination with an explicit consideration of differences between characteristics of individual cells in a battery pack ensures an accurate power prediction under all possible conditions. The proposed trade-off between the number of used cell parameters and the total accuracy as well as the optimized algorithm results in a real-time capability of the method, which is demonstrated on a low-cost 16 bit microcontroller. The verification tests performed on a software-in-the-loop test bench system with four 40 Ah lithium-ion cells show promising results.

  8. Incremental Validity of Personality Measures in Predicting Underwater Performance and Adaptation.

    Science.gov (United States)

    Colodro, Joaquín; Garcés-de-Los-Fayos, Enrique J; López-García, Juan J; Colodro-Conde, Lucía

    2015-03-17

    Intelligence and personality traits are currently considered effective predictors of human behavior and job performance. However, there are few studies about their relevance in the underwater environment. Data from a sample of military personnel performing scuba diving courses were analyzed with regression techniques, testing the contribution of individual differences and ascertaining the incremental validity of the personality in an environment with extreme psychophysical demands. The results confirmed the incremental validity of personality traits (ΔR 2 = .20, f 2 = .25) over the predictive contribution of general mental ability (ΔR 2 = .07, f 2 = .08) in divers' performance. Moreover, personality (R(L)2 = .34) also showed a higher validity to predict underwater adaptation than general mental ability ( R(L)2 = .09). The ROC curve indicated 86% of the maximum possible discrimination power for the prediction of underwater adaptation, AUC = .86, p personality traits as predictors of an effective response to the changing circumstances of military scuba diving. They also may improve the understanding of the behavioral effects and psychophysiological complications of diving and can also provide guidance for psychological intervention and prevention of risk in this extreme environment.

  9. A parallel adaptive mesh refinement algorithm for predicting turbulent non-premixed combusting flows

    International Nuclear Information System (INIS)

    Gao, X.; Groth, C.P.T.

    2005-01-01

    A parallel adaptive mesh refinement (AMR) algorithm is proposed for predicting turbulent non-premixed combusting flows characteristic of gas turbine engine combustors. The Favre-averaged Navier-Stokes equations governing mixture and species transport for a reactive mixture of thermally perfect gases in two dimensions, the two transport equations of the κ-ψ turbulence model, and the time-averaged species transport equations, are all solved using a fully coupled finite-volume formulation. A flexible block-based hierarchical data structure is used to maintain the connectivity of the solution blocks in the multi-block mesh and facilitate automatic solution-directed mesh adaptation according to physics-based refinement criteria. This AMR approach allows for anisotropic mesh refinement and the block-based data structure readily permits efficient and scalable implementations of the algorithm on multi-processor architectures. Numerical results for turbulent non-premixed diffusion flames, including cold- and hot-flow predictions for a bluff body burner, are described and compared to available experimental data. The numerical results demonstrate the validity and potential of the parallel AMR approach for predicting complex non-premixed turbulent combusting flows. (author)

  10. Prediction of Mechanical Properties of LDPE-TPS Nanocomposites Using Adaptive Neuro-Fuzzy Inference System

    Directory of Open Access Journals (Sweden)

    Maryam Sabetzadeh

    2012-12-01

    Full Text Available The changes in the behaviour of mechanical properties of low densitypolyethylene-thermoplastic corn starch (LDPE-TPCS nanocompositeswere studied by an adaptive neuro-fuzzy interference system. LDPE-TPCScomposites containing different quantities of nanoclay (Cloisite®15A, 0.5-3wt. % were prepared by extrusion process. In practice, it is difficult to carry out several experiments to identify the relationship between the extrusion process parameters and mechanical properties of the nanocomposites. In this paper, an adaptive neuro-fuzzy inference system (ANFIS was used for non-linear mapping between the processingparameters and the mechanical properties of LDPE-TPCS nanocomposites. ANFIS model due to possessing inference ability of fuzzy systems and also the learning feature of neural networks, could be used as a multiple inputs-multiple outputs to predict mechanical properties (such as ultimate tensile strength, elongation-at-break, Young’s modulus and relative impact strength of the nanocomposites. The proposed ANFIS model utilizes temperature, torque and Cloisite®15A contents as input parameters to predict the desired mechanical properties. The results obtained in this work indicatedthat ANFIS is an effective and intelligent method for prediction of the mechanical properties of the LDPE-TPCS nanocomposites with a good accuracy. The statistical quality of the ANFIS model was significant due to its acceptable mean square error criterion and good correlation coefficient (values > 0.8 between the experimental and simulated outputs.

  11. Esophageal cancer prediction based on qualitative features using adaptive fuzzy reasoning method

    Directory of Open Access Journals (Sweden)

    Raed I. Hamed

    2015-04-01

    Full Text Available Esophageal cancer is one of the most common cancers world-wide and also the most common cause of cancer death. In this paper, we present an adaptive fuzzy reasoning algorithm for rule-based systems using fuzzy Petri nets (FPNs, where the fuzzy production rules are represented by FPN. We developed an adaptive fuzzy Petri net (AFPN reasoning algorithm as a prognostic system to predict the outcome for esophageal cancer based on the serum concentrations of C-reactive protein and albumin as a set of input variables. The system can perform fuzzy reasoning automatically to evaluate the degree of truth of the proposition representing the risk degree value with a weight value to be optimally tuned based on the observed data. In addition, the implementation process for esophageal cancer prediction is fuzzily deducted by the AFPN algorithm. Performance of the composite model is evaluated through a set of experiments. Simulations and experimental results demonstrate the effectiveness and performance of the proposed algorithms. A comparison of the predictive performance of AFPN models with other methods and the analysis of the curve showed the same results with an intuitive behavior of AFPN models.

  12. The cerebellum does more than sensory prediction error-based learning in sensorimotor adaptation tasks.

    Science.gov (United States)

    Butcher, Peter A; Ivry, Richard B; Kuo, Sheng-Han; Rydz, David; Krakauer, John W; Taylor, Jordan A

    2017-09-01

    Individuals with damage to the cerebellum perform poorly in sensorimotor adaptation paradigms. This deficit has been attributed to impairment in sensory prediction error-based updating of an internal forward model, a form of implicit learning. These individuals can, however, successfully counter a perturbation when instructed with an explicit aiming strategy. This successful use of an instructed aiming strategy presents a paradox: In adaptation tasks, why do individuals with cerebellar damage not come up with an aiming solution on their own to compensate for their implicit learning deficit? To explore this question, we employed a variant of a visuomotor rotation task in which, before executing a movement on each trial, the participants verbally reported their intended aiming location. Compared with healthy control participants, participants with spinocerebellar ataxia displayed impairments in both implicit learning and aiming. This was observed when the visuomotor rotation was introduced abruptly ( experiment 1 ) or gradually ( experiment 2 ). This dual deficit does not appear to be related to the increased movement variance associated with ataxia: Healthy undergraduates showed little change in implicit learning or aiming when their movement feedback was artificially manipulated to produce similar levels of variability ( experiment 3 ). Taken together the results indicate that a consequence of cerebellar dysfunction is not only impaired sensory prediction error-based learning but also a difficulty in developing and/or maintaining an aiming solution in response to a visuomotor perturbation. We suggest that this dual deficit can be explained by the cerebellum forming part of a network that learns and maintains action-outcome associations across trials. NEW & NOTEWORTHY Individuals with cerebellar pathology are impaired in sensorimotor adaptation. This deficit has been attributed to an impairment in error-based learning, specifically, from a deficit in using sensory

  13. Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation

    Directory of Open Access Journals (Sweden)

    Gergely Takács

    2014-01-01

    Full Text Available This paper presents an adaptive-predictive vibration control system using extended Kalman filtering for the joint estimation of system states and model parameters. A fixed-free cantilever beam equipped with piezoceramic actuators serves as a test platform to validate the proposed control strategy. Deflection readings taken at the end of the beam have been used to reconstruct the position and velocity information for a second-order state-space model. In addition to the states, the dynamic system has been augmented by the unknown model parameters: stiffness, damping constant, and a voltage/force conversion constant, characterizing the actuating effect of the piezoceramic transducers. The states and parameters of this augmented system have been estimated in real time, using the hybrid extended Kalman filter. The estimated model parameters have been applied to define the continuous state-space model of the vibrating system, which in turn is discretized for the predictive controller. The model predictive control algorithm generates state predictions and dual-mode quadratic cost prediction matrices based on the updated discrete state-space models. The resulting cost function is then minimized using quadratic programming to find the sequence of optimal but constrained control inputs. The proposed active vibration control system is implemented and evaluated experimentally to investigate the viability of the control method.

  14. The Role of Senior University Students' Career Adaptability in Predicting Their Subjective Well-Being

    Science.gov (United States)

    Kirdök, Oguzhan; Bölükbasi, Ayten

    2018-01-01

    The aim of this study is to examine whether career adaptability and career adaptability subscales of senior undergraduates could predict subjective well-being. The research was a descriptive correlational study which was conducted on 310 senior students (173 women, 137 men) in a state-funded university on the Mediterranean coast of Turkey and…

  15. Adaptive algorithm for predicting increases in central loads of electrical energy systems

    Energy Technology Data Exchange (ETDEWEB)

    Arbachyauskene, N A; Pushinaytis, K V

    1982-01-01

    An adaptive algorithm for predicting increases in central loads of the electrical energy system is suggested for the task of evaluating the condition. The algorithm is based on the Kalman filter. In order to calculate the coefficient of intensification, the a priori assigned noise characteristics with low accuracy are used only in the beginning of the calculation. Further, the coefficient of intensification is calculated from the innovation sequence. This approach makes it possible to correct errors in the assignment of the statistical noise characteristics and to follow their changes. The algorithm is experimentally verified.

  16. Predictive densities for day-ahead electricity prices using time-adaptive quantile regression

    DEFF Research Database (Denmark)

    Jónsson, Tryggvi; Pinson, Pierre; Madsen, Henrik

    2014-01-01

    A large part of the decision-making problems actors of the power system are facing on a daily basis requires scenarios for day-ahead electricity market prices. These scenarios are most likely to be generated based on marginal predictive densities for such prices, then enhanced with a temporal...... dependence structure. A semi-parametric methodology for generating such densities is presented: it includes: (i) a time-adaptive quantile regression model for the 5%–95% quantiles; and (ii) a description of the distribution tails with exponential distributions. The forecasting skill of the proposed model...

  17. Prediction of ultrasonic pulse velocity for enhanced peat bricks using adaptive neuro-fuzzy methodology.

    Science.gov (United States)

    Motamedi, Shervin; Roy, Chandrabhushan; Shamshirband, Shahaboddin; Hashim, Roslan; Petković, Dalibor; Song, Ki-Il

    2015-08-01

    Ultrasonic pulse velocity is affected by defects in material structure. This study applied soft computing techniques to predict the ultrasonic pulse velocity for various peats and cement content mixtures for several curing periods. First, this investigation constructed a process to simulate the ultrasonic pulse velocity with adaptive neuro-fuzzy inference system. Then, an ANFIS network with neurons was developed. The input and output layers consisted of four and one neurons, respectively. The four inputs were cement, peat, sand content (%) and curing period (days). The simulation results showed efficient performance of the proposed system. The ANFIS and experimental results were compared through the coefficient of determination and root-mean-square error. In conclusion, use of ANFIS network enhances prediction and generation of strength. The simulation results confirmed the effectiveness of the suggested strategies. Copyright © 2015 Elsevier B.V. All rights reserved.

  18. Tracking Maneuvering Group Target with Extension Predicted and Best Model Augmentation Method Adapted

    Directory of Open Access Journals (Sweden)

    Linhai Gan

    2017-01-01

    Full Text Available The random matrix (RM method is widely applied for group target tracking. The assumption that the group extension keeps invariant in conventional RM method is not yet valid, as the orientation of the group varies rapidly while it is maneuvering; thus, a new approach with group extension predicted is derived here. To match the group maneuvering, a best model augmentation (BMA method is introduced. The existing BMA method uses a fixed basic model set, which may lead to a poor performance when it could not ensure basic coverage of true motion modes. Here, a maneuvering group target tracking algorithm is proposed, where the group extension prediction and the BMA adaption are exploited. The performance of the proposed algorithm will be illustrated by simulation.

  19. Adapt

    Science.gov (United States)

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  20. Branched Adaptive Testing with a Rasch-Model-Calibrated Test: Analysing Item Presentation's Sequence Effects Using the Rasch-Model-Based LLTM

    Science.gov (United States)

    Kubinger, Klaus D.; Reif, Manuel; Yanagida, Takuya

    2011-01-01

    Item position effects provoke serious problems within adaptive testing. This is because different testees are necessarily presented with the same item at different presentation positions, as a consequence of which comparing their ability parameter estimations in the case of such effects would not at all be fair. In this article, a specific…

  1. Predictive analytics of environmental adaptability in multi-omic network models.

    Science.gov (United States)

    Angione, Claudio; Lió, Pietro

    2015-10-20

    Bacterial phenotypic traits and lifestyles in response to diverse environmental conditions depend on changes in the internal molecular environment. However, predicting bacterial adaptability is still difficult outside of laboratory controlled conditions. Many molecular levels can contribute to the adaptation to a changing environment: pathway structure, codon usage, metabolism. To measure adaptability to changing environmental conditions and over time, we develop a multi-omic model of Escherichia coli that accounts for metabolism, gene expression and codon usage at both transcription and translation levels. After the integration of multiple omics into the model, we propose a multiobjective optimization algorithm to find the allowable and optimal metabolic phenotypes through concurrent maximization or minimization of multiple metabolic markers. In the condition space, we propose Pareto hypervolume and spectral analysis as estimators of short term multi-omic (transcriptomic and metabolic) evolution, thus enabling comparative analysis of metabolic conditions. We therefore compare, evaluate and cluster different experimental conditions, models and bacterial strains according to their metabolic response in a multidimensional objective space, rather than in the original space of microarray data. We finally validate our methods on a phenomics dataset of growth conditions. Our framework, named METRADE, is freely available as a MATLAB toolbox.

  2. Adaptively Constrained Stochastic Model Predictive Control for the Optimal Dispatch of Microgrid

    Directory of Open Access Journals (Sweden)

    Xiaogang Guo

    2018-01-01

    Full Text Available In this paper, an adaptively constrained stochastic model predictive control (MPC is proposed to achieve less-conservative coordination between energy storage units and uncertain renewable energy sources (RESs in a microgrid (MG. Besides the economic objective of MG operation, the limits of state-of-charge (SOC and discharging/charging power of the energy storage unit are formulated as chance constraints when accommodating uncertainties of RESs, considering mild violations of these constraints are allowed during long-term operation, and a closed-loop online update strategy is performed to adaptively tighten or relax constraints according to the actual deviation probability of violation level from the desired one as well as the current change rate of deviation probability. Numerical studies show that the proposed adaptively constrained stochastic MPC for MG optimal operation is much less conservative compared with the scenario optimization based robust MPC, and also presents a better convergence performance to the desired constraint violation level than other online update strategies.

  3. Predicting organismal vulnerability to climate warming: roles of behaviour, physiology and adaptation

    Science.gov (United States)

    Huey, Raymond B.; Kearney, Michael R.; Krockenberger, Andrew; Holtum, Joseph A. M.; Jess, Mellissa; Williams, Stephen E.

    2012-01-01

    A recently developed integrative framework proposes that the vulnerability of a species to environmental change depends on the species' exposure and sensitivity to environmental change, its resilience to perturbations and its potential to adapt to change. These vulnerability criteria require behavioural, physiological and genetic data. With this information in hand, biologists can predict organisms most at risk from environmental change. Biologists and managers can then target organisms and habitats most at risk. Unfortunately, the required data (e.g. optimal physiological temperatures) are rarely available. Here, we evaluate the reliability of potential proxies (e.g. critical temperatures) that are often available for some groups. Several proxies for ectotherms are promising, but analogous ones for endotherms are lacking. We also develop a simple graphical model of how behavioural thermoregulation, acclimation and adaptation may interact to influence vulnerability over time. After considering this model together with the proxies available for physiological sensitivity to climate change, we conclude that ectotherms sharing vulnerability traits seem concentrated in lowland tropical forests. Their vulnerability may be exacerbated by negative biotic interactions. Whether tropical forest (or other) species can adapt to warming environments is unclear, as genetic and selective data are scant. Nevertheless, the prospects for tropical forest ectotherms appear grim. PMID:22566674

  4. Using adaptive model predictive control to customize maintenance therapy chemotherapeutic dosing for childhood acute lymphoblastic leukemia.

    Science.gov (United States)

    Noble, Sarah L; Sherer, Eric; Hannemann, Robert E; Ramkrishna, Doraiswami; Vik, Terry; Rundell, Ann E

    2010-06-07

    Acute lymphoblastic leukemia (ALL) is a common childhood cancer in which nearly one-quarter of patients experience a disease relapse. However, it has been shown that individualizing therapy for childhood ALL patients by adjusting doses based on the blood concentration of active drug metabolite could significantly improve treatment outcome. An adaptive model predictive control (MPC) strategy is presented in which maintenance therapy for childhood ALL is personalized using routine patient measurements of red blood cell mean corpuscular volume as a surrogate for the active drug metabolite concentration. A clinically relevant mathematical model is developed and used to describe the patient response to the chemotherapeutic drug 6-mercaptopurine, with some model parameters being patient-specific. During the course of treatment, the patient-specific parameters are adaptively identified using recurrent complete blood count measurements, which sufficiently constrain the patient parameter uncertainty to support customized adjustments of the drug dose. While this work represents only a first step toward a quantitative tool for clinical use, the simulated treatment results indicate that the proposed mathematical model and adaptive MPC approach could serve as valuable resources to the oncologist toward creating a personalized treatment strategy that is both safe and effective. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

  5. Reinforcement Learning Based Novel Adaptive Learning Framework for Smart Grid Prediction

    Directory of Open Access Journals (Sweden)

    Tian Li

    2017-01-01

    Full Text Available Smart grid is a potential infrastructure to supply electricity demand for end users in a safe and reliable manner. With the rapid increase of the share of renewable energy and controllable loads in smart grid, the operation uncertainty of smart grid has increased briskly during recent years. The forecast is responsible for the safety and economic operation of the smart grid. However, most existing forecast methods cannot account for the smart grid due to the disabilities to adapt to the varying operational conditions. In this paper, reinforcement learning is firstly exploited to develop an online learning framework for the smart grid. With the capability of multitime scale resolution, wavelet neural network has been adopted in the online learning framework to yield reinforcement learning and wavelet neural network (RLWNN based adaptive learning scheme. The simulations on two typical prediction problems in smart grid, including wind power prediction and load forecast, validate the effectiveness and the scalability of the proposed RLWNN based learning framework and algorithm.

  6. A predictive model to inform adaptive management of double-crested cormorants and fisheries in Michigan

    Science.gov (United States)

    Tsehaye, Iyob; Jones, Michael L.; Irwin, Brian J.; Fielder, David G.; Breck, James E.; Luukkonen, David R.

    2015-01-01

    The proliferation of double-crested cormorants (DCCOs; Phalacrocorax auritus) in North America has raised concerns over their potential negative impacts on game, cultured and forage fishes, island and terrestrial resources, and other colonial water birds, leading to increased public demands to reduce their abundance. By combining fish surplus production and bird functional feeding response models, we developed a deterministic predictive model representing bird–fish interactions to inform an adaptive management process for the control of DCCOs in multiple colonies in Michigan. Comparisons of model predictions with observations of changes in DCCO numbers under management measures implemented from 2004 to 2012 suggested that our relatively simple model was able to accurately reconstruct past DCCO population dynamics. These comparisons helped discriminate among alternative parameterizations of demographic processes that were poorly known, especially site fidelity. Using sensitivity analysis, we also identified remaining critical uncertainties (mainly in the spatial distributions of fish vs. DCCO feeding areas) that can be used to prioritize future research and monitoring needs. Model forecasts suggested that continuation of existing control efforts would be sufficient to achieve long-term DCCO control targets in Michigan and that DCCO control may be necessary to achieve management goals for some DCCO-impacted fisheries in the state. Finally, our model can be extended by accounting for parametric or ecological uncertainty and including more complex assumptions on DCCO–fish interactions as part of the adaptive management process.

  7. Self-Adaptive MOEA Feature Selection for Classification of Bankruptcy Prediction Data

    Science.gov (United States)

    Gaspar-Cunha, A.; Recio, G.; Costa, L.; Estébanez, C.

    2014-01-01

    Bankruptcy prediction is a vast area of finance and accounting whose importance lies in the relevance for creditors and investors in evaluating the likelihood of getting into bankrupt. As companies become complex, they develop sophisticated schemes to hide their real situation. In turn, making an estimation of the credit risks associated with counterparts or predicting bankruptcy becomes harder. Evolutionary algorithms have shown to be an excellent tool to deal with complex problems in finances and economics where a large number of irrelevant features are involved. This paper provides a methodology for feature selection in classification of bankruptcy data sets using an evolutionary multiobjective approach that simultaneously minimise the number of features and maximise the classifier quality measure (e.g., accuracy). The proposed methodology makes use of self-adaptation by applying the feature selection algorithm while simultaneously optimising the parameters of the classifier used. The methodology was applied to four different sets of data. The obtained results showed the utility of using the self-adaptation of the classifier. PMID:24707201

  8. Interest Level in 2-Year-Olds with Autism Spectrum Disorder Predicts Rate of Verbal, Nonverbal, and Adaptive Skill Acquisition

    Science.gov (United States)

    Klintwall, Lars; Macari, Suzanne; Eikeseth, Svein; Chawarska, Katarzyna

    2015-01-01

    Recent studies have suggested that skill acquisition rates for children with autism spectrum disorders receiving early interventions can be predicted by child motivation. We examined whether level of interest during an Autism Diagnostic Observation Schedule assessment at 2?years predicts subsequent rates of verbal, nonverbal, and adaptive skill…

  9. An adaptive short-term prediction scheme for wind energy storage management

    International Nuclear Information System (INIS)

    Blonbou, Ruddy; Monjoly, Stephanie; Dorville, Jean-Francois

    2011-01-01

    Research highlights: → We develop a real time algorithm for grid-connected wind energy storage management. → The method aims to guarantee, with ±5% error margin, the power sent to the grid. → Dynamic scheduling of energy storage is based on short-term energy prediction. → Accurate predictions reduce the need in storage capacity. -- Abstract: Efficient forecasting scheme that includes some information on the likelihood of the forecast and based on a better knowledge of the wind variations characteristics along with their influence on power output variation is of key importance for the optimal integration of wind energy in island's power system. In the Guadeloupean archipelago (French West-Indies), with a total wind power capacity of 25 MW; wind energy can represent up to 5% of the instantaneous electricity production. At this level, wind energy contribution can be equivalent to the current network primary control reserve, which causes balancing difficult. The share of wind energy is due to grow even further since the objective is set to reach 118 MW by 2020. It is an absolute evidence for the network operator that due to security concerns of the electrical grid, the share of wind generation should not increase unless solutions are found to solve the prediction problem. The University of French West-Indies and Guyana has developed a short-term wind energy prediction scheme that uses artificial neural networks and adaptive learning procedures based on Bayesian approach and Gaussian approximation. This paper reports the results of the evaluation of the proposed approach; the improvement with respect to the simple persistent prediction model was globally good. A discussion on how such a tool combined with energy storage capacity could help to smooth the wind power variation and improve the wind energy penetration rate into island utility network is also proposed.

  10. An adaptive mode-driven spatiotemporal motion vector prediction for wavelet video coding

    Science.gov (United States)

    Zhao, Fan; Liu, Guizhong; Qi, Yong

    2010-07-01

    The three-dimensional subband/wavelet codecs use 5/3 filters rather than Haar filters for the motion compensation temporal filtering (MCTF) to improve the coding gain. In order to curb the increased motion vector rate, an adaptive motion mode driven spatiotemporal motion vector prediction (AMDST-MVP) scheme is proposed. First, by making use of the direction histograms of four motion vector fields resulting from the initial spatial motion vector prediction (SMVP), the motion mode of the current GOP is determined according to whether the fast or complex motion exists in the current GOP. Then the GOP-level MVP scheme is thereby determined by either the S-MVP or the AMDST-MVP, namely, AMDST-MVP is the combination of S-MVP and temporal-MVP (T-MVP). If the latter is adopted, the motion vector difference (MVD) between the neighboring MV fields and the S-MVP resulting MV of the current block is employed to decide whether or not the MV of co-located block in the previous frame is used for prediction the current block. Experimental results show that AMDST-MVP not only can improve the coding efficiency but also reduce the number of computation complexity.

  11. Adaptive Granulation-Based Prediction for Energy System of Steel Industry.

    Science.gov (United States)

    Wang, Tianyu; Han, Zhongyang; Zhao, Jun; Wang, Wei

    2018-01-01

    The flow variation tendency of byproduct gas plays a crucial role for energy scheduling in steel industry. An accurate prediction of its future trends will be significantly beneficial for the economic profits of steel enterprise. In this paper, a long-term prediction model for the energy system is proposed by providing an adaptive granulation-based method that considers the production semantics involved in the fluctuation tendency of the energy data, and partitions them into a series of information granules. To fully reflect the corresponding data characteristics of the formed unequal-length temporal granules, a 3-D feature space consisting of the timespan, the amplitude and the linetype is designed as linguistic descriptors. In particular, a collaborative-conditional fuzzy clustering method is proposed to granularize the tendency-based feature descriptors and specifically measure the amplitude variation of industrial data which plays a dominant role in the feature space. To quantify the performance of the proposed method, a series of real-world industrial data coming from the energy data center of a steel plant is employed to conduct the comparative experiments. The experimental results demonstrate that the proposed method successively satisfies the requirements of the practically viable prediction.

  12. Investigation of Diesel’s Residual Noise on Predictive Vehicles Noise Cancelling using LMS Adaptive Algorithm

    Science.gov (United States)

    Arttini Dwi Prasetyowati, Sri; Susanto, Adhi; Widihastuti, Ida

    2017-04-01

    Every noise problems require different solution. In this research, the noise that must be cancelled comes from roadway. Least Mean Square (LMS) adaptive is one of the algorithm that can be used to cancel that noise. Residual noise always appears and could not be erased completely. This research aims to know the characteristic of residual noise from vehicle’s noise and analysis so that it is no longer appearing as a problem. LMS algorithm was used to predict the vehicle’s noise and minimize the error. The distribution of the residual noise could be observed to determine the specificity of the residual noise. The statistic of the residual noise close to normal distribution with = 0,0435, = 1,13 and the autocorrelation of the residual noise forming impulse. As a conclusion the residual noise is insignificant.

  13. Do Proxies for the Neurotransmitter Cortisol Predict Adaptation to Life with Chronic Pain?

    Science.gov (United States)

    Deamond, Wade

    Among the numerous difficulties encountered by chronic pain patients, impulsive and dysfunctional decision-making complicate their already difficult life situations yet remains relatively understudied. This study examined a recently published neurobiological decision making model that identifies eight specific neurotransmitters and hormones (Dopamine, Testosterone, Endogenous Opioids Glutamate, Serotonin, Norepinephrine, Cortisol, and GABA) linked to unsound decision making related to cognitive, motivational and emotional dysregulation (Nussbaum et al., 2011) (see Appendix 2). The Perceived Stress Scale (PSS), a proxy for the cortisol element in the pharmacological decision making model was analyzed for the neurotransmitter's relationship to functionality and quality of life in a group of 37 chronic pain patients. Participants were comprised of males and females ranging from 23 to 52 years of age and were classified with respect to levels of adjustment to living with chronic pain based on the Quality of Life Scale (QLS), the Dartmouth WONCA COOP Charts and the Global Assessment of Functioning (GAF). The Iowa Gambling Task (IGT) and Frontal System Behavioral Scale (FSBS) measured decision making related to immediate gratification and daily living respectively. Results suggest that emotional dysregulation, as measured by the PSS is a significant predictor for adaptation to life with chronic pain and the PSS is superior to predicting adaptation to life with chronic pain than reported levels of pain as measured by the McGill Pain Questionnaire.

  14. Adaptive Anchoring Model: How Static and Dynamic Presentations of Time Series Influence Judgments and Predictions.

    Science.gov (United States)

    Kusev, Petko; van Schaik, Paul; Tsaneva-Atanasova, Krasimira; Juliusson, Asgeir; Chater, Nick

    2018-01-01

    When attempting to predict future events, people commonly rely on historical data. One psychological characteristic of judgmental forecasting of time series, established by research, is that when people make forecasts from series, they tend to underestimate future values for upward trends and overestimate them for downward ones, so-called trend-damping (modeled by anchoring on, and insufficient adjustment from, the average of recent time series values). Events in a time series can be experienced sequentially (dynamic mode), or they can also be retrospectively viewed simultaneously (static mode), not experienced individually in real time. In one experiment, we studied the influence of presentation mode (dynamic and static) on two sorts of judgment: (a) predictions of the next event (forecast) and (b) estimation of the average value of all the events in the presented series (average estimation). Participants' responses in dynamic mode were anchored on more recent events than in static mode for all types of judgment but with different consequences; hence, dynamic presentation improved prediction accuracy, but not estimation. These results are not anticipated by existing theoretical accounts; we develop and present an agent-based model-the adaptive anchoring model (ADAM)-to account for the difference between processing sequences of dynamically and statically presented stimuli (visually presented data). ADAM captures how variation in presentation mode produces variation in responses (and the accuracy of these responses) in both forecasting and judgment tasks. ADAM's model predictions for the forecasting and judgment tasks fit better with the response data than a linear-regression time series model. Moreover, ADAM outperformed autoregressive-integrated-moving-average (ARIMA) and exponential-smoothing models, while neither of these models accounts for people's responses on the average estimation task. Copyright © 2017 The Authors. Cognitive Science published by Wiley

  15. Stability of executive function and predictions to adaptive behavior from middle childhood to pre-adolescence

    Directory of Open Access Journals (Sweden)

    Madeline eHarms

    2014-04-01

    Full Text Available The shift from childhood to adolescence is characterized by rapid remodeling of the brain and increased risk-taking behaviors. Current theories hypothesize that developmental enhancements in sensitivity to affective environmental cues in adolescence may undermine executive function (EF and increase the likelihood of problematic behaviors. In the current study, we examined the extent to which EF in childhood predicts EF in early adolescence. We also tested whether individual differences in neural responses to affective cues (rewards/punishments in childhood serve as a biological marker for EF, sensation-seeking, academic performance, and social skills in early adolescence. At age 8, 84 children completed a gambling task while event-related potentials (ERPs were recorded. We examined the extent to which selections resulting in rewards or losses in this task elicited (i the P300, a post-stimulus waveform reflecting the allocation of attentional resources toward a stimulus, and (ii the SPN, a pre-stimulus anticipatory waveform reflecting a neural representation of a hunch about an outcome that originates in insula and ventromedial PFC. Children also completed a Dimensional Change Card-Sort (DCCS and Flanker task to measure EF. At age 12, 78 children repeated the DCCS and Flanker and completed a battery of questionnaires. Flanker and DCCS accuracy at age 8 predicted Flanker and DCCS performance at age 12, respectively. Individual differences in the magnitude of P300 (to losses vs. rewards and SPN (preceding outcomes with a high probability of punishment at age 8 predicted self-reported sensation seeking (lower and teacher-rated academic performance (higher at age 12. We suggest there is stability in EF from age 8 to 12, and that childhood neural sensitivity to reward and punishment predicts individual differences in sensation seeking and adaptive behaviors in children entering adolescence.

  16. Decision Trees Predicting Tumor Shrinkage for Head and Neck Cancer: Implications for Adaptive Radiotherapy.

    Science.gov (United States)

    Surucu, Murat; Shah, Karan K; Mescioglu, Ibrahim; Roeske, John C; Small, William; Choi, Mehee; Emami, Bahman

    2016-02-01

    To develop decision trees predicting for tumor volume reduction in patients with head and neck (H&N) cancer using pretreatment clinical and pathological parameters. Forty-eight patients treated with definitive concurrent chemoradiotherapy for squamous cell carcinoma of the nasopharynx, oropharynx, oral cavity, or hypopharynx were retrospectively analyzed. These patients were rescanned at a median dose of 37.8 Gy and replanned to account for anatomical changes. The percentages of gross tumor volume (GTV) change from initial to rescan computed tomography (CT; %GTVΔ) were calculated. Two decision trees were generated to correlate %GTVΔ in primary and nodal volumes with 14 characteristics including age, gender, Karnofsky performance status (KPS), site, human papilloma virus (HPV) status, tumor grade, primary tumor growth pattern (endophytic/exophytic), tumor/nodal/group stages, chemotherapy regimen, and primary, nodal, and total GTV volumes in the initial CT scan. The C4.5 Decision Tree induction algorithm was implemented. The median %GTVΔ for primary, nodal, and total GTVs was 26.8%, 43.0%, and 31.2%, respectively. Type of chemotherapy, age, primary tumor growth pattern, site, KPS, and HPV status were the most predictive parameters for primary %GTVΔ decision tree, whereas for nodal %GTVΔ, KPS, site, age, primary tumor growth pattern, initial primary GTV, and total GTV volumes were predictive. Both decision trees had an accuracy of 88%. There can be significant changes in primary and nodal tumor volumes during the course of H&N chemoradiotherapy. Considering the proposed decision trees, radiation oncologists can select patients predicted to have high %GTVΔ, who would theoretically gain the most benefit from adaptive radiotherapy, in order to better use limited clinical resources. © The Author(s) 2015.

  17. Prediction of Scour Depth around Bridge Piers using Adaptive Neuro-Fuzzy Inference Systems (ANFIS)

    Science.gov (United States)

    Valyrakis, Manousos; Zhang, Hanqing

    2014-05-01

    Earth's surface is continuously shaped due to the action of geophysical flows. Erosion due to the flow of water in river systems has been identified as a key problem in preserving ecological health of river systems but also a threat to our built environment and critical infrastructure, worldwide. As an example, it has been estimated that a major reason for bridge failure is due to scour. Even though the flow past bridge piers has been investigated both experimentally and numerically, and the mechanisms of scouring are relatively understood, there still lacks a tool that can offer fast and reliable predictions. Most of the existing formulas for prediction of bridge pier scour depth are empirical in nature, based on a limited range of data or for piers of specific shape. In this work, the application of a Machine Learning model that has been successfully employed in Water Engineering, namely an Adaptive Neuro-Fuzzy Inference System (ANFIS) is proposed to estimate the scour depth around bridge piers. In particular, various complexity architectures are sequentially built, in order to identify the optimal for scour depth predictions, using appropriate training and validation subsets obtained from the USGS database (and pre-processed to remove incomplete records). The model has five variables, namely the effective pier width (b), the approach velocity (v), the approach depth (y), the mean grain diameter (D50) and the skew to flow. Simulations are conducted with data groups (bed material type, pier type and shape) and different number of input variables, to produce reduced complexity and easily interpretable models. Analysis and comparison of the results indicate that the developed ANFIS model has high accuracy and outstanding generalization ability for prediction of scour parameters. The effective pier width (as opposed to skew to flow) is amongst the most relevant input parameters for the estimation.

  18. Predicting the need for adaptive radiotherapy in head and neck cancer

    International Nuclear Information System (INIS)

    Brown, Elizabeth; Owen, Rebecca; Harden, Fiona; Mengersen, Kerrie; Oestreich, Kimberley; Houghton, Whitney; Poulsen, Michael; Harris, Selina; Lin, Charles; Porceddu, Sandro

    2015-01-01

    Background and purpose: Adaptive radiotherapy (ART) can account for the dosimetric impact of anatomical change in head and neck cancer patients; however it can be resource intensive. Consequently, it is imperative that patients likely to require ART are identified. The purpose of this study was to find predictive factors that identify oropharyngeal squamous cell carcinoma (OPC) and nasopharyngeal carcinoma (NPC) patients more likely to need ART. Materials and methods: One hundred and ten patients with OPC or NPC were analysed. Patient demographics and tumour characteristics were compared between patients who were replanned and those that were not. Factors found to be significant were included in logistic regression models. Risk profiles were developed from these models. A dosimetric analysis was performed. Results: Nodal disease stage, pre-treatment largest involved node size, diagnosis and initial weight (categorised in 2 groups) were identified as significant for inclusion in the model. Two models were found to be significant (p = 0.001), correctly classifying 98.2% and 96.1% of patients respectively. Three ART risk profiles were developed. Conclusion: Predictive factors identifying OPC or NPC patients more likely to require ART were reported. A risk profile approach could facilitate the effective implementation of ART into radiotherapy departments through forward planning and appropriate resource allocation

  19. A Novel Adaptive Conditional Probability-Based Predicting Model for User’s Personality Traits

    Directory of Open Access Journals (Sweden)

    Mengmeng Wang

    2015-01-01

    Full Text Available With the pervasive increase in social media use, the explosion of users’ generated data provides a potentially very rich source of information, which plays an important role in helping online researchers understand user’s behaviors deeply. Since user’s personality traits are the driving force of user’s behaviors, hence, in this paper, along with social network features, we first extract linguistic features, emotional statistical features, and topic features from user’s Facebook status updates, followed by quantifying importance of features via Kendall correlation coefficient. And then, on the basis of weighted features and dynamic updated thresholds of personality traits, we deploy a novel adaptive conditional probability-based predicting model which considers prior knowledge of correlations between user’s personality traits to predict user’s Big Five personality traits. In the experimental work, we explore the existence of correlations between user’s personality traits which provides a better theoretical support for our proposed method. Moreover, on the same Facebook dataset, compared to other methods, our method can achieve an F1-measure of 80.6% when taking into account correlations between user’s personality traits, and there is an impressive improvement of 5.8% over other approaches.

  20. Bundle Branch Block

    Science.gov (United States)

    ... known cause. Causes can include: Left bundle branch block Heart attacks (myocardial infarction) Thickened, stiffened or weakened ... myocarditis) High blood pressure (hypertension) Right bundle branch block A heart abnormality that's present at birth (congenital) — ...

  1. Neuro-Oncology Branch

    Science.gov (United States)

    ... BTTC are experts in their respective fields. Neuro-Oncology Clinical Fellowship This is a joint program with ... can increase survival rates. Learn more... The Neuro-Oncology Branch welcomes Dr. Mark Gilbert as new Branch ...

  2. Branched polynomial covering maps

    DEFF Research Database (Denmark)

    Hansen, Vagn Lundsgaard

    1999-01-01

    A Weierstrass polynomial with multiple roots in certain points leads to a branched covering map. With this as the guiding example, we formally define and study the notion of a branched polynomial covering map. We shall prove that many finite covering maps are polynomial outside a discrete branch...... set. Particular studies are made of branched polynomial covering maps arising from Riemann surfaces and from knots in the 3-sphere....

  3. Interest level in 2-year-olds with autism spectrum disorder predicts rate of verbal, nonverbal, and adaptive skill acquisition

    OpenAIRE

    Klintwall, Lars; Macari, Suzanne; Eikeseth, Svein; Chawarska, Katarzyna

    2014-01-01

    Recent studies have suggested that skill acquisition rates for children with autism spectrum disorders receiving early interventions can be predicted by child motivation. We examined whether level of interest during an Autism Diagnostic Observation Schedule assessment at 2 years predicts subsequent rates of verbal, nonverbal, and adaptive skill acquisition to the age of 3 years. A total of 70 toddlers with autism spectrum disorder, mean age of 21.9 months, were scored using Interest Level Sco...

  4. Branched polynomial covering maps

    DEFF Research Database (Denmark)

    Hansen, Vagn Lundsgaard

    2002-01-01

    A Weierstrass polynomial with multiple roots in certain points leads to a branched covering map. With this as the guiding example, we formally define and study the notion of a branched polynomial covering map. We shall prove that many finite covering maps are polynomial outside a discrete branch ...... set. Particular studies are made of branched polynomial covering maps arising from Riemann surfaces and from knots in the 3-sphere. (C) 2001 Elsevier Science B.V. All rights reserved.......A Weierstrass polynomial with multiple roots in certain points leads to a branched covering map. With this as the guiding example, we formally define and study the notion of a branched polynomial covering map. We shall prove that many finite covering maps are polynomial outside a discrete branch...

  5. Environmental prediction, risk assessment and extreme events: adaptation strategies for the developing world

    Science.gov (United States)

    Webster, Peter J.; Jian, Jun

    2011-01-01

    The uncertainty associated with predicting extreme weather events has serious implications for the developing world, owing to the greater societal vulnerability to such events. Continual exposure to unanticipated extreme events is a contributing factor for the descent into perpetual and structural rural poverty. We provide two examples of how probabilistic environmental prediction of extreme weather events can support dynamic adaptation. In the current climate era, we describe how short-term flood forecasts have been developed and implemented in Bangladesh. Forecasts of impending floods with horizons of 10 days are used to change agricultural practices and planning, store food and household items and evacuate those in peril. For the first time in Bangladesh, floods were anticipated in 2007 and 2008, with broad actions taking place in advance of the floods, grossing agricultural and household savings measured in units of annual income. We argue that probabilistic environmental forecasts disseminated to an informed user community can reduce poverty caused by exposure to unanticipated extreme events. Second, it is also realized that not all decisions in the future can be made at the village level and that grand plans for water resource management require extensive planning and funding. Based on imperfect models and scenarios of economic and population growth, we further suggest that flood frequency and intensity will increase in the Ganges, Brahmaputra and Yangtze catchments as greenhouse-gas concentrations increase. However, irrespective of the climate-change scenario chosen, the availability of fresh water in the latter half of the twenty-first century seems to be dominated by population increases that far outweigh climate-change effects. Paradoxically, fresh water availability may become more critical if there is no climate change. PMID:22042897

  6. Career adaptability predicts subjective career success above and beyond personality traits and core self-evaluations

    NARCIS (Netherlands)

    Zacher, Hannes

    The Career Adapt-Abilities Scale (CAAS) measures career adaptability, as a higher-order construct that integrates four psychosocial resources of employees for managing their career development: concern, control, curiosity, and confidence. The goal of the present study was to investigate the validity

  7. Adaptability: How Students' Responses to Uncertainty and Novelty Predict Their Academic and Non-Academic Outcomes

    Science.gov (United States)

    Martin, Andrew J.; Nejad, Harry G.; Colmar, Susan; Liem, Gregory Arief D.

    2013-01-01

    Adaptability is defined as appropriate cognitive, behavioral, and/or affective adjustment in the face of uncertainty and novelty. Building on prior measurement work demonstrating the psychometric properties of an adaptability construct, the present study investigates dispositional predictors (personality, implicit theories) of adaptability, and…

  8. Goal orientation and work role performance: predicting adaptive and proactive work role performance through self-leadership strategies.

    Science.gov (United States)

    Marques-Quinteiro, Pedro; Curral, Luís Alberto

    2012-01-01

    This article explores the relationship between goal orientation, self-leadership dimensions, and adaptive and proactive work role performances. The authors hypothesize that learning orientation, in contrast to performance orientation, positively predicts proactive and adaptive work role performances and that this relationship is mediated by self-leadership behavior-focused strategies. It is posited that self-leadership natural reward strategies and thought pattern strategies are expected to moderate this relationship. Workers (N = 108) from a software company participated in this study. As expected, learning orientation did predict adaptive and proactive work role performance. Moreover, in the relationship between learning orientation and proactive work role performance through self-leadership behavior-focused strategies, a moderated mediation effect was found for self-leadership natural reward and thought pattern strategies. In the end, the authors discuss the results and implications are discussed and future research directions are proposed.

  9. Simulations research of the global predictive control with self-adaptive in the gas turbine of the nuclear power plant

    International Nuclear Information System (INIS)

    Su Jie; Xia Guoqing; Zhang Wei

    2007-01-01

    For further improving the dynamic control capabilities of the gas turbine of the nuclear power plant, this paper puts forward to apply the algorithm of global predictive control with self-adaptive in the rotate speed control of the gas turbine, including control structure and the design of controller in the base of expounding the math model of the gas turbine of the nuclear power plant. the simulation results show that the respond of the change of the gas turbine speed under the control algorithm of global predictive control with self-adaptive is ten second faster than that under the PID control algorithm, and the output value of the gas turbine speed under the PID control algorithm is 1%-2% higher than that under the control slgorithm of global predictive control with self-adaptive. It shows that the algorithm of global predictive control with self-adaptive can better control the output of the speed of the gas turbine of the nuclear power plant and get the better control effect. (authors)

  10. Simultaneous learning and filtering without delusions: a Bayes-optimal combination of Predictive Inference and Adaptive Filtering.

    Science.gov (United States)

    Kneissler, Jan; Drugowitsch, Jan; Friston, Karl; Butz, Martin V

    2015-01-01

    Predictive coding appears to be one of the fundamental working principles of brain processing. Amongst other aspects, brains often predict the sensory consequences of their own actions. Predictive coding resembles Kalman filtering, where incoming sensory information is filtered to produce prediction errors for subsequent adaptation and learning. However, to generate prediction errors given motor commands, a suitable temporal forward model is required to generate predictions. While in engineering applications, it is usually assumed that this forward model is known, the brain has to learn it. When filtering sensory input and learning from the residual signal in parallel, a fundamental problem arises: the system can enter a delusional loop when filtering the sensory information using an overly trusted forward model. In this case, learning stalls before accurate convergence because uncertainty about the forward model is not properly accommodated. We present a Bayes-optimal solution to this generic and pernicious problem for the case of linear forward models, which we call Predictive Inference and Adaptive Filtering (PIAF). PIAF filters incoming sensory information and learns the forward model simultaneously. We show that PIAF is formally related to Kalman filtering and to the Recursive Least Squares linear approximation method, but combines these procedures in a Bayes optimal fashion. Numerical evaluations confirm that the delusional loop is precluded and that the learning of the forward model is more than 10-times faster when compared to a naive combination of Kalman filtering and Recursive Least Squares.

  11. Simultaneous Learning and Filtering without Delusions: A Bayes-Optimal Derivation of Combining Predictive Inference and AdaptiveFiltering

    Directory of Open Access Journals (Sweden)

    Jan eKneissler

    2015-04-01

    Full Text Available Predictive coding appears to be one of the fundamental working principles of brain processing. Amongst other aspects, brains often predict the sensory consequences of their own actions. Predictive coding resembles Kalman filtering, where incoming sensory information is filtered to produce prediction errors for subsequent adaptation and learning. However, to generate prediction errors given motor commands, a suitable temporal forward model is required to generate predictions. While in engineering applications, it is usually assumed that this forward model is known, the brain has to learn it. When filtering sensory input and learning from the residual signal in parallel, a fundamental problem arises: the system can enter a delusional loop when filtering the sensory information using an overly trusted forward model. In this case, learning stalls before accurate convergence because uncertainty about the forward model is not properly accommodated. We present a Bayes-optimal solution to this generic and pernicious problem for the case of linear forward models, which we call Predictive Inference and Adaptive Filtering (PIAF. PIAF filters incoming sensory information and learns the forward model simultaneously. We show that PIAF is formally related to Kalman filtering and to the Recursive Least Squares linear approximation method, but combines these procedures in a Bayes optimal fashion. Numerical evaluations confirm that the delusional loop is precluded and that the learning of the forward model is more than ten-times faster when compared to a naive combination of Kalman filtering and Recursive Least Squares.

  12. An Adaptive Neuro-Fuzzy Inference System for Sea Level Prediction Considering Tide-Generating Forces and Oceanic Thermal Expansion

    Directory of Open Access Journals (Sweden)

    Li-Ching Lin Hsien-Kuo Chang

    2008-01-01

    Full Text Available The paper presents an adaptive neuro fuzzy inference system for predicting sea level considering tide-generating forces and oceanic thermal expansion assuming a model of sea level dependence on sea surface temperature. The proposed model named TGFT-FN (Tide-Generating Forces considering sea surface Temperature and Fuzzy Neuro-network system is applied to predict tides at five tide gauge sites located in Taiwan and has the root mean square of error of about 7.3 - 15.0 cm. The capability of TGFT-FN model is superior in sea level prediction than the previous TGF-NN model developed by Chang and Lin (2006 that considers the tide-generating forces only. The TGFT-FN model is employed to train and predict the sea level of Hua-Lien station, and is also appropriate for the same prediction at the tide gauge sites next to Hua-Lien station.

  13. Identification of Typical Left Bundle Branch Block Contraction by Strain Echocardiography Is Additive to Electrocardiography in Prediction of Long-Term Outcome After Cardiac Resynchronization Therapy

    DEFF Research Database (Denmark)

    Risum, Niels; Tayal, Bhupendar; Hansen, Thomas F

    2015-01-01

    BACKGROUND: Current guidelines suggest that patients with left bundle branch block (LBBB) be treated with cardiac resynchronization therapy (CRT); however, one-third do not have a significant activation delay, which can result in nonresponse. By identifying characteristic opposing wall contraction...... (ECG) morphology and duration. METHODS: From 2 centers, 208 CRT candidates (New York Heart Association classes II to IV, ejection fraction ≤35%, QRS duration ≥120 ms) with LBBB by ECG were prospectively included. Before CRT implantation, longitudinal strain in the apical 4-chamber view determined...... whether typical LBBB contraction was present. The pre-defined outcome was freedom from death, left ventricular assist device, or heart transplantation over 4 years. RESULTS: Two-thirds of patients (63%) had a typical LBBB contraction pattern. During 4 years, 48 patients (23%) reached the primary endpoint...

  14. A Question of Trust: Predictive Conditions for Adaptive and Technical Leadership in Educational Contexts

    Science.gov (United States)

    Daly, Alan J.; Chrispeels, Janet

    2008-01-01

    Recent studies have suggested that educational leaders enacting a balance of technical and adaptive leadership have an effect on increasing student achievement. Technical leadership focuses on problem-solving or first-order changes within existing structures and paradigms. Adaptive leadership involves deep or second-order changes that alter…

  15. A Frequency-Domain Adaptive Filter (FDAF) Prediction Error Method (PEM) Framework for Double-Talk-Robust Acoustic Echo Cancellation

    DEFF Research Database (Denmark)

    Gil-Cacho, Jose M.; van Waterschoot, Toon; Moonen, Marc

    2014-01-01

    to the FDAF-PEM-AFROW algorithm. We show that FDAF-PEM-AFROW is by construction related to the best linear unbiased estimate (BLUE) of the echo path. We depart from this framework to show an improvement in performance with respect to other adaptive filters minimizing the BLUE criterion, namely the PEM......In this paper, we propose a new framework to tackle the double-talk (DT) problem in acoustic echo cancellation (AEC). It is based on a frequency-domain adaptive filter (FDAF) implementation of the so-called prediction error method adaptive filtering using row operations (PEM-AFROW) leading...... regularization (VR) algorithms. The FDAF-PEM-AFROW versions significantly outperform the original versions in every simulation. In terms of computational complexity, the FDAF-PEM-AFROW versions are themselves about two orders of magnitude cheaper than the original versions....

  16. Entanglement branching operator

    Science.gov (United States)

    Harada, Kenji

    2018-01-01

    We introduce an entanglement branching operator to split a composite entanglement flow in a tensor network which is a promising theoretical tool for many-body systems. We can optimize an entanglement branching operator by solving a minimization problem based on squeezing operators. The entanglement branching is a new useful operation to manipulate a tensor network. For example, finding a particular entanglement structure by an entanglement branching operator, we can improve a higher-order tensor renormalization group method to catch a proper renormalization flow in a tensor network space. This new method yields a new type of tensor network states. The second example is a many-body decomposition of a tensor by using an entanglement branching operator. We can use it for a perfect disentangling among tensors. Applying a many-body decomposition recursively, we conceptually derive projected entangled pair states from quantum states that satisfy the area law of entanglement entropy.

  17. Persistence-Based Branch Misprediction Bounds for WCET Analysis

    DEFF Research Database (Denmark)

    Puffitsch, Wolfgang

    2015-01-01

    Branch prediction is an important feature of pipelined processors to achieve high performance. However, it can lead to overly pessimistic worst-case execution time (WCET) bounds when being modeled too conservatively. This paper presents bounds on the number of branch mispredictions for local...... dynamic branch predictors. To handle interferences between branch instructions we use the notion of persistence, a concept that is also found in cache analyses. The bounds apply to branches in general, not only to branches that close a loop. Furthermore, the bounds can be easily integrated into integer...... linear programming formulations of the WCET problem. An evaluation on a number of benchmarks shows that with these bounds, dynamic branch prediction does not necessarily lead to higher WCET bounds than static prediction schemes....

  18. Demonstration of the use of ADAPT to derive predictive maintenance algorithms for the KSC central heat plant

    Science.gov (United States)

    Hunter, H. E.

    1972-01-01

    The Avco Data Analysis and Prediction Techniques (ADAPT) were employed to determine laws capable of detecting failures in a heat plant up to three days in advance of the occurrence of the failure. The projected performance of algorithms yielded a detection probability of 90% with false alarm rates of the order of 1 per year for a sample rate of 1 per day with each detection, followed by 3 hourly samplings. This performance was verified on 173 independent test cases. The program also demonstrated diagnostic algorithms and the ability to predict the time of failure to approximately plus or minus 8 hours up to three days in advance of the failure. The ADAPT programs produce simple algorithms which have a unique possibility of a relatively low cost updating procedure. The algorithms were implemented on general purpose computers at Kennedy Space Flight Center and tested against current data.

  19. NOAA ESRI Grid - predictions of relative uncertainty for sediment size in the New York offshore planning area by NOAA Biogeography Branch

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset represents sediment size prediction uncertainty from a sediment spatial model developed for the New York offshore spatial planning area. The model also...

  20. NOAA ESRI Grid - predictions of relative uncertainty for seabird diversity metrics in the New York offshore planning area by NOAA Biogeography Branch

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset represents relative seabird abundance predictions from spatial models developed for the New York offshore spatial planning area. This raster was derived...

  1. NOAA ESRI Grid - predictions of seabird species richness in the New York offshore planning area made by the NOAA Biogeography Branch

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset represents seabird species richness, or number of species, predictions from spatial models developed for the New York offshore spatial planning area....

  2. NOAA ESRI Grid - predictions of relative seabird abundance in the New York offshore planning area made by the NOAA Biogeography Branch

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset represents relative seabird abundance predictions from spatial models developed for the New York offshore spatial planning area. This raster was derived...

  3. PREDICTIVE CONTROL OF A BATCH POLYMERIZATION SYSTEM USING A FEEDFORWARD NEURAL NETWORK WITH ONLINE ADAPTATION BY GENETIC ALGORITHM

    OpenAIRE

    Cancelier, A.; Claumann, C. A.; Bolzan, A.; Machado, R. A. F.

    2016-01-01

    Abstract This study used a predictive controller based on an empirical nonlinear model comprising a three-layer feedforward neural network for temperature control of the suspension polymerization process. In addition to the offline training technique, an algorithm was also analyzed for online adaptation of its parameters. For the offline training, the network was statically trained and the genetic algorithm technique was used in combination with the least squares method. For online training, ...

  4. Predicting Chinese human resource managers' strategic competence : roles of identity, career variety, organizational support and career adaptability.

    OpenAIRE

    Guan, Y.; Yang, W.; Zhou, X.; Tian, Z.; Eves, A.

    2016-01-01

    Based on career construction theory, the predictors of human resource managers' strategic competence in the Chinese context were examined. Results from a survey administered to Chinese HR managers (N = 220) showed that professional identification, career variety and organizational support for strategic human resource management positively predicted Chinese human resource managers' strategic competence. In addition, career adaptability served as a significant mediator for the above relations. ...

  5. Predicting adaptation to parenthood: The role of responsiveness, gratitude, and trust

    NARCIS (Netherlands)

    Kuile, H. ter; Kluwer, E.S.; Finkenauer, C.; Lippe, A.G. van der

    2017-01-01

    The influence of positive relationship processes, specifically perceived responsiveness, felt gratitude, and felt trust, on perceived adaptation to parenthood was investigated. It was hypothesized that both higher initial levels prior to pregnancy as well as increases over time in perceived

  6. Personal and situational variables, and career concerns: predicting career adaptability in young adults.

    Science.gov (United States)

    Yousefi, Zahra; Abedi, Mohammadreza; Baghban, Iran; Eatemadi, Ozra; Abedi, Ahmade

    2011-05-01

    This study examined relationships among career adaptability and career concerns, social support and goal orientation. We surveyed 304 university students using measures of career concerns, adaptability (career planning, career exploration, self-exploration, decision-making, self-regulation), goal-orientation (learning, performance-prove, performance-avoid) and social support (family, friends, significant others). Multiple regression analysis revealed career concerns, learning and performance-prove goal orientations emerged relatively as the most important contributors. Other variables did not contribute significantly.

  7. Poisson branching point processes

    International Nuclear Information System (INIS)

    Matsuo, K.; Teich, M.C.; Saleh, B.E.A.

    1984-01-01

    We investigate the statistical properties of a special branching point process. The initial process is assumed to be a homogeneous Poisson point process (HPP). The initiating events at each branching stage are carried forward to the following stage. In addition, each initiating event independently contributes a nonstationary Poisson point process (whose rate is a specified function) located at that point. The additional contributions from all points of a given stage constitute a doubly stochastic Poisson point process (DSPP) whose rate is a filtered version of the initiating point process at that stage. The process studied is a generalization of a Poisson branching process in which random time delays are permitted in the generation of events. Particular attention is given to the limit in which the number of branching stages is infinite while the average number of added events per event of the previous stage is infinitesimal. In the special case when the branching is instantaneous this limit of continuous branching corresponds to the well-known Yule--Furry process with an initial Poisson population. The Poisson branching point process provides a useful description for many problems in various scientific disciplines, such as the behavior of electron multipliers, neutron chain reactions, and cosmic ray showers

  8. Renal Branch Artery Stenosis

    DEFF Research Database (Denmark)

    Andersson, Zarah; Thisted, Ebbe; Andersen, Ulrik Bjørn

    2017-01-01

    Renovascular hypertension is a common cause of pediatric hypertension. In the fraction of cases that are unrelated to syndromes such as neurofibromatosis, patients with a solitary stenosis on a branch of the renal artery are common and can be diagnostically challenging. Imaging techniques...... that perform well in the diagnosis of main renal artery stenosis may fall short when it comes to branch artery stenosis. We report 2 cases that illustrate these difficulties and show that a branch artery stenosis may be overlooked even by the gold standard method, renal angiography....

  9. Adaptive adjustment of interval predictive control based on combined model and application in shell brand petroleum distillation tower

    Science.gov (United States)

    Sun, Chao; Zhang, Chunran; Gu, Xinfeng; Liu, Bin

    2017-10-01

    Constraints of the optimization objective are often unable to be met when predictive control is applied to industrial production process. Then, online predictive controller will not find a feasible solution or a global optimal solution. To solve this problem, based on Back Propagation-Auto Regressive with exogenous inputs (BP-ARX) combined control model, nonlinear programming method is used to discuss the feasibility of constrained predictive control, feasibility decision theorem of the optimization objective is proposed, and the solution method of soft constraint slack variables is given when the optimization objective is not feasible. Based on this, for the interval control requirements of the controlled variables, the slack variables that have been solved are introduced, the adaptive weighted interval predictive control algorithm is proposed, achieving adaptive regulation of the optimization objective and automatically adjust of the infeasible interval range, expanding the scope of the feasible region, and ensuring the feasibility of the interval optimization objective. Finally, feasibility and effectiveness of the algorithm is validated through the simulation comparative experiments.

  10. AptRank: an adaptive PageRank model for protein function prediction on   bi-relational graphs.

    Science.gov (United States)

    Jiang, Biaobin; Kloster, Kyle; Gleich, David F; Gribskov, Michael

    2017-06-15

    Diffusion-based network models are widely used for protein function prediction using protein network data and have been shown to outperform neighborhood-based and module-based methods. Recent studies have shown that integrating the hierarchical structure of the Gene Ontology (GO) data dramatically improves prediction accuracy. However, previous methods usually either used the GO hierarchy to refine the prediction results of multiple classifiers, or flattened the hierarchy into a function-function similarity kernel. No study has taken the GO hierarchy into account together with the protein network as a two-layer network model. We first construct a Bi-relational graph (Birg) model comprised of both protein-protein association and function-function hierarchical networks. We then propose two diffusion-based methods, BirgRank and AptRank, both of which use PageRank to diffuse information on this two-layer graph model. BirgRank is a direct application of traditional PageRank with fixed decay parameters. In contrast, AptRank utilizes an adaptive diffusion mechanism to improve the performance of BirgRank. We evaluate the ability of both methods to predict protein function on yeast, fly and human protein datasets, and compare with four previous methods: GeneMANIA, TMC, ProteinRank and clusDCA. We design four different validation strategies: missing function prediction, de novo function prediction, guided function prediction and newly discovered function prediction to comprehensively evaluate predictability of all six methods. We find that both BirgRank and AptRank outperform the previous methods, especially in missing function prediction when using only 10% of the data for training. The MATLAB code is available at https://github.rcac.purdue.edu/mgribsko/aptrank . gribskov@purdue.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  11. Predicting ethnic variation in adaptation to later life: styles of socioemotional functioning and constrained heterotypy.

    Science.gov (United States)

    Consedine, Nathan S; Magai, Carol; Conway, Francine

    2004-06-01

    It is an axiom of social gerontology that populations of older individuals become increasingly differentiated as they age. Adaptations to physical and social losses and the increased dependency that typically accompany greater age are likely to be similarly heterogeneous, with different individuals adjusting to the aging process in widely diverse ways. In this paper we consider how individuals with diverse emotional and regulatory profiles, different levels of religiosity, and varied patterns of social relatedness fare as they age. Specifically, we examine the relation between ethnicity and patterns of socioemotional adaptation in a large, ethnically diverse sample (N = 1118) of community-dwelling older adults. Cluster analysis was applied to 11 measures of socioemotional functioning. Ten qualitatively different profiles were extracted and then related to a measure of physical resiliency. Consistent with ethnographic and psychological theory, individuals from different ethnic backgrounds were unevenly distributed across the clusters. Resilient participants of African descent (African Americans, Jamaicans, Trinidadians, Barbadians) were more likely to manifest patterns of adaptation characterized by religious beliefs, while resilient US-born Whites and Immigrant Whites were more likely to be resilient as a result of non-religious social connectedness. Taken together, although these data underscore the diversity of adaptation to later life, we suggest that patterns of successful adaptation vary systematically across ethnic groups. Implications for the continued study of ethnicity in aging and directions for future research are given.

  12. Birth weight predicted baseline muscular efficiency, but not response of energy expenditure to calorie restriction: An empirical test of the predictive adaptive response hypothesis.

    Science.gov (United States)

    Workman, Megan; Baker, Jack; Lancaster, Jane B; Mermier, Christine; Alcock, Joe

    2016-07-01

    Aiming to test the evolutionary significance of relationships linking prenatal growth conditions to adult phenotypes, this study examined whether birth size predicts energetic savings during fasting. We specifically tested a Predictive Adaptive Response (PAR) model that predicts greater energetic saving among adults who were born small. Data were collected from a convenience sample of young adults living in Albuquerque, NM (n = 34). Indirect calorimetry quantified changes in resting energy expenditure (REE) and active muscular efficiency that occurred in response to a 29-h fast. Multiple regression analyses linked birth weight to baseline and postfast metabolic values while controlling for appropriate confounders (e.g., sex, body mass). Birth weight did not moderate the relationship between body size and energy expenditure, nor did it predict the magnitude change in REE or muscular efficiency observed from baseline to after fasting. Alternative indicators of birth size were also examined (e.g., low v. normal birth weight, comparison of tertiles), with no effects found. However, baseline muscular efficiency improved by 1.1% per 725 g (S.D.) increase in birth weight (P = 0.037). Birth size did not influence the sensitivity of metabolic demands to fasting-neither at rest nor during activity. Moreover, small birth size predicted a reduction in the efficiency with which muscles convert energy expended into work accomplished. These results do not support the ascription of adaptive function to phenotypes associated with small birth size. © 2015 Wiley Periodicals, Inc. Am. J. Hum. Biol. 28:484-492, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  13. Branching processes in biology

    CERN Document Server

    Kimmel, Marek

    2015-01-01

    This book provides a theoretical background of branching processes and discusses their biological applications. Branching processes are a well-developed and powerful set of tools in the field of applied probability. The range of applications considered includes molecular biology, cellular biology, human evolution and medicine. The branching processes discussed include Galton-Watson, Markov, Bellman-Harris, Multitype, and General Processes. As an aid to understanding specific examples, two introductory chapters, and two glossaries are included that provide background material in mathematics and in biology. The book will be of interest to scientists who work in quantitative modeling of biological systems, particularly probabilists, mathematical biologists, biostatisticians, cell biologists, molecular biologists, and bioinformaticians. The authors are a mathematician and cell biologist who have collaborated for more than a decade in the field of branching processes in biology for this new edition. This second ex...

  14. Branching trajectory continual integral

    International Nuclear Information System (INIS)

    Maslov, V.P.; Chebotarev, A.M.

    1980-01-01

    Heuristic definition of the Feynman continual integral over branching trajectories is suggested which makes it possible to obtain in the closed form the solution of the Cauchy problem for the model Hartree equation. A number of properties of the solution is derived from an integral representation. In particular, the quasiclassical asymptotics, exact solution in the gaussian case and perturbation theory series are described. The existence theorem for the simpliest continual integral over branching trajectories is proved [ru

  15. Better predictions, better allocations: scientific advances and adaptation to climate change.

    Science.gov (United States)

    Freeman, Mark C; Groom, Ben; Zeckhauser, Richard J

    2015-11-28

    Climate science initially aspired to improve understanding of what the future would bring, and thereby produce appropriate public policies and effective international climate agreements. If that hope is dashed, as now seems probable, effective policies for adapting to climate change become critical. Climate science assumes new responsibilities by helping to foster more appropriate adaptation measures, which might include shifting modes or locales of production. This theoretical article focuses on two broader tools: consumption smoothing in response to the risk of future losses, and physical adaptation measures to reduce potential damages. It shows that informative signals on the effects of climate change facilitate better decisions on the use of each tool, thereby increasing social welfare. © 2015 The Author(s).

  16. Branching processes and neutral evolution

    CERN Document Server

    Taïb, Ziad

    1992-01-01

    The Galton-Watson branching process has its roots in the problem of extinction of family names which was given a precise formulation by F. Galton as problem 4001 in the Educational Times (17, 1873). In 1875, an attempt to solve this problem was made by H. W. Watson but as it turned out, his conclusion was incorrect. Half a century later, R. A. Fisher made use of the Galton-Watson process to determine the extinction probability of the progeny of a mutant gene. However, it was J. B. S. Haldane who finally gave the first sketch of the correct conclusion. J. B. S. Haldane also predicted that mathematical genetics might some day develop into a "respectable branch of applied mathematics" (quoted in M. Kimura & T. Ohta, Theoretical Aspects of Population Genetics. Princeton, 1971). Since the time of Fisher and Haldane, the two fields of branching processes and mathematical genetics have attained a high degree of sophistication but in different directions. This monograph is a first attempt to apply the current sta...

  17. Prognosis assessment of persistent left bundle branch block after TAVI by an electrophysiological and remote monitoring risk-adapted algorithm: rationale and design of the multicentre LBBB-TAVI Study.

    Science.gov (United States)

    Massoullié, Grégoire; Bordachar, Pierre; Irles, Didier; Caussin, Christophe; Da Costa, Antoine; Defaye, Pascal; Jean, Frédéric; Mechulan, Alexis; Mondoly, Pierre; Souteyrand, Géraud; Pereira, Bruno; Ploux, Sylvain; Eschalier, Romain

    2016-10-26

    Percutaneous aortic valve replacement (transcatheter aortic valve implantation (TAVI)) notably increases the likelihood of the appearance of a complete left bundle branch block (LBBB) by direct lesion of the LBB of His. This block can lead to high-grade atrioventricular conduction disturbances responsible for a poorer prognosis. The management of this complication remains controversial. The screening of LBBB after TAVI persisting for more than 24 hours will be conducted by surface ECG. Stratification will be performed by post-TAVI intracardiac electrophysiological study. Patients at high risk of conduction disturbances (≥70 ms His-ventricle interval (HV) or presence of infra-Hisian block) will be implanted with a pacemaker enabling the recording of disturbance episodes. Those at lower risk (HV algorithm based on electrophysiological study and remote monitoring of CIEDs in the prediction of high-grade conduction disturbances in patients with LBBB after TAVI. The primary end point is to compare the incidence (rate and time to onset) of high-grade conduction disturbances in patients with LBBB after TAVI between the two groups at 12 months. Given the proportion of high-grade conduction disturbances (20-40%), a sample of 200 subjects will allow a margin of error of 6-7%. The LBBB-TAVI Study has been in an active recruiting phase since September 2015 (21 patients already included). Local ethics committee authorisation was obtained in May 2015. We will publish findings from this study in a peer-reviewed scientific journal and present results at national and international conferences. NCT02482844; Pre-results. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  18. ANFIS Based Time Series Prediction Method of Bank Cash Flow Optimized by Adaptive Population Activity PSO Algorithm

    Directory of Open Access Journals (Sweden)

    Jie-Sheng Wang

    2015-06-01

    Full Text Available In order to improve the accuracy and real-time of all kinds of information in the cash business, and solve the problem which accuracy and stability is not high of the data linkage between cash inventory forecasting and cash management information in the commercial bank, a hybrid learning algorithm is proposed based on adaptive population activity particle swarm optimization (APAPSO algorithm combined with the least squares method (LMS to optimize the adaptive network-based fuzzy inference system (ANFIS model parameters. Through the introduction of metric function of population diversity to ensure the diversity of population and adaptive changes in inertia weight and learning factors, the optimization ability of the particle swarm optimization (PSO algorithm is improved, which avoids the premature convergence problem of the PSO algorithm. The simulation comparison experiments are carried out with BP-LMS algorithm and standard PSO-LMS by adopting real commercial banks’ cash flow data to verify the effectiveness of the proposed time series prediction of bank cash flow based on improved PSO-ANFIS optimization method. Simulation results show that the optimization speed is faster and the prediction accuracy is higher.

  19. Leuconostoc mesenteroides growth in food products: prediction and sensitivity analysis by adaptive-network-based fuzzy inference systems.

    Directory of Open Access Journals (Sweden)

    Hue-Yu Wang

    Full Text Available BACKGROUND: An adaptive-network-based fuzzy inference system (ANFIS was compared with an artificial neural network (ANN in terms of accuracy in predicting the combined effects of temperature (10.5 to 24.5°C, pH level (5.5 to 7.5, sodium chloride level (0.25% to 6.25% and sodium nitrite level (0 to 200 ppm on the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. METHODS: THE ANFIS AND ANN MODELS WERE COMPARED IN TERMS OF SIX STATISTICAL INDICES CALCULATED BY COMPARING THEIR PREDICTION RESULTS WITH ACTUAL DATA: mean absolute percentage error (MAPE, root mean square error (RMSE, standard error of prediction percentage (SEP, bias factor (Bf, accuracy factor (Af, and absolute fraction of variance (R (2. Graphical plots were also used for model comparison. CONCLUSIONS: The learning-based systems obtained encouraging prediction results. Sensitivity analyses of the four environmental factors showed that temperature and, to a lesser extent, NaCl had the most influence on accuracy in predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. The observed effectiveness of ANFIS for modeling microbial kinetic parameters confirms its potential use as a supplemental tool in predictive mycology. Comparisons between growth rates predicted by ANFIS and actual experimental data also confirmed the high accuracy of the Gaussian membership function in ANFIS. Comparisons of the six statistical indices under both aerobic and anaerobic conditions also showed that the ANFIS model was better than all ANN models in predicting the four kinetic parameters. Therefore, the ANFIS model is a valuable tool for quickly predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions.

  20. Improved prediction error filters for adaptive feedback cancellation in hearing aids

    DEFF Research Database (Denmark)

    Ngo, Kim; van Waterschoot, Toon; Christensen, Mads Græsbøll

    2013-01-01

    feedback cancellation (AFC) where the goal is to adaptively model the acoustic feedback path and estimate the feedback signal, which is then subtracted from the microphone signal. The main problem in identifying the acoustic feedback path model is the correlation between the near-end signal...

  1. Cross-cultural adaptation of the STRATIFY tool in detecting and predicting risk of falling.

    Science.gov (United States)

    Enríquez de Luna-Rodríguez, Margarita; Aranda-Gallardo, Marta; Canca-Sánchez, José Carlos; Vazquez-Blanco, M José; Moya-Suárez, Ana Belén; Morales-Asencio, José Miguel

    To adapt to Spanish language the STRATIFY tool for clinical use in the Spanish-speaking World. A multicenter, 2 care settings cross-sectional study cultural adaptation study in acute care hospitals and nursing homes was performed in Andalusia during 2014. The adaptation process was divided into 4 stages: translation, back-translation, equivalence between the 2 back-translations and piloting of the Spanish version, thus obtaining the final version. The validity of appearance, content validity and the time required to complete the scale were taken into account. For analysis, the median, central tendency and dispersion of scores, the interquartile range, and the interquartile deviation for the possible variability in responses it was calculated. Content validity measured by content validity index reached a profit of 1. For the validity aspect the clarity and comprehensibility of the questions were taken into account. Of the 5 questions of the instrument, 2 had a small disagreement solved with the introduction of an explanatory phrase to achieve conceptual equivalence. Median both questions were equal or superior to 5. The average time for completion of the scale was less than 3 minutes. The process of adaptation to Spanish of STRATIFY has led to a semantic version and culturally equivalent to the original for easy filling and understanding for use in the Spanish-speaking world. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

  2. Robust model predictive cooperative adaptive cruise control subject to V2V impairments

    NARCIS (Netherlands)

    Van Nunen, Ellen; Verhaegh, Jan; Silvas, Emilia; Semsar-Kazerooni, Elham; Van De Wouw, Nathan

    2018-01-01

    To improve traffic throughput, Cooperative Adaptive Cruise Control (CACC) has been proposed as a solution. The usage of Vehicle-to-Vehicle (V2V) communication enables short following distances, thereby increasing road capacity and fuel reduction (especially for trucks). Control designs for CACC use

  3. Follow You, Follow  Me: Continuous Mutual Prediction and Adaptation in Joint Tapping

    DEFF Research Database (Denmark)

    Konvalinka, Ivana; Vuust, Peter; Roepstorff, Andreas

    2010-01-01

    both were hearing each other, the pair became a coupled, mutually and continuously adaptive unit of two “hyper-followers”, with their intertap intervals (ITIs) oscillating in opposite directions on a tap-to-tap basis. There was thus no evidence for the emergence of a leader–follower strategy. We also...

  4. Optimal Multitrial Prediction Combination and Subject-Specific Adaptation for Minimal Training Brain Switch Designs

    NARCIS (Netherlands)

    Spyrou, L.; Blokland, Y.M.; Farquhar, J.D.R.; Bruhn, J.

    2016-01-01

    Brain-Computer Interface (BCI) systems are traditionally designed by taking into account user-specific data to enable practical use. More recently, subject independent (SI) classification algorithms have been developed which bypass the subject specific adaptation and enable rapid use of the system.

  5. Optimal multitrial prediction combination and subject-specific adaptation for minimal training brain switch designs

    NARCIS (Netherlands)

    Spyrou, L.; Blokland, Y.M.; Farquhar, J.D.R.; Bruhn, J.

    2016-01-01

    Brain-Computer Interface systems are traditionally designed by taking into account user-specific data to enable practical use. More recently, subject independent (SI) classification algorithms have been developed which bypass the subject specific adaptation and enable rapid use of the system. A

  6. Temperature adaptation of soil bacterial communities along an Antarctic climate gradient: predicting responses to climate warming

    DEFF Research Database (Denmark)

    Rinnan, Riikka; Rousk, Johannes; Yergeau, Etienne

    2009-01-01

     °38'W) and the Falkland Islands (51 °76'S 59 °03'W). At each location, experimental plots were subjected to warming by open top chambers (OTCs) and paired with control plots on vegetated and fell-field habitats. The bacterial communities were adapted to the mean annual temperature of their environment...

  7. Towards an Online Seizure Advisory System—An Adaptive Seizure Prediction Framework Using Active Learning Heuristics

    NARCIS (Netherlands)

    Karuppiah Ramachandran, Vignesh Raja; Alblas, Huibert J.; Le Viet Duc, Duc Viet; Meratnia, Nirvana

    2018-01-01

    In the last decade, seizure prediction systems have gained a lot of attention because of their enormous potential to largely improve the quality-of-life of the epileptic patients. The accuracy of the prediction algorithms to detect seizure in real-world applications is largely limited because the

  8. Predictive local receptive fields based respiratory motion tracking for motion-adaptive radiotherapy.

    Science.gov (United States)

    Yubo Wang; Tatinati, Sivanagaraja; Liyu Huang; Kim Jeong Hong; Shafiq, Ghufran; Veluvolu, Kalyana C; Khong, Andy W H

    2017-07-01

    Extracranial robotic radiotherapy employs external markers and a correlation model to trace the tumor motion caused by the respiration. The real-time tracking of tumor motion however requires a prediction model to compensate the latencies induced by the software (image data acquisition and processing) and hardware (mechanical and kinematic) limitations of the treatment system. A new prediction algorithm based on local receptive fields extreme learning machines (pLRF-ELM) is proposed for respiratory motion prediction. All the existing respiratory motion prediction methods model the non-stationary respiratory motion traces directly to predict the future values. Unlike these existing methods, the pLRF-ELM performs prediction by modeling the higher-level features obtained by mapping the raw respiratory motion into the random feature space of ELM instead of directly modeling the raw respiratory motion. The developed method is evaluated using the dataset acquired from 31 patients for two horizons in-line with the latencies of treatment systems like CyberKnife. Results showed that pLRF-ELM is superior to that of existing prediction methods. Results further highlight that the abstracted higher-level features are suitable to approximate the nonlinear and non-stationary characteristics of respiratory motion for accurate prediction.

  9. Branches of the Facial Artery.

    Science.gov (United States)

    Hwang, Kun; Lee, Geun In; Park, Hye Jin

    2015-06-01

    The aim of this study is to review the name of the branches, to review the classification of the branching pattern, and to clarify a presence percentage of each branch of the facial artery, systematically. In a PubMed search, the search terms "facial," AND "artery," AND "classification OR variant OR pattern" were used. The IBM SPSS Statistics 20 system was used for statistical analysis. Among the 500 titles, 18 articles were selected and reviewed systematically. Most of the articles focused on "classification" according to the "terminal branch." Several authors classified the facial artery according to their terminal branches. Most of them, however, did not describe the definition of "terminal branch." There were confusions within the classifications. When the inferior labial artery was absent, 3 different types were used. The "alar branch" or "nasal branch" was used instead of the "lateral nasal branch." The angular branch was used to refer to several different branches. The presence as a percentage of each branch according to the branches in Gray's Anatomy (premasseteric, inferior labial, superior labial, lateral nasal, and angular) varied. No branch was used with 100% consistency. The superior labial branch was most frequently cited (95.7%, 382 arteries in 399 hemifaces). The angular branch (53.9%, 219 arteries in 406 hemifaces) and the premasseteric branch were least frequently cited (53.8%, 43 arteries in 80 hemifaces). There were significant differences among each of the 5 branches (P < 0.05) except between the angular branch and the premasseteric branch and between the superior labial branch and the inferior labial branch. The authors believe identifying the presence percentage of each branch will be helpful for surgical procedures.

  10. Age-related changes in predictive capacity versus internal model adaptability: electrophysiological evidence that individual differences outweigh effects of age

    Directory of Open Access Journals (Sweden)

    Ina eBornkessel-Schlesewsky

    2015-11-01

    Full Text Available Hierarchical predictive coding has been identified as a possible unifying principle of brain function, and recent work in cognitive neuroscience has examined how it may be affected by age–related changes. Using language comprehension as a test case, the present study aimed to dissociate age-related changes in prediction generation versus internal model adaptation following a prediction error. Event-related brain potentials (ERPs were measured in a group of older adults (60–81 years; n=40 as they read sentences of the form The opposite of black is white/yellow/nice. Replicating previous work in young adults, results showed a target-related P300 for the expected antonym (white; an effect assumed to reflect a prediction match, and a graded N400 effect for the two incongruous conditions (i.e. a larger N400 amplitude for the incongruous continuation not related to the expected antonym, nice, versus the incongruous associated condition, yellow. These effects were followed by a late positivity, again with a larger amplitude in the incongruous non-associated versus incongruous associated condition. Analyses using linear mixed-effects models showed that the target-related P300 effect and the N400 effect for the incongruous non-associated condition were both modulated by age, thus suggesting that age-related changes affect both prediction generation and model adaptation. However, effects of age were outweighed by the interindividual variability of ERP responses, as reflected in the high proportion of variance captured by the inclusion of by-condition random slopes for participants and items. We thus argue that – at both a neurophysiological and a functional level – the notion of general differences between language processing in young and older adults may only be of limited use, and that future research should seek to better understand the causes of interindividual variability in the ERP responses of older adults and its relation to cognitive

  11. An adaptive two-stage analog/regression model for probabilistic prediction of small-scale precipitation in France

    Science.gov (United States)

    Chardon, Jérémy; Hingray, Benoit; Favre, Anne-Catherine

    2018-01-01

    Statistical downscaling models (SDMs) are often used to produce local weather scenarios from large-scale atmospheric information. SDMs include transfer functions which are based on a statistical link identified from observations between local weather and a set of large-scale predictors. As physical processes driving surface weather vary in time, the most relevant predictors and the regression link are likely to vary in time too. This is well known for precipitation for instance and the link is thus often estimated after some seasonal stratification of the data. In this study, we present a two-stage analog/regression model where the regression link is estimated from atmospheric analogs of the current prediction day. Atmospheric analogs are identified from fields of geopotential heights at 1000 and 500 hPa. For the regression stage, two generalized linear models are further used to model the probability of precipitation occurrence and the distribution of non-zero precipitation amounts, respectively. The two-stage model is evaluated for the probabilistic prediction of small-scale precipitation over France. It noticeably improves the skill of the prediction for both precipitation occurrence and amount. As the analog days vary from one prediction day to another, the atmospheric predictors selected in the regression stage and the value of the corresponding regression coefficients can vary from one prediction day to another. The model allows thus for a day-to-day adaptive and tailored downscaling. It can also reveal specific predictors for peculiar and non-frequent weather configurations.

  12. Java-Based Coupling for Parallel Predictive-Adaptive Domain Decomposition

    Directory of Open Access Journals (Sweden)

    Cécile Germain‐Renaud

    1999-01-01

    Full Text Available Adaptive domain decomposition exemplifies the problem of integrating heterogeneous software components with intermediate coupling granularity. This paper describes an experiment where a data‐parallel (HPF client interfaces with a sequential computation server through Java. We show that seamless integration of data‐parallelism is possible, but requires most of the tools from the Java palette: Java Native Interface (JNI, Remote Method Invocation (RMI, callbacks and threads.

  13. Adaptive Control of the Packet Transmission Period with Solar Energy Harvesting Prediction in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Kideok Kwon

    2015-04-01

    Full Text Available A number of research works has studied packet scheduling policies in energy scavenging wireless sensor networks, based on the predicted amount of harvested energy. Most of them aim to achieve energy neutrality, which means that an embedded system can operate perpetually while meeting application requirements. Unlike other renewable energy sources, solar energy has the feature of distinct periodicity in the amount of harvested energy over a day. Using this feature, this paper proposes a packet transmission control policy that can enhance the network performance while keeping sensor nodes alive. Furthermore, this paper suggests a novel solar energy prediction method that exploits the relation between cloudiness and solar radiation. The experimental results and analyses show that the proposed packet transmission policy outperforms others in terms of the deadline miss rate and data throughput. Furthermore, the proposed solar energy prediction method can predict more accurately than others by 6.92%.

  14. Adaptive control of the packet transmission period with solar energy harvesting prediction in wireless sensor networks.

    Science.gov (United States)

    Kwon, Kideok; Yang, Jihoon; Yoo, Younghwan

    2015-04-24

    A number of research works has studied packet scheduling policies in energy scavenging wireless sensor networks, based on the predicted amount of harvested energy. Most of them aim to achieve energy neutrality, which means that an embedded system can operate perpetually while meeting application requirements. Unlike other renewable energy sources, solar energy has the feature of distinct periodicity in the amount of harvested energy over a day. Using this feature, this paper proposes a packet transmission control policy that can enhance the network performance while keeping sensor nodes alive. Furthermore, this paper suggests a novel solar energy prediction method that exploits the relation between cloudiness and solar radiation. The experimental results and analyses show that the proposed packet transmission policy outperforms others in terms of the deadline miss rate and data throughput. Furthermore, the proposed solar energy prediction method can predict more accurately than others by 6.92%.

  15. An Adaptive Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-ion Batteries

    Data.gov (United States)

    National Aeronautics and Space Administration — Prognostics is an emerging science of predicting the health condition of a system (or its components) based upon current and previous system states. A reliable...

  16. Adapting the Surgical Apgar Score for Perioperative Outcome Prediction in Liver Transplantation: A Retrospective Study

    Directory of Open Access Journals (Sweden)

    Amy C. S. Pearson, MD

    2017-11-01

    Conclusions. The SAS-LT utilized simple intraoperative metrics to predict early morbidity and mortality after liver transplant with similar accuracy to other scoring systems at an earlier postoperative time point.

  17. Adaptive Neuro-Fuzzy Inference Systems as a Strategy for Predicting and Controling the Energy Produced from Renewable Sources

    Directory of Open Access Journals (Sweden)

    Otilia Elena Dragomir

    2015-11-01

    Full Text Available The challenge for our paper consists in controlling the performance of the future state of a microgrid with energy produced from renewable energy sources. The added value of this proposal consists in identifying the most used criteria, related to each modeling step, able to lead us to an optimal neural network forecasting tool. In order to underline the effects of users’ decision making on the forecasting performance, in the second part of the article, two Adaptive Neuro-Fuzzy Inference System (ANFIS models are tested and evaluated. Several scenarios are built by changing: the prediction time horizon (Scenario 1 and the shape of membership functions (Scenario 2.

  18. VD-411 branch driver

    International Nuclear Information System (INIS)

    Gorbunov, N.V.; Karev, A.G.; Mal'tsev, Eh.I.; Morozov, B.A.

    1985-01-01

    The VD-411 branch driver for CAMAC moduli control by the SM-4 computer is described. The driver realizes data exchange with moduli disposed in 28 crates grouped in 4 branches. Data exchange can be carried out either in the program regime or in the regime of direct access to the memory. Fulfilment of 11 block regimes and one program regime is provided for. A possibility of individual programming of exchange methods in block regimes is left for users for organisation of quicker and most flexible data removal from the CAMAC moduli. In the regime of direct access the driver provides data transmission at the size up to 64 Kwords placing it in the computer memory of 2 M byte. High rate of data transmission and the developed system of interruptions ensure efficient utilization of the VD-411 branch driver at data removal from facilities in high energy physics experiments

  19. An innovative approach for Predicting Farmers' Adaptive Behavior at the Large Watershed Scale: Implications for Water Quality and Crop Yields

    Science.gov (United States)

    Valcu-Lisman, A. M.; Gassman, P. W.; Arritt, R. W.; Kling, C.; Arbuckle, J. G.; Roesch-McNally, G. E.; Panagopoulos, Y.

    2017-12-01

    Projected changes in the climatic patterns (higher temperatures, changes in extreme precipitation events, and higher levels of humidity) will affect agricultural cropping and management systems in major agricultural production areas. The concept of adaption to new climatic or economic conditions is an important aspect of the agricultural decision-making process. Adopting cover crops, reduced tillage, extending the drainage systems and adjusting crop management are only a few examples of adaptive actions. These actions can be easily implemented as long as they have private benefits (increased profits, reduced risk). However, each adaptive action has a different impact on water quality. Cover crops and no till usually have a positive impact on water quality, but increased tile drainage typically results in more degraded water quality due primarily to increased export of soluble nitrogen and phosphorus. The goal of this research is to determine the changes in water quality as well in crop yields as farmers undertake these adaptive measures. To answer this research question, we need to estimate the likelihood that these actions will occur, identify the agricultural areas where these actions are most likely to be implemented, and simulate the water quality impacts associated with each of these scenarios. We apply our modeling efforts to the whole Upper-Mississippi River Basin Basin (UMRB) and the Ohio-Tennessee River Basin (OTRB). These two areas are critical source regions for the re-occurring hypoxic zone in the gulf of Mexico. The likelihood of each adaptive agricultural action is estimated using data from a survey conducted in 2012. A large, representative sample of farmers in the Corn Belt was used in the survey to elicit behavioral intentions regarding three of the most important agricultural adaptation strategies (no-till, cover crops and tile drainage). We use these data to study the relationship between intent to adapt, farmer characteristics, farm

  20. Using Tests Designed to Measure Individual Sensorimotor Subsystem Perfomance to Predict Locomotor Adaptability

    Science.gov (United States)

    Peters, B. T.; Caldwell, E. E.; Batson, C. D.; Guined, J. R.; DeDios, Y. E.; Stepanyan, V.; Gadd, N. E.; Szecsy, D. L.; Mulavara, A. P.; Seidler, R. D.; hide

    2014-01-01

    Astronauts experience sensorimotor disturbances during the initial exposure to microgravity and during the readapation phase following a return to a gravitational environment. These alterations may lead to disruption in the ability to perform mission critical functions during and after these gravitational transitions. Astronauts show significant inter-subject variation in adaptive capability following gravitational transitions. The way each individual's brain synthesizes the available visual, vestibular and somatosensory information is likely the basis for much of the variation. Identifying the presence of biases in each person's use of information available from these sensorimotor subsystems and relating it to their ability to adapt to a novel locomotor task will allow us to customize a training program designed to enhance sensorimotor adaptability. Eight tests are being used to measure sensorimotor subsystem performance. Three of these use measures of body sway to characterize balance during varying sensorimotor challenges. The effect of vision is assessed by repeating conditions with eyes open and eyes closed. Standing on foam, or on a support surface that pitches to maintain a constant ankle angle provide somatosensory challenges. Information from the vestibular system is isolated when vision is removed and the support surface is compromised, and it is challenged when the tasks are done while the head is in motion. The integration and dominance of visual information is assessed in three additional tests. The Rod & Frame Test measures the degree to which a subject's perception of the visual vertical is affected by the orientation of a tilted frame in the periphery. Locomotor visual dependence is determined by assessing how much an oscillating virtual visual world affects a treadmill-walking subject. In the third of the visual manipulation tests, subjects walk an obstacle course while wearing up-down reversing prisms. The two remaining tests include direct

  1. A randomised comparison of Conventional versus Intentional straTegy in patients with high Risk prEdiction of Side branch OccLusion in coronary bifurcation interVEntion: rationale and design of the CIT-RESOLVE trial.

    Science.gov (United States)

    Zhang, Dong; Yin, Dong; Song, Chenxi; Zhu, Chengang; Kirtane, Ajay J; Xu, Bo; Dou, Kefei

    2017-06-12

    The intentional strategy (aggressive side branch (SB) protection strategy: elective two-stent strategy or jailed balloon technique) is thought to be associated with lower SB occlusion rate than conventional strategy (provisional two-stent strategy or jailed wire technique). However, most previous studies showed comparable outcomes between the two strategies, probably due to no risk classification of SB occlusion when enrolling patients. There is still no randomised trial compared the intentional and conventional strategy when treating bifurcation lesions with high risk of SB occlusion. We aim to investigate if intentional strategy is associated with significant reduction of SB occlusion rate compared with conventional strategy in high-risk patients. The Conventional versus Intentional straTegy in patients with high Risk prEdiction of Side branch OccLusion in coronary bifurcation interVEntion (CIT-RESOLVE) is a prospective, randomised, single-blind, multicentre clinical trial comparing the rate of SB occlusion between the intentional strategy group and the conventional strategy group (positive control group) in a consecutive cohort of patients with high risk of side branch occlusion defined by V-RESOLVE score, which is a validated angiographic scoring system to evaluate the risk of SB occlusion in bifurcation intervention and used as one of the inclusion criteria to select patients with high SB occlusion risk (V-RESOLVE score ≥12). A total of 21 hospitals from 10 provinces in China participated in the present study. 566 patients meeting all inclusion/exclusion criteria are randomised to either intentional strategy group or conventional strategy group. The primary endpoint is SB occlusion (defined as any decrease in thrombolysis in myocardial infarction flow grade or absence of flow in SB after main vessel stenting). All patients are followed up for 12-month postdischarge. The protocol has been approved by all local ethics committee. The ethics committee have

  2. Analysis prediction of Indonesian banks (BCA, BNI, MANDIRI) using adaptive neuro-fuzzy inference system (ANFIS) and investment strategies

    Science.gov (United States)

    Trianto, Andriantama Budi; Hadi, I. M.; Liong, The Houw; Purqon, Acep

    2015-09-01

    Indonesian economical development is growing well. It has effect for their invesment in Banks and the stock market. In this study, we perform prediction for the three blue chips of Indonesian bank i.e. BCA, BNI, and MANDIRI by using the method of Adaptive Neuro-Fuzzy Inference System (ANFIS) with Takagi-Sugeno rules and Generalized bell (Gbell) as the membership function. Our results show that ANFIS perform good prediction with RMSE for BCA of 27, BNI of 5.29, and MANDIRI of 13.41, respectively. Furthermore, we develop an active strategy to gain more benefit. We compare between passive strategy versus active strategy. Our results shows that for the passive strategy gains 13 million rupiah, while for the active strategy gains 47 million rupiah in one year. The active investment strategy significantly shows gaining multiple benefit than the passive one.

  3. Prediction of mechanical properties of a warm compacted molybdenum prealloy using artificial neural network and adaptive neuro-fuzzy models

    International Nuclear Information System (INIS)

    Zare, Mansour; Vahdati Khaki, Jalil

    2012-01-01

    Highlights: ► ANNs and ANFIS fairly predicted UTS and YS of warm compacted molybdenum prealloy. ► Effects of composition, temperature, compaction pressure on output were studied. ► ANFIS model was in better agreement with experimental data from published article. ► Sintering temperature had the most significant effect on UTS and YS. -- Abstract: Predictive models using artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) were successfully developed to predict yield strength and ultimate tensile strength of warm compacted 0.85 wt.% molybdenum prealloy samples. To construct these models, 48 different experimental data were gathered from the literature. A portion of the data set was randomly chosen to train both ANN with back propagation (BP) learning algorithm and ANFIS model with Gaussian membership function and the rest was implemented to verify the performance of the trained network against the unseen data. The generalization capability of the networks was also evaluated by applying new input data within the domain covered by the training pattern. To compare the obtained results, coefficient of determination (R 2 ), root mean squared error (RMSE) and average absolute error (AAE) indexes were chosen and calculated for both of the models. The results showed that artificial neural network and adaptive neuro-fuzzy system were both potentially strong for prediction of the mechanical properties of warm compacted 0.85 wt.% molybdenum prealloy; however, the proposed ANFIS showed better performance than the ANN model. Also, the ANFIS model was subjected to a sensitivity analysis to find the significant inputs affecting mechanical properties of the samples.

  4. Adaptive value of phenological traits in stressful environments: predictions based on seed production and laboratory natural selection.

    Directory of Open Access Journals (Sweden)

    Benjamin Brachi

    Full Text Available Phenological traits often show variation within and among natural populations of annual plants. Nevertheless, the adaptive value of post-anthesis traits is seldom tested. In this study, we estimated the adaptive values of pre- and post-anthesis traits in two stressful environments (water stress and interspecific competition, using the selfing annual species Arabidopsis thaliana. By estimating seed production and by performing laboratory natural selection (LNS, we assessed the strength and nature (directional, disruptive and stabilizing of selection acting on phenological traits in A. thaliana under the two tested stress conditions, each with four intensities. Both the type of stress and its intensity affected the strength and nature of selection, as did genetic constraints among phenological traits. Under water stress, both experimental approaches demonstrated directional selection for a shorter life cycle, although bolting time imposes a genetic constraint on the length of the interval between bolting and anthesis. Under interspecific competition, results from the two experimental approaches showed discrepancies. Estimation of seed production predicted directional selection toward early pre-anthesis traits and long post-anthesis periods. In contrast, the LNS approach suggested neutrality for all phenological traits. This study opens questions on adaptation in complex natural environment where many selective pressures act simultaneously.

  5. A New Predictive Model Based on the ABC Optimized Multivariate Adaptive Regression Splines Approach for Predicting the Remaining Useful Life in Aircraft Engines

    Directory of Open Access Journals (Sweden)

    Paulino José García Nieto

    2016-05-01

    Full Text Available Remaining useful life (RUL estimation is considered as one of the most central points in the prognostics and health management (PHM. The present paper describes a nonlinear hybrid ABC–MARS-based model for the prediction of the remaining useful life of aircraft engines. Indeed, it is well-known that an accurate RUL estimation allows failure prevention in a more controllable way so that the effective maintenance can be carried out in appropriate time to correct impending faults. The proposed hybrid model combines multivariate adaptive regression splines (MARS, which have been successfully adopted for regression problems, with the artificial bee colony (ABC technique. This optimization technique involves parameter setting in the MARS training procedure, which significantly influences the regression accuracy. However, its use in reliability applications has not yet been widely explored. Bearing this in mind, remaining useful life values have been predicted here by using the hybrid ABC–MARS-based model from the remaining measured parameters (input variables for aircraft engines with success. A correlation coefficient equal to 0.92 was obtained when this hybrid ABC–MARS-based model was applied to experimental data. The agreement of this model with experimental data confirmed its good performance. The main advantage of this predictive model is that it does not require information about the previous operation states of the aircraft engine.

  6. 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.

  7. Outcome prediction in home- and community-based brain injury rehabilitation using the Mayo-Portland Adaptability Inventory.

    Science.gov (United States)

    Malec, James F; Parrot, Devan; Altman, Irwin M; Swick, Shannon

    2015-01-01

    The objective of the study was to develop statistical formulas to predict levels of community participation on discharge from post-hospital brain injury rehabilitation using retrospective data analysis. Data were collected from seven geographically distinct programmes in a home- and community-based brain injury rehabilitation provider network. Participants were 642 individuals with post-traumatic brain injury. Interventions consisted of home- and community-based brain injury rehabilitation. The main outcome measure was the Mayo-Portland Adaptability Inventory (MPAI-4) Participation Index. Linear discriminant models using admission MPAI-4 Participation Index score and log chronicity correctly predicted excellent (no to minimal participation limitations), very good (very mild participation limitations), good (mild participation limitations), and limited (significant participation limitations) outcome levels at discharge. Predicting broad outcome categories for post-hospital rehabilitation programmes based on admission assessment data appears feasible and valid. Equations to provide patients and families with probability statements on admission about expected levels of outcome are provided. It is unknown to what degree these prediction equations can be reliably applied and valid in other settings.

  8. An Adaptive Model Predictive Load Frequency Control Method for Multi-Area Interconnected Power Systems with Photovoltaic Generations

    Directory of Open Access Journals (Sweden)

    Guo-Qiang Zeng

    2017-11-01

    Full Text Available As the penetration level of renewable distributed generations such as wind turbine generator and photovoltaic stations increases, the load frequency control issue of a multi-area interconnected power system becomes more challenging. This paper presents an adaptive model predictive load frequency control method for a multi-area interconnected power system with photovoltaic generation by considering some nonlinear features such as a dead band for governor and generation rate constraint for steam turbine. The dynamic characteristic of this system is formulated as a discrete-time state space model firstly. Then, the predictive dynamic model is obtained by introducing an expanded state vector, and rolling optimization of control signal is implemented based on a cost function by minimizing the weighted sum of square predicted errors and square future control values. The simulation results on a typical two-area power system consisting of photovoltaic and thermal generator have demonstrated the superiority of the proposed model predictive control method to these state-of-the-art control techniques such as firefly algorithm, genetic algorithm, and population extremal optimization-based proportional-integral control methods in cases of normal conditions, load disturbance and parameters uncertainty.

  9. Machine remaining useful life prediction: An integrated adaptive neuro-fuzzy and high-order particle filtering approach

    Science.gov (United States)

    Chen, Chaochao; Vachtsevanos, George; Orchard, Marcos E.

    2012-04-01

    Machine prognosis can be considered as the generation of long-term predictions that describe the evolution in time of a fault indicator, with the purpose of estimating the remaining useful life (RUL) of a failing component/subsystem so that timely maintenance can be performed to avoid catastrophic failures. This paper proposes an integrated RUL prediction method using adaptive neuro-fuzzy inference systems (ANFIS) and high-order particle filtering, which forecasts the time evolution of the fault indicator and estimates the probability density function (pdf) of RUL. The ANFIS is trained and integrated in a high-order particle filter as a model describing the fault progression. The high-order particle filter is used to estimate the current state and carry out p-step-ahead predictions via a set of particles. These predictions are used to estimate the RUL pdf. The performance of the proposed method is evaluated via the real-world data from a seeded fault test for a UH-60 helicopter planetary gear plate. The results demonstrate that it outperforms both the conventional ANFIS predictor and the particle-filter-based predictor where the fault growth model is a first-order model that is trained via the ANFIS.

  10. Prediction of Tensile Strength of Friction Stir Weld Joints with Adaptive Neuro-Fuzzy Inference System (ANFIS) and Neural Network

    Science.gov (United States)

    Dewan, Mohammad W.; Huggett, Daniel J.; Liao, T. Warren; Wahab, Muhammad A.; Okeil, Ayman M.

    2015-01-01

    Friction-stir-welding (FSW) is a solid-state joining process where joint properties are dependent on welding process parameters. In the current study three critical process parameters including spindle speed (??), plunge force (????), and welding speed (??) are considered key factors in the determination of ultimate tensile strength (UTS) of welded aluminum alloy joints. A total of 73 weld schedules were welded and tensile properties were subsequently obtained experimentally. It is observed that all three process parameters have direct influence on UTS of the welded joints. Utilizing experimental data, an optimized adaptive neuro-fuzzy inference system (ANFIS) model has been developed to predict UTS of FSW joints. A total of 1200 models were developed by varying the number of membership functions (MFs), type of MFs, and combination of four input variables (??,??,????,??????) utilizing a MATLAB platform. Note EFI denotes an empirical force index derived from the three process parameters. For comparison, optimized artificial neural network (ANN) models were also developed to predict UTS from FSW process parameters. By comparing ANFIS and ANN predicted results, it was found that optimized ANFIS models provide better results than ANN. This newly developed best ANFIS model could be utilized for prediction of UTS of FSW joints.

  11. MPC-based energy management with adaptive Markov-chain prediction for a dual-mode hybrid electric vehicle

    Institute of Scientific and Technical Information of China (English)

    XIANG; ChangLe; DING; Feng; WANG; WeiDa; HE; Wei; QI; YunLong

    2017-01-01

    The and energy to management strategy battery is state an important part of a hybrid electrical vehicle design.It is used to improve various fuel economy sustain a proper of charge an by controlling control the power components is while satisfying to constraints and driving demands.However,achieving optimal and performance challenging due the nonlinearities of the hybrid powertrain,conflicting vehicle the time varying constraints,the dilemma capable in which controller control complexity and real-time capability are generally objectives.In this paper,a of real-time cascaded complies strategy is proposed for a dual-mode hybrid electric that considers controller based nonlinearities based the system model and with all time-varying with constraints.sampling The strategy consists of a supervisory controller on a non-linear predictive control short(MPC)sampling a long time with future strategy interval and a coordinating on linear model predictive based control with a time interval to deal different load dynamics of the system.The Additionally,a novel data methodology using adaptive Markov chains to predict demand is introduced.predictive future information is used to improve controller cycles performance.conducted.The The proposed is implemented validity on a real test-bed approach and experimental trials using economy unknown is driving are results other demonstrate the of the proposed and show that fuel significantly improved compared with methods.

  12. MPC-based energy management with adaptive Markov-chain prediction for a dual-mode hybrid electric vehicle

    Institute of Scientific and Technical Information of China (English)

    XIANG ChangLe; DING Feng; WANG WeiDa; HE Wei; QI YunLong

    2017-01-01

    The energy management strategy is an important part of a hybrid electrical vehicle design.It is used to improve fuel economy and to sustain a proper battery state of charge by controlling the power components while satisfying various constraints and driving demands.However,achieving an optimal control performance is challenging due to the nonlinearities of the hybrid powertrain,the time varying constraints,and the dilemma in which controller complexity and real-time capability are generally conflicting objectives.In this paper,a real-time capable cascaded control strategy is proposed for a dual-mode hybrid electric vehicle that considers nonlinearities of the system and complies with all time-varying constraints.The strategy consists of a supervisory controller based on a non-linear model predictive control (MPC) with a long sampling time interval and a coordinating controller based on linear model predictive control with a short sampling time interval to deal with different dynamics of the system.Additionally,a novel data based methodology using adaptive Markov chains to predict future load demand is introduced.The predictive future information is used to improve controller performance.The proposed strategy is implemented on a real test-bed and experimental trials using unknown driving cycles are conducted.The results demonstrate the validity of the proposed approach and show that fuel economy is significantly improved compared with other methods.

  13. Exploiting the Adaptation Dynamics to Predict the Distribution of Beneficial Fitness Effects.

    Directory of Open Access Journals (Sweden)

    Sona John

    Full Text Available Adaptation of asexual populations is driven by beneficial mutations and therefore the dynamics of this process, besides other factors, depends on the distribution of beneficial fitness effects. It is known that on uncorrelated fitness landscapes, this distribution can only be of three types: truncated, exponential and power law. We performed extensive stochastic simulations to study the adaptation dynamics on rugged fitness landscapes, and identified two quantities that can be used to distinguish the underlying distribution of beneficial fitness effects. The first quantity studied here is the fitness difference between successive mutations that spread in the population, which is found to decrease in the case of truncated distributions, remains nearly a constant for exponentially decaying distributions and increases when the fitness distribution decays as a power law. The second quantity of interest, namely, the rate of change of fitness with time also shows quantitatively different behaviour for different beneficial fitness distributions. The patterns displayed by the two aforementioned quantities are found to hold good for both low and high mutation rates. We discuss how these patterns can be exploited to determine the distribution of beneficial fitness effects in microbial experiments.

  14. Adaptive Swarm Balancing Algorithms for rare-event prediction in imbalanced healthcare data

    Science.gov (United States)

    Wong, Raymond K.; Mohammed, Sabah; Fiaidhi, Jinan; Sung, Yunsick

    2017-01-01

    Clinical data analysis and forecasting have made substantial contributions to disease control, prevention and detection. However, such data usually suffer from highly imbalanced samples in class distributions. In this paper, we aim to formulate effective methods to rebalance binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat algorithm, and apply them to empower the effects of synthetic minority over-sampling technique (SMOTE) for pre-processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reported in this paper reveal that the performance improvements obtained by the former methods are not scalable to larger data scales. The latter methods, which we call Adaptive Swarm Balancing Algorithms, lead to significant efficiency and effectiveness improvements on large datasets while the first method is invalid. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. The proposed methods lead to more credible performances of the classifier, and shortening the run time compared to brute-force method. PMID:28753613

  15. Relative codon adaptation: a generic codon bias index for prediction of gene expression.

    Science.gov (United States)

    Fox, Jesse M; Erill, Ivan

    2010-06-01

    The development of codon bias indices (CBIs) remains an active field of research due to their myriad applications in computational biology. Recently, the relative codon usage bias (RCBS) was introduced as a novel CBI able to estimate codon bias without using a reference set. The results of this new index when applied to Escherichia coli and Saccharomyces cerevisiae led the authors of the original publications to conclude that natural selection favours higher expression and enhanced codon usage optimization in short genes. Here, we show that this conclusion was flawed and based on the systematic oversight of an intrinsic bias for short sequences in the RCBS index and of biases in the small data sets used for validation in E. coli. Furthermore, we reveal that how the RCBS can be corrected to produce useful results and how its underlying principle, which we here term relative codon adaptation (RCA), can be made into a powerful reference-set-based index that directly takes into account the genomic base composition. Finally, we show that RCA outperforms the codon adaptation index (CAI) as a predictor of gene expression when operating on the CAI reference set and that this improvement is significantly larger when analysing genomes with high mutational bias.

  16. Prenatal factors contribute to the emergence of kwashiorkor or marasmus in severe undernutrition: evidence for the predictive adaptation model.

    Directory of Open Access Journals (Sweden)

    Terrence E Forrester

    Full Text Available Severe acute malnutrition in childhood manifests as oedematous (kwashiorkor, marasmic kwashiorkor and non-oedematous (marasmus syndromes with very different prognoses. Kwashiorkor differs from marasmus in the patterns of protein, amino acid and lipid metabolism when patients are acutely ill as well as after rehabilitation to ideal weight for height. Metabolic patterns among marasmic patients define them as metabolically thrifty, while kwashiorkor patients function as metabolically profligate. Such differences might underlie syndromic presentation and prognosis. However, no fundamental explanation exists for these differences in metabolism, nor clinical pictures, given similar exposures to undernutrition. We hypothesized that different developmental trajectories underlie these clinical-metabolic phenotypes: if so this would be strong evidence in support of predictive adaptation model of developmental plasticity.We reviewed the records of all children admitted with severe acute malnutrition to the Tropical Metabolism Research Unit Ward of the University Hospital of the West Indies, Kingston, Jamaica during 1962-1992. We used Wellcome criteria to establish the diagnoses of kwashiorkor (n = 391, marasmus (n = 383, and marasmic-kwashiorkor (n = 375. We recorded participants' birth weights, as determined from maternal recall at the time of admission. Those who developed kwashiorkor had 333 g (95% confidence interval 217 to 449, p<0.001 higher mean birthweight than those who developed marasmus.These data are consistent with a model suggesting that plastic mechanisms operative in utero induce potential marasmics to develop with a metabolic physiology more able to adapt to postnatal undernutrition than those of higher birthweight. Given the different mortality risks of these different syndromes, this observation is supportive of the predictive adaptive response hypothesis and is the first empirical demonstration of the advantageous effects of such a

  17. Tracheobronchial Branching Anomalies

    International Nuclear Information System (INIS)

    Hong, Min Ji; Kim, Young Tong; Jou, Sung Shick; Park, A Young

    2010-01-01

    There are various congenital anomalies with respect to the number, length, diameter, and location of tracheobronchial branching patterns. The tracheobronchial anomalies are classified into two groups. The first one, anomalies of division, includes tracheal bronchus, cardiac bronchus, tracheal diverticulum, pulmonary isomerism, and minor variations. The second one, dysmorphic lung, includes lung agenesis-hypoplasia complex and lobar agenesis-aplasia complex

  18. Intermittency in branching models

    International Nuclear Information System (INIS)

    Chiu, C.B.; Texas Univ., Austin; Hwa, R.C.; Oregon Univ., Eugene

    1990-01-01

    The intermittency properties of three branching models have been investigated. The factorial moments show power-law behavior as function of small rapidity width. The slopes and energy dependences reveal different characteristics of the models. The gluon model has the weakest intermittency. (orig.)

  19. State-set branching

    DEFF Research Database (Denmark)

    Jensen, Rune Møller; Veloso, Manuela M.; Bryant, Randal E.

    2008-01-01

    In this article, we present a framework called state-set branching that combines symbolic search based on reduced ordered Binary Decision Diagrams (BDDs) with best-first search, such as A* and greedy best-first search. The framework relies on an extension of these algorithms from expanding a sing...

  20. Tracheobronchial Branching Anomalies

    Energy Technology Data Exchange (ETDEWEB)

    Hong, Min Ji; Kim, Young Tong; Jou, Sung Shick [Soonchunhyang University, Cheonan Hospital, Cheonan (Korea, Republic of); Park, A Young [Soonchunhyang University College of Medicine, Asan (Korea, Republic of)

    2010-04-15

    There are various congenital anomalies with respect to the number, length, diameter, and location of tracheobronchial branching patterns. The tracheobronchial anomalies are classified into two groups. The first one, anomalies of division, includes tracheal bronchus, cardiac bronchus, tracheal diverticulum, pulmonary isomerism, and minor variations. The second one, dysmorphic lung, includes lung agenesis-hypoplasia complex and lobar agenesis-aplasia complex

  1. Tradeoffs Between Branch Mispredictions and Comparisons for Sorting Algorithms

    DEFF Research Database (Denmark)

    Brodal, Gerth Stølting; Moruz, Gabriel

    2005-01-01

    Branch mispredictions is an important factor affecting the running time in practice. In this paper we consider tradeoffs between the number of branch mispredictions and the number of comparisons for sorting algorithms in the comparison model. We prove that a sorting algorithm using O(dnlog n......) comparisons performs Omega(nlogd n) branch mispredictions. We show that Multiway MergeSort achieves this tradeoff by adopting a multiway merger with a low number of branch mispredictions. For adaptive sorting algorithms we similarly obtain that an algorithm performing O(dn(1+log (1+Inv/n))) comparisons must...... perform Omega(nlogd (1+Inv/n)) branch mispredictions, where Inv is the number of inversions in the input. This tradeoff can be achieved by GenericSort by Estivill-Castro and Wood by adopting a multiway division protocol and a multiway merging algorithm with a low number of branch mispredictions....

  2. Predictive analytics on evolving data streams anticipating and adapting to changes in known and unknown contexts

    NARCIS (Netherlands)

    Pechenizkiy, M.

    2015-01-01

    Ever increasing volumes of sensor readings, transactional records, web data and event logs call for next generation of big data mining technology providing effective and efficient tools for making use of the streaming data. Predictive analytics on data streams is actively studied in research

  3. Toward a Smart Car: Hybrid Nonlinear Predictive Controller With Adaptive Horizon

    Czech Academy of Sciences Publication Activity Database

    Pčolka, M.; Žáčeková, E.; Čelikovský, Sergej; Šebek, M.

    (2018), č. článku 08059760. ISSN 1063-6536 R&D Projects: GA ČR(CZ) GA17-04682S Institutional support: RVO:67985556 Keywords : Autonomous vehicles * hybrid systems * nonlinear model predictive control (MPC) * optimization * vehicle control Subject RIV: BC - Control Systems Theory Impact factor: 3.882, year: 2016 http://ieeexplore.ieee.org/document/8059760/

  4. Adapting the Water Erosion Prediction Project (WEPP) model for forest applications

    Science.gov (United States)

    Shuhui Dun; Joan Q. Wu; William J. Elliot; Peter R. Robichaud; Dennis C. Flanagan; James R. Frankenberger; Robert E. Brown; Arthur C. Xu

    2009-01-01

    There has been an increasing public concern over forest stream pollution by excessive sedimentation due to natural or human disturbances. Adequate erosion simulation tools are needed for sound management of forest resources. The Water Erosion Prediction Project (WEPP) watershed model has proved useful in forest applications where Hortonian flow is the major form of...

  5. Results of Instrument Observations and Adaptive Prediction of Thermoabrasion of Banks of the Vilyui Reservoir

    International Nuclear Information System (INIS)

    Velikin, S. A.; Sobol’, I. S.; Sobol’, S. V.; Khokhlov, D. N.

    2013-01-01

    Quantitative data derived from observations of reformation of the thermoabrasive banks of the Viliyui Reservoir in Yakutia during the service period from 1972 through 2011, and results of analytical prediction of bank formations over the next 20 years for purposes of monitoring the ecological safety of this water body are presented

  6. Results of Instrument Observations and Adaptive Prediction of Thermoabrasion of Banks of the Vilyui Reservoir

    Energy Technology Data Exchange (ETDEWEB)

    Velikin, S. A. [Vilyuisk Permafrost Scientific-Research Station, Institute of Permafrost Science, Siberian Division of the Russian Academy of Sciences (Russian Federation); Sobol' , I. S.; Sobol' , S. V.; Khokhlov, D. N. [Nizhnii Novgorod State Architectural and Civil-Engineering University (Russian Federation)

    2013-11-15

    Quantitative data derived from observations of reformation of the thermoabrasive banks of the Viliyui Reservoir in Yakutia during the service period from 1972 through 2011, and results of analytical prediction of bank formations over the next 20 years for purposes of monitoring the ecological safety of this water body are presented.

  7. Development of a Skin Burn Predictive Model adapted to Laser Irradiation

    Science.gov (United States)

    Sonneck-Museux, N.; Scheer, E.; Perez, L.; Agay, D.; Autrique, L.

    2016-12-01

    Laser technology is increasingly used, and it is crucial for both safety and medical reasons that the impact of laser irradiation on human skin can be accurately predicted. This study is mainly focused on laser-skin interactions and potential lesions (burns). A mathematical model dedicated to heat transfers in skin exposed to infrared laser radiations has been developed. The model is validated by studying heat transfers in human skin and simultaneously performing experimentations an animal model (pig). For all experimental tests, pig's skin surface temperature is recorded. Three laser wavelengths have been tested: 808 nm, 1940 nm and 10 600 nm. The first is a diode laser producing radiation absorbed deep within the skin. The second wavelength has a more superficial effect. For the third wavelength, skin is an opaque material. The validity of the developed models is verified by comparison with experimental results (in vivo tests) and the results of previous studies reported in the literature. The comparison shows that the models accurately predict the burn degree caused by laser radiation over a wide range of conditions. The results show that the important parameter for burn prediction is the extinction coefficient. For the 1940 nm wavelength especially, significant differences between modeling results and literature have been observed, mainly due to this coefficient's value. This new model can be used as a predictive tool in order to estimate the amount of injury induced by several types (couple power-time) of laser aggressions on the arm, the face and on the palm of the hand.

  8. Stock returns predictability and the adaptive market hypothesis in emerging markets: evidence from India.

    Science.gov (United States)

    Hiremath, Gourishankar S; Kumari, Jyoti

    2014-01-01

    This study addresses the question of whether the adaptive market hypothesis provides a better description of the behaviour of emerging stock market like India. We employed linear and nonlinear methods to evaluate the hypothesis empirically. The linear tests show a cyclical pattern in linear dependence suggesting that the Indian stock market switched between periods of efficiency and inefficiency. In contrast, the results from nonlinear tests reveal a strong evidence of nonlinearity in returns throughout the sample period with a sign of tapering magnitude of nonlinear dependence in the recent period. The findings suggest that Indian stock market is moving towards efficiency. The results provide additional insights on association between financial crises, foreign portfolio investments and inefficiency. G14; G12; C12.

  9. Phenotypic plasticity as an adaptive response to predictable and unpredictable environmental changes

    DEFF Research Database (Denmark)

    Manenti, Tommaso

    Phenotypic plasticity is the ability of a genotype to modify its phenotype in response to environmental changes as a consequence of an interaction between genes and environment (Bradshaw, 1965). Plasticity contributes to the vast phenotypic variation observed in natural populations. Many examples...... of a plastic response are expected to depend on the environmental conditions experienced by organisms. Thus, in populations exposed to a non-changing environment, the plastic machinery might be a waste of resources. Contrary, in populations experiencing varying environmental conditions, plasticity is expected...... such as anti-predator behaviours or the activation of mechanisms to prevent thermal stress injuries suggest that plasticity is an adaptive response, favoured by natural selection. At the same time, organisms do show limited plastic responses, indicating that this ability is not for free. Costs and benefits...

  10. A longitudinal examination of the Adaptation to Poverty-Related Stress Model: predicting child and adolescent adjustment over time.

    Science.gov (United States)

    Wadsworth, Martha E; Rindlaub, Laura; Hurwich-Reiss, Eliana; Rienks, Shauna; Bianco, Hannah; Markman, Howard J

    2013-01-01

    This study tests key tenets of the Adaptation to Poverty-related Stress Model. This model (Wadsworth, Raviv, Santiago, & Etter, 2011 ) builds on Conger and Elder's family stress model by proposing that primary control coping and secondary control coping can help reduce the negative effects of economic strain on parental behaviors central to the family stress model, namely, parental depressive symptoms and parent-child interactions, which together can decrease child internalizing and externalizing problems. Two hundred seventy-five co-parenting couples with children between the ages of 1 and 18 participated in an evaluation of a brief family strengthening intervention, aimed at preventing economic strain's negative cascade of influence on parents, and ultimately their children. The longitudinal path model, analyzed at the couple dyad level with mothers and fathers nested within couple, showed very good fit, and was not moderated by child gender or ethnicity. Analyses revealed direct positive effects of primary control coping and secondary control coping on mothers' and fathers' depressive symptoms. Decreased economic strain predicted more positive father-child interactions, whereas increased secondary control coping predicted less negative mother-child interactions. Positive parent-child interactions, along with decreased parent depression and economic strain, predicted child internalizing and externalizing over the course of 18 months. Multiple-group models analyzed separately by parent gender revealed, however, that child age moderated father effects. Findings provide support for the adaptation to poverty-related stress model and suggest that prevention and clinical interventions for families affected by poverty-related stress may be strengthened by including modules that address economic strain and efficacious strategies for coping with strain.

  11. An approximation to the adaptive exponential integrate-and-fire neuron model allows fast and predictive fitting to physiological data

    Directory of Open Access Journals (Sweden)

    Loreen eHertäg

    2012-09-01

    Full Text Available For large-scale network simulations, it is often desirable to have computationally tractable, yet in a defined sense still physiologically valid neuron models. In particular, these models should be able to reproduce physiological measurements, ideally in a predictive sense, and under different input regimes in which neurons may operate in vivo. Here we present an approach to parameter estimation for a simple spiking neuron model mainly based on standard f-I curves obtained from in vitro recordings. Such recordings are routinely obtained in standard protocols and assess a neuron's response under a wide range of mean input currents. Our fitting procedure makes use of closed-form expressions for the firing rate derived from an approximation to the adaptive exponential integrate-and-fire (AdEx model. The resulting fitting process is simple and about two orders of magnitude faster compared to methods based on numerical integration of the differential equations. We probe this method on different cell types recorded from rodent prefrontal cortex. After fitting to the f-I current-clamp data, the model cells are tested on completely different sets of recordings obtained by fluctuating ('in-vivo-like' input currents. For a wide range of different input regimes, cell types, and cortical layers, the model could predict spike times on these test traces quite accurately within the bounds of physiological reliability, although no information from these distinct test sets was used for model fitting. Further analyses delineated some of the empirical factors constraining model fitting and the model's generalization performance. An even simpler adaptive LIF neuron was also examined in this context. Hence, we have developed a 'high-throughput' model fitting procedure which is simple and fast, with good prediction performance, and which relies only on firing rate information and standard physiological data widely and easily available.

  12. Bridging the gap between the linear and nonlinear predictive control: Adaptations fo refficient building climate control

    Czech Academy of Sciences Publication Activity Database

    Pčolka, M.; Žáčeková, E.; Robinett, R.; Čelikovský, Sergej; Šebek, M.

    2016-01-01

    Roč. 53, č. 1 (2016), s. 124-138 ISSN 0967-0661 R&D Projects: GA ČR GA13-20433S Institutional support: RVO:67985556 Keywords : Model predictive control * Identification for control * Building climatecontrol Subject RIV: BC - Control Systems Theory Impact factor: 2.602, year: 2016 http://library.utia.cas.cz/separaty/2016/TR/celikovsky-0460306.pdf

  13. A fast linear predictive adaptive model of packed bed coupled with UASB reactor treating onion waste to produce biofuel.

    Science.gov (United States)

    Milquez-Sanabria, Harvey; Blanco-Cocom, Luis; Alzate-Gaviria, Liliana

    2016-10-03

    Agro-industrial wastes are an energy source for different industries. However, its application has not reached small industries. Previous and current research activities performed on the acidogenic phase of two-phase anaerobic digestion processes deal particularly with process optimization of the acid-phase reactors operating with a wide variety of substrates, both soluble and complex in nature. Mathematical models for anaerobic digestion have been developed to understand and improve the efficient operation of the process. At present, lineal models with the advantages of requiring less data, predicting future behavior and updating when a new set of data becomes available have been developed. The aim of this research was to contribute to the reduction of organic solid waste, generate biogas and develop a simple but accurate mathematical model to predict the behavior of the UASB reactor. The system was maintained separate for 14 days during which hydrolytic and acetogenic bacteria broke down onion waste, produced and accumulated volatile fatty acids. On this day, two reactors were coupled and the system continued for 16 days more. The biogas and methane yields and volatile solid reduction were 0.6 ± 0.05 m 3 (kg VS removed ) -1 , 0.43 ± 0.06 m 3 (kg VS removed ) -1 and 83.5 ± 9.8 %, respectively. The model application showed a good prediction of all process parameters defined; maximum error between experimental and predicted value was 1.84 % for alkalinity profile. A linear predictive adaptive model for anaerobic digestion of onion waste in a two-stage process was determined under batch-fed condition. Organic load rate (OLR) was maintained constant for the entire operation, modifying effluent hydrolysis reactor feed to UASB reactor. This condition avoids intoxication of UASB reactor and also limits external buffer addition.

  14. An adaptive two-stage analog/regression model for probabilistic prediction of small-scale precipitation in France

    Directory of Open Access Journals (Sweden)

    J. Chardon

    2018-01-01

    Full Text Available Statistical downscaling models (SDMs are often used to produce local weather scenarios from large-scale atmospheric information. SDMs include transfer functions which are based on a statistical link identified from observations between local weather and a set of large-scale predictors. As physical processes driving surface weather vary in time, the most relevant predictors and the regression link are likely to vary in time too. This is well known for precipitation for instance and the link is thus often estimated after some seasonal stratification of the data. In this study, we present a two-stage analog/regression model where the regression link is estimated from atmospheric analogs of the current prediction day. Atmospheric analogs are identified from fields of geopotential heights at 1000 and 500 hPa. For the regression stage, two generalized linear models are further used to model the probability of precipitation occurrence and the distribution of non-zero precipitation amounts, respectively. The two-stage model is evaluated for the probabilistic prediction of small-scale precipitation over France. It noticeably improves the skill of the prediction for both precipitation occurrence and amount. As the analog days vary from one prediction day to another, the atmospheric predictors selected in the regression stage and the value of the corresponding regression coefficients can vary from one prediction day to another. The model allows thus for a day-to-day adaptive and tailored downscaling. It can also reveal specific predictors for peculiar and non-frequent weather configurations.

  15. Statistical learning methods for aero-optic wavefront prediction and adaptive-optic latency compensation

    Science.gov (United States)

    Burns, W. Robert

    Since the early 1970's research in airborne laser systems has been the subject of continued interest. Airborne laser applications depend on being able to propagate a near diffraction-limited laser beam from an airborne platform. Turbulent air flowing over the aircraft produces density fluctuations through which the beam must propagate. Because the index of refraction of the air is directly related to the density, the turbulent flow imposes aberrations on the beam passing through it. This problem is referred to as Aero-Optics. Aero-Optics is recognized as a major technical issue that needs to be solved before airborne optical systems can become routinely fielded. This dissertation research specifically addresses an approach to mitigating the deleterious effects imposed on an airborne optical system by aero-optics. A promising technology is adaptive optics: a feedback control method that measures optical aberrations and imprints the conjugate aberrations onto an outgoing beam. The challenge is that it is a computationally-difficult problem, since aero-optic disturbances are on the order of kilohertz for practical applications. High control loop frequencies and high disturbance frequencies mean that adaptive-optic systems are sensitive to latency in sensors, mirrors, amplifiers, and computation. These latencies build up to result in a dramatic reduction in the system's effective bandwidth. This work presents two variations of an algorithm that uses model reduction and data-driven predictors to estimate the evolution of measured wavefronts over a short temporal horizon and thus compensate for feedback latency. The efficacy of the two methods are compared in this research, and evaluated against similar algorithms that have been previously developed. The best version achieved over 75% disturbance rejection in simulation in the most optically active flow region in the wake of a turret, considerably outperforming conventional approaches. The algorithm is shown to be

  16. Prediction of radical scavenging activities of anthocyanins applying adaptive neuro-fuzzy inference system (ANFIS) with quantum chemical descriptors.

    Science.gov (United States)

    Jhin, Changho; Hwang, Keum Taek

    2014-08-22

    Radical scavenging activity of anthocyanins is well known, but only a few studies have been conducted by quantum chemical approach. The adaptive neuro-fuzzy inference system (ANFIS) is an effective technique for solving problems with uncertainty. The purpose of this study was to construct and evaluate quantitative structure-activity relationship (QSAR) models for predicting radical scavenging activities of anthocyanins with good prediction efficiency. ANFIS-applied QSAR models were developed by using quantum chemical descriptors of anthocyanins calculated by semi-empirical PM6 and PM7 methods. Electron affinity (A) and electronegativity (χ) of flavylium cation, and ionization potential (I) of quinoidal base were significantly correlated with radical scavenging activities of anthocyanins. These descriptors were used as independent variables for QSAR models. ANFIS models with two triangular-shaped input fuzzy functions for each independent variable were constructed and optimized by 100 learning epochs. The constructed models using descriptors calculated by both PM6 and PM7 had good prediction efficiency with Q-square of 0.82 and 0.86, respectively.

  17. Prediction of Radical Scavenging Activities of Anthocyanins Applying Adaptive Neuro-Fuzzy Inference System (ANFIS with Quantum Chemical Descriptors

    Directory of Open Access Journals (Sweden)

    Changho Jhin

    2014-08-01

    Full Text Available Radical scavenging activity of anthocyanins is well known, but only a few studies have been conducted by quantum chemical approach. The adaptive neuro-fuzzy inference system (ANFIS is an effective technique for solving problems with uncertainty. The purpose of this study was to construct and evaluate quantitative structure-activity relationship (QSAR models for predicting radical scavenging activities of anthocyanins with good prediction efficiency. ANFIS-applied QSAR models were developed by using quantum chemical descriptors of anthocyanins calculated by semi-empirical PM6 and PM7 methods. Electron affinity (A and electronegativity (χ of flavylium cation, and ionization potential (I of quinoidal base were significantly correlated with radical scavenging activities of anthocyanins. These descriptors were used as independent variables for QSAR models. ANFIS models with two triangular-shaped input fuzzy functions for each independent variable were constructed and optimized by 100 learning epochs. The constructed models using descriptors calculated by both PM6 and PM7 had good prediction efficiency with Q-square of 0.82 and 0.86, respectively.

  18. Neural-Fuzzy Digital Strategy of Continuous-Time Nonlinear Systems Using Adaptive Prediction and Random-Local-Optimization Design

    Directory of Open Access Journals (Sweden)

    Zhi-Ren Tsai

    2013-01-01

    Full Text Available A tracking problem, time-delay, uncertainty and stability analysis of a predictive control system are considered. The predictive control design is based on the input and output of neural plant model (NPM, and a recursive fuzzy predictive tracker has scaling factors which limit the value zone of measured data and cause the tuned parameters to converge to obtain a robust control performance. To improve the further control performance, the proposed random-local-optimization design (RLO for a model/controller uses offline initialization to obtain a near global optimal model/controller. Other issues are the considerations of modeling error, input-delay, sampling distortion, cost, greater flexibility, and highly reliable digital products of the model-based controller for the continuous-time (CT nonlinear system. They are solved by a recommended two-stage control design with the first-stage (offline RLO and second-stage (online adaptive steps. A theorizing method is then put forward to replace the sensitivity calculation, which reduces the calculation of Jacobin matrices of the back-propagation (BP method. Finally, the feedforward input of reference signals helps the digital fuzzy controller improve the control performance, and the technique works to control the CT systems precisely.

  19. Adaptive Encoding of Outcome Prediction by Prefrontal Cortex Ensembles Supports Behavioral Flexibility.

    Science.gov (United States)

    Del Arco, Alberto; Park, Junchol; Wood, Jesse; Kim, Yunbok; Moghaddam, Bita

    2017-08-30

    The prefrontal cortex (PFC) is thought to play a critical role in behavioral flexibility by monitoring action-outcome contingencies. How PFC ensembles represent shifts in behavior in response to changes in these contingencies remains unclear. We recorded single-unit activity and local field potentials in the dorsomedial PFC (dmPFC) of male rats during a set-shifting task that required them to update their behavior, among competing options, in response to changes in action-outcome contingencies. As behavior was updated, a subset of PFC ensembles encoded the current trial outcome before the outcome was presented. This novel outcome-prediction encoding was absent in a control task, in which actions were rewarded pseudorandomly, indicating that PFC neurons are not merely providing an expectancy signal. In both control and set-shifting tasks, dmPFC neurons displayed postoutcome discrimination activity, indicating that these neurons also monitor whether a behavior is successful in generating rewards. Gamma-power oscillatory activity increased before the outcome in both tasks but did not differentiate between expected outcomes, suggesting that this measure is not related to set-shifting behavior but reflects expectation of an outcome after action execution. These results demonstrate that PFC neurons support flexible rule-based action selection by predicting outcomes that follow a particular action. SIGNIFICANCE STATEMENT Tracking action-outcome contingencies and modifying behavior when those contingencies change is critical to behavioral flexibility. We find that ensembles of dorsomedial prefrontal cortex neurons differentiate between expected outcomes when action-outcome contingencies change. This predictive mode of signaling may be used to promote a new response strategy at the service of behavioral flexibility. Copyright © 2017 the authors 0270-6474/17/378363-11$15.00/0.

  20. Predicting knee cartilage loss using adaptive partitioning of cartilage thickness maps

    DEFF Research Database (Denmark)

    Jørgensen, Dan Richter; Dam, Erik Bjørnager; Lillholm, Martin

    2013-01-01

    This study investigates whether measures of knee cartilage thickness can predict future loss of knee cartilage. A slow and a rapid progressor group was determined using longitudinal data, and anatomically aligned cartilage thickness maps were extracted from MRI at baseline. A novel machine learning...... framework was then trained using these maps. Compared to measures of mean cartilage plate thickness, group separation was increased by focusing on local cartilage differences. This result is central for clinical trials where inclusion of rapid progressors may help reduce the period needed to study effects...

  1. Climate Change Effects on Agricultural Production of Iran: II. Predicting Productivity of Field Crops and Adaptation Strategies

    Directory of Open Access Journals (Sweden)

    A Koocheki

    2016-07-01

    Full Text Available Introduction Recent evidences confirm that during the next few decades, many agroclimatic indices of Iran would be affected by global climate change. Koocheki et al. using two General Circulation Models showed that the mean annual temperature of the country will increase between 3.5-4.5°C while mean precipitation will reduce by 7-15% to 2050. It is well established that crop growth and development would drastically affect by the future global warming and its consequences because yield determining processes such as photosynthesis and crop phenology are directly related to temperature. On the other hands, the combined effects of CO2 enrichment and temperature rise on crop growth are complicated and should be studied using crop simulation models. Furthermore, adapting to climatic variability will have a substantially greater effect in reducing impacts than willing mitigation. However, such impacts on crop productivity at national scale and adaptive measures for future conditions are rarely studied in Iran. In this research crop development and yield of wheat, corn, chickpea and sugar beet were simulated for the target year of 2050 and the results are compared with the current yield as the baseline. Materials and Methods Future climatic variables were predicted using A1f (business as usual scenario by GFDL general circulation model and the results were used as weather inputs in the SUCROS model which was previously validated against measured data of the four crops. To account for the effect of CO2 enrichment on crop growth the photosynthesis routine of the model was adopted for increased CO2 concentration using a scaling factor. Changes in developmental stages of each crop were estimated for the future conditions and the relation between duration of these stages and yield was determined. Predicted crop yields for the year 2050 were compared with the current potential yields considering some adaptation strategies. Results and Discussion Results

  2. Right bundle branch block

    DEFF Research Database (Denmark)

    Bussink, Barbara E; Holst, Anders Gaarsdal; Jespersen, Lasse

    2013-01-01

    AimsTo determine the prevalence, predictors of newly acquired, and the prognostic value of right bundle branch block (RBBB) and incomplete RBBB (IRBBB) on a resting 12-lead electrocardiogram in men and women from the general population.Methods and resultsWe followed 18 441 participants included...... in the Copenhagen City Heart Study examined in 1976-2003 free from previous myocardial infarction (MI), chronic heart failure, and left bundle branch block through registry linkage until 2009 for all-cause mortality and cardiovascular outcomes. The prevalence of RBBB/IRBBB was higher in men (1.4%/4.7% in men vs. 0.......5%/2.3% in women, P block was associated with significantly...

  3. RETRACTED: Adaptive neuro-fuzzy prediction of modulation transfer function of optical lens system

    Science.gov (United States)

    Petković, Dalibor; Shamshirband, Shahaboddin; Anuar, Nor Badrul; Md Nasir, Mohd Hairul Nizam; Pavlović, Nenad T.; Akib, Shatirah

    2014-07-01

    This article has been retracted: please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy). This article has been retracted at the request of the Editor. Sections ;1. Introduction; and ;2. Modulation transfer function;, as well as Figures 1-3, plagiarize the article published by N. Gül and M. Efe in Turk J Elec Eng & Comp Sci 18 (2010) 71 (http://journals.tubitak.gov.tr/elektrik/issues/elk-10-18-1/elk-18-1-6-0811-9.pdf). Sections ;4. Adaptive neuro-fuzzy inference system; and ;6. Conclusion; duplicate parts of the articles previously published by the corresponding author et al in ;Expert Systems with Applications; 39 (2012) 13295-13304, http://dx.doi.org/10.1016/j.eswa.2012.05.072 and ;Expert Systems with Applications; 40 (2013) 281-286, http://dx.doi.org/10.1016/j.eswa.2012.07.076. One of the conditions of submission of a paper for publication is that authors declare explicitly that the paper is not under consideration for publication elsewhere. Re-use of any data should be appropriately cited. As such this article represents an abuse of the scientific publishing system. The scientific community takes a very strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission process.

  4. Performance and Adaptive Surge-Preventing Acceleration Prediction of a Turboshaft Engine under Inlet Flow Distortion

    Directory of Open Access Journals (Sweden)

    Cao Dalu

    2017-01-01

    Full Text Available The intention of this paper is to research the inlet flow distortion influence on overall performance of turboshaft engine and put forward a method called Distortion Factor Item (DFI to improve the fuel supply plan for surge-preventing acceleration when turboshaft engine suddenly encounters inlet flow distortion. Based on the parallel compressor theory, steady-state and transition-state numerical simulation model of turboshaft engine with sub-compressor model were established for researching the influence of inlet flow distortion on turboshaft engine. This paper made a detailed analysis on the compressor operation from the aspects of performance and stability, and then analyzed the overall performance and dynamic response of the whole engine under inlet flow distortion. Improved fuel supply plan with DFI method was applied to control the acceleration process adaptively when encountering different inlet flow distortion. Several simulation examples about extreme natural environments were calculated to testify DFI method’s environmental applicability. The result shows that the inlet flow distortion reduces the air inflow and decreases the surge margin of compressor, and increase the engine exhaust loss. Encountering inlet flow distortion has many adverse influences such as sudden rotor acceleration, turbine inlet temperature rise and power output reduction. By using improved fuel supply plan with DFI, turboshaft engine above-idle acceleration can avoid surge effectively under inlet flow distortion with environmental applicability.

  5. Adaptive Resource Utilization Prediction System for Infrastructure as a Service Cloud

    Directory of Open Access Journals (Sweden)

    Qazi Zia Ullah

    2017-01-01

    Full Text Available Infrastructure as a Service (IaaS cloud provides resources as a service from a pool of compute, network, and storage resources. Cloud providers can manage their resource usage by knowing future usage demand from the current and past usage patterns of resources. Resource usage prediction is of great importance for dynamic scaling of cloud resources to achieve efficiency in terms of cost and energy consumption while keeping quality of service. The purpose of this paper is to present a real-time resource usage prediction system. The system takes real-time utilization of resources and feeds utilization values into several buffers based on the type of resources and time span size. Buffers are read by R language based statistical system. These buffers’ data are checked to determine whether their data follows Gaussian distribution or not. In case of following Gaussian distribution, Autoregressive Integrated Moving Average (ARIMA is applied; otherwise Autoregressive Neural Network (AR-NN is applied. In ARIMA process, a model is selected based on minimum Akaike Information Criterion (AIC values. Similarly, in AR-NN process, a network with the lowest Network Information Criterion (NIC value is selected. We have evaluated our system with real traces of CPU utilization of an IaaS cloud of one hundred and twenty servers.

  6. Adaptation, plasticity, and extinction in a changing environment: towards a predictive theory.

    Directory of Open Access Journals (Sweden)

    Luis-Miguel Chevin

    2010-04-01

    Full Text Available Many species are experiencing sustained environmental change mainly due to human activities. The unusual rate and extent of anthropogenic alterations of the environment may exceed the capacity of developmental, genetic, and demographic mechanisms that populations have evolved to deal with environmental change. To begin to understand the limits to population persistence, we present a simple evolutionary model for the critical rate of environmental change beyond which a population must decline and go extinct. We use this model to highlight the major determinants of extinction risk in a changing environment, and identify research needs for improved predictions based on projected changes in environmental variables. Two key parameters relating the environment to population biology have not yet received sufficient attention. Phenotypic plasticity, the direct influence of environment on the development of individual phenotypes, is increasingly considered an important component of phenotypic change in the wild and should be incorporated in models of population persistence. Environmental sensitivity of selection, the change in the optimum phenotype with the environment, still crucially needs empirical assessment. We use environmental tolerance curves and other examples of ecological and evolutionary responses to climate change to illustrate how these mechanistic approaches can be developed for predictive purposes.

  7. Adaptive compressive learning for prediction of protein-protein interactions from primary sequence.

    Science.gov (United States)

    Zhang, Ya-Nan; Pan, Xiao-Yong; Huang, Yan; Shen, Hong-Bin

    2011-08-21

    Protein-protein interactions (PPIs) play an important role in biological processes. Although much effort has been devoted to the identification of novel PPIs by integrating experimental biological knowledge, there are still many difficulties because of lacking enough protein structural and functional information. It is highly desired to develop methods based only on amino acid sequences for predicting PPIs. However, sequence-based predictors are often struggling with the high-dimensionality causing over-fitting and high computational complexity problems, as well as the redundancy of sequential feature vectors. In this paper, a novel computational approach based on compressed sensing theory is proposed to predict yeast Saccharomyces cerevisiae PPIs from primary sequence and has achieved promising results. The key advantage of the proposed compressed sensing algorithm is that it can compress the original high-dimensional protein sequential feature vector into a much lower but more condensed space taking the sparsity property of the original signal into account. What makes compressed sensing much more attractive in protein sequence analysis is its compressed signal can be reconstructed from far fewer measurements than what is usually considered necessary in traditional Nyquist sampling theory. Experimental results demonstrate that proposed compressed sensing method is powerful for analyzing noisy biological data and reducing redundancy in feature vectors. The proposed method represents a new strategy of dealing with high-dimensional protein discrete model and has great potentiality to be extended to deal with many other complicated biological systems. Copyright © 2011 Elsevier Ltd. All rights reserved.

  8. Generalized Markov branching models

    OpenAIRE

    Li, Junping

    2005-01-01

    In this thesis, we first considered a modified Markov branching process incorporating both state-independent immigration and resurrection. After establishing the criteria for regularity and uniqueness, explicit expressions for the extinction probability and mean extinction time are presented. The criteria for recurrence and ergodicity are also established. In addition, an explicit expression for the equilibrium distribution is presented.\\ud \\ud We then moved on to investigate the basic proper...

  9. Tau leptonic branching ratios

    CERN Document Server

    Buskulic, Damir; De Bonis, I; Décamp, D; Ghez, P; Goy, C; Lees, J P; Lucotte, A; Minard, M N; Odier, P; Pietrzyk, B; Ariztizabal, F; Chmeissani, M; Crespo, J M; Efthymiopoulos, I; Fernández, E; Fernández-Bosman, M; Gaitan, V; Garrido, L; Martínez, M; Orteu, S; Pacheco, A; Padilla, C; Palla, Fabrizio; Pascual, A; Perlas, J A; Sánchez, F; Teubert, F; Colaleo, A; Creanza, D; De Palma, M; Farilla, A; Gelao, G; Girone, M; Iaselli, Giuseppe; Maggi, G; Maggi, M; Marinelli, N; Natali, S; Nuzzo, S; Ranieri, A; Raso, G; Romano, F; Ruggieri, F; Selvaggi, G; Silvestris, L; Tempesta, P; Zito, G; Huang, X; Lin, J; Ouyang, Q; Wang, T; Xie, Y; Xu, R; Xue, S; Zhang, J; Zhang, L; Zhao, W; Bonvicini, G; Cattaneo, M; Comas, P; Coyle, P; Drevermann, H; Engelhardt, A; Forty, Roger W; Frank, M; Hagelberg, R; Harvey, J; Jacobsen, R; Janot, P; Jost, B; Kneringer, E; Knobloch, J; Lehraus, Ivan; Markou, C; Martin, E B; Mato, P; Minten, Adolf G; Miquel, R; Oest, T; Palazzi, P; Pater, J R; Pusztaszeri, J F; Ranjard, F; Rensing, P E; Rolandi, Luigi; Schlatter, W D; Schmelling, M; Schneider, O; Tejessy, W; Tomalin, I R; Venturi, A; Wachsmuth, H W; Wiedenmann, W; Wildish, T; Witzeling, W; Wotschack, J; Ajaltouni, Ziad J; Bardadin-Otwinowska, Maria; Barrès, A; Boyer, C; Falvard, A; Gay, P; Guicheney, C; Henrard, P; Jousset, J; Michel, B; Monteil, S; Montret, J C; Pallin, D; Perret, P; Podlyski, F; Proriol, J; Rossignol, J M; Saadi, F; Fearnley, Tom; Hansen, J B; Hansen, J D; Hansen, J R; Hansen, P H; Nilsson, B S; Kyriakis, A; Simopoulou, Errietta; Siotis, I; Vayaki, Anna; Zachariadou, K; Blondel, A; Bonneaud, G R; Brient, J C; Bourdon, P; Passalacqua, L; Rougé, A; Rumpf, M; Tanaka, R; Valassi, Andrea; Verderi, M; Videau, H L; Candlin, D J; Parsons, M I; Focardi, E; Parrini, G; Corden, M; Delfino, M C; Georgiopoulos, C H; Jaffe, D E; Antonelli, A; Bencivenni, G; Bologna, G; Bossi, F; Campana, P; Capon, G; Chiarella, V; Felici, G; Laurelli, P; Mannocchi, G; Murtas, F; Murtas, G P; Pepé-Altarelli, M; Dorris, S J; Halley, A W; ten Have, I; Knowles, I G; Lynch, J G; Morton, W T; O'Shea, V; Raine, C; Reeves, P; Scarr, J M; Smith, K; Smith, M G; Thompson, A S; Thomson, F; Thorn, S; Turnbull, R M; Becker, U; Braun, O; Geweniger, C; Graefe, G; Hanke, P; Hepp, V; Kluge, E E; Putzer, A; Rensch, B; Schmidt, M; Sommer, J; Stenzel, H; Tittel, K; Werner, S; Wunsch, M; Beuselinck, R; Binnie, David M; Cameron, W; Colling, D J; Dornan, Peter J; Konstantinidis, N P; Moneta, L; Moutoussi, A; Nash, J; San Martin, G; Sedgbeer, J K; Stacey, A M; Dissertori, G; Girtler, P; Kuhn, D; Rudolph, G; Bowdery, C K; Brodbeck, T J; Colrain, P; Crawford, G; Finch, A J; Foster, F; Hughes, G; Sloan, Terence; Whelan, E P; Williams, M I; Galla, A; Greene, A M; Kleinknecht, K; Quast, G; Raab, J; Renk, B; Sander, H G; Wanke, R; Van Gemmeren, P; Zeitnitz, C; Aubert, Jean-Jacques; Bencheikh, A M; Benchouk, C; Bonissent, A; Bujosa, G; Calvet, D; Carr, J; Diaconu, C A; Etienne, F; Thulasidas, M; Nicod, D; Payre, P; Rousseau, D; Talby, M; Abt, I; Assmann, R W; Bauer, C; Blum, Walter; Brown, D; Dietl, H; Dydak, Friedrich; Ganis, G; Gotzhein, C; Jakobs, K; Kroha, H; Lütjens, G; Lutz, Gerhard; Männer, W; Moser, H G; Richter, R H; Rosado-Schlosser, A; Schael, S; Settles, Ronald; Seywerd, H C J; Saint-Denis, R; Wolf, G; Alemany, R; Boucrot, J; Callot, O; Cordier, A; Courault, F; Davier, M; Duflot, L; Grivaz, J F; Heusse, P; Jacquet, M; Kim, D W; Le Diberder, F R; Lefrançois, J; Lutz, A M; Musolino, G; Nikolic, I A; Park, H J; Park, I C; Schune, M H; Simion, S; Veillet, J J; Videau, I; Abbaneo, D; Azzurri, P; Bagliesi, G; Batignani, G; Bettarini, S; Bozzi, C; Calderini, G; Carpinelli, M; Ciocci, M A; Ciulli, V; Dell'Orso, R; Fantechi, R; Ferrante, I; Foà, L; Forti, F; Giassi, A; Giorgi, M A; Gregorio, A; Ligabue, F; Lusiani, A; Marrocchesi, P S; Messineo, A; Rizzo, G; Sanguinetti, G; Sciabà, A; Spagnolo, P; Steinberger, Jack; Tenchini, Roberto; Tonelli, G; Triggiani, G; Vannini, C; Verdini, P G; Walsh, J; Betteridge, A P; Blair, G A; Bryant, L M; Cerutti, F; Gao, Y; Green, M G; Johnson, D L; Medcalf, T; Mir, L M; Perrodo, P; Strong, J A; Bertin, V; Botterill, David R; Clifft, R W; Edgecock, T R; Haywood, S; Edwards, M; Maley, P; Norton, P R; Thompson, J C; Bloch-Devaux, B; Colas, P; Emery, S; Kozanecki, Witold; Lançon, E; Lemaire, M C; Locci, E; Marx, B; Pérez, P; Rander, J; Renardy, J F; Roussarie, A; Schuller, J P; Schwindling, J; Trabelsi, A; Vallage, B; Johnson, R P; Kim, H Y; Litke, A M; McNeil, M A; Taylor, G; Beddall, A; Booth, C N; Boswell, R; Cartwright, S L; Combley, F; Dawson, I; Köksal, A; Letho, M; Newton, W M; Rankin, C; Thompson, L F; Böhrer, A; Brandt, S; Cowan, G D; Feigl, E; Grupen, Claus; Lutters, G; Minguet-Rodríguez, J A; Rivera, F; Saraiva, P; Smolik, L; Stephan, F; Apollonio, M; Bosisio, L; Della Marina, R; Giannini, G; Gobbo, B; Ragusa, F; Rothberg, J E; Wasserbaech, S R; Armstrong, S R; Bellantoni, L; Elmer, P; Feng, Z; Ferguson, D P S; Gao, Y S; González, S; Grahl, J; Harton, J L; Hayes, O J; Hu, H; McNamara, P A; Nachtman, J M; Orejudos, W; Pan, Y B; Saadi, Y; Schmitt, M; Scott, I J; Sharma, V; Turk, J; Walsh, A M; Wu Sau Lan; Wu, X; Yamartino, J M; Zheng, M; Zobernig, G

    1996-01-01

    A sample of 62249 \\tau-pair events is selected from data taken with the ALEPH detector in 1991, 1992 and 1993. The measurement of the branching fractions for \\tau decays into electrons and muons is presented with emphasis on the study of systematic effects from selection, particle identification and decay classification. Combined with the most recent ALEPH determination of the \\tau lifetime, these results provide a relative measurement of the leptonic couplings in the weak charged current for transverse W bosons.

  10. Total tree, merchantable stem and branch volume models for ...

    African Journals Online (AJOL)

    Total tree, merchantable stem and branch volume models for miombo woodlands of Malawi. Daud J Kachamba, Tron Eid. Abstract. The objective of this study was to develop general (multispecies) models for prediction of total tree, merchantable stem and branch volume including options with diameter at breast height (dbh) ...

  11. A parallel solution-adaptive scheme for predicting multi-phase core flows in solid propellant rocket motors

    International Nuclear Information System (INIS)

    Sachdev, J.S.; Groth, C.P.T.; Gottlieb, J.J.

    2003-01-01

    The development of a parallel adaptive mesh refinement (AMR) scheme is described for solving the governing equations for multi-phase (gas-particle) core flows in solid propellant rocket motors (SRM). An Eulerian formulation is used to described the coupled motion between the gas and particle phases. A cell-centred upwind finite-volume discretization and the use of limited solution reconstruction, Riemann solver based flux functions for the gas and particle phases, and explicit multi-stage time-stepping allows for high solution accuracy and computational robustness. A Riemann problem is formulated for prescribing boundary data at the burning surface. Efficient and scalable parallel implementations are achieved with domain decomposition on distributed memory multiprocessor architectures. Numerical results are described to demonstrate the capabilities of the approach for predicting SRM core flows. (author)

  12. PREDICTIVE CONTROL OF A BATCH POLYMERIZATION SYSTEM USING A FEEDFORWARD NEURAL NETWORK WITH ONLINE ADAPTATION BY GENETIC ALGORITHM

    Directory of Open Access Journals (Sweden)

    A. Cancelier

    Full Text Available Abstract This study used a predictive controller based on an empirical nonlinear model comprising a three-layer feedforward neural network for temperature control of the suspension polymerization process. In addition to the offline training technique, an algorithm was also analyzed for online adaptation of its parameters. For the offline training, the network was statically trained and the genetic algorithm technique was used in combination with the least squares method. For online training, the network was trained on a recurring basis and only the technique of genetic algorithms was used. In this case, only the weights and bias of the output layer neuron were modified, starting from the parameters obtained from the offline training. From the experimental results obtained in a pilot plant, a good performance was observed for the proposed control system, with superior performance for the control algorithm with online adaptation of the model, particularly with respect to the presence of off-set for the case of the fixed parameters model.

  13. Savings through the use of adaptive predictive control of thermo-active building systems (TABS): A case study

    International Nuclear Information System (INIS)

    Schmelas, Martin; Feldmann, Thomas; Bollin, Elmar

    2017-01-01

    Highlights: •An adaptive and predictive algorithm for the control of TABS (AMLR) is evaluated. •Comparison of standard TABS control and AMLR over a period of nine month each. •Thermal comfort, energy and investment savings in a passive seminar building. •Reduction of peak power of chilled beams (auxiliary system) with AMLR algorithm. •Simplification of the TABS hydraulics with AMLR algorithm. -- Abstract: The building sector is one of the main consumers of energy. Therefore, heating and cooling concepts for renewable energy sources become increasingly important. For this purpose, low-temperature systems such as thermo-active building systems (TABS) are particularly suitable. This paper presents results of the use of a novel adaptive and predictive computation method, based on multiple linear regression (AMLR) for the control of TABS in a passive seminar building. Detailed comparisons are shown between the standard TABS and AMLR strategies over a period of nine months each. In addition to the reduction of thermal energy use by approx. 26% and a significant reduction of the TABS pump operation time, this paper focuses on investment savings in a passive seminar building through the use of the AMLR strategy. This includes the reduction of peak power of the chilled beams (auxiliary system) as well as a simplification of the TABS hydronic circuit and the saving of an external temperature sensor. The AMLR proves its practicality by learning from the historical building operation, by dealing with forecasting errors and it is easy to integrate into a building automation system.

  14. Adapting SWAT hillslope erosion model to predict sediment concentrations and yields in large Basins.

    Science.gov (United States)

    Vigiak, Olga; Malagó, Anna; Bouraoui, Fayçal; Vanmaercke, Matthias; Poesen, Jean

    2015-12-15

    The Soil and Water Assessment Tool (SWAT) is used worldwide for water quality assessment and planning. This paper aimed to assess and adapt SWAT hillslope sediment yield model (Modified Universal Soil Loss Equation, MUSLE) for applications in large basins, i.e. when spatial data is coarse and model units are large; and to develop a robust sediment calibration method for large regions. The Upper Danube Basin (132,000km(2)) was used as case study representative of large European Basins. The MUSLE was modified to reduce sensitivity of sediment yields to the Hydrologic Response Unit (HRU) size, and to identify appropriate algorithms for estimating hillslope length (L) and slope-length factor (LS). HRUs gross erosion was broadly calibrated against plot data and soil erosion map estimates. Next, mean annual SWAT suspended sediment concentrations (SSC, mg/L) were calibrated and validated against SSC data at 55 gauging stations (622 station-years). SWAT annual specific sediment yields in subbasin reaches (RSSY, t/km(2)/year) were compared to yields measured at 33 gauging stations (87station-years). The best SWAT configuration combined a MUSLE equation modified by the introduction of a threshold area of 0.01km(2) where L and LS were estimated with flow accumulation algorithms. For this configuration, the SSC residual interquartile was less than +/-15mg/L both for the calibration (1995-2004) and the validation (2005-2009) periods. The mean SSC percent bias for 1995-2009 was 24%. RSSY residual interquartile was within +/-10t/km(2)/year, with a mean RSSY percent bias of 12%. Residuals showed no bias with respect to drainage area, slope, or spatial distribution. The use of multiple data types at multiple sites enabled robust simulation of sediment concentrations and yields of the region. The MUSLE modifications are recommended for use in large basins. Based on SWAT simulations, we present a sediment budget for the Upper Danube Basin. Copyright © 2015. Published by Elsevier B.V.

  15. Beware batch culture: Seasonality and niche construction predicted to favor bacterial adaptive diversification.

    Directory of Open Access Journals (Sweden)

    Charles Rocabert

    2017-03-01

    Full Text Available Metabolic cross-feeding interactions between microbial strains are common in nature, and emerge during evolution experiments in the laboratory, even in homogeneous environments providing a single carbon source. In sympatry, when the environment is well-mixed, the reasons why emerging cross-feeding interactions may sometimes become stable and lead to monophyletic genotypic clusters occupying specific niches, named ecotypes, remain unclear. As an alternative to evolution experiments in the laboratory, we developed Evo2Sim, a multi-scale model of in silico experimental evolution, equipped with the whole tool case of experimental setups, competition assays, phylogenetic analysis, and, most importantly, allowing for evolvable ecological interactions. Digital organisms with an evolvable genome structure encoding an evolvable metabolic network evolved for tens of thousands of generations in environments mimicking the dynamics of real controlled environments, including chemostat or batch culture providing a single limiting resource. We show here that the evolution of stable cross-feeding interactions requires seasonal batch conditions. In this case, adaptive diversification events result in two stably co-existing ecotypes, with one feeding on the primary resource and the other on by-products. We show that the regularity of serial transfers is essential for the maintenance of the polymorphism, as it allows for at least two stable seasons and thus two temporal niches. A first season is externally generated by the transfer into fresh medium, while a second one is internally generated by niche construction as the provided nutrient is replaced by secreted by-products derived from bacterial growth. In chemostat conditions, even if cross-feeding interactions emerge, they are not stable on the long-term because fitter mutants eventually invade the whole population. We also show that the long-term evolution of the two stable ecotypes leads to character

  16. Vegetative and adaptive traits predict different outcomes for restoration using hybrids

    Directory of Open Access Journals (Sweden)

    Philip Crystal

    2016-11-01

    Full Text Available Abstract – Hybridization has been implicated as a driver of speciation, extinction, and invasiveness, but can also provide resistant breeding stock following epidemics. However, evaluating the appropriateness of hybrids for use in restoration programs is difficult. Past the F1 generation, the proportion of a progenitor’s genome can vary widely, as can the combinations of parental genomes. Detailed genetic analysis can reveal this information, but cannot expose phenotypic alterations due to heterosis, transgressive traits, or changes in metabolism or development. In addition, because evolution is often driven by extreme individuals, decisions based on phenotypic averages of hybrid classes may have unintended results. We demonstrate a strategy to evaluate hybrids for use in restoration by visualizing hybrid phenotypes across selected groups of traits relative to both progenitor species. Specifically, we used discriminant analysis to differentiate among butternut (Juglans cinerea L., black walnut (J. nigra L., and Japanese walnut (J. ailantifolia Carr. var. cordiformis using vegetative characters and then with functional adaptive traits associated with seedling performance. When projected onto the progenitor trait space, naturally occurring hybrids (J. ×bixbyi Rehd. between butternut and Japanese walnut showed introgression towards Japanese walnut at vegetative characters but exhibited a hybrid swarm at functional traits. Both results indicate that hybrids have morphological and ecological phenotypes that distinguish them from butternut, demonstrating a lack of ecological equivalency that should not be carried into restoration breeding efforts. Despite these discrepancies, some hybrids were projected into the space occupied by butternut seedlings’ 95% confidence ellipse, signifying that some hybrids were similar at the measured traits. Determining how to consistently identify these individuals is imperative for future breeding and species

  17. Heart rate variability in prediction of individual adaptation to endurance training in recreational endurance runners.

    Science.gov (United States)

    Vesterinen, V; Häkkinen, K; Hynynen, E; Mikkola, J; Hokka, L; Nummela, A

    2013-03-01

    The aim of this study was to investigate whether nocturnal heart rate variability (HRV) can be used to predict changes in endurance performance during 28 weeks of endurance training. The training was divided into 14 weeks of basic training (BTP) and 14 weeks of intensive training periods (ITP). Endurance performance characteristics, nocturnal HRV, and serum hormone concentrations were measured before and after both training periods in 28 recreational endurance runners. During the study peak treadmill running speed (Vpeak ) improved by 7.5 ± 4.5%. No changes were observed in HRV indices after BTP, but after ITP, these indices increased significantly (HFP: 1.9%, P=0.026; TP: 1.7%, P=0.007). Significant correlations were observed between the change of Vpeak and HRV indices (TP: r=0.75, PHRV among recreational endurance runners, it seems that moderate- and high-intensity training are needed. This study showed that recreational endurance runners with a high HRV at baseline improved their endurance running performance after ITP more than runners with low baseline HRV. © 2011 John Wiley & Sons A/S.

  18. Conflict adaptation is predicted by the cognitive, but not the affective alexithymia dimension

    Directory of Open Access Journals (Sweden)

    Michiel ede Galan

    2014-07-01

    Full Text Available Stimulus-induced response conflict (e.g., in Simon or Stroop tasks is often reduced after conflict trials—the Gratton effect. It is generally assumed that this effect is due to a strengthening of the representation of the current intention or goal, which in turn increases the degree of stimulus and/or response control. Recent evidence suggests that the motivational signal driving the Gratton effect might be affective in nature. If so, individual differences in either the strength of affective signals and/or the ability to interpret such signals might explain individual differences in cognitive-control adjustments as reflected in the Gratton effect. We tested this hypothesis by relating individual sizes of the Gratton effect in a Simon task to scores on the affective and the cognitive dimension of the Bermond/Vorst Alexithymia Questionnaire (BVAQ—which we assumed to assess individual differences in affective-signal strength and ability to interpret affective signals, respectively. Results show that the cognitive, but not the affective dimension predicted control adjustment, while the accuracy of heartbeat detection was only (and only weakly related to online control. This suggests that the motivation to fine-tune one’s cognitive-control operations is mediated by, and may depend on one’s ability to interpret one’s own affective signals.

  19. Optimal recall from bounded metaplastic synapses: predicting functional adaptations in hippocampal area CA3.

    Directory of Open Access Journals (Sweden)

    Cristina Savin

    2014-02-01

    Full Text Available A venerable history of classical work on autoassociative memory has significantly shaped our understanding of several features of the hippocampus, and most prominently of its CA3 area, in relation to memory storage and retrieval. However, existing theories of hippocampal memory processing ignore a key biological constraint affecting memory storage in neural circuits: the bounded dynamical range of synapses. Recent treatments based on the notion of metaplasticity provide a powerful model for individual bounded synapses; however, their implications for the ability of the hippocampus to retrieve memories well and the dynamics of neurons associated with that retrieval are both unknown. Here, we develop a theoretical framework for memory storage and recall with bounded synapses. We formulate the recall of a previously stored pattern from a noisy recall cue and limited-capacity (and therefore lossy synapses as a probabilistic inference problem, and derive neural dynamics that implement approximate inference algorithms to solve this problem efficiently. In particular, for binary synapses with metaplastic states, we demonstrate for the first time that memories can be efficiently read out with biologically plausible network dynamics that are completely constrained by the synaptic plasticity rule, and the statistics of the stored patterns and of the recall cue. Our theory organises into a coherent framework a wide range of existing data about the regulation of excitability, feedback inhibition, and network oscillations in area CA3, and makes novel and directly testable predictions that can guide future experiments.

  20. An Adaptive Medium Access Parameter Prediction Scheme for IEEE 802.11 Real-Time Applications

    Directory of Open Access Journals (Sweden)

    Estefanía Coronado

    2017-01-01

    Full Text Available Multimedia communications have experienced an unprecedented growth due mainly to the increase in the content quality and the emergence of smart devices. The demand for these contents is tending towards wireless technologies. However, these transmissions are quite sensitive to network delays. Therefore, ensuring an optimum QoS level becomes of great importance. The IEEE 802.11e amendment was released to address the lack of QoS capabilities in the original IEEE 802.11 standard. Accordingly, the Enhanced Distributed Channel Access (EDCA function was introduced, allowing it to differentiate traffic streams through a group of Medium Access Control (MAC parameters. Although EDCA recommends a default configuration for these parameters, it has been proved that it is not optimum in many scenarios. In this work a dynamic prediction scheme for these parameters is presented. This approach ensures an appropriate traffic differentiation while maintaining compatibility with the stations without QoS support. As the APs are the only devices that use this algorithm, no changes are required to current network cards. The results show improvements in both voice and video transmissions, as well as in the QoS level of the network that the proposal achieves with regard to EDCA.

  1. Adaptive Neuro-Fuzzy Inference System Applied QSAR with Quantum Chemical Descriptors for Predicting Radical Scavenging Activities of Carotenoids.

    Science.gov (United States)

    Jhin, Changho; Hwang, Keum Taek

    2015-01-01

    One of the physiological characteristics of carotenoids is their radical scavenging activity. In this study, the relationship between radical scavenging activities and quantum chemical descriptors of carotenoids was determined. Adaptive neuro-fuzzy inference system (ANFIS) applied quantitative structure-activity relationship models (QSAR) were also developed for predicting and comparing radical scavenging activities of carotenoids. Semi-empirical PM6 and PM7 quantum chemical calculations were done by MOPAC. Ionisation energies of neutral and monovalent cationic carotenoids and the product of chemical potentials of neutral and monovalent cationic carotenoids were significantly correlated with the radical scavenging activities, and consequently these descriptors were used as independent variables for the QSAR study. The ANFIS applied QSAR models were developed with two triangular-shaped input membership functions made for each of the independent variables and optimised by a backpropagation method. High prediction efficiencies were achieved by the ANFIS applied QSAR. The R-square values of the developed QSAR models with the variables calculated by PM6 and PM7 methods were 0.921 and 0.902, respectively. The results of this study demonstrated reliabilities of the selected quantum chemical descriptors and the significance of QSAR models.

  2. Adaptive Neuro-Fuzzy Inference System Applied QSAR with Quantum Chemical Descriptors for Predicting Radical Scavenging Activities of Carotenoids.

    Directory of Open Access Journals (Sweden)

    Changho Jhin

    Full Text Available One of the physiological characteristics of carotenoids is their radical scavenging activity. In this study, the relationship between radical scavenging activities and quantum chemical descriptors of carotenoids was determined. Adaptive neuro-fuzzy inference system (ANFIS applied quantitative structure-activity relationship models (QSAR were also developed for predicting and comparing radical scavenging activities of carotenoids. Semi-empirical PM6 and PM7 quantum chemical calculations were done by MOPAC. Ionisation energies of neutral and monovalent cationic carotenoids and the product of chemical potentials of neutral and monovalent cationic carotenoids were significantly correlated with the radical scavenging activities, and consequently these descriptors were used as independent variables for the QSAR study. The ANFIS applied QSAR models were developed with two triangular-shaped input membership functions made for each of the independent variables and optimised by a backpropagation method. High prediction efficiencies were achieved by the ANFIS applied QSAR. The R-square values of the developed QSAR models with the variables calculated by PM6 and PM7 methods were 0.921 and 0.902, respectively. The results of this study demonstrated reliabilities of the selected quantum chemical descriptors and the significance of QSAR models.

  3. Prediction of matching condition for a microstrip subsystem using artificial neural network and adaptive neuro-fuzzy inference system

    Science.gov (United States)

    Salehi, Mohammad Reza; Noori, Leila; Abiri, Ebrahim

    2016-11-01

    In this paper, a subsystem consisting of a microstrip bandpass filter and a microstrip low noise amplifier (LNA) is designed for WLAN applications. The proposed filter has a small implementation area (49 mm2), small insertion loss (0.08 dB) and wide fractional bandwidth (FBW) (61%). To design the proposed LNA, the compact microstrip cells, an field effect transistor, and only a lumped capacitor are used. It has a low supply voltage and a low return loss (-40 dB) at the operation frequency. The matching condition of the proposed subsystem is predicted using subsystem analysis, artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). To design the proposed filter, the transmission matrix of the proposed resonator is obtained and analysed. The performance of the proposed ANN and ANFIS models is tested using the numerical data by four performance measures, namely the correlation coefficient (CC), the mean absolute error (MAE), the average percentage error (APE) and the root mean square error (RMSE). The obtained results show that these models are in good agreement with the numerical data, and a small error between the predicted values and numerical solution is obtained.

  4. Voluntary ethanol intake predicts κ-opioid receptor supersensitivity and regionally distinct dopaminergic adaptations in macaques.

    Science.gov (United States)

    Siciliano, Cody A; Calipari, Erin S; Cuzon Carlson, Verginia C; Helms, Christa M; Lovinger, David M; Grant, Kathleen A; Jones, Sara R

    2015-04-15

    The dopaminergic projections from the ventral midbrain to the striatum have long been implicated in mediating motivated behaviors and addiction. Previously it was demonstrated that κ-opioid receptor (KOR) signaling in the striatum plays a critical role in the increased reinforcing efficacy of ethanol following ethanol vapor exposure in rodent models. Although rodents have been used extensively to determine the neurochemical consequences of chronic ethanol exposure, establishing high levels of voluntary drinking in these models has proven difficult. Conversely, nonhuman primates exhibit similar intake and pattern to humans in regard to drinking. Here we examine the effects of chronic voluntary ethanol self-administration on dopamine neurotransmission and the ability of KORs to regulate dopamine release in the dorsolateral caudate (DLC) and nucleus accumbens (NAc) core. Using voltammetry in brain slices from cynomolgus macaques after 6 months of ad libitum ethanol drinking, we found increased KOR sensitivity in both the DLC and NAc. The magnitude of ethanol intake predicted increases in KOR sensitivity in the NAc core, but not the DLC. Additionally, ethanol drinking increased dopamine release and uptake in the NAc, but decreased both of these measures in the DLC. These data suggest that chronic daily drinking may result in regionally distinct disruptions of striatal outputs. In concert with previous reports showing increased KOR regulation of drinking behaviors induced by ethanol exposure, the strong relationship between KOR activity and voluntary ethanol intake observed here gives further support to the hypothesis that KORs may provide a promising pharmacotherapeutic target in the treatment of alcoholism. Copyright © 2015 the authors 0270-6474/15/355959-10$15.00/0.

  5. The branch librarians' handbook

    CERN Document Server

    Rivers, Vickie

    2004-01-01

    ""Recommended""--Booklist; ""an excellent addition...highly recommended""--Public Libraries; ""clear...very sound advice...strongly recommend""--Catholic Library World; ""excellent resource...organized...well written""--Against the Grain; ""interesting...thoroughly practical...a very good book...well organized...clearly written""--ARBA. This handbook covers a wide variety of issues that the branch librarian must deal with every day. Chapters are devoted to mission statements (the Dallas Public Library and Dayton Metro Library mission statements are highlighted as examples), library systems,

  6. Prediction of flood abnormalities for improved public safety using a modified adaptive neuro-fuzzy inference system.

    Science.gov (United States)

    Aqil, M; Kita, I; Yano, A; Nishiyama, S

    2006-01-01

    It is widely accepted that an efficient flood alarm system may significantly improve public safety and mitigate economical damages caused by inundations. In this paper, a modified adaptive neuro-fuzzy system is proposed to modify the traditional neuro-fuzzy model. This new method employs a rule-correction based algorithm to replace the error back propagation algorithm that is employed by the traditional neuro-fuzzy method in backward pass calculation. The final value obtained during the backward pass calculation using the rule-correction algorithm is then considered as a mapping function of the learning mechanism of the modified neuro-fuzzy system. Effectiveness of the proposed identification technique is demonstrated through a simulation study on the flood series of the Citarum River in Indonesia. The first four-year data (1987 to 1990) was used for model training/calibration, while the other remaining data (1991 to 2002) was used for testing the model. The number of antecedent flows that should be included in the input variables was determined by two statistical methods, i.e. autocorrelation and partial autocorrelation between the variables. Performance accuracy of the model was evaluated in terms of two statistical indices, i.e. mean average percentage error and root mean square error. The algorithm was developed in a decision support system environment in order to enable users to process the data. The decision support system is found to be useful due to its interactive nature, flexibility in approach, and evolving graphical features, and can be adopted for any similar situation to predict the streamflow. The main data processing includes gauging station selection, input generation, lead-time selection/generation, and length of prediction. This program enables users to process the flood data, to train/test the model using various input options, and to visualize results. The program code consists of a set of files, which can be modified as well to match other

  7. Quiver Varieties and Branching

    Directory of Open Access Journals (Sweden)

    Hiraku Nakajima

    2009-01-01

    Full Text Available Braverman and Finkelberg recently proposed the geometric Satake correspondence for the affine Kac-Moody group Gaff [Braverman A., Finkelberg M., arXiv:0711.2083]. They conjecture that intersection cohomology sheaves on the Uhlenbeck compactification of the framed moduli space of Gcpt-instantons on $R^4/Z_r$ correspond to weight spaces of representations of the Langlands dual group $G_{aff}^{vee}$ at level $r$. When $G = SL(l$, the Uhlenbeck compactification is the quiver variety of type $sl(r_{aff}$, and their conjecture follows from the author's earlier result and I. Frenkel's level-rank duality. They further introduce a convolution diagram which conjecturally gives the tensor product multiplicity [Braverman A., Finkelberg M., Private communication, 2008]. In this paper, we develop the theory for the branching in quiver varieties and check this conjecture for $G = SL(l$.

  8. Integrating over Higgs branches

    International Nuclear Information System (INIS)

    Moore, G.; Shatashvili, S.

    2000-01-01

    We develop some useful techniques for integrating over Higgs branches in supersymmetric theories with 4 and 8 supercharges. In particular, we define a regularized volume for hyperkaehler quotients. We evaluate this volume for certain ALE and ALF spaces in terms of the hyperkaehler periods. We also reduce these volumes for a large class of hyperkaehler quotients to simpler integrals. These quotients include complex coadjoint orbits, instanton moduli spaces on R 4 and ALE manifolds, Hitchin spaces, and moduli spaces of (parabolic) Higgs bundles on Riemann surfaces. In the case of Hitchin spaces the evaluation of the volume reduces to a summation over solutions of Bethe ansatz equations for the non-linear Schroedinger system. We discuss some applications of our results. (orig.)

  9. Simulating Physiological Response with a Passive Sensor Manikin and an Adaptive Thermal Manikin to Predict Thermal Sensation and Comfort

    Energy Technology Data Exchange (ETDEWEB)

    Rugh, John P [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Chaney, Larry [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hepokoski, Mark [ThermoAnalytics Inc.; Curran, Allen [ThermoAnalytics Inc.; Burke, Richard [Measurement Technology NW; Maranville, Clay [Ford Motor Company

    2015-04-14

    Reliable assessment of occupant thermal comfort can be difficult to obtain within automotive environments, especially under transient and asymmetric heating and cooling scenarios. Evaluation of HVAC system performance in terms of comfort commonly requires human subject testing, which may involve multiple repetitions, as well as multiple test subjects. Instrumentation (typically comprised of an array of temperature sensors) is usually only sparsely applied across the human body, significantly reducing the spatial resolution of available test data. Further, since comfort is highly subjective in nature, a single test protocol can yield a wide variation in results which can only be overcome by increasing the number of test replications and subjects. In light of these difficulties, various types of manikins are finding use in automotive testing scenarios. These manikins can act as human surrogates from which local skin and core temperatures can be obtained, which are necessary for accurately predicting local and whole body thermal sensation and comfort using a physiology-based comfort model (e.g., the Berkeley Comfort Model). This paper evaluates two different types of manikins, i) an adaptive sweating thermal manikin, which is coupled with a human thermoregulation model, running in real-time, to obtain realistic skin temperatures; and, ii) a passive sensor manikin, which is used to measure boundary conditions as they would act on a human, from which skin and core temperatures can be predicted using a thermophysiological model. The simulated physiological responses and comfort obtained from both of these manikin-model coupling schemes are compared to those of a human subject within a vehicle cabin compartment transient heat-up scenario.

  10. FPGA/NIOS Implementation of an Adaptive FIR Filter Using Linear Prediction to Reduce Narrow-Band RFI for Radio Detection of Cosmic Rays

    NARCIS (Netherlands)

    Szadkowski, Zbigniew; Fraenkel, E. D.; van den Berg, Ad M.

    2013-01-01

    We present the FPGA/NIOS implementation of an adaptive finite impulse response (FIR) filter based on linear prediction to suppress radio frequency interference (RFI). This technique will be used for experiments that observe coherent radio emission from extensive air showers induced by

  11. The efficiency of bank branches

    OpenAIRE

    Omid Takbiri; Mohammad Mohammadi; Bahman Naderi

    2015-01-01

    Banking industry has significant contribution in development of economies of developing countries. Most banks execute their operations through different branches. Therefore it is important to measure the relative efficiencies of these branches. Data envelopment analysis (DEA) is one of the most useful tools in measuring banks’ performance. The present paper aims to extract ranking pattern of banks based on performance evaluation using DEA analysis. In the present research, 120 bank branches o...

  12. Methods and Technologies Branch (MTB)

    Science.gov (United States)

    The Methods and Technologies Branch focuses on methods to address epidemiologic data collection, study design and analysis, and to modify technological approaches to better understand cancer susceptibility.

  13. On the anomalous characteristics in the P and R branches in a hydrogen fulcher band

    International Nuclear Information System (INIS)

    Kado, Shinichiro; Okamoto, Atsushi; Yamasaki, Daisuke; Iida, Yohei; Kajita, Shin; Shikama, Taiichi; Oishi, Tetsutaro; Tanaka, Satoru; Xiao Bingjia

    2006-01-01

    Anomalous characteristics in the P and R branches in hydrogen Fulcher-α emissions were investigated with respect to rotational temperature and population in the excited electronic state (upper-Fulcher state). The ro-vibrational population distribution of the ground electronic state was deduced by applying the coronal equilibrium to the Q branch, and then the population for the P and R branches was predicted. The anomalies in P and R branches can be found in the rotational temperature and the branching ratio between the branches. Our results suggest that the sum of the emission from P and R branches seems to agree with that predicted based on the Q branch emission. (author)

  14. More adaptive versus less maladaptive coping: What is more predictive of symptom severity? Development of a new scale to investigate coping profiles across different psychopathological syndromes.

    Science.gov (United States)

    Moritz, Steffen; Jahns, Anna Katharina; Schröder, Johanna; Berger, Thomas; Lincoln, Tania M; Klein, Jan Philipp; Göritz, Anja S

    2016-02-01

    Lack of adaptive and enhanced maladaptive coping with stress and negative emotions are implicated in many psychopathological disorders. We describe the development of a new scale to investigate the relative contribution of different coping styles to psychopathology in a large population sample. We hypothesized that the magnitude of the supposed positive correlation between maladaptive coping and psychopathology would be stronger than the supposed negative correlation between adaptive coping and psychopathology. We also examined whether distinct coping style patterns emerge for different psychopathological syndromes. A total of 2200 individuals from the general population participated in an online survey. The Patient Health Questionnaire-9 (PHQ-9), the Obsessive-Compulsive Inventory revised (OCI-R) and the Paranoia Checklist were administered along with a novel instrument called Maladaptive and Adaptive Coping Styles (MAX) questionnaire. Participants were reassessed six months later. MAX consists of three dimensions representing adaptive coping, maladaptive coping and avoidance. Across all psychopathological syndromes, similar response patterns emerged. Maladaptive coping was more strongly related to psychopathology than adaptive coping both cross-sectionally and longitudinally. The overall number of coping styles adopted by an individual predicted greater psychopathology. Mediation analysis suggests that a mild positive relationship between adaptive and certain maladaptive styles (emotional suppression) partially accounts for the attenuated relationship between adaptive coping and depressive symptoms. Results should be replicated in a clinical population. Results suggest that maladaptive and adaptive coping styles are not reciprocal. Reducing maladaptive coping seems to be more important for outcome than enhancing adaptive coping. The study supports transdiagnostic approaches advocating that maladaptive coping is a common factor across different psychopathologies

  15. Tau hadronic branching ratios

    CERN Document Server

    Buskulic, Damir; De Bonis, I; Décamp, D; Ghez, P; Goy, C; Lees, J P; Lucotte, A; Minard, M N; Odier, P; Pietrzyk, B; Ariztizabal, F; Chmeissani, M; Crespo, J M; Efthymiopoulos, I; Fernández, E; Fernández-Bosman, M; Gaitan, V; Martínez, M; Orteu, S; Pacheco, A; Padilla, C; Palla, Fabrizio; Pascual, A; Perlas, J A; Sánchez, F; Teubert, F; Colaleo, A; Creanza, D; De Palma, M; Farilla, A; Gelao, G; Girone, M; Iaselli, Giuseppe; Maggi, G; Maggi, M; Marinelli, N; Natali, S; Nuzzo, S; Ranieri, A; Raso, G; Romano, F; Ruggieri, F; Selvaggi, G; Silvestris, L; Tempesta, P; Zito, G; Huang, X; Lin, J; Ouyang, Q; Wang, T; Xie, Y; Xu, R; Xue, S; Zhang, J; Zhang, L; Zhao, W; Bonvicini, G; Cattaneo, M; Comas, P; Coyle, P; Drevermann, H; Engelhardt, A; Forty, Roger W; Frank, M; Hagelberg, R; Harvey, J; Jacobsen, R; Janot, P; Jost, B; Kneringer, E; Knobloch, J; Lehraus, Ivan; Markou, C; Martin, E B; Mato, P; Minten, Adolf G; Miquel, R; Oest, T; Palazzi, P; Pater, J R; Pusztaszeri, J F; Ranjard, F; Rensing, P E; Rolandi, Luigi; Schlatter, W D; Schmelling, M; Schneider, O; Tejessy, W; Tomalin, I R; Venturi, A; Wachsmuth, H W; Wiedenmann, W; Wildish, T; Witzeling, W; Wotschack, J; Ajaltouni, Ziad J; Bardadin-Otwinowska, Maria; Barrès, A; Boyer, C; Falvard, A; Gay, P; Guicheney, C; Henrard, P; Jousset, J; Michel, B; Monteil, S; Pallin, D; Perret, P; Podlyski, F; Proriol, J; Rossignol, J M; Saadi, F; Fearnley, Tom; Hansen, J B; Hansen, J D; Hansen, J R; Hansen, P H; Nilsson, B S; Kyriakis, A; Simopoulou, Errietta; Siotis, I; Vayaki, Anna; Zachariadou, K; Blondel, A; Bonneaud, G R; Brient, J C; Bourdon, P; Passalacqua, L; Rougé, A; Rumpf, M; Tanaka, R; Valassi, Andrea; Verderi, M; Videau, H L; Candlin, D J; Parsons, M I; Focardi, E; Parrini, G; Corden, M; Delfino, M C; Georgiopoulos, C H; Jaffe, D E; Antonelli, A; Bencivenni, G; Bologna, G; Bossi, F; Campana, P; Capon, G; Chiarella, V; Felici, G; Laurelli, P; Mannocchi, G; Murtas, F; Murtas, G P; Pepé-Altarelli, M; Dorris, S J; Halley, A W; ten Have, I; Knowles, I G; Lynch, J G; Morton, W T; O'Shea, V; Raine, C; Reeves, P; Scarr, J M; Smith, K; Smith, M G; Thompson, A S; Thomson, F; Thorn, S; Turnbull, R M; Becker, U; Braun, O; Geweniger, C; Graefe, G; Hanke, P; Hepp, V; Kluge, E E; Putzer, A; Rensch, B; Schmidt, M; Sommer, J; Stenzel, H; Tittel, K; Werner, S; Wunsch, M; Beuselinck, R; Binnie, David M; Cameron, W; Colling, D J; Dornan, Peter J; Konstantinidis, N P; Moneta, L; Moutoussi, A; Nash, J; San Martin, G; Sedgbeer, J K; Stacey, A M; Dissertori, G; Girtler, P; Kuhn, D; Rudolph, G; Bowdery, C K; Brodbeck, T J; Colrain, P; Crawford, G; Finch, A J; Foster, F; Hughes, G; Sloan, Terence; Whelan, E P; Williams, M I; Galla, A; Greene, A M; Kleinknecht, K; Quast, G; Raab, J; Renk, B; Sander, H G; Wanke, R; Van Gemmeren, P; Zeitnitz, C; Aubert, Jean-Jacques; Bencheikh, A M; Benchouk, C; Bonissent, A; Bujosa, G; Calvet, D; Carr, J; Diaconu, C A; Etienne, F; Thulasidas, M; Nicod, D; Payre, P; Rousseau, D; Talby, M; Abt, I; Assmann, R W; Bauer, C; Blum, Walter; Brown, D; Dietl, H; Dydak, Friedrich; Ganis, G; Gotzhein, C; Jakobs, K; Kroha, H; Lütjens, G; Lutz, Gerhard; Männer, W; Moser, H G; Richter, R H; Rosado-Schlosser, A; Schael, S; Settles, Ronald; Seywerd, H C J; Saint-Denis, R; Wolf, G; Alemany, R; Boucrot, J; Callot, O; Cordier, A; Courault, F; Davier, M; Duflot, L; Grivaz, J F; Heusse, P; Jacquet, M; Kim, D W; Le Diberder, F R; Lefrançois, J; Lutz, A M; Musolino, G; Nikolic, I A; Park, H J; Park, I C; Schune, M H; Simion, S; Veillet, J J; Videau, I; Abbaneo, D; Azzurri, P; Bagliesi, G; Batignani, G; Bettarini, S; Bozzi, C; Calderini, G; Carpinelli, M; Ciocci, M A; Ciulli, V; Dell'Orso, R; Fantechi, R; Ferrante, I; Foà, L; Forti, F; Giassi, A; Giorgi, M A; Gregorio, A; Ligabue, F; Lusiani, A; Marrocchesi, P S; Messineo, A; Rizzo, G; Sanguinetti, G; Sciabà, A; Spagnolo, P; Steinberger, Jack; Tenchini, Roberto; Tonelli, G; Triggiani, G; Vannini, C; Verdini, P G; Walsh, J; Betteridge, A P; Blair, G A; Bryant, L M; Cerutti, F; Gao, Y; Green, M G; Johnson, D L; Medcalf, T; Mir, L M; Perrodo, P; Strong, J A; Bertin, V; Botterill, David R; Clifft, R W; Edgecock, T R; Haywood, S; Edwards, M; Maley, P; Norton, P R; Thompson, J C; Bloch-Devaux, B; Colas, P; Emery, S; Kozanecki, Witold; Lançon, E; Lemaire, M C; Locci, E; Marx, B; Pérez, P; Rander, J; Renardy, J F; Roussarie, A; Schuller, J P; Schwindling, J; Trabelsi, A; Vallage, B; Johnson, R P; Kim, H Y; Litke, A M; McNeil, M A; Taylor, G; Beddall, A; Booth, C N; Boswell, R; Cartwright, S L; Combley, F; Dawson, I; Köksal, A; Letho, M; Newton, W M; Rankin, C; Thompson, L F; Böhrer, A; Brandt, S; Cowan, G D; Feigl, E; Grupen, Claus; Lutters, G; Minguet-Rodríguez, J A; Rivera, F; Saraiva, P; Smolik, L; Stephan, F; Apollonio, M; Bosisio, L; Della Marina, R; Giannini, G; Gobbo, B; Ragusa, F; Rothberg, J E; Wasserbaech, S R; Armstrong, S R; Bellantoni, L; Elmer, P; Feng, Z; Ferguson, D P S; Gao, Y S; González, S; Grahl, J; Harton, J L; Hayes, O J; Hu, H; McNamara, P A; Nachtman, J M; Orejudos, W; Pan, Y B; Saadi, Y; Schmitt, M; Scott, I J; Sharma, V; Turk, J; Walsh, A M; Wu Sau Lan; Wu, X; Yamartino, J M; Zheng, M; Zobernig, G

    1996-01-01

    From 64492 selected \\tau-pair events, produced at the Z^0 resonance, the measurement of the tau decays into hadrons from a global analysis using 1991, 1992 and 1993 ALEPH data is presented. Special emphasis is given to the reconstruction of photons and \\pi^0's, and the removal of fake photons. A detailed study of the systematics entering the \\pi^0 reconstruction is also given. A complete and consistent set of tau hadronic branching ratios is presented for 18 exclusive modes. Most measurements are more precise than the present world average. The new level of precision reached allows a stringent test of \\tau-\\mu universality in hadronic decays, g_\\tau/g_\\mu \\ = \\ 1.0013 \\ \\pm \\ 0.0095, and the first measurement of the vector and axial-vector contributions to the non-strange hadronic \\tau decay width: R_{\\tau ,V} \\ = \\ 1.788 \\ \\pm \\ 0.025 and R_{\\tau ,A} \\ = \\ 1.694 \\ \\pm \\ 0.027. The ratio (R_{\\tau ,V} - R_{\\tau ,A}) / (R_{\\tau ,V} + R_{\\tau ,A}), equal to (2.7 \\pm 1.3) \\ \\%, is a measure of the importance of Q...

  16. Characterization of the Diameter, branch angle and longevity of axial branches of Nothofagusobliqua

    Directory of Open Access Journals (Sweden)

    Patricio Corvalán Vera

    2017-08-01

    Full Text Available The lack of knowledge about grow dynamics of the living tree crown of Nothofagusobliqua secondary growth forests strongly limits the objective formulation of silvicultural schemes oriented to the industrial production of high quality wood. Therefore, in this work, we described basic relationships between tree size, age and angle branches insertion and the crown. Considering a sample data of 59 dominant trees, distributed in different age conditions, we applied a combined analysis technique of stem analysis, steam taper analysis and thickest branch measurement in each decile of the total height. This approach allowed us to determine that there is a significant relationship between the steam diameter, the angle insertion and the age of the branch, as well as the size and age of the trees. Also, the thicker branches tend to have lower insertion angles, to be older, to be located at lower relative heights and to be located in larger diameter sections. Taking into consideration these relationships, it is possible to build new predicted branch models as tools for the development of silvicultural schemes to suit different log grade.

  17. "Your Model Is Predictive-- but Is It Useful?" Theoretical and Empirical Considerations of a New Paradigm for Adaptive Tutoring Evaluation

    Science.gov (United States)

    González-Brenes, José P.; Huang, Yun

    2015-01-01

    Classification evaluation metrics are often used to evaluate adaptive tutoring systems-- programs that teach and adapt to humans. Unfortunately, it is not clear how intuitive these metrics are for practitioners with little machine learning background. Moreover, our experiments suggest that existing convention for evaluating tutoring systems may…

  18. A two-stage predictive model to simultaneous control of trihalomethanes in water treatment plants and distribution systems: adaptability to treatment processes.

    Science.gov (United States)

    Domínguez-Tello, Antonio; Arias-Borrego, Ana; García-Barrera, Tamara; Gómez-Ariza, José Luis

    2017-10-01

    The trihalomethanes (TTHMs) and others disinfection by-products (DBPs) are formed in drinking water by the reaction of chlorine with organic precursors contained in the source water, in two consecutive and linked stages, that starts at the treatment plant and continues in second stage along the distribution system (DS) by reaction of residual chlorine with organic precursors not removed. Following this approach, this study aimed at developing a two-stage empirical model for predicting the formation of TTHMs in the water treatment plant and subsequently their evolution along the water distribution system (WDS). The aim of the two-stage model was to improve the predictive capability for a wide range of scenarios of water treatments and distribution systems. The two-stage model was developed using multiple regression analysis from a database (January 2007 to July 2012) using three different treatment processes (conventional and advanced) in the water supply system of Aljaraque area (southwest of Spain). Then, the new model was validated using a recent database from the same water supply system (January 2011 to May 2015). The validation results indicated no significant difference in the predictive and observed values of TTHM (R 2 0.874, analytical variance distribution systems studied, proving the adaptability of the new model to the boundary conditions. Finally the predictive capability of the new model was compared with 17 other models selected from the literature, showing satisfactory results prediction and excellent adaptability to treatment processes.

  19. mPLR-Loc: an adaptive decision multi-label classifier based on penalized logistic regression for protein subcellular localization prediction.

    Science.gov (United States)

    Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

    2015-03-15

    Proteins located in appropriate cellular compartments are of paramount importance to exert their biological functions. Prediction of protein subcellular localization by computational methods is required in the post-genomic era. Recent studies have been focusing on predicting not only single-location proteins but also multi-location proteins. However, most of the existing predictors are far from effective for tackling the challenges of multi-label proteins. This article proposes an efficient multi-label predictor, namely mPLR-Loc, based on penalized logistic regression and adaptive decisions for predicting both single- and multi-location proteins. Specifically, for each query protein, mPLR-Loc exploits the information from the Gene Ontology (GO) database by using its accession number (AC) or the ACs of its homologs obtained via BLAST. The frequencies of GO occurrences are used to construct feature vectors, which are then classified by an adaptive decision-based multi-label penalized logistic regression classifier. Experimental results based on two recent stringent benchmark datasets (virus and plant) show that mPLR-Loc remarkably outperforms existing state-of-the-art multi-label predictors. In addition to being able to rapidly and accurately predict subcellular localization of single- and multi-label proteins, mPLR-Loc can also provide probabilistic confidence scores for the prediction decisions. For readers' convenience, the mPLR-Loc server is available online (http://bioinfo.eie.polyu.edu.hk/mPLRLocServer). Copyright © 2014 Elsevier Inc. All rights reserved.

  20. Brain-behavioral adaptability predicts response to cognitive behavioral therapy for emotional disorders: A person-centered event-related potential study.

    Science.gov (United States)

    Stange, Jonathan P; MacNamara, Annmarie; Kennedy, Amy E; Hajcak, Greg; Phan, K Luan; Klumpp, Heide

    2017-06-23

    Single-trial-level analyses afford the ability to link neural indices of elaborative attention (such as the late positive potential [LPP], an event-related potential) with downstream markers of attentional processing (such as reaction time [RT]). This approach can provide useful information about individual differences in information processing, such as the ability to adapt behavior based on attentional demands ("brain-behavioral adaptability"). Anxiety and depression are associated with maladaptive information processing implicating aberrant cognition-emotion interactions, but whether brain-behavioral adaptability predicts response to psychotherapy is not known. We used a novel person-centered, trial-level analysis approach to link neural indices of stimulus processing to behavioral responses and to predict treatment outcome. Thirty-nine patients with anxiety and/or depression received 12 weeks of cognitive behavioral therapy (CBT). Prior to treatment, patients performed a speeded reaction-time task involving briefly-presented pairs of aversive and neutral pictures while electroencephalography was recorded. Multilevel modeling demonstrated that larger LPPs predicted slower responses on subsequent trials, suggesting that increased attention to the task-irrelevant nature of pictures interfered with reaction time on subsequent trials. Whereas using LPP and RT averages did not distinguish CBT responders from nonresponders, in trial-level analyses individuals who demonstrated greater ability to benefit behaviorally (i.e., faster RT) from smaller LPPs on the previous trial (greater brain-behavioral adaptability) were more likely to respond to treatment and showed greater improvements in depressive symptoms. These results highlight the utility of trial-level analyses to elucidate variability in within-subjects, brain-behavioral attentional coupling in the context of emotion processing, in predicting response to CBT for emotional disorders. Copyright © 2017 Elsevier Ltd

  1. Left bundle-branch block

    DEFF Research Database (Denmark)

    Risum, Niels; Strauss, David; Sogaard, Peter

    2013-01-01

    The relationship between myocardial electrical activation by electrocardiogram (ECG) and mechanical contraction by echocardiography in left bundle-branch block (LBBB) has never been clearly demonstrated. New strict criteria for LBBB based on a fundamental understanding of physiology have recently...

  2. Spiral branches and star formation

    International Nuclear Information System (INIS)

    Zasov, A.V.

    1974-01-01

    Origin of spiral branches of galaxies and formation of stars in them are considered from the point of view of the theory of the gravitational gas condensation, one of comparatively young theories. Arguments are presented in favour of the stellar condensation theory. The concept of the star formation of gas is no longer a speculative hypothesis. This is a theory which assumes quantitative verification and explains qualitatively many facts observed. And still our knowledge on the nature of spiral branches is very poor. It still remains vague what processes give origin to spiral branches, why some galaxies have spirals and others have none. And shapes of spiral branches are diverse. Some cases are known when spiral branches spread outside boundaries of galaxies themselves. Such spirals arise exclusively in the region where there are two or some interacting galaxies. Only first steps have been made in the explanation of the galaxy spiral branches, and it is necessary to carry out new observations and new theoretical calculations

  3. STARDUST FROM ASYMPTOTIC GIANT BRANCH STARS

    International Nuclear Information System (INIS)

    Gail, H.-P.; Zhukovska, S. V.; Hoppe, P.; Trieloff, M.

    2009-01-01

    The formation of dust in the outflows of low- and intermediate-mass stars on the first giant branch and asymptotic giant branch (AGB) is studied and the relative contributions of stars of different initial masses and metallicities to the interstellar medium (ISM) at the instant of solar system formation are derived. These predictions are compared with the characteristics of the parent stars of presolar dust grains found in primitive meteorites and interplanetary dust particles (IDPs) inferred from their isotopic compositions. For this purpose, model calculations for dust condensation in stellar outflows are combined with synthetic models of stellar evolution on the first giant branch and AGB and an evolution model of the Milky Way for the solar neighborhood. The dust components considered are olivine, pyroxene, carbon, SiC, and iron. The corresponding dust production rates are derived for the solar vicinity. From these rates and taking into account dust destruction by supernova shocks in the ISM, the contributions to the inventory of presolar dust grains in the solar system are derived for stars of different initial masses and metallicities. It is shown that stars on the first giant branch and the early AGB are not expected to form dust, in accord with astronomical observations. Dust formation is concentrated in the last phase of evolution, the thermally pulsing AGB. Due to the limited lifetime of dust grains in the ISM only parent stars from a narrow range of metallicities are expected to contribute to the population of presolar dust grains. Silicate and silicon carbide dust grains are predicted to come from parent stars with metallicities not less than about Z ∼ 0.008 (0.6 x solar). This metallicity limit is higher than that inferred from presolar SiC grain isotope data. The population of presolar carbon dust grains is predicted to originate from a wider range of metallicities, down to Z ∼ 0.004. Masses of AGB stars that produce C-rich dust are in the range

  4. Wind-Induced Reconfigurations in Flexible Branched Trees

    Science.gov (United States)

    Ojo, Oluwafemi; Shoele, Kourosh

    2017-11-01

    Wind induced stresses are the major mechanical cause of failure in trees. We know that the branching mechanism has an important effect on the stress distribution and stability of a tree in the wind. Eloy in PRL 2011, showed that Leonardo da Vinci's original observation which states the total cross section of branches is conserved across branching nodes is the best configuration for resisting wind-induced fracture in rigid trees. However, prediction of the fracture risk and pattern of a tree is also a function of their reconfiguration capabilities and how they mitigate large wind-induced stresses. In this studies through developing an efficient numerical simulation of flexible branched trees, we explore the role of the tree flexibility on the optimal branching. Our results show that the probability of a tree breaking at any point depends on both the cross-section changes in the branching nodes and the level of tree flexibility. It is found that the branching mechanism based on Leonardo da Vinci's original observation leads to a uniform stress distribution over a wide range of flexibilities but the pattern changes for more flexible systems.

  5. Prediction of adaptive self-regulatory responses to arthritis pain anxiety in exercising adults: does pain acceptance matter?

    Science.gov (United States)

    Cary, Miranda Ashley; Gyurcsik, Nancy C; Brawley, Lawrence R

    2015-01-01

    Exercising for ≥ 150 min/week is a recommended strategy for self-managing arthritis. However, exercise nonadherence is a problem. Arthritis pain anxiety may interfere with regular exercise. According to the fear-avoidance model, individuals may confront their pain anxiety by using adaptive self-regulatory responses (eg, changing exercise type or duration). Furthermore, the anxiety-self-regulatory responses relationship may vary as a function of individuals' pain acceptance levels. To investigate pain acceptance as a moderator of the pain anxiety-adaptive self-regulatory responses relationship. The secondary objective was to examine whether groups of patients who differed in meeting exercise recommendations also differed in pain-related and self-regulatory responses. Adults (mean [± SD] age 49.75 ± 13.88 years) with medically diagnosed arthritis completed online measures of arthritis pain-related variables and self-regulatory responses at baseline, and exercise participation two weeks later. Individuals meeting (n=87) and not meeting (n=49) exercise recommendations were identified. Hierarchical multiple regression analysis revealed that pain acceptance moderated the anxiety-adaptive self-regulatory responses relationship. When pain anxiety was lower, greater pain acceptance was associated with less frequent use of adaptive responses. When anxiety was higher, adaptive responses were used regardless of pain acceptance level. MANOVA findings revealed that participants meeting the recommended exercise dose reported significantly lower pain and pain anxiety, and greater pain acceptance (Pself-regulatory capacity to cope with additional challenges to exercise adherence (eg, busy schedule).

  6. The influence of branch order on optimal leaf vein geometries: Murray's law and area preserving branching.

    Directory of Open Access Journals (Sweden)

    Charles A Price

    Full Text Available Models that predict the form of hierarchical branching networks typically invoke optimization based on biomechanical similitude, the minimization of impedance to fluid flow, or construction costs. Unfortunately, due to the small size and high number of vein segments found in real biological networks, complete descriptions of networks needed to evaluate such models are rare. To help address this we report results from the analysis of the branching geometry of 349 leaf vein networks comprising over 1.5 million individual vein segments. In addition to measuring the diameters of individual veins before and after vein bifurcations, we also assign vein orders using the Horton-Strahler ordering algorithm adopted from the study of river networks. Our results demonstrate that across all leaves, both radius tapering and the ratio of daughter to parent branch areas for leaf veins are in strong agreement with the expectation from Murray's law. However, as veins become larger, area ratios shift systematically toward values expected under area-preserving branching. Our work supports the idea that leaf vein networks differentiate roles of leaf support and hydraulic supply between hierarchical orders.

  7. Linear and Branched PEIs (Polyethylenimines and Their Property Space

    Directory of Open Access Journals (Sweden)

    Claudiu N. Lungu

    2016-04-01

    Full Text Available A chemical property space defines the adaptability of a molecule to changing conditions and its interaction with other molecular systems determining a pharmacological response. Within a congeneric molecular series (compounds with the same derivatization algorithm and thus the same brute formula the chemical properties vary in a monotonic manner, i.e., congeneric compounds share the same chemical property space. The chemical property space is a key component in molecular design, where some building blocks are functionalized, i.e., derivatized, and eventually self-assembled in more complex systems, such as enzyme-ligand systems, of which (physico-chemical properties/bioactivity may be predicted by QSPR/QSAR (quantitative structure-property/activity relationship studies. The system structure is determined by the binding type (temporal/permanent; electrostatic/covalent and is reflected in its local electronic (and/or magnetic properties. Such nano-systems play the role of molecular devices, important in nano-medicine. In the present article, the behavior of polyethylenimine (PEI macromolecules (linear LPEI and branched BPEI, respectively with respect to the glucose oxidase enzyme GOx is described in terms of their (interacting energy, geometry and topology, in an attempt to find the best shape and size of PEIs to be useful for a chosen (nanochemistry purpose.

  8. Experimental studies on possible regulatory role of nitric oxide on the differential effects of chronic predictable and unpredictable stress on adaptive immune responses.

    Science.gov (United States)

    Thakur, Tarun; Gulati, Kavita; Rai, Nishant; Ray, Arunabha

    2017-09-01

    The present study was designed to investigate the effects of chronic predictable stress (CPS) and chronic unpredictable stress (CUS) on immunological responses in KLH-sensitized rats and involvement of NOergic signaling pathways mediating such responses. Male Wistar rats (200-250g) were exposed to either CPS or CUS for 14days and IgG antibody levels and delayed type hypersensitivity (DTH) response was determined to assess changes in adaptive immunity. To evaluate the role of nitric oxide during such immunomodulation, biochemical estimation of stable metabolite of nitric oxide (NOx) and 3-nitrotyrosine (3-NT, a marker of peroxynitrite formation) were done in both blood and brain. Chronic stress exposure resulted in suppression of IgG and DTH response and elevated NOx and 3-NT levels, with a difference in magnitude of response in CPS vs CUS. Pretreatment with aminoguanidine (iNOS inhibitor) caused further reduction of adaptive immune responses and attenuated the increased NOx and 3-NT levels in CPS or CUS exposed rats. On the other hand 7-NI (nNOS inhibitor) did not significantly affect these estimated parameters. The results suggest involvement of iNOS and lesser/no role of nNOS during modulation of adaptive immunity to stress. Thus, the result showed that predictability of stressors results in differential degree of modulation of immune responses and complex NO-mediated signaling mechanisms may be involved during responses. Copyright © 2017. Published by Elsevier B.V.

  9. Space plasma branch at NRL

    Science.gov (United States)

    The Naval Research Laboratory (Washington, D.C.) formed the Space Plasma Branch within its Plasma Physics Division on July 1. Vithal Patel, former Program Director of Magnetospheric Physics, National Science Foundation, also joined NRL on the same date as Associate Superintendent of the Plasma Physics Division. Barret Ripin is head of the newly organized branch. The Space Plasma branch will do basic and applied space plasma research using a multidisciplinary approach. It consolidates traditional rocket and satellite space experiments, space plasma theory and computation, with laboratory space-related experiments. About 40 research scientists, postdoctoral fellows, engineers, and technicians are divided among its five sections. The Theory and Computation sections are led by Joseph Huba and Joel Fedder, the Space Experiments section is led by Paul Rodriguez, and the Pharos Laser Facility and Laser Experiments sections are headed by Charles Manka and Jacob Grun.

  10. Coulomb branches with complex singularities

    Science.gov (United States)

    Argyres, Philip C.; Martone, Mario

    2018-06-01

    We construct 4d superconformal field theories (SCFTs) whose Coulomb branches have singular complex structures. This implies, in particular, that their Coulomb branch coordinate rings are not freely generated. Our construction also gives examples of distinct SCFTs which have identical moduli space (Coulomb, Higgs, and mixed branch) geometries. These SCFTs thus provide an interesting arena in which to test the relationship between moduli space geometries and conformal field theory data. We construct these SCFTs by gauging certain discrete global symmetries of N = 4 superYang-Mills (sYM) theories. In the simplest cases, these discrete symmetries are outer automorphisms of the sYM gauge group, and so these theories have lagrangian descriptions as N = 4 sYM theories with disconnected gauge groups.

  11. Branching pathways in the photocycle of bacteriorhodopsin

    International Nuclear Information System (INIS)

    Kalisky, O.; Ottolenghi, M.

    1982-01-01

    The pulsed laser photolysis of light-adapted bacteriorhodopsin (BR 570 ) is carried out between 25 C and -92 C in neutral and alkaline water-glycerol solutions. At relatively low temperatures the primary photoproduct K 610 equilibrates with a blue-shifted species, Ksub(p). Both K 610 and the new intermediate subsequently decay into another species, K'sub(p), in a process which competes with the formation of L 550 . Finally, K'sub(p) converts very slowly to L 550 . This branched pathway delays the formation of L 550 and thus of M 412 , without affecting the final yield of either species. A thermal back-reaction regenerating BR 570 takes place at the stage of L 550 , inhibiting the formation of M 412 . The reaction which also predominates at low temperatures, is relatively inefficient at high pH when the forward L 550 → M 412 step is highly catalyzed. It is the superposition of both these branching mechanisms which accounts for the complex effects of temperature and pH on the photocycle of BR 570 . The latter mechanism is accounted for by a molecular scheme in which deprotonation of a tyrosine moiety at the stage of L 550 constitutes a prerequisite for deprotonation of the retinal-lysine schiff-base as required for forming M 412 . This scheme appears to be directly related to the proton pump. (author)

  12. Comparison of adaptive neuro-fuzzy inference system (ANFIS) and Gaussian processes for machine learning (GPML) algorithms for the prediction of skin temperature in lower limb prostheses.

    Science.gov (United States)

    Mathur, Neha; Glesk, Ivan; Buis, Arjan

    2016-10-01

    Monitoring of the interface temperature at skin level in lower-limb prosthesis is notoriously complicated. This is due to the flexible nature of the interface liners used impeding the required consistent positioning of the temperature sensors during donning and doffing. Predicting the in-socket residual limb temperature by monitoring the temperature between socket and liner rather than skin and liner could be an important step in alleviating complaints on increased temperature and perspiration in prosthetic sockets. In this work, we propose to implement an adaptive neuro fuzzy inference strategy (ANFIS) to predict the in-socket residual limb temperature. ANFIS belongs to the family of fused neuro fuzzy system in which the fuzzy system is incorporated in a framework which is adaptive in nature. The proposed method is compared to our earlier work using Gaussian processes for machine learning. By comparing the predicted and actual data, results indicate that both the modeling techniques have comparable performance metrics and can be efficiently used for non-invasive temperature monitoring. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  13. A spatially-averaged mathematical model of kidney branching morphogenesis

    KAUST Repository

    Zubkov, V.S.

    2015-08-01

    © 2015 Published by Elsevier Ltd. Kidney development is initiated by the outgrowth of an epithelial ureteric bud into a population of mesenchymal cells. Reciprocal morphogenetic responses between these two populations generate a highly branched epithelial ureteric tree with the mesenchyme differentiating into nephrons, the functional units of the kidney. While we understand some of the mechanisms involved, current knowledge fails to explain the variability of organ sizes and nephron endowment in mice and humans. Here we present a spatially-averaged mathematical model of kidney morphogenesis in which the growth of the two key populations is described by a system of time-dependant ordinary differential equations. We assume that branching is symmetric and is invoked when the number of epithelial cells per tip reaches a threshold value. This process continues until the number of mesenchymal cells falls below a critical value that triggers cessation of branching. The mathematical model and its predictions are validated against experimentally quantified C57Bl6 mouse embryonic kidneys. Numerical simulations are performed to determine how the final number of branches changes as key system parameters are varied (such as the growth rate of tip cells, mesenchyme cells, or component cell population exit rate). Our results predict that the developing kidney responds differently to loss of cap and tip cells. They also indicate that the final number of kidney branches is less sensitive to changes in the growth rate of the ureteric tip cells than to changes in the growth rate of the mesenchymal cells. By inference, increasing the growth rate of mesenchymal cells should maximise branch number. Our model also provides a framework for predicting the branching outcome when ureteric tip or mesenchyme cells change behaviour in response to different genetic or environmental developmental stresses.

  14. A spatially-averaged mathematical model of kidney branching morphogenesis

    KAUST Repository

    Zubkov, V.S.; Combes, A.N.; Short, K.M.; Lefevre, J.; Hamilton, N.A.; Smyth, I.M.; Little, M.H.; Byrne, H.M.

    2015-01-01

    © 2015 Published by Elsevier Ltd. Kidney development is initiated by the outgrowth of an epithelial ureteric bud into a population of mesenchymal cells. Reciprocal morphogenetic responses between these two populations generate a highly branched epithelial ureteric tree with the mesenchyme differentiating into nephrons, the functional units of the kidney. While we understand some of the mechanisms involved, current knowledge fails to explain the variability of organ sizes and nephron endowment in mice and humans. Here we present a spatially-averaged mathematical model of kidney morphogenesis in which the growth of the two key populations is described by a system of time-dependant ordinary differential equations. We assume that branching is symmetric and is invoked when the number of epithelial cells per tip reaches a threshold value. This process continues until the number of mesenchymal cells falls below a critical value that triggers cessation of branching. The mathematical model and its predictions are validated against experimentally quantified C57Bl6 mouse embryonic kidneys. Numerical simulations are performed to determine how the final number of branches changes as key system parameters are varied (such as the growth rate of tip cells, mesenchyme cells, or component cell population exit rate). Our results predict that the developing kidney responds differently to loss of cap and tip cells. They also indicate that the final number of kidney branches is less sensitive to changes in the growth rate of the ureteric tip cells than to changes in the growth rate of the mesenchymal cells. By inference, increasing the growth rate of mesenchymal cells should maximise branch number. Our model also provides a framework for predicting the branching outcome when ureteric tip or mesenchyme cells change behaviour in response to different genetic or environmental developmental stresses.

  15. A modular function architecture for adaptive and predictive energy management in hybrid electric vehicles; Eine modulare Funktionsarchitektur fuer adaptives und vorausschauendes Energiemanagement in Hybridfahrzeugen

    Energy Technology Data Exchange (ETDEWEB)

    Wilde, Andreas

    2009-10-27

    Due to the relatively low energy density of electrical energy storage devices, the control strategy of hybrid electric vehicles has to fulfil a variety of requirements in order to provide both, the availability of hybrid functions, and their efficient execution. Energy consuming functions such as electric drive or electric boost need a high amount of energy stored in the battery. On the other hand for the optimum use of the energy regeneration function a lower state of charge is preferable in order to enable storage of the kinetic energy of the vehicle in all situations, including upon deceleration from high speeds or downhill driving. These diverging requirements yield a conflict of objectives for the charging strategy of hybrid electric vehicles. This work proposes a way to overcome the restrictions on efficiency in hybrid electric vehicles without deteriorating overall driving performance by charging or discharging the traction battery, and by setting the energy management parametres according to the current and forthcoming driving situation. Specific charging and electric drive strategies are presented for various driving situations which are identified by sensors such as navigation systems, cameras or radar. Necessary sensor data fusion methods for driving situation identification are described and a modular function architecture for predictive energy management is derived that is plug-and-play compatible with a broad fleet of vehicles. In order to evaluate its potential, this work also focuses on the simulation of the energy functions and their implementation into an experimental vehicle. This allows measurements under real traffic conditions and a sensivity analysis of the main module interactions within the architecture. (orig.)

  16. Additional chain-branching pathways in the low-temperature oxidation of branched alkanes

    KAUST Repository

    Wang, Zhandong

    2015-12-31

    Chain-branching reactions represent a general motif in chemistry, encountered in atmospheric chemistry, combustion, polymerization, and photochemistry; the nature and amount of radicals generated by chain-branching are decisive for the reaction progress, its energy signature, and the time towards its completion. In this study, experimental evidence for two new types of chain-branching reactions is presented, based upon detection of highly oxidized multifunctional molecules (HOM) formed during the gas-phase low-temperature oxidation of a branched alkane under conditions relevant to combustion. The oxidation of 2,5-dimethylhexane (DMH) in a jet-stirred reactor (JSR) was studied using synchrotron vacuum ultra-violet photoionization molecular beam mass spectrometry (SVUV-PI-MBMS). Specifically, species with four and five oxygen atoms were probed, having molecular formulas of C8H14O4 (e.g., diketo-hydroperoxide/keto-hydroperoxy cyclic ether) and C8H16O5 (e.g., keto-dihydroperoxide/dihydroperoxy cyclic ether), respectively. The formation of C8H16O5 species involves alternative isomerization of OOQOOH radicals via intramolecular H-atom migration, followed by third O2 addition, intramolecular isomerization, and OH release; C8H14O4 species are proposed to result from subsequent reactions of C8H16O5 species. The mechanistic pathways involving these species are related to those proposed as a source of low-volatility highly oxygenated species in Earth\\'s troposphere. At the higher temperatures relevant to auto-ignition, they can result in a net increase of hydroxyl radical production, so these are additional radical chain-branching pathways for ignition. The results presented herein extend the conceptual basis of reaction mechanisms used to predict the reaction behavior of ignition, and have implications on atmospheric gas-phase chemistry and the oxidative stability of organic substances. © 2015 The Combustion Institute.

  17. Modeling and simulation of adaptive Neuro-fuzzy based intelligent system for predictive stabilization in structured overlay networks

    Directory of Open Access Journals (Sweden)

    Ramanpreet Kaur

    2017-02-01

    Full Text Available Intelligent prediction of neighboring node (k well defined neighbors as specified by the dht protocol dynamism is helpful to improve the resilience and can reduce the overhead associated with topology maintenance of structured overlay networks. The dynamic behavior of overlay nodes depends on many factors such as underlying user’s online behavior, geographical position, time of the day, day of the week etc. as reported in many applications. We can exploit these characteristics for efficient maintenance of structured overlay networks by implementing an intelligent predictive framework for setting stabilization parameters appropriately. Considering the fact that human driven behavior usually goes beyond intermittent availability patterns, we use a hybrid Neuro-fuzzy based predictor to enhance the accuracy of the predictions. In this paper, we discuss our predictive stabilization approach, implement Neuro-fuzzy based prediction in MATLAB simulation and apply this predictive stabilization model in a chord based overlay network using OverSim as a simulation tool. The MATLAB simulation results present that the behavior of neighboring nodes is predictable to a large extent as indicated by the very small RMSE. The OverSim based simulation results also observe significant improvements in the performance of chord based overlay network in terms of lookup success ratio, lookup hop count and maintenance overhead as compared to periodic stabilization approach.

  18. A prediction model of ammonia emission from a fattening pig room based on the indoor concentration using adaptive neuro fuzzy inference system

    Energy Technology Data Exchange (ETDEWEB)

    Xie, Qiuju, E-mail: xqj197610@163.com [Institute of Information Technology, Heilongjiang Bayi Agricultural University, Daqing 163319 (China); Ni, Ji-qin [Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN 47907 (United States); Su, Zhongbin [Institute of Electric and Information, Northeast Agricultural University, Harbin 150030 (China)

    2017-03-05

    Highlights: • A prediction model of ammonia emission was built based on the indoor ammonia concentration prediction model using ANFIS. • Five kinds of membership functions were compared to get a well fitted prediction model. • Compared with the BP and MLRM model, the ANFIS prediction model with “gbell” membership function has the best performances. - Abstract: Ammonia (NH{sub 3}) is considered one of the significant pollutions contributor to indoor air quality and odor gas emission from swine house because of the negative impact on the health of pigs, the workers and local environment. Prediction models could provide a reasonable way for pig industries and environment regulatory to determine environment control strategies and give an effective method to evaluate the air quality. The adaptive neuro fuzzy inference system (ANFIS) simulates human’s vague thinking manner to solve the ambiguity and nonlinear problems which are difficult to be processed by conventional mathematics. Five kinds of membership functions were used to build a well fitted ANFIS prediction model. It was shown that the prediction model with “Gbell” membership function had the best capabilities among those five kinds of membership functions, and it had the best performances compared with backpropagation (BP) neuro network model and multiple linear regression model (MLRM) both in wintertime and summertime, the smallest value of mean square error (MSE), mean absolute percentage error (MAPE) and standard deviation (SD) are 0.002 and 0.0047, 31.1599 and 23.6816, 0.0564 and 0.0802, respectively, and the largest coefficients of determination (R{sup 2}) are 0.6351 and 0.6483, repectively. The ANFIS prediction model could be served as a beneficial strategy for the environment control system that has input parameters with highly fluctuating, complexity, and non-linear relationship.

  19. A prediction model of ammonia emission from a fattening pig room based on the indoor concentration using adaptive neuro fuzzy inference system

    International Nuclear Information System (INIS)

    Xie, Qiuju; Ni, Ji-qin; Su, Zhongbin

    2017-01-01

    Highlights: • A prediction model of ammonia emission was built based on the indoor ammonia concentration prediction model using ANFIS. • Five kinds of membership functions were compared to get a well fitted prediction model. • Compared with the BP and MLRM model, the ANFIS prediction model with “gbell” membership function has the best performances. - Abstract: Ammonia (NH_3) is considered one of the significant pollutions contributor to indoor air quality and odor gas emission from swine house because of the negative impact on the health of pigs, the workers and local environment. Prediction models could provide a reasonable way for pig industries and environment regulatory to determine environment control strategies and give an effective method to evaluate the air quality. The adaptive neuro fuzzy inference system (ANFIS) simulates human’s vague thinking manner to solve the ambiguity and nonlinear problems which are difficult to be processed by conventional mathematics. Five kinds of membership functions were used to build a well fitted ANFIS prediction model. It was shown that the prediction model with “Gbell” membership function had the best capabilities among those five kinds of membership functions, and it had the best performances compared with backpropagation (BP) neuro network model and multiple linear regression model (MLRM) both in wintertime and summertime, the smallest value of mean square error (MSE), mean absolute percentage error (MAPE) and standard deviation (SD) are 0.002 and 0.0047, 31.1599 and 23.6816, 0.0564 and 0.0802, respectively, and the largest coefficients of determination (R"2) are 0.6351 and 0.6483, repectively. The ANFIS prediction model could be served as a beneficial strategy for the environment control system that has input parameters with highly fluctuating, complexity, and non-linear relationship.

  20. Discriminating between adaptive and carcinogenic liver hypertrophy in rat studies using logistic ridge regression analysis of toxicogenomic data: The mode of action and predictive models.

    Science.gov (United States)

    Liu, Shujie; Kawamoto, Taisuke; Morita, Osamu; Yoshinari, Kouichi; Honda, Hiroshi

    2017-03-01

    Chemical exposure often results in liver hypertrophy in animal tests, characterized by increased liver weight, hepatocellular hypertrophy, and/or cell proliferation. While most of these changes are considered adaptive responses, there is concern that they may be associated with carcinogenesis. In this study, we have employed a toxicogenomic approach using a logistic ridge regression model to identify genes responsible for liver hypertrophy and hypertrophic hepatocarcinogenesis and to develop a predictive model for assessing hypertrophy-inducing compounds. Logistic regression models have previously been used in the quantification of epidemiological risk factors. DNA microarray data from the Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System were used to identify hypertrophy-related genes that are expressed differently in hypertrophy induced by carcinogens and non-carcinogens. Data were collected for 134 chemicals (72 non-hypertrophy-inducing chemicals, 27 hypertrophy-inducing non-carcinogenic chemicals, and 15 hypertrophy-inducing carcinogenic compounds). After applying logistic ridge regression analysis, 35 genes for liver hypertrophy (e.g., Acot1 and Abcc3) and 13 genes for hypertrophic hepatocarcinogenesis (e.g., Asns and Gpx2) were selected. The predictive models built using these genes were 94.8% and 82.7% accurate, respectively. Pathway analysis of the genes indicates that, aside from a xenobiotic metabolism-related pathway as an adaptive response for liver hypertrophy, amino acid biosynthesis and oxidative responses appear to be involved in hypertrophic hepatocarcinogenesis. Early detection and toxicogenomic characterization of liver hypertrophy using our models may be useful for predicting carcinogenesis. In addition, the identified genes provide novel insight into discrimination between adverse hypertrophy associated with carcinogenesis and adaptive hypertrophy in risk assessment. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. Genotyping by Sequencing and Genome–Environment Associations in Wild Common Bean Predict Widespread Divergent Adaptation to Drought

    Directory of Open Access Journals (Sweden)

    Andrés J. Cortés

    2018-02-01

    Full Text Available Drought will reduce global crop production by >10% in 2050 substantially worsening global malnutrition. Breeding for resistance to drought will require accessing crop genetic diversity found in the wild accessions from the driest high stress ecosystems. Genome–environment associations (GEA in crop wild relatives reveal natural adaptation, and therefore can be used to identify adaptive variation. We explored this approach in the food crop Phaseolus vulgaris L., characterizing 86 geo-referenced wild accessions using genotyping by sequencing (GBS to discover single nucleotide polymorphisms (SNPs. The wild beans represented Mesoamerica, Guatemala, Colombia, Ecuador/Northern Peru and Andean groupings. We found high polymorphism with a total of 22,845 SNPs across the 86 accessions that confirmed genetic relationships for the groups. As a second objective, we quantified allelic associations with a bioclimatic-based drought index using 10 different statistical models that accounted for population structure. Based on the optimum model, 115 SNPs in 90 regions, widespread in all 11 common bean chromosomes, were associated with the bioclimatic-based drought index. A gene coding for an ankyrin repeat-containing protein and a phototropic-responsive NPH3 gene were identified as potential candidates. Genomic windows of 1 Mb containing associated SNPs had more positive Tajima’s D scores than windows without associated markers. This indicates that adaptation to drought, as estimated by bioclimatic variables, has been under natural divergent selection, suggesting that drought tolerance may be favorable under dry conditions but harmful in humid conditions. Our work exemplifies that genomic signatures of adaptation are useful for germplasm characterization, potentially enhancing future marker-assisted selection and crop improvement.

  2. Bayesian prediction and adaptive sampling algorithms for mobile sensor networks online environmental field reconstruction in space and time

    CERN Document Server

    Xu, Yunfei; Dass, Sarat; Maiti, Tapabrata

    2016-01-01

    This brief introduces a class of problems and models for the prediction of the scalar field of interest from noisy observations collected by mobile sensor networks. It also introduces the problem of optimal coordination of robotic sensors to maximize the prediction quality subject to communication and mobility constraints either in a centralized or distributed manner. To solve such problems, fully Bayesian approaches are adopted, allowing various sources of uncertainties to be integrated into an inferential framework effectively capturing all aspects of variability involved. The fully Bayesian approach also allows the most appropriate values for additional model parameters to be selected automatically by data, and the optimal inference and prediction for the underlying scalar field to be achieved. In particular, spatio-temporal Gaussian process regression is formulated for robotic sensors to fuse multifactorial effects of observations, measurement noise, and prior distributions for obtaining the predictive di...

  3. A novel and simple test of gait adaptability predicts gold standard measures of functional mobility in stroke survivors.

    Science.gov (United States)

    Hollands, K L; Pelton, T A; van der Veen, S; Alharbi, S; Hollands, M A

    2016-01-01

    Although there is evidence that stroke survivors have reduced gait adaptability, the underlying mechanisms and the relationship to functional recovery are largely unknown. We explored the relationships between walking adaptability and clinical measures of balance, motor recovery and functional ability in stroke survivors. Stroke survivors (n=42) stepped to targets, on a 6m walkway, placed to elicit step lengthening, shortening and narrowing on paretic and non-paretic sides. The number of targets missed during six walks and target stepping speed was recorded. Fugl-Meyer (FM), Berg Balance Scale (BBS), self-selected walking speed (SWWS) and single support (SS) and step length (SL) symmetry (using GaitRite when not walking to targets) were also assessed. Stepwise multiple-linear regression was used to model the relationships between: total targets missed, number missed with paretic and non-paretic legs, target stepping speed, and each clinical measure. Regression revealed a significant model for each outcome variable that included only one independent variable. Targets missed by the paretic limb, was a significant predictor of FM (F(1,40)=6.54, p=0.014,). Speed of target stepping was a significant predictor of each of BBS (F(1,40)=26.36, padaptability is a clinically meaningful target for measurement and treatment of functionally adaptive walking ability in stroke survivors. Copyright © 2015 Elsevier B.V. All rights reserved.

  4. Predicting the impacts of climate change on animal distributions: the importance of local adaptation and species' traits

    Energy Technology Data Exchange (ETDEWEB)

    HELLMANN, J. J.; LOBO, N. F.

    2011-12-20

    The geographic range limits of many species are strongly affected by climate and are expected to change under global warming. For species that are able to track changing climate over broad geographic areas, we expect to see shifts in species distributions toward the poles and away from the equator. A number of ecological and evolutionary factors, however, could restrict this shifting or redistribution under climate change. These factors include restricted habitat availability, restricted capacity for or barriers to movement, or reduced abundance of colonists due the perturbation effect of climate change. This research project examined the last of these constraints - that climate change could perturb local conditions to which populations are adapted, reducing the likelihood that a species will shift its distribution by diminishing the number of potential colonists. In the most extreme cases, species ranges could collapse over a broad geographic area with no poleward migration and an increased risk of species extinction. Changes in individual species ranges are the processes that drive larger phenomena such as changes in land cover, ecosystem type, and even changes in carbon cycling. For example, consider the poleward range shift and population outbreaks of the mountain pine beetle that has decimated millions of acres of Douglas fir trees in the western US and Canada. Standing dead trees cause forest fires and release vast quantities of carbon to the atmosphere. The beetle likely shifted its range because it is not locally adapted across its range, and it appears to be limited by winter low temperatures that have steadily increased in the last decades. To understand range and abundance changes like the pine beetle, we must reveal the extent of adaptive variation across species ranges - and the physiological basis of that adaptation - to know if other species will change as readily as the pine beetle. Ecologists tend to assume that range shifts are the dominant

  5. Cash efficiency for bank branches.

    Science.gov (United States)

    Cabello, Julia García

    2013-01-01

    Bank liquidity management has become a major issue during the financial crisis as liquidity shortages have intensified and have put pressure on banks to diversity and improve their liquidity sources. While a significant strand of the literature concentrates on wholesale liquidity generation and on the alternative to deposit funding, the management of an inventory of cash holdings within the banks' branches is also a relevant issue as any significant improvement in cash management at the bank distribution channels may have a positive effect in reducing liquidity tensions. In this paper, we propose a simple programme of cash efficiency for the banks' branches, very easy to implement, which conform to a set of instructions to be imposed from the bank to their branches. This model proves to significantly reduce cash holdings at branches thereby providing efficiency improvements in liquidity management. The methodology we propose is based on the definition of some stochastic processes combined with renewal processes, which capture the random elements of the cash flow, before applying suitable optimization programmes to all the costs involved in cash movements. The classical issue of the Transaction Demand for the Cash and some aspects of Inventory Theory are also present. Mathematics Subject Classification (2000) C02, C60, E50.

  6. NCI: DCTD: Biometric Research Branch

    Science.gov (United States)

    The Biometric Research Branch (BRB) is the statistical and biomathematical component of the Division of Cancer Treatment, Diagnosis and Centers (DCTDC). Its members provide statistical leadership for the national and international research programs of the division in developmental therapeutics, developmental diagnostics, diagnostic imaging and clinical trials.

  7. Risk Factor Assessment Branch (RFAB)

    Science.gov (United States)

    The Risk Factor Assessment Branch (RFAB) focuses on the development, evaluation, and dissemination of high-quality risk factor metrics, methods, tools, technologies, and resources for use across the cancer research continuum, and the assessment of cancer-related risk factors in the population.

  8. Architecture, Assembly, and Emerging Applications of Branched Functional Polyelectrolytes and Poly(ionic liquid)s.

    Science.gov (United States)

    Xu, Weinan; Ledin, Petr A; Shevchenko, Valery V; Tsukruk, Vladimir V

    2015-06-17

    Branched polyelectrolytes with cylindrical brush, dendritic, hyperbranched, grafted, and star architectures bearing ionizable functional groups possess complex and unique assembly behavior in solution at surfaces and interfaces as compared to their linear counterparts. This review summarizes the recent developments in the introduction of various architectures and understanding of the assembly behavior of branched polyelectrolytes with a focus on functional polyelectrolytes and poly(ionic liquid)s with responsive properties. The branched polyelectrolytes and poly(ionic liquid)s interact electrostatically with small molecules, linear polyelectrolytes, or other branched polyelectrolytes to form assemblies of hybrid nanoparticles, multilayer thin films, responsive microcapsules, and ion-conductive membranes. The branched structures lead to unconventional assemblies and complex hierarchical structures with responsive properties as summarized in this review. Finally, we discuss prospectives for emerging applications of branched polyelectrolytes and poly(ionic liquid)s for energy harvesting and storage, controlled delivery, chemical microreactors, adaptive surfaces, and ion-exchange membranes.

  9. Refining a measure of brain injury sequelae to predict postacute rehabilitation outcome: rating scale analysis of the Mayo-Portland Adaptability Inventory.

    Science.gov (United States)

    Malec, J F; Moessner, A M; Kragness, M; Lezak, M D

    2000-02-01

    Evaluate the psychometric properties of the Mayo-Portland Adaptability Inventory (MPAI). Rating scale (Rasch) analysis of MPAI and principal component analysis of residuals; the predictive validity of the MPAI measures and raw scores was assessed in a sample from a day rehabilitation program. Outpatient brain injury rehabilitation. 305 persons with brain injury. A 22-item scale reflecting severity of sequelae of brain injury that contained a mix of indicators of impairment, activity, and participation was identified. Scores and measures for MPAI scales were strongly correlated and their predictive validities were comparable. Impairment, activity, and participation define a single dimension of brain injury sequelae. The MPAI shows promise as a measure of this construct.

  10. Application of Adaptive Neuro-Fuzzy Inference System for Prediction of Neutron Yield of IR-IECF Facility in High Voltages

    Science.gov (United States)

    Adineh-Vand, A.; Torabi, M.; Roshani, G. H.; Taghipour, M.; Feghhi, S. A. H.; Rezaei, M.; Sadati, S. M.

    2013-09-01

    This paper presents a soft computing based artificial intelligent technique, adaptive neuro-fuzzy inference system (ANFIS) to predict the neutron production rate (NPR) of IR-IECF device in wide discharge current and voltage ranges. A hybrid learning algorithm consists of back-propagation and least-squares estimation is used for training the ANFIS model. The performance of the proposed ANFIS model is tested using the experimental data using four performance measures: correlation coefficient, mean absolute error, mean relative error percentage (MRE%) and root mean square error. The obtained results show that the proposed ANFIS model has achieved good agreement with the experimental results. In comparison to the experimental data the proposed ANFIS model has MRE% training and testing data respectively. Therefore, this model can be used as an efficient tool to predict the NPR in the IR-IECF device.

  11. Module for the organization of a branch of the universal branch driver in the CAMAC standard

    International Nuclear Information System (INIS)

    Nguen Fuk; Smirnov, V.A.; Khmelevski, E.

    1976-01-01

    A module is elaborated for the organization of a branch of the universal branch driver in the CAMAC standard for the conjugation of a control crate trunk with a branch trunk. A block diagram of the module is described; its principal specifications are given. The universal branch driver system may accomodate up to 10 branch organization modules with one control source module

  12. Living on the edge: adaptive and plastic responses of the tree Nothofagus pumilio to a long-term transplant experiment predict rear-edge upward expansion.

    Science.gov (United States)

    Mathiasen, Paula; Premoli, Andrea C

    2016-06-01

    Current climate change affects the competitive ability and reproductive success of many species, leading to local extinctions, adjustment to novel local conditions by phenotypic plasticity or rapid adaptation, or tracking their optima through range shifts. However, many species have limited ability to expand to suitable areas. Altitudinal gradients, with abrupt changes in abiotic conditions over short distances, represent "natural experiments" for the evaluation of ecological and evolutionary responses under scenarios of climate change. Nothofagus pumilio is the tree species which dominates as pure stands the montane forests of Patagonia. We evaluated the adaptive value of variation in quantitative traits of N. pumilio under contrasting conditions of the altitudinal gradient with a long-term reciprocal transplant experimental design. While high-elevation plants show little response in plant, leaf, and phenological traits to the experimental trials, low-elevation ones show greater plasticity in their responses to changing environments, particularly at high elevation. Our results suggest a relatively reduced potential for evolutionary adaptation of high-elevation genotypes, and a greater evolutionary potential of low-elevation ones. Under global warming scenarios of forest upslope migration, high-elevation variants may be outperformed by low-elevation ones during this process, leading to the local extinction and/or replacement of these genotypes. These results challenge previous models and predictions expected under global warming for altitudinal gradients, on which the leading edge is considered to be the upper treeline forests.

  13. Prediction of the mass gain during high temperature oxidation of aluminized nanostructured nickel using adaptive neuro-fuzzy inference system

    Science.gov (United States)

    Hayati, M.; Rashidi, A. M.; Rezaei, A.

    2012-10-01

    In this paper, the applicability of ANFIS as an accurate model for the prediction of the mass gain during high temperature oxidation using experimental data obtained for aluminized nanostructured (NS) nickel is presented. For developing the model, exposure time and temperature are taken as input and the mass gain as output. A hybrid learning algorithm consists of back-propagation and least-squares estimation is used for training the network. We have compared the proposed ANFIS model with experimental data. The predicted data are found to be in good agreement with the experimental data with mean relative error less than 1.1%. Therefore, we can use ANFIS model to predict the performances of thermal systems in engineering applications, such as modeling the mass gain for NS materials.

  14. Spatial prediction of landslide susceptibility using an adaptive neuro-fuzzy inference system combined with frequency ratio, generalized additive model, and support vector machine techniques

    Science.gov (United States)

    Chen, Wei; Pourghasemi, Hamid Reza; Panahi, Mahdi; Kornejady, Aiding; Wang, Jiale; Xie, Xiaoshen; Cao, Shubo

    2017-11-01

    The spatial prediction of landslide susceptibility is an important prerequisite for the analysis of landslide hazards and risks in any area. This research uses three data mining techniques, such as an adaptive neuro-fuzzy inference system combined with frequency ratio (ANFIS-FR), a generalized additive model (GAM), and a support vector machine (SVM), for landslide susceptibility mapping in Hanyuan County, China. In the first step, in accordance with a review of the previous literature, twelve conditioning factors, including slope aspect, altitude, slope angle, topographic wetness index (TWI), plan curvature, profile curvature, distance to rivers, distance to faults, distance to roads, land use, normalized difference vegetation index (NDVI), and lithology, were selected. In the second step, a collinearity test and correlation analysis between the conditioning factors and landslides were applied. In the third step, we used three advanced methods, namely, ANFIS-FR, GAM, and SVM, for landslide susceptibility modeling. Subsequently, the results of their accuracy were validated using a receiver operating characteristic curve. The results showed that all three models have good prediction capabilities, while the SVM model has the highest prediction rate of 0.875, followed by the ANFIS-FR and GAM models with prediction rates of 0.851 and 0.846, respectively. Thus, the landslide susceptibility maps produced in the study area can be applied for management of hazards and risks in landslide-prone Hanyuan County.

  15. Next Day Building Load Predictions based on Limited Input Features Using an On-Line Laterally Primed Adaptive Resonance Theory Artificial Neural Network.

    Energy Technology Data Exchange (ETDEWEB)

    Jones, Christian Birk [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Photovoltaic and Grid Integration Group; Robinson, Matt [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Mechanical Engineering; Yasaei, Yasser [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Electrical and Computer Engineering; Caudell, Thomas [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Electrical and Computer Engineering; Martinez-Ramon, Manel [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Electrical and Computer Engineering; Mammoli, Andrea [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Mechanical Engineering

    2016-07-01

    Optimal integration of thermal energy storage within commercial building applications requires accurate load predictions. Several methods exist that provide an estimate of a buildings future needs. Methods include component-based models and data-driven algorithms. This work implemented a previously untested algorithm for this application that is called a Laterally Primed Adaptive Resonance Theory (LAPART) artificial neural network (ANN). The LAPART algorithm provided accurate results over a two month period where minimal historical data and a small amount of input types were available. These results are significant, because common practice has often overlooked the implementation of an ANN. ANN have often been perceived to be too complex and require large amounts of data to provide accurate results. The LAPART neural network was implemented in an on-line learning manner. On-line learning refers to the continuous updating of training data as time occurs. For this experiment, training began with a singe day and grew to two months of data. This approach provides a platform for immediate implementation that requires minimal time and effort. The results from the LAPART algorithm were compared with statistical regression and a component-based model. The comparison was based on the predictions linear relationship with the measured data, mean squared error, mean bias error, and cost savings achieved by the respective prediction techniques. The results show that the LAPART algorithm provided a reliable and cost effective means to predict the building load for the next day.

  16. Developing Predictive Approaches to Characterize Adaptive Responses of the Reproductive Endocrine Axis to Aromatase Inhibition: Computational Modeling

    Science.gov (United States)

    Exposure to endocrine disrupting chemicals can affect reproduction and development in both humans and wildlife. We developed a mechanistic mathematical model of the hypothalamic-pituitary-gonadal (HPG) axis in female fathead minnows to predict dose-response and time-course (DRTC)...

  17. Predicting Adaptive Response to Fadrozole Exposure:Computational Model of the Fathead MinnowsHypothalamic-Pituitary-Gonadal Axis

    Science.gov (United States)

    Exposure to endocrine disrupting chemicals can affect reproduction and development in both humans and wildlife. We are developing a mechanistic mathematical model of the hypothalamic-pituitary-gonadal (HPG) axis in female fathead minnows to predict doseresponse and time-course (...

  18. Predicting Adaptive Response to Fadrozole Exposure: Computational Model of the Fathead Minnow Hypothalamic-Pituitary-Gonadal Axis

    Science.gov (United States)

    Exposure to endocrine disrupting chemicals can affect reproduction and development in both humans and wildlife. We are developing a mechanistic mathematical model of the hypothalamic-pituitary-gonadal (HPG) axis in female fathead minnows to predict dose-response and time-course (...

  19. Discriminating between adaptive and carcinogenic liver hypertrophy in rat studies using logistic ridge regression analysis of toxicogenomic data: The mode of action and predictive models

    International Nuclear Information System (INIS)

    Liu, Shujie; Kawamoto, Taisuke; Morita, Osamu; Yoshinari, Kouichi; Honda, Hiroshi

    2017-01-01

    Chemical exposure often results in liver hypertrophy in animal tests, characterized by increased liver weight, hepatocellular hypertrophy, and/or cell proliferation. While most of these changes are considered adaptive responses, there is concern that they may be associated with carcinogenesis. In this study, we have employed a toxicogenomic approach using a logistic ridge regression model to identify genes responsible for liver hypertrophy and hypertrophic hepatocarcinogenesis and to develop a predictive model for assessing hypertrophy-inducing compounds. Logistic regression models have previously been used in the quantification of epidemiological risk factors. DNA microarray data from the Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System were used to identify hypertrophy-related genes that are expressed differently in hypertrophy induced by carcinogens and non-carcinogens. Data were collected for 134 chemicals (72 non-hypertrophy-inducing chemicals, 27 hypertrophy-inducing non-carcinogenic chemicals, and 15 hypertrophy-inducing carcinogenic compounds). After applying logistic ridge regression analysis, 35 genes for liver hypertrophy (e.g., Acot1 and Abcc3) and 13 genes for hypertrophic hepatocarcinogenesis (e.g., Asns and Gpx2) were selected. The predictive models built using these genes were 94.8% and 82.7% accurate, respectively. Pathway analysis of the genes indicates that, aside from a xenobiotic metabolism-related pathway as an adaptive response for liver hypertrophy, amino acid biosynthesis and oxidative responses appear to be involved in hypertrophic hepatocarcinogenesis. Early detection and toxicogenomic characterization of liver hypertrophy using our models may be useful for predicting carcinogenesis. In addition, the identified genes provide novel insight into discrimination between adverse hypertrophy associated with carcinogenesis and adaptive hypertrophy in risk assessment. - Highlights: • Hypertrophy (H) and hypertrophic

  20. Discriminating between adaptive and carcinogenic liver hypertrophy in rat studies using logistic ridge regression analysis of toxicogenomic data: The mode of action and predictive models

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Shujie; Kawamoto, Taisuke; Morita, Osamu [R& D, Safety Science Research, Kao Corporation, Tochigi (Japan); Yoshinari, Kouichi [Department of Molecular Toxicology, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka (Japan); Honda, Hiroshi, E-mail: honda.hiroshi@kao.co.jp [R& D, Safety Science Research, Kao Corporation, Tochigi (Japan)

    2017-03-01

    Chemical exposure often results in liver hypertrophy in animal tests, characterized by increased liver weight, hepatocellular hypertrophy, and/or cell proliferation. While most of these changes are considered adaptive responses, there is concern that they may be associated with carcinogenesis. In this study, we have employed a toxicogenomic approach using a logistic ridge regression model to identify genes responsible for liver hypertrophy and hypertrophic hepatocarcinogenesis and to develop a predictive model for assessing hypertrophy-inducing compounds. Logistic regression models have previously been used in the quantification of epidemiological risk factors. DNA microarray data from the Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System were used to identify hypertrophy-related genes that are expressed differently in hypertrophy induced by carcinogens and non-carcinogens. Data were collected for 134 chemicals (72 non-hypertrophy-inducing chemicals, 27 hypertrophy-inducing non-carcinogenic chemicals, and 15 hypertrophy-inducing carcinogenic compounds). After applying logistic ridge regression analysis, 35 genes for liver hypertrophy (e.g., Acot1 and Abcc3) and 13 genes for hypertrophic hepatocarcinogenesis (e.g., Asns and Gpx2) were selected. The predictive models built using these genes were 94.8% and 82.7% accurate, respectively. Pathway analysis of the genes indicates that, aside from a xenobiotic metabolism-related pathway as an adaptive response for liver hypertrophy, amino acid biosynthesis and oxidative responses appear to be involved in hypertrophic hepatocarcinogenesis. Early detection and toxicogenomic characterization of liver hypertrophy using our models may be useful for predicting carcinogenesis. In addition, the identified genes provide novel insight into discrimination between adverse hypertrophy associated with carcinogenesis and adaptive hypertrophy in risk assessment. - Highlights: • Hypertrophy (H) and hypertrophic

  1. Testing the adaptation to poverty-related stress model: predicting psychopathology symptoms in families facing economic hardship.

    Science.gov (United States)

    Wadsworth, Martha E; Raviv, Tali; Santiago, Catherine Decarlo; Etter, Erica M

    2011-01-01

    This study tested the Adaptation to Poverty-related Stress Model and its proposed relations between poverty-related stress, effortful and involuntary stress responses, and symptoms of psychopathology in an ethnically diverse sample of low-income children and their parents. Prospective Hierarchical Linear Modeling analyses conducted with 98 families (300 family members: 136 adults, 82 adolescents and preadolescents, 82 school-age children) revealed that, consistent with the model, primary and secondary control coping were protective against poverty-related stress primarily for internalizing symptoms. Conversely, disengagement coping exacerbated externalizing symptoms over time. In addition, involuntary engagement stress responses exacerbated the effects of poverty-related stress for internalizing symptoms, whereas involuntary disengagement responses exacerbated externalizing symptoms. Age and gender effects were found in most models, reflecting more symptoms of both types for parents than children and higher levels of internalizing symptoms for girls.

  2. BDC 500 branch driver controller

    CERN Document Server

    Dijksman, A

    1981-01-01

    This processor has been designed for very fast data acquisition and date pre-processing. The dataway and branch highway speeds have been optimized for approximately 1.5 mu sec. The internal processor cycle is approximately 0.8 mu sec. The standard version contains the following functions (slots): crate controller type A1; branch highway driver including terminator; serial I/O port (TTY, VDU); 24 bit ALU and 24 bit program counter; 16 bit memory address counter and 4 word stack; 4k bit memory for program and/or data; battery backup for the memory; CNAFD and crate LAM display; request/grant logic for time- sharing operation of several BDCs. The free slots can be equipped with e.g. extra RAM, computer interfaces, hardware multiplier/dividers, etc. (0 refs).

  3. An adaptive least-squares global sensitivity method and application to a plasma-coupled combustion prediction with parametric correlation

    Science.gov (United States)

    Tang, Kunkun; Massa, Luca; Wang, Jonathan; Freund, Jonathan B.

    2018-05-01

    We introduce an efficient non-intrusive surrogate-based methodology for global sensitivity analysis and uncertainty quantification. Modified covariance-based sensitivity indices (mCov-SI) are defined for outputs that reflect correlated effects. The overall approach is applied to simulations of a complex plasma-coupled combustion system with disparate uncertain parameters in sub-models for chemical kinetics and a laser-induced breakdown ignition seed. The surrogate is based on an Analysis of Variance (ANOVA) expansion, such as widely used in statistics, with orthogonal polynomials representing the ANOVA subspaces and a polynomial dimensional decomposition (PDD) representing its multi-dimensional components. The coefficients of the PDD expansion are obtained using a least-squares regression, which both avoids the direct computation of high-dimensional integrals and affords an attractive flexibility in choosing sampling points. This facilitates importance sampling using a Bayesian calibrated posterior distribution, which is fast and thus particularly advantageous in common practical cases, such as our large-scale demonstration, for which the asymptotic convergence properties of polynomial expansions cannot be realized due to computation expense. Effort, instead, is focused on efficient finite-resolution sampling. Standard covariance-based sensitivity indices (Cov-SI) are employed to account for correlation of the uncertain parameters. Magnitude of Cov-SI is unfortunately unbounded, which can produce extremely large indices that limit their utility. Alternatively, mCov-SI are then proposed in order to bound this magnitude ∈ [ 0 , 1 ]. The polynomial expansion is coupled with an adaptive ANOVA strategy to provide an accurate surrogate as the union of several low-dimensional spaces, avoiding the typical computational cost of a high-dimensional expansion. It is also adaptively simplified according to the relative contribution of the different polynomials to the total

  4. Application of adaptive neuro-fuzzy inference system techniques and artificial neural networks to predict solid oxide fuel cell performance in residential microgeneration installation

    Energy Technology Data Exchange (ETDEWEB)

    Entchev, Evgueniy; Yang, Libing [Integrated Energy Systems Laboratory, CANMET Energy Technology Centre, 1 Haanel Dr., Ottawa, Ontario (Canada)

    2007-06-30

    This study applies adaptive neuro-fuzzy inference system (ANFIS) techniques and artificial neural network (ANN) to predict solid oxide fuel cell (SOFC) performance while supplying both heat and power to a residence. A microgeneration 5 kW{sub el} SOFC system was installed at the Canadian Centre for Housing Technology (CCHT), integrated with existing mechanical systems and connected in parallel to the grid. SOFC performance data were collected during the winter heating season and used for training of both ANN and ANFIS models. The ANN model was built on back propagation algorithm as for ANFIS model a combination of least squares method and back propagation gradient decent method were developed and applied. Both models were trained with experimental data and used to predict selective SOFC performance parameters such as fuel cell stack current, stack voltage, etc. The study revealed that both ANN and ANFIS models' predictions agreed well with variety of experimental data sets representing steady-state, start-up and shut-down operations of the SOFC system. The initial data set was subjected to detailed sensitivity analysis and statistically insignificant parameters were excluded from the training set. As a result, significant reduction of computational time was achieved without affecting models' accuracy. The study showed that adaptive models can be applied with confidence during the design process and for performance optimization of existing and newly developed solid oxide fuel cell systems. It demonstrated that by using ANN and ANFIS techniques SOFC microgeneration system's performance could be modelled with minimum time demand and with a high degree of accuracy. (author)

  5. Use of a radioimmunoassay of plasma progesterone for predicting litter size and subsequent adaptation of feeding level in sheep

    International Nuclear Information System (INIS)

    Wiel, D.F.M. van de; Visscher, A.H.; Dekker, T.P.

    1976-01-01

    Litter sizes in ewes were predicted using the plasma progesterone concentration at 80-110 days after mating, with or without multiplication by bodyweight, as well as a priori probabilities and expected economic losses caused by incorrect classifications. Progesterone was assayed using a fluorimetric method and radioimmunoassay, and the results of both methods were compared in the Texel breed. Ewes were allotted to three feeding classes, according to the predicted litter sizes of 0-1, 2-3 and >=4 lambs. Using these classes the fluorimetric method gave 82.9% correct classifications, and the radioimmunoassay 80.0% correct. When calculated on the total of 194 ewes of the Finnish Landrace, Ile de France and Texel breeds, the fluorimetric method showed an accuracy of 65.0% correct classifications. (author)

  6. Branching geodesics in normed spaces

    International Nuclear Information System (INIS)

    Ivanov, A O; Tuzhilin, A A

    2002-01-01

    We study branching extremals of length functionals on normed spaces. This is a natural generalization of the Steiner problem in normed spaces. We obtain criteria for a network to be extremal under deformations that preserve the topology of networks as well as under deformations with splitting. We discuss the connection between locally shortest networks and extremal networks. In the important particular case of the Manhattan plane, we get a criterion for a locally shortest network to be extremal

  7. Cash efficiency for bank branches

    OpenAIRE

    Cabello, Julia Garc?a

    2013-01-01

    Bank liquidity management has become a major issue during the financial crisis as liquidity shortages have intensified and have put pressure on banks to diversity and improve their liquidity sources. While a significant strand of the literature concentrates on wholesale liquidity generation and on the alternative to deposit funding, the management of an inventory of cash holdings within the banks? branches is also a relevant issue as any significant improvement in cash management at the bank ...

  8. Solid State Photovoltaic Research Branch

    Energy Technology Data Exchange (ETDEWEB)

    1990-09-01

    This report summarizes the progress of the Solid State Photovoltaic Research Branch of the Solar Energy Research Institute (SERI) from October 1, 1988, through September 30,l 1989. Six technical sections of the report cover these main areas of SERIs in-house research: Semiconductor Crystal Growth, Amorphous Silicon Research, Polycrystalline Thin Films, III-V High-Efficiency Photovoltaic Cells, Solid-State Theory, and Laser Raman and Luminescence Spectroscopy. Sections have been indexed separately for inclusion on the data base.

  9. Strategy of Irrigation Branch in Russia

    Science.gov (United States)

    Zeyliger, A.; Ermolaeva, O.

    2012-04-01

    At this moment, at the starting time of the program on restoration of a large irrigation in Russia till 2020, the scientific and technical community of irrigation branch does not have clear vision on how to promote a development of irrigated agriculture and without repeating of mistakes having a place in the past. In many respects absence of a vision is connected to serious backlog of a scientific and technical and informational and technological level of development of domestic irrigation branch from advanced one. Namely such level of development is necessary for the resolving of new problems in new conditions of managing, and also for adequate answers to new challenges from climate and degradation of ground & water resources, as well as a rigorous requirement from an environment. In such important situation for irrigation branch when it is necessary quickly generate a scientific and technical politics for the current decade for maintenance of translation of irrigated agriculture in the Russian Federation on a new highly effective level of development, in our opinion, it is required to carry out open discussion of needs and requirements as well as a research for a adequate solutions. From political point of view a framework organized in FP6 DESIRE 037046 project is an example of good practice that can serve as methodical approach how to organize and develop such processes. From technical point of view a technology of operational management of irrigation at large scale presents a prospective alternative to the current type of management based on planning. From point of view ICT operational management demands creation of a new platform for the professional environment of activity. This platform should allow to perceive processes in real time, at their partial predictability on signals of a straight line and a feedback, within the framework of variability of decision making scenarious, at high resolution and the big ex-awning of sensor controls and the gauges

  10. Simple statistical model for branched aggregates

    DEFF Research Database (Denmark)

    Lemarchand, Claire; Hansen, Jesper Schmidt

    2015-01-01

    , given that it already has bonds with others. The model is applied here to asphaltene nanoaggregates observed in molecular dynamics simulations of Cooee bitumen. The variation with temperature of the probabilities deduced from this model is discussed in terms of statistical mechanics arguments....... The relevance of the statistical model in the case of asphaltene nanoaggregates is checked by comparing the predicted value of the probability for one molecule to have exactly i bonds with the same probability directly measured in the molecular dynamics simulations. The agreement is satisfactory......We propose a statistical model that can reproduce the size distribution of any branched aggregate, including amylopectin, dendrimers, molecular clusters of monoalcohols, and asphaltene nanoaggregates. It is based on the conditional probability for one molecule to form a new bond with a molecule...

  11. An ab initio/Rice-Ramsperger-Kassel-Marcus prediction of rate constant and product branching ratios for unimolecular decomposition of propen-2-ol and related H+CH2COHCH2 reaction

    Science.gov (United States)

    Zhou, Chong-Wen; Li, Ze-Rong; Liu, Cun-Xi; Li, Xiang-Yuan

    2008-12-01

    Enols have been found to be important intermediates in the combustion flames of hydrocarbon [C. A. Taatjes et al., Science 308, 1887 (2005)]. The removal mechanism of enols in combustion flame has not been established yet. In this work, the potential energy surface for the unimolecular decomposition of syn-propen-2-ol and H+CH2COHCH2 recombination reactions have been first investigated by CCSD(T) method. The barrier heights, reaction energies, and geometrical parameters of the reactants, products, intermediates, and transition states have been investigated theoretically. The results show that the formation of CH3CO+CH3 via the CH3COCH3 intermediate is dominant for the unimolecular decomposition of syn-propen-2-ol and its branching ratio is over 99% in the whole temperature range from 700 to 3000 K, and its rate constant can be expressed as an analytical form in the range of T =700-3000 K at atmospheric pressure. This can be attributed to the lower energy barrier of this channel compared to the other channels. The association reaction of H with CH2COHCH2 is shown to be a little more complicated than the unimolecular decomposition of syn-propen-2-ol. The channel leading to CH3CO+CH3 takes a key role in the whole temperature range at atmospheric pressure. However at the higher pressure of 100 atm, the recombination by direct formation of syn-propen-2-ol through H addition is important at T 1400 K, the recombination channel leading to CH3CO+CH3 turns out to be significant.

  12. Branching pathways in the photocycle of bacteriorhodopsin

    Energy Technology Data Exchange (ETDEWEB)

    Kalisky, O.; Ottolenghi, M. (Hebrew Univ., Jerusalem (Israel). Dept. of Physical Chemistry)

    1982-01-01

    The pulsed laser photolysis of light-adapted bacteriorhodopsin (BR/sub 570/) is carried out between 25 C and -92 C in neutral and alkaline water-glycerol solutions. At relatively low temperatures the primary photoproduct K/sub 610/ equilibrates with a blue-shifted species, Ksub(p). Both K/sub 610/ and the new intermediate subsequently decay into another species, K'sub(p), in a process which competes with the formation of L/sub 550/. Finally, K'sub(p) converts very slowly to L/sub 550/. This branched pathway delays the formation of L/sub 550/ and thus of M/sub 412/, without affecting the final yield of either species. A thermal back-reaction regenerating BR/sub 570/ takes place at the stage of L/sub 550/, inhibiting the formation of M/sub 412/. The reaction which also predominates at low temperatures, is relatively inefficient at high pH when the forward L/sub 550/ ..-->.. M/sub 412/ step is highly catalyzed. It is the superposition of both these branching mechanisms which accounts for the complex effects of temperature and pH on the photocycle of BR/sub 570/. The latter mechanism is accounted for by a molecular scheme in which deprotonation of a tyrosine moiety at the stage of L/sub 550/ constitutes a prerequisite for deprotonation of the retinal-lysine schiff-base as required for forming M/sub 412/. This scheme appears to be directly related to the proton pump.

  13. Prediction of monthly global solar radiation using adaptive neuro fuzzy inference system (ANFIS) technique over the state of Tamilnadu (India): a comparative study

    International Nuclear Information System (INIS)

    Sumithira, T. R.; Nirmal, Kumar A.

    2012-01-01

    Enormous potential of solar energy as a clean and pollution free source enrich the global power generation. India, being a tropical country, has high solar radiation and it lies to the north of equator between 8 degree 4' and 37 degree 6' North latitude and 68 degree 7' , and 97 degree 5' East longitude. In south india, Tamilnadu is located in the extreme south east with an average temperature of grater than 27.5 degree (> 81.5 F). In this study, an adaptive neuro-fuzzy inference system (ANFIS) based modelling approach to predict the monthly global solar radiation (MGSR) in Tamilnadu is presented using the real meteorological solar radiation data from the 31 districts of Tamilnadu with different latitude and longitude. The purpose of the study is to compare the accuracy of ANFIS and other soft computing models as found in literature to assess the solar radiation. The performance of the proposed model was tested and compared with other earth region in a case study. The statistical performance parameters such as root mean square error (RMSE), mean bias error (MBE), and coefficient of determination (R2) are presented and compared to validate the performance. The comparative test results prove the ANFIS based prediction are better than other models and furthermore proves its prediction capability for any geographical area with changing meteorological conditions. (author)

  14. Predicting intentions to consume functional foods and supplements to offset memory loss using an adaptation of protection motivation theory.

    Science.gov (United States)

    Cox, D N; Koster, A; Russell, C G

    2004-08-01

    The widespread use of dietary supplements and so-called 'functional foods' is thought to be partially motivated by self-control of health. However, whilst consumers want foods associated with well-being or disease prevention, they are unlikely to be willing to compromise on taste or technology. This presents a dilemma for promoters of functional foods. Middle-aged consumers' intentions to consume functional foods or supplements that may improve memory were tested within an adaptation of Protection Motivation theory (PMT). Participants evaluated text descriptions of four products described as: having an unpleasant bitter taste (Natural-FF); having 'additives' to reduce bitterness (Sweetened-FF); being genetically modified to enhance function (GM-FF) and Supplements. Participants were recruited as being of high and low perceived vulnerability to memory failure. In total, 290 middle-aged consumers (aged 40-60 years) participated in the study. Motivations to consume the GM-FF were the lowest. There were gender differences between intention to consume the supplements, Natural-FF and Sweetened-FF and product differences within genders. Women were less favourable than men in their attitudes towards genetic modification in general. Regression analyses indicated that PM predictors of intention to consume functional foods or supplements explained 59-63% of the variance (R2). Overall, perceived 'efficacy' (of the behaviour) and self-efficacy were the most important predictors of intentions to consume.

  15. Improved variable reduction in partial least squares modelling based on predictive-property-ranked variables and adaptation of partial least squares complexity.

    Science.gov (United States)

    Andries, Jan P M; Vander Heyden, Yvan; Buydens, Lutgarde M C

    2011-10-31

    The calibration performance of partial least squares for one response variable (PLS1) can be improved by elimination of uninformative variables. Many methods are based on so-called predictive variable properties, which are functions of various PLS-model parameters, and which may change during the variable reduction process. In these methods variable reduction is made on the variables ranked in descending order for a given variable property. The methods start with full spectrum modelling. Iteratively, until a specified number of remaining variables is reached, the variable with the smallest property value is eliminated; a new PLS model is calculated, followed by a renewed ranking of the variables. The Stepwise Variable Reduction methods using Predictive-Property-Ranked Variables are denoted as SVR-PPRV. In the existing SVR-PPRV methods the PLS model complexity is kept constant during the variable reduction process. In this study, three new SVR-PPRV methods are proposed, in which a possibility for decreasing the PLS model complexity during the variable reduction process is build in. Therefore we denote our methods as PPRVR-CAM methods (Predictive-Property-Ranked Variable Reduction with Complexity Adapted Models). The selective and predictive abilities of the new methods are investigated and tested, using the absolute PLS regression coefficients as predictive property. They were compared with two modifications of existing SVR-PPRV methods (with constant PLS model complexity) and with two reference methods: uninformative variable elimination followed by either a genetic algorithm for PLS (UVE-GA-PLS) or an interval PLS (UVE-iPLS). The performance of the methods is investigated in conjunction with two data sets from near-infrared sources (NIR) and one simulated set. The selective and predictive performances of the variable reduction methods are compared statistically using the Wilcoxon signed rank test. The three newly developed PPRVR-CAM methods were able to retain

  16. Predictive-property-ranked variable reduction in partial least squares modelling with final complexity adapted models: comparison of properties for ranking.

    Science.gov (United States)

    Andries, Jan P M; Vander Heyden, Yvan; Buydens, Lutgarde M C

    2013-01-14

    The calibration performance of partial least squares regression for one response (PLS1) can be improved by eliminating uninformative variables. Many variable-reduction methods are based on so-called predictor-variable properties or predictive properties, which are functions of various PLS-model parameters, and which may change during the steps of the variable-reduction process. Recently, a new predictive-property-ranked variable reduction method with final complexity adapted models, denoted as PPRVR-FCAM or simply FCAM, was introduced. It is a backward variable elimination method applied on the predictive-property-ranked variables. The variable number is first reduced, with constant PLS1 model complexity A, until A variables remain, followed by a further decrease in PLS complexity, allowing the final selection of small numbers of variables. In this study for three data sets the utility and effectiveness of six individual and nine combined predictor-variable properties are investigated, when used in the FCAM method. The individual properties include the absolute value of the PLS1 regression coefficient (REG), the significance of the PLS1 regression coefficient (SIG), the norm of the loading weight (NLW) vector, the variable importance in the projection (VIP), the selectivity ratio (SR), and the squared correlation coefficient of a predictor variable with the response y (COR). The selective and predictive performances of the models resulting from the use of these properties are statistically compared using the one-tailed Wilcoxon signed rank test. The results indicate that the models, resulting from variable reduction with the FCAM method, using individual or combined properties, have similar or better predictive abilities than the full spectrum models. After mean-centring of the data, REG and SIG, provide low numbers of informative variables, with a meaning relevant to the response, and lower than the other individual properties, while the predictive abilities are

  17. Online visual feedback during error-free channel trials leads to active unlearning of movement dynamics: evidence for adaptation to trajectory prediction errors.

    Directory of Open Access Journals (Sweden)

    Angel Lago-Rodriguez

    2016-09-01

    Full Text Available Prolonged exposure to movement perturbations leads to creation of motor memories which decay towards previous states when the perturbations are removed. However, it remains unclear whether this decay is due only to a spontaneous and passive recovery of the previous state. It has recently been reported that activation of reinforcement-based learning mechanisms delays the onset of the decay. This raises the question whether other motor learning mechanisms may also contribute to the retention and/or decay of the motor memory. Therefore, we aimed to test whether mechanisms of error-based motor adaptation are active during the decay of the motor memory. Forty-five right-handed participants performed point-to-point reaching movements under an external dynamic perturbation. We measured the expression of the motor memory through error-clamped (EC trials, in which lateral forces constrained movements to a straight line towards the target. We found greater and faster decay of the motor memory for participants who had access to full online visual feedback during these EC trials (Cursor group, when compared with participants who had no EC feedback regarding movement trajectory (Arc group. Importantly, we did not find between-group differences in adaptation to the external perturbation. In addition, we found greater decay of the motor memory when we artificially increased feedback errors through the manipulation of visual feedback (Augmented-Error group. Our results then support the notion of an active decay of the motor memory, suggesting that adaptive mechanisms are involved in correcting for the mismatch between predicted movement trajectories and actual sensory feedback, which leads to greater and faster decay of the motor memory.

  18. A Hybrid Approach Based on the Combination of Adaptive Neuro-Fuzzy Inference System and Imperialist Competitive Algorithm: Oil Flow Rate of the Wells Prediction Case Study

    Directory of Open Access Journals (Sweden)

    Shahram Mollaiy Berneti

    2013-04-01

    Full Text Available In this paper, a novel hybrid approach composed of adaptive neuro-fuzzy inference system (ANFIS and imperialist competitive algorithm is proposed. The imperialist competitive algorithm (ICA is used in this methodology to determine the most suitable initial membership functions of the ANFIS. The proposed model combines the global search ability of ICA with local search ability of gradient descent method. To illustrate the suitability and capability of the proposed model, this model is applied to predict oil flow rate of the wells utilizing data set of 31 wells in one of the northern Persian Gulf oil fields of Iran. The data set collected in a three month period for each well from Dec. 2002 to Nov. 2010. For the sake of performance evaluation, the results of the proposed model are compared with the conventional ANFIS model. The results show that the significant improvements are achievable using the proposed model in comparison with the results obtained by conventional ANFIS.

  19. A hybrid self-adaptive Particle Swarm Optimization–Genetic Algorithm–Radial Basis Function model for annual electricity demand prediction

    International Nuclear Information System (INIS)

    Yu, Shiwei; Wang, Ke; Wei, Yi-Ming

    2015-01-01

    Highlights: • A hybrid self-adaptive PSO–GA-RBF model is proposed for electricity demand prediction. • Each mixed-coding particle is composed by two coding parts of binary and real. • Five independent variables have been selected to predict future electricity consumption in Wuhan. • The proposed model has a simpler structure or higher estimating precision than other ANN models. • No matter what the scenario, the electricity consumption of Wuhan will grow rapidly. - Abstract: The present study proposes a hybrid Particle Swarm Optimization and Genetic Algorithm optimized Radial Basis Function (PSO–GA-RBF) neural network for prediction of annual electricity demand. In the model, each mixed-coding particle (or chromosome) is composed of two coding parts, binary and real, which optimizes the structure of the RBF by GA operation and the parameters of the basis and weights by a PSO–GA implementation. Five independent variables have been selected to predict future electricity consumption in Wuhan by using optimized networks. The results shows that (1) the proposed PSO–GA-RBF model has a simpler network structure (fewer hidden neurons) or higher estimation precision than other selected ANN models; and (2) no matter what the scenario, the electricity consumption of Wuhan will grow rapidly at average annual growth rates of about 9.7–11.5%. By 2020, the electricity demand in the planning scenario, the highest among the scenarios, will be 95.85 billion kW h. The lowest demand is estimated for the business-as-usual scenario, and will be 88.45 billion kW h

  20. Nonlinear predictive control for adaptive adjustments of deep brain stimulation parameters in basal ganglia-thalamic network.

    Science.gov (United States)

    Su, Fei; Wang, Jiang; Niu, Shuangxia; Li, Huiyan; Deng, Bin; Liu, Chen; Wei, Xile

    2018-02-01

    The efficacy of deep brain stimulation (DBS) for Parkinson's disease (PD) depends in part on the post-operative programming of stimulation parameters. Closed-loop stimulation is one method to realize the frequent adjustment of stimulation parameters. This paper introduced the nonlinear predictive control method into the online adjustment of DBS amplitude and frequency. This approach was tested in a computational model of basal ganglia-thalamic network. The autoregressive Volterra model was used to identify the process model based on physiological data. Simulation results illustrated the efficiency of closed-loop stimulation methods (amplitude adjustment and frequency adjustment) in improving the relay reliability of thalamic neurons compared with the PD state. Besides, compared with the 130Hz constant DBS the closed-loop stimulation methods can significantly reduce the energy consumption. Through the analysis of inter-spike-intervals (ISIs) distribution of basal ganglia neurons, the evoked network activity by the closed-loop frequency adjustment stimulation was closer to the normal state. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Pen Branch Delta and Savannah River Swamp Hydraulic Model

    International Nuclear Information System (INIS)

    Chen, K.F.

    1999-01-01

    The proposed Savannah River Site (SRS) Wetlands Restoration Project area is located in Barnwell County, South Carolina on the southwestern boundary of the SRS Reservation. The swamp covers about 40.5 km2 and is bounded to the west and south by the Savannah River and to the north and east by low bluffs at the edge of the Savannah River floodplain. Water levels within the swamp are determined by stage along the Savannah River, local drainage, groundwater seepage, and inflows from four tributaries, Beaver Dam Creek, Fourmile Branch, Pen Branch, and Steel Creek. Historic discharges of heated process water into these tributaries scoured the streambed, created deltas in the adjacent wetland, and killed native vegetation in the vicinity of the delta deposits. Future releases from these tributaries will be substantially smaller and closer to ambient temperatures. One component of the proposed restoration project will be to reestablish indigenous wetland vegetation on the Pen Branch delta that covers about 1.0 km2. Long-term predictions of water levels within the swamp are required to determine the characteristics of suitable plants. The objective of the study was to predict water levels at various locations within the proposed SRS Wetlands Restoration Project area for a range of Savannah River flows and regulated releases from Pen Branch. TABS-MD, a United States Army Corps of Engineer developed two-dimensional finite element open channel hydraulic computer code, was used to model the SRS swamp area for various flow conditions

  2. Genomic prediction accounting for genotype by environment interaction offers an effective framework for breeding simultaneously for adaptation to an abiotic stress and performance under normal cropping conditions in rice

    OpenAIRE

    Ahmadi, Nourollah; Cao, Tuong-Vi; Valé, Giampiero; Bartholomé, Jérôme; Hassen, Manel

    2018-01-01

    Developing rice varieties adapted to alternate wetting and drying water management is crucial for the sustainability of irrigated rice cropping systems. Here we report the first study exploring the feasibility of breeding rice for adaptation to alternate wetting and drying using genomic prediction methods that account for genotype by environment interactions. Two breeding populations (a reference panel of 284 accessions and a progeny population of 97 advanced lines) were evaluated under alter...

  3. Branched-Chain Amino Acids.

    Science.gov (United States)

    Yamamoto, Keisuke; Tsuchisaka, Atsunari; Yukawa, Hideaki

    Branched-chain amino acids (BCAAs), viz., L-isoleucine, L-leucine, and L-valine, are essential amino acids that cannot be synthesized in higher organisms and are important nutrition for humans as well as livestock. They are also valued as synthetic intermediates for pharmaceuticals. Therefore, the demand for BCAAs in the feed and pharmaceutical industries is increasing continuously. Traditional industrial fermentative production of BCAAs was performed using microorganisms isolated by random mutagenesis. A collection of these classical strains was also scientifically useful to clarify the details of the BCAA biosynthetic pathways, which are tightly regulated by feedback inhibition and transcriptional attenuation. Based on this understanding of the metabolism of BCAAs, it is now possible for us to pursue strains with higher BCAA productivity using rational design and advanced molecular biology techniques. Additionally, systems biology approaches using augmented omics information help us to optimize carbon flux toward BCAA production. Here, we describe the biosynthetic pathways of BCAAs and their regulation and then overview the microorganisms developed for BCAA production. Other chemicals, including isobutanol, i.e., a second-generation biofuel, can be synthesized by branching the BCAA biosynthetic pathways, which are also outlined.

  4. Analysis and adaptation of a mathematical model for the prediction of solar radiation; Analisis y adaptacion de un modelo matematico de prediccion de radiacion solar

    Energy Technology Data Exchange (ETDEWEB)

    Zambrano, Lorenzo [Instituto de Investigaciones Electricas, Cuernavaca (Mexico)

    1987-12-31

    There is an abundant, reliable, free, source of energy whose use can be planned and besides, practicably inexhaustible: the solar energy. In Mexico it constitutes an important resource, because of its geographical position; for this reason it is fundamental to know it well, either by means of measurements conducted for several years or by mathematical models. These last ones predict with meteorological variables, the values of the solar radiation with acceptable precision. At the Instituto de Investigaciones Electricas (IIE) a model is studied for the prediction of the solar radiation to be adapted to the local conditions of Mexico. It is used in simulation studies of the solar plants functioning and other solar systems. [Espanol] Existe una fuente de energia abundante, confiable, gratuita, cuyo uso puede planearse y, ademas, es practicamente inagotable: la solar. En Mexico constituye un recurso importante, por la posicion geografica del pais; por eso es fundamental conocerlo bien, ya mediante mediciones realizadas durante algunos anos, ya mediante modelos matematicos. Estos ultimos predicen, con datos de variables meteorologicas, los valores de la radiacion solar con precision aceptable. En el Instituto de Investigaciones Electricas (IIE) se estudia un modelo de prediccion de radiacion solar para adaptarlo a las condiciones locales de Mexico. Se usa en estudios de simulacion del funcionamiento de plantas helioelectricas y otros sistemas solares.

  5. Prediction of the Velocity Contours in Triangular Channel with Non-uniform Roughness Distributions by Adaptive Neuro-Fuzzy Inference System

    Directory of Open Access Journals (Sweden)

    Sara Bardestani

    2017-09-01

    Full Text Available Triangular channels have different applications in many water and wastewater engineering problems. For this purpose investigating hydraulic characteristics of flow in these sections has great importance. Researchers have presented different prediction methods for the velocity contours in prismatic sections. Most proposed methods are not able to consider the effect of walls roughness, the roughness distribution and secondary flows. However, due to complexity and nonlinearity of velocity contours in open channel flow, there is no simple relationship that can be fully able to exactly draw the velocity contours. In this paper an efficient approach for modeling velocity contours in triangular open channels with non-uniform roughness distributions by Adaptive Neuro-Fuzzy Inference System (ANFIS has been suggested. For training and testing model, the experimental data including 1703 data in triangular channels with geometric symmetry and non-uniform roughness distributions have been used. Comparing experimental results with predicted values by model indicates that ANFIS model is capable to be used in simulation of local velocity and determining velocity contours and the independent evaluation showed that the calculated values of discharge and depth-averaged velocity from model information are precisely in conformity with experimental values.

  6. A Novel Method for Predicting Late Genitourinary Toxicity After Prostate Radiation Therapy and the Need for Age-Based Risk-Adapted Dose Constraints

    International Nuclear Information System (INIS)

    Ahmed, Awad A.; Egleston, Brian; Alcantara, Pino; Li, Linna; Pollack, Alan; Horwitz, Eric M.; Buyyounouski, Mark K.

    2013-01-01

    Background: There are no well-established normal tissue sparing dose–volume histogram (DVH) criteria that limit the risk of urinary toxicity from prostate radiation therapy (RT). The aim of this study was to determine which criteria predict late toxicity among various DVH parameters when contouring the entire solid bladder and its contents versus the bladder wall. The area under the histogram curve (AUHC) was also analyzed. Methods and Materials: From 1993 to 2000, 503 men with prostate cancer received 3-dimensional conformal RT (median follow-up time, 71 months). The whole bladder and the bladder wall were contoured in all patients. The primary endpoint was grade ≥2 genitourinary (GU) toxicity occurring ≥3 months after completion of RT. Cox regressions of time to grade ≥2 toxicity were estimated separately for the entire bladder and bladder wall. Concordance probability estimates (CPE) assessed model discriminative ability. Before training the models, an external random test group of 100 men was set aside for testing. Separate analyses were performed based on the mean age (≤ 68 vs >68 years). Results: Age, pretreatment urinary symptoms, mean dose (entire bladder and bladder wall), and AUHC (entire bladder and bladder wall) were significant (P 68 years. Conclusion: The AUHC method based on bladder wall volumes was superior for predicting late GU toxicity. Age >68 years was associated with late grade ≥2 GU toxicity, which suggests that risk-adapted dose constraints based on age should be explored

  7. The implementation of two stages clustering (k-means clustering and adaptive neuro fuzzy inference system) for prediction of medicine need based on medical data

    Science.gov (United States)

    Husein, A. M.; Harahap, M.; Aisyah, S.; Purba, W.; Muhazir, A.

    2018-03-01

    Medication planning aim to get types, amount of medicine according to needs, and avoid the emptiness medicine based on patterns of disease. In making the medicine planning is still rely on ability and leadership experience, this is due to take a long time, skill, difficult to obtain a definite disease data, need a good record keeping and reporting, and the dependence of the budget resulted in planning is not going well, and lead to frequent lack and excess of medicines. In this research, we propose Adaptive Neuro Fuzzy Inference System (ANFIS) method to predict medication needs in 2016 and 2017 based on medical data in 2015 and 2016 from two source of hospital. The framework of analysis using two approaches. The first phase is implementing ANFIS to a data source, while the second approach we keep using ANFIS, but after the process of clustering from K-Means algorithm, both approaches are calculated values of Root Mean Square Error (RMSE) for training and testing. From the testing result, the proposed method with better prediction rates based on the evaluation analysis of quantitative and qualitative compared with existing systems, however the implementation of K-Means Algorithm against ANFIS have an effect on the timing of the training process and provide a classification accuracy significantly better without clustering.

  8. Analysis and adaptation of a mathematical model for the prediction of solar radiation; Analisis y adaptacion de un modelo matematico de prediccion de radiacion solar

    Energy Technology Data Exchange (ETDEWEB)

    Zambrano, Lorenzo [Instituto de Investigaciones Electricas, Cuernavaca (Mexico)

    1986-12-31

    There is an abundant, reliable, free, source of energy whose use can be planned and besides, practicably inexhaustible: the solar energy. In Mexico it constitutes an important resource, because of its geographical position; for this reason it is fundamental to know it well, either by means of measurements conducted for several years or by mathematical models. These last ones predict with meteorological variables, the values of the solar radiation with acceptable precision. At the Instituto de Investigaciones Electricas (IIE) a model is studied for the prediction of the solar radiation to be adapted to the local conditions of Mexico. It is used in simulation studies of the solar plants functioning and other solar systems. [Espanol] Existe una fuente de energia abundante, confiable, gratuita, cuyo uso puede planearse y, ademas, es practicamente inagotable: la solar. En Mexico constituye un recurso importante, por la posicion geografica del pais; por eso es fundamental conocerlo bien, ya mediante mediciones realizadas durante algunos anos, ya mediante modelos matematicos. Estos ultimos predicen, con datos de variables meteorologicas, los valores de la radiacion solar con precision aceptable. En el Instituto de Investigaciones Electricas (IIE) se estudia un modelo de prediccion de radiacion solar para adaptarlo a las condiciones locales de Mexico. Se usa en estudios de simulacion del funcionamiento de plantas helioelectricas y otros sistemas solares.

  9. Model-Based Evolution of a Fast Hybrid Fuzzy Adaptive Controller for a Pneumatic Muscle Actuator

    Directory of Open Access Journals (Sweden)

    Alexander Hošovský

    2012-07-01

    Full Text Available Pneumatic artificial muscle-based robotic systems usually necessitate the use of various nonlinear control techniques in order to improve their performance. Their robustness to parameter variation, which is generally difficult to predict, should also be tested. Here a fast hybrid adaptive control is proposed, where a conventional PD controller is placed into the feedforward branch and a fuzzy controller is placed into the adaptation branch. The fuzzy controller compensates for the actions of the PD controller under conditions of inertia moment variation. The fuzzy controller of Takagi-Sugeno type is evolved through a genetic algorithm using the dynamic model of a pneumatic muscle actuator. The results confirm the capability of the designed system to provide robust performance under the conditions of varying inertia.

  10. Vere-Jones' self-similar branching model

    International Nuclear Information System (INIS)

    Saichev, A.; Sornette, D.

    2005-01-01

    Motivated by its potential application to earthquake statistics as well as for its intrinsic interest in the theory of branching processes, we study the exactly self-similar branching process introduced recently by Vere-Jones. This model extends the ETAS class of conditional self-excited branching point-processes of triggered seismicity by removing the problematic need for a minimum (as well as maximum) earthquake size. To make the theory convergent without the need for the usual ultraviolet and infrared cutoffs, the distribution of magnitudes m ' of daughters of first-generation of a mother of magnitude m has two branches m ' ' >m with exponent β+d, where β and d are two positive parameters. We investigate the condition and nature of the subcritical, critical, and supercritical regime in this and in an extended version interpolating smoothly between several models. We predict that the distribution of magnitudes of events triggered by a mother of magnitude m over all generations has also two branches m ' ' >m with exponent β+h, with h=d√(1-s), where s is the fraction of triggered events. This corresponds to a renormalization of the exponent d into h by the hierarchy of successive generations of triggered events. For a significant part of the parameter space, the distribution of magnitudes over a full catalog summed over an average steady flow of spontaneous sources (immigrants) reproduces the distribution of the spontaneous sources with a single branch and is blind to the exponents β,d of the distribution of triggered events. Since the distribution of earthquake magnitudes is usually obtained with catalogs including many sequences, we conclude that the two branches of the distribution of aftershocks are not directly observable and the model is compatible with real seismic catalogs. In summary, the exactly self-similar Vere-Jones model provides an attractive new approach to model triggered seismicity, which alleviates delicate questions on the role of

  11. Quasiparticle branch mixing rates in superconducting aluminum

    International Nuclear Information System (INIS)

    Chi, C.C.; Clarke, J.

    1979-01-01

    The kinetic equation is used to compute the elastic and inelastic quasiparticle branch mixing rates for a superconducting film into which quasiparticles are injected via a tunnel barrier from a second superconducting film. Representative graphs are presented of the steady-state quasiparticle distribution, the quasiparticle charge imbalance Q* versus injection current, the charge relaxation rate tau -1 /sub Q/* vs Δ/k/sub B/T/sub c/ for several values of elastic scattering rate, and the quasiparticle branch relaxation rate tau -1 /sub Q/ as a function of energy. The quasiparticle potential developed in the injection film is related to tau -1 /sub Q/, and thence to tau -1 0 , a characteristic electron-phonon scattering time. Detailed measurements of tau/sub Q/ are reported for films of superconducting Al, some of which were doped with oxygen to give a range of transition temperatures from 1.2 to 2.1 K. From the dependence of tau -1 /sub Q/* on Δ/k/sub B/T/sub c/, values are deduced for the gap anisotropy of the films. In the cleanest samples, tau 0 or approx. = 2Δ) mean-free-path measurements, but a factor of about 4 smaller than that obtained from recombination time measurements and theoretical calculations. The value of tau -1 /sub o/ in the Al films increases with the transition temperature T/sub c/ as T 5 /sub c/ or T 6 /sub c/, instead of T 3 /sub c/ as predicted by simple theory. It is suggested that the rapid increase of tau -1 0 with T/sub c/ may arise from either a strong dependence of α 2 F (ω) on T/sub c/ or from a small concentration of magnetic impurities

  12. Adaptive neuro-fuzzy inference system (ANFIS) to predict CI engine parameters fueled with nano-particles additive to diesel fuel

    Science.gov (United States)

    Ghanbari, M.; Najafi, G.; Ghobadian, B.; Mamat, R.; Noor, M. M.; Moosavian, A.

    2015-12-01

    This paper studies the use of adaptive neuro-fuzzy inference system (ANFIS) to predict the performance parameters and exhaust emissions of a diesel engine operating on nanodiesel blended fuels. In order to predict the engine parameters, the whole experimental data were randomly divided into training and testing data. For ANFIS modelling, Gaussian curve membership function (gaussmf) and 200 training epochs (iteration) were found to be optimum choices for training process. The results demonstrate that ANFIS is capable of predicting the diesel engine performance and emissions. In the experimental step, Carbon nano tubes (CNT) (40, 80 and 120 ppm) and nano silver particles (40, 80 and 120 ppm) with nanostructure were prepared and added as additive to the diesel fuel. Six cylinders, four-stroke diesel engine was fuelled with these new blended fuels and operated at different engine speeds. Experimental test results indicated the fact that adding nano particles to diesel fuel, increased diesel engine power and torque output. For nano-diesel it was found that the brake specific fuel consumption (bsfc) was decreased compared to the net diesel fuel. The results proved that with increase of nano particles concentrations (from 40 ppm to 120 ppm) in diesel fuel, CO2 emission increased. CO emission in diesel fuel with nano-particles was lower significantly compared to pure diesel fuel. UHC emission with silver nano-diesel blended fuel decreased while with fuels that contains CNT nano particles increased. The trend of NOx emission was inverse compared to the UHC emission. With adding nano particles to the blended fuels, NOx increased compared to the net diesel fuel. The tests revealed that silver & CNT nano particles can be used as additive in diesel fuel to improve combustion of the fuel and reduce the exhaust emissions significantly.

  13. Ground Motion Prediction Model Using Adaptive Neuro-Fuzzy Inference Systems: An Example Based on the NGA-West 2 Data

    Science.gov (United States)

    Ameur, Mourad; Derras, Boumédiène; Zendagui, Djawed

    2018-03-01

    Adaptive neuro-fuzzy inference systems (ANFIS) are used here to obtain the robust ground motion prediction model (GMPM). Avoiding a priori functional form, ANFIS provides fully data-driven predictive models. A large subset of the NGA-West2 database is used, including 2335 records from 580 sites and 137 earthquakes. Only shallow earthquakes and recordings corresponding to stations with measured V s30 properties are selected. Three basics input parameters are chosen: the moment magnitude ( Mw), the Joyner-Boore distance ( R JB) and V s30. ANFIS model output is the peak ground acceleration (PGA), peak ground velocity (PGV) and 5% damped pseudo-spectral acceleration (PSA) at periods from 0.01 to 4 s. A procedure similar to the random-effects approach is developed to provide between- and within-event standard deviations. The total standard deviation (SD) varies between [0.303 and 0.360] (log10 units) depending on the period. The ground motion predictions resulting from such simple three explanatory variables ANFIS models are shown to be comparable to the most recent NGA results (e.g., Boore et al., in Earthquake Spectra 30:1057-1085, 2014; Derras et al., in Earthquake Spectra 32:2027-2056, 2016). The main advantage of ANFIS compared to artificial neuronal network (ANN) is its simple and one-off topology: five layers. Our results exhibit a number of physically sound features: magnitude scaling of the distance dependency, near-fault saturation distance increasing with magnitude and amplification on soft soils. The ability to implement ANFIS model using an analytic equation and Excel is demonstrated.

  14. Adaptive filtering and change detection

    CERN Document Server

    Gustafsson, Fredrik

    2003-01-01

    Adaptive filtering is a classical branch of digital signal processing (DSP). Industrial interest in adaptive filtering grows continuously with the increase in computer performance that allows ever more conplex algorithms to be run in real-time. Change detection is a type of adaptive filtering for non-stationary signals and is also the basic tool in fault detection and diagnosis. Often considered as separate subjects Adaptive Filtering and Change Detection bridges a gap in the literature with a unified treatment of these areas, emphasizing that change detection is a natural extensi

  15. ACPSEM (NZ Branch) annual meeting

    International Nuclear Information System (INIS)

    McEwan, A.C.

    1999-01-01

    The 1998 annual meeting of the New Zealand Branch of the Australasian College of Physical Scientists and Engineers in Medicine was held at the Christchurch School of Medicine over 26-27 November 1998, and attracted a record number of around 45 registrations. The meeting serves a number of purposes but one of the primary ones is to bring together scientists in medicine from around the country to compare notes on practices and advances, particularly in radiotherapy and diagnostic radiology physics. Following the meeting format established over recent years, separate workshops were devoted to radiotherapy physics and developments in the regional centres represented, and to practical issues relating to medical physics in diagnostic radiology. The workshops were held in parallel with presentations of scientific papers covering a wide range of topics, but with about half relating to engineering applications in medicine. (author)

  16. Branching process models of cancer

    CERN Document Server

    Durrett, Richard

    2015-01-01

    This volume develops results on continuous time branching processes and applies them to study rate of tumor growth, extending classic work on the Luria-Delbruck distribution. As a consequence, the authors calculate the probability that mutations that confer resistance to treatment are present at detection and quantify the extent of tumor heterogeneity. As applications, the authors evaluate ovarian cancer screening strategies and give rigorous proofs for results of Heano and Michor concerning tumor metastasis. These notes should be accessible to students who are familiar with Poisson processes and continuous time. Richard Durrett is mathematics professor at Duke University, USA. He is the author of 8 books, over 200 journal articles, and has supervised more than 40 Ph.D. students. Most of his current research concerns the applications of probability to biology: ecology, genetics, and most recently cancer.

  17. Vegetation survey of PEN Branch wetlands

    Energy Technology Data Exchange (ETDEWEB)

    1991-01-01

    A survey was conducted of vegetation along Pen Branch Creek at Savannah River Site (SRS) in support of K-Reactor restart. Plants were identified to species by overstory, understory, shrub, and groundcover strata. Abundance was also characterized and richness and diversity calculated. Based on woody species basal area, the Pen Branch delta was the most impacted, followed by the sections between the reactor and the delta. Species richness for shrub and groundcover strata were also lowest in the delta. No endangered plant species were found. Three upland pine areas were also sampled. In support of K Reactor restart, this report summarizes a study of the wetland vegetation along Pen Branch. Reactor effluent enters Indian Grove Branch and then flows into Pen Branch and the Pen Branch Delta.

  18. Field electron emission from branched nanotubes film

    International Nuclear Information System (INIS)

    Zeng Baoqing; Tian Shikai; Yang Zhonghai

    2005-01-01

    We describe the preparation and analyses of films composed of branched carbon nanotubes (CNTs). The CNTs were grown on a Ni catalyst film using chemical vapor deposition from a gas containing acetylene. From scanning electron microscope (SEM) and transmission electron microscope (TEM) analyses, the branched structure of the CNTs was determined; the field emission characteristics in a vacuum chamber indicated a lower turn on field for branched CNTs than normal CNTs

  19. Current perspectives on shoot branching regulation

    Directory of Open Access Journals (Sweden)

    Cunquan YUAN,Lin XI,Yaping KOU,Yu ZHAO,Liangjun ZHAO

    2015-03-01

    Full Text Available Shoot branching is regulated by the complex interactions among hormones, development, and environmental factors. Recent studies into the regulatory mecha-nisms of shoot branching have focused on strigolactones, which is a new area of investigation in shoot branching regulation. Elucidation of the function of the D53 gene has allowed exploration of detailed mechanisms of action of strigolactones in regulating shoot branching. In addition, the recent discovery that sucrose is key for axillary bud release has challenged the established auxin theory, in which auxin is the principal agent in the control of apical dominance. These developments increase our understan-ding of branching control and indicate that regulation of shoot branching involves a complex network. Here, we first summarize advances in the systematic regulatory network of plant shoot branching based on current information. Then we describe recent developments in the synthesis and signal transduction of strigolactones. Based on these considerations, we further summarize the plant shoot branching regulatory network, including long distance systemic signals and local gene activity mediated by strigolactones following perception of external envi-ronmental signals, such as shading, in order to provide a comprehensive overview of plant shoot branching.

  20. [Branches of the National Institute of Hygiene].

    Science.gov (United States)

    Gromulska, Marta

    2008-01-01

    National Epidemiological Institute (National Institute of Hygiene, from 7th September 1923) was established in 1918 in Warsaw and acted at national level. Its actions in the field of diseases combat were supported by bacteriological stations and vaccine production in voivodeship cities, which were taken charge of by the state, and names "National Epidemiological Institutes". According to the ministers resolution from 6th July 1921,Epidemiological Institutes were merged to National Central Epidemiological Institutes (PZH), the epidemiological institutes outside Warsaw were named branches, which were to be located in every voivodeship city, according to the initial organizational resolutions. There were country branches of NCEI in: Cracow, Lwów, Lódź, Toruń, Lublin, and Wilno in the period 1919-1923. New branches in Poznań (1925), Gdynia(1934), Katowice (Voivodeship Institute of Hygiene (1936), Luck (1937), Stanisławów (1937), Kielce(1938), and Brześć/Bug (Municipal Station acting as branch of National Central Epidemiological Institute. Branches were subordinated to NCEI-PZH) in Warsaw where action plans and unified research and diagnostic method were established and annual meeting of the country branches managers took place. All branches cooperated with hospitals, national health services, district general practitioners and administration structure in control of infectious diseases. In 1938, the post of branch inspector was established, the first of whom was Feliks Przesmycki PhD. Branches cooperated also with University of Cracow, University of Lwów and University of Wilno. In 1935, National Institutes of Food Research was incorporated in PZH, Water Department was established, and these areas of activity began to develop in the branches accordingly. In 1938 there were 13 branches of PZH, and each had three divisions: bacteriological, food research and water research. Three branches in Cracow, Kielce and Lublin worked during World War II under German

  1. An Extracellular Cell-Attached Pullulanase Confers Branched α-Glucan Utilization in Human Gut Lactobacillus acidophilus.

    Science.gov (United States)

    Møller, Marie S; Goh, Yong Jun; Rasmussen, Kasper Bøwig; Cypryk, Wojciech; Celebioglu, Hasan Ufuk; Klaenhammer, Todd R; Svensson, Birte; Abou Hachem, Maher

    2017-06-15

    Of the few predicted extracellular glycan-active enzymes, glycoside hydrolase family 13 subfamily 14 (GH13_14) pullulanases are the most common in human gut lactobacilli. These enzymes share a unique modular organization, not observed in other bacteria, featuring a catalytic module, two starch binding modules, a domain of unknown function, and a C-terminal surface layer association protein (SLAP) domain. Here, we explore the specificity of a representative of this group of pullulanases, Lactobacillus acidophilus Pul13_14 ( La Pul13_14), and its role in branched α-glucan metabolism in the well-characterized Lactobacillus acidophilus NCFM, which is widely used as a probiotic. Growth experiments with L. acidophilus NCFM on starch-derived branched substrates revealed a preference for α-glucans with short branches of about two to three glucosyl moieties over amylopectin with longer branches. Cell-attached debranching activity was measurable in the presence of α-glucans but was repressed by glucose. The debranching activity is conferred exclusively by La Pul13_14 and is abolished in a mutant strain lacking a functional La Pul13_14 gene. Hydrolysis kinetics of recombinant La Pul13_14 confirmed the preference for short-branched α-glucan oligomers consistent with the growth data. Curiously, this enzyme displayed the highest catalytic efficiency and the lowest K m reported for a pullulanase. Inhibition kinetics revealed mixed inhibition by β-cyclodextrin, suggesting the presence of additional glucan binding sites besides the active site of the enzyme, which may contribute to the unprecedented substrate affinity. The enzyme also displays high thermostability and higher activity in the acidic pH range, reflecting adaptation to the physiologically challenging conditions in the human gut. IMPORTANCE Starch is one of the most abundant glycans in the human diet. Branched α-1,6-glucans in dietary starch and glycogen are nondegradable by human enzymes and constitute a

  2. Molecular weight​/branching distribution modeling of low-​density-​polyethylene accounting for topological scission and combination termination in continuous stirred tank reactor

    NARCIS (Netherlands)

    Yaghini, N.; Iedema, P.D.

    2014-01-01

    We present a comprehensive model to predict the molecular weight distribution (MWD),(1) and branching distribution of low-density polyethylene (IdPE),(2) for free radical polymerization system in a continuous stirred tank reactor (CSTR).(3) The model accounts for branching, by branching moment or

  3. Compounded effects of heat waves and droughts over the Western Electricity Grid: spatio-temporal scales of impacts and predictability toward mitigation and adaptation.

    Science.gov (United States)

    Voisin, N.; Kintner-Meyer, M.; Skaggs, R.; Xie, Y.; Wu, D.; Nguyen, T. B.; Fu, T.; Zhou, T.

    2016-12-01

    Heat waves and droughts are projected to be more frequent and intense. We have seen in the past the effects of each of those extreme climate events on electricity demand and constrained electricity generation, challenging power system operations. Our aim here is to understand the compounding effects under historical conditions. We present a benchmark of Western US grid performance under 55 years of historical climate, and including droughts, using 2010-level of water demand and water management infrastructure, and 2010-level of electricity grid infrastructure and operations. We leverage CMIP5 historical hydrology simulations and force a large scale river routing- reservoir model with 2010-level sectoral water demands. The regulated flow at each water-dependent generating plants is processed to adjust water-dependent electricity generation parameterization in a production cost model, that represents 2010-level power system operations with hourly energy demand of 2010. The resulting benchmark includes a risk distribution of several grid performance metrics (unserved energy, production cost, carbon emission) as a function of inter-annual variability in regional water availability and predictability using large scale climate oscillations. In the second part of the presentation, we describe an approach to map historical heat waves onto this benchmark grid performance using a building energy demand model. The impact of the heat waves, combined with the impact of droughts, is explored at multiple scales to understand the compounding effects. Vulnerabilities of the power generation and transmission systems are highlighted to guide future adaptation.

  4. Reliable prediction of heat transfer coefficient in three-phase bubble column reactor via adaptive neuro-fuzzy inference system and regularization network

    Science.gov (United States)

    Garmroodi Asil, A.; Nakhaei Pour, A.; Mirzaei, Sh.

    2018-04-01

    In the present article, generalization performances of regularization network (RN) and optimize adaptive neuro-fuzzy inference system (ANFIS) are compared with a conventional software for prediction of heat transfer coefficient (HTC) as a function of superficial gas velocity (5-25 cm/s) and solid fraction (0-40 wt%) at different axial and radial locations. The networks were trained by resorting several sets of experimental data collected from a specific system of air/hydrocarbon liquid phase/silica particle in a slurry bubble column reactor (SBCR). A special convection HTC measurement probe was manufactured and positioned in an axial distance of 40 and 130 cm above the sparger at center and near the wall of SBCR. The simulation results show that both in-house RN and optimized ANFIS due to powerful noise filtering capabilities provide superior performances compared to the conventional software of MATLAB ANFIS and ANN toolbox. For the case of 40 and 130 cm axial distance from center of sparger, at constant superficial gas velocity of 25 cm/s, adding 40 wt% silica particles to liquid phase leads to about 66% and 69% increasing in HTC respectively. The HTC in the column center for all the cases studied are about 9-14% larger than those near the wall region.

  5. Branched-Chain Amino Acids

    Directory of Open Access Journals (Sweden)

    Matteo Ghiringhelli

    2015-07-01

    Full Text Available Our study is focused on evaluation and use of the most effective and correct nutrients. In particular, our attention is directed to the role of certain amino acids in cachectic patients. During parenteral nutrition in humans, physician already associates in the PN-bags different formulations including amino acids, lipids and glucose solutions or essential amino acids solution alone or exclusively branched-chain amino acids (BCAA. Studies investigated the effects of dietary BCAA ingestion on different diseases and conditions such as obesity and metabolic disorders, liver disease, muscle atrophy, cancer, impaired immunity or injuries (surgery, trauma, burns, and sepsis. BCAAs have been shown to affect gene expression, protein metabolism, apoptosis and regeneration of hepatocytes, and insulin resistance. They have also been shown to inhibit the proliferation of liver cancer cells in vitro, and are essential for lymphocyte proliferation and dendritic cell maturation. Oral or parenteral administration of these three amino acids will allow us to evaluate the real efficacy of these compounds during a therapy to treat malnutrition in subjects unable to feed themselves.

  6. AVM branch vibration test equipment

    International Nuclear Information System (INIS)

    Anne, J.P.

    1995-01-01

    An inventory of the test equipment of the AVM Branch ''Acoustic and Vibratory Mechanics Analysis Methods'' group has been undertaken. The purpose of this inventory is to enable better acquaintance with the technical characteristics of the equipment, providing an accurate definition of their functionalities, ad to inform potential users of the possibilities and equipment available in this field. The report first summarizes the various experimental surveys conduced. Then, using the AVM equipment database to draw up an exhaustive list of available equipment, it provides a full-scope picture of the vibration measurement systems (sensors, conditioners and exciters) and data processing resources commonly used on industrial sites and in laboratories. A definition is also given of a mobile test unit, called 'shelter', and a test bench used for the testing and performance rating of the experimental analysis methods developed by the group. The report concludes with a description of two fixed installations: - the calibration bench ensuring the requisite quality level for the vibration measurement systems ; - the training bench, whereby know-how acquired in the field in the field of measurement and experimental analysis processes is made available to others. (author). 27 refs., 15 figs., 2 appends

  7. Genomic Prediction Accounting for Genotype by Environment Interaction Offers an Effective Framework for Breeding Simultaneously for Adaptation to an Abiotic Stress and Performance Under Normal Cropping Conditions in Rice.

    Science.gov (United States)

    Ben Hassen, Manel; Bartholomé, Jérôme; Valè, Giampiero; Cao, Tuong-Vi; Ahmadi, Nourollah

    2018-05-09

    Developing rice varieties adapted to alternate wetting and drying water management is crucial for the sustainability of irrigated rice cropping systems. Here we report the first study exploring the feasibility of breeding rice for adaptation to alternate wetting and drying using genomic prediction methods that account for genotype by environment interactions. Two breeding populations (a reference panel of 284 accessions and a progeny population of 97 advanced lines) were evaluated under alternate wetting and drying and continuous flooding management systems. The predictive ability of genomic prediction for response variables (index of relative performance and the slope of the joint regression) and for multi-environment genomic prediction models were compared. For the three traits considered (days to flowering, panicle weight and nitrogen-balance index), significant genotype by environment interactions were observed in both populations. In cross validation, predictive ability for the index was on average lower (0.31) than that of the slope of the joint regression (0.64) whatever the trait considered. Similar results were found for progeny validation. Both cross-validation and progeny validation experiments showed that the performance of multi-environment models predicting unobserved phenotypes of untested entrees was similar to the performance of single environment models with differences in predictive ability ranging from -6% to 4% depending on the trait and on the statistical model concerned. The predictive ability of multi-environment models predicting unobserved phenotypes of entrees evaluated under both water management systems outperformed single environment models by an average of 30%. Practical implications for breeding rice for adaptation to alternate wetting and drying system are discussed. Copyright © 2018, G3: Genes, Genomes, Genetics.

  8. Geometrical scaling, furry branching and minijets

    International Nuclear Information System (INIS)

    Hwa, R.C.

    1988-01-01

    Scaling properties and their violations in hadronic collisions are discussed in the framework of the geometrical branching model. Geometrical scaling supplemented by Furry branching characterizes the soft component, while the production of jets specifies the hard component. Many features of multiparticle production processes are well described by this model. 21 refs

  9. Branching out Has So Much to Offer

    Science.gov (United States)

    Murray, Joe

    2012-01-01

    In 1989 there were thirty ATM branches nationally. In January 2012 there were just twelve ATM branches with another three "proposed". How can that happen? How did it happen? Maybe the most pertinent question is: Why did it happen? There is no single answer to the last question, but perhaps it was something to do with the changes that…

  10. Conformal branching rules and modular invariants

    International Nuclear Information System (INIS)

    Walton, M.A.

    1989-01-01

    Using the outer automorphisms of the affine algebra SU(n), we show how the branching rules for the conformal subalgebra SU(pq) contains SU(p) x SU(q) may be simply calculated. We demonstrate that new modular invariant combinations of SU(n) characters are obtainable from the branching rules. (orig.)

  11. Aeroacoustics of pipe systems with closed branches

    NARCIS (Netherlands)

    Tonon, D.; Hirschberg, A.; Golliard, J.; Ziada, S.

    2011-01-01

    Flow induced pulsations in resonant pipe networks with closed branches are considered in this review paper. These pulsations, observed in many technical applications, have been identified as self-sustained aeroacoustic oscillations driven by the instability of the flow along the closed branches. The

  12. Branching miter joints : principles and artwork

    NARCIS (Netherlands)

    Verhoeff, T.; Verhoeff, K.; Hart, G.W.; Sarhangi, R.

    2010-01-01

    A miter joint connects two beams, typically of the same cross section, at an angle such that the longitudinal beam edges continue across the joint. When more than two beams meet in one point, like in a tree, we call this a branching joint. In a branching miter joint, the beams’ longitudinal edges

  13. Branching bisimulation congruence for probabilistic systems

    NARCIS (Netherlands)

    Trcka, N.; Georgievska, S.; Aldini, A.; Baier, C.

    2008-01-01

    The notion of branching bisimulation for the alternating model of probabilistic systems is not a congruence with respect to parallel composition. In this paper we first define another branching bisimulation in the more general model allowing consecutive probabilistic transitions, and we prove that

  14. Prebiotic branched galacto-oligosaccharides (gos)

    NARCIS (Netherlands)

    Lammerts van Bueren-Brandt, Alica; Dijkhuizen, Lubbert

    2018-01-01

    The invention relates to galacto-oligosaccharide (GOS) compositions and the use thereof. Provided is the use of a GOS composition comprising branched and linear GOS species having a degree of polymerization (DP) of 3, wherein the branched DP3 GOS species are present in excess of linear DP3 GOS

  15. Two-phase flow through small branches in a horizontal pipe with stratified flow

    International Nuclear Information System (INIS)

    Smoglie, C.

    1985-02-01

    In the field of reactor safety the occurrence of a small break in a horizontal primary coolant pipe is of great importance. This report presents the description and results of experiments designed to determine the mass flow rate and quality through a small break at the bottom, the top or the side of a main pipe with stratified gas-liquid flow. If the interface level is far below (above) the branch, only single-phase gas (liquid) flow enters the branch. For smaller distances the interface is locally deformed because of the pressure decrease due to the fluid acceleration near the branch inlet (Bernoulli effect) and liquid (gas) can be entrained. This report contains photographs illustrating the flow phenomena as well as a general correlation to determine the beginning of entrainment. Results are presented on the branch mass flow rate and quality as a function of a normalized distance between the interface and the branch inlet. A model was developed which enables to predict the branch quality and mass flux. Results from air-water flow through horizontal branches, were extrapolated for steam water flow at high pressure with critical branch mass flux. (orig./HS) [de

  16. Two-phase flow through small branches in a horizontal pipe with stratified flow

    International Nuclear Information System (INIS)

    Smoglie, C.

    1984-12-01

    This report presents the description and results of experiments designed to determine the mass flow rate and quality through a small break at the bottom, the top or the side of a main pipe with stratified gas-liquid flow. If the interface level is far below (above) the branch, only single-phase gas (liquid) flow enters the branch. For smaller distances the interface is locally deformed because of the pressure decrease due to the fluid acceleration near the branch inlet (Bernoulli effect) and liquid (gas) can be entrained. This report contains photographs illustrating the flow phenomena as well as a general correlation to determine the beginning of entrainment. Results are presented on the branch mass flow rate and quality as a function of a normalized distance between the interface and the branch inlet. A model was developed which enables to predict the branch quality and mass flux. Results from air-water flow through horizontal branches, were extrapolated for steam water flow at high pressure with critical branch mass flux. (orig./HP) [de

  17. Behavioral Adaptation and Acceptance

    NARCIS (Netherlands)

    Martens, M.H.; Jenssen, G.D.

    2012-01-01

    One purpose of Intelligent Vehicles is to improve road safety, throughput, and emissions. However, the predicted effects are not always as large as aimed for. Part of this is due to indirect behavioral changes of drivers, also called behavioral adaptation. Behavioral adaptation (BA) refers to

  18. [Croatian Medical Association--Branch Zagreb].

    Science.gov (United States)

    Kaić, Zvonimir; Sain, Snjezana; Gulić, Mirjana; Mahovlić, Vjekoslav; Krznarić, Zeljko

    2014-01-01

    The available literature shows us that "Druztvo ljeciteljah u Zagrebus (the Society of Healers in Zagreb) was founded as far back as the year 1845 by a total of thirteen members. This data allows us to follow the role of doctors and health workers in Zagreb through their everyday profession, research, organizational and social work as well as management through a period of over one hundred to seventy years. The Branch Zagreb was active before the official establishment of subsidiaries of CMA which is evident from the minutes of the regular annual assembly of the Croatian Medical Association on 21 March 1948. Until the end of 1956, there was no clear division of labor, functions and competencies between the Branch and the Main Board. Their actions were instead consolidated and the Branch operated within and under the name of Croatian Medical Association. In that year the Branch became independent. The Branch Zagreb is the largest and one of the most active branches of the Croatian Medical Association. At the moment, the Branch brings together 3621 members, regular members--doctors of medicine (2497), doctors of dental medicine (384), retired physicians (710), and associate members (30 specialists with higher education who are not doctors). The Branch is especially accomplished in its activities in the area of professional development of its members and therefore organizes a series of scientific conferences in the framework of continuous education of physicians, allowing its members to acquire necessary points for the extension of their operating license. The choir "Zagrebacki lijecnici pjevaci" (Zagreb Physicians' Choir) of the Croatian Medical Music Society of the CMA and its activities are inseparable from the Branch Zagreb. The Branch is firmly linked to the parent body, the CMA, and thus has a visible impact on the strategy and the activities of the Association as a whole. Most professional societies of the CMA have their headquarters in Zagreb and this is

  19. Behavior of Steel Branch Connections during Fatigue Loading

    Directory of Open Access Journals (Sweden)

    Sládek A.

    2017-09-01

    Full Text Available Fatigue behavior of the branch connection made of low-alloyed steel with yield stress of 355 MPa during low-cycle bending test is investigated in the article. Numerical prediction of the stress and strain distribution are described and experimentally verified by fatigue test of the branch connection sample. Experimental verification is based on low-cycle bending testing of the steel pipes welded by manual metal arc process and loaded by external force in the appropriate distance. Stresses and displacement of the samples induced by bending moment were measured by unidirectional strain gauges and displacement transducers. Samples were loaded in different testing levels according to required stress for 2.106 cycles. Increase of the stress value was applied until the crack formation and growth was observed. Results showed a high agreement of numerical and experimental results of stress and displacement.

  20. EEG Theta Dynamics within Frontal and Parietal Cortices for Error Processing during Reaching Movements in a Prism Adaptation Study Altering Visuo-Motor Predictive Planning.

    Science.gov (United States)

    Arrighi, Pieranna; Bonfiglio, Luca; Minichilli, Fabrizio; Cantore, Nicoletta; Carboncini, Maria Chiara; Piccotti, Emily; Rossi, Bruno; Andre, Paolo

    2016-01-01

    Modulation of frontal midline theta (fmθ) is observed during error commission, but little is known about the role of theta oscillations in correcting motor behaviours. We investigate EEG activity of healthy partipants executing a reaching task under variable degrees of prism-induced visuo-motor distortion and visual occlusion of the initial arm trajectory. This task introduces directional errors of different magnitudes. The discrepancy between predicted and actual movement directions (i.e. the error), at the time when visual feedback (hand appearance) became available, elicits a signal that triggers on-line movement correction. Analysis were performed on 25 EEG channels. For each participant, the median value of the angular error of all reaching trials was used to partition the EEG epochs into high- and low-error conditions. We computed event-related spectral perturbations (ERSP) time-locked either to visual feedback or to the onset of movement correction. ERSP time-locked to the onset of visual feedback showed that fmθ increased in the high- but not in the low-error condition with an approximate time lag of 200 ms. Moreover, when single epochs were sorted by the degree of motor error, fmθ started to increase when a certain level of error was exceeded and, then, scaled with error magnitude. When ERSP were time-locked to the onset of movement correction, the fmθ increase anticipated this event with an approximate time lead of 50 ms. During successive trials, an error reduction was observed which was associated with indices of adaptations (i.e., aftereffects) suggesting the need to explore if theta oscillations may facilitate learning. To our knowledge this is the first study where the EEG signal recorded during reaching movements was time-locked to the onset of the error visual feedback. This allowed us to conclude that theta oscillations putatively generated by anterior cingulate cortex activation are implicated in error processing in semi-naturalistic motor

  1. Quantifying branch architecture of tropical trees using terrestrial LiDAR and 3D modelling

    NARCIS (Netherlands)

    Lau, Alvaro; Bentley, Lisa Patrick; Martius, Christopher; Shenkin, Alexander; Bartholomeus, Harm; Raumonen, Pasi; Malhi, Yadvinder; Jackson, Tobias; Herold, Martin

    2018-01-01

    Tree architecture is the three-dimensional arrangement of above ground parts of a tree. Ecologists hypothesize that the topology of tree branches represents optimized adaptations to tree’s environment. Thus, an accurate description of tree architecture leads to a better understanding of how form is

  2. Limit on $B_S^0\\to\\mu^+\\mu^-$ Branching Fraction

    CERN Document Server

    Chan, Wing Sheung

    2013-01-01

    A search for the decay Bs -> mu+mu- has been performed using proton-proton collisions recorded with the ATLAS detector at the LHC. The Standard Model predicts the time-integrated branching fraction for the decay to be extremely small. CLs tests method is used in extracting upper limit of the branching fraction from the experimental data. This report describes the two test methods used, the counting method and the mass fit method, and compares them.

  3. Randomized controlled trial to evaluate the effects of personalized prediction and adaptation tools on treatment outcome in outpatient psychotherapy: study protocol.

    Science.gov (United States)

    Lutz, Wolfgang; Zimmermann, Dirk; Müller, Viola N L S; Deisenhofer, Anne-Katharina; Rubel, Julian A

    2017-08-24

    Psychotherapy is successful for the majority of patients, but not for every patient. Hence, further knowledge is needed on how treatments should be adapted for those who do not profit or deteriorate. In the last years prediction tools as well as feedback interventions were part of a trend to more personalized approaches in psychotherapy. Research on psychometric prediction and feedback into ongoing treatment has the potential to enhance treatment outcomes, especially for patients with an increased risk of treatment failure or drop-out. The research project investigates in a randomized controlled trial the effectiveness as well as moderating and mediating factors of psychometric feedback to therapists. In the intended study a total of 423 patients, who applied for a cognitive-behavioral therapy at the psychotherapy clinic of the University Trier and suffer from a depressive and/or an anxiety disorder (SCID interviews), will be included. The patients will be randomly assigned either to one therapist as well as to one of two intervention groups (CG, IG2). An additional intervention group (IG1) will be generated from an existing archival data set via propensity score matching. Patients of the control group (CG; n = 85) will be monitored concerning psychological impairment but therapists will not be provided with any feedback about the patients assessments. In both intervention groups (IG1: n = 169; IG2: n = 169) the therapists are provided with feedback about the patients self-evaluation in a computerized feedback portal. Therapists of the IG2 will additionally be provided with clinical support tools, which will be developed in this project, on the basis of existing systems. Therapists will also be provided with a personalized treatment recommendation based on similar patients (Nearest Neighbors) at the beginning of treatment. Besides the general effectiveness of feedback and the clinical support tools for negatively developing patients, further mediating and

  4. The purpose of adaptation.

    Science.gov (United States)

    Gardner, Andy

    2017-10-06

    A central feature of Darwin's theory of natural selection is that it explains the purpose of biological adaptation. Here, I: emphasize the scientific importance of understanding what adaptations are for, in terms of facilitating the derivation of empirically testable predictions; discuss the population genetical basis for Darwin's theory of the purpose of adaptation, with reference to Fisher's 'fundamental theorem of natural selection'; and show that a deeper understanding of the purpose of adaptation is achieved in the context of social evolution, with reference to inclusive fitness and superorganisms.

  5. FY 1990 Applied Sciences Branch annual report

    Energy Technology Data Exchange (ETDEWEB)

    Keyes, B.M.; Dippo, P.C. (eds.)

    1991-11-01

    The Applied Sciences Branch actively supports the advancement of DOE/SERI goals for the development and implementation of the solar photovoltaic technology. The primary focus of the laboratories is to provide state-of-the-art analytical capabilities for materials and device characterization and fabrication. The branch houses a comprehensive facility which is capable of providing information on the full range of photovoltaic components. A major objective of the branch is to aggressively pursue collaborative research with other government laboratories, universities, and industrial firms for the advancement of photovoltaic technologies. Members of the branch disseminate research findings to the technical community in publications and presentations. This report contains information on surface and interface analysis, materials characterization, development, electro-optical characterization module testing and performance, surface interactions and FTIR spectroscopy.

  6. Code 672 observational science branch computer networks

    Science.gov (United States)

    Hancock, D. W.; Shirk, H. G.

    1988-01-01

    In general, networking increases productivity due to the speed of transmission, easy access to remote computers, ability to share files, and increased availability of peripherals. Two different networks within the Observational Science Branch are described in detail.

  7. Overview of the Advanced High Frequency Branch

    Science.gov (United States)

    Miranda, Felix A.

    2015-01-01

    This presentation provides an overview of the competencies, selected areas of research and technology development activities, and current external collaborative efforts of the NASA Glenn Research Center's Advanced High Frequency Branch.

  8. Star-Branched Polymers (Star Polymers)

    KAUST Repository

    Hirao, Akira; Hayashi, Mayumi; Ito, Shotaro; Goseki, Raita; Higashihara, Tomoya; Hadjichristidis, Nikolaos

    2015-01-01

    The synthesis of well-defined regular and asymmetric mixed arm (hereinafter miktoarm) star-branched polymers by the living anionic polymerization is reviewed in this chapter. In particular, much attention is being devoted to the synthetic

  9. Surface effects on the red giant branch

    Science.gov (United States)

    Ball, W. H.; Themeßl, N.; Hekker, S.

    2018-05-01

    Individual mode frequencies have been detected in thousands of individual solar-like oscillators on the red giant branch (RGB). Fitting stellar models to these mode frequencies, however, is more difficult than in main-sequence stars. This is partly because of the uncertain magnitude of the surface effect: the systematic difference between observed and modelled frequencies caused by poor modelling of the near-surface layers. We aim to study the magnitude of the surface effect in RGB stars. Surface effect corrections used for main-sequence targets are potentially large enough to put the non-radial mixed modes in RGB stars out of order, which is unphysical. Unless this can be circumvented, model-fitting of evolved RGB stars is restricted to the radial modes, which reduces the number of available modes. Here, we present a method to suppress gravity modes (g-modes) in the cores of our stellar models, so that they have only pure pressure modes (p-modes). We show that the method gives unbiased results and apply it to three RGB solar-like oscillators in double-lined eclipsing binaries: KIC 8410637, KIC 9540226 and KIC 5640750. In all three stars, the surface effect decreases the model frequencies consistently by about 0.1-0.3 μHz at the frequency of maximum oscillation power νmax, which agrees with existing predictions from three-dimensional radiation hydrodynamics simulations. Though our method in essence discards information about the stellar cores, it provides a useful step forward in understanding the surface effect in RGB stars.

  10. Branch retinal artery occlusion in Susac's syndrome

    Directory of Open Access Journals (Sweden)

    Ricardo Evangelista Marrocos de Aragão

    2015-02-01

    Full Text Available Susac's syndrome is a rare disease attribuited to a microangiopathy involving the arterioles of the cochlea, retina and brain. Encefalopathy, hearing loss, and visual deficits are the hallmarks of the disease. Visual loss is due to multiple, recurrent branch arterial retinal occlusions. We report a case of a 20-year-old women with Susac syndrome presented with peripheral vestibular syndrome, hearing loss, ataxia, vertigo, and vision loss due occlusion of the retinal branch artery.

  11. AGB [asymptotic giant branch]: Star evolution

    International Nuclear Information System (INIS)

    Becker, S.A.

    1987-01-01

    Asymptotic giant branch stars are red supergiant stars of low-to-intermediate mass. This class of stars is of particular interest because many of these stars can have nuclear processed material brought up repeatedly from the deep interior to the surface where it can be observed. A review of recent theoretical and observational work on stars undergoing the asymptotic giant branch phase is presented. 41 refs

  12. Multiprogrammation fast branch driver for microcomputer MICRAL

    International Nuclear Information System (INIS)

    Kaiser, Josef; Lacroix, Jean.

    1975-01-01

    This branch driver allows in association with the FIFO memories of the microcomputer Micral, very fast exchanges with the 7 crates of a CAMAC branch. A CAMAC programm (command, test, read, write) is loaded in the 1K FIFO buffer of the Micral before execution time and executed in sequence at a rate of 1,5μs per CAMAC command. After programm execution, data may be transferred directly on a magnetic tape [fr

  13. Joint switched transmit diversity and adaptive modulation in spectrum sharing systems

    KAUST Repository

    Qaraqe, Khalid A.; Bouida, Zied; Abdallah, Mohamed M.; Alouini, Mohamed-Slim

    2011-01-01

    Under the scenario of an underlay cognitive radio network, we propose in this paper an adaptive scheme using switched transmit diversity and adaptive modulation in order to minimize the average number of switched branches at the secondary

  14. Conformations and solution properties of star-branched polyelectrolytes

    NARCIS (Netherlands)

    Borisov, O.V.; Zhulina, E.B.; Leermakers, F.A.M.; Ballauff, M.; Muller, A.H.E.

    2011-01-01

    Aqueous solutions of star-like polyelectrolytes (PEs) exhibit distinctive features that originate from the topological complexity of branched macromolecules. In a salt-free solution of branched PEs, mobile counterions preferentially localize in the intramolecular volume of branched macroions.

  15. All change at the CERN UBS branch

    CERN Multimedia

    Antonella Del Rosso

    2012-01-01

    UBS branches across the country are being modernised, and the CERN branch is no exception. The Bulletin brings you a preview of the project, which will get under way in January 2013.   Mock-up of the renovated UBS branch. The changes at the UBS branch in CERN's Main Building will be no simple facelift. The entire bank will be renovated, transforming the present relatively confined premises into an open and attractive area. "The renovation of the UBS branches is part of a wider campaign designed to further enhance our customer relations," explains Ezio Mangia, the head of the CERN branch.  The UBS bank currently occupies three sets of premises in CERN's Main Building (two on the ground floor and one in the basement). "By the end of the work, which is scheduled to be completed by the middle of next year, CERN customers will benefit from a new area with open-plan counters and "hole-in-the-wall" machines accessible to...

  16. Quantifying the Adaptive Cycle.

    Directory of Open Access Journals (Sweden)

    David G Angeler

    Full Text Available The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994-2011 data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.

  17. Adaptive management

    DEFF Research Database (Denmark)

    Rist, Lucy; Campbell, Bruce Morgan; Frost, Peter

    2013-01-01

    Adaptive management (AM) emerged in the literature in the mid-1970s in response both to a realization of the extent of uncertainty involved in management, and a frustration with attempts to use modelling to integrate knowledge and make predictions. The term has since become increasingly widely used...... in scientific articles, policy documents and management plans, but both understanding and application of the concept is mixed. This paper reviews recent literature from conservation and natural resource management journals to assess diversity in how the term is used, highlight ambiguities and consider how...... the concept might be further assessed. AM is currently being used to describe many different management contexts, scales and locations. Few authors define the term explicitly or describe how it offers a means to improve management outcomes in their specific management context. Many do not adhere to the idea...

  18. EEG Theta Dynamics within Frontal and Parietal Cortices for Error Processing during Reaching Movements in a Prism Adaptation Study Altering Visuo-Motor Predictive Planning.

    Directory of Open Access Journals (Sweden)

    Pieranna Arrighi

    Full Text Available Modulation of frontal midline theta (fmθ is observed during error commission, but little is known about the role of theta oscillations in correcting motor behaviours. We investigate EEG activity of healthy partipants executing a reaching task under variable degrees of prism-induced visuo-motor distortion and visual occlusion of the initial arm trajectory. This task introduces directional errors of different magnitudes. The discrepancy between predicted and actual movement directions (i.e. the error, at the time when visual feedback (hand appearance became available, elicits a signal that triggers on-line movement correction. Analysis were performed on 25 EEG channels. For each participant, the median value of the angular error of all reaching trials was used to partition the EEG epochs into high- and low-error conditions. We computed event-related spectral perturbations (ERSP time-locked either to visual feedback or to the onset of movement correction. ERSP time-locked to the onset of visual feedback showed that fmθ increased in the high- but not in the low-error condition with an approximate time lag of 200 ms. Moreover, when single epochs were sorted by the degree of motor error, fmθ started to increase when a certain level of error was exceeded and, then, scaled with error magnitude. When ERSP were time-locked to the onset of movement correction, the fmθ increase anticipated this event with an approximate time lead of 50 ms. During successive trials, an error reduction was observed which was associated with indices of adaptations (i.e., aftereffects suggesting the need to explore if theta oscillations may facilitate learning. To our knowledge this is the first study where the EEG signal recorded during reaching movements was time-locked to the onset of the error visual feedback. This allowed us to conclude that theta oscillations putatively generated by anterior cingulate cortex activation are implicated in error processing in semi

  19. Measurement of the inclusive charmless and double-charm B branching ratios

    CERN Document Server

    Abreu, P; Adye, T; Adzic, P; Alekseev, G D; Alemany, R; Allport, P P; Almehed, S; Amaldi, Ugo; Amato, S; Andersson, P; Andreazza, A; Antilogus, P; Apel, W D; Arnoud, Y; Åsman, B; Augustin, J E; Augustinus, A; Baillon, Paul; Bambade, P; Barão, F; Barbier, R; Bardin, Dimitri Yuri; Barker, G; Baroncelli, A; Bärring, O; Bates, M J; Battaglia, Marco; Baubillier, M; Becks, K H; Begalli, M; Beillière, P; Belokopytov, Yu A; Belous, K S; Benvenuti, Alberto C; Bérat, C; Berggren, M; Bertini, D; Bertrand, D; Besançon, M; Bianchi, F; Bigi, M; Bilenky, S M; Billoir, P; Bizouard, M A; Bloch, D; Bonesini, M; Bonivento, W; Boonekamp, M; Booth, P S L; Borgland, A W; Borisov, G; Bosio, C; Botner, O; Boudinov, E; Bouquet, B; Bourdarios, C; Bowcock, T J V; Bozovic, I; Bozzo, M; Branchini, P; Brand, K D; Brenke, T; Brenner, R A; Brown, R; Brückman, P; Brunet, J M; Bugge, L; Buran, T; Burgsmüller, T; Buschmann, P; Cabrera, S; Caccia, M; Calvi, M; Camacho-Rozas, A J; Camporesi, T; Canale, V; Canepa, M; Carena, F; Carroll, L; Caso, Carlo; Castillo-Gimenez, M V; Cattai, A; Cavallo, F R; Cerruti, C; Chabaud, V; Chapkin, M M; Charpentier, P; Chaussard, L; Checchia, P; Chelkov, G A; Chen, M; Chierici, R; Chliapnikov, P V; Chochula, P; Chorowicz, V; Chudoba, J; Collins, P; Colomer, M; Contri, R; Cortina, E; Cosme, G; Cossutti, F; Cowell, J H; Crawley, H B; Crennell, D J; Crosetti, G; Cuevas-Maestro, J; Czellar, S; D'Almagne, B; Damgaard, G; Dauncey, P D; Davenport, Martyn; Da Silva, W; Deghorain, A; Della Ricca, G; Delpierre, P A; Demaria, N; De Angelis, A; de Boer, Wim; De Brabandere, S; De Clercq, C; La Vaissière, C de; De Lotto, B; De Min, A; De Paula, L S; Dijkstra, H; Di Ciaccio, Lucia; Di Diodato, A; Djannati, A; Dolbeau, J; Doroba, K; Dracos, M; Drees, J; Drees, K A; Dris, M; Duperrin, A; Durand, J D; Edsall, D M; Ehret, R; Eigen, G; Ekelöf, T J C; Ekspong, Gösta; Ellert, M; Elsing, M; Engel, J P; Erzen, B; Espirito-Santo, M C; Falk, E; Fanourakis, G K; Fassouliotis, D; Fayot, J; Feindt, Michael; Fenyuk, A; Ferrari, P; Ferrer, A; Fichet, S; Firestone, A; Fischer, P A; Flagmeyer, U; Föth, H; Fokitis, E; Fontanelli, F; Formenti, F; Franek, B J; Frodesen, A G; Frühwirth, R; Fulda-Quenzer, F; Fuster, J A; Galloni, A; Gamba, D; Gandelman, M; García, C; García, J; Gaspar, C; Gaspar, M; Gasparini, U; Gavillet, P; Gazis, E N; Gelé, D; Gerber, J P; Gerdyukov, L N; Ghodbane, N; Glege, F; Gokieli, R; Golob, B; González-Caballero, I; Gopal, Gian P; Gorn, L; Górski, M; Gracco, Valerio; Grahl, J; Graziani, E; Green, C; Grefrath, A; Gris, P; Grosdidier, G; Grzelak, K; Günther, M; Guy, J; Hahn, F; Hahn, S; Haider, S; Hajduk, Z; Hallgren, A; Hamacher, K; Harris, F J; Hedberg, V; Heising, S; Henriques, R P; Hernández, J J; Herquet, P; Herr, H; Hessing, T L; Heuser, J M; Higón, E; Holmgren, S O; Holt, P J; Holthuizen, D J; Hoorelbeke, S; Houlden, M A; Hrubec, Josef; Huet, K; Hultqvist, K; Jackson, J N; Jacobsson, R; Jalocha, P; Janik, R; Jarlskog, C; Jarlskog, G; Jarry, P; Jean-Marie, B; Johansson, E K; Jönsson, L B; Jönsson, P E; Joram, C; Juillot, P; Kapusta, F; Karafasoulis, K; Katsanevas, S; Katsoufis, E C; Keränen, R; Khokhlov, Yu A; Khomenko, B A; Khovanskii, N N; King, B J; Kjaer, N J; Klapp, O; Klein, H; Kluit, P M; Knoblauch, D; Kokkinias, P; Koratzinos, M; Korcyl, K; Kostyukhin, V; Kourkoumelis, C; Kuznetsov, O; Krammer, Manfred; Kreuter, C; Kronkvist, I J; Krumshtein, Z; Kubinec, P; Kucewicz, W; Kurvinen, K L; Lacasta, C; Lamsa, J; Lanceri, L; Lane, D W; Langefeld, P; Laugier, J P; Lauhakangas, R; Leder, Gerhard; Ledroit, F; Lefébure, V; Legan, C K; Leisos, A; Leitner, R; Lemonne, J; Lenzen, Georg; Lepeltier, V; Lesiak, T; Lethuillier, M; Libby, J; Liko, D; Lipniacka, A; Lippi, I; Lörstad, B; Loken, J G; Lopes, J H; López, J M; Loukas, D; Lutz, P; Lyons, L; MacNaughton, J N; Mahon, J R; Maio, A; Malek, A; Malmgren, T G M; Malychev, V; Mandl, F; Marco, J; Marco, R P; Maréchal, B; Margoni, M; Marin, J C; Mariotti, C; Markou, A; Martínez-Rivero, C; Martínez-Vidal, F; Martí i García, S; Matorras, F; Matteuzzi, C; Matthiae, Giorgio; Mazzucato, F; Mazzucato, M; McCubbin, M L; McKay, R; McNulty, R; McPherson, G; Medbo, J; Meroni, C; Meyer, W T; Michelotto, M; Migliore, E; Mirabito, L; Mitaroff, Winfried A; Mjörnmark, U; Moa, T; Møller, R; Mönig, K; Monge, M R; Moreau, X; Morettini, P; Münich, K; Mulders, M; Mundim, L M; Murray, W J; Muryn, B; Myatt, Gerald; Myklebust, T; Naraghi, F; Navarria, Francesco Luigi; Navas, S; Nawrocki, K; Negri, P; Némécek, S; Neufeld, N; Neumann, W; Neumeister, N; Nicolaidou, R; Nielsen, B S; Nieuwenhuizen, M; Nikolaenko, V; Nikolenko, M; Niss, P; Nomerotski, A; Normand, Ainsley; Nygren, A; Oberschulte-Beckmann, W; Obraztsov, V F; Olshevskii, A G; Onofre, A; Orava, Risto; Orazi, G; Österberg, K; Ouraou, A; Paganini, P; Paganoni, M; Paiano, S; Pain, R; Paiva, R; Palka, H; Papadopoulou, T D; Papageorgiou, K; Pape, L; Parkes, C; Parodi, F; Parzefall, U; Passeri, A; Pegoraro, M; Peralta, L; Pernegger, H; Pernicka, Manfred; Perrotta, A; Petridou, C; Petrolini, A; Phillips, H T; Piana, G; Pierre, F; Pimenta, M; Piotto, E; Podobnik, T; Podobrin, O; Pol, M E; Polok, G; Poropat, P; Pozdnyakov, V; Privitera, P; Pukhaeva, N; Pullia, Antonio; Radojicic, D; Ragazzi, S; Rahmani, H; Rames, J; Ratoff, P N; Read, A L; Rebecchi, P; Redaelli, N G; Regler, Meinhard; Reid, D; Reinhardt, R; Renton, P B; Resvanis, L K; Richard, F; Rídky, J; Rinaudo, G; Røhne, O M; Romero, A; Ronchese, P; Rosenberg, E I; Rosinsky, P; Roudeau, Patrick; Rovelli, T; Ruhlmann-Kleider, V; Ruiz, A; Saarikko, H; Sacquin, Yu; Sadovskii, A; Sajot, G; Salt, J; Sampsonidis, D; Sannino, M; Schneider, H; Schwickerath, U; Schyns, M A E; Scuri, F; Seager, P; Sedykh, Yu; Segar, A M; Sekulin, R L; Shellard, R C; Sheridan, A; Silvestre, R; Simonetto, F; Sissakian, A N; Skaali, T B; Smadja, G; Smirnov, N; Smirnova, O G; Smith, G R; Solovyanov, O; Sopczak, André; Sosnowski, R; Souza-Santos, D; Spassoff, Tz; Spiriti, E; Sponholz, P; Squarcia, S; Stampfer, D; Stanescu, C; Stanic, S; Stapnes, Steinar; Stavitski, I; Stevenson, K; Stocchi, A; Strauss, J; Strub, R; Stugu, B; Szczekowski, M; Szeptycka, M; Tabarelli de Fatis, T; Chikilev, O G; Tegenfeldt, F; Terranova, F; Thomas, J; Tilquin, A; Timmermans, J; Tkatchev, L G; Todorov, T; Todorova, S; Toet, D Z; Tomaradze, A G; Tomé, B; Tonazzo, A; Tortora, L; Tranströmer, G; Treille, D; Tristram, G; Trombini, A; Troncon, C; Tsirou, A L; Turluer, M L; Tyapkin, I A; Tyndel, M; Tzamarias, S; Überschär, B; Ullaland, O; Uvarov, V; Valenti, G; Vallazza, E; van Apeldoorn, G W; van Dam, P; Van Eldik, J; Van Lysebetten, A; Van Vulpen, I B; Vassilopoulos, N; Vegni, G; Ventura, L; Venus, W A; Verbeure, F; Verlato, M; Vertogradov, L S; Verzi, V; Vilanova, D; Vincent, P; Vitale, L; Vlasov, E; Vodopyanov, A S; Vrba, V; Wahlen, H; Walck, C; Waldner, F; Weiser, C; Wetherell, Alan M; Wicke, D; Wickens, J H; Wilkinson, G R; Williams, W S C; Winter, M; Witek, M; Wlodek, T; Wolf, G; Yi, J; Yushchenko, O P; Zaitsev, A; Zalewska-Bak, A; Zalewski, Piotr; Zavrtanik, D; Zevgolatakos, E; Zimin, N I; Zucchelli, G C; Zumerle, G

    1998-01-01

    The DELPHI experiment at LEP has measured the inclusive charmless $B$ hadron decay branching ratio, the $B$ branching ratio into two charmed particles, and the total number of charmed particles per $B$ decay, using the hadronic Z data taken between 1992 and 1995. The results are extracted from a fit to the $b$-tagging probability distribution based on the precise impact parameter measurements made using the microvertex detector. The inclusive charmless $B$ branching ratio, including $B$ decays into hidden charm ($c\\bar{c}$), is measured to be $0.033 \\pm 0.021$. The $B$ branching ratio into two open charmed particles is $0.136 \\pm 0.042$. The mean number of charmed particles per $B$ decay (including hidden charm) is $1.147 \\pm 0.041$. After subtracting the $B$ decay branching ratio into hidden charm, the charmless $B$ branching ratio is found to be $0.007 \\pm 0.021$, compatible with the Standard Model expectation. Models that predict an additional contribution to the charmless $B$ branching ratio of 0.037 or h...

  20. Predicting debris-flow initiation and run-out with a depth-averaged two-phase model and adaptive numerical methods

    Science.gov (United States)

    George, D. L.; Iverson, R. M.

    2012-12-01

    Numerically simulating debris-flow motion presents many challenges due to the complicated physics of flowing granular-fluid mixtures, the diversity of spatial scales (ranging from a characteristic particle size to the extent of the debris flow deposit), and the unpredictability of the flow domain prior to a simulation. Accurately predicting debris-flows requires models that are complex enough to represent the dominant effects of granular-fluid interaction, while remaining mathematically and computationally tractable. We have developed a two-phase depth-averaged mathematical model for debris-flow initiation and subsequent motion. Additionally, we have developed software that numerically solves the model equations efficiently on large domains. A unique feature of the mathematical model is that it includes the feedback between pore-fluid pressure and the evolution of the solid grain volume fraction, a process that regulates flow resistance. This feature endows the model with the ability to represent the transition from a stationary mass to a dynamic flow. With traditional approaches, slope stability analysis and flow simulation are treated separately, and the latter models are often initialized with force balances that are unrealistically far from equilibrium. Additionally, our new model relies on relatively few dimensionless parameters that are functions of well-known material properties constrained by physical data (eg. hydraulic permeability, pore-fluid viscosity, debris compressibility, Coulomb friction coefficient, etc.). We have developed numerical methods and software for accurately solving the model equations. By employing adaptive mesh refinement (AMR), the software can efficiently resolve an evolving debris flow as it advances through irregular topography, without needing terrain-fit computational meshes. The AMR algorithms utilize multiple levels of grid resolutions, so that computationally inexpensive coarse grids can be used where the flow is absent, and

  1. Branch xylem density variations across the Amazon Basin

    Directory of Open Access Journals (Sweden)

    S. Patiño

    2009-04-01

    Full Text Available Xylem density is a physical property of wood that varies between individuals, species and environments. It reflects the physiological strategies of trees that lead to growth, survival and reproduction. Measurements of branch xylem density, ρx, were made for 1653 trees representing 598 species, sampled from 87 sites across the Amazon basin. Measured values ranged from 218 kg m−3 for a Cordia sagotii (Boraginaceae from Mountagne de Tortue, French Guiana to 1130 kg m−3 for an Aiouea sp. (Lauraceae from Caxiuana, Central Pará, Brazil. Analysis of variance showed significant differences in average ρx across regions and sampled plots as well as significant differences between families, genera and species. A partitioning of the total variance in the dataset showed that species identity (family, genera and species accounted for 33% with environment (geographic location and plot accounting for an additional 26%; the remaining "residual" variance accounted for 41% of the total variance. Variations in plot means, were, however, not only accountable by differences in species composition because xylem density of the most widely distributed species in our dataset varied systematically from plot to plot. Thus, as well as having a genetic component, branch xylem density is a plastic trait that, for any given species, varies according to where the tree is growing in a predictable manner. Within the analysed taxa, exceptions to this general rule seem to be pioneer species belonging for example to the Urticaceae whose branch xylem density is more constrained than most species sampled in this study. These patterns of variation of branch xylem density across Amazonia suggest a large functional diversity amongst Amazonian trees which is not well understood.

  2. Branch xylem density variations across the Amazon Basin

    Science.gov (United States)

    Patiño, S.; Lloyd, J.; Paiva, R.; Baker, T. R.; Quesada, C. A.; Mercado, L. M.; Schmerler, J.; Schwarz, M.; Santos, A. J. B.; Aguilar, A.; Czimczik, C. I.; Gallo, J.; Horna, V.; Hoyos, E. J.; Jimenez, E. M.; Palomino, W.; Peacock, J.; Peña-Cruz, A.; Sarmiento, C.; Sota, A.; Turriago, J. D.; Villanueva, B.; Vitzthum, P.; Alvarez, E.; Arroyo, L.; Baraloto, C.; Bonal, D.; Chave, J.; Costa, A. C. L.; Herrera, R.; Higuchi, N.; Killeen, T.; Leal, E.; Luizão, F.; Meir, P.; Monteagudo, A.; Neil, D.; Núñez-Vargas, P.; Peñuela, M. C.; Pitman, N.; Priante Filho, N.; Prieto, A.; Panfil, S. N.; Rudas, A.; Salomão, R.; Silva, N.; Silveira, M.; Soares Dealmeida, S.; Torres-Lezama, A.; Vásquez-Martínez, R.; Vieira, I.; Malhi, Y.; Phillips, O. L.

    2009-04-01

    Xylem density is a physical property of wood that varies between individuals, species and environments. It reflects the physiological strategies of trees that lead to growth, survival and reproduction. Measurements of branch xylem density, ρx, were made for 1653 trees representing 598 species, sampled from 87 sites across the Amazon basin. Measured values ranged from 218 kg m-3 for a Cordia sagotii (Boraginaceae) from Mountagne de Tortue, French Guiana to 1130 kg m-3 for an Aiouea sp. (Lauraceae) from Caxiuana, Central Pará, Brazil. Analysis of variance showed significant differences in average ρx across regions and sampled plots as well as significant differences between families, genera and species. A partitioning of the total variance in the dataset showed that species identity (family, genera and species) accounted for 33% with environment (geographic location and plot) accounting for an additional 26%; the remaining "residual" variance accounted for 41% of the total variance. Variations in plot means, were, however, not only accountable by differences in species composition because xylem density of the most widely distributed species in our dataset varied systematically from plot to plot. Thus, as well as having a genetic component, branch xylem density is a plastic trait that, for any given species, varies according to where the tree is growing in a predictable manner. Within the analysed taxa, exceptions to this general rule seem to be pioneer species belonging for example to the Urticaceae whose branch xylem density is more constrained than most species sampled in this study. These patterns of variation of branch xylem density across Amazonia suggest a large functional diversity amongst Amazonian trees which is not well understood.

  3. Neuromuscular adaptations predict functional disability independently of clinical pain and psychological factors in patients with chronic non-specific low back pain.

    Science.gov (United States)

    Dubois, Jean-Daniel; Abboud, Jacques; St-Pierre, Charles; Piché, Mathieu; Descarreaux, Martin

    2014-08-01

    Patients with chronic low back pain exhibit characteristics such as clinical pain, psychological symptoms and neuromuscular adaptations. The purpose of this study was to determine the independent contribution of clinical pain, psychological factors and neuromuscular adaptations to disability in patients with chronic low back pain. Clinical pain intensity, pain catastrophizing, fear-avoidance beliefs, anxiety, neuromuscular adaptations to chronic pain and neuromuscular responses to experimental pain were assessed in 52 patients with chronic low back pain. Lumbar muscle electromyographic activity was assessed during a flexion-extension task (flexion relaxation phenomenon) to assess both chronic neuromuscular adaptations and neuromuscular responses to experimental pain during the task. Multiple regressions showed that independent predictors of disability included neuromuscular adaptations to chronic pain (β=0.25, p=0.006, sr(2)=0.06), neuromuscular responses to experimental pain (β=-0.24, p=0.011, sr(2)=0.05), clinical pain intensity (β=0.28, p=0.002, sr(2)=0.08) and psychological factors (β=0.58, ppain intensity and psychological factors, and contribute to inter-individual differences in patients' disability. This suggests that disability, in chronic low back pain patients, is determined by a combination of factors, including clinical pain, psychological factors and neuromuscular adaptations. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. Can adaptive threshold-based metabolic tumor volume (MTV) and lean body mass corrected standard uptake value (SUL) predict prognosis in head and neck cancer patients treated with definitive radiotherapy/chemoradiotherapy?

    Science.gov (United States)

    Akagunduz, Ozlem Ozkaya; Savas, Recep; Yalman, Deniz; Kocacelebi, Kenan; Esassolak, Mustafa

    2015-11-01

    To evaluate the predictive value of adaptive threshold-based metabolic tumor volume (MTV), maximum standardized uptake value (SUVmax) and maximum lean body mass corrected SUV (SULmax) measured on pretreatment positron emission tomography and computed tomography (PET/CT) imaging in head and neck cancer patients treated with definitive radiotherapy/chemoradiotherapy. Pretreatment PET/CT of the 62 patients with locally advanced head and neck cancer who were treated consecutively between May 2010 and February 2013 were reviewed retrospectively. The maximum FDG uptake of the primary tumor was defined according to SUVmax and SULmax. Multiple threshold levels between 60% and 10% of the SUVmax and SULmax were tested with intervals of 5% to 10% in order to define the most suitable threshold value for the metabolic activity of each patient's tumor (adaptive threshold). MTV was calculated according to this value. We evaluated the relationship of mean values of MTV, SUVmax and SULmax with treatment response, local recurrence, distant metastasis and disease-related death. Receiver-operating characteristic (ROC) curve analysis was done to obtain optimal predictive cut-off values for MTV and SULmax which were found to have a predictive value. Local recurrence-free (LRFS), disease-free (DFS) and overall survival (OS) were examined according to these cut-offs. Forty six patients had complete response, 15 had partial response, and 1 had stable disease 6 weeks after the completion of treatment. Median follow-up of the entire cohort was 18 months. Of 46 complete responders 10 had local recurrence, and of 16 partial or no responders 10 had local progression. Eighteen patients died. Adaptive threshold-based MTV had significant predictive value for treatment response (p=0.011), local recurrence/progression (p=0.050), and disease-related death (p=0.024). SULmax had a predictive value for local recurrence/progression (p=0.030). ROC curves analysis revealed a cut-off value of 14.00 mL for

  5. Adaptive therapy.

    Science.gov (United States)

    Gatenby, Robert A; Silva, Ariosto S; Gillies, Robert J; Frieden, B Roy

    2009-06-01

    subpopulations. Computer simulations show that this strategy can result in prolonged survival that is substantially greater than that of high dose density or metronomic therapies. The feasibility of adaptive therapy is supported by in vivo experiments. [Cancer Res 2009;69(11):4894-903] Major FindingsWe present mathematical analysis of the evolutionary dynamics of tumor populations with and without therapy. Analytic solutions and numerical simulations show that, with pretreatment, therapy-resistant cancer subpopulations are present due to phenotypic or microenvironmental factors; maximum dose density chemotherapy hastens rapid expansion of resistant populations. The models predict that host survival can be maximized if "treatment-for-cure strategy" is replaced by "treatment-for-stability." Specifically, the models predict that an optimal treatment strategy will modulate therapy to maintain a stable population of chemosensitive cells that can, in turn, suppress the growth of resistant populations under normal tumor conditions (i.e., when therapy-induced toxicity is absent). In vivo experiments using OVCAR xenografts treated with carboplatin show that adaptive therapy is feasible and, in this system, can produce long-term survival.

  6. Research on pyrolysis behavior of Camellia sinensis branches via the Discrete Distributed Activation Energy Model.

    Science.gov (United States)

    Zhou, Bingliang; Zhou, Jianbin; Zhang, Qisheng

    2017-10-01

    This study aims at investigating the pyrolysis behavior of Camellia sinensis branches by the Discrete Distributed Activation Energy Model (DAEM) and thermogravimetric experiments. Then the Discrete DAEM method is used to describe pyrolysis process of Camellia sinensis branches dominated by 12 characterized reactions. The decomposition mechanism of Camellia sinensis branches and interaction with components are observed. And the reaction at 350.77°C is a significant boundary of the first and second reaction range. The pyrolysis process of Camellia sinensis branches at the heating rate of 10,000°C/min is predicted and provides valuable references for gasification or combustion. The relationship and function between four typical indexes and heating rates from 10 to 10,000°C/min are revealed. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. Airway branching morphogenesis in three dimensional culture

    Directory of Open Access Journals (Sweden)

    Gudjonsson Thorarinn

    2010-11-01

    Full Text Available Abstract Background Lungs develop from the fetal digestive tract where epithelium invades the vascular rich stroma in a process called branching morphogenesis. In organogenesis, endothelial cells have been shown to be important for morphogenesis and the maintenance of organ structure. The aim of this study was to recapitulate human lung morphogenesis in vitro by establishing a three dimensional (3D co-culture model where lung epithelial cells were cultured in endothelial-rich stroma. Methods We used a human bronchial epithelial cell line (VA10 recently developed in our laboratory. This cell line cell line maintains a predominant basal cell phenotype, expressing p63 and other basal markers such as cytokeratin-5 and -14. Here, we cultured VA10 with human umbilical vein endothelial cells (HUVECs, to mimic the close interaction between these cell types during lung development. Morphogenesis and differentiation was monitored by phase contrast microscopy, immunostainings and confocal imaging. Results We found that in co-culture with endothelial cells, the VA10 cells generated bronchioalveolar like structures, suggesting that lung epithelial branching is facilitated by the presence of endothelial cells. The VA10 derived epithelial structures display various complex patterns of branching and show partial alveolar type-II differentiation with pro-Surfactant-C expression. The epithelial origin of the branching VA10 colonies was confirmed by immunostaining. These bronchioalveolar-like structures were polarized with respect to integrin expression at the cell-matrix interface. The endothelial-induced branching was mediated by soluble factors. Furthermore, fibroblast growth factor receptor-2 (FGFR-2 and sprouty-2 were expressed at the growing tips of the branching structures and the branching was inhibited by the FGFR-small molecule inhibitor SU5402. Discussion In this study we show that a human lung epithelial cell line can be induced by endothelial cells to

  8. Thermoelectric effects in disordered branched nanowires

    Science.gov (United States)

    Roslyak, Oleksiy; Piriatinskiy, Andrei

    2013-03-01

    We shall develop formalism of thermal and electrical transport in Si1 - x Gex and BiTe nanowires. The key feature of those nanowires is the possibility of dendrimer type branching. The branching tree can be of size comparable to the short wavelength of phonons and by far smaller than the long wavelength of conducting electrons. Hence it is expected that the branching may suppress thermal and let alone electrical conductance. We demonstrate that the morphology of branches strongly affects the electronic conductance. The effect is important to the class of materials known as thermoelectrics. The small size of the branching region makes large temperature and electrical gradients. On the other hand the smallness of the region would allow the electrical transport being ballistic. As usual for the mesoscopic systems we have to solve macroscopic (temperature) and microscopic ((electric potential, current)) equations self-consistently. Electronic conductance is studied via NEGF formalism on the irreducible electron transfer graph. We also investigate the figure of merit ZT as a measure of the suppressed electron conductance.

  9. Pulsed positive corona streamer propagation and branching

    International Nuclear Information System (INIS)

    Veldhuizen, E.M. van; Rutgers, W.R.

    2002-01-01

    The propagation and branching of pulsed positive corona streamers in a short gap is observed with high resolution in space and time. The appearance of the pre-breakdown phenomena can be controlled by the electrode configuration, the gas composition and the impedance of the pulsed power circuit. In a point-wire gap the positive corona shows much more branching than in the parallel plane gap with a protrusion. In air, the branching is more pronounced than in argon. The pulsed power circuit appears to operate in two modes, either as an inductive circuit creating a lower number of thick streamers or as a resistive circuit giving a higher number of thin streamers. A possible cause for branching is electrostatic repulsion of two parts of the streamer head. The electric field at the streamer head is limited, the maximum values found are ∼170 kV cm -1 in air and ∼100 kV cm -1 in argon. At these maximum field strengths, the electrons have 5-10 eV energy, so the ionization is dominated by two-step processes. Differences between argon and ambient air in the field strength at which streamers propagate are ascribed to the difference in de-excitation processes in noble and molecular gases. The fact that the pulsed power circuit can control the streamer structure is important for applications, but this effect must also be taken into account in fundamental studies of streamer propagation and branching. (author)

  10. Pulsed positive corona streamer propagation and branching

    Energy Technology Data Exchange (ETDEWEB)

    Veldhuizen, E.M. van [Department of Physics, Technische Universiteit Eindhoven, Eindhoven (Netherlands)]. E-mail: e.m.v.veldhuizen@tue.nl; Rutgers, W.R. [Department of Physics, Technische Universiteit Eindhoven, Eindhoven (Netherlands)

    2002-09-07

    The propagation and branching of pulsed positive corona streamers in a short gap is observed with high resolution in space and time. The appearance of the pre-breakdown phenomena can be controlled by the electrode configuration, the gas composition and the impedance of the pulsed power circuit. In a point-wire gap the positive corona shows much more branching than in the parallel plane gap with a protrusion. In air, the branching is more pronounced than in argon. The pulsed power circuit appears to operate in two modes, either as an inductive circuit creating a lower number of thick streamers or as a resistive circuit giving a higher number of thin streamers. A possible cause for branching is electrostatic repulsion of two parts of the streamer head. The electric field at the streamer head is limited, the maximum values found are {approx}170 kV cm{sup -1} in air and {approx}100 kV cm{sup -1} in argon. At these maximum field strengths, the electrons have 5-10 eV energy, so the ionization is dominated by two-step processes. Differences between argon and ambient air in the field strength at which streamers propagate are ascribed to the difference in de-excitation processes in noble and molecular gases. The fact that the pulsed power circuit can control the streamer structure is important for applications, but this effect must also be taken into account in fundamental studies of streamer propagation and branching. (author)

  11. Prediction of adaptation difficulties by country of origin, cumulate psychosocial stressors and attitude toward integrating: a Swedish study of first-generation immigrants from Somalia, Vietnam and China.

    Science.gov (United States)

    Johnsson, Ewa; Zolkowska, Krystyna; McNeil, Thomas F

    2015-03-01

    Different types of accumulated stress have been found to have negative consequences for immigrants' capacity to adapt to the new environment. It remains unclear which factors have the greatest influence. The study investigated whether immigrants' experience of great difficulty in adapting to a new country could best be explained by (1) country of origin, (2) exposure to accumulated stressors before arrival or (3) after arrival in the new country and/or (4) reserved attitude toward integrating into the new society. The 119 first-generation immigrants from Somalia, Vietnam and China, living in Malmö, Sweden, were interviewed in a standardized manner. Experiencing great difficulty in adapting to Sweden was independent of length of residence, but significantly related to all four influences, studied one at a time. Country of origin was also related to stressors and attitude. When the effects of the other influences were mutually controlled for, only exposure to accumulated stressors in Sweden (and especially experiencing discrimination/xenophobia/racism) accounted for great adaptation difficulty. Stressors in Sweden had a greater effect if the immigrant had been exposed to stressors earlier. Immigrants' long-term experiences of great difficulty in adapting to a new country were explained primarily by exposure to accumulated stressors while moving to and living in the new country, rather than by their backgrounds or attitudes toward integrating. This suggests promoting strategies to avoid discrimination and other stressors in the host country. © The Author(s) 2014.

  12. Prediction of adaptation difficulties by country of origin, cumulate psychosocial stressors and attitude toward integrating: A Swedish study of first-generation immigrants from Somalia, Vietnam and China

    Science.gov (United States)

    Zolkowska, Krystyna; McNeil, Thomas F

    2015-01-01

    Background: Different types of accumulated stress have been found to have negative consequences for immigrants’ capacity to adapt to the new environment. It remains unclear which factors have the greatest influence. Aims: The study investigated whether immigrants’ experience of great difficulty in adapting to a new country could best be explained by (1) country of origin, (2) exposure to accumulated stressors before arrival or (3) after arrival in the new country and/or (4) reserved attitude toward integrating into the new society. Methods: The 119 first-generation immigrants from Somalia, Vietnam and China, living in Malmö, Sweden, were interviewed in a standardized manner. Results: Experiencing great difficulty in adapting to Sweden was independent of length of residence, but significantly related to all four influences, studied one at a time. Country of origin was also related to stressors and attitude. When the effects of the other influences were mutually controlled for, only exposure to accumulated stressors in Sweden (and especially experiencing discrimination/xenophobia/racism) accounted for great adaptation difficulty. Stressors in Sweden had a greater effect if the immigrant had been exposed to stressors earlier. Conclusions: Immigrants’ long-term experiences of great difficulty in adapting to a new country were explained primarily by exposure to accumulated stressors while moving to and living in the new country, rather than by their backgrounds or attitudes toward integrating. This suggests promoting strategies to avoid discrimination and other stressors in the host country. PMID:24927925

  13. Life Cycle Assessment of Alfalfa Production and Prediction of Emissions using Multi-Layer Adaptive Neuro-Fuzzy Inference System in Bukan Township

    Directory of Open Access Journals (Sweden)

    O Ghaderpour

    2018-03-01

    checking comparison between experimental and modeled data, the t-test was performed. The null hypothesis was equality of data average. To develop ANFIS models, MATLAB software (R2015a was used. Results and Discussion Impact categories including Global warming potential (GWP, eutrophication potential (EP, human toxicity potential (HTP, terrestrial ecotoxicity potential (TEP, oxidant formation potential (OFP, acidification potential (AP, Abiotic depletion (AD and Abiotic depletion (fossil fuels were calculated as 13373 kg CO2 eq, 19.78 kg PO4-2 eq, 2054 kg 1,4-DCB eq, 38.7 kg 1,4-DCB eq, 3.84 kg Ethylene eq, 90.64 kg SO2 eq, 0.015 kg Sb eq and 205169 MJ, respectively. The results of damage assessment of alfalfa production revealed that electricity in three categories, human health damage, climate change and ecosystem quality had maximum role, but in the resources damage category was the largest share of damage related direct emissions. The value of the climate change was calculated as 13373 kg CO2 eq. The best structure was including five ANFIS network in the first layer, two network in the second layer and a network in output layer. Values of R, MSE and RMSE for the final ANFIS in k-fold model were 0.983, 0.107 and 0.327 and in C-means model were 0.999, 0.007 and 0.082, respectively. The p-value in t-test was 0.9987 that indicates non-significant difference between the mean of modeling and experimental data. Coefficient of determination (R2 between actual and predicted GWP based on the best k-fold and C-means models were 0.994 and 0.99, respectively. The coefficient of determination for these index demonstrated the suitability of the developed network for prediction of GWP of alfalfa production in the studied area. Conclusions Based on the results of this study, to reduce the emissions, electricity consumption should be reduced. Adapting of electro pumps power with the well depth and the amount of required water taken for field will be a possible solution to reduce the use

  14. Computational models of airway branching morphogenesis.

    Science.gov (United States)

    Varner, Victor D; Nelson, Celeste M

    2017-07-01

    The bronchial network of the mammalian lung consists of millions of dichotomous branches arranged in a highly complex, space-filling tree. Recent computational models of branching morphogenesis in the lung have helped uncover the biological mechanisms that construct this ramified architecture. In this review, we focus on three different theoretical approaches - geometric modeling, reaction-diffusion modeling, and continuum mechanical modeling - and discuss how, taken together, these models have identified the geometric principles necessary to build an efficient bronchial network, as well as the patterning mechanisms that specify airway geometry in the developing embryo. We emphasize models that are integrated with biological experiments and suggest how recent progress in computational modeling has advanced our understanding of airway branching morphogenesis. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Tillering and panicle branching genes in rice.

    Science.gov (United States)

    Liang, Wei-hong; Shang, Fei; Lin, Qun-ting; Lou, Chen; Zhang, Jing

    2014-03-01

    Rice (Oryza sativa L.) is one of the most important staple food crops in the world, and rice tillering and panicle branching are important traits determining grain yield. Since the gene MONOCULM 1 (MOC 1) was first characterized as a key regulator in controlling rice tillering and branching, great progress has been achieved in identifying important genes associated with grain yield, elucidating the genetic basis of yield-related traits. Some of these important genes were shown to be applicable for molecular breeding of high-yielding rice. This review focuses on recent advances, with emphasis on rice tillering and panicle branching genes, and their regulatory networks. Copyright © 2013 Elsevier B.V. All rights reserved.

  16. Measurement of Tau Lepton Branching Fractions

    Energy Technology Data Exchange (ETDEWEB)

    Nicol, N.

    2003-12-19

    We present {tau}{sup -} lepton branching fraction measurements based on data from the TPC/Two-Gamma detector at PEP. Using a sample of {tau}{sup -} {yields} {nu}{sub {tau}}K{sup -}{pi}{sup +}{pi}{sup -} events, we examine the resonance structure of the K{sup -}{pi}{sup +}{pi}{sup -} system and obtain the first measurements of branching fractions for {tau}{sup -} {yields} {nu}{sub {tau}}K{sub 1}{sup -}(1270) and {tau}{sup -} {yields} {nu}{sub {tau}}K{sub 1}{sup -}(1400). We also describe a complete set of branching fraction measurements in which all the decays of the {tau}{sup -} lepton are separated into classes defined by the identities of the charged particles and an estimate of the number of neutrals. This is the first such global measurement with decay classes defined by the four possible charged particle species, e, {mu}, {pi}, and K.

  17. Joint Applications Pilot of the National Climate Predictions and Projections Platform and the North Central Climate Science Center: Delivering climate projections on regional scales to support adaptation planning

    Science.gov (United States)

    Ray, A. J.; Ojima, D. S.; Morisette, J. T.

    2012-12-01

    The DOI North Central Climate Science Center (NC CSC) and the NOAA/NCAR National Climate Predictions and Projections (NCPP) Platform and have initiated a joint pilot study to collaboratively explore the "best available climate information" to support key land management questions and how to provide this information. NCPP's mission is to support state of the art approaches to develop and deliver comprehensive regional climate information and facilitate its use in decision making and adaptation planning. This presentation will describe the evolving joint pilot as a tangible, real-world demonstration of linkages between climate science, ecosystem science and resource management. Our joint pilot is developing a deliberate, ongoing interaction to prototype how NCPP will work with CSCs to develop and deliver needed climate information products, including translational information to support climate data understanding and use. This pilot also will build capacity in the North Central CSC by working with NCPP to use climate information used as input to ecological modeling. We will discuss lessons to date on developing and delivering needed climate information products based on this strategic partnership. Four projects have been funded to collaborate to incorporate climate information as part of an ecological modeling project, which in turn will address key DOI stakeholder priorities in the region: Riparian Corridors: Projecting climate change effects on cottonwood and willow seed dispersal phenology, flood timing, and seedling recruitment in western riparian forests. Sage Grouse & Habitats: Integrating climate and biological data into land management decision models to assess species and habitat vulnerability Grasslands & Forests: Projecting future effects of land management, natural disturbance, and CO2 on woody encroachment in the Northern Great Plains The value of climate information: Supporting management decisions in the Plains and Prairie Potholes LCC. NCCSC's role in

  18. Light Signaling in Bud Outgrowth and Branching in Plants

    Directory of Open Access Journals (Sweden)

    Nathalie Leduc

    2014-04-01

    Full Text Available Branching determines the final shape of plants, which influences adaptation, survival and the visual quality of many species. It is an intricate process that includes bud outgrowth and shoot extension, and these in turn respond to environmental cues and light conditions. Light is a powerful environmental factor that impacts multiple processes throughout plant life. The molecular basis of the perception and transduction of the light signal within buds is poorly understood and undoubtedly requires to be further unravelled. This review is based on current knowledge on bud outgrowth-related mechanisms and light-mediated regulation of many physiological processes. It provides an extensive, though not exhaustive, overview of the findings related to this field. In parallel, it points to issues to be addressed in the near future.

  19. Branching time, indeterminism and tense logic

    DEFF Research Database (Denmark)

    Ploug, Thomas; Øhrstrøm, Peter

    2012-01-01

    This paper deals with the historical and philosophical background of the introduction of the notion of branching time in philosophical logic as it is revealed in the hitherto unpublished mail-correspondence between Saul Kripke and A.N. Prior in the late 1950s. The paper reveals that the idea...... relativity. The correspondence underpins the point that Prior’s later development of branching time may be understood as a crucial part of his attempt at the formulating a conceptual framework integrating basic human notions of time and free choice....

  20. Electronic branching ratio of the τ lepton

    International Nuclear Information System (INIS)

    Ammar, R.; Baringer, P.; Coppage, D.; Davis, R.; Kelly, M.; Kwak, N.; Lam, H.; Ro, S.; Kubota, Y.; Lattery, M.; Nelson, J.K.; Perticone, D.; Poling, R.; Schrenk, S.; Wang, R.; Alam, M.S.; Kim, I.J.; Nemati, B.; Romero, V.; Sun, C.R.; Wang, P.; Zoeller, M.M.; Crawford, G.; Fulton, R.; Gan, K.K.; Kagan, H.; Kass, R.; Lee, J.; Malchow, R.; Morrow, F.; Sung, M.K.; Whitmore, J.; Wilson, P.; Butler, F.; Fu, X.; Kalbfleisch, G.; Lambrecht, M.; Skubic, P.; Snow, J.; Wang, P.; Bortoletto, D.; Brown, D.N.; Dominick, J.; McIlwain, R.L.; Miller, D.H.; Modesitt, M.; Shibata, E.I.; Schaffner, S.F.; Shipsey, I.P.J.; Battle, M.; Ernst, J.; Kroha, H.; Roberts, S.; Sparks, K.; Thorndike, E.H.; Wang, C.; Stroynowski, R.; Artuso, M.; Goldberg, M.; Haupt, T.; Horwitz, N.; Kennett, R.; Moneti, G.C.; Playfer, S.; Rozen, Y.; Rubin, P.; Skwarnicki, T.; Stone, S.; Thulasidas, M.; Yao, W.; Zhu, G.; Barnes, A.V.; Bartelt, J.; Csorna, S.E.; Jain, V.; Letson, T.; Mestayer, M.D.; Akerib, D.S.; Barish, B.; Chadha, M.; Cowen, D.F.; Eigen, G.; Miller, J.S.; Urheim, J.; Weinstein, A.J.; Morrison, R.J.; Tajima, H.; Schmidt, D.; Sperka, D.; Procario, M.; Daoudi, M.; Ford, W.T.; Johnson, D.R.; Lingel, K.; Lohner, M.; Rankin, P.; Smith, J.G.; Alexander, J.; Bebek, C.; Berkelman, K.; Besson, D.; Browder, T.E.; Cassel, D.G.; Cheu, E.; Coffman, D.M.; Drell, P.S.; Ehrlich, R.; Galik, R.S.; Garcia-Sciveres, M.; Geiser, B.; Gittelman, B.; Gray, S.W.; Hartill, D.L.; Heltsley, B.K.; Honscheid, K.; Jones, C.; Kandaswamy, J.; Katayama, N.; Kim, P.C.; Kreinick, D.L.; Ludwig, G.S.; Masui, J.; Mevissen, J.; Mistry, N.B.; Nandi, S.; Ng, C.R.; Nordberg, E.; O'Grady, C.; Patterson, J.R.; Peterson, D.; Riley, D.; Sapper, M.; Selen, M.; Worden, H.; Worris, M.; Wuerthwein, F.; Avery, P.; Freyberger, A.; Rodriguez, J.; Yelton, J.; Henderson, S.; Kinoshita, K.; Pipkin, F.; Saulnier, M.; Wilson, R.; Wolinski, J.; Xiao, D.; Yamamoto, H.; Sadoff, A.J.

    1992-01-01

    Using data accumulated by the CLEO I detector operating at the Cornell Electron Storage Ring, we have measured the ratio R=Γ(τ→e bar ν e ν τ )/Γ 1 , where Γ 1 is the τ decay rate to final states with one charged particle. We find R=0.2231±0.0044±0.0073 where the first error is statistical and the second is systematic. Together with the measured topological one-charged-particle branching fraction, this yields the branching fraction of the τ lepton to electrons, B e =0.192±0.004±0.006

  1. A new ripplon branch in He II

    International Nuclear Information System (INIS)

    Tanatarov, I.V.; Tanatarov, I.V.; Adamenko, I.N.; Nemchenko, K.E.; Wyatt, A.F.G.

    2010-01-01

    We analyse the dispersion relation of ripplons, on the surface of superfluid helium, using the dispersive hydrodynamics approach and find a new ripplon branch. We obtain analytical equation for the dispersion relation and analytic expressions for the limiting cases. The probabilities of decay of unstable ripplons above the roton gap into rotons are derived. A numerical solution for the ripplon dispersion curve is obtained. The new ripplon branch is found at energies just below the instability point of the bulk spectrum, and is investigated; its stability is discussed.

  2. A Dynamic Branch-Switching Method for Parametrically Excited Systems

    Directory of Open Access Journals (Sweden)

    A.Y.T. Leung

    1999-01-01

    Full Text Available The branch-switching algorithm in static is applied to steady state dynamic problems. The governing ordinary differential equations are transformed to nonlinear algebraic equations by means of harmonic balance method using multiple frequency components. The frequency components of the (irrational nonlinearity of oscillator are obtained by Fast Fourier Transform and Toeplitz Jacobian method (FFT/TJM. All singularities, folds, flips, period doubling and period bubbling, are computed accurately in an analytical manner. Coexisting solutions can be predicted without using initial condition search. The consistence of both stability criteria in time and frequency domains is discussed. A highly nonlinear parametrically excited system is given as example. All connected solution paths are predicted.

  3. Adaptive-Predictive Organ Localization Using Cone-Beam Computed Tomography for Improved Accuracy in External Beam Radiotherapy for Bladder Cancer

    International Nuclear Information System (INIS)

    Lalondrelle, Susan; Huddart, Robert; Warren-Oseni, Karole; Hansen, Vibeke Nordmark; McNair, Helen; Thomas, Karen; Dearnaley, David; Horwich, Alan; Khoo, Vincent

    2011-01-01

    Purpose: To examine patterns of bladder wall motion during high-dose hypofractionated bladder radiotherapy and to validate a novel adaptive planning method, A-POLO, to prevent subsequent geographic miss. Methods and Materials: Patterns of individual bladder filling were obtained with repeat computed tomography planning scans at 0, 15, and 30 minutes after voiding. A series of patient-specific plans corresponding to these time-displacement points was created. Pretreatment cone-beam computed tomography was performed before each fraction and assessed retrospectively for adaptive intervention. In fractions that would have required intervention, the most appropriate plan was chosen from the patient's 'library,' and the resulting target coverage was reassessed with repeat cone-beam computed tomography. Results: A large variation in patterns of bladder filling and interfraction displacement was seen. During radiotherapy, predominant translations occurred cranially (maximum 2.5 cm) and anteriorly (maximum 1.75 cm). No apparent explanation was found for this variation using pretreatment patient factors. A need for adaptive planning was demonstrated by 51% of fractions, and 73% of fractions would have been delivered correctly using A-POLO. The adaptive strategy improved target coverage and was able to account for intrafraction motion also. Conclusions: Bladder volume variation will result in geographic miss in a high proportion of delivered bladder radiotherapy treatments. The A-POLO strategy can be used to correct for this and can be implemented from the first fraction of radiotherapy; thus, it is particularly suited to hypofractionated bladder radiotherapy regimens.

  4. Developing predictive approaches to characterize adaptive responses of the reproductive endocrine axis to aromatase inhibition: I. Data generation in a small fish model

    Science.gov (United States)

    Adaptive or compensatory responses to chemical exposure can significantly influence in vivo concentration-duration-response relationships. The aim of this study was to provide data to support development of a computational dynamic model of the hypothalamic-pituitary-gonadal axis ...

  5. An adaptive recurrent neural-network controller using a stabilization matrix and predictive inputs to solve a tracking problem under disturbances.

    Science.gov (United States)

    Fairbank, Michael; Li, Shuhui; Fu, Xingang; Alonso, Eduardo; Wunsch, Donald

    2014-01-01

    We present a recurrent neural-network (RNN) controller designed to solve the tracking problem for control systems. We demonstrate that a major difficulty in training any RNN is the problem of exploding gradients, and we propose a solution to this in the case of tracking problems, by introducing a stabilization matrix and by using carefully constrained context units. This solution allows us to achieve consistently lower training errors, and hence allows us to more easily introduce adaptive capabilities. The resulting RNN is one that has been trained off-line to be rapidly adaptive to changing plant conditions and changing tracking targets. The case study we use is a renewable-energy generator application; that of producing an efficient controller for a three-phase grid-connected converter. The controller we produce can cope with the random variation of system parameters and fluctuating grid voltages. It produces tracking control with almost instantaneous response to changing reference states, and virtually zero oscillation. This compares very favorably to the classical proportional integrator (PI) controllers, which we show produce a much slower response and settling time. In addition, the RNN we propose exhibits better learning stability and convergence properties, and can exhibit faster adaptation, than has been achieved with adaptive critic designs. Copyright © 2013 Elsevier Ltd. All rights reserved.

  6. Turing mechanism underlying a branching model for lung morphogenesis.

    Science.gov (United States)

    Xu, Hui; Sun, Mingzhu; Zhao, Xin

    2017-01-01

    The mammalian lung develops through branching morphogenesis. Two primary forms of branching, which occur in order, in the lung have been identified: tip bifurcation and side branching. However, the mechanisms of lung branching morphogenesis remain to be explored. In our previous study, a biological mechanism was presented for lung branching pattern formation through a branching model. Here, we provide a mathematical mechanism underlying the branching patterns. By decoupling the branching model, we demonstrated the existence of Turing instability. We performed Turing instability analysis to reveal the mathematical mechanism of the branching patterns. Our simulation results show that the Turing patterns underlying the branching patterns are spot patterns that exhibit high local morphogen concentration. The high local morphogen concentration induces the growth of branching. Furthermore, we found that the sparse spot patterns underlie the tip bifurcation patterns, while the dense spot patterns underlies the side branching patterns. The dispersion relation analysis shows that the Turing wavelength affects the branching structure. As the wavelength decreases, the spot patterns change from sparse to dense, the rate of tip bifurcation decreases and side branching eventually occurs instead. In the process of transformation, there may exists hybrid branching that mixes tip bifurcation and side branching. Since experimental studies have reported that branching mode switching from side branching to tip bifurcation in the lung is under genetic control, our simulation results suggest that genes control the switch of the branching mode by regulating the Turing wavelength. Our results provide a novel insight into and understanding of the formation of branching patterns in the lung and other biological systems.

  7. The impact of switching costs on closing of service branches

    OpenAIRE

    Baron, Mira G.

    2002-01-01

    The paper deals with the optimal location of service branches. Consumers can receive service from different firms and branches offering substitute services. The consumer chooses the firm and the branch. Examples are banking services (which firm and branch?), healthcare providers, insurance companies and their agents, brokerage firms and their branches. With the change in the accessibility of the internet, the service industry witnesses the impact of the change in technology. More customers pr...

  8. Dynamical adaptation in photoreceptors.

    Directory of Open Access Journals (Sweden)

    Damon A Clark

    Full Text Available Adaptation is at the heart of sensation and nowhere is it more salient than in early visual processing. Light adaptation in photoreceptors is doubly dynamical: it depends upon the temporal structure of the input and it affects the temporal structure of the response. We introduce a non-linear dynamical adaptation model of photoreceptors. It is simple enough that it can be solved exactly and simulated with ease; analytical and numerical approaches combined provide both intuition on the behavior of dynamical adaptation and quantitative results to be compared with data. Yet the model is rich enough to capture intricate phenomenology. First, we show that it reproduces the known phenomenology of light response and short-term adaptation. Second, we present new recordings and demonstrate that the model reproduces cone response with great precision. Third, we derive a number of predictions on the response of photoreceptors to sophisticated stimuli such as periodic inputs, various forms of flickering inputs, and natural inputs. In particular, we demonstrate that photoreceptors undergo rapid adaptation of response gain and time scale, over ∼ 300[Formula: see text] ms-i. e., over the time scale of the response itself-and we confirm this prediction with data. For natural inputs, this fast adaptation can modulate the response gain more than tenfold and is hence physiologically relevant.

  9. The influence of variability on the optimal shape of an airway tree branching asymmetrically

    International Nuclear Information System (INIS)

    Mauroy, Benjamin; Bokov, Plamen

    2010-01-01

    The asymmetry of the bronchial tree has been reported on numerous occasions, and bronchi in the lung bifurcate most of the time into a major and a minor daughter. Asymmetry is most probably bound to play a role on the hydrodynamic resistance and volume occupation of the bronchial tree. Thus, in this work, we search for an optimal asymmetric airway tree crossed by Poiseuille flow that would be a good candidate to model the distal conductive part of the lung. The geometry is controlled by major and minor diameter reduction factors that depend on the generation. We show that the optimal asymmetric tree has diameter reduction factors that are adimensional from the second level of bifurcation and that they are highly dependent on the asymmetric ratio that defines the relative sizes of the major and minor branches in a bifurcation. This optimization also gives access to a cost function whose particularity is to be asymmetric around its minimum. Thus, the cliff-edge hypothesis predicts that if the system suffers variability, then the best tree is shifted from the optimal. We apply a recent theoretical model of cliff-edge in order to measure the role of variability on the determination of the best asymmetric tree. Then, we compare our results with lung data of the literature. In particular, we are able to quantify the variability needed to fit the data and to give hypothesis that could explain, at least partially, the shift found between the optimal tree and the measures in the case of asymmetric bronchial trees. Finally, our model predicts that, even if the population is adapted at best, there always exist individuals whose bronchial trees are associated with larger costs comparatively to the average and who ought to be more sensitive to geometrical remodeling

  10. BranchAnalysis2D/3D automates morphometry analyses of branching structures.

    Science.gov (United States)

    Srinivasan, Aditya; Muñoz-Estrada, Jesús; Bourgeois, Justin R; Nalwalk, Julia W; Pumiglia, Kevin M; Sheen, Volney L; Ferland, Russell J

    2018-01-15

    Morphometric analyses of biological features have become increasingly common in recent years with such analyses being subject to a large degree of observer bias, variability, and time consumption. While commercial software packages exist to perform these analyses, they are expensive, require extensive user training, and are usually dependent on the observer tracing the morphology. To address these issues, we have developed a broadly applicable, no-cost ImageJ plugin we call 'BranchAnalysis2D/3D', to perform morphometric analyses of structures with branching morphologies, such as neuronal dendritic spines, vascular morphology, and primary cilia. Our BranchAnalysis2D/3D algorithm allows for rapid quantification of the length and thickness of branching morphologies, independent of user tracing, in both 2D and 3D data sets. We validated the performance of BranchAnalysis2D/3D against pre-existing software packages using trained human observers and images from brain and retina. We found that the BranchAnalysis2D/3D algorithm outputs results similar to available software (i.e., Metamorph, AngioTool, Neurolucida), while allowing faster analysis times and unbiased quantification. BranchAnalysis2D/3D allows inexperienced observers to output results like a trained observer but more efficiently, thereby increasing the consistency, speed, and reliability of morphometric analyses. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. ORD’s Urban Watershed Management Branch

    Science.gov (United States)

    This is a poster for the Edison Science Day, tentatively scheduled for June 10, 2009. This poster presentation summarizes key elements of the EPA Office of Research and Development’s (ORD) Urban Watershed Management Branch (UWMB). An overview of the national problems posed by w...

  12. Medial branch neurotomy in low back pain

    Energy Technology Data Exchange (ETDEWEB)

    Masala, Salvatore; Mammucari, Matteo; Simonetti, Giovanni [Interventional Radiology and Radiotherapy University ' ' Tor Vergata' ' , Department of Diagnostic and Molecular Imaging, Rome (Italy); Nano, Giovanni [Interventional Radiology and Radiotherapy University ' ' Tor Vergata' ' , Department of Diagnostic and Molecular Imaging, Rome (Italy); University ' ' Tor Vergata' ' , Department of Radiology, Rome (Italy); Marcia, Stefano [S. Giovanni di Dio Hospital, Department of Diagnostic and Molecular Imaging, Cagliari (Italy)

    2012-07-15

    This study aimed to assess the effectiveness of pulsed radiofrequency medial branch dorsal ramus neurotomy in patients with facet joint syndrome. From January 2008 to April 2010, 92 patients with facet joint syndrome diagnosed by strict inclusion criteria and controlled diagnostic blocks undergone medial branch neurotomy. We did not exclude patients with failed back surgery syndrome (FBSS). Electrodes (20G) with 5-mm active tip were placed under fluoroscopy guide parallel to medial branch. Patients were followed up by physical examination and by Visual Analog Scale and Oswestry Disability Index at 1, 6, and 12 months. In all cases, pain improvement was statistically significant and so quality of life. Three non-FBSS patients had to undergo a second neurotomy because of non-satisfactory pain decrease. Complications were reported in no case. Medial branch radiofrequency neurotomy has confirmed its well-established effectiveness in pain and quality of life improvement as long as strict inclusion criteria be fulfilled and nerve ablation be accomplished by parallel electrode positioning. This statement can be extended also to FBSS patients. (orig.)

  13. Heavy metal contamination in TIMS Branch sediments

    International Nuclear Information System (INIS)

    Pickett, J.B.

    1990-01-01

    The objective of this memorandum is to summarize results of previous sediment studies on Tims Branch and Steed's Pond conducted by Health Protection (HP) and by the Savannah River Laboratory (SRL) in conjunction with Reactor Materials Engineering ampersand Technology (RMET). The results for other heavy metals, such as lead, nickel, copper, mercury, chromium, cadmium, zinc, and thorium are also summarized

  14. Organizing Organoids: Stem Cells Branch Out.

    Science.gov (United States)

    Davies, Jamie A

    2017-12-07

    In this issue of Cell Stem Cell, Taguchi and Nishinakamura (2017) describe a carefully optimized method for making a branch-competent ureteric bud, a tissue fundamental to kidney development, from mouse embryonic stem cells and human induced pluripotent stem cells. The work illuminates embryology and has important implications for making more realistic kidney organoids. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. Annealed star-branched polyelectrolytes in solution

    NARCIS (Netherlands)

    Klein Wolterink, J.; Male, van J.; Cohen Stuart, M.A.; Koopal, L.K.; Zhulina, E.B.; Borisov, O.V.

    2002-01-01

    Equilibrium conformations of annealed star-branched polyelectrolytes (polyacids) are calculated with a numerical self-consistent-field (SCF) model. From the calculations we obtain also the size and charge of annealed polyelectrolyte stars as a function of the number of arms, pH, and the ionic

  16. Branch President gives evidence at Scottish Parliament.

    Science.gov (United States)

    2017-07-01

    As the Scottish Government moves forward with its recently announced package of measures on animal health and welfare, Hayley Atkin, BVA Policy Officer, describes a busy month for the President of BVA Scottish Branch representing members in the Scottish Parliament. British Veterinary Association.

  17. Medial branch neurotomy in low back pain

    International Nuclear Information System (INIS)

    Masala, Salvatore; Mammucari, Matteo; Simonetti, Giovanni; Nano, Giovanni; Marcia, Stefano

    2012-01-01

    This study aimed to assess the effectiveness of pulsed radiofrequency medial branch dorsal ramus neurotomy in patients with facet joint syndrome. From January 2008 to April 2010, 92 patients with facet joint syndrome diagnosed by strict inclusion criteria and controlled diagnostic blocks undergone medial branch neurotomy. We did not exclude patients with failed back surgery syndrome (FBSS). Electrodes (20G) with 5-mm active tip were placed under fluoroscopy guide parallel to medial branch. Patients were followed up by physical examination and by Visual Analog Scale and Oswestry Disability Index at 1, 6, and 12 months. In all cases, pain improvement was statistically significant and so quality of life. Three non-FBSS patients had to undergo a second neurotomy because of non-satisfactory pain decrease. Complications were reported in no case. Medial branch radiofrequency neurotomy has confirmed its well-established effectiveness in pain and quality of life improvement as long as strict inclusion criteria be fulfilled and nerve ablation be accomplished by parallel electrode positioning. This statement can be extended also to FBSS patients. (orig.)

  18. Laughter-induced left bundle branch block.

    Science.gov (United States)

    Chow, Grant V; Desai, Dipan; Spragg, David D; Zakaria, Sammy

    2012-10-01

    We present the case of a patient with ischemic heart disease and intermittent left bundle branch block, reproducibly induced by laughter. Following treatment of ischemia with successful deployment of a drug-eluting stent, no further episodes of inducible LBBB were seen. Transient ischemia, exacerbated by elevated intrathoracic pressure during laughter, may have contributed to onset of this phenomenon. © 2012 Wiley Periodicals, Inc.

  19. Branching bisimulation congruence for probabilistic systems

    NARCIS (Netherlands)

    Andova, S.; Georgievska, S.; Trcka, N.

    2012-01-01

    A notion of branching bisimilarity for the alternating model of probabilistic systems, compatible with parallel composition, is defined. For a congruence result, an internal transition immediately followed by a non-trivial probability distribution is not considered inert. A weaker definition of

  20. Infrared studies of asymptotic giant branch stars

    International Nuclear Information System (INIS)

    Willems, F.J.

    1987-01-01

    In this thesis studies are presented of asymptotic giant branch stars, which are thought to be an important link in the evolution of the galaxy. The studies were performed on the basis of data collected by the IRAS, the infrared astronomical satelite. 233 refs.; 33 figs.; 16 tabs

  1. Semileptonic b branching fractions at LEP

    CERN Document Server

    Gagnon, P

    2000-01-01

    I review recent results on semileptonic branching fractions at LEP for Z/sup 0/ to bb data, for the average b hadron then for b baryons. From the inclusive BR(b to lX), one can obtain the most precise value for the CKM matrix element V/sub cb/. (14 refs).

  2. Origin of buds, branches, and sprouts

    Science.gov (United States)

    Kevin T. Smith

    2014-01-01

    Recent research shows that survivor trees in rural, managed forests rebuild broken crowns with new branches and foliage after ice storm injury (Shortle et al. 2014). Veteran trees in historic parks and landscapes show repeated cycles of crown loss and recovery (Fay 2002). Crown rebuilding or reiteration from sprouts is a physiological response with architectural...

  3. High speed CAMAC differential branch highway driver

    International Nuclear Information System (INIS)

    McMillan, D.E.; Nelson, R.O.; Poore, R.V.; Sunier, J.W.; Ross, J.J.

    1979-01-01

    A new CAMAC branch driver is described that incorporates several unusual features which combine to give reliable, high-speed performance. These include balanced line driver/receivers, stored CAMAC command lists, 8 DMA channels, pseudo LAMS, hardware priority encoding of LAMS, and hardware-implemented Q-controlled block transfers. 3 figures

  4. Adaptive Education.

    Science.gov (United States)

    Anderson, Lorin W.

    1979-01-01

    Schools have devised several ways to adapt instruction to a wide variety of student abilities and needs. Judged by criteria for what adaptive education should be, most learning for mastery programs look good. (Author/JM)

  5. Environmental control of branching in petunia.

    Science.gov (United States)

    Drummond, Revel S M; Janssen, Bart J; Luo, Zhiwei; Oplaat, Carla; Ledger, Susan E; Wohlers, Mark W; Snowden, Kimberley C

    2015-06-01

    Plants alter their development in response to changes in their environment. This responsiveness has proven to be a successful evolutionary trait. Here, we tested the hypothesis that two key environmental factors, light and nutrition, are integrated within the axillary bud to promote or suppress the growth of the bud into a branch. Using petunia (Petunia hybrida) as a model for vegetative branching, we manipulated both light quality (as crowding and the red-to-far-red light ratio) and phosphate availability, such that the axillary bud at node 7 varied from deeply dormant to rapidly growing. In conjunction with the phenotypic characterization, we also monitored the state of the strigolactone (SL) pathway by quantifying SL-related gene transcripts. Mutants in the SL pathway inhibit but do not abolish the branching response to these environmental signals, and neither signal is dominant over the other, suggesting that the regulation of branching in response to the environment is complex. We have isolated three new putatively SL-related TCP (for Teosinte branched1, Cycloidia, and Proliferating cell factor) genes from petunia, and have identified that these TCP-type transcription factors may have roles in the SL signaling pathway both before and after the reception of the SL signal at the bud. We show that the abundance of the receptor transcript is regulated by light quality, such that axillary buds growing in added far-red light have greatly increased receptor transcript abundance. This suggests a mechanism whereby the impact of any SL signal reaching an axillary bud is modulated by the responsiveness of these cells to the signal. © 2015 American Society of Plant Biologists. All Rights Reserved.

  6. Tree Branching: Leonardo da Vinci's Rule versus Biomechanical Models

    Science.gov (United States)

    Minamino, Ryoko; Tateno, Masaki

    2014-01-01

    This study examined Leonardo da Vinci's rule (i.e., the sum of the cross-sectional area of all tree branches above a branching point at any height is equal to the cross-sectional area of the trunk or the branch immediately below the branching point) using simulations based on two biomechanical models: the uniform stress and elastic similarity models. Model calculations of the daughter/mother ratio (i.e., the ratio of the total cross-sectional area of the daughter branches to the cross-sectional area of the mother branch at the branching point) showed that both biomechanical models agreed with da Vinci's rule when the branching angles of daughter branches and the weights of lateral daughter branches were small; however, the models deviated from da Vinci's rule as the weights and/or the branching angles of lateral daughter branches increased. The calculated values of the two models were largely similar but differed in some ways. Field measurements of Fagus crenata and Abies homolepis also fit this trend, wherein models deviated from da Vinci's rule with increasing relative weights of lateral daughter branches. However, this deviation was small for a branching pattern in nature, where empirical measurements were taken under realistic measurement conditions; thus, da Vinci's rule did not critically contradict the biomechanical models in the case of real branching patterns, though the model calculations described the contradiction between da Vinci's rule and the biomechanical models. The field data for Fagus crenata fit the uniform stress model best, indicating that stress uniformity is the key constraint of branch morphology in Fagus crenata rather than elastic similarity or da Vinci's rule. On the other hand, mechanical constraints are not necessarily significant in the morphology of Abies homolepis branches, depending on the number of daughter branches. Rather, these branches were often in agreement with da Vinci's rule. PMID:24714065

  7. Tree branching: Leonardo da Vinci's rule versus biomechanical models.

    Science.gov (United States)

    Minamino, Ryoko; Tateno, Masaki

    2014-01-01

    This study examined Leonardo da Vinci's rule (i.e., the sum of the cross-sectional area of all tree branches above a branching point at any height is equal to the cross-sectional area of the trunk or the branch immediately below the branching point) using simulations based on two biomechanical models: the uniform stress and elastic similarity models. Model calculations of the daughter/mother ratio (i.e., the ratio of the total cross-sectional area of the daughter branches to the cross-sectional area of the mother branch at the branching point) showed that both biomechanical models agreed with da Vinci's rule when the branching angles of daughter branches and the weights of lateral daughter branches were small; however, the models deviated from da Vinci's rule as the weights and/or the branching angles of lateral daughter branches increased. The calculated values of the two models were largely similar but differed in some ways. Field measurements of Fagus crenata and Abies homolepis also fit this trend, wherein models deviated from da Vinci's rule with increasing relative weights of lateral daughter branches. However, this deviation was small for a branching pattern in nature, where empirical measurements were taken under realistic measurement conditions; thus, da Vinci's rule did not critically contradict the biomechanical models in the case of real branching patterns, though the model calculations described the contradiction between da Vinci's rule and the biomechanical models. The field data for Fagus crenata fit the uniform stress model best, indicating that stress uniformity is the key constraint of branch morphology in Fagus crenata rather than elastic similarity or da Vinci's rule. On the other hand, mechanical constraints are not necessarily significant in the morphology of Abies homolepis branches, depending on the number of daughter branches. Rather, these branches were often in agreement with da Vinci's rule.

  8. Synergy of multi-scale toughening and protective mechanisms at hierarchical branch-stem interfaces

    Science.gov (United States)

    Müller, Ulrich; Gindl-Altmutter, Wolfgang; Konnerth, Johannes; Maier, Günther A.; Keckes, Jozef

    2015-09-01

    Biological materials possess a variety of artful interfaces whose size and properties are adapted to their hierarchical levels and functional requirements. Bone, nacre, and wood exhibit an impressive fracture resistance based mainly on small crystallite size, interface organic adhesives and hierarchical microstructure. Currently, little is known about mechanical concepts in macroscopic biological interfaces like the branch-stem junction with estimated 1014 instances on earth and sizes up to few meters. Here we demonstrate that the crack growth in the upper region of the branch-stem interface of conifer trees proceeds along a narrow predefined region of transversally loaded tracheids, denoted as sacrificial tissue, which fail upon critical bending moments on the branch. The specific arrangement of the tracheids allows disconnecting the overloaded branch from the stem in a controlled way by maintaining the stem integrity. The interface microstructure based on the sharply adjusted cell orientation and cell helical angle secures a zig-zag crack propagation path, mechanical interlock closing after the bending moment is removed, crack gap bridging and self-repairing by resin deposition. The multi-scale synergetic concepts allows for a controllable crack growth between stiff stem and flexible branch, as well as mechanical tree integrity, intact physiological functions and recovery after the cracking.

  9. Dorsal Branches of Abdominal Aorta in the Rabbit and the European Hare

    Directory of Open Access Journals (Sweden)

    Flešárová S.

    2016-06-01

    Full Text Available The aim of this study was to describe the anatomical arrangement of the branches arising from the dorsal surface of the aorta abdominalis in the rabbit and the hare. The study was carried out on ten adult rabbits and ten adult European hares using the corrosion technique. After the euthanasia, the vascular network was perfused with saline. After polymerization of the casting medium, the maceration was carried out in a KOH solution. We found different variations in; the number of arteries, level of their origin and arrangement. The aa. lumbales of the same level arose by means of a common trunk or their origin was independent. The aa. lumbales VI or aa. lumbales VI et VII originated also from the a. sacralis mediana. By aa. lumbales we found an important interspecies difference in; number, diameter, ramification and density of dorsal branches, which are designated for the dorsal muscles of the body stem. All listed parameters of branches were higher in the hare. This anatomical arrangement of dorsal branches is adapted to the higher movement activity of the hare. According to our results, it can be concluded that the anatomical arrangement of the branches of the aorta abdominalis shows a higher number of variations in the domesticated rabbit in comparison with the hare.

  10. New Measurement of the π → eν branching ratio

    International Nuclear Information System (INIS)

    Dixit, M.S.; Bryman, D.A.; Dubois, R.; Numao, T.; Olaniyi, B.; Olin, A.; Berghofer, D.; Poutissou, J.-M.; Macdonald, J.A.

    1982-11-01

    A new measurement of the π → eν branching ratio yields GAMMA(π→eν + π→eνγ) / GAMMA(π→μν + π→γνμ) = (1.218 +- 0.014) x 10 -4 . The measured value is in good agreement with the standard model prediction incorporating electron-muon universality

  11. Expression and characterization of thermostable glycogen branching enzyme from Geobacillus mahadia Geo-05

    Directory of Open Access Journals (Sweden)

    Nur Syazwani Mohtar

    2016-12-01

    Full Text Available The glycogen branching enzyme (EC 2.4.1.18, which catalyses the formation of α-1,6-glycosidic branch points in glycogen structure, is often used to enhance the nutritional value and quality of food and beverages. In order to be applicable in industries, enzymes that are stable and active at high temperature are much desired. Using genome mining, the nucleotide sequence of the branching enzyme gene (glgB was extracted from the Geobacillus mahadia Geo-05 genome sequence provided by the Malaysia Genome Institute. The size of the gene is 2013 bp, and the theoretical molecular weight of the protein is 78.43 kDa. The gene sequence was then used to predict the thermostability, function and the three dimensional structure of the enzyme. The gene was cloned and overexpressed in E. coli to verify the predicted result experimentally. The purified enzyme was used to study the effect of temperature and pH on enzyme activity and stability, and the inhibitory effect by metal ion on enzyme activity. This thermostable glycogen branching enzyme was found to be most active at 55 °C, and the half-life at 60 °C and 70 °C was 24 h and 5 h, respectively. From this research, a thermostable glycogen branching enzyme was successfully isolated from Geobacillus mahadia Geo-05 by genome mining together with molecular biology technique.

  12. 3rd Workshop on Branching Processes and their Applications

    CERN Document Server

    González, Miguel; Gutiérrez, Cristina; Martínez, Rodrigo; Minuesa, Carmen; Molina, Manuel; Mota, Manuel; Ramos, Alfonso; WBPA15

    2016-01-01

    This volume gathers papers originally presented at the 3rd Workshop on Branching Processes and their Applications (WBPA15), which was held from 7 to 10 April 2015 in Badajoz, Spain (http://branching.unex.es/wbpa15/index.htm). The papers address a broad range of theoretical and practical aspects of branching process theory. Further, they amply demonstrate that the theoretical research in this area remains vital and topical, as well as the relevance of branching concepts in the development of theoretical approaches to solving new problems in applied fields such as Epidemiology, Biology, Genetics, and, of course, Population Dynamics. The topics covered can broadly be classified into the following areas: 1. Coalescent Branching Processes 2. Branching Random Walks 3. Population Growth Models in Varying and Random Environments 4. Size/Density/Resource-Dependent Branching Models 5. Age-Dependent Branching Models 6. Special Branching Models 7. Applications in Epidemiology 8. Applications in Biology and Genetics Offer...

  13. Adaptive Lighting

    DEFF Research Database (Denmark)

    Petersen, Kjell Yngve; Søndergaard, Karin; Kongshaug, Jesper

    2015-01-01

    Adaptive Lighting Adaptive lighting is based on a partial automation of the possibilities to adjust the colour tone and brightness levels of light in order to adapt to people’s needs and desires. IT support is key to the technical developments that afford adaptive control systems. The possibilities...... offered by adaptive lighting control are created by the ways that the system components, the network and data flow can be coordinated through software so that the dynamic variations are controlled in ways that meaningfully adapt according to people’s situations and design intentions. This book discusses...... differently into an architectural body. We also examine what might occur when light is dynamic and able to change colour, intensity and direction, and when it is adaptive and can be brought into interaction with its surroundings. In short, what happens to an architectural space when artificial lighting ceases...

  14. Distribution of degrees of polymerization in statistically branched polymers with tetrafunctional branch points: model calculations

    Czech Academy of Sciences Publication Activity Database

    Netopilík, Miloš; Kratochvíl, Pavel

    2006-01-01

    Roč. 55, č. 2 (2006), s. 196-203 ISSN 0959-8103 R&D Projects: GA AV ČR IAA100500501; GA AV ČR IAA4050403; GA AV ČR IAA4050409; GA ČR GA203/03/0617 Institutional research plan: CEZ:AV0Z40500505 Keywords : statistical branching * tetrafunctional branch points * molecular-weight distribution Subject RIV: CD - Macromolecular Chemistry Impact factor: 1.475, year: 2006

  15. Individual Differences in Computerized Adaptive Testing.

    Science.gov (United States)

    Kim, JinGyu

    Research on the major computerized adaptive testing (CAT) strategies is reviewed, and some findings are reported that examine effects of examinee demographic and psychological characteristics on CAT strategies. In fixed branching strategies, all examinees respond to a common routing test, the score of which is used to assign examinees to a…

  16. Inferring the gene network underlying the branching of tomato inflorescence.

    Directory of Open Access Journals (Sweden)

    Laura Astola

    Full Text Available The architecture of tomato inflorescence strongly affects flower production and subsequent crop yield. To understand the genetic activities involved, insight into the underlying network of genes that initiate and control the sympodial growth in the tomato is essential. In this paper, we show how the structure of this network can be derived from available data of the expressions of the involved genes. Our approach starts from employing biological expert knowledge to select the most probable gene candidates behind branching behavior. To find how these genes interact, we develop a stepwise procedure for computational inference of the network structure. Our data consists of expression levels from primary shoot meristems, measured at different developmental stages on three different genotypes of tomato. With the network inferred by our algorithm, we can explain the dynamics corresponding to all three genotypes simultaneously, despite their apparent dissimilarities. We also correctly predict the chronological order of expression peaks for the main hubs in the network. Based on the inferred network, using optimal experimental design criteria, we are able to suggest an informative set of experiments for further investigation of the mechanisms underlying branching behavior.

  17. Modeling adaptive and non-adaptive responses to environmental change

    DEFF Research Database (Denmark)

    Coulson, Tim; Kendall, Bruce E; Barthold, Julia A.

    2017-01-01

    , with plastic responses being either adaptive or non-adaptive. We develop an approach that links quantitative genetic theory with data-driven structured models to allow prediction of population responses to environmental change via plasticity and adaptive evolution. After introducing general new theory, we...... construct a number of example models to demonstrate that evolutionary responses to environmental change over the short-term will be considerably slower than plastic responses, and that the rate of adaptive evolution to a new environment depends upon whether plastic responses are adaptive or non-adaptive....... Parameterization of the models we develop requires information on genetic and phenotypic variation and demography that will not always be available, meaning that simpler models will often be required to predict responses to environmental change. We consequently develop a method to examine whether the full...

  18. Fort Collins Science Center Ecosystem Dynamics Branch

    Science.gov (United States)

    Wilson, Jim; Melcher, C.; Bowen, Z.

    2009-01-01

    Complex natural resource issues require understanding a web of interactions among ecosystem components that are (1) interdisciplinary, encompassing physical, chemical, and biological processes; (2) spatially complex, involving movements of animals, water, and airborne materials across a range of landscapes and jurisdictions; and (3) temporally complex, occurring over days, weeks, or years, sometimes involving response lags to alteration or exhibiting large natural variation. Scientists in the Ecosystem Dynamics Branch of the U.S. Geological Survey, Fort Collins Science Center, investigate a diversity of these complex natural resource questions at the landscape and systems levels. This Fact Sheet describes the work of the Ecosystems Dynamics Branch, which is focused on energy and land use, climate change and long-term integrated assessments, herbivore-ecosystem interactions, fire and post-fire restoration, and environmental flows and river restoration.

  19. Photovoltaic Program Branch annual report, FY 1989

    Energy Technology Data Exchange (ETDEWEB)

    Summers, K A [ed.

    1990-03-01

    This report summarizes the progress of the Photovoltaic (PV) Program Branch of the Solar Energy Research Institute (SERI) from October 1, 1988, through September 30, 1989. The branch is responsible for managing the subcontracted portion of SERI's PV Advanced Research and Development Project. In fiscal year (FY) 1989, this included nearly 50 subcontracts, with a total annualized funding of approximately $13.1 million. Approximately two-thirds of the subcontracts were with universities, at a total funding of nearly $4 million. The six technical sections of the report cover the main areas of the subcontracted program: Amorphous Silicon Research, Polycrystalline Thin Films, Crystalline Silicon Materials Research, High-Efficiency Concepts, New Ideas, and University Participation. Technical summaries of each of the subcontracted programs provide a discussion of approaches, major accomplishments in FY 1989, and future research directions. Each report will be cataloged individually.

  20. Mass loss on the Asymptotic Giant Branch

    OpenAIRE

    Zijlstra, Albert

    2006-01-01

    Mass loss on the Asymptotic Giant Branch provides the origin of planetary nebulae. This paper reviews several relevant aspects of AGB evolution: pulsation properties, mass loss formalisms and time variable mass loss, evidence for asymmetries on the AGB, binarity, ISM interaction, and mass loss at low metallicity. There is growing evidence that mass loss on the AGB is already asymmetric, but with spherically symmetric velocity fields. The origin of the rings may be in pulsational instabilities...

  1. Bent and branched chains of nanoresonators

    Science.gov (United States)

    Melikhova, A. S.; Popov, I. Yu

    2014-10-01

    We study the spectral problem for bent and branched chains of weakly coupled conglobate resonators. At the joint points the δ-coupling is assumed. Our approach is based on the theory of self-adjoint extensions of symmetric operators and transfer matrix method. The structure of the spectrum is described. For the both cases it is proved that the Hamiltonian has negative eigenvalue for some values of the model parameters.

  2. COELIAC TRUNK BRANCHING PATTERN AND VARIATION

    Directory of Open Access Journals (Sweden)

    Jude Jose Thomson

    2017-01-01

    Full Text Available BACKGROUND Anatomical variations involving the visceral arteries are common. However, variations in coeliac trunk are usually asymptomatic, they may become important in patients undergoing diagnostic angiography for gastrointestinal bleeding or prior to an operative procedure. This study was useful for knowing the possible morphological variations before an upper abdominal surgery. MATERIALS AND METHODS This was a descriptive study done by cadaveric dissection, conducted on thirty cadavers. The coeliac trunk being examined for its origin, branching pattern, distribution, and variations. Results were statistically analysed and compared with the previous studies. RESULTS In our study, 60% of the coeliac trunk shows variations and 40% have normal branching pattern. A complete absence of coeliac trunk was observed in one case. In the present study the Right inferior phrenic artery arising from coeliac trunk in 2 cases (6.6% and left inferior phrenic artery arising from coeliac trunk in 3 cases (9.9%. Both inferior phrenic arteries are arising from coeliac trunk in 2 cases (6.6%. The common hepatomesenteric trunk and gastro splenic trunk was found in 1 case (3.3%. Hepatosplenic trunk was found in 2 cases (6.6%. In another 2 cases (6.6% gastric and hepatic artery originate from coeliac trunk but splenic artery has a separate origin from abdominal aorta. An absent trunk was also found in 1 case (3.3%. In 5 cases (16.7% showed trifurcation with variation in the branching pattern. CONCLUSION The branching pattern and extreme degree variability in coeliac trunk as brought out in the observations of the present study make it obvious that the present study almost falls in description with previous studies.

  3. Prediction of settled water turbidity and optimal coagulant dosage in drinking water treatment plant using a hybrid model of k-means clustering and adaptive neuro-fuzzy inference system

    Science.gov (United States)

    Kim, Chan Moon; Parnichkun, Manukid

    2017-11-01

    Coagulation is an important process in drinking water treatment to attain acceptable treated water quality. However, the determination of coagulant dosage is still a challenging task for operators, because coagulation is nonlinear and complicated process. Feedback control to achieve the desired treated water quality is difficult due to lengthy process time. In this research, a hybrid of k-means clustering and adaptive neuro-fuzzy inference system ( k-means-ANFIS) is proposed for the settled water turbidity prediction and the optimal coagulant dosage determination using full-scale historical data. To build a well-adaptive model to different process states from influent water, raw water quality data are classified into four clusters according to its properties by a k-means clustering technique. The sub-models are developed individually on the basis of each clustered data set. Results reveal that the sub-models constructed by a hybrid k-means-ANFIS perform better than not only a single ANFIS model, but also seasonal models by artificial neural network (ANN). The finally completed model consisting of sub-models shows more accurate and consistent prediction ability than a single model of ANFIS and a single model of ANN based on all five evaluation indices. Therefore, the hybrid model of k-means-ANFIS can be employed as a robust tool for managing both treated water quality and production costs simultaneously.

  4. Fabrication and characterization of branched carbon nanostructures

    Directory of Open Access Journals (Sweden)

    Sharali Malik

    2016-09-01

    Full Text Available Carbon nanotubes (CNTs have atomically smooth surfaces and tend not to form covalent bonds with composite matrix materials. Thus, it is the magnitude of the CNT/fiber interfacial strength that limits the amount of nanomechanical interlocking when using conventional CNTs to improve the structural behavior of composite materials through reinforcement. This arises from two well-known, long standing problems in this research field: (a inhomogeneous dispersion of the filler, which can lead to aggregation and (b insufficient reinforcement arising from bonding interactions between the filler and the matrix. These dispersion and reinforcement issues could be addressed by using branched multiwalled carbon nanotubes (b-MWCNTs as it is known that branched fibers can greatly enhance interfacial bonding and dispersability. Therefore, the use of b-MWCNTs would lead to improved mechanical performance and, in the case of conductive composites, improved electrical performance if the CNT filler was better dispersed and connected. This will provide major benefits to the existing commercial application of CNT-reinforced composites in electrostatic discharge materials (ESD: There would be also potential usage for energy conversion, e.g., in supercapacitors, solar cells and Li-ion batteries. However, the limited availability of b-MWCNTs has, to date, restricted their use in such technological applications. Herein, we report an inexpensive and simple method to fabricate large amounts of branched-MWCNTs, which opens the door to a multitude of possible applications.

  5. Cold versus hot fusion deuterium branching ratios

    International Nuclear Information System (INIS)

    Fox, H.; Bass, R.

    1995-01-01

    A major source of misunderstanding of the nature of cold nuclear fusion has been the expectation that the deuterium branching ratios occurring within a palladium lattice would be consistent with the gas-plasma branching ratios. This misunderstanding has led to the concept of the dead graduate student, the 1989's feverish but fruitless search for neutron emissions from cold fusion reactors, and the follow-on condemnation of the new science of cold fusion. The experimental facts are that in a properly loaded palladium lattice, the deuterium fusion produces neutrons at little above background, a greatly less-than-expected production of tritium (the tritium desert), and substantially more helium-4 than is observed in hot plasma physics. The experimental evidence is now compelling (800 reports of success from 30 countries) that cold nuclear fusion is a reality, that the branching ratios are unexpected, and that a new science is struggling to be recognized. Commercialization of some types of cold fusion devices has already begun

  6. Controlling smart grid adaptivity

    OpenAIRE

    Toersche, Hermen; Nykamp, Stefan; Molderink, Albert; Hurink, Johann L.; Smit, Gerardus Johannes Maria

    2012-01-01

    Methods are discussed for planning oriented smart grid control to cope with scenarios with limited predictability, supporting an increasing penetration of stochastic renewable resources. The performance of these methods is evaluated with simulations using measured wind generation and consumption data. Forecast errors are shown to affect worst case behavior in particular, the severity of which depends on the chosen adaptivity strategy and error model.

  7. SETD2 loss-of-function promotes renal cancer branched evolution through replication stress and impaired DNA repair

    DEFF Research Database (Denmark)

    Kanu, N.; Grönroos, E.; Martinez, P.

    2015-01-01

    Defining mechanisms that generate intratumour heterogeneity and branched evolution may inspire novel therapeutic approaches to limit tumour diversity and adaptation. SETD2 (Su(var), Enhancer of zeste, Trithorax-domain containing 2) trimethylates histone-3 lysine-36 (H3K36me3) at sites of active t...

  8. Computational Modeling of Hypothalamic-Pituitary-Gonadal Axis to Predict Adaptive Responses in Female Fathead Minnows Exposed to an Aromatase Inhibitor

    Science.gov (United States)

    Exposure to endocrine disrupting chemicals can affect reproduction and development in both humans and wildlife. We are developing a mechanistic computational model of the hypothalamic-pituitary-gonadal (HPG) axis in female fathead minnows to predict dose response and time-course...

  9. ADAPT Dataset

    Data.gov (United States)

    National Aeronautics and Space Administration — Advanced Diagnostics and Prognostics Testbed (ADAPT) Project Lead: Scott Poll Subject Fault diagnosis in electrical power systems Description The Advanced...

  10. Measurement of the K+ --> pi+ nu nu branching ratio

    Energy Technology Data Exchange (ETDEWEB)

    Adler, S.; /Brookhaven; Anisimovsky, V.V.; /Moscow, INR; Aoki, M.; /TRIUMF; Ardebili, M.; /Princeton U.; Artamonov, A.V.; /Serpukhov, IHEP; Atiya, M.; /Brookhaven; Bassalleck, B.; /New Mexico U.; Bazarko, A.O.; /Princeton U.; Bhuyan, B.; /Brookhaven; Blackmore, E.W.; /TRIUMF; Bryman, D.A.; /British Columbia U. /Tsinghua U., Beijing /TRIUMF

    2008-03-01

    Experiment E949 at Brookhaven National Laboratory studied the rare decay K{sup +}-->pi{sup +} nu{ovr {nu}} and other processes with an exposure of 1.77 x 10{sup 12} k{sup +}'s. The data were analyzed using a blind analysis technique yielding one candidate event with an estimated background of 0.30 {+-} 0.03 events. Combining this result with the observation of two candidate events by the predecessor experiment E787 gave the branching ratio B(K{sup +}-->pi{sup +} nu{ovr {nu}}) = (1.47{sub -0.89}{sup +1.30}) x 10{sup -10}, consistent with the standard model prediction of (0.74 {+-} 0.20) x 10{sup -10}. This is a more detailed report of results previously published [V.V. Anisimovsky et al., Phys. Rev. Lett. 93, 031801 (2004)].

  11. FLUORINE ABUNDANCES IN GALACTIC ASYMPTOTIC GIANT BRANCH STARS

    International Nuclear Information System (INIS)

    Abia, C.; Cristallo, S.; DomInguez, I.; Cunha, K.; Hinkle, K.; Smith, V. V.; De Laverny, P.; Recio-Blanco, A.; Eriksson, K.; Wahlin, R.; Gialanella, L.; Imbriani, G.; Straniero, O.

    2010-01-01

    An analysis of the fluorine abundance in Galactic asymptotic giant branch (AGB) carbon stars (24 N-type, 5 SC-type, and 5 J-type) is presented. This study uses the state-of-the-art carbon-rich atmosphere models and improved atomic and molecular line lists in the 2.3 μm region. Significantly lower F abundances are obtained in comparison to previous studies in the literature. This difference is mainly due to molecular blends. In the case of carbon stars of SC-type, differences in the model atmospheres are also relevant. The new F enhancements are now in agreement with the most recent theoretical nucleosynthesis models in low-mass AGB stars, solving the long-standing problem of F in Galactic AGB stars. Nevertheless, some SC-type carbon stars still show larger F abundances than predicted by stellar models. The possibility that these stars are of larger mass is briefly discussed.

  12. Optimization of multi-branch switched diversity systems

    KAUST Repository

    Nam, Haewoon; Alouini, Mohamed-Slim

    2009-01-01

    A performance optimization based on the optimal switching threshold(s) for a multi-branch switched diversity system is discussed in this paper. For the conventional multi-branch switched diversity system with a single switching threshold

  13. Auxin transport in the evolution of branching forms.

    Science.gov (United States)

    Harrison, C Jill

    2017-07-01

    Contents 545 I. 545 II. 546 III. 546 IV. 548 V. 548 VI. 549 VII. 549 Acknowledgements 549 References 549 SUMMARY: Branching is one of the most striking aspects of land plant architecture, affecting resource acquisition and yield. Polar auxin transport by PIN proteins is a primary determinant of flowering plant branching patterns regulating both branch initiation and branch outgrowth. Several lines of experimental evidence suggest that PIN-mediated polar auxin transport is a conserved regulator of branching in vascular plant sporophytes. However, the mechanisms of branching and auxin transport and relationships between the two are not well known outside the flowering plants, and the paradigm for PIN-regulated branching in flowering plants does not fit bryophyte gametophytes. The evidence reviewed here suggests that divergent auxin transport routes contributed to the diversification of branching forms in distinct land plant lineages. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

  14. Collinear and TMD quark and gluon densities from parton branching solution of QCD evolution equations

    Energy Technology Data Exchange (ETDEWEB)

    Hautmann, F. [Rutherford Appleton Laboratory, Chilton (United Kingdom); Oxford Univ. (United Kingdom). Dept. of Theoretical Physics; Antwerpen Univ. (Belgium). Elementaire Deeltjes Fysica; Jung, H.; Lelek, A.; Zlebcik, R. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Radescu, V. [European Organization for Nuclear Research (CERN), Geneva (Switzerland)

    2017-08-15

    We study parton-branching solutions of QCD evolution equations and present a method to construct both collinear and transverse momentum dependent (TMD) parton densities from this approach. We work with next-to-leading-order (NLO) accuracy in the strong coupling. Using the unitarity picture in terms of resolvable and non-resolvable branchings, we analyze the role of the soft-gluon resolution scale in the evolution equations. For longitudinal momentum distributions, we find agreement of our numerical calculations with existing evolution programs at the level of better than 1 percent over a range of five orders of magnitude both in evolution scale and in longitudinal momentum fraction. We make predictions for the evolution of transverse momentum distributions. We perform fits to the high-precision deep inelastic scattering (DIS) structure function measurements, and we present a set of NLO TMD distributions based on the parton branching approach.

  15. Asymptotic behaviour near extinction of continuous-state branching processes

    OpenAIRE

    Berzunza, Gabriel; Pardo, Juan Carlos

    2016-01-01

    In this note, we study the asymptotic behaviour near extinction of (sub-) critical continuous state branching processes. In particular, we establish an analogue of Khintchin's law of the iterated logarithm near extinction time for a continuous state branching process whose branching mechanism satisfies a given condition and its reflected process at its infimum.

  16. 40 CFR 721.10094 - Decene, branched and linear.

    Science.gov (United States)

    2010-07-01

    ... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Decene, branched and linear. 721.10094... Substances § 721.10094 Decene, branched and linear. (a) Chemical substance and significant new uses subject to reporting. (1) The chemical substance identified as decene, branched and linear (PMN P-03-272; CAS...

  17. 40 CFR 721.3627 - Branched synthetic fatty acid.

    Science.gov (United States)

    2010-07-01

    ... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Branched synthetic fatty acid. 721... Substances § 721.3627 Branched synthetic fatty acid. (a) Chemical substance and significant new uses subject to reporting. (1) The chemical substance identified generically as a branched synthetic fatty acid...

  18. Ambiguous Adaptation

    DEFF Research Database (Denmark)

    Møller Larsen, Marcus; Lyngsie, Jacob

    2017-01-01

    We investigate the connection between contract duration, relational mechanisms, and premature relationship termination. Based on an analysis of a large sample of exchange relationships in the global service-provider industry, we argue that investments in either longer contract duration or more in...... ambiguous reference points for adaption and thus increase the likelihood of premature termination by restricting the parties' set of adaptive actions....

  19. Climate adaptation

    Science.gov (United States)

    Kinzig, Ann P.

    2015-03-01

    This paper is intended as a brief introduction to climate adaptation in a conference devoted otherwise to the physics of sustainable energy. Whereas mitigation involves measures to reduce the probability of a potential event, such as climate change, adaptation refers to actions that lessen the impact of climate change. Mitigation and adaptation differ in other ways as well. Adaptation does not necessarily have to be implemented immediately to be effective; it only needs to be in place before the threat arrives. Also, adaptation does not necessarily require global, coordinated action; many effective adaptation actions can be local. Some urban communities, because of land-use change and the urban heat-island effect, currently face changes similar to some expected under climate change, such as changes in water availability, heat-related morbidity, or changes in disease patterns. Concern over those impacts might motivate the implementation of measures that would also help in climate adaptation, despite skepticism among some policy makers about anthropogenic global warming. Studies of ancient civilizations in the southwestern US lends some insight into factors that may or may not be important to successful adaptation.

  20. Estimating the Propagation of Interdependent Cascading Outages with Multi-Type Branching Processes

    Energy Technology Data Exchange (ETDEWEB)

    Qi, Junjian; Ju, Wenyun; Sun, Kai

    2016-01-01

    In this paper, the multi-type branching process is applied to describe the statistics and interdependencies of line outages, the load shed, and isolated buses. The offspring mean matrix of the multi-type branching process is estimated by the Expectation Maximization (EM) algorithm and can quantify the extent of outage propagation. The joint distribution of two types of outages is estimated by the multi-type branching process via the Lagrange-Good inversion. The proposed model is tested with data generated by the AC OPA cascading simulations on the IEEE 118-bus system. The largest eigenvalues of the offspring mean matrix indicate that the system is closer to criticality when considering the interdependence of different types of outages. Compared with empirically estimating the joint distribution of the total outages, good estimate is obtained by using the multitype branching process with a much smaller number of cascades, thus greatly improving the efficiency. It is shown that the multitype branching process can effectively predict the distribution of the load shed and isolated buses and their conditional largest possible total outages even when there are no data of them.