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Sample records for predictive state representations

  1. Representable states on quasilocal quasi *-algebras

    SciTech Connect

    Bagarello, F.; Trapani, C.; Triolo, S.

    2011-01-15

    Continuing a previous analysis originally motivated by physics, we consider representable states on quasilocal quasi *-algebras, starting with examining the possibility for a compatible family of local states to give rise to a global state. Some properties of local modifications of representable states and some aspects of their asymptotic behavior are also considered.

  2. On state representations of nonlinear implicit systems

    NASA Astrophysics Data System (ADS)

    Pereira da Silva, Paulo Sergio; Batista, Simone

    2010-03-01

    This work considers a semi-implicit system Δ, that is, a pair (S, y), where S is an explicit system described by a state representation ? , where x(t) ∈ ℝ n and u(t) ∈ ℝ m , which is subject to a set of algebraic constraints y(t) = h(t, x(t), u(t)) = 0, where y(t) ∈ ℝ l . An input candidate is a set of functions v = (v 1, …, v s ), which may depend on time t, on x, and on u and its derivatives up to a finite order. The problem of finding a (local) proper state representation ż = g(t, z, v) with input v for the implicit system Δ is studied in this article. The main result shows necessary and sufficient conditions for the solution of this problem, under mild assumptions on the class of admissible state representations of Δ. These solvability conditions rely on an integrability test that is computed from the explicit system S. The approach of this article is the infinite-dimensional differential geometric setting of Fliess, Lévine, Martin, and Rouchon (1999) ('A Lie-Bäcklund Approach to Equivalence and Flatness of Nonlinear Systems', IEEE Transactions on Automatic Control, 44(5), (922-937)).

  3. Thermodynamic depth of causal states: Objective complexity via minimal representations

    SciTech Connect

    Crutchfield, J.P. |; Shalizi, C.R. |

    1999-01-01

    Thermodynamic depth is an appealing but flawed structural complexity measure. It depends on a set of macroscopic states for a system, but neither its original introduction by Lloyd and Pagels nor any follow-up work has considered how to select these states. Depth, therefore, is at root arbitrary. Computational mechanics, an alternative approach to structural complexity, provides a definition for a system{close_quote}s minimal, necessary causal states and a procedure for finding them. We show that the rate of increase in thermodynamic depth, or {ital dive}, is the system{close_quote}s reverse-time Shannon entropy rate, and so depth only measures degrees of macroscopic randomness, not structure. To fix this, we redefine the depth in terms of the causal state representation{emdash}{epsilon}-machines{emdash}and show that this representation gives the minimum dive consistent with accurate prediction. Thus, {epsilon}-machines are optimally shallow. {copyright} {ital 1999} {ital The American Physical Society}

  4. Acoustic and Lexical Representations for Affect Prediction in Spontaneous Conversations

    PubMed Central

    Cao, Houwei; Savran, Arman; Verma, Ragini; Nenkova, Ani

    2014-01-01

    In this article we investigate what representations of acoustics and word usage are most suitable for predicting dimensions of affect|AROUSAL, VALANCE, POWER and EXPECTANCY|in spontaneous interactions. Our experiments are based on the AVEC 2012 challenge dataset. For lexical representations, we compare corpus-independent features based on psychological word norms of emotional dimensions, as well as corpus-dependent representations. We find that corpus-dependent bag of words approach with mutual information between word and emotion dimensions is by far the best representation. For the analysis of acoustics, we zero in on the question of granularity. We confirm on our corpus that utterance-level features are more predictive than word-level features. Further, we study more detailed representations in which the utterance is divided into regions of interest (ROI), each with separate representation. We introduce two ROI representations, which significantly outperform less informed approaches. In addition we show that acoustic models of emotion can be improved considerably by taking into account annotator agreement and training the model on smaller but reliable dataset. Finally we discuss the potential for improving prediction by combining the lexical and acoustic modalities. Simple fusion methods do not lead to consistent improvements over lexical classifiers alone but improve over acoustic models. PMID:25382936

  5. A new protein structure representation for efficient protein function prediction.

    PubMed

    Maghawry, Huda A; Mostafa, Mostafa G M; Gharib, Tarek F

    2014-12-01

    One of the challenging problems in bioinformatics is the prediction of protein function. Protein function is the main key that can be used to classify different proteins. Protein function can be inferred experimentally with very small throughput or computationally with very high throughput. Computational methods are sequence based or structure based. Structure-based methods produce more accurate protein function prediction. In this article, we propose a new protein structure representation for efficient protein function prediction. The representation is based on three-dimensional patterns of protein residues. In the analysis, we used protein function based on enzyme activity through six mechanistically diverse enzyme superfamilies: amidohydrolase, crotonase, haloacid dehalogenase, isoprenoid synthase type I, and vicinal oxygen chelate. We applied three different classification methods, naïve Bayes, k-nearest neighbors, and random forest, to predict the enzyme superfamily of a given protein. The prediction accuracy using the proposed representation outperforms a recently introduced representation method that is based only on the distance patterns. The results show that the proposed representation achieved prediction accuracy up to 98%, with improvement of about 10% on average. PMID:25343279

  6. The Representation of Prediction Error in Auditory Cortex.

    PubMed

    Rubin, Jonathan; Ulanovsky, Nachum; Nelken, Israel; Tishby, Naftali

    2016-08-01

    To survive, organisms must extract information from the past that is relevant for their future. How this process is expressed at the neural level remains unclear. We address this problem by developing a novel approach from first principles. We show here how to generate low-complexity representations of the past that produce optimal predictions of future events. We then illustrate this framework by studying the coding of 'oddball' sequences in auditory cortex. We find that for many neurons in primary auditory cortex, trial-by-trial fluctuations of neuronal responses correlate with the theoretical prediction error calculated from the short-term past of the stimulation sequence, under constraints on the complexity of the representation of this past sequence. In some neurons, the effect of prediction error accounted for more than 50% of response variability. Reliable predictions often depended on a representation of the sequence of the last ten or more stimuli, although the representation kept only few details of that sequence. PMID:27490251

  7. The Representation of Prediction Error in Auditory Cortex

    PubMed Central

    Rubin, Jonathan; Ulanovsky, Nachum; Tishby, Naftali

    2016-01-01

    To survive, organisms must extract information from the past that is relevant for their future. How this process is expressed at the neural level remains unclear. We address this problem by developing a novel approach from first principles. We show here how to generate low-complexity representations of the past that produce optimal predictions of future events. We then illustrate this framework by studying the coding of ‘oddball’ sequences in auditory cortex. We find that for many neurons in primary auditory cortex, trial-by-trial fluctuations of neuronal responses correlate with the theoretical prediction error calculated from the short-term past of the stimulation sequence, under constraints on the complexity of the representation of this past sequence. In some neurons, the effect of prediction error accounted for more than 50% of response variability. Reliable predictions often depended on a representation of the sequence of the last ten or more stimuli, although the representation kept only few details of that sequence. PMID:27490251

  8. Multilevel Atomic Coherent States and Atomic Holomorphic Representation

    NASA Technical Reports Server (NTRS)

    Cao, Chang-Qi; Haake, Fritz

    1996-01-01

    The notion of atomic coherent states is extended to the case of multilevel atom collective. Based on atomic coherent states, a holomorphic representation for atom collective states and operators is defined. An example is given to illustrate its application.

  9. Visualizing spin states using the spin coherent state representation

    NASA Astrophysics Data System (ADS)

    Lee Loh, Yen; Kim, Monica

    2015-01-01

    Orbital angular momentum eigenfunctions are readily understood in terms of spherical harmonics. However, the quantum mechanical phenomenon of spin is often said to be mysterious and hard to visualize, with no classical analog. Many textbooks give a heuristic and somewhat unsatisfying picture of a precessing spin vector. Here, we show that the spin-coherent-state representation is a striking, elegant, and mathematically meaningful tool for visualizing spin states. We also demonstrate that cartographic projections such as the Hammer projection are useful for visualizing functions defined on spherical surfaces.

  10. Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records

    PubMed Central

    Miotto, Riccardo; Li, Li; Kidd, Brian A.; Dudley, Joel T.

    2016-01-01

    Secondary use of electronic health records (EHRs) promises to advance clinical research and better inform clinical decision making. Challenges in summarizing and representing patient data prevent widespread practice of predictive modeling using EHRs. Here we present a novel unsupervised deep feature learning method to derive a general-purpose patient representation from EHR data that facilitates clinical predictive modeling. In particular, a three-layer stack of denoising autoencoders was used to capture hierarchical regularities and dependencies in the aggregated EHRs of about 700,000 patients from the Mount Sinai data warehouse. The result is a representation we name “deep patient”. We evaluated this representation as broadly predictive of health states by assessing the probability of patients to develop various diseases. We performed evaluation using 76,214 test patients comprising 78 diseases from diverse clinical domains and temporal windows. Our results significantly outperformed those achieved using representations based on raw EHR data and alternative feature learning strategies. Prediction performance for severe diabetes, schizophrenia, and various cancers were among the top performing. These findings indicate that deep learning applied to EHRs can derive patient representations that offer improved clinical predictions, and could provide a machine learning framework for augmenting clinical decision systems. PMID:27185194

  11. Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records.

    PubMed

    Miotto, Riccardo; Li, Li; Kidd, Brian A; Dudley, Joel T

    2016-01-01

    Secondary use of electronic health records (EHRs) promises to advance clinical research and better inform clinical decision making. Challenges in summarizing and representing patient data prevent widespread practice of predictive modeling using EHRs. Here we present a novel unsupervised deep feature learning method to derive a general-purpose patient representation from EHR data that facilitates clinical predictive modeling. In particular, a three-layer stack of denoising autoencoders was used to capture hierarchical regularities and dependencies in the aggregated EHRs of about 700,000 patients from the Mount Sinai data warehouse. The result is a representation we name "deep patient". We evaluated this representation as broadly predictive of health states by assessing the probability of patients to develop various diseases. We performed evaluation using 76,214 test patients comprising 78 diseases from diverse clinical domains and temporal windows. Our results significantly outperformed those achieved using representations based on raw EHR data and alternative feature learning strategies. Prediction performance for severe diabetes, schizophrenia, and various cancers were among the top performing. These findings indicate that deep learning applied to EHRs can derive patient representations that offer improved clinical predictions, and could provide a machine learning framework for augmenting clinical decision systems. PMID:27185194

  12. Cognition and procedure representational requirements for predictive human performance models

    NASA Technical Reports Server (NTRS)

    Corker, K.

    1992-01-01

    Models and modeling environments for human performance are becoming significant contributors to early system design and analysis procedures. Issues of levels of automation, physical environment, informational environment, and manning requirements are being addressed by such man/machine analysis systems. The research reported here investigates the close interaction between models of human cognition and models that described procedural performance. We describe a methodology for the decomposition of aircrew procedures that supports interaction with models of cognition on the basis of procedures observed; that serves to identify cockpit/avionics information sources and crew information requirements; and that provides the structure to support methods for function allocation among crew and aiding systems. Our approach is to develop an object-oriented, modular, executable software representation of the aircrew, the aircraft, and the procedures necessary to satisfy flight-phase goals. We then encode in a time-based language, taxonomies of the conceptual, relational, and procedural constraints among the cockpit avionics and control system and the aircrew. We have designed and implemented a goals/procedures hierarchic representation sufficient to describe procedural flow in the cockpit. We then execute the procedural representation in simulation software and calculate the values of the flight instruments, aircraft state variables and crew resources using the constraints available from the relationship taxonomies. The system provides a flexible, extensible, manipulative and executable representation of aircrew and procedures that is generally applicable to crew/procedure task-analysis. The representation supports developed methods of intent inference, and is extensible to include issues of information requirements and functional allocation. We are attempting to link the procedural representation to models of cognitive functions to establish several intent inference methods

  13. Concrete Representation and Separability Criteria for Symmetric Quantum State

    NASA Astrophysics Data System (ADS)

    Li, Chang'e.; Tao, Yuanhong; Zhang, Jun; Li, Linsong; Nan, Hua

    2014-09-01

    Using the typical generators of the special unitary groups S U(2), the concrete representation of symmetric quantum state is established, then the relations satisfied by those coefficients in the representation are presented. Based on the representation of density matrix, the PPT criterion and CCNR criterion are proved to be equivalent on judging the separability of symmetric quantum states. Moreover, it is showed that the matrix Γ ρ of symmetric quantum state only has five efficient entries, thus the calculation of ∥Γ ρ ∥ is simplified. Finally, the quantitative expressions of real symmetric quantum state under the ∥Γ ρ ∥ separability criterion are obtained.

  14. Interface Representations of Critical Ground States

    NASA Astrophysics Data System (ADS)

    Kondev, Jane

    1995-01-01

    We study the critical properties of the F model, the three-coloring model on the honeycomb lattice, and the four-coloring model on the square lattice, by mapping these models to models of rough interfaces. In particular, we construct operators in a systematic way, which is provided by the interface representation, and we show that their scaling dimensions can be related to the stiffness of the interface. Two types of operators are found, and they correspond to electric and magnetic charges in the Coulomb gas which is related to the interface model by the usual duality transformation. Furthermore, we find that the stiffness of the interface models, and therefore all the critical exponents, can be calculated exactly by considering the contour correlation function which measures the probability that two points on the interface belong to the same contour loop. The exact information about the stiffness also allows us to analyze in detail the conformal field theories (CFT) that represent the scaling limits of the interface models. We find that CFT's associated with the F model, the three -coloring model, and the four-coloring model, have chiral symmetry algebras given by the su(2)_{k=1 }, su(3)_{k=1}, and su(4) _{k=1} Kac-Moody algebras, respectively. The three-coloring and the four coloring-model are ground states of certain antiferromagnetic Potts models, and the behavior of these Potts models at small but finite temperatures is determined by topological defects that can be defined in the associated interface models. In this way we calculate the correlation length and the specific heat of the Potts models, and they are in good agreement with numerical simulations. We also present our Monte-Carlo results for the scaling dimensions of operators in the four-coloring model, and they are in excellent agreement with our analytical results. Finally, we define geometrical exponents for contour loops on self -affine interfaces and calculate their values as a function of the

  15. Semantic representations in the temporal pole predict false memories.

    PubMed

    Chadwick, Martin J; Anjum, Raeesa S; Kumaran, Dharshan; Schacter, Daniel L; Spiers, Hugo J; Hassabis, Demis

    2016-09-01

    Recent advances in neuroscience have given us unprecedented insight into the neural mechanisms of false memory, showing that artificial memories can be inserted into the memory cells of the hippocampus in a way that is indistinguishable from true memories. However, this alone is not enough to explain how false memories can arise naturally in the course of our daily lives. Cognitive psychology has demonstrated that many instances of false memory, both in the laboratory and the real world, can be attributed to semantic interference. Whereas previous studies have found that a diverse set of regions show some involvement in semantic false memory, none have revealed the nature of the semantic representations underpinning the phenomenon. Here we use fMRI with representational similarity analysis to search for a neural code consistent with semantic false memory. We find clear evidence that false memories emerge from a similarity-based neural code in the temporal pole, a region that has been called the "semantic hub" of the brain. We further show that each individual has a partially unique semantic code within the temporal pole, and this unique code can predict idiosyncratic patterns of memory errors. Finally, we show that the same neural code can also predict variation in true-memory performance, consistent with an adaptive perspective on false memory. Taken together, our findings reveal the underlying structure of neural representations of semantic knowledge, and how this semantic structure can both enhance and distort our memories. PMID:27551087

  16. Structural class prediction of protein using novel feature extraction method from chaos game representation of predicted secondary structure.

    PubMed

    Zhang, Lichao; Kong, Liang; Han, Xiaodong; Lv, Jinfeng

    2016-07-01

    Protein structural class prediction plays an important role in protein structure and function analysis, drug design and many other biological applications. Extracting good representation from protein sequence is fundamental for this prediction task. In recent years, although several secondary structure based feature extraction strategies have been specially proposed for low-similarity protein sequences, the prediction accuracy still remains limited. To explore the potential of secondary structure information, this study proposed a novel feature extraction method from the chaos game representation of predicted secondary structure to mainly capture sequence order information and secondary structure segments distribution information in a given protein sequence. Several kinds of prediction accuracies obtained by the jackknife test are reported on three widely used low-similarity benchmark datasets (25PDB, 1189 and 640). Compared with the state-of-the-art prediction methods, the proposed method achieves the highest overall accuracies on all the three datasets. The experimental results confirm that the proposed feature extraction method is effective for accurate prediction of protein structural class. Moreover, it is anticipated that the proposed method could be extended to other graphical representations of protein sequence and be helpful in future research. PMID:27084358

  17. Adaptive modelling of structured molecular representations for toxicity prediction

    NASA Astrophysics Data System (ADS)

    Bertinetto, Carlo; Duce, Celia; Micheli, Alessio; Solaro, Roberto; Tiné, Maria Rosaria

    2012-12-01

    We investigated the possibility of modelling structure-toxicity relationships by direct treatment of the molecular structure (without using descriptors) through an adaptive model able to retain the appropriate structural information. With respect to traditional descriptor-based approaches, this provides a more general and flexible way to tackle prediction problems that is particularly suitable when little or no background knowledge is available. Our method employs a tree-structured molecular representation, which is processed by a recursive neural network (RNN). To explore the realization of RNN modelling in toxicological problems, we employed a data set containing growth impairment concentrations (IGC50) for Tetrahymena pyriformis.

  18. Predicting RNA folding thermodynamics with a reduced chain representation model.

    PubMed

    Cao, Song; Chen, Shi-Jie

    2005-12-01

    Based on the virtual bond representation for the nucleotide backbone, we develop a reduced conformational model for RNA. We use the experimentally measured atomic coordinates to model the helices and use the self-avoiding walks in a diamond lattice to model the loop conformations. The atomic coordinates of the helices and the lattice representation for the loops are matched at the loop-helix junction, where steric viability is accounted for. Unlike the previous simplified lattice-based models, the present virtual bond model can account for the atomic details of realistic three-dimensional RNA structures. Based on the model, we develop a statistical mechanical theory for RNA folding energy landscapes and folding thermodynamics. Tests against experiments show that the theory can give much more improved predictions for the native structures, the thermal denaturation curves, and the equilibrium folding/unfolding pathways than the previous models. The application of the model to the P5abc region of Tetrahymena group I ribozyme reveals the misfolded intermediates as well as the native-like intermediates in the equilibrium folding process. Moreover, based on the free energy landscape analysis for each and every loop mutation, the model predicts five lethal mutations that can completely alter the free energy landscape and the folding stability of the molecule. PMID:16251382

  19. Ground state fidelity from tensor network representations.

    PubMed

    Zhou, Huan-Qiang; Orús, Roman; Vidal, Guifre

    2008-02-29

    For any D-dimensional quantum lattice system, the fidelity between two ground state many-body wave functions is mapped onto the partition function of a D-dimensional classical statistical vertex lattice model with the same lattice geometry. The fidelity per lattice site, analogous to the free energy per site, is well defined in the thermodynamic limit and can be used to characterize the phase diagram of the model. We explain how to compute the fidelity per site in the context of tensor network algorithms, and demonstrate the approach by analyzing the two-dimensional quantum Ising model with transverse and parallel magnetic fields. PMID:18352611

  20. A verification logic representation of indeterministic signal states

    NASA Technical Reports Server (NTRS)

    Gambles, J. W.; Windley, P. J.

    1991-01-01

    The integration of modern CAD tools with formal verification environments require translation from hardware description language to verification logic. A signal representation including both unknown state and a degree of strength indeterminacy is essential for the correct modeling of many VLSI circuit designs. A higher-order logic theory of indeterministic logic signals is presented.

  1. Fast Sequences of Non-spatial State Representations in Humans.

    PubMed

    Kurth-Nelson, Zeb; Economides, Marcos; Dolan, Raymond J; Dayan, Peter

    2016-07-01

    Fast internally generated sequences of neural representations are suggested to support learning and online planning. However, these sequences have only been studied in the context of spatial tasks and never in humans. Here, we recorded magnetoencephalography (MEG) while human subjects performed a novel non-spatial reasoning task. The task required selecting paths through a set of six visual objects. We trained pattern classifiers on the MEG activity elicited by direct presentation of the visual objects alone and tested these classifiers on activity recorded during periods when no object was presented. During these object-free periods, the brain spontaneously visited representations of approximately four objects in fast sequences lasting on the order of 120 ms. These sequences followed backward trajectories along the permissible paths in the task. Thus, spontaneous fast sequential representation of states can be measured non-invasively in humans, and these sequences may be a fundamental feature of neural computation across tasks. PMID:27321922

  2. An exploration of alternative approaches to the representation of uncertainty in model predictions.

    SciTech Connect

    Johnson, Jay Dean; Oberkampf, William Louis; Helton, Jon Craig

    2003-06-01

    Several simple test problems are used to explore the following approaches to the representation of the uncertainty in model predictions that derives from uncertainty in model inputs: probability theory, evidence theory, possibility theory, and interval analysis. Each of the test problems has rather diffuse characterizations of the uncertainty in model inputs obtained from one or more equally credible sources. These given uncertainty characterizations are translated into the mathematical structure associated with each of the indicated approaches to the representation of uncertainty and then propagated through the model with Monte Carlo techniques to obtain the corresponding representation of the uncertainty in one or more model predictions. The different approaches to the representation of uncertainty can lead to very different appearing representations of the uncertainty in model predictions even though the starting information is exactly the same for each approach. To avoid misunderstandings and, potentially, bad decisions, these representations must be interpreted in the context of the theory/procedure from which they derive.

  3. Dynamics of open bosonic quantum systems in coherent state representation

    SciTech Connect

    Dalvit, D. A. R.; Berman, G. P.; Vishik, M.

    2006-01-15

    We consider the problem of decoherence and relaxation of open bosonic quantum systems from a perspective alternative to the standard master equation or quantum trajectories approaches. Our method is based on the dynamics of expectation values of observables evaluated in a coherent state representation. We examine a model of a quantum nonlinear oscillator with a density-density interaction with a collection of environmental oscillators at finite temperature. We derive the exact solution for dynamics of observables and demonstrate a consistent perturbation approach.

  4. Quantifying Representation and Using Representation Weights to Interpolate Flux Tower Measurements across the United States

    NASA Astrophysics Data System (ADS)

    Hargrove, W. W.; Hoffman, F. M.

    2003-12-01

    We are using a new multivariate statistical technique to quantitatively divide the lower 48 United States into a series of flux-relevant ecoregions. On the basis of these flux-relevant ecoregions, we will quantify the representativeness of the existing network of AmeriFlux towers, showing how well each ecoregion is represented by the current stations in the AmeriFlux network. Quantifying AmeriFlux representation will indicate the best locations where additional AmeriFlux towers should be placed. Using a "paint-by-number" approach, we are attempting to use the flux ecoregions as the statistical basis for extrapolating measurements made at the 52 actively-reporting AmeriFlux towers into a continuous 1-km grid across the United States seasonally. We will use the similarity of the suite of flux-relevant ecosystem characteristics to modify existing flux measurements and estimate fluxes within unmeasured flux ecoregions. Weights calculated for each environmental gradient will allow us to mix new "paint-by-number" colors, extending the process beyond the palette of existing flux measurements. The map of 2000 to 5000 flux ecoregions will produce a highly-resolved national map of estimated fluxes, and will be equivalent to creating thousands of new "virtual" flux towers across the nation. Once flux ecoregions and representation weights have been determined, it may be possible to use them to obtain an interpolated grid of the estimated flux at any point in time across the United States.

  5. Predictive coding accounts of shared representations in parieto-insular networks.

    PubMed

    Ishida, Hiroaki; Suzuki, Keisuke; Grandi, Laura Clara

    2015-04-01

    The discovery of mirror neurons in the ventral premotor cortex (area F5) and inferior parietal cortex (area PFG) in the macaque monkey brain has provided the physiological evidence for direct matching of the intrinsic motor representations of the self and the visual image of the actions of others. The existence of mirror neurons implies that the brain has mechanisms reflecting shared self and other action representations. This may further imply that the neural basis self-body representations may also incorporate components that are shared with other-body representations. It is likely that such a mechanism is also involved in predicting other's touch sensations and emotions. However, the neural basis of shared body representations has remained unclear. Here, we propose a neural basis of body representation of the self and of others in both human and non-human primates. We review a series of behavioral and physiological findings which together paint a picture that the systems underlying such shared representations require integration of conscious exteroception and interoception subserved by a cortical sensory-motor network involving parieto-inner perisylvian circuits (the ventral intraparietal area [VIP]/inferior parietal area [PFG]-secondary somatosensory cortex [SII]/posterior insular cortex [pIC]/anterior insular cortex [aIC]). Based on these findings, we propose a computational mechanism of the shared body representation in the predictive coding (PC) framework. Our mechanism proposes that processes emerging from generative models embedded in these specific neuronal circuits play a pivotal role in distinguishing a self-specific body representation from a shared one. The model successfully accounts for normal and abnormal shared body phenomena such as mirror-touch synesthesia and somatoparaphrenia. In addition, it generates a set of testable experimental predictions. PMID:25447372

  6. The generalization of attachment representations to new social situations: predicting behavior during initial interactions with strangers.

    PubMed

    Feeney, Brooke C; Cassidy, Jude; Ramos-Marcuse, Fatima

    2008-12-01

    The idea that attachment representations are generalized to new social situations and guide behavior with unfamiliar others is central to attachment theory. However, research regarding this important theoretical postulate has been lacking in adolescence and adulthood, as most research has focused on establishing the influence of attachment representations on close relationship dynamics. Thus, the goal of this investigation was to examine the extent to which attachment representations are predictive of adolescents' initial behavior when meeting and interacting with new peers. High school adolescents (N=135) participated with unfamiliar peers from another school in 2 social support interactions that were videotaped and coded by independent observers. Results indicated that attachment representations (assessed through interview and self-report measures) were predictive of behaviors exhibited during the discussions. Theoretical implications of the results and contributions to the existing literature are discussed. PMID:19025297

  7. Sparse Representation for Prediction of HIV-1 Protease Drug Resistance.

    PubMed

    Yu, Xiaxia; Weber, Irene T; Harrison, Robert W

    2013-01-01

    HIV rapidly evolves drug resistance in response to antiviral drugs used in AIDS therapy. Estimating the specific resistance of a given strain of HIV to individual drugs from sequence data has important benefits for both the therapy of individual patients and the development of novel drugs. We have developed an accurate classification method based on the sparse representation theory, and demonstrate that this method is highly effective with HIV-1 protease. The protease structure is represented using our newly proposed encoding method based on Delaunay triangulation, and combined with the mutated amino acid sequences of known drug-resistant strains to train a machine-learning algorithm both for classification and regression of drug-resistant mutations. An overall cross-validated classification accuracy of 97% is obtained when trained on a publically available data base of approximately 1.5×10(4) known sequences (Stanford HIV database http://hivdb.stanford.edu/cgi-bin/GenoPhenoDS.cgi). Resistance to four FDA approved drugs is computed and comparisons with other algorithms demonstrate that our method shows significant improvements in classification accuracy. PMID:24910813

  8. Sparse Representation for Prediction of HIV-1 Protease Drug Resistance

    PubMed Central

    Yu, Xiaxia; Weber, Irene T.; Harrison, Robert W.

    2013-01-01

    HIV rapidly evolves drug resistance in response to antiviral drugs used in AIDS therapy. Estimating the specific resistance of a given strain of HIV to individual drugs from sequence data has important benefits for both the therapy of individual patients and the development of novel drugs. We have developed an accurate classification method based on the sparse representation theory, and demonstrate that this method is highly effective with HIV-1 protease. The protease structure is represented using our newly proposed encoding method based on Delaunay triangulation, and combined with the mutated amino acid sequences of known drug-resistant strains to train a machine-learning algorithm both for classification and regression of drug-resistant mutations. An overall cross-validated classification accuracy of 97% is obtained when trained on a publically available data base of approximately 1.5×104 known sequences (Stanford HIV database http://hivdb.stanford.edu/cgi-bin/GenoPhenoDS.cgi). Resistance to four FDA approved drugs is computed and comparisons with other algorithms demonstrate that our method shows significant improvements in classification accuracy. PMID:24910813

  9. Prediction of protein-protein interactions with clustered amino acids and weighted sparse representation.

    PubMed

    Huang, Qiaoying; You, Zhuhong; Zhang, Xiaofeng; Zhou, Yong

    2015-01-01

    With the completion of the Human Genome Project, bioscience has entered into the era of the genome and proteome. Therefore, protein-protein interactions (PPIs) research is becoming more and more important. Life activities and the protein-protein interactions are inseparable, such as DNA synthesis, gene transcription activation, protein translation, etc. Though many methods based on biological experiments and machine learning have been proposed, they all spent a long time to learn and obtained an imprecise accuracy. How to efficiently and accurately predict PPIs is still a big challenge. To take up such a challenge, we developed a new predictor by incorporating the reduced amino acid alphabet (RAAA) information into the general form of pseudo-amino acid composition (PseAAC) and with the weighted sparse representation-based classification (WSRC). The remarkable advantages of introducing the reduced amino acid alphabet is being able to avoid the notorious dimensionality disaster or overfitting problem in statistical prediction. Additionally, experiments have proven that our method achieved good performance in both a low- and high-dimensional feature space. Among all of the experiments performed on the PPIs data of Saccharomyces cerevisiae, the best one achieved 90.91% accuracy, 94.17% sensitivity, 87.22% precision and a 83.43% Matthews correlation coefficient (MCC) value. In order to evaluate the prediction ability of our method, extensive experiments are performed to compare with the state-of-the-art technique, support vector machine (SVM). The achieved results show that the proposed approach is very promising for predicting PPIs, and it can be a helpful supplement for PPIs prediction. PMID:25984606

  10. Prediction of Protein–Protein Interactions with Clustered Amino Acids and Weighted Sparse Representation

    PubMed Central

    Huang, Qiaoying; You, Zhuhong; Zhang, Xiaofeng; Zhou, Yong

    2015-01-01

    With the completion of the Human Genome Project, bioscience has entered into the era of the genome and proteome. Therefore, protein–protein interactions (PPIs) research is becoming more and more important. Life activities and the protein–protein interactions are inseparable, such as DNA synthesis, gene transcription activation, protein translation, etc. Though many methods based on biological experiments and machine learning have been proposed, they all spent a long time to learn and obtained an imprecise accuracy. How to efficiently and accurately predict PPIs is still a big challenge. To take up such a challenge, we developed a new predictor by incorporating the reduced amino acid alphabet (RAAA) information into the general form of pseudo-amino acid composition (PseAAC) and with the weighted sparse representation-based classification (WSRC). The remarkable advantages of introducing the reduced amino acid alphabet is being able to avoid the notorious dimensionality disaster or overfitting problem in statistical prediction. Additionally, experiments have proven that our method achieved good performance in both a low- and high-dimensional feature space. Among all of the experiments performed on the PPIs data of Saccharomyces cerevisiae, the best one achieved 90.91% accuracy, 94.17% sensitivity, 87.22% precision and a 83.43% Matthews correlation coefficient (MCC) value. In order to evaluate the prediction ability of our method, extensive experiments are performed to compare with the state-of-the-art technique, support vector machine (SVM). The achieved results show that the proposed approach is very promising for predicting PPIs, and it can be a helpful supplement for PPIs prediction. PMID:25984606

  11. Parenting and children's representations of family predict disruptive and callous-unemotional behaviors

    PubMed Central

    Wagner, Nicholas J.; Mills-Koonce, W. Roger; Willoughby, Michael T.; Zvara, Bharathi; Cox, Martha J.

    2015-01-01

    Data from a large prospective longitudinal study (n = 1,239) was used to investigate the association between observed sensitive parenting in early childhood and children's representations of family relationships as measured by the Family Drawing Paradigm (FDP) in first grade as well as the extent to which these representations partially mediate the influences of early caregiving experiences on later conduct problems and callous-unemotional behaviors. A structural equation modeling approach revealed that less sensitive parenting at 24, 36, and 58 months predicts higher levels of conduct problems (CP) and callous-unemotional (CU) behaviors in first grade controlling for earlier measures of CP and CU behaviors. Results also indicated that greater dysfunctional family representations, as assessed with the FDP, are significantly associated with higher CU behaviors in the first grade, but not CP. Finally, a test of the indirect pathway suggests that children's dysfunctional family representations may, in part, account for the association between sensitive parenting and CU behaviors. PMID:26010385

  12. Representation of aversive prediction errors in the human periaqueductal gray

    PubMed Central

    Roy, Mathieu; Shohamy, Daphna; Daw, Nathaniel; Jepma, Marieke; Wimmer, Elliott; Wager, Tor D.

    2014-01-01

    Pain is a primary driver of learning and motivated action. It is also a target of learning, as nociceptive brain responses are shaped by learning processes. We combined an instrumental pain avoidance task with an axiomatic approach to assessing fMRI signals related to prediction errors (PEs), which drive reinforcement-based learning. We found that pain PEs were encoded in the periaqueductal gray (PAG), an important structure for pain control and learning in animal models. Axiomatic tests combined with dynamic causal modeling suggested that ventromedial prefrontal cortex, supported by putamen, provides an expected value-related input to the PAG, which then conveys PE signals to prefrontal regions important for behavioral regulation, including orbitofrontal, anterior mid-cingulate, and dorsomedial prefrontal cortices. Thus, pain-related learning involves distinct neural circuitry, with implications for behavior and pain dynamics. PMID:25282614

  13. Representation of aversive prediction errors in the human periaqueductal gray.

    PubMed

    Roy, Mathieu; Shohamy, Daphna; Daw, Nathaniel; Jepma, Marieke; Wimmer, G Elliott; Wager, Tor D

    2014-11-01

    Pain is a primary driver of learning and motivated action. It is also a target of learning, as nociceptive brain responses are shaped by learning processes. We combined an instrumental pain avoidance task with an axiomatic approach to assessing fMRI signals related to prediction errors (PEs), which drive reinforcement-based learning. We found that pain PEs were encoded in the periaqueductal gray (PAG), a structure important for pain control and learning in animal models. Axiomatic tests combined with dynamic causal modeling suggested that ventromedial prefrontal cortex, supported by putamen, provides an expected value-related input to the PAG, which then conveys PE signals to prefrontal regions important for behavioral regulation, including orbitofrontal, anterior mid-cingulate and dorsomedial prefrontal cortices. Thus, pain-related learning involves distinct neural circuitry, with implications for behavior and pain dynamics. PMID:25282614

  14. Neural evidence that three dimensions organize mental state representation: Rationality, social impact, and valence

    PubMed Central

    Tamir, Diana I.; Thornton, Mark A.; Contreras, Juan Manuel; Mitchell, Jason P.

    2016-01-01

    How do people understand the minds of others? Existing psychological theories have suggested a number of dimensions that perceivers could use to make sense of others’ internal mental states. However, it remains unclear which of these dimensions, if any, the brain spontaneously uses when we think about others. The present study used multivoxel pattern analysis (MVPA) of neuroimaging data to identify the primary organizing principles of social cognition. We derived four unique dimensions of mental state representation from existing psychological theories and used functional magnetic resonance imaging to test whether these dimensions organize the neural encoding of others’ mental states. MVPA revealed that three such dimensions could predict neural patterns within the medial prefrontal and parietal cortices, temporoparietal junction, and anterior temporal lobes during social thought: rationality, social impact, and valence. These results suggest that these dimensions serve as organizing principles for our understanding of other people. PMID:26621704

  15. V4 activity predicts the strength of visual short-term memory representations.

    PubMed

    Sligte, Ilja G; Scholte, H Steven; Lamme, Victor A F

    2009-06-10

    Recent studies have shown the existence of a form of visual memory that lies intermediate of iconic memory and visual short-term memory (VSTM), in terms of both capacity (up to 15 items) and the duration of the memory trace (up to 4 s). Because new visual objects readily overwrite this intermediate visual store, we believe that it reflects a weak form of VSTM with high capacity that exists alongside a strong but capacity-limited form of VSTM. In the present study, we isolated brain activity related to weak and strong VSTM representations using functional magnetic resonance imaging. We found that activity in visual cortical area V4 predicted the strength of VSTM representations; activity was low when there was no VSTM, medium when there was a weak VSTM representation regardless of whether this weak representation was available for report or not, and high when there was a strong VSTM representation. Altogether, this study suggests that the high capacity yet weak VSTM store is represented in visual parts of the brain. Allegedly, only some of these VSTM traces are amplified by parietal and frontal regions and as a consequence reside in traditional or strong VSTM. The additional weak VSTM representations remain available for conscious access and report when attention is redirected to them yet are overwritten as soon as new visual stimuli hit the eyes. PMID:19515911

  16. Hierarchical Novelty-Familiarity Representation in the Visual System by Modular Predictive Coding

    PubMed Central

    Vladimirskiy, Boris; Urbanczik, Robert; Senn, Walter

    2015-01-01

    Predictive coding has been previously introduced as a hierarchical coding framework for the visual system. At each level, activity predicted by the higher level is dynamically subtracted from the input, while the difference in activity continuously propagates further. Here we introduce modular predictive coding as a feedforward hierarchy of prediction modules without back-projections from higher to lower levels. Within each level, recurrent dynamics optimally segregates the input into novelty and familiarity components. Although the anatomical feedforward connectivity passes through the novelty-representing neurons, it is nevertheless the familiarity information which is propagated to higher levels. This modularity results in a twofold advantage compared to the original predictive coding scheme: the familiarity-novelty representation forms quickly, and at each level the full representational power is exploited for an optimized readout. As we show, natural images are successfully compressed and can be reconstructed by the familiarity neurons at each level. Missing information on different spatial scales is identified by novelty neurons and complements the familiarity representation. Furthermore, by virtue of the recurrent connectivity within each level, non-classical receptive field properties still emerge. Hence, modular predictive coding is a biologically realistic metaphor for the visual system that dynamically extracts novelty at various scales while propagating the familiarity information. PMID:26670700

  17. Photon-number superselection and the entangled coherent-state representation

    SciTech Connect

    Sanders, Barry C.; Bartlett, Stephen D.; Rudolph, Terry; Knight, Peter L.

    2003-10-01

    We introduce the entangled coherent-state representation, which provides a powerful technique for efficiently and elegantly describing and analyzing quantum optics sources and detectors while respecting the photon-number superselection rule that is satisfied by all known quantum optics experiments. We apply the entangled coherent-state representation to elucidate and resolve the long-standing puzzles of the coherence of a laser output field, interference between two number states, and dichotomous interpretations of quantum teleportation of coherent states.

  18. Emerging Object Representations in the Visual System Predict Reaction Times for Categorization

    PubMed Central

    Ritchie, J. Brendan; Tovar, David A.; Carlson, Thomas A.

    2015-01-01

    Recognizing an object takes just a fraction of a second, less than the blink of an eye. Applying multivariate pattern analysis, or “brain decoding”, methods to magnetoencephalography (MEG) data has allowed researchers to characterize, in high temporal resolution, the emerging representation of object categories that underlie our capacity for rapid recognition. Shortly after stimulus onset, object exemplars cluster by category in a high-dimensional activation space in the brain. In this emerging activation space, the decodability of exemplar category varies over time, reflecting the brain’s transformation of visual inputs into coherent category representations. How do these emerging representations relate to categorization behavior? Recently it has been proposed that the distance of an exemplar representation from a categorical boundary in an activation space is critical for perceptual decision-making, and that reaction times should therefore correlate with distance from the boundary. The predictions of this distance hypothesis have been born out in human inferior temporal cortex (IT), an area of the brain crucial for the representation of object categories. When viewed in the context of a time varying neural signal, the optimal time to “read out” category information is when category representations in the brain are most decodable. Here, we show that the distance from a decision boundary through activation space, as measured using MEG decoding methods, correlates with reaction times for visual categorization during the period of peak decodability. Our results suggest that the brain begins to read out information about exemplar category at the optimal time for use in choice behaviour, and support the hypothesis that the structure of the representation for objects in the visual system is partially constitutive of the decision process in recognition. PMID:26107634

  19. Representation of DNA sequences in genetic codon context with applications in exon and intron prediction.

    PubMed

    Yin, Changchuan

    2015-04-01

    To apply digital signal processing (DSP) methods to analyze DNA sequences, the sequences first must be specially mapped into numerical sequences. Thus, effective numerical mappings of DNA sequences play key roles in the effectiveness of DSP-based methods such as exon prediction. Despite numerous mappings of symbolic DNA sequences to numerical series, the existing mapping methods do not include the genetic coding features of DNA sequences. We present a novel numerical representation of DNA sequences using genetic codon context (GCC) in which the numerical values are optimized by simulation annealing to maximize the 3-periodicity signal to noise ratio (SNR). The optimized GCC representation is then applied in exon and intron prediction by Short-Time Fourier Transform (STFT) approach. The results show the GCC method enhances the SNR values of exon sequences and thus increases the accuracy of predicting protein coding regions in genomes compared with the commonly used 4D binary representation. In addition, this study offers a novel way to reveal specific features of DNA sequences by optimizing numerical mappings of symbolic DNA sequences. PMID:25491390

  20. Intention understanding over T: a neuroimaging study on shared representations and tennis return predictions

    PubMed Central

    Cacioppo, Stephanie; Fontang, Frederic; Patel, Nisa; Decety, Jean; Monteleone, George; Cacioppo, John T.

    2014-01-01

    Studying the way athletes predict actions of their peers during fast-ball sports, such as a tennis, has proved to be a valuable tool for increasing our knowledge of intention understanding. The working model in this area is that the anticipatory representations of others' behaviors require internal predictive models of actions formed from pre-established and shared representations between the observer and the actor. This model also predicts that observers would not be able to read accurately the intentions of a competitor if the competitor were to perform the action without prior knowledge of their intention until moments before the action. To test this hypothesis, we recorded brain activity from 25 male tennis players while they performed a novel behavioral tennis intention inference task, which included two conditions: (i) one condition in which they viewed video clips of a tennis athlete who knew in advance where he was about to act/serve (initially intended serves) and (ii) one condition in which they viewed video clips of that same athlete when he did not know where he was to act/serve until the target was specified after he had tossed the ball into the air to complete his serve (non-initially intended serves). Our results demonstrated that (i) tennis expertise is related to the accuracy in predicting where another server intends to serve when that server knows where he intends to serve before (but not after) he tosses the ball in the air; and (ii) accurate predictions are characterized by the recruitment of both cortical areas within the human mirror neuron system (that is known to be involved in higher-order (top-down) processes of embodied cognition and shared representation) and subcortical areas within brain regions involved in procedural memory (caudate nucleus). Interestingly, inaccurate predictions instead recruit areas known to be involved in low-level (bottom-up) computational processes associated with the sense of agency and self-other distinction

  1. Using abiotic variables to predict importance of sites for species representation.

    PubMed

    Albuquerque, Fabio; Beier, Paul

    2015-10-01

    In systematic conservation planning, species distribution data for all sites in a planning area are used to prioritize each site in terms of the site's importance toward meeting the goal of species representation. But comprehensive species data are not available in most planning areas and would be expensive to acquire. As a shortcut, ecologists use surrogates, such as occurrences of birds or another well-surveyed taxon, or land types defined from remotely sensed data, in the hope that sites that represent the surrogates also represent biodiversity. Unfortunately, surrogates have not performed reliably. We propose a new type of surrogate, predicted importance, that can be developed from species data for a q% subset of sites. With species data from this subset of sites, importance can be modeled as a function of abiotic variables available at no charge for all terrestrial areas on Earth. Predicted importance can then be used as a surrogate to prioritize all sites. We tested this surrogate with 8 sets of species data. For each data set, we used a q% subset of sites to model importance as a function of abiotic variables, used the resulting function to predict importance for all sites, and evaluated the number of species in the sites with highest predicted importance. Sites with the highest predicted importance represented species efficiently for all data sets when q = 25% and for 7 of 8 data sets when q = 20%. Predicted importance requires less survey effort than direct selection for species representation and meets representation goals well compared with other surrogates currently in use. This less expensive surrogate may be useful in those areas of the world that need it most, namely tropical regions with the highest biodiversity, greatest biodiversity loss, most severe lack of inventory data, and poorly developed protected area networks. PMID:25959590

  2. Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection.

    PubMed

    Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie

    2015-01-01

    Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks. PMID:26496370

  3. Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection

    PubMed Central

    Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie

    2015-01-01

    Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks. PMID:26496370

  4. Physical Properties, Exciton Analysis, and Visualization of Core-Excited States: An Intermediate State Representation Approach.

    PubMed

    Wenzel, Jan; Dreuw, Andreas

    2016-03-01

    The theoretical simulation of X-ray absorption spectra is in general a challenging task. However, for small and medium-sized organic molecules, the algebraic diagrammatic construction scheme (ADC) for the polarization operator in combination with the core-valence separation approximation (CVS) has proven to yield core-excitation energies and transition moments with almost quantitative accuracy allowing for reliable construction of X-ray absorption spectra. Still, to understand core-excitation processes in detail, it is not sufficient to only compute energies, but also properties like static dipole moments and state densities are important as they provide deeper insight into the nature of core-excited states. Here, we present for the first time an implementation of the intermediate state representation (ISR) approach in combination with the CVS approximation (CVS-ISR), which gives, in combination with the CVS-ADC method, direct access to core-excited state properties. The performance of the CVS-ADC/CVS-ISR approach is demonstrated by means of small- and medium-sized organic molecules. Besides the calculation of core-excited state dipole moments, advanced analyses of core-excited state densities are performed using descriptors like exciton sizes and distances. Plotting electron and hole densities helps to determine the character of the state, and in particular, the investigation of detachment/attachment densities provides information about orbital relaxation effects that are crucial for understanding core excitations. PMID:26845396

  5. An optimized toolchain for predicting directivity patterns from digital representations of biological shapes

    NASA Astrophysics Data System (ADS)

    Müller, Rolf

    2005-09-01

    Animals have evolved intricate shapes which diffract emitted or received sound and thereby generate a specific directivity pattern. Computer-tomographic methods can generate high-resolution digital representations of these morphological structures in the form of three-dimensional voxel arrays. However, predicting acoustic directivity patterns from these representations with numerical methods can incur high computational cost, e.g., for large structures with fine detail and/or high wave numbers (as in bats and dolphins). Here, the design of a toolchain is described which can handle all steps of deriving a directivity prediction from a voxel representation: generation of a finite-element mesh, assembly of the system matrix, computation of an approximate solution, forward projection into the far field. All individual operations are performed by self-contained tools, which communicate through files. This gives access to intermediate results and limits re-execution upon parameter changes to downstream steps. At each stage, optimizations can be made based on the specifics of the problem such as the regular structure of the voxel array and the distance independence of the directivity. Use of these optimizations has resulted in a highly efficient performance, which is documented by measures for execution speed, memory usage, and accuracy.

  6. newDNA-Prot: Prediction of DNA-binding proteins by employing support vector machine and a comprehensive sequence representation.

    PubMed

    Zhang, Yanping; Xu, Jun; Zheng, Wei; Zhang, Chen; Qiu, Xingye; Chen, Ke; Ruan, Jishou

    2014-10-01

    Identification of DNA-binding proteins is essential in studying cellular activities as the DNA-binding proteins play a pivotal role in gene regulation. In this study, we propose newDNA-Prot, a DNA-binding protein predictor that employs support vector machine classifier and a comprehensive feature representation. The sequence representation are categorized into 6 groups: primary sequence based, evolutionary profile based, predicted secondary structure based, predicted relative solvent accessibility based, physicochemical property based and biological function based features. The mRMR, wrapper and two-stage feature selection methods are employed for removing irrelevant features and reducing redundant features. Experiments demonstrate that the two-stage method performs better than the mRMR and wrapper methods. We also perform a statistical analysis on the selected features and results show that more than 95% of the selected features are statistically significant and they cover all 6 feature groups. The newDNA-Prot method is compared with several state of the art algorithms, including iDNA-Prot, DNAbinder and DNA-Prot. The results demonstrate that newDNA-Prot method outperforms the iDNA-Prot, DNAbinder and DNA-Prot methods. More specific, newDNA-Prot improves the runner-up method, DNA-Prot for around 10% on several evaluation measures. The proposed newDNA-Prot method is available at http://sourceforge.net/projects/newdnaprot/ PMID:25240115

  7. Ontology and modeling patterns for state-based behavior representation

    NASA Technical Reports Server (NTRS)

    Castet, Jean-Francois; Rozek, Matthew L.; Ingham, Michel D.; Rouquette, Nicolas F.; Chung, Seung H.; Kerzhner, Aleksandr A.; Donahue, Kenneth M.; Jenkins, J. Steven; Wagner, David A.; Dvorak, Daniel L.; Karban, Robert

    2015-01-01

    This paper provides an approach to capture state-based behavior of elements, that is, the specification of their state evolution in time, and the interactions amongst them. Elements can be components (e.g., sensors, actuators) or environments, and are characterized by state variables that vary with time. The behaviors of these elements, as well as interactions among them are represented through constraints on state variables. This paper discusses the concepts and relationships introduced in this behavior ontology, and the modeling patterns associated with it. Two example cases are provided to illustrate their usage, as well as to demonstrate the flexibility and scalability of the behavior ontology: a simple flashlight electrical model and a more complex spacecraft model involving instruments, power and data behaviors. Finally, an implementation in a SysML profile is provided.

  8. Predictive decision making driven by multiple time-linked reward representations in the anterior cingulate cortex

    PubMed Central

    Wittmann, Marco K.; Kolling, Nils; Akaishi, Rei; Chau, Bolton K. H.; Brown, Joshua W.; Nelissen, Natalie; Rushworth, Matthew F. S.

    2016-01-01

    In many natural environments the value of a choice gradually gets better or worse as circumstances change. Discerning such trends makes predicting future choice values possible. We show that humans track such trends by comparing estimates of recent and past reward rates, which they are able to hold simultaneously in the dorsal anterior cingulate cortex (dACC). Comparison of recent and past reward rates with positive and negative decision weights is reflected by opposing dACC signals indexing these quantities. The relative strengths of time-linked reward representations in dACC predict whether subjects persist in their current behaviour or switch to an alternative. Computationally, trend-guided choice can be modelled by using a reinforcement-learning mechanism that computes a longer-term estimate (or expectation) of prediction errors. Using such a model, we find a relative predominance of expected prediction errors in dACC, instantaneous prediction errors in the ventral striatum and choice signals in the ventromedial prefrontal cortex. PMID:27477632

  9. Predictive decision making driven by multiple time-linked reward representations in the anterior cingulate cortex.

    PubMed

    Wittmann, Marco K; Kolling, Nils; Akaishi, Rei; Chau, Bolton K H; Brown, Joshua W; Nelissen, Natalie; Rushworth, Matthew F S

    2016-01-01

    In many natural environments the value of a choice gradually gets better or worse as circumstances change. Discerning such trends makes predicting future choice values possible. We show that humans track such trends by comparing estimates of recent and past reward rates, which they are able to hold simultaneously in the dorsal anterior cingulate cortex (dACC). Comparison of recent and past reward rates with positive and negative decision weights is reflected by opposing dACC signals indexing these quantities. The relative strengths of time-linked reward representations in dACC predict whether subjects persist in their current behaviour or switch to an alternative. Computationally, trend-guided choice can be modelled by using a reinforcement-learning mechanism that computes a longer-term estimate (or expectation) of prediction errors. Using such a model, we find a relative predominance of expected prediction errors in dACC, instantaneous prediction errors in the ventral striatum and choice signals in the ventromedial prefrontal cortex. PMID:27477632

  10. Bound states in gauge theories as the Poincare group representations

    SciTech Connect

    Cherny, A. Yu.; Dorokhov, A. E.; Han, Nguyen Suan; Pervushin, V. N. Shilin, V. I.

    2013-03-15

    The bound-state generating functional is constructed in gauge theories. This construction is based on the Dirac Hamiltonian approach to gauge theories, the Poincare group classification of fields and their nonlocal bound states, and the Markov-Yukawa constraint of irreducibility. The generating functional contains additional anomalous creations of pseudoscalar bound states: para-positronium in QED and mesons inQCDin the two-gamma processes of the type of {gamma} + {gamma} {yields} {pi}{sub 0} +para-positronium. The functional allows us to establish physically clear and transparent relations between the perturbativeQCD to its nonperturbative low-energy model by means of normal ordering and the quark and gluon condensates. In the limit of small current quark masses, the Gell-Mann-Oakes-Renner relation is derived from the Schwinger-Dyson and Bethe-Salpeter equations. The constituent quark masses can be calculated from a self-consistent nonlinear equation.

  11. Spatially-explicit representation of state-and-transition models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The broad-scale assessment of natural resource conditions (e.g., rangeland health, restoration needs) requires knowledge of their spatial distribution. We argue that creating a database that links state-and-transition models (STMs) to spatial units is a valuable management tool for structuring groun...

  12. The semiclassical coherent state propagator in the Weyl representation

    SciTech Connect

    Braun, Carol; Li, Feifei; Garg, Anupam; Stone, Michael

    2015-12-15

    It is shown that the semiclassical coherent state propagator takes its simplest form when the quantum mechanical Hamiltonian is replaced by its Weyl symbol in defining the classical action, in that there is then no need for a Solari-Kochetov correction. It is also shown that such a correction exists if a symbol other than the Weyl symbol is chosen and that its form is different depending on the symbol chosen. The various forms of the propagator based on different symbols are shown to be equivalent provided the correspondingly correct Solari-Kochetov correction is included. All these results are shown for both particle and spin coherent state propagators. The global anomaly in the fluctuation determinant is further elucidated by a study of the connection between the discrete fluctuation determinant and the discrete Jacobi equation.

  13. On coherent-state representations of quantum mechanics: Wave mechanics in phase space

    NASA Astrophysics Data System (ADS)

    Møller, Klaus B.; Jørgensen, Thomas G.; Torres-Vega, Gabino

    1997-05-01

    In this article we argue that the state-vector phase-space representation recently proposed by Torres-Vega and co-workers [introduced in J. Chem. Phys. 98, 3103 (1993)] coincides with the totality of coherent-state representations for the Heisenberg-Weyl group. This fact leads to ambiguities when one wants to solve the stationary Schrödinger equation in phase space and we devise two schemes for the removal of these ambiguities. The physical interpretation of the phase-space wave functions is discussed and a procedure for computing expectation values as integrals over phase space is presented. Our formal points are illustrated by two examples.

  14. Obtaining Multimode Entangled State Representation by Generalized Radon Transformation of the Wigner Operator

    NASA Astrophysics Data System (ADS)

    Xu, Xue-Fen

    2010-07-01

    In a preceding paper (Fan and Lv in J. Math. Phys. 50:102108, 2009), the phase-space integration corresponding to the straight line characteristic of two different real parameters λ, τ over the Wigner operator (i.e. the Radon transformation) leads to pure-state density operator | u> λ, τ λ, τ < u|, where | u> λ, τ is just the coordinate-momentum intermediate representation. In this work we show that generalized Radon transformation of the Wigner operator yields multimode density operator of continuum variables. This provides us with a new approach for obtaining multimode entangled state representation. The Weyl ordering of the Wigner operator is used in our discussions.

  15. Significant contribution of realistic vegetation representation to improved simulation and prediction of climate anomalies over land

    NASA Astrophysics Data System (ADS)

    Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Doblas-Reyes, Francisco; van den Hurk, Bart; Miller, Paul

    2015-04-01

    The EC-Earth earth system model has been recently developed to include the dynamics of vegetation through the coupling with the LPJ-Guess model. In its original formulation, the coupling between atmosphere and vegetation variability is simply operated by the vegetation Leaf Area Index (LAI), which affects climate by only changing the vegetation physiological resistance to evapotranspiration. This coupling with no implied change of the vegetation fractional coverage has been reported to have a weak effect on the surface climate modeled by EC-Earth (e.g.: also Weiss et al. 2012). The effective sub-grid vegetation fractional coverage can vary seasonally and at interannual time-scales as a function of leaf-canopy growth, phenology and senescence, and therefore affect biophysical parameters such as the surface roughness, albedo and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation densitiy to the LAI, based on a Lambert-Beer formulation. By comparing historical 20th century simulations and retrospective forecasts performed applying the new effective fractional-coverage parameterization with the respective reference simulations using the original constant vegetation-fraction, we showed an increased effect of vegetation on the EC-Earth surface climate. The analysis shows considerable sensitivity of EC-Earth surface climate at seasonal to interannual time-scales due to the variability of vegetation effective fractional coverage. Particularly large effects are shown over boreal winter middle-to-high latitudes, where the cooling effect of the new parameterization corrects the warm biases of the control simulations over land. For boreal winter, the realistic representation of vegetation variability leads to a significant improvement of the skill in predicting surface climate over land at seasonal time-scales. A potential predictability experiment extended to longer time-scales also indicates the

  16. Complete separability and Fourier representations of n-qubit states

    NASA Astrophysics Data System (ADS)

    Pittenger, Arthur O.; Rubin, Morton H.

    2000-10-01

    Necessary conditions for separability are most easily expressed in the computational basis, while sufficient conditions are most conveniently expressed in the spin basis. We use the Hadamard matrix to define the relationship between these two bases and to emphasize its interpretation as a Fourier transform. We then prove a general sufficient condition for complete separability in terms of the spin coefficients and give necessary and sufficient conditions for the complete separability of a class of generalized Werner densities. As a further application of the theory, we give necessary and sufficient conditions for full separability for a particular set of n-qubit states whose densities all satisfy the Peres condition.

  17. The New Operational Hydro-meteorological Ensemble Prediction System at Meteo-France and its representation interface for the French Service for Flood Prediction (SCHAPI)

    NASA Astrophysics Data System (ADS)

    Rousset-Regimbeau, Fabienne; Coustau, Mathieu; Martin, Eric; Thirel, Guillaume; Habets, Florence; De Saint Aubin, Céline; Ardilouze, Constantin

    2013-04-01

    The coupled physically-based hydro-meteorological model SAFRAN-ISBA-MODCOU (SIM) is developed at Meteo-France for many years. This fully distributed catchment model is used in an operationnal real-time mode since 2005 for producing mid-range ensemble streamflow forecasts based on the 51-member 10-day ECMWF EPS. New improvements have been recently implemented in this forecasting chain. First, the new version of the forecasting chain includes new atmopheric products from the ECWMF (EPS at the resolution of 0,25° over France). Then an improvement of the physics of the ISBA model (a new physical representation of the soil hydraulic conductivity) is now used. And finally, a past discharges assimilation system has been implemented in order to improve the initial states of the ensemble streamflow forecasts. These developpement were first tested in the framework of a Phd thesis, and are now evaluated in real-time conditions. This study aims to assess the improvements obtained by the new version of the forecasting chain. Several experiments were performed ton assess the effects of i) the high resolution atmospheric forcing ii) the new representation of the hydraulic conductivity iii) the data assimilation method and iv) the real-time framework. Tested on a 18-month period of reforecasts, the new chain presents significantly improved ensemble streamflow forecasts compared to the previous version. Finally, this system provides ensemble 10-day streamflow prediction to the French National Service for Flood Prediction (SCHAPI). A collaboration between Meteo-France and SCHAPI led to the development of a new website. This website shows the streamflow predictions for about 200 selected river stations over France (selected regarding their interest for flood warning) , as well as alerts for high flows (two levels of high flows corresponding to the levels of risk of the French flood warning system). It aims at providing to the French hydrological forecaters a real-time tool for mid

  18. A sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory.

    SciTech Connect

    Johnson, J. D.; Oberkampf, William Louis; Helton, Jon Craig (Arizona State University, Tempe, AZ); Storlie, Curtis B. (North Carolina State University, Raleigh, NC)

    2006-10-01

    Evidence theory provides an alternative to probability theory for the representation of epistemic uncertainty in model predictions that derives from epistemic uncertainty in model inputs, where the descriptor epistemic is used to indicate uncertainty that derives from a lack of knowledge with respect to the appropriate values to use for various inputs to the model. The potential benefit, and hence appeal, of evidence theory is that it allows a less restrictive specification of uncertainty than is possible within the axiomatic structure on which probability theory is based. Unfortunately, the propagation of an evidence theory representation for uncertainty through a model is more computationally demanding than the propagation of a probabilistic representation for uncertainty, with this difficulty constituting a serious obstacle to the use of evidence theory in the representation of uncertainty in predictions obtained from computationally intensive models. This presentation describes and illustrates a sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory. Preliminary trials indicate that the presented strategy can be used to propagate uncertainty representations based on evidence theory in analysis situations where naive sampling-based (i.e., unsophisticated Monte Carlo) procedures are impracticable due to computational cost.

  19. Quantum thermalization of two coupled two-level systems in eigenstate and bare-state representations

    SciTech Connect

    Liao Jieqiao; Huang Jinfeng; Kuang Leman

    2011-05-15

    We study analytically the quantum thermalization of two coupled two-level systems (TLSs), which are connected with either two independent heat baths (IHBs) or a common heat bath (CHB). We understand the quantum thermalization in eigenstate and bare-state representations when the coupling between the two TLSs is stronger and weaker than the TLS-bath couplings, respectively. In the IHB case, we find that, when the two IHBs have the same temperatures, the two coupled TLSs in eigenstate representation can be thermalized with the same temperature as those of the IHBs. However, in the case of two IHBs at different temperatures, just when the energy detuning between the two TLSs satisfies a special condition, the two coupled TLSs in eigenstate representation can be thermalized with an immediate temperature between those of the two IHBs. In bare-state representation, we find a counterintuitive phenomenon that, under some conditions, the temperature of the TLS connected with the high-temperature bath is lower than that of the other TLS, which is connected with the low-temperature bath. In the CHB case, the coupled TLSs in eigenstate representation can be thermalized with the same temperature as that of the CHB in nonresonant cases. In bare-state representation, the TLS with a larger energy separation can be thermalized to a thermal equilibrium with a lower temperature. In the resonant case, we find a phenomenon of antithermalization. We also study the steady-state entanglement between the two TLSs in both the IHB and CHB cases.

  20. Individual differences and the neural representations of reward expectation and reward prediction error

    PubMed Central

    2007-01-01

    Reward expectation and reward prediction errors are thought to be critical for dynamic adjustments in decision-making and reward-seeking behavior, but little is known about their representation in the brain during uncertainty and risk-taking. Furthermore, little is known about what role individual differences might play in such reinforcement processes. In this study, it is shown behavioral and neural responses during a decision-making task can be characterized by a computational reinforcement learning model and that individual differences in learning parameters in the model are critical for elucidating these processes. In the fMRI experiment, subjects chose between high- and low-risk rewards. A computational reinforcement learning model computed expected values and prediction errors that each subject might experience on each trial. These outputs predicted subjects’ trial-to-trial choice strategies and neural activity in several limbic and prefrontal regions during the task. Individual differences in estimated reinforcement learning parameters proved critical for characterizing these processes, because models that incorporated individual learning parameters explained significantly more variance in the fMRI data than did a model using fixed learning parameters. These findings suggest that the brain engages a reinforcement learning process during risk-taking and that individual differences play a crucial role in modeling this process. PMID:17710118

  1. Representability of Bloch states on Projector-augmented-wave (PAW) basis sets

    NASA Astrophysics Data System (ADS)

    Agapito, Luis; Ferretti, Andrea; Curtarolo, Stefano; Buongiorno Nardelli, Marco

    2015-03-01

    Design of small, yet `complete', localized basis sets is necessary for an efficient dual representation of Bloch states on both plane-wave and localized basis. Such simultaneous dual representation permits the development of faster more accurate (beyond DFT) electronic-structure methods for atomistic materials (e.g. the ACBN0 method.) by benefiting from algorithms (real and reciprocal space) and hardware acceleration (e.g. GPUs) used in the quantum-chemistry and solid-state communities. Finding a `complete' atomic-orbital basis (partial waves) is also a requirement in the generation of robust and transferable PAW pseudopotentials. We have employed the atomic-orbital basis from available PAW data sets, which extends through most of the periodic table, and tested the representability of Bloch states on such basis. Our results show that PAW data sets allow systematic and accurate representability of the PAW Bloch states, better than with traditional quantum-chemistry double-zeta- and double-zeta-polarized-quality basis sets.

  2. Relativistic dynamics of quasistable states. II. Differentiable representations of the causal Poincare semigroup

    SciTech Connect

    Wickramasekara, S.

    2009-07-15

    We construct two rigged Hilbert spaces that furnish differentiable representations of the causal Poincare semigroup. These rigged Hilbert spaces provide the mathematical foundation for a theory of relativistic quasistable states that synthesizes the S-matrix description of resonance scattering with the Bakamjian-Thomas construction for interacting relativistic quantum systems.

  3. General formula for finding mother wavelets by virtue of Dirac's representation theory and the coherent state.

    PubMed

    Fan, Hong-Yi; Lu, Hai-Liang

    2006-02-01

    The admissibility condition of a mother wavelet is explored in the context of quantum optics theory. By virtue of Dirac's representation theory and the coherent state property we derive a general formula for finding qualified mother wavelets. A comparison between a wavelet transform computed with the newly found mother wavelet and one computed with a Mexican hat wavelet is presented. PMID:16480224

  4. Mother wavelets for complex wavelet transform derived by Einstein-Podolsky-Rosen entangled state representation.

    PubMed

    Fan, Hong-Yi; Lu, Hai-Liang

    2007-03-01

    The Einstein-Podolsky-Rosen entangled state representation is applied to studying the admissibility condition of mother wavelets for complex wavelet transforms, which leads to a family of new mother wavelets. Mother wavelets thus are classified as the Hermite-Gaussian type for real wavelet transforms and the Laguerre-Gaussian type for the complex case. PMID:17392919

  5. Secure base representations for both fathers and mothers predict children's secure base behavior in a sample of Portuguese families.

    PubMed

    Monteiro, Ligia; Verissimo, Manuela; Vaughn, Brian E; Santos, Antonio J; Bost, Kelly K

    2008-06-01

    Relations between fathers' and mothers' representations of attachment (independently assessed using an attachment script representation task) and children's secure base behavior (assessed using the Attachment Q-sort; AQS) were studied in 56 Portuguese families (mean age of child = 31.9 months). Each parent's secure base script representation score predicted AQS security scores for the child with that parent at approximately equivalent degrees of association. However, both parental secure base script scores and AQS security scores were positively correlated across parents. A hierarchical regression predicting AQS security with father from both parent's scriptedness scores and from the AQS score with mother showed a unique, significant influence of father's scriptedness score and the AQS score with mother, but mother's scriptedness score did not uniquely add to the prediction. Difficult temperament was ruled out as a mediator of the cross-parent association for AQS security scores. PMID:18773318

  6. 5 CFR 2641.202 - Two-year restriction on any former employee's representations to United States concerning...

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... disqualified from participating in a matter in accordance with subparts D, E, or F of 5 CFR part 2635 or part... employee's representations to United States concerning particular matter for which the employee had... restriction on any former employee's representations to United States concerning particular matter for...

  7. 5 CFR 2641.202 - Two-year restriction on any former employee's representations to United States concerning...

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... disqualified from participating in a matter in accordance with subparts D, E, or F of 5 CFR part 2635 or part... employee's representations to United States concerning particular matter for which the employee had... restriction on any former employee's representations to United States concerning particular matter for...

  8. Counting SO(9) x SU(2) representations in coordinate independent state space of SU(2) matrix theory

    SciTech Connect

    Michishita, Yoji

    2010-12-15

    We consider decomposition of coordinate independent states into SO(9) x SU(2) representations in SU(2) matrix theory. To see what and how many representations appear in the decomposition, we compute the character, which is given by a trace over the coordinate independent states, and decompose it into the sum of products of SO(9) and SU(2) characters.

  9. Year of the Woman, Decade of the Man: trajectories of growth in women's state legislative representation.

    PubMed

    Paxton, Pamela; Painter, Matthew A; Hughes, Melanie M

    2009-03-01

    The expansion of women's political representation ranks among the most significant trends in American politics of the last 100 years. In this paper, we develop two longitudinal theories to explain patterns of growth and change in women's state legislative representation over time. Gender salience suggests that years in which women's absence from politics is problematized (e.g., 1992-the Year of the Woman) will demonstrate higher levels of growth. Political climate suggests that periods in which domestic issues are stressed (e.g., the 1990s) will produce higher levels of growth than periods in which international issues are stressed (e.g., post 9/11). Combinations of these two theories create four possible trajectories of growth in women's representation that may be observed over time. We use latent growth curve models to assess the four theoretical trajectories, using data on women's state legislative representation from 1982 to 2006. We find that while women achieved fleeting success in the Year of the Woman, further gains were limited in the remainder of the 1990s and average growth stalled completely after 2001. Our results show futher that gender salience and, to a lesser extent political, climate matter to growth and change in women's political power over time. PMID:19569294

  10. Human creativity, evolutionary algorithms, and predictive representations: The mechanics of thought trials.

    PubMed

    Dietrich, Arne; Haider, Hilde

    2015-08-01

    Creative thinking is arguably the pinnacle of cerebral functionality. Like no other mental faculty, it has been omnipotent in transforming human civilizations. Probing the neural basis of this most extraordinary capacity, however, has been doggedly frustrated. Despite a flurry of activity in cognitive neuroscience, recent reviews have shown that there is no coherent picture emerging from the neuroimaging work. Based on this, we take a different route and apply two well established paradigms to the problem. First is the evolutionary framework that, despite being part and parcel of creativity research, has no informed experimental work in cognitive neuroscience. Second is the emerging prediction framework that recognizes predictive representations as an integrating principle of all cognition. We show here how the prediction imperative revealingly synthesizes a host of new insights into the way brains process variation-selection thought trials and present a new neural mechanism for the partial sightedness in human creativity. Our ability to run offline simulations of expected future environments and action outcomes can account for some of the characteristic properties of cultural evolutionary algorithms running in brains, such as degrees of sightedness, the formation of scaffolds to jump over unviable intermediate forms, or how fitness criteria are set for a selection process that is necessarily hypothetical. Prospective processing in the brain also sheds light on how human creating and designing - as opposed to biological creativity - can be accompanied by intentions and foresight. This paper raises questions about the nature of creative thought that, as far as we know, have never been asked before. PMID:25304474

  11. Frontal–Medial Temporal Interactions Mediate Transitions among Representational States in Short-Term Memory

    PubMed Central

    Jonides, John

    2014-01-01

    Short-term memory (STM), the brief maintenance of information in the absence of external stimulation, is central to higher-level cognition. Behavioral and neural data indicate that information maintained in STM can be represented in qualitatively distinct states. These states include a single chunk held in the focus of attention available for immediate processing (the “focus”), a capacity-limited set of additional actively maintained items that the focus can access (the “active state”), and passively maintained items (the “passive state”). Little is known about how information is shifted among these states. Here, we used fMRI in humans to examine the neural correlates of shifting information among representational states of STM. We used a paradigm that has demonstrated dissociable performance costs associated with shifting the focus among active items and switching sets of items between active and passive states. Behavioral results confirmed distinct behavioral costs associated with different representational states. Neural results indicated that the caudal superior frontal sulcus (cSFS), in the vicinity of the frontal eye fields, was associated with shifting the focus, consistent with the role of this region in internal and external attention. By contrast, the ventral premotor cortex (PMv) was associated with shifting between active and passive states. Increased cSFS-medial temporal lobe (MTL) connectivity was associated with shifting the focus, while cSFS-MTL connectivity was disrupted when the active state was changed. By contrast, PMv–MTL connectivity increased when the active state was switched. These data indicate that dissociable frontal–MTL interactions mediate shifts of information among different representational states in STM. PMID:24899718

  12. Constraints of artificial neural networks for rainfall-runoff modelling: trade-offs in hydrological state representation and model evaluation

    NASA Astrophysics Data System (ADS)

    de Vos, N. J.; Rientjes, T. H. M.

    2005-07-01

    The application of Artificial Neural Networks (ANNs) in rainfall-runoff modelling needs to be researched more extensively in order to appreciate and fulfil the potential of this modelling approach. This paper reports on the application of multi-layer feedforward ANNs for rainfall-runoff modelling of the Geer catchment (Belgium) using both daily and hourly data. The daily forecast results indicate that ANNs can be considered good alternatives for traditional rainfall-runoff modelling approaches, but the simulations based on hourly data reveal timing errors as a result of a dominating autoregressive component. This component is introduced in model simulations by using previously observed runoff values as ANN model input, which is a popular method for indirectly representing the hydrological state of a catchment. Two possible solutions to this problem of lagged predictions are presented. Firstly, several alternatives for representation of the hydrological state are tested as ANN inputs: moving averages over time of observed discharges and rainfall, and the output of the simple GR4J model component for soil moisture. A combination of these hydrological state representers produces good results in terms of timing, but the overall goodness of fit is not as good as the simulations with previous runoff data. Secondly, the possibility of using multiple measures of model performance during ANN training is mentioned.

  13. An efficient computational method for predicting rotational diffusion tensors of globular proteins using an ellipsoid representation.

    PubMed

    Ryabov, Yaroslav E; Geraghty, Charles; Varshney, Amitabh; Fushman, David

    2006-12-01

    We propose a new computational method for predicting rotational diffusion properties of proteins in solution. The method is based on the idea of representing protein surface as an ellipsoid shell. In contrast to other existing approaches this method uses principal component analysis of protein surface coordinates, which results in a substantial increase in the computational efficiency of the method. Direct comparison with the experimental data as well as with the recent computational approach (Garcia de la Torre; et al. J. Magn. Reson. 2000, B147, 138-146), based on representation of protein surface as a set of small spherical friction elements, shows that the method proposed here reproduces experimental data with at least the same level of accuracy and precision as the other approach, while being approximately 500 times faster. Using the new method we investigated the effect of hydration layer and protein surface topography on the rotational diffusion properties of a protein. We found that a hydration layer constructed of approximately one monolayer of water molecules smoothens the protein surface and effectively doubles the overall tumbling time. We also calculated the rotational diffusion tensors for a set of 841 protein structures representing the known protein folds. Our analysis suggests that an anisotropic rotational diffusion model is generally required for NMR relaxation data analysis in single-domain proteins, and that the axially symmetric model could be sufficient for these purposes in approximately half of the proteins. PMID:17132010

  14. Inversion formula and Parseval theorem for complex continuous wavelet transforms studied by entangled state representation

    NASA Astrophysics Data System (ADS)

    Hu, Li-Yun; Fan, Hong-Yi

    2010-07-01

    In a preceding letter (2007 Opt. Lett. 32 554) we propose complex continuous wavelet transforms and found Laguerre-Gaussian mother wavelets family. In this work we present the inversion formula and Parseval theorem for complex continuous wavelet transform by virtue of the entangled state representation, which makes the complex continuous wavelet transform theory complete. A new orthogonal property of mother wavelet in parameter space is revealed.

  15. Parenting and Children's Representations of Family Predict Disruptive and Callous-Unemotional Behaviors

    ERIC Educational Resources Information Center

    Wagner, Nicholas J.; Mills-Koonce, W. Roger; Willoughby, Michael T.; Zvara, Bharathi; Cox, Martha J.

    2015-01-01

    Data from a large prospective longitudinal study (n = 1,239) was used to investigate the association between observed sensitive parenting in early childhood and children's representations of family relationships as measured by the Family Drawing Paradigm (FDP) in first grade as well as the extent to which these representations partially mediate…

  16. Generalized and specific attachment representations: unique and interactive roles in predicting conflict behaviors in close relationships.

    PubMed

    Creasey, Gary; Ladd, Aimee

    2005-08-01

    The authors expected that associations between the representations individuals possess regarding romantic partners and their conflict behavior would be moderated by generalized attachment representations (GAR). To test this premise, college students (N =130) were administered two attachment measures and were observed during conflict negotiation with their partners. The Relationship Styles Questionnaire assessed specific representations regarding partners and GAR were measured by the Adult Attachment Interview. The relationship between romantic partner representations and conflict tactics were dependent on GAR. Individuals who possessed secure GAR generally displayed good conflict management skills, regardless of their attachment representations regarding their romantic partners. Individuals who held more anxious or avoidant perceptions of romantic partners displayed more problematic conflict tactics if they possessed insecure GAR; however, these associations were dependent on the type of conflict behavior and the type of insecure GAR. Implications for future research are discussed. PMID:16000265

  17. Information content of contact-pattern representations and predictability of epidemic outbreaks

    NASA Astrophysics Data System (ADS)

    Holme, Petter

    2015-09-01

    To understand the contact patterns of a population—who is in contact with whom, and when the contacts happen—is crucial for modeling outbreaks of infectious disease. Traditional theoretical epidemiology assumes that any individual can meet any with equal probability. A more modern approach, network epidemiology, assumes people are connected into a static network over which the disease spreads. Newer yet, temporal network epidemiology, includes the time in the contact representations. In this paper, we investigate the effect of these successive inclusions of more information. Using empirical proximity data, we study both outbreak sizes from unknown sources, and from known states of ongoing outbreaks. In the first case, there are large differences going from a fully mixed simulation to a network, and from a network to a temporal network. In the second case, differences are smaller. We interpret these observations in terms of the temporal network structure of the data sets. For example, a fast overturn of nodes and links seem to make the temporal information more important.

  18. Information content of contact-pattern representations and predictability of epidemic outbreaks

    PubMed Central

    Holme, Petter

    2015-01-01

    To understand the contact patterns of a population—who is in contact with whom, and when the contacts happen—is crucial for modeling outbreaks of infectious disease. Traditional theoretical epidemiology assumes that any individual can meet any with equal probability. A more modern approach, network epidemiology, assumes people are connected into a static network over which the disease spreads. Newer yet, temporal network epidemiology, includes the time in the contact representations. In this paper, we investigate the effect of these successive inclusions of more information. Using empirical proximity data, we study both outbreak sizes from unknown sources, and from known states of ongoing outbreaks. In the first case, there are large differences going from a fully mixed simulation to a network, and from a network to a temporal network. In the second case, differences are smaller. We interpret these observations in terms of the temporal network structure of the data sets. For example, a fast overturn of nodes and links seem to make the temporal information more important. PMID:26403504

  19. Acoustic Prediction State of the Art Assessment

    NASA Technical Reports Server (NTRS)

    Dahl, Milo D.

    2007-01-01

    The acoustic assessment task for both the Subsonic Fixed Wing and the Supersonic projects under NASA s Fundamental Aeronautics Program was designed to assess the current state-of-the-art in noise prediction capability and to establish baselines for gauging future progress. The documentation of our current capabilities included quantifying the differences between predictions of noise from computer codes and measurements of noise from experimental tests. Quantifying the accuracy of both the computed and experimental results further enhanced the credibility of the assessment. This presentation gives sample results from codes representative of NASA s capabilities in aircraft noise prediction both for systems and components. These include semi-empirical, statistical, analytical, and numerical codes. System level results are shown for both aircraft and engines. Component level results are shown for a landing gear prototype, for fan broadband noise, for jet noise from a subsonic round nozzle, and for propulsion airframe aeroacoustic interactions. Additional results are shown for modeling of the acoustic behavior of duct acoustic lining and the attenuation of sound in lined ducts with flow.

  20. Numerical Modeling of the Central Spin Problem Using the Spin-Coherent-State P Representation

    SciTech Connect

    Al Hassanieh, Khaled A; Dobrovitski, V. V.; Dagotto, Elbio R; Harmon, B. N.

    2006-01-01

    In this work, we consider decoherence of a central spin by a spin bath. In order to study the nonperturbative decoherence regimes, we develop an efficient mean-field-based method for modeling the spin-bath decoherence, based on the P representation of the central spin density matrix. The method can be applied to longitudinal and transverse relaxation at different external fields. In particular, by modeling large-size quantum systems (up to 16 000 bath spins), we make controlled predictions for the slow long-time decoherence of the central spin.

  1. Nonclassicality and Entanglement of Photon-Subtracted Two-Mode Squeezed Coherent States Studied via Entangled-States Representation

    NASA Astrophysics Data System (ADS)

    Wang, Zhen; Li, Heng-Mei; Yuan, Hong-Chun

    2016-06-01

    We theoretically introduce a kind of non-Gaussian entangled states, i.e., photon-subtracted two-mode squeezed coherent states (PSTMSCS), by successively subtracting photons from each mode of the two-mode squeezed coherent states. The normalization factor which is related to bivariate Hermite polynomials is obtained by virtue of the two-mode squeezing operator in entangled-states representation. The sub-Poissonian photon statistics, antibunching effects, and partial negative Wigner function, respectively, are observed numerically, which fully reflect the nonclassicality of the resultant states. Finally, employing the SV criteria and the EPR correlation, respectively, the entangled property of PSTMSCS is analyzed. It is shown that the photon subtraction operation can effectively enhance the inseparability between the two modes.

  2. Predicting protein-protein interactions from primary protein sequences using a novel multi-scale local feature representation scheme and the random forest.

    PubMed

    You, Zhu-Hong; Chan, Keith C C; Hu, Pengwei

    2015-01-01

    The study of protein-protein interactions (PPIs) can be very important for the understanding of biological cellular functions. However, detecting PPIs in the laboratories are both time-consuming and expensive. For this reason, there has been much recent effort to develop techniques for computational prediction of PPIs as this can complement laboratory procedures and provide an inexpensive way of predicting the most likely set of interactions at the entire proteome scale. Although much progress has already been achieved in this direction, the problem is still far from being solved. More effective approaches are still required to overcome the limitations of the current ones. In this study, a novel Multi-scale Local Descriptor (MLD) feature representation scheme is proposed to extract features from a protein sequence. This scheme can capture multi-scale local information by varying the length of protein-sequence segments. Based on the MLD, an ensemble learning method, the Random Forest (RF) method, is used as classifier. The MLD feature representation scheme facilitates the mining of interaction information from multi-scale continuous amino acid segments, making it easier to capture multiple overlapping continuous binding patterns within a protein sequence. When the proposed method is tested with the PPI data of Saccharomyces cerevisiae, it achieves a prediction accuracy of 94.72% with 94.34% sensitivity at the precision of 98.91%. Extensive experiments are performed to compare our method with existing sequence-based method. Experimental results show that the performance of our predictor is better than several other state-of-the-art predictors also with the H. pylori dataset. The reason why such good results are achieved can largely be credited to the learning capabilities of the RF model and the novel MLD feature representation scheme. The experiment results show that the proposed approach can be very promising for predicting PPIs and can be a useful tool for future

  3. PREDICTING RECIDIVISM FOR RELEASED STATE PRISON OFFENDERS

    PubMed Central

    Stahler, Gerald J.; Mennis, Jeremy; Belenko, Steven; Welsh, Wayne N.; Hiller, Matthew L.; Zajac, Gary

    2013-01-01

    We examined the influence of individual and neighborhood characteristics and spatial contagion in predicting reincarceration on a sample of 5,354 released Pennsylvania state prisoners. Independent variables included demographic characteristics, offense type, drug involvement, various neighborhood variables (e.g., concentrated disadvantage, residential mobility), and spatial contagion (i.e., proximity to others who become reincarcerated). Using geographic information systems (GIS) and logistic regression modeling, our results showed that the likelihood of reincarceration was increased with male gender, drug involvement, offense type, and living in areas with high rates of recidivism. Older offenders and those convicted of violent or drug offenses were less likely to be reincarcerated. For violent offenders, drug involvement, age, and spatial contagion were particular risk factors for reincarceration. None of the neighborhood environment variables were associated with increased risk of reincarceration. Reentry programs need to particularly address substance abuse issues of ex-offenders as well as take into consideration their residential locations. PMID:24443612

  4. Toward the Computational Representation of Individual Cultural, Cognitive, and Physiological State: The Sensor Shooter Simulation

    SciTech Connect

    RAYBOURN,ELAINE M.; FORSYTHE,JAMES C.

    2001-08-01

    This report documents an exploratory FY 00 LDRD project that sought to demonstrate the first steps toward a realistic computational representation of the variability encountered in individual human behavior. Realism, as conceptualized in this project, required that the human representation address the underlying psychological, cultural, physiological, and environmental stressors. The present report outlines the researchers' approach to representing cognitive, cultural, and physiological variability of an individual in an ambiguous situation while faced with a high-consequence decision that would greatly impact subsequent events. The present project was framed around a sensor-shooter scenario as a soldier interacts with an unexpected target (two young Iraqi girls). A software model of the ''Sensor Shooter'' scenario from Desert Storm was developed in which the framework consisted of a computational instantiation of Recognition Primed Decision Making in the context of a Naturalistic Decision Making model [1]. Recognition Primed Decision Making was augmented with an underlying foundation based on our current understanding of human neurophysiology and its relationship to human cognitive processes. While the Gulf War scenario that constitutes the framework for the Sensor Shooter prototype is highly specific, the human decision architecture and the subsequent simulation are applicable to other problems similar in concept, intensity, and degree of uncertainty. The goal was to provide initial steps toward a computational representation of human variability in cultural, cognitive, and physiological state in order to attain a better understanding of the full depth of human decision-making processes in the context of ambiguity, novelty, and heightened arousal.

  5. Representation of Sea Ice Processes in State of the Art Earth System Models.

    NASA Astrophysics Data System (ADS)

    Bailey, D. A.; Holland, M. M.

    2015-12-01

    The majority of Earth System Models now include thermodynamic-dynamic sea ice models with a subgridscale representation of ice thickness. The current sea ice component of the Community Earth System Model is the Los Alamos sea ice model (CICE) version 5. This new version of the model includes prognostic salinity in the vertical thermodynamic calculation as well as a representation of melt pond drainage through the sea ice. The CICE5 also includes a melt pond parameterization that takes into account the deformed and non-deformed ice within a model grid cell. Snow on sea ice processes allow for an evolving effective snow grain radius as a function of temperature, which is used in the shortwave radiative transfer and surface albedo calculation. I will discuss the results from coupled climate model sensitivity simulations that consider the subgridscale representations of some of these processes. This will include analysis of mean state and feedbacks in both the Arctic and Antarctic. Additional discussion will be provided on how we have used observations to guide these efforts.

  6. The multivariate Meixner polynomials as matrix elements of SO(d, 1) representations on oscillator states

    NASA Astrophysics Data System (ADS)

    Genest, Vincent X.; Miki, Hiroshi; Vinet, Luc; Zhedanov, Alexei

    2014-01-01

    The multivariate Meixner polynomials are shown to arise as matrix elements of unitary representations of the SO(d, 1) group on oscillator states. These polynomials depend on d discrete variables and are orthogonal with respect to the negative multinomial distribution. The emphasis is put on the bivariate case for which the SO(2, 1) connection is used to derive the main properties of the polynomials: orthogonality relation, raising/lowering relations, generating function, recurrence relations and difference equations as well as explicit expressions in terms of standard (univariate) Krawtchouk and Meixner polynomials. It is explained how these results generalize directly to d variables.

  7. Multiple coherent states for first-principles semiclassical initial value representation molecular dynamics.

    PubMed

    Ceotto, Michele; Atahan, Sule; Tantardini, Gian Franco; Aspuru-Guzik, Alán

    2009-06-21

    A multiple coherent states implementation of the semiclassical approximation is introduced and employed to obtain the power spectra with a few classical trajectories. The method is integrated with the time-averaging semiclassical initial value representation to successfully reproduce anharmonicity and Fermi resonance splittings at a level of accuracy comparable to semiclassical simulations of thousands of trajectories. The method is tested on two different model systems with analytical potentials and implemented in conjunction with the first-principles molecular dynamics scheme to obtain the power spectrum for the carbon dioxide molecule. PMID:19548717

  8. Distributions in the Error Space: Goal-Directed Movements Described in Time and State-Space Representations

    PubMed Central

    Fisher, Moria E.; Huang, Felix C.; Wright, Zachary A.; Patton, James L.

    2016-01-01

    Manipulation of error feedback has been of great interest to recent studies in motor control and rehabilitation. Typically, motor adaptation is shown as a change in performance with a single scalar metric for each trial, yet such an approach might overlook details about how error evolves through the movement. We believe that statistical distributions of movement error through the extent of the trajectory can reveal unique patterns of adaption and possibly reveal clues to how the motor system processes information about error. This paper describes different possible ordinate domains, focusing on representations in time and state-space, used to quantify reaching errors. We hypothesized that the domain with the lowest amount of variability would lead to a predictive model of reaching error with the highest accuracy. Here we showed that errors represented in a time domain demonstrate the least variance and allow for the highest predictive model of reaching errors. These predictive models will give rise to more specialized methods of robotic feedback and improve previous techniques of error augmentation. PMID:25571595

  9. Atypical lateralization of language predicts cerebral asymmetries in parietal gesture representations

    PubMed Central

    Króliczak, Gregory; Piper, Brian J.; Frey, Scott H.

    2011-01-01

    Humans typically show left-hemisphere dominance both for language and manual gestures. If this reflects a dependence of these behaviors on a common cerebral specialization, then healthy left-handers with atypical organization of language should show a similar pattern for gesture. Consistent with this hypothesis, we report fMRI data indicating that sinistrals (5/15) with bilateral, or right-lateralized, language representations in inferior frontal cortex exhibit a similar atypical pattern in inferior parietal representations of familiar gestures. PMID:21382390

  10. A new integral representation for the scalar products of Bethe states for the XXX spin chain

    NASA Astrophysics Data System (ADS)

    Kazama, Yoichi; Komatsu, Shota; Nishimura, Takuya

    2013-09-01

    Based on the method of separation of variables due to Sklyanin, we construct a new integral representation for the scalar products of the Bethe states for the SU(2) XXX spin 1/2 chain obeying the periodic boundary condition. Due to the compactness of the symmetry group, a twist matrix must be introduced at the boundary in order to extract the separated variables properly. Then by deriving the integration measure and the spectrum of the separated variables, we express the inner product of an on-shell and an off-shell Bethe states in terms of a multiple contour integral involving a product of Baxter wave functions. Its form is reminiscent of the integral over the eigenvalues of a matrix model and is expected to be useful in studying the semi-classical limit of the product.

  11. Thirst and the state-dependent representation of incentive stimulus value in human motive circuitry.

    PubMed

    Becker, Christoph A; Schmälzle, Ralf; Flaisch, Tobias; Renner, Britta; Schupp, Harald T

    2015-12-01

    Depletion imposes both need and desire to drink, and potentiates the response to need-relevant cues in the environment. The present fMRI study aimed to determine which neural structures selectively increase the incentive value of need-relevant stimuli in a thirst state. Towards this end, participants were scanned twice--either in a thirst or no-thirst state--while viewing pictures of beverages and chairs. As expected, thirst led to a selective increase in self-reported pleasantness and arousal by beverages. Increased responses to beverage when compared with chair stimuli were observed in the cingulate cortex, insular cortex and the amygdala in the thirst state, which were absent in the no-thirst condition. Enhancing the incentive value of need-relevant cues in a thirst state is a key mechanism for motivating drinking behavior. Overall, distributed regions of the motive circuitry, which are also implicated in salience processing, craving and interoception, provide a dynamic body-state dependent representation of stimulus value. PMID:25971601

  12. Tensor representation techniques in post-Hartree-Fock methods: matrix product state tensor format

    NASA Astrophysics Data System (ADS)

    Benedikt, Udo; Auer, Henry; Espig, Mike; Hackbusch, Wolfgang; Auer, Alexander A.

    2013-09-01

    In this proof-of-principle study, we discuss the application of various tensor representation formats and their implications on memory requirements and computational effort for tensor manipulations as they occur in typical post-Hartree-Fock (post-HF) methods. A successive tensor decomposition/rank reduction scheme in the matrix product state (MPS) format for the two-electron integrals in the AO and MO bases and an estimate of the t 2 amplitudes as obtained from second-order many-body perturbation theory (MP2) are described. Furthermore, the AO-MO integral transformation, the calculation of the MP2 energy and the potential usage of tensors in low-rank MPS representation for the tensor contractions in coupled cluster theory are discussed in detail. We are able to show that the overall scaling of the memory requirements is reduced from the conventional N 4 scaling to approximately N 3 and the scaling of computational effort for tensor contractions in post-HF methods can be reduced to roughly N 4 while the decomposition itself scales as N 5. While efficient algorithms with low prefactor for the tensor decomposition have yet to be devised, this ansatz offers the possibility to find a robust approximation with low-scaling behaviour with system and basis-set size for post-HF ab initio methods.

  13. Spin Coherent State Representation of the Crow-Kimura and Eigen Models of Quasispecies Theory

    NASA Astrophysics Data System (ADS)

    Ancliff, Mark; Park, Jeong-Man

    2011-05-01

    We present a spin coherent state representation of the Crow-Kimura and Eigen models of biological evolution. We deal with quasispecies models where the fitness is a function of Hamming distances from one or more reference sequences. In the limit of large sequence length N, we find exact expressions for the mean fitness and magnetization of the asymptotic quasispecies distribution in symmetric fitness landscapes. The results are obtained by constructing a path integral for the propagator on the coset SU(2)/ U(1) and taking the classical limit. The classical limit gives a Hamiltonian function on a circle for one reference sequence, and on the product of 2 m -1 circles for m reference sequences. We apply our representation to study the Schuster-Swetina phenomena, where a wide lower peak is selected over a narrow higher peak. The quadratic landscape with two reference sequences is also analyzed specifically and we present the phase diagram on the mutation-fitness parameter phase space. Furthermore, we use our method to investigate more biologically relevant system, a model of escape from adaptive conflict through gene duplication, and find three different phases for the asymptotic population distribution.

  14. Ab Initio Quality NMR Parameters in Solid-State Materials Using a High-Dimensional Neural-Network Representation.

    PubMed

    Cuny, Jérôme; Xie, Yu; Pickard, Chris J; Hassanali, Ali A

    2016-02-01

    Nuclear magnetic resonance (NMR) spectroscopy is one of the most powerful experimental tools to probe the local atomic order of a wide range of solid-state compounds. However, due to the complexity of the related spectra, in particular for amorphous materials, their interpretation in terms of structural information is often challenging. These difficulties can be overcome by combining molecular dynamics simulations to generate realistic structural models with an ab initio evaluation of the corresponding chemical shift and quadrupolar coupling tensors. However, due to computational constraints, this approach is limited to relatively small system sizes which, for amorphous materials, prevents an adequate statistical sampling of the distribution of the local environments that is required to quantitatively describe the system. In this work, we present an approach to efficiently and accurately predict the NMR parameters of very large systems. This is achieved by using a high-dimensional neural-network representation of NMR parameters that are calculated using an ab initio formalism. To illustrate the potential of this approach, we applied this neural-network NMR (NN-NMR) method on the (17)O and (29)Si quadrupolar coupling and chemical shift parameters of various crystalline silica polymorphs and silica glasses. This approach is, in principal, general and has the potential to be applied to predict the NMR properties of various materials. PMID:26730889

  15. DISULFIND: a disulfide bonding state and cysteine connectivity prediction server

    PubMed Central

    Ceroni, Alessio; Passerini, Andrea; Vullo, Alessandro; Frasconi, Paolo

    2006-01-01

    DISULFIND is a server for predicting the disulfide bonding state of cysteines and their disulfide connectivity starting from sequence alone. Optionally, disulfide connectivity can be predicted from sequence and a bonding state assignment given as input. The output is a simple visualization of the assigned bonding state (with confidence degrees) and the most likely connectivity patterns. The server is available at . PMID:16844986

  16. Automatic prediction regarding the next state of a visual object: Electrophysiological indicators of prediction match and mismatch.

    PubMed

    Kimura, Motohiro; Takeda, Yuji

    2015-11-11

    Behavioral phenomena such as representational momentum suggest that the brain can automatically predict the next state of a visual object, based on sequential rules embedded in its preceding spatiotemporal context. To identify electrophysiological indicators of automatic visual prediction in terms of prediction match and mismatch, we recorded event-related brain potentials (ERPs) while participants passively viewed three types of task-irrelevant sequences of a bar stimulus: (1) an oddball sequence, which contained a sequential rule defined by stimulus repetition, providing repetition-rule-conforming (standard) and -violating (deviant) stimuli; (2) a rotating-oddball sequence, which contained a sequential rule defined by stimulus change (i.e., rotation), providing change-rule-conforming (regular) and -violating (irregular) stimuli; and (3) a random sequence, which did not contain a sequential rule, providing a neutral (control) stimulus. This protocol allowed us to expect that (1) an ERP effect that reflects a prediction-mismatch process should be exclusively observed in both the deviant-minus-control and irregular-minus-control comparisons and (2) an ERP effect that reflects a prediction-match process should be exclusively observed in both the standard-minus-control and regular-minus-control comparisons. The results showed that the ERP effect that met the criterion for prediction mismatch was an occipito-temporal negative deflection at around 170-300ms (visual mismatch negativity), while the ERP effect that met the criterion for prediction match was a frontal/central negative deflection at around 150-270ms (probably, the reduction of P2). These two contrasting ERP effects support a hypothetical view that automatic visual prediction would involve both an increase in the neural response to prediction-incongruent (i.e., novel) events and a decrease in the neural response to prediction-congruent (i.e., redundant) events. This article is part of a Special Issue entitled

  17. Vector coherent state theory of the generic representations of so(5) in an so(3) basis

    SciTech Connect

    Turner, P.S.; Rowe, D.J.; Repka, J.

    2006-02-15

    For applications of group theory in quantum mechanics, one generally needs explicit matrix representations of the spectrum generating algebras that arise in bases that reduce the symmetry group of some Hamiltonian of interest. Here we use vector coherent state techniques to develop an algorithm for constructing the matrices for arbitrary finite-dimensional irreps of the SO(5) Lie algebra in an SO(3) basis. The SO(3) subgroup of SO(5) is defined by regarding SO(5) as linear transformations of the five-dimensional space of an SO(3) irrep of angular momentum two. A need for such irreps arises in the nuclear collective model of quadrupole vibrations and rotations. The algorithm has been implemented in MAPLE, and some tables of results are presented.

  18. A diabatic representation of the two lowest electronic states of Li{sub 3}

    SciTech Connect

    Ghassemi, Elham Nour; Larson, Jonas; Institut für Theoretische Physik, Universität zu Köln, Köln De-50937 ; Larson, Åsa

    2014-04-21

    Using the Multi-Reference Configuration Interaction method, the adiabatic potential energy surfaces of Li{sub 3} are computed. The two lowest electronic states are bound and exhibit a conical intersection. By fitting the calculated potential energy surfaces to the cubic E ⊗ ε Jahn-Teller model we extract the effective Jahn-Teller parameters corresponding to Li{sub 3}. These are used to set up the transformation matrix which transforms from the adiabatic to a diabatic representation. This diabatization method gives a Hamiltonian for Li{sub 3} which is free from singular non-adiabatic couplings and should be accurate for large internuclear distances, and it thereby allows for bound dynamics in the vicinity of the conical intersection to be explored.

  19. A finite element surface impedance representation for steady-state problems

    NASA Technical Reports Server (NTRS)

    Kalinowski, A. J.

    1986-01-01

    A procedure for determining the scattered pressure field resulting from a monochromatic harmonic wave that is incident upon a layer energy absorbing structure is treated. The situation where the structure is modeled with finite elements and the surrounding acoustic medium (water or air) is represented with either acoustic finite elements, or some type of boundary integral formulation, is considered. Finite element modeling problems arise when the construction of the structure, at the fluid structure interface, are nonhomogeneous and in particular, when the inhomogeneities are small relative to the acoustic wave length. An approximate procedure is presented for replacing the detailed microscopic representation of the layered surface configuration with an equivalent simple surface impedance finite element, which is especially designed to work only at limited frequencies. An example problem is presented using NASTRAN. However, the procedure is general enough to adapt to practically any finite element code having a steady state option.

  20. Qubit phase space: SU(n) coherent-state P representations

    NASA Astrophysics Data System (ADS)

    Barry, D. W.; Drummond, P. D.

    2008-11-01

    We introduce a phase-space representation for qubits and spin models. The technique uses an SU(n) coherent-state basis and can equally be used for either static or dynamical simulations. We review previously known definitions and operator identities, and show how these can be used to define an off-diagonal, positive phase-space representation analogous to the positive- P function. As an illustration of the phase-space method, we use the example of the Ising model, which has exact solutions for the finite-temperature canonical ensemble in two dimensions. We show how a canonical ensemble for an Ising model of arbitrary structure can be efficiently simulated using SU(2) or atomic coherent states. The technique utilizes a transformation from a canonical (imaginary-time) weighted simulation to an equivalent unweighted real-time simulation. The results are compared to the exactly soluble two-dimensional case. We note that Ising models in one, two, or three dimensions are potentially achievable experimentally as a lattice gas of ultracold atoms in optical lattices. The technique is not restricted to canonical ensembles or to Ising-like couplings. It is also able to be used for real-time evolution and for systems whose time evolution follows a master equation describing decoherence and coupling to external reservoirs. The case of SU(n) phase space is used to describe n -level systems. In general, the requirement that time evolution be stochastic corresponds to a restriction to Hamiltonians and master equations that are quadratic in the group generators or generalized spin operators.

  1. Do attachment representations predict depression and anxiety in psychiatrically hospitalized prepubertal children?

    PubMed

    Goodman, Geoff; Stroh, Martha; Valdez, Adina

    2012-01-01

    Thirty-six prepubertal inpatients were videotaped completing five stories thematically related to attachment experiences and classified by their attachment representations. Children also completed the Children's Depression Inventory and Diagnostic Interview for Children and Adolescents-Revised. Mothers completed demographic questionnaires. Percentage of secure (B) attachment was only about one tenth of the normative percentage, anxious-ambivalent (C) attachment was between two and three times the normative percentage, and disorganized (D) attachment was almost twice the normative percentage. Both D attachment and the total number of disorganized story responses were associated with negative self-esteem and clinical-range depression. Anxious-avoidant (A) attachment decreased the likelihood, while C and D attachment increased the likelihood, of separation anxiety disorder. Clinical intervention needs to focus on the meaning of parental relationships represented in the child's mind, specifically the negative self-esteem and separation anxiety associated with the lack of felt security provided by the parents. PMID:22988901

  2. Early Numeracy Indicators: Examining Predictive Utility Across Years and States

    ERIC Educational Resources Information Center

    Conoyer, Sarah J.; Foegen, Anne; Lembke, Erica S.

    2016-01-01

    Two studies using similar methods in two states investigated the long-term predictive utility of two single-skill early numeracy Curriculum Based Measures (CBMs) and the degree to which they can adequately predict high-stakes test scores. Data were drawn from kindergarten and first-grade students. State standardized assessment data from the…

  3. Point-process high-resolution representations of heartbeat dynamics for multiscale analysis: A CHF survivor prediction study.

    PubMed

    Valenza, G; Wendt, H; Kiyono, K; Hayano, J; Watanabe, E; Yamamoto, Y; Abry, P; Barbieri, R

    2015-08-01

    Multiscale analysis of human heartbeat dynamics has been proved effective in characterizeing cardiovascular control physiology in health and disease. However, estimation of multiscale properties can be affected by the interpolation procedure used to preprocess the unevenly sampled R-R intervals derived from the ECG. To this extent, in this study we propose the estimation of wavelet coefficients and wavelet leaders on the output of inhomogeneous point process models of heartbeat dynamics. The RR interval series is modeled using probability density functions (pdfs) characterizing and predicting the time until the next heartbeat event occurs, as a linear function of the past history. Multiscale analysis is then applied to the pdfs' instantaneous first order moment. The proposed approach is tested on experimental data gathered from 57 congestive heart failure (CHF) patients by evaluating the recognition accuracy in predicting survivor and non-survivor patients, and by comparing performances from the informative point-process based interpolation and non-informative spline-based interpolation. Results demonstrate that multiscale analysis of point-process high-resolution representations achieves the highest prediction accuracy of 65.45%, proving our method as a promising tool to assess risk prediction in CHF patients. PMID:26736666

  4. Talking about Internal States in Mother-Child Reminiscing Influences Children's Self-Representations: A Cross-Cultural Study

    ERIC Educational Resources Information Center

    Wang, Qi; Doan, Stacey N.; Song, Qingfang

    2010-01-01

    This study examined the relation of mother-child discussions of internal states during reminiscing to the development of trait and evaluative self-representations in 131 European American and Chinese immigrant 3-year olds. Mothers and children discussed one positive and one negative event, and children were interviewed for self-descriptions.…

  5. Multiple coherent states semiclassical initial value representation spectra calculations of lateral interactions for CO on Cu(100).

    PubMed

    Ceotto, Michele; Dell'Angelo, David; Tantardini, Gian Franco

    2010-08-01

    Lateral interactions between carbon monoxide molecules adsorbed on a copper Cu(100) surface are investigated via semiclassical initial value representation (SC-IVR) molecular dynamics. A previous analytical potential is extended to include long-range dipole interactions between coadsorbed molecules and preliminary classical simulations were performed to tune the potential parameters. Then, the spectra for several coadsorbed molecules are calculated using the multiple coherent states approximation of the time-averaging representation of the SC-IVR propagator. Results show strong resonances between coadsorbed molecules as observed by past experiments. Resonances turn into dephasing when isotopical substitutions are performed. PMID:20707543

  6. Predictability sieve, pointer states, and the classicality of quantum trajectories

    SciTech Connect

    Dalvit, D. A. R.; Zurek, W. H.; Dziarmaga, J.

    2005-12-15

    We study various measures of classicality of the states of open quantum systems subject to decoherence. Classical states are expected to be stable in spite of decoherence, and are thought to leave conspicuous imprints on the environment. Here these expected features of environment-induced superselection are quantified using four different criteria: predictability sieve (which selects states that produce least entropy), purification time (which looks for states that are the easiest to find out from the imprint they leave on the environment), efficiency threshold (which finds states that can be deduced from measurements on a smallest fraction of the environment), and purity loss time (that looks for states for which it takes the longest to lose a set fraction of their initial purity). We show that when pointer states--the most predictable states of an open quantum system selected by the predictability sieve--are well defined, all four criteria agree that they are indeed the most classical states. We illustrate this with two examples: an underdamped harmonic oscillator, for which coherent states are unanimously chosen by all criteria, and a free particle undergoing quantum Brownian motion, for which most criteria select almost identical Gaussian states (although, in this case, the predictability sieve does not select well defined pointer states)

  7. The Frequency of "Brilliant" and "Genius" in Teaching Evaluations Predicts the Representation of Women and African Americans across Fields.

    PubMed

    Storage, Daniel; Horne, Zachary; Cimpian, Andrei; Leslie, Sarah-Jane

    2016-01-01

    Women and African Americans-groups targeted by negative stereotypes about their intellectual abilities-may be underrepresented in careers that prize brilliance and genius. A recent nationwide survey of academics provided initial support for this possibility. Fields whose practitioners believed that natural talent is crucial for success had fewer female and African American PhDs. The present study seeks to replicate this initial finding with a different, and arguably more naturalistic, measure of the extent to which brilliance and genius are prized within a field. Specifically, we measured field-by-field variability in the emphasis on these intellectual qualities by tallying-with the use of a recently released online tool-the frequency of the words "brilliant" and "genius" in over 14 million reviews on RateMyProfessors.com, a popular website where students can write anonymous evaluations of their instructors. This simple word count predicted both women's and African Americans' representation across the academic spectrum. That is, we found that fields in which the words "brilliant" and "genius" were used more frequently on RateMyProfessors.com also had fewer female and African American PhDs. Looking at an earlier stage in students' educational careers, we found that brilliance-focused fields also had fewer women and African Americans obtaining bachelor's degrees. These relationships held even when accounting for field-specific averages on standardized mathematics assessments, as well as several competing hypotheses concerning group differences in representation. The fact that this naturalistic measure of a field's focus on brilliance predicted the magnitude of its gender and race gaps speaks to the tight link between ability beliefs and diversity. PMID:26938242

  8. Representation of Vegetation and Other Nonerodible Elements in Aeolian Shear Stress Partitioning Models for Predicting Transport Threshold

    NASA Technical Reports Server (NTRS)

    King, James; Nickling, William G.; Gillies, John A.

    2005-01-01

    The presence of nonerodible elements is well understood to be a reducing factor for soil erosion by wind, but the limits of its protection of the surface and erosion threshold prediction are complicated by the varying geometry, spatial organization, and density of the elements. The predictive capabilities of the most recent models for estimating wind driven particle fluxes are reduced because of the poor representation of the effectiveness of vegetation to reduce wind erosion. Two approaches have been taken to account for roughness effects on sediment transport thresholds. Marticorena and Bergametti (1995) in their dust emission model parameterize the effect of roughness on threshold with the assumption that there is a relationship between roughness density and the aerodynamic roughness length of a surface. Raupach et al. (1993) offer a different approach based on physical modeling of wake development behind individual roughness elements and the partition of the surface stress and the total stress over a roughened surface. A comparison between the models shows the partitioning approach to be a good framework to explain the effect of roughness on entrainment of sediment by wind. Both models provided very good agreement for wind tunnel experiments using solid objects on a nonerodible surface. However, the Marticorena and Bergametti (1995) approach displays a scaling dependency when the difference between the roughness length of the surface and the overall roughness length is too great, while the Raupach et al. (1993) model's predictions perform better owing to the incorporation of the roughness geometry and the alterations to the flow they can cause.

  9. Trait-Based Representation of Biological Nitrification: Model Development, Testing, and Predicted Community Composition

    PubMed Central

    Bouskill, Nicholas J.; Tang, Jinyun; Riley, William J.; Brodie, Eoin L.

    2012-01-01

    Trait-based microbial models show clear promise as tools to represent the diversity and activity of microorganisms across ecosystem gradients. These models parameterize specific traits that determine the relative fitness of an “organism” in a given environment, and represent the complexity of biological systems across temporal and spatial scales. In this study we introduce a microbial community trait-based modeling framework (MicroTrait) focused on nitrification (MicroTrait-N) that represents the ammonia-oxidizing bacteria (AOB) and ammonia-oxidizing archaea (AOA) and nitrite-oxidizing bacteria (NOB) using traits related to enzyme kinetics and physiological properties. We used this model to predict nitrifier diversity, ammonia (NH3) oxidation rates, and nitrous oxide (N2O) production across pH, temperature, and substrate gradients. Predicted nitrifier diversity was predominantly determined by temperature and substrate availability, the latter was strongly influenced by pH. The model predicted that transient N2O production rates are maximized by a decoupling of the AOB and NOB communities, resulting in an accumulation and detoxification of nitrite to N2O by AOB. However, cumulative N2O production (over 6 month simulations) is maximized in a system where the relationship between AOB and NOB is maintained. When the reactions uncouple, the AOB become unstable and biomass declines rapidly, resulting in decreased NH3 oxidation and N2O production. We evaluated this model against site level chemical datasets from the interior of Alaska and accurately simulated NH3 oxidation rates and the relative ratio of AOA:AOB biomass. The predicted community structure and activity indicate (a) parameterization of a small number of traits may be sufficient to broadly characterize nitrifying community structure and (b) changing decadal trends in climate and edaphic conditions could impact nitrification rates in ways that are not captured by extant biogeochemical models. PMID

  10. Improved pan-specific MHC class I peptide-binding predictions using a novel representation of the MHC-binding cleft environment.

    PubMed

    Carrasco Pro, S; Zimic, M; Nielsen, M

    2014-02-01

    Major histocompatibility complex (MHC) molecules play a key role in cell-mediated immune responses presenting bounded peptides for recognition by the immune system cells. Several in silico methods have been developed to predict the binding affinity of a given peptide to a specific MHC molecule. One of the current state-of-the-art methods for MHC class I is NetMHCpan, which has a core ingredient for the representation of the MHC class I molecule using a pseudo-sequence representation of the binding cleft amino acid environment. New and large MHC-peptide-binding data sets are constantly being made available, and also new structures of MHC class I molecules with a bound peptide have been published. In order to test if the NetMHCpan method can be improved by integrating this novel information, we created new pseudo-sequence definitions for the MHC-binding cleft environment from sequence and structural analyses of different MHC data sets including human leukocyte antigen (HLA), non-human primates (chimpanzee, macaque and gorilla) and other animal alleles (cattle, mouse and swine). From these constructs, we showed that by focusing on MHC sequence positions found to be polymorphic across the MHC molecules used to train the method, the NetMHCpan method achieved a significant increase in the predictive performance, in particular, of non-human MHCs. This study hence showed that an improved performance of MHC-binding methods can be achieved not only by the accumulation of more MHC-peptide-binding data but also by a refined definition of the MHC-binding environment including information from non-human species. PMID:24447175

  11. Moon meteoritic seismic hum: Steady state prediction

    USGS Publications Warehouse

    Lognonne, P.; Feuvre, M.L.; Johnson, C.L.; Weber, R.C.

    2009-01-01

    We use three different statistical models describing the frequency of meteoroid impacts on Earth to estimate the seismic background noise due to impacts on the lunar surface. Because of diffraction, seismic events on the Moon are typically characterized by long codas, lasting 1 h or more. We find that the small but frequent impacts generate seismic signals whose codas overlap in time, resulting in a permanent seismic noise that we term the "lunar hum" by analogy with the Earth's continuous seismic background seismic hum. We find that the Apollo era impact detection rates and amplitudes are well explained by a model that parameterizes (1) the net seismic impulse due to the impactor and resulting ejecta and (2) the effects of diffraction and attenuation. The formulation permits the calculation of a composite waveform at any point on the Moon due to simulated impacts at any epicentral distance. The root-mean-square amplitude of this waveform yields a background noise level that is about 100 times lower than the resolution of the Apollo long-period seismometers. At 2 s periods, this noise level is more than 1000 times lower than the low noise model prediction for Earth's microseismic noise. Sufficiently sensitive seismometers will allow the future detection of several impacts per day at body wave frequencies. Copyright 2009 by the American Geophysical Union.

  12. Construal Levels and Psychological Distance: Effects on Representation, Prediction, Evaluation, and Behavior

    PubMed Central

    Trope, Yaacov; Liberman, Nira; Wakslak, Cheryl

    2011-01-01

    Construal level theory (CLT) is an account of how psychological distance influences individuals’ thoughts and behavior. CLT assumes that people mentally construe objects that are psychologically near in terms of low-level, detailed, and contextualized features, whereas at a distance they construe the same objects or events in terms of high-level, abstract, and stable characteristics. Research has shown that different dimensions of psychological distance (time, space, social distance, and hypotheticality) affect mental construal and that these construals, in turn, guide prediction, evaluation, and behavior. The present paper reviews this research and its implications for consumer psychology. PMID:21822366

  13. Echo state network prediction method and its application in flue gas turbine condition prediction

    NASA Astrophysics Data System (ADS)

    Wang, Shaohong; Chen, Tao; Xu, Xiaoli

    2010-12-01

    On the background of the complex production process of fluid catalytic cracking energy recovery system in large-scale petrochemical refineries, this paper introduced an improved echo state network (ESN) model prediction method which is used to address the condition trend prediction problem of the key power equipment--flue gas turbine. Singular value decomposition method was used to obtain the ESN output weight. Through selecting the appropriate parameters and discarding small singular value, this method overcame the defective solution problem in the prediction by using the linear regression algorithm, improved the prediction performance of echo state network, and gave the network prediction process. In order to solve the problem of noise contained in production data, the translation-invariant wavelet transform analysis method is combined to denoise the noisy time series before prediction. Condition trend prediction results show the effectiveness of the proposed method.

  14. The Current State of Predicting Furrow Irrigation Erosion

    Technology Transfer Automated Retrieval System (TEKTRAN)

    There continues to be a need to predict furrow irrigation erosion to estimate on- and off-site impacts of irrigation management. The objective of this paper is to review the current state of furrow erosion prediction technology considering four models: SISL, WEPP, WinSRFR and APEX. SISL is an empiri...

  15. Movement representation in the primary motor cortex and its contribution to generalizable EMG predictions.

    PubMed

    Oby, Emily R; Ethier, Christian; Miller, Lee E

    2013-02-01

    It is well known that discharge of neurons in the primary motor cortex (M1) depends on end-point force and limb posture. However, the details of these relations remain unresolved. With the development of brain-machine interfaces (BMIs), these issues have taken on practical as well as theoretical importance. We examined how the M1 encodes movement by comparing single-neuron and electromyographic (EMG) preferred directions (PDs) and by predicting force and EMGs from multiple neurons recorded during an isometric wrist task. Monkeys moved a cursor from a central target to one of eight peripheral targets by exerting force about the wrist while the forearm was held in one of two postures. We fit tuning curves to both EMG and M1 activity measured during the hold period, from which we computed both PDs and the change in PD between forearm postures (ΔPD). We found a unimodal distribution of these ΔPDs, the majority of which were intermediate between the typical muscle response and an unchanging, extrinsic coordinate system. We also discovered that while most neuron-to-EMG predictions generalized well across forearm postures, end-point force measured in extrinsic coordinates did not. The lack of force generalization was due to musculoskeletal changes with posture. Our results show that the dynamics of most of the recorded M1 signals are similar to those of muscle activity and imply that a BMI designed to drive an actuator with dynamics like those of muscles might be more robust and easier to learn than a BMI that commands forces or movements in external coordinates. PMID:23155172

  16. Applying representational state transfer (REST) architecture to archetype-based electronic health record systems

    PubMed Central

    2013-01-01

    Background The openEHR project and the closely related ISO 13606 standard have defined structures supporting the content of Electronic Health Records (EHRs). However, there is not yet any finalized openEHR specification of a service interface to aid application developers in creating, accessing, and storing the EHR content. The aim of this paper is to explore how the Representational State Transfer (REST) architectural style can be used as a basis for a platform-independent, HTTP-based openEHR service interface. Associated benefits and tradeoffs of such a design are also explored. Results The main contribution is the formalization of the openEHR storage, retrieval, and version-handling semantics and related services into an implementable HTTP-based service interface. The modular design makes it possible to prototype, test, replicate, distribute, cache, and load-balance the system using ordinary web technology. Other contributions are approaches to query and retrieval of the EHR content that takes caching, logging, and distribution into account. Triggering on EHR change events is also explored. A final contribution is an open source openEHR implementation using the above-mentioned approaches to create LiU EEE, an educational EHR environment intended to help newcomers and developers experiment with and learn about the archetype-based EHR approach and enable rapid prototyping. Conclusions Using REST addressed many architectural concerns in a successful way, but an additional messaging component was needed to address some architectural aspects. Many of our approaches are likely of value to other archetype-based EHR implementations and may contribute to associated service model specifications. PMID:23656624

  17. Dynamic filtering improves attentional state prediction with fNIRS.

    PubMed

    Harrivel, Angela R; Weissman, Daniel H; Noll, Douglas C; Huppert, Theodore; Peltier, Scott J

    2016-03-01

    Brain activity can predict a person's level of engagement in an attentional task. However, estimates of brain activity are often confounded by measurement artifacts and systemic physiological noise. The optimal method for filtering this noise - thereby increasing such state prediction accuracy - remains unclear. To investigate this, we asked study participants to perform an attentional task while we monitored their brain activity with functional near infrared spectroscopy (fNIRS). We observed higher state prediction accuracy when noise in the fNIRS hemoglobin [Hb] signals was filtered with a non-stationary (adaptive) model as compared to static regression (84% ± 6% versus 72% ± 15%). PMID:27231602

  18. Dynamic filtering improves attentional state prediction with fNIRS

    PubMed Central

    Harrivel, Angela R.; Weissman, Daniel H.; Noll, Douglas C.; Huppert, Theodore; Peltier, Scott J.

    2016-01-01

    Brain activity can predict a person’s level of engagement in an attentional task. However, estimates of brain activity are often confounded by measurement artifacts and systemic physiological noise. The optimal method for filtering this noise – thereby increasing such state prediction accuracy – remains unclear. To investigate this, we asked study participants to perform an attentional task while we monitored their brain activity with functional near infrared spectroscopy (fNIRS). We observed higher state prediction accuracy when noise in the fNIRS hemoglobin [Hb] signals was filtered with a non-stationary (adaptive) model as compared to static regression (84% ± 6% versus 72% ± 15%). PMID:27231602

  19. Valence-separated representation of reward prediction error in feedback-related negativity and positivity.

    PubMed

    Bai, Yu; Katahira, Kentaro; Ohira, Hideki

    2015-02-11

    Feedback-related negativity (FRN) is an event-related brain potential (ERP) component elicited by errors and negative outcomes. Previous studies proposed that FRN reflects the activity of a general error-processing system that incorporates reward prediction error (RPE). However, other studies reported inconsistent results on this issue - namely, that FRN only reflects the valence of feedback and that the magnitude of RPE is reflected by the other ERP component called P300. The present study focused on the relationship between the FRN amplitude and RPE. ERPs were recorded during a reversal learning task performed by the participants, and a computational model was used to estimate trial-by-trial RPEs, which we correlated with the ERPs. The results indicated that FRN and P300 reflected the magnitude of RPE in negative outcomes and positive outcomes, respectively. In addition, the correlation between RPE and the P300 amplitude was stronger than the correlation between RPE and the FRN amplitude. These differences in the correlation between ERP and RPE components may explain the inconsistent results reported by previous studies; the asymmetry in the correlations might make it difficult to detect the effect of the RPE magnitude on the FRN and makes it appear that the FRN only reflects the valence of feedback. PMID:25634316

  20. Model Representation of Multi-Cyclic Phenomena Using Role State Variables: Model Based Fast Idling Control of SI Engine

    NASA Astrophysics Data System (ADS)

    Jimbo, Tomohiko; Hayakawa, Yoshikazu

    The present paper describes a model representation of multi-cyclic phenomena for a multi-cylinder engine system. The model is simplified for implementation as a practical engine controller. The simplified model with physically meaningful variables can be used in design considering practical objectives and constraints more effectively. The proposed approach consists of two steps. First, an approximate analytical discrete crank angle model (i.e., a periodically time-varying state space model) is derived from the conservation laws. Second, the concept of role state variables is proposed to transform the periodically time-varying state space model into a time-invariant state space model. The stabilizability and optimality of the time-invariant state space model imply those of the periodically time-varying state space model. The time-invariant state space model is used to design cold start feedforward and feedback controllers.

  1. State-space representation of Li-ion battery porous electrode impedance model with balanced model reduction

    NASA Astrophysics Data System (ADS)

    Jun, Myungsoo; Smith, Kandler; Graf, Peter

    2015-01-01

    This paper presents an approximate time-domain solution for physics-based electrochemical lithium-ion cell battery models. The time-domain solution is represented in state-space form and can be easily used for the design of a state estimator or controller. It uses an interconnection-of-system approach to derive a state-space representation of a battery impedance model and provides a reduced order model based via the balanced truncation method. Simulation results are also provided to show the performance of the proposed model in the frequency domain.

  2. Potential impact of remote sensing data on sea-state analysis and prediction

    NASA Technical Reports Server (NTRS)

    Cardone, V. J.

    1983-01-01

    The severe North Atlantic storm which damaged the ocean liner Queen Elizabeth 2 (QE2) was studied to assess the impact of remotely sensed marine surface wind data obtained by SEASAT-A, on sea state specifications and forecasts. Alternate representations of the surface wind field in the QE2 storm were produced from the SEASAT enhanced data base, and from operational analyses based upon conventional data. The wind fields were used to drive a high resolution spectral ocean surface wave prediction model. Results show that sea state analyses would have been vastly improved during the period of storm formation and explosive development had remote sensing wind data been available in real time. A modest improvement in operational 12 to 24 hour wave forecasts would have followed automatically from the improved initial state specification made possible by the remote sensing data in both numerical and sea state prediction models. Significantly improved 24 to 48 hour wave forecasts require in addition to remote sensing data, refinement in the numerical and physical aspects of weather prediction models.

  3. The Invisible Link: Using State Space Representations to Investigate the Connection between Variables and Their Referents

    ERIC Educational Resources Information Center

    Pollack, Courtney

    2012-01-01

    The ability to represent numerical quantities in symbolic form is a necessary foundation for mathematical competence. Variables are particularly important symbolic representations for learning algebra and succeeding in higher mathematics, but the mechanisms of how students link a variable to what it represents are not well understood. Research…

  4. Leaders as attachment figures: leaders' attachment orientations predict leadership-related mental representations and followers' performance and mental health.

    PubMed

    Davidovitz, Rivka; Mikulincer, Mario; Shaver, Phillip R; Izsak, Ronit; Popper, Micha

    2007-10-01

    In 3 studies, the authors examined the contribution of leaders' attachment styles to their leadership motives and beliefs and to followers' outcomes. In Study 1, participants completed measures of attachment orientation, leadership motives, self-representations, and leadership style. Studies 2 and 3 were conducted within Israeli military units either during a leadership workshop or during intensive combat training. Israeli military officers and their soldiers (followers) reported on their attachment styles, and the soldiers reported on the officers' leadership qualities and on the soldiers' own performance and mental health. Leaders' attachment anxiety was associated with more self-serving leadership motives and with poorer leadership qualities in task-oriented situations. Leaders' attachment anxiety also predicted followers' poorer instrumental functioning. Leaders' attachment-related avoidance was negatively associated with prosocial motives to lead, with the failure to act as a security provider, and with followers' poorer socioemotional functioning and poorer long-range mental health. Results are discussed with respect to the value of attachment theory for the study of leadership. PMID:17892336

  5. Representation of Ecological Systems within the Protected Areas Network of the Continental United States

    PubMed Central

    Aycrigg, Jocelyn L.; Davidson, Anne; Svancara, Leona K.; Gergely, Kevin J.; McKerrow, Alexa; Scott, J. Michael

    2013-01-01

    If conservation of biodiversity is the goal, then the protected areas network of the continental US may be one of our best conservation tools for safeguarding ecological systems (i.e., vegetation communities). We evaluated representation of ecological systems in the current protected areas network and found insufficient representation at three vegetation community levels within lower elevations and moderate to high productivity soils. We used national-level data for ecological systems and a protected areas database to explore alternative ways we might be able to increase representation of ecological systems within the continental US. By following one or more of these alternatives it may be possible to increase the representation of ecological systems in the protected areas network both quantitatively (from 10% up to 39%) and geographically and come closer to meeting the suggested Convention on Biological Diversity target of 17% for terrestrial areas. We used the Landscape Conservation Cooperative framework for regional analysis and found that increased conservation on some private and public lands may be important to the conservation of ecological systems in Western US, while increased public-private partnerships may be important in the conservation of ecological systems in Eastern US. We have not assessed the pros and cons of following the national or regional alternatives, but rather present them as possibilities that may be considered and evaluated as decisions are made to increase the representation of ecological systems in the protected areas network across their range of ecological, geographical, and geophysical occurrence in the continental US into the future. PMID:23372754

  6. Predicting user mental states in spoken dialogue systems

    NASA Astrophysics Data System (ADS)

    Callejas, Zoraida; Griol, David; López-Cózar, Ramón

    2011-12-01

    In this paper we propose a method for predicting the user mental state for the development of more efficient and usable spoken dialogue systems. This prediction, carried out for each user turn in the dialogue, makes it possible to adapt the system dynamically to the user needs. The mental state is built on the basis of the emotional state of the user and their intention, and is recognized by means of a module conceived as an intermediate phase between natural language understanding and the dialogue management in the architecture of the systems. We have implemented the method in the UAH system, for which the evaluation results with both simulated and real users show that taking into account the user's mental state improves system performance as well as its perceived quality.

  7. Mental Health and Immigrant Detainees in the United States: Competency and Self-Representation.

    PubMed

    Korngold, Caleb; Ochoa, Kristen; Inlender, Talia; McNiel, Dale; Binder, Renée

    2015-09-01

    Most immigrant detainees held in U.S. Immigration and Customs Enforcement (ICE) facilities do not have legal representation, because immigration proceedings are a matter of civil, not criminal, law. In 2005, Mr. Franco, an immigrant from Mexico with an IQ between 35 and 55, was found incompetent to stand trial, but was not appointed an attorney for his immigration proceedings. This failure led to a class action lawsuit, known as the Franco litigation, and in April 2013, a federal judge ordered the U. S. government to provide legal representation for immigrant detainees in California, Arizona, and Washington who are incompetent to represent themselves due to a mental disorder or defect. This development has implications for forensic evaluators, because there is likely to be an increase in the number of competency examinations requested by courts for immigrant detainees. Furthermore, forensic evaluators must understand that an evaluation for competency of an immigrant detainee includes both the Dusky criteria and capacity for self-representation. In this article, we explore the legal context and ethics concerns related to the Franco litigation. PMID:26438803

  8. Infants' Joint Attention Skills Predict Toddlers' Emerging Mental State Language

    ERIC Educational Resources Information Center

    Kristen, Susanne; Sodian, Beate; Thoermer, Claudia; Perst, Hannah

    2011-01-01

    To assess predictive relations between joint attention skills, intention understanding, and mental state vocabulary, 88 children were tested with measures of comprehension of gaze and referential pointing, as well as the production of declarative gestures and the comprehension and production of imperative gestures, at the ages of 7-18 months.…

  9. 26 CFR 301.6361-2 - Judicial and administrative proceedings; Federal representation of State interests.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... involving the constitution of such State is unaffected by any provision of this paragraph; however, the... in a case involving the validity of a qualified tax statute under the State constitution, the State... State court involving the constitution of such State, to......

  10. 26 CFR 301.6361-2 - Judicial and administrative proceedings; Federal representation of State interests.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... involving the constitution of such State is unaffected by any provision of this paragraph; however, the... in a case involving the validity of a qualified tax statute under the State constitution, the State... State court involving the constitution of such State, to......

  11. 26 CFR 301.6361-2 - Judicial and administrative proceedings; Federal representation of State interests.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... involving the constitution of such State is unaffected by any provision of this paragraph; however, the... in a case involving the validity of a qualified tax statute under the State constitution, the State... State court involving the constitution of such State, to......

  12. 26 CFR 301.6361-2 - Judicial and administrative proceedings; Federal representation of State interests.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... involving the constitution of such State is unaffected by any provision of this paragraph; however, the... in a case involving the validity of a qualified tax statute under the State constitution, the State... State court involving the constitution of such State, to......

  13. Unacquainted callers can predict which citizens will vote over and above citizens' stated self-predictions.

    PubMed

    Rogers, Todd; Ten Brinke, Leanne; Carney, Dana R

    2016-06-01

    People are regularly asked to report on their likelihoods of carrying out consequential future behaviors, including complying with medical advice, completing educational assignments, and voting in upcoming elections. Despite these stated self-predictions being notoriously unreliable, they are used to inform many strategic decisions. We report two studies examining stated self-prediction about whether citizens will vote. We find that most self-predicted voters do not actually vote despite saying they will, and that campaign callers can discern which self-predicted voters will not actually vote. In study 1 (n = 4,463), self-predicted voters rated by callers as "100% likely to vote" were 2 times more likely to actually vote than those rated unlikely to vote. Study 2 (n = 3,064) replicated this finding and further demonstrated that callers' prediction accuracy was mediated by citizens' nonverbal signals of uncertainty and deception. Strangers can use nonverbal signals to improve predictions of follow through on self-reported intentions-an insight of potential value for politics, medicine, and education. PMID:27217566

  14. State of Jet Noise Prediction-NASA Perspective

    NASA Technical Reports Server (NTRS)

    Bridges, James E.

    2008-01-01

    This presentation covers work primarily done under the Airport Noise Technical Challenge portion of the Supersonics Project in the Fundamental Aeronautics Program. To provide motivation and context, the presentation starts with a brief overview of the Airport Noise Technical Challenge. It then covers the state of NASA s jet noise prediction tools in empirical, RANS-based, and time-resolved categories. The empirical tools, requires seconds to provide a prediction of noise spectral directivity with an accuracy of a few dB, but only for axisymmetric configurations. The RANS-based tools are able to discern the impact of three-dimensional features, but are currently deficient in predicting noise from heated jets and jets with high speed and require hours to produce their prediction. The time-resolved codes are capable of predicting resonances and other time-dependent phenomena, but are very immature, requiring months to deliver predictions without unknown accuracies and dependabilities. In toto, however, when one considers the progress being made it appears that aeroacoustic prediction tools are soon to approach the level of sophistication and accuracy of aerodynamic engineering tools.

  15. SEPARATE PERSONALITY TRAITS FROM STATES TO PREDICT DEPRESSION

    PubMed Central

    Vittengl, Jeffrey; Kraft, Dolores

    2005-01-01

    Results have been inconsistent regarding the ability of personality measures to predict future depression severity levels, leading some researchers to question the validity of personality assessment, especially when patients are acutely depressed. Using a combination of regression and factor analytic techniques, we separated the variance of personality measures into stable trait and variable state-affect components. Findings supported the hypotheses that depression severity measured at different time points would correlate with both stable trait and concurrent state-affect components in personality measures, whereas change in depression severity would correlate with state changes but not with stable trait scores. Thus, personality assessments tap both state affect and trait variance, with the state-affect variance masking the trait variance when patients are depressed. PMID:12755328

  16. Nonlinear Dependence of Global Warming Prediction on Ocean State

    NASA Astrophysics Data System (ADS)

    Liang, M.; Lin, L.; Tung, K. K.; Yung, Y. L.; Sun, S.

    2010-12-01

    Global temperature has increased by 0.8 C since the pre-industrial era, and is likely to increase further if greenhouse gas emission continues unchecked. Various mitigation efforts are being negotiated among nations to keep the increase under 2 C, beyond which the outcome is believed to be catastrophic. Such policy efforts are currently based on predictions by the state-of-the-art coupled atmosphere ocean models (AOGCM). Caution is advised for their use for the purpose of short-term (less than a century) climate prediction as the predicted warming and spatial patterns vary depending on the initial state of the ocean, even in an ensemble mean. The range of uncertainty in such predictions by Intergovernmental Panel on Climate Change (IPCC) models may be underreported when models were run with their oceans at various stages of adjustment with their atmospheres. By comparing a very long run (> 1000 years) of the coupled Goddard Institute for Space Studies (GISS) model with what was reported to IPCC Fourth Assessment Report (AR4), we show that the fully adjusted model transient climate sensitivity should be 30% higher for the same model, and the 2 C warming should occur sooner than previously predicted. Using model archives we further argue that this may be a common problem for the IPCC AR4 models, since few, if any, of the models has a fully adjusted ocean. For all models, multi-decadal climate predictions to 2050 are highly dependent on the initial ocean state (and so are unreliable). Such dependence cannot be removed simply by subtracting the climate drift from control runs.

  17. Perisaccadic Updating of Visual Representations and Attentional States: Linking Behavior and Neurophysiology

    PubMed Central

    Marino, Alexandria C.; Mazer, James A.

    2016-01-01

    During natural vision, saccadic eye movements lead to frequent retinal image changes that result in different neuronal subpopulations representing the same visual feature across fixations. Despite these potentially disruptive changes to the neural representation, our visual percept is remarkably stable. Visual receptive field remapping, characterized as an anticipatory shift in the position of a neuron’s spatial receptive field immediately before saccades, has been proposed as one possible neural substrate for visual stability. Many of the specific properties of remapping, e.g., the exact direction of remapping relative to the saccade vector and the precise mechanisms by which remapping could instantiate stability, remain a matter of debate. Recent studies have also shown that visual attention, like perception itself, can be sustained across saccades, suggesting that the attentional control system can also compensate for eye movements. Classical remapping could have an attentional component, or there could be a distinct attentional analog of visual remapping. At this time we do not yet fully understand how the stability of attentional representations relates to perisaccadic receptive field shifts. In this review, we develop a vocabulary for discussing perisaccadic shifts in receptive field location and perisaccadic shifts of attentional focus, review and synthesize behavioral and neurophysiological studies of perisaccadic perception and perisaccadic attention, and identify open questions that remain to be experimentally addressed. PMID:26903820

  18. Perisaccadic Updating of Visual Representations and Attentional States: Linking Behavior and Neurophysiology.

    PubMed

    Marino, Alexandria C; Mazer, James A

    2016-01-01

    During natural vision, saccadic eye movements lead to frequent retinal image changes that result in different neuronal subpopulations representing the same visual feature across fixations. Despite these potentially disruptive changes to the neural representation, our visual percept is remarkably stable. Visual receptive field remapping, characterized as an anticipatory shift in the position of a neuron's spatial receptive field immediately before saccades, has been proposed as one possible neural substrate for visual stability. Many of the specific properties of remapping, e.g., the exact direction of remapping relative to the saccade vector and the precise mechanisms by which remapping could instantiate stability, remain a matter of debate. Recent studies have also shown that visual attention, like perception itself, can be sustained across saccades, suggesting that the attentional control system can also compensate for eye movements. Classical remapping could have an attentional component, or there could be a distinct attentional analog of visual remapping. At this time we do not yet fully understand how the stability of attentional representations relates to perisaccadic receptive field shifts. In this review, we develop a vocabulary for discussing perisaccadic shifts in receptive field location and perisaccadic shifts of attentional focus, review and synthesize behavioral and neurophysiological studies of perisaccadic perception and perisaccadic attention, and identify open questions that remain to be experimentally addressed. PMID:26903820

  19. State public policy issues involved with the Parkfield prediction experiment.

    USGS Publications Warehouse

    Andrews, R.; Goltz, J.

    1988-01-01

    The earthquake-prediction experiment at Parkfield may well be the most important such experiment currently underway worldwide. Its importance, however, extends beyond the scientific data that will be gathered and whether those data that will be gathered and whether those data can provide reliable prediction methods. Important public policy lessons are being learned (and are yet to be learned), and these lessons may be transferable to other parts of California and the nation. Indeed, the Parkfield experiment has captured the interest of numerous Californians, including State officials, emergency managers, the news media, and at least some of the public.

  20. The Operational Hydro-meteorological Ensemble Prediction System at Meteo-France and its representation interface for the French Service for Flood Prediction (SCHAPI) : description and undergoing developments.

    NASA Astrophysics Data System (ADS)

    Rousset-Regimbeau, F.; Martin, E.; Thirel, G.; Habets, F.; Coustau, M.; Roquelaure, S.; De Saint Aubin, C.; Ardilouze, C.

    2012-04-01

    The coupled physically-based hydro-meteorological model SAFRAN-ISBA-MODCOU (SIM) is developed at Meteo-France for many years. This fully distributed catchment model is used in a pre-operational mode since 2005 for producing mid-range ensemble streamflow forecasts based on the 51-member 10-day ECMWF EPS. Improvements have been made during the past few years.. First, a statistical adaptation has been performed to improve the meteorological ensemble predictions from the ECMWF. It has been developped over a 3-year archive, and assessed over a 1-year period. Its impact on the performance of the streamflow forecasts has been calculated over 8 months of predictions. Then, a past discharges assimilation system has been implemented in order to improve the initial states of these ensemble streamflow forecasts. It has been developped in the framework of a Phd thesis, and it is now evaluated in real-time conditions. Moreover, an improvement of the physics of the ISBA model (the exponential profile of the hydraulic conductivity in the soil) was implemented. Finally, this system provides ensemble 10-day streamflow prediction to the French National Service for Flood Prediction (SCHAPI). A collaboration between Meteo-France and SCHAPI led to the development of a new website. This website shows the streamflow predictions for about 200 selected river stations over France (selected regarding their interest for flood warning) , as well as alerts for high flows (two levels of high flows corresponding to the levels of risk of the French flood warning system). It aims at providing to the French hydrological forecaters a real-time tool for mid-range flood awareness.

  1. Predicting outcome from subacute unresponsive wakefulness syndrome or vegetative state.

    PubMed

    Bodart, Olivier; Laureys, Steven

    2014-01-01

    Predicting recovery of consciousness in patients who survive their coma but evolve to a vegetative state (recently coined unresponsive wakefulness syndrome) remains a challenge. Most previous prognostic studies have focused on the acute coma phase. A novel outcome scale (combining behavioural, aetiology, electroencephalographic, sleep electroencephalographic and somatosensory evoked potential data) has been proposed for patients in subacute unresponsive wakefulness syndrome. The scale's clinical application awaits validation in a larger population. PMID:25029668

  2. Predicting outcome from subacute unresponsive wakefulness syndrome or vegetative state

    PubMed Central

    2014-01-01

    Predicting recovery of consciousness in patients who survive their coma but evolve to a vegetative state (recently coined unresponsive wakefulness syndrome) remains a challenge. Most previous prognostic studies have focused on the acute coma phase. A novel outcome scale (combining behavioural, aetiology, electroencephalographic, sleep electroencephalographic and somatosensory evoked potential data) has been proposed for patients in subacute unresponsive wakefulness syndrome. The scale’s clinical application awaits validation in a larger population. PMID:25029668

  3. Disproportionate Representation in Placements of Preschoolers with Disabilities in Five Southern States

    ERIC Educational Resources Information Center

    Morrier, Michael J.; Gallagher, Peggy A.

    2011-01-01

    Special education placements for more than 69,000 preschoolers with disabilities were examined within and across five southern states. Data were gathered from the 2007 December 1st Child Count reported to the U.S. Department of Education. All states examined offered state-funded prekindergarten programs. Analyses compared disproportionate…

  4. Representation, Classification and Information Fusion for Robust and Efficient Multimodal Human States Recognition

    ERIC Educational Resources Information Center

    Li, Ming

    2013-01-01

    The goal of this work is to enhance the robustness and efficiency of the multimodal human states recognition task. Human states recognition can be considered as a joint term for identifying/verifing various kinds of human related states, such as biometric identity, language spoken, age, gender, emotion, intoxication level, physical activity, vocal…

  5. Parallel Representation of Value-Based and Finite State-Based Strategies in the Ventral and Dorsal Striatum.

    PubMed

    Ito, Makoto; Doya, Kenji

    2015-11-01

    Previous theoretical studies of animal and human behavioral learning have focused on the dichotomy of the value-based strategy using action value functions to predict rewards and the model-based strategy using internal models to predict environmental states. However, animals and humans often take simple procedural behaviors, such as the "win-stay, lose-switch" strategy without explicit prediction of rewards or states. Here we consider another strategy, the finite state-based strategy, in which a subject selects an action depending on its discrete internal state and updates the state depending on the action chosen and the reward outcome. By analyzing choice behavior of rats in a free-choice task, we found that the finite state-based strategy fitted their behavioral choices more accurately than value-based and model-based strategies did. When fitted models were run autonomously with the same task, only the finite state-based strategy could reproduce the key feature of choice sequences. Analyses of neural activity recorded from the dorsolateral striatum (DLS), the dorsomedial striatum (DMS), and the ventral striatum (VS) identified significant fractions of neurons in all three subareas for which activities were correlated with individual states of the finite state-based strategy. The signal of internal states at the time of choice was found in DMS, and for clusters of states was found in VS. In addition, action values and state values of the value-based strategy were encoded in DMS and VS, respectively. These results suggest that both the value-based strategy and the finite state-based strategy are implemented in the striatum. PMID:26529522

  6. Women's Political Representation and Welfare State Spending in 12 Capitalist Democracies

    ERIC Educational Resources Information Center

    Bolzendahl, Catherine; Brooks, Clem

    2007-01-01

    One of the sharpest criticisms of welfare state research is insufficient attention to factors relating to gender relations and inequalities. Recent scholarship has begun to address welfare state effects on gender-related outcomes, but the evaluation of theories of welfare development with respect to gender factors is somewhat less developed,…

  7. 77 FR 64189 - Changes to Representation of Others Before the United States Patent and Trademark Office

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-10-18

    ... 50 FR 5158 (February 6, 1985). Since that time, the vast majority of State bars in the United States... investigations in 2008. See 73 FR 47650 (August 14, 2008). Experience under these rules has demonstrated areas in... Rulemaking, Setting and Adjusting Patent Fees, 77 FR 55028, 55082, proposing to adjust the...

  8. Legislative Agenda Setting for In-State Resident Tuition Policies: Immigration, Representation, and Educational Access

    ERIC Educational Resources Information Center

    McLendon, Michael K.; Mokher, Christine G.; Flores, Stella M.

    2011-01-01

    Few recent issues in higher education have been as contentious as that of legislation extending in-state college tuition benefits to undocumented students, initiatives now known as in-state resident tuition (ISRT) policies. Building on several strands of literature in political science and higher education studies, we analyze the effects of…

  9. Dimensionless Equation of State to Predict Microemulsion Phase Behavior.

    PubMed

    Ghosh, Soumyadeep; Johns, Russell T

    2016-09-01

    Prediction of microemulsion phase behavior for changing state variables is critical to formulation design of surfactant-oil-brine (SOB) systems. SOB systems find applications in various chemical and petroleum processes, including enhanced oil recovery. A dimensional equation-of-state (EoS) was recently presented by Ghosh and Johns1 that relied on estimation of the surfactant tail length and surface area. We give an algorithm for flash calculations for estimation of three-phase Winsor regions that is more robust, simpler, and noniterative by making the equations dimensionless so that estimates of tail length and surface area are no longer needed. We predict phase behavior as a function temperature, pressure, volume, salinity, oil type, oil-water ratio, and surfactant/alcohol concentration. The dimensionless EoS is based on coupling the HLD-NAC (Hydrophilic Lipophilic Difference-Net Average Curvature) equations with new relationships between optimum salinity and solubility. An updated HLD expression that includes pressure is also used to complete the state description. A significant advantage of the dimensionless form of the EoS over the dimensional version is that salinity scans are tuned based only on one parameter, the interfacial volume ratio. Further, stability conditions are developed in a simplified way to predict whether an overall compositions lies within the single, two-, or three-phase regions. Important new microemulsion relationships are also found, the most important of which is that optimum solubilization ratio is equal to the harmonic mean of the oil and water solubilization ratios in the type III region. Thus, only one experimental measurement is needed in the three-phase zone to estimate the optimum solubilization ratio, a result which can aid experimental design and improve estimates of optimum from noisy data. Predictions with changing state variables are illustrated by comparison to experimental data using standard diagrams including a new type

  10. Constraints of artificial neural networks for rainfall-runoff modelling: trade-offs in hydrological state representation and model evaluation

    NASA Astrophysics Data System (ADS)

    de Vos, N. J.; Rientjes, T. H. M.

    2005-02-01

    The application of Artificial Neural Networks (ANNs) on rainfall-runoff modelling needs to be researched more extensively in order to appreciate and fulfil the potential of this modelling approach. This paper reports on the application of multi-layer feedforward ANNs for rainfall-runoff modelling in the Geer catchment (Belgium) using both daily and hourly data. The good daily forecast results indicate that ANNs can be considered alternatives for traditional rainfall-runoff modelling approaches. However, investigation of the forecasts based on hourly data reveal a constraint that has hitherto been neglected by hydrologists. A timing error occurs due to a dominating autoregressive component that is introduced by using previous runoff values as ANN model input. The reason for the popular practice of using these previous runoff data is that this information indirectly represents the hydrological state of the catchment. Two possible solutions to this timing problem are discussed. Firstly, several alternatives for representation of the hydrological state are presented: moving averages over the previous discharge and over the previous rainfall, and the output of the simple GR4J model component for soil moisture. A combination of these various hydrological state representators produces good results in terms of timing, but the overall goodness of fit is not as good as the simulations with previous runoff data. Secondly, the use of a combination of multiple measures of model performance during ANN training is suggested, since not all differences between modelled and observed hydrograph characteristics such as timing, volume, and absolute values can be adequately expressed by a single performance measure. The possible undervaluation of timing errors by the commonly-used squared-error-based functions is a clear example of this inability.

  11. Constrained model predictive control, state estimation and coordination

    NASA Astrophysics Data System (ADS)

    Yan, Jun

    In this dissertation, we study the interaction between the control performance and the quality of the state estimation in a constrained Model Predictive Control (MPC) framework for systems with stochastic disturbances. This consists of three parts: (i) the development of a constrained MPC formulation that adapts to the quality of the state estimation via constraints; (ii) the application of such a control law in a multi-vehicle formation coordinated control problem in which each vehicle operates subject to a no-collision constraint posed by others' imperfect prediction computed from finite bit-rate, communicated data; (iii) the design of the predictors and the communication resource assignment problem that satisfy the performance requirement from Part (ii). Model Predictive Control (MPC) is of interest because it is one of the few control design methods which preserves standard design variables and yet handles constraints. MPC is normally posed as a full-state feedback control and is implemented in a certainty-equivalence fashion with best estimates of the states being used in place of the exact state. However, if the state constraints were handled in the same certainty-equivalence fashion, the resulting control law could drive the real state to violate the constraints frequently. Part (i) focuses on exploring the inclusion of state estimates into the constraints. It does this by applying constrained MPC to a system with stochastic disturbances. The stochastic nature of the problem requires re-posing the constraints in a probabilistic form. In Part (ii), we consider applying constrained MPC as a local control law in a coordinated control problem of a group of distributed autonomous systems. Interactions between the systems are captured via constraints. First, we inspect the application of constrained MPC to a completely deterministic case. Formation stability theorems are derived for the subsystems and conditions on the local constraint set are derived in order to

  12. Digital representation of the Washington state geologic map: a contribution to the Interior Columbia River Basin Ecosystem Management Project

    USGS Publications Warehouse

    Raines, Gary L.; Johnson, Bruce R.

    1996-01-01

    This report describes the digital representation of the Washington state geologic map (Hunting and others, 1961). This report contains an explantion of why the data were prepared, a description of the digital data, and information on obtaining the digital files. This report is one in a series of digital maps, data files, and reports generated by the U.S. Geological Survey to provide geologic process and mineral resource information to the Interior Columbia Basin Ecosystem Management Project (ICBEMP). The various digital maps and data files are being used in a geographic information system (GIS)-based ecosystem assessment including an analysis of diverse questions relating to past, present, and future conditions within the general area of the Columbia River Basin east of the Cascade Mountains.

  13. Pure-state noninteracting v-representability of electron densities from Kohn-Sham calculations with finite basis sets

    NASA Astrophysics Data System (ADS)

    de Silva, Piotr; Wesolowski, Tomasz A.

    2012-03-01

    Within the linear combination of atomic orbitals (LCAO) approximation, one can distinguish two different Kohn-Sham potentials. One is the potential available numerically in calculations, and the other is the exact potential corresponding to the LCAO density. The latter is usually not available, but can be obtained from the total density by a numerical inversion procedure or, as is done here, analytically using only one LCAO Kohn-Sham orbital. In the complete basis-set limit, the lowest-lying Kohn-Sham orbital suffices to perform the analytical inversion, and the two potentials differ by no more than a constant. The relation between these two potentials is investigated here for diatomic molecules and several atomic basis sets of increasing size and quality. The differences between the two potentials are usually qualitative (wrong behavior at nuclear cusps and far from the molecule even if Slater-type orbitals are used) and δ-like features at nodal planes of the lowest-lying LCAO Kohn-Sham orbital. Such nodes occur frequently in LCAO calculations and are not physical. Whereas the behavior of the potential can be systematically improved locally by the increase of the basis sets, the occurrence of nodes is not correlated with the size of the basis set. The presence of nodes in the lowest-lying LCAO orbital can be used to monitor whether the effective potential in LCAO Kohn-Sham equations can be interpreted as the potential needed for pure-state noninteracting v-representability of the LCAO density. Squares of such node-containing lowest-lying LCAO Kohn-Sham orbitals are nontrivial examples of two-electron densities which are not pure-state noninteracting v-representable.

  14. Ethnic Labels, Latino Lives. Identity and the Politics of (Re)Presentation in the United States.

    ERIC Educational Resources Information Center

    Oboler, Suzanne

    The history and current use of the label "Hispanic" are discussed in this exploration of the myth of cultural and national homogeneity among people of Latin American descent in the United States. The historical process of labeling groups of individuals is discussed, and how ethnic labels affect the meaning of citizenship and the struggle for full…

  15. Conal representation of quantum states and non-trace-preserving quantum operations

    SciTech Connect

    Arrighi, Pablo; Patricot, Christophe

    2003-10-01

    We represent generalized density matrices of a d-complex dimensional quantum system as a subcone of a real pointed cone of revolution in R{sup d{sup 2}}, or indeed a Minkowskian cone in E{sup 1,d{sup 2}-1}. Generalized pure states correspond to certain future-directed lightlike vectors of E{sup 1,d{sup 2}-1}. This extension of the generalized Bloch sphere enables us to cater for non-trace-preserving quantum operations, and in particular to view the per-outcome effects of generalized measurements. We show that these consist of the product of an orthogonal transform about the axis of the cone of revolution and a positive real linear transform. We give detailed formulas for the one-qubit case and express the post-measurement states in terms of the initial-state vectors and measurement vectors. We apply these results in order to find the information gain versus disturbance trade-off in the case of two equiprobable pure states. Thus we recover Fuchs and Peres's formula in an elegant manner.

  16. 78 FR 20179 - Changes to Representation of Others Before The United States Patent and Trademark Office

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-04-03

    ... Professional Responsibility. See 50 FR 5158 (Feb. 6, 1985). Since that time, the vast majority of State bars in... Trademark Office, a Notice of Proposed Rulemaking in the Federal Register (77 FR 64190) proposing the new... investigations in 2008. See 73 FR 47650 (Aug. 14, 2008). Experience under these rules has demonstrated areas...

  17. Validation of Atmospheric Dynamics (VADY) - representation of circulation types/dynamical modes in the decadal-prediction model system of MPI-ESM

    NASA Astrophysics Data System (ADS)

    Lang, Benjamin; Jacobeit, Jucundus; Beck, Christoph; Philipp, Andreas

    2016-04-01

    The climate research program "Medium-range Climate Predictions" (MiKlip), funded by the Federal Ministry of Education and Research in Germany (BMBF), has the aim to improve a climate model system (MPI-ESM) in such a way that it can provide reliable decadal predictions of climate, including extreme weather events. A substantial part of the development process is a comprehensive model validation. Within MiKlip, it includes comparisons of model simulations and observations in order to allow statements about the performance of the model and to give particular recommendations for the further development of the model. The research project "Validation of Atmospheric Dynamics" (VADY), conducted by the cooperation partners "Institute of Geography at the University of Augsburg" (IGUA) and the "German Aerospace Centre" (DLR), contributes to model validation within MiKlip with a special focus on atmospheric waves (DLR) and circulation dynamics (IGUA). Within the framework of VADY, DLR validates the representation of atmospheric waves on different levels and scales based on suitable activity indices (e.g. the so-called large-scale dynamical activity index (LDAI), which is a measure for the activity of planetary waves). The focus of IGUA is on the model validation with respect to the representation of atmospheric circulation types, dynamical modes and the teleconnectivity of the atmospheric circulation. The present contribution provides results of the model validation concerning circulation types/dynamical modes. Results are shown for both the frequency of occurrence and internal characteristics (e. g. persistence or intensity), and for different classification methods (e. g. based on PCA or clustering techniques). The representation of circulation types/dynamical modes will be compared for different generations of the MPI-ESM decadal-prediction model (baseline0, baseline1, prototype) in order to clarify both advances and limitations in the development of the model. Furthermore

  18. Neural network programming in bioprocess variable estimation and state prediction.

    PubMed

    Linko, P; Zhu, Y H

    1991-12-01

    A neural network program with efficient learning ability for bioprocess variable estimation and state prediction was developed. A 3 layer, feed-forward neural network architecture was used, and the program was written in Quick C ver 2.5 for an IBM compatible computer with a 80486/33 MHz processor. A back propagation training algorithm was used based on learning by pattern and momentum in a combination as used to adjust the connection of weights of the neurons in adjacent layers. The delta rule was applied in a gradient descent search technique to minimize a cost function equal to the mean square difference between the target and the network output. A non-linear, sigmoidal logistic transfer function was used in squashing the weighted sum of the inputs of each neuron to a limited range output. A good neural network prediction model was obtained by training with a sequence of past time course data of a typical bioprocess. The well trained neural network estimated accurately and rapidly the state variables with or without noise even under varying process dynamics. PMID:1367695

  19. Predicting brain states associated with object categories from fMRI data.

    PubMed

    Behroozi, Mehdi; Daliri, Mohammad Reza

    2014-12-01

    Recently, the multivariate analysis methods have been widely used for predicting the human cognitive states from fMRI data. Here, we explore the possibility of predicting the human cognitive states using a pattern of brain activities associated with thinking about concrete objects. The fMRI signals in conjunction with pattern recognition methods were used for the analysis of cognitive functions associated with viewing of 60 object pictures named by the words in 12 categories. The important step in Multi Voxel Pattern Analysis (MVPA) is feature extraction and feature selection parts. In this study, the new feature selection method (accuracy method) was developed for multi-class fMRI dataset to select the informative voxels corresponding to the objects category from the whole brain voxels. Here the result of three multivariate classifiers namely, Naïve Bayes, K-nearest neighbor and support vector machine, were compared for predicting the category of presented objects from activation BOLD patterns in human whole brain. We investigated whether the multivariate classifiers are capable to find the associated regions of the brain with the visual presentation of categories of various objects. Overall Naïve Bayes classifier perfumed best and it was the best method for extracting features from the whole brain data. In addition, the results of this study indicate that thinking about different semantic categories of objects have an effect on different spatial patterns of neural activation, and so it is possible to identify the category of the objects based on the patterns of neural activation recorded during representation of object line drawing from participants with high accuracy. Finally we demonstrated that the selected brain regions that were informative for object categorization were similar across subjects and this distribution of selected voxels on the cortex may neutrally represent the various object's category properties. PMID:25352153

  20. A state-space dynamical representation for multibody mechanical systems. II - Systems with closed loops

    NASA Astrophysics Data System (ADS)

    Schwertassek, R.; Roberson, R. E.

    1984-05-01

    The dynamical equations of motion of a multibody system are reduced to state-space equations in the computer-oriented multibody formalism of Roberson and Wittenberg (1966), extending the analysis of Schwertassek and Roberson (1983) to systems with closed loops. The multibody spacecraft model of Kane and Levinson (1980) and Schiehlen and Kreuzer (1977) is analyzed as an example. The closed-loop equations permit the use of the MULTIBODY computer code (Schwertassek, 1978) to treat such more general systems.

  1. Representation of the Heisenberg Algebra h4 by the Lowest Landau Levels and Their Coherent States

    NASA Astrophysics Data System (ADS)

    Fakhri, H.; Shadman, Z.

    Using simultaneous shape invariance with respect to two different parameters, we introduce a pair of appropriate operators which realize shape invariance symmetry for the monomials on a half-axis. It leads to the derivation of rotational symmetry and dynamical symmetry group H4 with infinite-fold degeneracy for the lowest Landau levels. This allows us to represent the Heisenberg-Lie algebra h4 not only by the lowest Landau levels, but also by their corresponding standard coherent states.

  2. Basolateral amygdala rapid glutamate release encodes an outcome-specific representation vital for reward-predictive cues to selectively invigorate reward-seeking actions

    PubMed Central

    Malvaez, Melissa; Greenfield, Venuz Y.; Wang, Alice S.; Yorita, Allison M.; Feng, Lili; Linker, Kay E.; Monbouquette, Harold G.; Wassum, Kate M.

    2015-01-01

    Environmental stimuli have the ability to generate specific representations of the rewards they predict and in so doing alter the selection and performance of reward-seeking actions. The basolateral amygdala participates in this process, but precisely how is unknown. To rectify this, we monitored, in near-real time, basolateral amygdala glutamate concentration changes during a test of the ability of reward-predictive cues to influence reward-seeking actions (Pavlovian-instrumental transfer). Glutamate concentration was found to be transiently elevated around instrumental reward seeking. During the Pavlovian-instrumental transfer test these glutamate transients were time-locked to and correlated with only those actions invigorated by outcome-specific motivational information provided by the reward-predictive stimulus (i.e., actions earning the same specific outcome as predicted by the presented CS). In addition, basolateral amygdala AMPA, but not NMDA glutamate receptor inactivation abolished the selective excitatory influence of reward-predictive cues over reward seeking. These data the hypothesis that transient glutamate release in the BLA can encode the outcome-specific motivational information provided by reward-predictive stimuli. PMID:26212790

  3. A qualia representation of cyberspace

    NASA Astrophysics Data System (ADS)

    Lacey, Timothy H.; Mills, Robert F.; Raines, Richard A.; Oxley, Mark E.; Bauer, Kenneth W.; Rogers, Steven K.

    2008-04-01

    E.C Adam defined Situational Awareness (SA) as "the mental representation and understanding of objects, events, people, system states, interactions, environmental conditions, and other situation-specific factors affecting human performance in complex and dynamic tasks. Stated in lay terms, SA is simply knowing what is going on so you can figure out what to do." We propose a novel idea to assist the human in gaining SA. Our hypothesis is that nature uses qualia as a compression scheme to represent the many concepts encountered in everyday life. Qualia enable humans to quickly come up with SA based on many complex measurements from their sensors, (eyes, ears, taste, touch, memory, etc.), expectations, and experiences. Our ultimate objective is to develop a computer that uses qualia concepts to transform sensor data to assist the human in gaining and maintaining improved SA. However, before any computer can use qualia, we must first define a representation for qualia that can be implemented computationally. This paper will present our representation for qualia. The representation is not simply a hierarchical aggregation of input data. Instead, it is a prediction of what will happen next, derived from computations resulting from sensory inputs and the computational engine of a qualia generator and qualia processor.

  4. Cluster-based representation of hydraulic systems. [stable (closed valve) and unstable (open valve) states

    NASA Technical Reports Server (NTRS)

    Farley, Arthur M.

    1988-01-01

    The authors present a technique for structural abstraction applicable to the domain of pressurized hydraulic systems. Valves, when closed, functionally isolate clusters of components; when opened, neighboring clusters are merged. A cluster can only be in the one of two qualitative states-stable, where pressures are equal throughout and no flow occurs, or unstable, where flow from high-pressure source(s) to low-pressure sink(s) occurs. Reasoning in terms of clusters is shown to facilitate the generation and explanation of plans for operating and troubleshooting hydraulic systems.

  5. Characterizing and differentiating task-based and resting state fMRI signals via two-stage sparse representations.

    PubMed

    Zhang, Shu; Li, Xiang; Lv, Jinglei; Jiang, Xi; Guo, Lei; Liu, Tianming

    2016-03-01

    A relatively underexplored question in fMRI is whether there are intrinsic differences in terms of signal composition patterns that can effectively characterize and differentiate task-based or resting state fMRI (tfMRI or rsfMRI) signals. In this paper, we propose a novel two-stage sparse representation framework to examine the fundamental difference between tfMRI and rsfMRI signals. Specifically, in the first stage, the whole-brain tfMRI or rsfMRI signals of each subject were composed into a big data matrix, which was then factorized into a subject-specific dictionary matrix and a weight coefficient matrix for sparse representation. In the second stage, all of the dictionary matrices from both tfMRI/rsfMRI data across multiple subjects were composed into another big data-matrix, which was further sparsely represented by a cross-subjects common dictionary and a weight matrix. This framework has been applied on the recently publicly released Human Connectome Project (HCP) fMRI data and experimental results revealed that there are distinctive and descriptive atoms in the cross-subjects common dictionary that can effectively characterize and differentiate tfMRI and rsfMRI signals, achieving 100% classification accuracy. Moreover, our methods and results can be meaningfully interpreted, e.g., the well-known default mode network (DMN) activities can be recovered from the very noisy and heterogeneous aggregated big-data of tfMRI and rsfMRI signals across all subjects in HCP Q1 release. PMID:25732072

  6. Low dimensional state-space representations for classical unsteady aerodynamic models

    NASA Astrophysics Data System (ADS)

    Brunton, Steven L.; Rowley, Clarence W.

    2010-11-01

    This work develops reduced order models for the unsteady aerodynamic forces on a small wing in response to agile maneuvers and gusts. In particular, the classical unsteady models of Wagner and Theodorsen are cast into a low-dimensional state-space framework. Low order state-space models are more computationally efficient than the classical formulations, and are well suited for modification with nonlinear dynamics and the application of control techniques. Reduced order models are obtained using the eigensystem realization algorithm on force data from the direct numerical simulation (DNS) of a pitching or plunging 2D flat plate at Reynolds numbers between 100 and 1000. Models are tested on rapid pitch and plunge maneuvers with a range of effective angle-of-attack. We evaluate the performance of the models based on agreement with results from DNS, in particular, the ability to reproduce lift forces over a range of pitching and plunging frequencies. Bode plots of the reduced order models, Wagner's and Theodorsen's methods, and DNS provide a concise assessment.

  7. Sulfur Mass Balances of Forested Catchments: Improving Predictions of Stream Sulfate Concentrations Through Better Representation of Soil Storage and Release

    NASA Astrophysics Data System (ADS)

    Scanlon, T. M.; Rice, K. C.; Riscassi, A.; Cosby, B. J., Jr.

    2015-12-01

    Sulfur dioxide (SO2) emissions in the eastern United States have declined by more than 80% since 1970, when the Clean Air Act first established limits on emissions from stationary and mobile sources. In many areas throughout the northeastern U.S., the resulting declines in sulfate (SO42-) deposition have been accompanied by declines in stream SO42- concentrations. In the southeastern U.S., however, declines in stream SO42- concentrations have not been observed on a widespread basis. In fact, SO42- concentrations continue to increase in many southeastern streams despite decades of declining deposition. This difference in behavior between northeastern and southeastern streams, owing to the distinct geological histories of their catchment soils, was anticipated by the Direct/Delayed Response Project initiated by the U.S. EPA during the early 1980s. At that time, understanding of how catchments store and release SO42- was mostly grounded in theory. Now, with the accumulation of long-term stream chemistry and hydrological datasets in forested catchments, we may develop an empirical basis for characterizing catchment storage and release of SO42-. In particular, are whole-catchment isotherms that described the partitioning between adsorbed and dissolved SO42- (1) linear or non-linear and (2) reversible or irreversible? How do these isotherms vary on a geographical basis? We apply mass balance combined with a simple theoretical framework to infer whole-catchment SO42- isotherms in Virginia and New England. Knowledge of this key soil geochemical property is needed to improve predictions of how catchments will store and export SO42- under changing levels of atmospheric deposition.

  8. Discontinuous steady-state analytical solutions of the Boussinesq equation and their numerical representation by MODFLOW.

    PubMed

    Zaidel, Jacob

    2013-01-01

    Known analytical solutions of groundwater flow equations are routinely used for verification of computer codes. However, these analytical solutions (e.g., the Dupuit solution for the steady-state unconfined unidirectional flow in a uniform aquifer with a flat bottom) represent smooth and continuous water table configurations, simulating which does not pose any significant problems for the numerical groundwater flow models, like MODFLOW. One of the most challenging numerical cases for MODFLOW arises from drying-rewetting problems often associated with abrupt changes in the elevations of impervious base of a thin unconfined aquifer. Numerical solutions of groundwater flow equations cannot be rigorously verified for such cases due to the lack of corresponding exact analytical solutions. Analytical solutions of the steady-state Boussinesq equation, associated with the discontinuous water table configurations over a stairway impervious base, are presented in this article. Conditions resulting in such configurations are analyzed and discussed. These solutions appear to be well suited for testing and verification of computer codes. Numerical solutions, obtained by the latest versions of MODFLOW (MODFLOW-2005 and MODFLOW-NWT), are compared with the presented discontinuous analytical solutions. It is shown that standard MODFLOW-2005 code (as well as MODFLOW-2000 and older versions) has significant convergence problems simulating such cases. The problems manifest themselves either in a total convergence failure or erroneous results. Alternatively, MODFLOW-NWT, providing a good match to the presented discontinuous analytical solutions, appears to be a more reliable and appropriate code for simulating abrupt changes in water table elevations. PMID:23387826

  9. Control and Transfer of Entanglement between Two Atoms Driven by Classical Fields under Dressed-State Representation

    NASA Astrophysics Data System (ADS)

    Liao, Qing-Hong; Zhang, Qi; Xu, Juan; Yan, Qiu-Rong; Liu, Ye; Chen, An

    2016-06-01

    We have studied the dynamics and transfer of the entanglement of the two identical atoms simultaneously interacting with vacuum field by employing the dressed-state representation. The two atoms are driven by classical fields. The influence of the initial entanglement degree of two atoms, the coupling strength between the atom and the classical field and the detuning between the atomic transition frequency and the frequency of classical field on the entanglement and atomic linear entropy is discussed. The initial entanglement of the two atoms can be transferred into the entanglement between the atom and cavity field when the dissipation is neglected. The maximally entangled state between the atoms and cavity field can be obtained under some certain conditions. The time of disentanglement of two atoms can be controlled and manipulated by adjusting the detuning and classical driving fields. Moreover, the larger the cavity decay rate is, the more quickly the entanglement of the two atoms decays. Supported by National Natural Science Foundation of China under Grant Nos. 11247213, 61368002, 11304010, 11264030, 61168001, China Postdoctoral Science Foundation under Grant No. 2013M531558, Jiangxi Postdoctoral Research Project under Grant No. 2013KY33, the Natural Science Foundation of Jiangxi Province under Grant No. 20142BAB217001, the Foundation for Young Scientists of Jiangxi Province (Jinggang Star) under Grant No. 20122BCB23002, the Research Foundation of the Education Department of Jiangxi Province under Grant Nos. GJJ13051, GJJ13057, and the Graduate Innovation Special Fund of Nanchang University under Grant No. cx2015137

  10. Predicting ion charge state distributions of vacuum arc plasmas

    SciTech Connect

    Anders, A.; Schulke, T.

    1996-04-01

    Multiply charged ions are present in vacuum arc plasmas. The ions are produced at cathode spots, and their charge state distributions (CSDs) depend on the cathode material but only little on the arc current or other parameters as long as the current is relatively low and the anode is not actively involved in the plasma production. There are experimental data of ion CSDs available in the literature for 50 different cathode materials. The CSDs can be calculated based on the assumption that thermodynamic equilibrium is valid in the vicinity of the cathode spot, and the equilibrium CSDs `freeze` at a certain distance from the cathode spot (transition to a non-equilibrium plasma). Plasma temperatures and densities at the `freezing points` have been calculated, and, based on the existence of characteristic groups of elements in the Periodic Table, predictions of CSDs can be made for metallic elements which have not yet been used as cathode materials.

  11. Sensitivity of global model prediction to initial state uncertainty

    NASA Astrophysics Data System (ADS)

    Miguez-Macho, Gonzalo

    The sensitivity of global and North American forecasts to uncertainties in the initial conditions is studied. The Utah Global Model is initialized with reanalysis data sets obtained from the National Centers for Environmental Prediction (NCEP) and the European Centre for Medium- Range Weather Forecasts (ECMWF). The differences between these analyses provide an estimate of initial uncertainty. The influence of certain scales of the initial uncertainty is tested in experiments with initial data change from NCEP to ECMWF reanalysis in a selected spectral band. Experiments are also done to determine the benefits of targeting local regions for forecast errors over North America. In these tests, NCEP initial data are replaced by ECMWF data in the considered region. The accuracy of predictions with initial data from either reanalysis only differs over the mid-latitudes of the Southern Hemisphere, where ECMWF initialized forecasts have somewhat greater skill. Results from the spectral experiments indicate that most of this benefit is explained by initial differences of the longwave components (wavenumbers 0-15). Approximately 67% of the 120-h global forecast difference produced by changing initial data from ECMWF to NCEP reanalyses is due to initial changes only in wavenumbers 0-15, and more than 85% of this difference is produced by initial changes in wavenumbers 0-20. The results suggest that large-scale errors of the initial state may play a more prominent role than suggested in some singular vector analyses, and favor global observational coverage to resolve the long waves. Results from the regional targeting experiments indicate that for forecast errors over North America, a systematic benefit comes only when the ``targeted'' region includes most of the north Pacific, pointing again at large scale errors as being prominent, even for midrange predictions over a local area.

  12. Representation of Type 4 wind turbine generator for steady state short-circuit calculations

    NASA Astrophysics Data System (ADS)

    Kamara, Wouleye

    Various technical impacts are associated to the interconnection of wind turbine generators to the grid. Among them, the increase of short-circuit levels along with its effect on the settings of protecting relays has long acted as an important inhibiting factor for the interconnection of new wind power plants to the grid. This is especially true at the medium voltage level where networks operate close to their short-circuit design value [1]. As renewable energies are progressively replacing traditional power generation sources, short-circuit studies need to adequately assess the impact of newly interconnected wind power plants on the fault level of the network. For planning and design purposes, short-circuit studies are usually performed using steady-state short-circuit programs. Unfortunately, very few have developed models of wind turbine generators that accurately estimate their fault contribution in the phase domain. In particular, no commercial fault-flow analysis program specifically addresses the modeling of inverter-based wind turbine generators which behavior is based on the inverter's characteristics rather than the generator's. The main contribution of this research work is the development of a simplified and yet accurate model of full-scale converter based wind turbine generator, also called Type 4 wind turbine generator, for steady-state short-circuit calculations. The model reproduces the real behavior of the Type 4 wind turbine generator under fault conditions by correctly accounting for the effect of the full-scale converter. The data used for the model is easily accessible to planning engineers. An additional contribution of this research work is the development of a short-circuit algorithm adapted to support the proposed model of Type 4 wind-turbine generator. Short-circuit algorithm based on modified-augmented-nodal analysis (MANA) is solved iteratively to accommodate the proposed model. The algorithm is successfully implemented in CYME 7.0, a

  13. Why Representations?

    ERIC Educational Resources Information Center

    Schultz, James E.; Waters, Michael S.

    2000-01-01

    Discusses representations in the context of solving a system of linear equations. Views representations (concrete, tables, graphs, algebraic, matrices) from perspectives of understanding, technology, generalization, exact versus approximate solution, and learning style. (KHR)

  14. Manipulating Representations.

    PubMed

    Recchia-Luciani, Angelo N M

    2012-04-01

    The present paper proposes a definition for the complex polysemic concepts of consciousness and awareness (in humans as well as in other species), and puts forward the idea of a progressive ontological development of consciousness from a state of 'childhood' awareness, in order to explain that humans are not only able to manipulate objects, but also their mental representations. The paper builds on the idea of qualia intended as entities posing regular invariant requests to neural processes, trough the permanence of different properties. The concept of semantic differential introduces the properties of metaphorical qualia as an exclusively human ability. Furthermore this paper proposes a classification of qualia, according to the models-with different levels of abstraction-they are implied in, in a taxonomic perspective. This, in turn, becomes a source of categorization of divergent representations, sign systems, and forms of intentionality, relying always on biological criteria. New emerging image-of-the-world-devices are proposed, whose qualia are likely to be only accessible to humans: emotional qualia, where emotion accounts for the invariant and dominant property; and the qualic self where continuity, combined with the oneness of the self, accounts for the invariant and dominant property. The concept of congruence between different domains in a metaphor introduces the possibility of a general evaluation of truth and falsity of all kinds of metaphorical constructs, while the work of Matte Blanco enables us to classify conscious versus unconscious metaphors, both in individuals and in social organizations. PMID:22347988

  15. Hidden state prediction: a modification of classic ancestral state reconstruction algorithms helps unravel complex symbioses

    PubMed Central

    Zaneveld, Jesse R. R.; Thurber, Rebecca L. V.

    2014-01-01

    Complex symbioses between animal or plant hosts and their associated microbiotas can involve thousands of species and millions of genes. Because of the number of interacting partners, it is often impractical to study all organisms or genes in these host-microbe symbioses individually. Yet new phylogenetic predictive methods can use the wealth of accumulated data on diverse model organisms to make inferences into the properties of less well-studied species and gene families. Predictive functional profiling methods use evolutionary models based on the properties of studied relatives to put bounds on the likely characteristics of an organism or gene that has not yet been studied in detail. These techniques have been applied to predict diverse features of host-associated microbial communities ranging from the enzymatic function of uncharacterized genes to the gene content of uncultured microorganisms. We consider these phylogenetically informed predictive techniques from disparate fields as examples of a general class of algorithms for Hidden State Prediction (HSP), and argue that HSP methods have broad value in predicting organismal traits in a variety of contexts, including the study of complex host-microbe symbioses. PMID:25202302

  16. The Representation of Other Cultures in Award-Winning Picture Books from the United States, Australia, and Great Britain (1960-2009)

    ERIC Educational Resources Information Center

    Hall, Virginia

    2011-01-01

    The purpose of this study was to investigate the representation of other cultures in award-winning picture books from the United States, Australia, and Great Britain between 1960 and 2009. Not only was the cultural content of children's literature over the past fifty years investigated, but the protocol created to evaluate the books was a newly…

  17. High Stakes Principalship--Sleepless Nights, Heart Attacks and Sudden Death Accountabilities: Reading Media Representations of the United States Principal Shortage.

    ERIC Educational Resources Information Center

    Thomson, Pat; Blackmore, Jill; Sachs, Judyth; Tregenza, Karen

    2003-01-01

    Subjects a corpus of predominantly United States news articles to deconstructive narrative analysis and finds that the dominant media representation of principals' work is one of long hours, low salary, high stress, and sudden death from high stakes accountabilities. Notes that the media picture may perpetuate the problem, and that it is at odds…

  18. Slavery, the Civil War Era, and African American Representation in U.S. History: An Analysis of Four States' Academic Standards

    ERIC Educational Resources Information Center

    Anderson, Carl B.; Metzger, Scott Alan

    2011-01-01

    This study is a mixed-methods text analysis of African American representation within K-12 U.S. History content standards treating the revolutionary era, the early U.S. republic, the Civil War era, and Reconstruction. The states included in the analysis are Michigan, New Jersey, South Carolina, and Virginia. The analysis finds that the reviewed…

  19. Non-parametric representation and prediction of single- and multi-shell diffusion-weighted MRI data using Gaussian processes

    PubMed Central

    Andersson, Jesper L.R.; Sotiropoulos, Stamatios N.

    2015-01-01

    Diffusion MRI offers great potential in studying the human brain microstructure and connectivity. However, diffusion images are marred by technical problems, such as image distortions and spurious signal loss. Correcting for these problems is non-trivial and relies on having a mechanism that predicts what to expect. In this paper we describe a novel way to represent and make predictions about diffusion MRI data. It is based on a Gaussian process on one or several spheres similar to the Geostatistical method of “Kriging”. We present a choice of covariance function that allows us to accurately predict the signal even from voxels with complex fibre patterns. For multi-shell data (multiple non-zero b-values) the covariance function extends across the shells which means that data from one shell is used when making predictions for another shell. PMID:26236030

  20. Predicting standard-dose PET image from low-dose PET and multimodal MR images using mapping-based sparse representation

    NASA Astrophysics Data System (ADS)

    Wang, Yan; Zhang, Pei; An, Le; Ma, Guangkai; Kang, Jiayin; Shi, Feng; Wu, Xi; Zhou, Jiliu; Lalush, David S.; Lin, Weili; Shen, Dinggang

    2016-01-01

    Positron emission tomography (PET) has been widely used in clinical diagnosis for diseases and disorders. To obtain high-quality PET images requires a standard-dose radionuclide (tracer) injection into the human body, which inevitably increases risk of radiation exposure. One possible solution to this problem is to predict the standard-dose PET image from its low-dose counterpart and its corresponding multimodal magnetic resonance (MR) images. Inspired by the success of patch-based sparse representation (SR) in super-resolution image reconstruction, we propose a mapping-based SR (m-SR) framework for standard-dose PET image prediction. Compared with the conventional patch-based SR, our method uses a mapping strategy to ensure that the sparse coefficients, estimated from the multimodal MR images and low-dose PET image, can be applied directly to the prediction of standard-dose PET image. As the mapping between multimodal MR images (or low-dose PET image) and standard-dose PET images can be particularly complex, one step of mapping is often insufficient. To this end, an incremental refinement framework is therefore proposed. Specifically, the predicted standard-dose PET image is further mapped to the target standard-dose PET image, and then the SR is performed again to predict a new standard-dose PET image. This procedure can be repeated for prediction refinement of the iterations. Also, a patch selection based dictionary construction method is further used to speed up the prediction process. The proposed method is validated on a human brain dataset. The experimental results show that our method can outperform benchmark methods in both qualitative and quantitative measures.

  1. Predicting standard-dose PET image from low-dose PET and multimodal MR images using mapping-based sparse representation.

    PubMed

    Wang, Yan; Zhang, Pei; An, Le; Ma, Guangkai; Kang, Jiayin; Shi, Feng; Wu, Xi; Zhou, Jiliu; Lalush, David S; Lin, Weili; Shen, Dinggang

    2016-01-21

    Positron emission tomography (PET) has been widely used in clinical diagnosis for diseases and disorders. To obtain high-quality PET images requires a standard-dose radionuclide (tracer) injection into the human body, which inevitably increases risk of radiation exposure. One possible solution to this problem is to predict the standard-dose PET image from its low-dose counterpart and its corresponding multimodal magnetic resonance (MR) images. Inspired by the success of patch-based sparse representation (SR) in super-resolution image reconstruction, we propose a mapping-based SR (m-SR) framework for standard-dose PET image prediction. Compared with the conventional patch-based SR, our method uses a mapping strategy to ensure that the sparse coefficients, estimated from the multimodal MR images and low-dose PET image, can be applied directly to the prediction of standard-dose PET image. As the mapping between multimodal MR images (or low-dose PET image) and standard-dose PET images can be particularly complex, one step of mapping is often insufficient. To this end, an incremental refinement framework is therefore proposed. Specifically, the predicted standard-dose PET image is further mapped to the target standard-dose PET image, and then the SR is performed again to predict a new standard-dose PET image. This procedure can be repeated for prediction refinement of the iterations. Also, a patch selection based dictionary construction method is further used to speed up the prediction process. The proposed method is validated on a human brain dataset. The experimental results show that our method can outperform benchmark methods in both qualitative and quantitative measures. PMID:26732849

  2. Multi-decadal changes and predictions over the Southern Hemisphere Polar region: role of the stratospheric representation in CMIP5 models

    NASA Astrophysics Data System (ADS)

    Rea, Gloria; Cagnazzo, Chiara; Riccio, Angelo; Fierli, Federico; Cairo, Francesco

    2016-04-01

    In the last decades, the strong ozone hole at Southern Hemisphere (SH) polar latitudes has been responsible of a long-term lower stratospheric cooling that seasonally superimposes to the GHG cooling, affecting summertime circulation from the stratosphere to the surface. In the troposphere, the ozone-induced cooling implies a poleward shift of the mid-latitude jet and projects onto the positive phase of the Southern Annular Mode (SAM) at the surface affecting also oceanic circulation and temperature by variations in wind stress at the ocean surface and in the oceanic Ekman transport. The SAM positive phase projects onto Sea Surface Temperature (SST) colder anomalies around most of Antarctica and warmer anomalies around the west side of Antarctic Peninsula and at mid-high latitudes, contributing to accelerate initially the upper branch of the Atlantic Meridional Overturning Circulation (AMOC) in opposition to the weakening induced by global warming. We demonstrate that a proper representation of the stratospheric processes in climate models is the key ingredient to fully capture multi-decadal climate changes in the SH and to make more reliable future predictions. We perform a multi-model analysis assessing to which extent a limited representation of stratospheric processes in the Coupled Intercomparison Project Phase 5 (CMIP5) models leads to biases in the representation of simulated SH stratospheric, tropospheric and surface changes on multi-decadal time scales. All these same changes are analyzed for future scenarios with projected increase of GHGs and ozone recovery. We investigate also the relationship between the SAM positive phase and the SST summertime trends and possible effects on the oceanic circulation for the different model classifications.

  3. Transition-state theory predicts clogging at the microscale

    PubMed Central

    Laar, T. van de; Klooster, S. ten; Schroën, K.; Sprakel, J.

    2016-01-01

    Clogging is one of the main failure mechanisms encountered in industrial processes such as membrane filtration. Our understanding of the factors that govern the build-up of fouling layers and the emergence of clogs is largely incomplete, so that prevention of clogging remains an immense and costly challenge. In this paper we use a microfluidic model combined with quantitative real-time imaging to explore the influence of pore geometry and particle interactions on suspension clogging in constrictions, two crucial factors which remain relatively unexplored. We find a distinct dependence of the clogging rate on the entrance angle to a membrane pore which we explain quantitatively by deriving a model, based on transition-state theory, which describes the effect of viscous forces on the rate with which particles accumulate at the channel walls. With the same model we can also predict the effect of the particle interaction potential on the clogging rate. In both cases we find excellent agreement between our experimental data and theory. A better understanding of these clogging mechanisms and the influence of design parameters could form a stepping stone to delay or prevent clogging by rational membrane design. PMID:27328715

  4. Transition-state theory predicts clogging at the microscale.

    PubMed

    Laar, T van de; Klooster, S Ten; Schroën, K; Sprakel, J

    2016-01-01

    Clogging is one of the main failure mechanisms encountered in industrial processes such as membrane filtration. Our understanding of the factors that govern the build-up of fouling layers and the emergence of clogs is largely incomplete, so that prevention of clogging remains an immense and costly challenge. In this paper we use a microfluidic model combined with quantitative real-time imaging to explore the influence of pore geometry and particle interactions on suspension clogging in constrictions, two crucial factors which remain relatively unexplored. We find a distinct dependence of the clogging rate on the entrance angle to a membrane pore which we explain quantitatively by deriving a model, based on transition-state theory, which describes the effect of viscous forces on the rate with which particles accumulate at the channel walls. With the same model we can also predict the effect of the particle interaction potential on the clogging rate. In both cases we find excellent agreement between our experimental data and theory. A better understanding of these clogging mechanisms and the influence of design parameters could form a stepping stone to delay or prevent clogging by rational membrane design. PMID:27328715

  5. Nucleotide Docking: Prediction of Reactant State Complexes for Ribonuclease Enzymes

    SciTech Connect

    Elsasser, Brigitta M.; Fels, Gregor

    2010-12-01

    Ribonuclease enzymes (RNases) play key roles in the maturation and metabolism of all RNA molecules. Computational simulations of the processes involved can help to elucidate the underlying enzymatic mechanism and is often employed in a synergistic approach together with biochemical experiments. Theoretical calculations require atomistic details regarding the starting geometries of the molecules involved, which, in the absence of crystallographic data, can only be achieved from computational docking studies. Fortunately, docking algorithms have improved tremendously in recent years, so that reliable structures of enzyme-ligand complexes can now be successfully obtained from computation. However, most docking programs are not particularly optimized for nucleotide docking. In order to assist our studies on the cleavage of RNA by the two most important ribonuclease enzymes, RNase A and RNase H, we evaluated four docking tools - MOE2009, Glide 5.5, QXP-Flo+0802, and Autodock 4.0 - for their ability to simulate complexes between these enzymes and RNA oligomers. To validate our results, we analyzed the docking results with respect to the known key interactions between the protein and the nucleotide. In addition, we compared the predicted complexes with X-ray structures of the mutated enzyme as well as with structures obtained from previous calculations. In this manner, we were able to prepare the desired reaction state complex so that it could be used as the starting structure for further DFT/B3LYP QM/MM reaction mechanism studies.

  6. Transition-state theory predicts clogging at the microscale

    NASA Astrophysics Data System (ADS)

    Laar, T. Van De; Klooster, S. Ten; Schroën, K.; Sprakel, J.

    2016-06-01

    Clogging is one of the main failure mechanisms encountered in industrial processes such as membrane filtration. Our understanding of the factors that govern the build-up of fouling layers and the emergence of clogs is largely incomplete, so that prevention of clogging remains an immense and costly challenge. In this paper we use a microfluidic model combined with quantitative real-time imaging to explore the influence of pore geometry and particle interactions on suspension clogging in constrictions, two crucial factors which remain relatively unexplored. We find a distinct dependence of the clogging rate on the entrance angle to a membrane pore which we explain quantitatively by deriving a model, based on transition-state theory, which describes the effect of viscous forces on the rate with which particles accumulate at the channel walls. With the same model we can also predict the effect of the particle interaction potential on the clogging rate. In both cases we find excellent agreement between our experimental data and theory. A better understanding of these clogging mechanisms and the influence of design parameters could form a stepping stone to delay or prevent clogging by rational membrane design.

  7. Dispersion Representation of Deeply Virtual Compton Scattering

    NASA Astrophysics Data System (ADS)

    Pasquini, B.

    2015-09-01

    We discuss the dispersive representation of the D-term form factor for hard exclusive reactions, using unsubtracted t-channel dispersion relations. This representation provides a microscopical interpretation of the physical content of the D-term form factor in terms of t-channel exchanges with the appropriate quantum numbers. The contribution from two-pion intermediate states is explicitly evaluated, and the corresponding results for the D-term form factor as function of t as well as at t = 0 are discussed in comparison with available model predictions and phenomenological parametrizations.

  8. The Frequency of “Brilliant” and “Genius” in Teaching Evaluations Predicts the Representation of Women and African Americans across Fields

    PubMed Central

    Storage, Daniel; Horne, Zachary; Cimpian, Andrei; Leslie, Sarah-Jane

    2016-01-01

    Women and African Americans—groups targeted by negative stereotypes about their intellectual abilities—may be underrepresented in careers that prize brilliance and genius. A recent nationwide survey of academics provided initial support for this possibility. Fields whose practitioners believed that natural talent is crucial for success had fewer female and African American PhDs. The present study seeks to replicate this initial finding with a different, and arguably more naturalistic, measure of the extent to which brilliance and genius are prized within a field. Specifically, we measured field-by-field variability in the emphasis on these intellectual qualities by tallying—with the use of a recently released online tool—the frequency of the words “brilliant” and “genius” in over 14 million reviews on RateMyProfessors.com, a popular website where students can write anonymous evaluations of their instructors. This simple word count predicted both women’s and African Americans’ representation across the academic spectrum. That is, we found that fields in which the words “brilliant” and “genius” were used more frequently on RateMyProfessors.com also had fewer female and African American PhDs. Looking at an earlier stage in students’ educational careers, we found that brilliance-focused fields also had fewer women and African Americans obtaining bachelor’s degrees. These relationships held even when accounting for field-specific averages on standardized mathematics assessments, as well as several competing hypotheses concerning group differences in representation. The fact that this naturalistic measure of a field’s focus on brilliance predicted the magnitude of its gender and race gaps speaks to the tight link between ability beliefs and diversity. PMID:26938242

  9. Predicting the enantioselectivity of the copper-catalysed cyclopropanation of alkenes by using quantitative quadrant-diagram representations of the catalysts.

    PubMed

    Aguado-Ullate, Sonia; Urbano-Cuadrado, Manuel; Villalba, Isabel; Pires, Elísabet; García, José I; Bo, Carles; Carbó, Jorge J

    2012-10-29

    We present a new methodology to predict the enantioselectivity of asymmetric catalysis based on quantitative quadrant-diagram representations of the catalysts and quantitative structure-selectivity relationship (QSSR) modelling. To account for quadrant occupation, we used two types of molecular steric descriptors: the Taft-Charton steric parameter (ν(Charton)) and the distance-weighted volume (V(W) ). By assigning the value of the steric descriptors to each of the positions of the quadrant diagram, we generated the independent variables to build the multidimensional QSSR models. The methodology was applied to predict the enantioselectivity in the cyclopropanation of styrene catalysed by copper complexes. The dataset comprised 30 chiral ligands belonging to four different oxazoline-based ligand families: bis- (Box), azabis- (AzaBox), quinolinyl- (Quinox) and pyridyl-oxazoline (Pyox). In the first-order approximation, we generated QSSR models with good predictive ability (r(2) =0.89 and q(2) =0.88). The derived stereochemical model indicated that placing very large groups at two diagonal quadrants and leaving free the other two might be enough to obtain an enantioselective catalyst. Fitting the data to a higher-order polynomial, which included crossterms between the descriptors of the quadrants, resulted in an improvement of the predicting ability of the QSSR model (r(2) =0.96 and q(2) =0.93). This suggests that the relationship between the steric hindrance and the enantioselectivity is non-linear, and that bulky substituents in diagonal quadrants operate synergistically. We believe that the quantitative quadrant-diagram-based QSSR modelling is a further conceptual tool that can be used to predict the selectivity of chiral catalysts and other aspects of catalytic performance. PMID:22987760

  10. Effective impedance for predicting the existence of surface states

    NASA Astrophysics Data System (ADS)

    Xiao, Meng; Huang, Xueqin; Fang, Anan; Chan, C. T.

    2016-03-01

    We build an effective impedance for two-dimensional (2D) photonic crystals (PCs) comprising a rectangular lattice of dielectric cylinders with the incident electric field polarized along the axis of the cylinders. In particular, we discuss the feasibility of constructing an effective impedance for the case where the Bloch wave vector is far away from the center of Brillouin zone, where the optical response of the PC is necessarily anisotropic, and hence the effective description becomes inevitably angle dependent. We employ the scattering theory and treat the 2D system as a stack of 1D arrays. We consider only the zero-order interlayer diffraction, and all the higher order diffraction terms of interlayer scattering are ignored. This approximation works well when the higher order diffraction terms are all evanescent waves and the interlayer distance is far enough for them to decay out. Scattering theory enables the calculation of transmission and reflection coefficients of a finite-sized slab, and we extract the effective parameters such as the effective impedance (Ze) and the effective refractive index (ne) using a parameter retrieval method. We note that ne is uniquely defined only in a very limited region of the reciprocal space. (nek0a ≪1 , where k0 is the wave vector inside the vacuum and a is thickness of the slab for retrieval), but Ze is uniquely defined and has a well-defined meaning inside a much larger domain in the reciprocal space. For a lossless system, the effective impedance Ze is purely real for the pass band and purely imaginary in the band gaps. Using the sign of the imaginary part of Ze, we can classify the band gaps into two groups, and this classification explains why there is usually no surface state on the boundary of typical fully gapped PCs composed of a lattice of dielectric cylinders. This effective medium approach also allows us to predict the dispersion of surface states even when the surface wave vectors are well beyond the zone

  11. Medico-Artistic Complicities on Swedish Stages: The Boys in the Band and the Regulation of Gay Male Representation in the Welfare State.

    PubMed

    Gindt, Dirk

    2016-05-01

    Seeking to understand the highly unfavorable conditions for the development of gay male theater in Sweden, this essay engages in a historical study of the national opening of Mart Crowley's The Boys in the Band at Malmö City Theatre in 1970. Propelled by a Foucauldian-inspired theoretical approach, it identifies the subtle, yet highly effective, measures of control that the, at the time, social democratic welfare state exercised over representations of homosexuality on stage. State representatives, who complied with the official political and medical doctrine that homosexuality was a mental illness and posed a potential threat to social stability, interfered at various levels of the production, including the rehearsal process and post-performance talks between cast members and audiences. This alliance between Swedish theaters and members of the medical, psychological, and sexological professions constituted a medico-artistic complicity that supervised and regulated early attempts of gay representation on stage. PMID:26565769

  12. Threefold representation of M-N-O systems as a guide to predict mechanosynthesis of M-N nanocrystals

    NASA Astrophysics Data System (ADS)

    Rojas-Chávez, H.; Reyes-Carmona, F.; Huerta, L.; Jaramillo-Vigueras, D.

    2013-06-01

    A method is proposed to forecast how micrometric powders are converted on intermetallic nanocrystals by high-energy milling. Mixtures of MO-N or M-N as precursors were processed to obtain PbTe or PbSe. This transformation takes place by oxidizing highly reactive chalcogens such as Se or Te and reoxidation of PbO to form Pb complex chalcoxides. In the latter phases Te or Se share electrons to act as TeIV or SeIV, PbTeO3 or PbSeO3. Once that state is completed, the reduction state manifests itself as an amorphous precipitation of phases. The final stage is traced as high purity nanocrystals.

  13. Predictive sufficiency and the use of stored internal state

    NASA Technical Reports Server (NTRS)

    Musliner, David J.; Durfee, Edmund H.; Shin, Kang G.

    1994-01-01

    In all embedded computing systems, some delay exists between sensing and acting. By choosing an action based on sensed data, a system is essentially predicting that there will be no significant changes in the world during this delay. However, the dynamic and uncertain nature of the real world can make these predictions incorrect, and thus, a system may execute inappropriate actions. Making systems more reactive by decreasing the gap between sensing and action leaves less time for predictions to err, but still provides no principled assurance that they will be correct. Using the concept of predictive sufficiency described in this paper, a system can prove that its predictions are valid, and that it will never execute inappropriate actions. In the context of our CIRCA system, we also show how predictive sufficiency allows a system to guarantee worst-case response times to changes in its environment. Using predictive sufficiency, CIRCA is able to build real-time reactive control plans which provide a sound basis for performance guarantees that are unavailable with other reactive systems.

  14. Predicting Switchgrass Farmgate and Delivered Costs: An 11-State Analysis

    SciTech Connect

    Graham, R.L.; English, B.C.; Noon, C.E.; Jager, H.I.; Daly, M.J.

    1997-08-24

    A GIS-based modeling system was developed for analyzing the geographic variation in potential switchgrass feedstock supplies and prices. The modeling system is designed for analyzing individual US states; parameters for six southern states (Alabama, Florida, Georgia, Missouri, South Carolina, Tennessee) and five midwestern states (Iowa, Minnesota, Nebraska, North Dakota, South Dakota). Potential switchgrass supplies are estimated for each state under two switchgrass technology adoption scenarios.

  15. Predicting Periodontitis at State and Local Levels in the United States.

    PubMed

    Eke, P I; Zhang, X; Lu, H; Wei, L; Thornton-Evans, G; Greenlund, K J; Holt, J B; Croft, J B

    2016-05-01

    The objective of the study was to estimate the prevalence of periodontitis at state and local levels across the United States by using a novel, small area estimation (SAE) method. Extended multilevel regression and poststratification analyses were used to estimate the prevalence of periodontitis among adults aged 30 to 79 y at state, county, congressional district, and census tract levels by using periodontal data from the National Health and Nutrition Examination Survey (NHANES) 2009-2012, population counts from the 2010 US census, and smoking status estimates from the Behavioral Risk Factor Surveillance System in 2012. The SAE method used age, race, gender, smoking, and poverty variables to estimate the prevalence of periodontitis as defined by the Centers for Disease Control and Prevention/American Academy of Periodontology case definitions at the census block levels and aggregated to larger administrative and geographic areas of interest. Model-based SAEs were validated against national estimates directly from NHANES 2009-2012. Estimated prevalence of periodontitis ranged from 37.7% in Utah to 52.8% in New Mexico among the states (mean, 45.1%; median, 44.9%) and from 33.7% to 68% among counties (mean, 46.6%; median, 45.9%). Severe periodontitis ranged from 7.27% in New Hampshire to 10.26% in Louisiana among the states (mean, 8.9%; median, 8.8%) and from 5.2% to 17.9% among counties (mean, 9.2%; median, 8.8%). Overall, the predicted prevalence of periodontitis was highest for southeastern and southwestern states and for geographic areas in the Southeast along the Mississippi Delta, as well as along the US and Mexico border. Aggregated model-based SAEs were consistent with national prevalence estimates from NHANES 2009-2012. This study is the first-ever estimation of periodontitis prevalence at state and local levels in the United States, and this modeling approach complements public health surveillance efforts to identify areas with a high burden of

  16. Simple Model Representations of Transport in a Complex Fracture and Their Effects on Long-Term Predictions

    SciTech Connect

    Doughty, Christine; Tsang, Chin-Fu; Doughty, Christine; Uchida, Masahiro

    2007-11-07

    simple models can be calibrated to reproduce the peak arrival time and height of the complex-fracture-model BTCs, but the overall match remains quite poor. Using simple models with short-term SC-calibrated parameters for long-term calculations causes order-of-magnitude errors in tracer BTCs: peak arrival time is 10-100 times too late, and peak height is 50-300 times too small. On the other hand, using simple models with laboratory-measured properties of unfractured rock samples for 10,000-year calculations results in peak arrivals and heights up to a factor of 50 too early and large, respectively. The actual magnitudes of the errors made by using the simple models depend on the parameter values assumed for the complex fracture model, but in general, simple models are not expected to provide reliable long-term predictions. The paper concludes with some suggestions on how to improve long-term prediction calculations.

  17. The Scholarship of Teaching and Web-Based Representations of Teaching in the United States: Definitions, Histories, and New Directions

    ERIC Educational Resources Information Center

    Hatch, Thomas

    2009-01-01

    The relationship between the scholarship of teaching and practitioner inquiry is characterized both by questions of definition (what "counts" as scholarship and who can produce it) and execution (how to facilitate the representation, interpretation and analysis of teaching). This article addresses both issues by beginning with an overview of the…

  18. Representation and Analysis of Chemistry Core Ideas in Science Education Standards between China and the United States

    ERIC Educational Resources Information Center

    Wan, Yanlan; Bi, Hualin

    2016-01-01

    Chemistry core ideas play an important role in students' chemistry learning. On the basis of the representations of chemistry core ideas about "substances" and "processes" in the Chinese Chemistry Curriculum Standards (CCCS) and the U.S. Next Generation Science Standards (NGSS), we conduct a critical comparison of chemistry…

  19. Statistical Mining of Predictability of Seasonal Precipitation over the United States

    NASA Technical Reports Server (NTRS)

    Lau, William K. M.; Kim, Kyu-Myong; Shen, S. P.

    2001-01-01

    Results from a new ensemble canonical correlation (ECC) prediction model yield a remarkable (10-20%) increases in baseline prediction skills for seasonal precipitation over the US for all seasons, compared to traditional statistical predictions. While the tropical Pacific, i.e., El Nino, contributes to the largest share of potential predictability in the southern tier States during boreal winter, the North Pacific and the North Atlantic are responsible for enhanced predictability in the northern Great Plains, Midwest and the southwest US during boreal summer. Most importantly, ECC significantly reduces the spring predictability barrier over the conterminous US, thereby raising the skill bar for dynamical predictions.

  20. Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates

    DOE PAGESBeta

    Wang, Dong; Dasari, Surendra; Chambers, Matthew C.; Holman, Jerry D.; Chen, Kan; Liebler, Daniel; Orton, Daniel J.; Purvine, Samuel O.; Monroe, Matthew E.; Chung, Chang Y.; et al

    2013-03-07

    In shotgun proteomics, database search algorithms rely on fragmentation models to predict fragment ions that should be observed for a given peptide sequence. The most widely used strategy (Naive model) is oversimplified, cleaving all peptide bonds with equal probability to produce fragments of all charges below that of the precursor ion. More accurate models, based on fragmentation simulation, are too computationally intensive for on-the-fly use in database search algorithms. We have created an ordinal-regression-based model called Basophile that takes fragment size and basic residue distribution into account when determining the charge retention during CID/higher-energy collision induced dissociation (HCD) of chargedmore » peptides. This model improves the accuracy of predictions by reducing the number of unnecessary fragments that are routinely predicted for highly-charged precursors. Basophile increased the identification rates by 26% (on average) over the Naive model, when analyzing triply-charged precursors from ion trap data. Basophile achieves simplicity and speed by solving the prediction problem with an ordinal regression equation, which can be incorporated into any database search software for shotgun proteomic identification.« less

  1. Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates

    SciTech Connect

    Wang, Dong; Dasari, Surendra; Chambers, Matthew C.; Holman, Jerry D.; Chen, Kan; Liebler, Daniel; Orton, Daniel J.; Purvine, Samuel O.; Monroe, Matthew E.; Chung, Chang Y.; Rose, Kristie L.; Tabb, David L.

    2013-03-07

    In shotgun proteomics, database search algorithms rely on fragmentation models to predict fragment ions that should be observed for a given peptide sequence. The most widely used strategy (Naive model) is oversimplified, cleaving all peptide bonds with equal probability to produce fragments of all charges below that of the precursor ion. More accurate models, based on fragmentation simulation, are too computationally intensive for on-the-fly use in database search algorithms. We have created an ordinal-regression-based model called Basophile that takes fragment size and basic residue distribution into account when determining the charge retention during CID/higher-energy collision induced dissociation (HCD) of charged peptides. This model improves the accuracy of predictions by reducing the number of unnecessary fragments that are routinely predicted for highly-charged precursors. Basophile increased the identification rates by 26% (on average) over the Naive model, when analyzing triply-charged precursors from ion trap data. Basophile achieves simplicity and speed by solving the prediction problem with an ordinal regression equation, which can be incorporated into any database search software for shotgun proteomic identification.

  2. Adjoints and Low-rank Covariance Representation

    NASA Technical Reports Server (NTRS)

    Tippett, Michael K.; Cohn, Stephen E.

    2000-01-01

    Quantitative measures of the uncertainty of Earth System estimates can be as important as the estimates themselves. Second moments of estimation errors are described by the covariance matrix, whose direct calculation is impractical when the number of degrees of freedom of the system state is large. Ensemble and reduced-state approaches to prediction and data assimilation replace full estimation error covariance matrices by low-rank approximations. The appropriateness of such approximations depends on the spectrum of the full error covariance matrix, whose calculation is also often impractical. Here we examine the situation where the error covariance is a linear transformation of a forcing error covariance. We use operator norms and adjoints to relate the appropriateness of low-rank representations to the conditioning of this transformation. The analysis is used to investigate low-rank representations of the steady-state response to random forcing of an idealized discrete-time dynamical system.

  3. Regionalized Hydrologic Parameters Estimates for a Seamless Prediction of Continental scale Water Fluxes and States

    NASA Astrophysics Data System (ADS)

    Kumar, R.; Mai, J.; Rakovec, O.; Cuntz, M.; Thober, S.; Zink, M.; Attinger, S.; Schaefer, D.; Schrön, M.; Samaniego, L. E.

    2015-12-01

    Accurate representation of water fluxes and states is crucial for hydrological assessments of societally relevant events such as floods and droughts. Hydrologic and/or land surface models are now commonly used for this purpose. The seamless prediction of continental scale water fluxes from these models requires among other things (i) a robust parameterization technique that allows the model to operate across a range of spatial resolutions and (ii) an efficient parameter estimation technique to derive a representative set of spatially consistent hydrologic parameters to avoid discontinuities of simulated hydrologic fields. In this study, we demonstrate the applicability of a mesoscale hydrologic modeling framework that incorporates a novel multiscale parameter regionalization technique (mHM-MPR) to derive the long-term gridded estimates of water fluxes and states over the Pan-EU domain. The MPR technique allows establishing linkages between hydrologic parameter fields and basin geophysical attributes (e.g., terrain, soil, vegetation properties) through a set of transfer functions and quasi-scale invariant global parameters. We devise a multi-basin parameter estimation strategy that utilizes observed streamflows from a reduced set of hydrologically diverse basins to infer a representative set of global parameters. The selection of diverse basins is guided through a stepwise clustering algorithm based on the basins geophysical and hydro-climatic attributes. Results of this strategy are contrasted against the single-basin calibration strategy across 400 European basins varying from approximately 100 km2 to 500000 km2. The single-basin parameter estimates although produced the site-specific best results, but their transferability to other basins resulted in poor performance. Initial results indicate that the multi-basin calibration strategy is at least as good as the best single-basin cross-validated results. Furthermore, the gridded fields of hydrologic parameters and

  4. The Predictive Brain State: Asynchrony in Disorders of Attention?

    PubMed Central

    Ghajar, Jamshid; Ivry, Richard B.

    2015-01-01

    It is postulated that a key function of attention in goal-oriented behavior is to reduce performance variability by generating anticipatory neural activity that can be synchronized with expected sensory information. A network encompassing the prefrontal cortex, parietal lobe, and cerebellum may be critical in the maintenance and timing of such predictive neural activity. Dysfunction of this temporal process may constitute a fundamental defect in attention, causing working memory problems, distractibility, and decreased awareness. PMID:19074688

  5. Incrementality and Prediction in Human Sentence Processing

    PubMed Central

    Altmann, Gerry T. M.; Mirković, Jelena

    2010-01-01

    We identify a number of principles with respect to prediction that, we argue, underpin adult language comprehension: (a) comprehension consists in realizing a mapping between the unfolding sentence and the event representation corresponding to the real-world event being described; (b) the realization of this mapping manifests as the ability to predict both how the language will unfold, and how the real-world event would unfold if it were being experienced directly; (c) concurrent linguistic and nonlinguistic inputs, and the prior internal states of the system, each drive the predictive process; (d) the representation of prior internal states across a representational substrate common to the linguistic and nonlinguistic domains enables the predictive process to operate over variable time frames and variable levels of representational abstraction. We review empirical data exemplifying the operation of these principles and discuss the relationship between prediction, event structure, thematic role assignment, and incrementality. PMID:20396405

  6. Nonequilibrium, steady-state electron transport with N-representable density matrices from the anti-Hermitian contracted Schrödinger equation.

    PubMed

    Rothman, Adam E; Mazziotti, David A

    2010-03-14

    We study molecular conductivity for a one-electron, bath-molecule-bath model Hamiltonian. The primary quantum-mechanical variable is the one-electron reduced density matrix (1-RDM). By identifying similarities between the steady-state Liouville equation and the anti-Hermitian contracted Schrödinger equation (ACSE) [D. A. Mazziotti, Phys. Rev. A 75, 022505 (2007)], we develop a way of enforcing nonequilibrium, steady-state behavior in a time-independent theory. Our results illustrate the relationship between current and voltage in molecular junctions assuming that the total number of electrons under consideration can be fixed across all driving potentials. The impetus for this work is a recent study by Subotnik et al. that also uses the 1-RDM to study molecular conductivity under different assumptions regarding the total number of electrons [J. E. Subotnik et al., J. Chem. Phys. 130, 144105 (2009)]. Unlike calculations in the previous study, our calculations result in 1-RDMs that are fully N-representable. The present work maintains N-representability through a bath-bath mixing that is related to a time-independent relaxation of the baths in the absence of the molecule, as governed by the ACSE. A lack of N-representability can be important since it corresponds to occupying energy states in the molecule or baths with more than one electron or hole (the absence of an electron) in violation of the Pauli principle. For this reason the present work may serve as an important, albeit preliminary, step in designing a 2-RDM/ACSE method for studying steady-state molecular conductivity with an explicit treatment of electron correlation. PMID:20232952

  7. Modified Inverse First Order Reliability Method (I-FORM) for Predicting Extreme Sea States.

    SciTech Connect

    Eckert-Gallup, Aubrey Celia; Sallaberry, Cedric Jean-Marie; Dallman, Ann Renee; Neary, Vincent Sinclair

    2014-09-01

    Environmental contours describing extreme sea states are generated as the input for numerical or physical model simulation s as a part of the stand ard current practice for designing marine structure s to survive extreme sea states. Such environmental contours are characterized by combinations of significant wave height ( ) and energy period ( ) values calculated for a given recurrence interval using a set of data based on hindcast simulations or buoy observations over a sufficient period of record. The use of the inverse first - order reliability method (IFORM) i s standard design practice for generating environmental contours. In this paper, the traditional appli cation of the IFORM to generating environmental contours representing extreme sea states is described in detail and its merits and drawbacks are assessed. The application of additional methods for analyzing sea state data including the use of principal component analysis (PCA) to create an uncorrelated representation of the data under consideration is proposed. A reexamination of the components of the IFORM application to the problem at hand including the use of new distribution fitting techniques are shown to contribute to the development of more accurate a nd reasonable representations of extreme sea states for use in survivability analysis for marine struc tures. Keywords: In verse FORM, Principal Component Analysis , Environmental Contours, Extreme Sea State Characteri zation, Wave Energy Converters

  8. Using General Outcome Measures to Predict Student Performance on State-Mandated Assessments: An Applied Approach for Establishing Predictive Cutscores

    ERIC Educational Resources Information Center

    Leblanc, Michael; Dufore, Emily; McDougal, James

    2012-01-01

    Cutscores for reading and math (general outcome measures) to predict passage on New York state-mandated assessments were created by using a freely available Excel workbook. The authors used linear regression to create the cutscores and diagnostic indicators were provided. A rationale and procedure for using this method is outlined. This method…

  9. A history of wind erosion prediction models in the United States Department of Agriculture: The Wind Erosion Prediction System (WEPS)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Development of the Wind Erosion Prediction System (WEPS) was officially inaugurated in 1985 by United States Department of Agriculture-Agricultural Research Service (USDA-ARS) scientists in response to customer requests, particularly those coming from the USDA Soil Conservation Service (SCS), for im...

  10. Predicting SOA from organic nitrates in the southeastern United States

    EPA Science Inventory

    Organic nitrates have been identified as an important component of ambient aerosol in the Southeast United States. In this work, we use the Community Multiscale Air Quality (CMAQ) model to explore the relationship between gas-phase production of organic nitrates and their subsequ...

  11. The Predictive Validity of Osun State Junior Secondary Certificate Examination

    ERIC Educational Resources Information Center

    Faleye, B. A.; Afolabi, E. R. I.

    2005-01-01

    Introduction: The Junior Secondary Certificate Examination (JSCE) is a summative examination taken by candidates at the end (the third year) of Junior Secondary Education in Nigeria. The Examination is in two versions--(a) the one being conducted by the States' Ministries of Education (MOE) and (b) the Federal version being conducted by the…

  12. Investigating Marine Boundary Layer Parameterizations for Improved Off-Shore Wind Predictions by Combining Observations with Models via State Estimation

    NASA Astrophysics Data System (ADS)

    Delle Monache, Luca; Hacker, Josh; Kosovic, Branko; Lee, Jared; Vandenberghe, Francois; Wu, Yonghui; Clifton, Andrew; Hawkins, Sam; Nissen, Jesper; Rostkier-Edelstein, Dorita

    2014-05-01

    Despite advances in model representation of the spatial and temporal evolution of the atmospheric boundary layer (ABL) a fundamental understanding of the processes shaping the Marine Boundary Layer (MBL) is still lacking. As part of a project funded by the U.S. Department of Energy, we are tackling this problem by combining available atmosphere and ocean observations with advanced coupled atmosphere-wave models, and via state estimation (SE) methodologies. The over-arching goal is to achieve significant advances in the scientific understanding and prediction of the underlying physical processes of the MBL, with an emphasis on the coupling between the atmosphere and the ocean via momentum and heat fluxes. We are using the single-column model (SCM) and three-dimensional (3D) versions of the Weather Research and Forecasting (WRF) model, observations of MBL structure as provided by coastal and offshore remote sensing platforms and meteorological towers, and probabilistic SE. We are systematically investigating the errors in the treatment of the surface layer of the MBL, identifying structural model inadequacies associated with its representation. We expect one key deficiency of current model representations of the surface layer of the MBL that can have a profound effect on fluxes estimates: the use of Monin-Obukhov similarity theory (MOST). This theory was developed for continental ABLs using land-based measurements, which accounts for mechanical and thermal forcing on turbulence but neglects the influence of ocean waves. We have developed an atmosphere-wave coupled modeling system by interfacing WRF with a wave model (Wavewatch III - WWIII), which is used for evaluating errors in the representation of wave-induced forcing on the energy balance at the interface between atmosphere and ocean. The Data Assimilation Research Testbed (DART) includes the SE algorithms that provide the framework for obtaining spatial and temporal statistics of wind-error evolution (and hence

  13. On Belief State Representation and Its Application in Planning with Incomplete Information, Nondeterministic Actions, and Sensing Actions

    ERIC Educational Resources Information Center

    To, Son Thanh

    2012-01-01

    "Belief state" refers to the set of possible world states satisfying the agent's (usually imperfect) knowledge. The use of belief state allows the agent to reason about the world with incomplete information, by considering each possible state in the belief state individually, in the same way as if it had perfect knowledge. However, the…

  14. Heart rate variability predicts the emotional state in dogs.

    PubMed

    Katayama, Maki; Kubo, Takatomi; Mogi, Kazutaka; Ikeda, Kazushi; Nagasawa, Miho; Kikusui, Takefumi

    2016-07-01

    Although it is known that heart rate variability (HRV) is a useful indicator of emotional states in animals, there are few reports of research in dogs. Thus, we investigated the relationship between HRV and emotional states in dogs. The electrocardiogram and behavior in two situations that elicited a positive and negative emotion, in addition to baseline (when dogs were not presented any social stimuli), were recorded in 33 healthy house dogs. After testing, we chose 15seconds from each situation and baseline and calculated three HRV parameters: standard deviation of normal-to-normal R-R intervals (SDNN), the root mean square of successive heartbeat interval differences (RMSSD), and mean R-R intervals (mean RRI). In comparing these parameters with baseline, only SDNN was lower in a positive situation. In contrast, only RMSSD was lower in a negative situation. A change in HRV occurred with a stimulus eliciting emotion, and was able to distinguish between positive and negative situations. Thus, HRV is useful for estimating the emotional state in dogs. PMID:27129806

  15. Representation is representation of similarities.

    PubMed

    Edelman, S

    1998-08-01

    Advanced perceptual systems are faced with the problem of securing a principled (ideally, veridical) relationship between the world and its internal representation. I propose a unified approach to visual representation, addressing the need for superordinate and basic-level categorization and for the identification of specific instances of familiar categories. According to the proposed theory, a shape is represented internally by the responses of a small number of tuned modules, each broadly selective for some reference shape, whose similarity to the stimulus it measures. This amounts to embedding the stimulus in a low-dimensional proximal shape space spanned by the outputs of the active modules. This shape space supports representations of distal shape similarities that are veridical as Shepard's (1968) second-order isomorphisms (i.e., correspondence between distal and proximal similarities among shapes, rather than between distal shapes and their proximal representations). Representation in terms of similarities to reference shapes supports processing (e.g., discrimination) of shapes that are radically different from the reference ones, without the need for the computationally problematic decomposition into parts required by other theories. Furthermore, a general expression for similarity between two stimuli, based on comparisons to reference shapes, can be used to derive models of perceived similarity ranging from continuous, symmetric, and hierarchical ones, as in multidimensional scaling (Shepard 1980), to discrete and nonhierarchical ones, as in the general contrast models (Shepard & Arabie 1979; Tversky 1977). PMID:10097019

  16. Representing Representation

    ERIC Educational Resources Information Center

    Kuntz, Aaron M.

    2010-01-01

    What can be known and how to render what we know are perpetual quandaries met by qualitative research, complicated further by the understanding that the everyday discourses influencing our representations are often tacit, unspoken or heard so often that they seem to warrant little reflection. In this article, I offer analytic memos as a means for…

  17. Meditation-induced states predict attentional control over time.

    PubMed

    Colzato, Lorenza S; Sellaro, Roberta; Samara, Iliana; Baas, Matthijs; Hommel, Bernhard

    2015-12-01

    Meditation is becoming an increasingly popular topic for scientific research and various effects of extensive meditation practice (ranging from weeks to several years) on cognitive processes have been demonstrated. Here we show that extensive practice may not be necessary to achieve those effects. Healthy adult non-meditators underwent a brief single session of either focused attention meditation (FAM), which is assumed to increase top-down control, or open monitoring meditation (OMM), which is assumed to weaken top-down control, before performing an Attentional Blink (AB) task - which assesses the efficiency of allocating attention over time. The size of the AB was considerably smaller after OMM than after FAM, which suggests that engaging in meditation immediately creates a cognitive-control state that has a specific impact on how people allocate their attention over time. PMID:26320866

  18. Two States Mapping Based Time Series Neural Network Model for Compensation Prediction Residual Error

    NASA Astrophysics Data System (ADS)

    Jung, Insung; Koo, Lockjo; Wang, Gi-Nam

    2008-11-01

    The objective of this paper was to design a model of human bio signal data prediction system for decreasing of prediction error using two states mapping based time series neural network BP (back-propagation) model. Normally, a lot of the industry has been applied neural network model by training them in a supervised manner with the error back-propagation algorithm for time series prediction systems. However, it still has got a residual error between real value and prediction result. Therefore, we designed two states of neural network model for compensation residual error which is possible to use in the prevention of sudden death and metabolic syndrome disease such as hypertension disease and obesity. We determined that most of the simulation cases were satisfied by the two states mapping based time series prediction model. In particular, small sample size of times series were more accurate than the standard MLP model.

  19. Systems and Methods for Automated Vessel Navigation Using Sea State Prediction

    NASA Technical Reports Server (NTRS)

    Huntsberger, Terrance L. (Inventor); Rankin, Arturo (Inventor); Aghazarian, Hrand (Inventor); Howard, Andrew B. (Inventor); Reinhart, Rene Felix (Inventor)

    2015-01-01

    Systems and methods for sea state prediction and autonomous navigation in accordance with embodiments of the invention are disclosed. One embodiment of the invention includes a method of predicting a future sea state including generating a sequence of at least two 3D images of a sea surface using at least two image sensors, detecting peaks and troughs in the 3D images using a processor, identifying at least one wavefront in each 3D image based upon the detected peaks and troughs using the processor, characterizing at least one propagating wave based upon the propagation of wavefronts detected in the sequence of 3D images using the processor, and predicting a future sea state using at least one propagating wave characterizing the propagation of wavefronts in the sequence of 3D images using the processor. Another embodiment includes a method of autonomous vessel navigation based upon a predicted sea state and target location.

  20. Are Droughts in the United States Great Plains Predictable on Seasonal and Longer Time Scales?

    NASA Technical Reports Server (NTRS)

    Schubert, Siegfried D.; Suarez, M.; Pegion, P.; Kistler, M.; Einaudi, Franco (Technical Monitor)

    2001-01-01

    The United States Great Plains has experienced numerous episodes of unusually dry conditions lasting anywhere from months to several years, In this presentation, we will examine the predictability of such episodes and the physical mechanisms controlling the variability of the summer climate of the continental United States. The analysis is based on ensembles of multi-year simulations and seasonal hindcasts generated with the NASA Seasonal to-Interannual Prediction Project (NSIPP-1) General Circulation Model.

  1. How to trust a perfect stranger: predicting initial trust behavior from resting-state brain-electrical connectivity

    PubMed Central

    Notebaert, Karolien; Anderl, Christine; Teckentrup, Vanessa; Kaßecker, Anja; Windmann, Sabine

    2015-01-01

    Reciprocal exchanges can be understood as the updating of an initial belief about a partner. This initial level of trust is essential when it comes to establishing cooperation with an unknown partner, as cooperation cannot arise without a minimum of trust not justified by previous successful exchanges with this partner. Here we demonstrate the existence of a representation of the initial trust level before an exchange with a partner has occurred. Specifically, we can predict the Investor’s initial investment—i.e. his initial level of trust toward the unknown trustee in Round 1 of a standard 10-round Trust Game—from resting-state functional connectivity data acquired several minutes before the start of the Trust Game. Resting-state functional connectivity is, however, not significantly associated with the level of trust in later rounds, potentially mirroring the updating of the initial belief about the partner. Our results shed light on how the initial level of trust is represented. In particular, we show that a person’s initial level of trust is, at least in part, determined by brain electrical activity acquired well before the beginning of an exchange. PMID:25274577

  2. How to trust a perfect stranger: predicting initial trust behavior from resting-state brain-electrical connectivity.

    PubMed

    Hahn, Tim; Notebaert, Karolien; Anderl, Christine; Teckentrup, Vanessa; Kaßecker, Anja; Windmann, Sabine

    2015-06-01

    Reciprocal exchanges can be understood as the updating of an initial belief about a partner. This initial level of trust is essential when it comes to establishing cooperation with an unknown partner, as cooperation cannot arise without a minimum of trust not justified by previous successful exchanges with this partner. Here we demonstrate the existence of a representation of the initial trust level before an exchange with a partner has occurred. Specifically, we can predict the Investor's initial investment--i.e. his initial level of trust toward the unknown trustee in Round 1 of a standard 10-round Trust Game-from resting-state functional connectivity data acquired several minutes before the start of the Trust Game. Resting-state functional connectivity is, however, not significantly associated with the level of trust in later rounds, potentially mirroring the updating of the initial belief about the partner. Our results shed light on how the initial level of trust is represented. In particular, we show that a person's initial level of trust is, at least in part, determined by brain electrical activity acquired well before the beginning of an exchange. PMID:25274577

  3. Replication and Extension: Separate Personality Traits from States to Predict Depression

    PubMed Central

    Vittengl, Jeffrey R.; Clark, Lee Anna; Thase, Michael E.; Jarrett, Robin B.

    2013-01-01

    Changes in personality trait levels often parallel episodes of major depressive disorder (MDD), whereas trait factor structures and substantial retest correlations are preserved. We explicated this dual state/trait nature of personality assessments among adults with recurrent MDD (N=351) receiving cognitive therapy (CT). We tested stability and change in the Schedule for Nonadaptive and Adaptive Personality, 2nd Edition (SNAP-2; Clark et al., in press), separated state and trait variance, and predicted depressive symptoms and clinical outcomes. Many SNAP scale scores changed in CT (e.g., positive temperament increased, negative temperament decreased), and decreases in depressive symptoms accounted for most scales' score changes. Nonetheless, SNAP scales' state and trait components predicted depressive symptoms early and late in CT as well as clinical outcomes, and state components predicted changes in symptoms and clinical outcomes. These results support the validity of the SNAP-2 among depressed patients and highlight the salience of personality-relevant state affect. PMID:23786268

  4. Prediction and Control of Slip-Free Rotation States in Sphere Assemblies

    NASA Astrophysics Data System (ADS)

    Stäger, D. V.; Araújo, N. A. M.; Herrmann, H. J.

    2016-06-01

    We study fixed assemblies of touching spheres that can individually rotate. From any initial state, sliding friction drives an assembly toward a slip-free rotation state. For bipartite assemblies, which have only even loops, this state has at least four degrees of freedom. For exactly four degrees of freedom, we analytically predict the final state, which we prove to be independent of the strength of sliding friction, from an arbitrary initial one. With a tabletop experiment, we show how to impose any slip-free rotation state by only controlling two spheres, regardless of the total number.

  5. Prediction and Control of Slip-Free Rotation States in Sphere Assemblies.

    PubMed

    Stäger, D V; Araújo, N A M; Herrmann, H J

    2016-06-24

    We study fixed assemblies of touching spheres that can individually rotate. From any initial state, sliding friction drives an assembly toward a slip-free rotation state. For bipartite assemblies, which have only even loops, this state has at least four degrees of freedom. For exactly four degrees of freedom, we analytically predict the final state, which we prove to be independent of the strength of sliding friction, from an arbitrary initial one. With a tabletop experiment, we show how to impose any slip-free rotation state by only controlling two spheres, regardless of the total number. PMID:27391726

  6. Prediction of Filamentous Sludge Bulking using a State-based Gaussian Processes Regression Model

    PubMed Central

    Liu, Yiqi; Guo, Jianhua; Wang, Qilin; Huang, Daoping

    2016-01-01

    Activated sludge process has been widely adopted to remove pollutants in wastewater treatment plants (WWTPs). However, stable operation of activated sludge process is often compromised by the occurrence of filamentous bulking. The aim of this study is to build a proper model for timely diagnosis and prediction of filamentous sludge bulking in an activated sludge process. This study developed a state-based Gaussian Process Regression (GPR) model to monitor the filamentous sludge bulking related parameter, sludge volume index (SVI), in such a way that the evolution of SVI can be predicted over multi-step ahead. This methodology was validated with SVI data collected from one full-scale WWTP. Online diagnosis and prediction of filamentous bulking sludge with real-time SVI prediction was tested through a simulation study. The results showed that the proposed methodology was capable of predicting future SVIs with good accuracy, thus providing sufficient time for predicting and controlling filamentous sludge bulking. PMID:27498888

  7. Prediction of Filamentous Sludge Bulking using a State-based Gaussian Processes Regression Model.

    PubMed

    Liu, Yiqi; Guo, Jianhua; Wang, Qilin; Huang, Daoping

    2016-01-01

    Activated sludge process has been widely adopted to remove pollutants in wastewater treatment plants (WWTPs). However, stable operation of activated sludge process is often compromised by the occurrence of filamentous bulking. The aim of this study is to build a proper model for timely diagnosis and prediction of filamentous sludge bulking in an activated sludge process. This study developed a state-based Gaussian Process Regression (GPR) model to monitor the filamentous sludge bulking related parameter, sludge volume index (SVI), in such a way that the evolution of SVI can be predicted over multi-step ahead. This methodology was validated with SVI data collected from one full-scale WWTP. Online diagnosis and prediction of filamentous bulking sludge with real-time SVI prediction was tested through a simulation study. The results showed that the proposed methodology was capable of predicting future SVIs with good accuracy, thus providing sufficient time for predicting and controlling filamentous sludge bulking. PMID:27498888

  8. Modeling and analysis of several classes of self-oscillating inverters. I - State-plane representations. II - Model extension, classification, and duality relationships

    NASA Technical Reports Server (NTRS)

    Lee, F. C. Y.; Wilson, T. G.

    1982-01-01

    The present investigation is concerned with an important class of power conditioning networks, taking into account self-oscillating dc-to-square-wave transistor inverters. The considered circuits are widely used both as the principal power converting and processing means in many systems and as low-power analog-to-discrete-time converters for controlling the switching of the output-stage semiconductors in a variety of power conditioning systems. Aspects of piecewise-linear modeling are discussed, taking into consideration component models, and an equivalent-circuit model. Questions of singular point analysis and state plane representation are also investigated, giving attention to limit cycles, starting circuits, the region of attraction, a hard oscillator, and a soft oscillator.

  9. Wavelet modeling and prediction of the stability of states: the Roman Empire and the European Union

    NASA Astrophysics Data System (ADS)

    Yaroshenko, Tatyana Y.; Krysko, Dmitri V.; Dobriyan, Vitalii; Zhigalov, Maksim V.; Vos, Hendrik; Vandenabeele, Peter; Krysko, Vadim A.

    2015-09-01

    How can the stability of a state be quantitatively determined and its future stability predicted? The rise and collapse of empires and states is very complex, and it is exceedingly difficult to understand and predict it. Existing theories are usually formulated as verbal models and, consequently, do not yield sharply defined, quantitative prediction that can be unambiguously validated with data. Here we describe a model that determines whether the state is in a stable or chaotic condition and predicts its future condition. The central model, which we test, is that growth and collapse of states is reflected by the changes of their territories, populations and budgets. The model was simulated within the historical societies of the Roman Empire (400 BC to 400 AD) and the European Union (1957-2007) by using wavelets and analysis of the sign change of the spectrum of Lyapunov exponents. The model matches well with the historical events. During wars and crises, the state becomes unstable; this is reflected in the wavelet analysis by a significant increase in the frequency ω (t) and wavelet coefficients W (ω, t) and the sign of the largest Lyapunov exponent becomes positive, indicating chaos. We successfully reconstructed and forecasted time series in the Roman Empire and the European Union by applying artificial neural network. The proposed model helps to quantitatively determine and forecast the stability of a state.

  10. ELECTROMAGNETISM, OPTICS, ACOUSTICS, HEAT TRANSFER, CLASSICAL MECHANICS, AND FLUID DYNAMICS: New Approach for Solving Master Equations in Quantum Optics and Quantum Statistics by Virtue of Thermo-Entangled State Representation

    NASA Astrophysics Data System (ADS)

    Fan, Hong-Yi; Hu, Li-Yun

    2009-04-01

    By introducing a fictitious mode to be a counterpart mode of the system mode under review we introduce the entangled state representation langleη|, which can arrange master equations of density operators ρ(t) in quantum statistics as state-vector evolution equations due to the elegant properties of langleη|. In this way many master equations (respectively describing damping oscillator, laser, phase sensitive, and phase diffusion processes with different initial density operators) can be concisely solved. Specially, for a damping process characteristic of the decay constant κ we find that the matrix element of ρ(t) at time t in langleη| representation is proportional to that of the initial ρ0 in the decayed entangled state langleηe-κt| representation, accompanying with a Gaussian damping factor. Thus we have a new insight about the nature of the dissipative process. We also set up the so-called thermo-entangled state representation of density operators, ρ = ∫(d2η/π)langleη|ρrangleD(η), which is different from all the previous known representations.

  11. Predicting electrocardiogram and arterial blood pressure waveforms with different Echo State Network architectures.

    PubMed

    Fong, Allan; Mittu, Ranjeev; Ratwani, Raj; Reggia, James

    2014-01-01

    Alarm fatigue caused by false alarms and alerts is an extremely important issue for the medical staff in Intensive Care Units. The ability to predict electrocardiogram and arterial blood pressure waveforms can potentially help the staff and hospital systems better classify a patient's waveforms and subsequent alarms. This paper explores the use of Echo State Networks, a specific type of neural network for mining, understanding, and predicting electrocardiogram and arterial blood pressure waveforms. Several network architectures are designed and evaluated. The results show the utility of these echo state networks, particularly ones with larger integrated reservoirs, for predicting electrocardiogram waveforms and the adaptability of such models across individuals. The work presented here offers a unique approach for understanding and predicting a patient's waveforms in order to potentially improve alarm generation. We conclude with a brief discussion of future extensions of this research. PMID:25954359

  12. Attention Stabilizes Representations in the Human Hippocampus.

    PubMed

    Aly, Mariam; Turk-Browne, Nicholas B

    2016-02-01

    Attention and memory are intricately linked, but how attention modulates brain areas that subserve memory, such as the hippocampus, is unknown. We hypothesized that attention may stabilize patterns of activity in human hippocampus, resulting in distinct but reliable activity patterns for different attentional states. To test this prediction, we utilized high-resolution functional magnetic resonance imaging and a novel "art gallery" task. On each trial, participants viewed a room containing a painting, and searched a stream of rooms for a painting from the same artist (art state) or a room with the same layout (room state). Bottom-up stimulation was the same in both tasks, enabling the isolation of neural effects related to top-down attention. Multivariate analyses revealed greater pattern similarity in all hippocampal subfields for trials from the same, compared with different, attentional state. This stability was greater for the room than art state, was unrelated to univariate activity, and, in CA2/CA3/DG, was correlated with behavior. Attention therefore induces representational stability in the human hippocampus, resulting in distinct activity patterns for different attentional states. Modulation of hippocampal representational stability highlights the far-reaching influence of attention outside of sensory systems. PMID:25766839

  13. Representation in incremental learning

    NASA Technical Reports Server (NTRS)

    1993-01-01

    Work focused on two areas in machine learning: representation for inductive learning and how to apply concept learning techniques to learning state preferences, which can represent search control knowledge for problem solving. Specifically, in the first area the issues of the effect of representation on learning, on how learning formalisms are biased, and how concept learning can benefit from the use of a hybrid formalism are addressed. In the second area, the issues of developing an agent to learn search control knowledge from the relative values of states, of the source of that qualitative information, and of the ability to use both quantitative and qualitative information in order to develop an effective problem-solving policy are examined.

  14. Predicting most probable conformations of a given peptide sequence in the random coil state.

    PubMed

    Bayrak, Cigdem Sevim; Erman, Burak

    2012-11-01

    In this work, we present a computational scheme for finding high probability conformations of peptides. The scheme calculates the probability of a given conformation of the given peptide sequence using the probability distribution of torsion states. Dependence of the states of a residue on the states of its first neighbors along the chain is considered. Prior probabilities of torsion states are obtained from a coil library. Posterior probabilities are calculated by the matrix multiplication Rotational Isomeric States Model of polymer theory. The conformation of a peptide with highest probability is determined by using a hidden Markov model Viterbi algorithm. First, the probability distribution of the torsion states of the residues is obtained. Using the highest probability torsion state, one can generate, step by step, states with lower probabilities. To validate the method, the highest probability state of residues in a given sequence is calculated and compared with probabilities obtained from the Coil Databank. Predictions based on the method are 32% better than predictions based on the most probable states of residues. The ensemble of "n" high probability conformations of a given protein is also determined using the Viterbi algorithm with multistep backtracking. PMID:22955874

  15. Naturalising Representational Content

    PubMed Central

    Shea, Nicholas

    2014-01-01

    This paper sets out a view about the explanatory role of representational content and advocates one approach to naturalising content – to giving a naturalistic account of what makes an entity a representation and in virtue of what it has the content it does. It argues for pluralism about the metaphysics of content and suggests that a good strategy is to ask the content question with respect to a variety of predictively successful information processing models in experimental psychology and cognitive neuroscience; and hence that data from psychology and cognitive neuroscience should play a greater role in theorising about the nature of content. Finally, the contours of the view are illustrated by drawing out and defending a surprising consequence: that individuation of vehicles of content is partly externalist. PMID:24563661

  16. Naturalising Representational Content.

    PubMed

    Shea, Nicholas

    2013-05-01

    This paper sets out a view about the explanatory role of representational content and advocates one approach to naturalising content - to giving a naturalistic account of what makes an entity a representation and in virtue of what it has the content it does. It argues for pluralism about the metaphysics of content and suggests that a good strategy is to ask the content question with respect to a variety of predictively successful information processing models in experimental psychology and cognitive neuroscience; and hence that data from psychology and cognitive neuroscience should play a greater role in theorising about the nature of content. Finally, the contours of the view are illustrated by drawing out and defending a surprising consequence: that individuation of vehicles of content is partly externalist. PMID:24563661

  17. Operational prediction of air quality for the United States: applications of satellite observations

    NASA Astrophysics Data System (ADS)

    Stajner, Ivanka; Lee, Pius; Tong, Daniel; Pan, Li; McQueen, Jeff; Huang, Jianping; Huang, Ho-Chun; Draxler, Roland; Kondragunta, Shobha; Upadhayay, Sikchya

    2015-04-01

    Operational predictions of ozone and wildfire smoke over United States (U.S.) and predictions of airborne dust over the contiguous 48 states are provided by NOAA at http://airquality.weather.gov/. North American Mesoscale (NAM) weather predictions with inventory based emissions estimates from the U.S. Environmental Protection Agency (EPA) and chemical processes within the Community Multiscale Air Quality (CMAQ) model are combined together to produce ozone predictions. Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model is used to predict wildfire smoke and dust storm predictions. Routine verification of ozone predictions relies on AIRNow compilation of observations from surface monitors. Retrievals of smoke column integrals from GOES satellites and dust column integrals from MODIS satellite instruments are used for verification of smoke and dust predictions. Recent updates of NOAA's operational air quality predictions have focused on mobile emissions using the projections of mobile sources for 2012. Since emission inventories are complex and take years to assemble and evaluate causing a lag of information, we recently began combing inventory information with projections of mobile sources. In order to evaluate this emission update, these changes in projected NOx emissions from 2005-2012 were compared with observed changes in Ozone Monitoring Instrument (OMI) NO2 observations and NOx measured by surface monitors over large U.S. cities over the same period. Comparisons indicate that projected decreases in NOx emissions from 2005 to 2012 are similar, but not as strong as the decreases in the observed NOx concentrations and in OMI NO2 retrievals. Nevertheless, the use of projected mobile NOx emissions in the predictions reduced biases in predicted NOx concentrations, with the largest improvement in the urban areas. Ozone biases are reduced as well, with the largest improvement seen in rural areas. Recent testing of PM2.5 predictions is relying on

  18. Web of Objects Based Ambient Assisted Living Framework for Emergency Psychiatric State Prediction.

    PubMed

    Alam, Md Golam Rabiul; Abedin, Sarder Fakhrul; Al Ameen, Moshaddique; Hong, Choong Seon

    2016-01-01

    Ambient assisted living can facilitate optimum health and wellness by aiding physical, mental and social well-being. In this paper, patients' psychiatric symptoms are collected through lightweight biosensors and web-based psychiatric screening scales in a smart home environment and then analyzed through machine learning algorithms to provide ambient intelligence in a psychiatric emergency. The psychiatric states are modeled through a Hidden Markov Model (HMM), and the model parameters are estimated using a Viterbi path counting and scalable Stochastic Variational Inference (SVI)-based training algorithm. The most likely psychiatric state sequence of the corresponding observation sequence is determined, and an emergency psychiatric state is predicted through the proposed algorithm. Moreover, to enable personalized psychiatric emergency care, a service a web of objects-based framework is proposed for a smart-home environment. In this framework, the biosensor observations and the psychiatric rating scales are objectified and virtualized in the web space. Then, the web of objects of sensor observations and psychiatric rating scores are used to assess the dweller's mental health status and to predict an emergency psychiatric state. The proposed psychiatric state prediction algorithm reported 83.03 percent prediction accuracy in an empirical performance study. PMID:27608023

  19. Personality cannot be predicted from the power of resting state EEG

    PubMed Central

    Korjus, Kristjan; Uusberg, Andero; Uusberg, Helen; Kuldkepp, Nele; Kreegipuu, Kairi; Allik, Jüri; Vicente, Raul; Aru, Jaan

    2015-01-01

    In the present study we asked whether it is possible to decode personality traits from resting state EEG data. EEG was recorded from a large sample of subjects (n = 289) who had answered questionnaires measuring personality trait scores of the five dimensions as well as the 10 subordinate aspects of the Big Five. Machine learning algorithms were used to build a classifier to predict each personality trait from power spectra of the resting state EEG data. The results indicate that the five dimensions as well as their subordinate aspects could not be predicted from the resting state EEG data. Finally, to demonstrate that this result is not due to systematic algorithmic or implementation mistakes the same methods were used to successfully classify whether the subject had eyes open or closed. These results indicate that the extraction of personality traits from the power spectra of resting state EEG is extremely noisy, if possible at all. PMID:25762912

  20. Exact density of states for lowest Landau level in white noise potential superfield representation for interacting systems

    NASA Astrophysics Data System (ADS)

    Wegner, Franz

    1983-12-01

    The density of states of two-dimensional electrons in a strong perpendicular magnetic field and white-noise potential is calculated exactly under the provision that only the states of the free electrons in the lowest Landau level are taken into account. It is used that the integral over the coordinates in the plane perpendicular to the magnetic field in a Feynman graph yields the inverse of the number λ of Euler trails through the graph, whereas the weight by which a Feynman graph contributes in this disordered system is λ times that of the corresponding interacting system. Thus the factors λ cancel which allows the reduction of the d dimensional disordered problem to a ( d-2) dimensional φ4 interaction problem. The inverse procedure and the equivalence of disordered harmonic systems with interacting systems of superfields is used to give a mapping of interacting systems with U(1) invariance in d dimensions to interacting systems with UPL(1,1) invariance in ( d+2) dimensions. The partition function of the new systems is unity so that systems with quenched disorder can be treated by averaging exp(- H) without recourse to the replica trick.

  1. Distinct state anxiety after predictable and unpredictable fear training in mice.

    PubMed

    Seidenbecher, Thomas; Remmes, Jasmin; Daldrup, Thiemo; Lesting, Jörg; Pape, Hans-Christian

    2016-05-01

    Sustained fear paradigms in rodents have been developed to monitor states of anxious apprehension and to model situations in patients suffering from long-lasting anxiety disorders. A recent report describes a fear conditioning paradigm, allowing distinction between phasic and sustained states of conditioned fear in non-restrained mice. However, so far no prospective studies have yet been conducted to elucidate whether induction of phasic or sustained fear can affect states of anxiety. Here, we used CS (conditioned stimulus) and US (unconditioned stimulus) pairing with predictable and unpredictable timing to induce phasic and sustained fear in mice. State anxiety during various fear response components was assessed using the elevated plus-maze test. Training with unpredictable CS-US timing resulted in CS-evoked sustained components of fear (freezing), while predictable CS-US timing resulted in rapid decline. Data suggested the influence of training procedure on state anxiety which is dependent on progression of conditioned fear during fear memory retrieval. Animals trained with unpredictable CS-US timing showed an unchanged high anxiety state throughout behavioral observation. In contrast, mice trained with predictable CS-US timing showed anxiolytic-like behavior 3min after CS onset, which was accompanied by a fast decline of the fear conditioned response (freezing). Further systematic studies are needed to validate the phasic/sustained fear model in rodents as translational model for anxiety disorders in humans. PMID:26876138

  2. A multi-state model approach for prediction in chronic myeloid leukaemia.

    PubMed

    Lauseker, Michael; Hasford, Joerg; Hoffmann, Verena S; Müller, Martin C; Hehlmann, Rüdiger; Pfirrmann, Markus

    2015-06-01

    Multi-state models support prediction in medicine. With different states of disease, chronic myeloid leukaemia (CML) is particularly suited for the application of multi-state models. In this article, we tried to find a model for CML that allows predicting the prevalence of three different states (initial state of disease, remission and progression) in dependence on treatment, adjusted for age, sex and risk score. Based on the German CML Study IV, one of the largest randomised studies in CML, the model was able to represent the known effects of age and risk score on the probabilities of remission and progression. Patients achieving a major molecular remission had a better chance of surviving without progression, but this effect was not significant. Comparing treatments, patient of the high-dose arm had the greatest chance to be in the state "remission" at 5 years but did not seem to have an advantage considering "progression". The proposed illness-death model can be useful for predicting the course of CML based on the patient's individual covariates (trial registration: this is an explorative analysis of ClinicalTrials.gov Identifier: NCT00055874). PMID:25465231

  3. Solution- and Adsorbed-State Structural Ensembles Predicted for the Statherin-Hydroxyapatite System

    PubMed Central

    Masica, David L.; Gray, Jeffrey J.

    2009-01-01

    Abstract We have developed a multiscale structure prediction technique to study solution- and adsorbed-state ensembles of biomineralization proteins. The algorithm employs a Metropolis Monte Carlo-plus-minimization strategy that varies all torsional and rigid-body protein degrees of freedom. We applied the technique to fold statherin, starting from a fully extended peptide chain in solution, in the presence of hydroxyapatite (HAp) (001), (010), and (100) monoclinic crystals. Blind (unbiased) predictions capture experimentally observed macroscopic and high-resolution structural features and show minimal statherin structural change upon adsorption. The dominant structural difference between solution and adsorbed states is an experimentally observed folding event in statherin's helical binding domain. Whereas predicted statherin conformers vary slightly at three different HAp crystal faces, geometric and chemical similarities of the surfaces allow structurally promiscuous binding. Finally, we compare blind predictions with those obtained from simulation biased to satisfy all previously published solid-state NMR (ssNMR) distance and angle measurements (acquired from HAp-adsorbed statherin). Atomic clashes in these structures suggest a plausible, alternative interpretation of some ssNMR measurements as intermolecular rather than intramolecular. This work demonstrates that a combination of ssNMR and structure prediction could effectively determine high-resolution protein structures at biomineral interfaces. PMID:19383454

  4. Representations of mechanical assembly sequences

    NASA Astrophysics Data System (ADS)

    Homem de Mello, Luiz S.; Sanderson, Arthur C.

    1991-04-01

    Five types of representations for assembly sequences are reviewed: the directed graph of feasible assembly sequences, the AND/OR graph of feasible assembly sequences, the set of establishment conditions, and two types of sets of precedence relationships. (precedence relationships between the establishment of one connection between parts and the establishment of another connection, and precedence relationships between the establishment of one connection and states of the assembly process). The mappings of one representation into the others are established. The correctness and completeness of these representations are established. The results presented are needed in the proof of correctness and completeness of algorithms for the generation of mechanical assembly sequences.

  5. Representations of mechanical assembly sequences

    NASA Technical Reports Server (NTRS)

    Homem De Mello, Luiz S.; Sanderson, Arthur C.

    1991-01-01

    Five types of representations for assembly sequences are reviewed: the directed graph of feasible assembly sequences, the AND/OR graph of feasible assembly sequences, the set of establishment conditions, and two types of sets of precedence relationships. (precedence relationships between the establishment of one connection between parts and the establishment of another connection, and precedence relationships between the establishment of one connection and states of the assembly process). The mappings of one representation into the others are established. The correctness and completeness of these representations are established. The results presented are needed in the proof of correctness and completeness of algorithms for the generation of mechanical assembly sequences.

  6. Linear State-Space Representation of the Dynamics of Relative Motion, Based on Restricted Three Body Dynamics

    NASA Technical Reports Server (NTRS)

    Luquette, Richard J.; Sanner, Robert M.

    2004-01-01

    Precision Formation Flying is an enabling technology for a variety of proposed space- based observatories, including the Micro-Arcsecond X-ray Imaging Mission (MAXIM), Stellar Imager (SI) and the Terrestrial Planet Finder (TPF). An essential element of the technology is the control algorithm, requiring a clear understanding of the dynamics of relative motion. This paper examines the dynamics of relative motion in the context of the Restricted Three Body Problem (RTBP). The natural dynamics of relative motion are presented in their full nonlinear form. Motivated by the desire to apply linear control methods, the dynamics equations are linearized and presented in state-space form. The stability properties are explored for regions in proximity to each of the libration points in the Earth/Moon - Sun rotating frame. The dynamics of relative motion are presented in both the inertial and rotating coordinate frames.

  7. Linear State-Space Representation of the Dynamics of Relative Motion, Based on Restricted Three Body Dynamics

    NASA Technical Reports Server (NTRS)

    Luquette,Richard J.; Sanner, Robert M.

    2004-01-01

    Precision Formation Flying is an enabling technology for a variety of proposed space-based observatories, including the Micro-Arcsecond X-ray Imaging Mission (MAXIM) , the associated MAXIM pathfinder mission, Stellar Imager (SI) and the Terrestrial Planet Finder (TPF). An essential element of the technology is the control algorithm, requiring a clear understanding of the dynamics of relative motion. This paper examines the dynamics of relative motion in the context of the Restricted Three Body Problem (RTBP). The natural dynamics of relative motion are presented in their full nonlinear form. Motivated by the desire to apply linear control methods, the dynamics equations are linearized and presented in state-space form. The stability properties are explored for regions in proximity to each of the libration points in the Earth/Moon - Sun rotating frame. The dynamics of relative motion are presented in both the inertial and rotating coordinate frames.

  8. Predictive Validity of Early Literacy Measures for Korean English Language Learners in the United States

    ERIC Educational Resources Information Center

    Han, Jeanie Nam; Vanderwood, Michael L.; Lee, Catherine Y.

    2015-01-01

    This study examined the predictive validity of early literacy measures with first-grade Korean English language learners (ELLs) in the United States at varying levels of English proficiency. Participants were screened using Dynamic Indicators of Basic Early Literacy Skills (DIBELS) Phoneme Segmentation Fluency (PSF), DIBELS Nonsense Word Fluency…

  9. CURRENT STATE OF PREDICTING THE RESPIRATORY ALLERGY POTENTIAL OF CHEMICALS: WHAT ARE THE ISSUES?

    EPA Science Inventory

    Current State of Predicting the Respiratory Allergy Potential of Chemicals: What Are the Issues? M I. Gilmour1 and S. E. Loveless2, 1USEPA, Research Triangle Park, NC and 2DuPont Haskell Laboratory, Newark, DE.

    Many chemicals are clearly capable of eliciting immune respon...

  10. Predicting Employment Outcomes of Consumers of State-Operated Comprehensive Rehabilitation Centers

    ERIC Educational Resources Information Center

    Beach, David Thomas

    2009-01-01

    This study used records from a state-operated comprehensive rehabilitation center to investigate possible predictive factors related to completing comprehensive rehabilitation center programs and successful vocational rehabilitation (VR) case closure. An analysis of demographic data of randomly selected comprehensive rehabilitation center…

  11. Extreme Appraisals of Internal States and Bipolar Symptoms: The Hypomanic Attitudes and Positive Predictions Inventory

    ERIC Educational Resources Information Center

    Dodd, Alyson L.; Mansell, Warren; Morrison, Anthony P.; Tai, Sara

    2011-01-01

    The Hypomanic Attitudes and Positive Predictions Inventory (HAPPI; W. Mansell, 2006) was developed to assess multiple, extreme, self-relevant appraisals of internal states. The present study aimed to validate the HAPPI in a clinical sample. Participants (N = 50) with a diagnosis of bipolar disorder (confirmed by a structured clinical interview)…

  12. A Pilot Test of the Resource Requirements Prediction Model at Humboldt State College.

    ERIC Educational Resources Information Center

    California State Colleges, Inglewood. Office of the Chancellor.

    This publication presents Humboldt State College's experience with the pilot testing of the Resource Requirements Prediction Model (RRPM), an analytic computer designed to aid management decisionmaking and planning in institutions of higher education. RRPM has great potential as a planning tool that can improve resource management in higher…

  13. Resting-state qEEG predicts rate of second language learning in adults.

    PubMed

    Prat, Chantel S; Yamasaki, Brianna L; Kluender, Reina A; Stocco, Andrea

    2016-01-01

    Understanding the neurobiological basis of individual differences in second language acquisition (SLA) is important for research on bilingualism, learning, and neural plasticity. The current study used quantitative electroencephalography (qEEG) to predict SLA in college-aged individuals. Baseline, eyes-closed resting-state qEEG was used to predict language learning rate during eight weeks of French exposure using an immersive, virtual scenario software. Individual qEEG indices predicted up to 60% of the variability in SLA, whereas behavioral indices of fluid intelligence, executive functioning, and working-memory capacity were not correlated with learning rate. Specifically, power in beta and low-gamma frequency ranges over right temporoparietal regions were strongly positively correlated with SLA. These results highlight the utility of resting-state EEG for studying the neurobiological basis of SLA in a relatively construct-free, paradigm-independent manner. PMID:27164483

  14. Physiological state gates acquisition and expression of mesolimbic reward prediction signals

    PubMed Central

    Cone, Jackson J.; Fortin, Samantha M.; McHenry, Jenna A.; Stuber, Garret D.; McCutcheon, James E.; Roitman, Mitchell F.

    2016-01-01

    Phasic dopamine signaling participates in associative learning by reinforcing associations between outcomes (unconditioned stimulus; US) and their predictors (conditioned stimulus; CS). However, prior work has always engendered these associations with innately rewarding stimuli. Thus, whether dopamine neurons can acquire prediction signals in the absence of appetitive experience and update them when the value of the outcome changes remains unknown. Here, we used sodium depletion to reversibly manipulate the appetitive value of a hypertonic sodium solution while measuring phasic dopamine signaling in rat nucleus accumbens. Dopamine responses to the NaCl US following sodium depletion updated independent of prior experience. In contrast, prediction signals were only acquired through extensive experience with a US that had positive affective value. Once learned, dopamine prediction signals were flexibly expressed in a state-dependent manner. Our results reveal striking differences with respect to how physiological state shapes dopamine signals evoked by outcomes and their predictors. PMID:26831116

  15. Machine learning classification of resting state functional connectivity predicts smoking status

    PubMed Central

    Pariyadath, Vani; Stein, Elliot A.; Ross, Thomas J.

    2014-01-01

    Machine learning-based approaches are now able to examine functional magnetic resonance imaging data in a multivariate manner and extract features predictive of group membership. We applied support vector machine (SVM)-based classification to resting state functional connectivity (rsFC) data from nicotine-dependent smokers and healthy controls to identify brain-based features predictive of nicotine dependence. By employing a network-centered approach, we observed that within-network functional connectivity measures offered maximal information for predicting smoking status, as opposed to between-network connectivity, or the representativeness of each individual node with respect to its parent network. Further, our analysis suggests that connectivity measures within the executive control and frontoparietal networks are particularly informative in predicting smoking status. Our findings suggest that machine learning-based approaches to classifying rsFC data offer a valuable alternative technique to understanding large-scale differences in addiction-related neurobiology. PMID:24982629

  16. Independence and Interdependence Predict Health and Wellbeing: Divergent Patterns in the United States and Japan

    PubMed Central

    Kitayama, Shinobu; Karasawa, Mayumi; Curhan, Katherine B.; Ryff, Carol D.; Markus, Hazel Rose

    2010-01-01

    A cross-cultural survey was used to examine two hypotheses designed to link culture to wellbeing and health. The first hypothesis states that people are motivated toward prevalent cultural mandates of either independence (personal control) in the United States or interdependence (relational harmony) in Japan. As predicted, Americans with compromised personal control and Japanese with strained relationships reported high perceived constraint. The second hypothesis holds that people achieve wellbeing and health through actualizing the respective cultural mandates in their modes of being. As predicted, the strongest predictor of wellbeing and health was personal control in the United States, but the absence of relational strain in Japan. All analyses controlled for age, gender, educational attainment, and personality traits. The overall pattern of findings underscores culturally distinct pathways (independent versus interdependent) in achieving the positive life outcomes. PMID:21833228

  17. On the description of conical intersections—A continuous representation of the local topography of seams of conical intersection of three or more electronic states: A generalization of the two state result

    SciTech Connect

    Zhu, Xiaolei Yarkony, David R.

    2014-11-07

    For conical intersections of two states (I,J = I + 1) the vectors defining the branching or g-h plane, the energy difference gradient vector g{sup I,J}, and the interstate coupling vector h{sup I,J}, can be made orthogonal by a one parameter rotation of the degenerate electronic eigenstates. The representation obtained from this rotation is used to construct the parameters that describe the vicinity of the conical intersection seam, the conical parameters, s{sup I,J}{sub x} (R), s{sup I,J}{sub y} (R), g{sup I,J}(R), and h{sup I,J}(R). As a result of the orthogonalization these parameters can be made continuous functions of R, the internuclear coordinates. In this work we generalize this notion to construct continuous parametrizations of conical intersection seams of three or more states. The generalization derives from a recently introduced procedure for using non-degenerate electronic states to construct coupled diabatic states that represent adiabatic states coupled by conical intersections. The procedure is illustrated using the seam of conical intersections of three states in parazolyl as an example.

  18. Braid group representation on quantum computation

    SciTech Connect

    Aziz, Ryan Kasyfil; Muchtadi-Alamsyah, Intan

    2015-09-30

    There are many studies about topological representation of quantum computation recently. One of diagram representation of quantum computation is by using ZX-Calculus. In this paper we will make a diagrammatical scheme of Dense Coding. We also proved that ZX-Calculus diagram of maximally entangle state satisfies Yang-Baxter Equation and therefore, we can construct a Braid Group representation of set of maximally entangle state.

  19. Turbulence Modeling Effects on the Prediction of Equilibrium States of Buoyant Shear Flows

    NASA Technical Reports Server (NTRS)

    Zhao, C. Y.; So, R. M. C.; Gatski, T. B.

    2001-01-01

    The effects of turbulence modeling on the prediction of equilibrium states of turbulent buoyant shear flows were investigated. The velocity field models used include a two-equation closure, a Reynolds-stress closure assuming two different pressure-strain models and three different dissipation rate tensor models. As for the thermal field closure models, two different pressure-scrambling models and nine different temperature variance dissipation rate, Epsilon(0) equations were considered. The emphasis of this paper is focused on the effects of the Epsilon(0)-equation, of the dissipation rate models, of the pressure-strain models and of the pressure-scrambling models on the prediction of the approach to equilibrium turbulence. Equilibrium turbulence is defined by the time rate (if change of the scaled Reynolds stress anisotropic tensor and heat flux vector becoming zero. These conditions lead to the equilibrium state parameters. Calculations show that the Epsilon(0)-equation has a significant effect on the prediction of the approach to equilibrium turbulence. For a particular Epsilon(0)-equation, all velocity closure models considered give an equilibrium state if anisotropic dissipation is accounted for in one form or another in the dissipation rate tensor or in the Epsilon(0)-equation. It is further found that the models considered for the pressure-strain tensor and the pressure-scrambling vector have little or no effect on the prediction of the approach to equilibrium turbulence.

  20. Predictive Models of Resting State Networks for Assessment of Altered Functional Connectivity in MCI

    PubMed Central

    Jiang, Xi; Zhu, Dajiang; Li, Kaiming; Zhang, Tuo; Shen, Dinggang; Guo, Lei; Liu, Tianming

    2014-01-01

    Due to the difficulties in establishing accurate correspondences of brain network nodes across individual subjects, systematic elucidation of possible functional connectivity (FC) alterations in mild cognitive impairment (MCI) compared with normal controls (NC) is a challenging problem. To address this challenge, in this paper, we develop and apply novel predictive models of resting state networks (RSNs) learned from multimodal resting state fMRI (R-fMRI) and DTI data to assess large-scale FC alterations in MCI. Our rationale is that some RSNs in MCI are substantially altered and can hardly be directly compared with those in NC. Instead, structural landmarks derived from DTI data are much more consistent and correspondent across MCI/NC brains, and therefore can be employed to encode RSNs in NC and serve as the predictive models of RSNs for MCI. To derive these predictive models, RSNs in NC are constructed by group-wise ICA clustering and employed to functionally annotate corresponding structural landmarks. Afterwards, these functionally-annotated structural landmarks are predicted in MCI based on DTI data and used to assess FC alterations in MCI. Experimental results demonstrated that the predictive models of RSNs are effective and can comprehensively reveal widespread FC alterations in MCI. PMID:24579199

  1. Geographical information system and predictive risk maps of urinary schistosomiasis in Ogun State, Nigeria

    PubMed Central

    Ekpo, Uwem F; Mafiana, Chiedu F; Adeofun, Clement O; Solarin, Adewale RT; Idowu, Adewumi B

    2008-01-01

    Background The control of urinary schistosomiasis in Ogun State, Nigeria remains inert due to lack of reliable data on the geographical distribution of the disease and the population at risk. To help in developing a control programme, delineating areas of risk, geographical information system and remotely sensed environmental images were used to developed predictive risk maps of the probability of occurrence of the disease and quantify the risk for infection in Ogun State, Nigeria. Methods Infection data used were derived from carefully validated morbidity questionnaires among primary school children in 2001–2002, in which school children were asked among other questions if they have experienced "blood in urine" or urinary schistosomiasis. The infection data from 1,092 schools together with remotely sensed environmental data such as rainfall, vegetation, temperature, soil-types, altitude and land cover were analysis using binary logistic regression models to identify environmental features that influence the spatial distribution of the disease. The final regression equations were then used in Arc View 3.2a GIS software to generate predictive risk maps of the distribution of the disease and population at risk in the state. Results Logistic regression analysis shows that the only significant environmental variable in predicting the presence and absence of urinary schistosomiasis in any area of the State was Land Surface Temperature (LST) (B = 0.308, p = 0.013). While LST (B = -0.478, p = 0.035), rainfall (B = -0.006, p = 0.0005), ferric luvisols (B = 0.539, p = 0.274), dystric nitosols (B = 0.133, p = 0.769) and pellic vertisols (B = 1.386, p = 0.008) soils types were the final variables in the model for predicting the probability of an area having an infection prevalence equivalent to or more than 50%. The two predictive risk maps suggest that urinary schistosomiasis is widely distributed and occurring in all the Local Government Areas (LGAs) in State. The high

  2. Information entrophy via Glauber's Q-representation

    NASA Technical Reports Server (NTRS)

    Keitel, C. H.; Wodkiewicz, K.

    1993-01-01

    We present a convenient way to evaluate the information entropy of a quantum mechanical state via the Glauber Q-representation. As an example we discuss the information entropy of a thermally relaxing squeezed state in terms of its Q-representation and show the validity of the corresponding entropic uncertainty- and Araki-Lieb inequalities.

  3. Prediction of high-dimensional states subject to respiratory motion: a manifold learning approach

    NASA Astrophysics Data System (ADS)

    Liu, Wenyang; Sawant, Amit; Ruan, Dan

    2016-07-01

    The development of high-dimensional imaging systems in image-guided radiotherapy provides important pathways to the ultimate goal of real-time full volumetric motion monitoring. Effective motion management during radiation treatment usually requires prediction to account for system latency and extra signal/image processing time. It is challenging to predict high-dimensional respiratory motion due to the complexity of the motion pattern combined with the curse of dimensionality. Linear dimension reduction methods such as PCA have been used to construct a linear subspace from the high-dimensional data, followed by efficient predictions on the lower-dimensional subspace. In this study, we extend such rationale to a more general manifold and propose a framework for high-dimensional motion prediction with manifold learning, which allows one to learn more descriptive features compared to linear methods with comparable dimensions. Specifically, a kernel PCA is used to construct a proper low-dimensional feature manifold, where accurate and efficient prediction can be performed. A fixed-point iterative pre-image estimation method is used to recover the predicted value in the original state space. We evaluated and compared the proposed method with a PCA-based approach on level-set surfaces reconstructed from point clouds captured by a 3D photogrammetry system. The prediction accuracy was evaluated in terms of root-mean-squared-error. Our proposed method achieved consistent higher prediction accuracy (sub-millimeter) for both 200 ms and 600 ms lookahead lengths compared to the PCA-based approach, and the performance gain was statistically significant.

  4. Prediction of high-dimensional states subject to respiratory motion: a manifold learning approach.

    PubMed

    Liu, Wenyang; Sawant, Amit; Ruan, Dan

    2016-07-01

    The development of high-dimensional imaging systems in image-guided radiotherapy provides important pathways to the ultimate goal of real-time full volumetric motion monitoring. Effective motion management during radiation treatment usually requires prediction to account for system latency and extra signal/image processing time. It is challenging to predict high-dimensional respiratory motion due to the complexity of the motion pattern combined with the curse of dimensionality. Linear dimension reduction methods such as PCA have been used to construct a linear subspace from the high-dimensional data, followed by efficient predictions on the lower-dimensional subspace. In this study, we extend such rationale to a more general manifold and propose a framework for high-dimensional motion prediction with manifold learning, which allows one to learn more descriptive features compared to linear methods with comparable dimensions. Specifically, a kernel PCA is used to construct a proper low-dimensional feature manifold, where accurate and efficient prediction can be performed. A fixed-point iterative pre-image estimation method is used to recover the predicted value in the original state space. We evaluated and compared the proposed method with a PCA-based approach on level-set surfaces reconstructed from point clouds captured by a 3D photogrammetry system. The prediction accuracy was evaluated in terms of root-mean-squared-error. Our proposed method achieved consistent higher prediction accuracy (sub-millimeter) for both 200 ms and 600 ms lookahead lengths compared to the PCA-based approach, and the performance gain was statistically significant. PMID:27299958

  5. Measurements of Gene Expression at Steady State Improve the Predictability of Part Assembly.

    PubMed

    Zhang, Haoqian M; Chen, Shuobing; Shi, Handuo; Ji, Weiyue; Zong, Yeqing; Ouyang, Qi; Lou, Chunbo

    2016-03-18

    Mathematical modeling of genetic circuits generally assumes that gene expression is at steady state when measurements are performed. However, conventional methods of measurement do not necessarily guarantee that this assumption is satisfied. In this study, we reveal a bi-plateau mode of gene expression at the single-cell level in bacterial batch cultures. The first plateau is dynamically active, where gene expression is at steady state; the second plateau, however, is dynamically inactive. We further demonstrate that the predictability of assembled genetic circuits in the first plateau (steady state) is much higher than that in the second plateau where conventional measurements are often performed. By taking the nature of steady state into consideration, our method of measurement promises to directly capture the intrinsic property of biological parts/circuits regardless of circuit-host or circuit-environment interactions. PMID:26652307

  6. Optimal dosing of cancer chemotherapy using model predictive control and moving horizon state/parameter estimation.

    PubMed

    Chen, Tao; Kirkby, Norman F; Jena, Raj

    2012-12-01

    Model predictive control (MPC), originally developed in the community of industrial process control, is a potentially effective approach to optimal scheduling of cancer therapy. The basis of MPC is usually a state-space model (a system of ordinary differential equations), whereby existing studies usually assume that the entire states can be directly measured. This paper aims to demonstrate that when the system states are not fully measurable, in conjunction with model parameter discrepancy, MPC is still a useful method for cancer treatment. This aim is achieved through the application of moving horizon estimation (MHE), an optimisation-based method to jointly estimate the system states and parameters. The effectiveness of the MPC-MHE scheme is illustrated through scheduling the dose of tamoxifen for simulated tumour-bearing patients, and the impact of estimation horizon and magnitude of parameter discrepancy is also investigated. PMID:22739208

  7. Texture Representations Using Subspace Embeddings

    PubMed Central

    Yang, Xiaodong; Tian, YingLi

    2013-01-01

    In this paper, we propose a texture representation framework to map local texture patches into a low-dimensional texture subspace. In natural texture images, textons are entangled with multiple factors, such as rotation, scaling, viewpoint variation, illumination change, and non-rigid surface deformation. Mapping local texture patches into a low-dimensional subspace can alleviate or eliminate these undesired variation factors resulting from both geometric and photometric transformations. We observe that texture representations based on subspace embeddings have strong resistance to image deformations, meanwhile, are more distinctive and more compact than traditional representations. We investigate both linear and non-linear embedding methods including Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Locality Preserving Projections (LPP) to compute the essential texture subspace. The experiments in the context of texture classification on benchmark datasets demonstrate that the proposed subspace embedding representations achieve the state-of-the-art results while with much fewer feature dimensions. PMID:23710105

  8. Texture Representations Using Subspace Embeddings.

    PubMed

    Yang, Xiaodong; Tian, Yingli

    2013-07-15

    In this paper, we propose a texture representation framework to map local texture patches into a low-dimensional texture subspace. In natural texture images, textons are entangled with multiple factors, such as rotation, scaling, viewpoint variation, illumination change, and non-rigid surface deformation. Mapping local texture patches into a low-dimensional subspace can alleviate or eliminate these undesired variation factors resulting from both geometric and photometric transformations. We observe that texture representations based on subspace embeddings have strong resistance to image deformations, meanwhile, are more distinctive and more compact than traditional representations. We investigate both linear and non-linear embedding methods including Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Locality Preserving Projections (LPP) to compute the essential texture subspace. The experiments in the context of texture classification on benchmark datasets demonstrate that the proposed subspace embedding representations achieve the state-of-the-art results while with much fewer feature dimensions. PMID:23710105

  9. A novel thermodynamic model of Mg2SiO4 with a superior representation of experimental data predicts negligible layering in mantle convection

    NASA Astrophysics Data System (ADS)

    Jacobs, M. H.; de Jong, B. H.; van den Berg, A. P.

    2005-12-01

    We present a new thermodynamic database for Mg2SiO4. This novel database has three characteristics (1) thermodynamic properties are anomaly free in the complete temperature-pressure space and experimental data are represented within their experimental uncertainties in accordance with Calphad criteria (2) it discriminates between experimental data (3) it includes thermo-mechanical properties and matches them against tomographic results within experimental uncertainty. Recently [1], we showed that large differences exist between experimental data on ambient volume and between thermal expansivity data for γ-Mg2SiO4, possibly related to hydration effects. We demonstrated that a thermodynamic technique based on polynomial parameterizations of 1 bar thermodynamic properties cannot discriminate between the different ambient volume data and thermal expansivity data for γ-Mg2SiO4, hampering the accurate prediction of bulk sound velocities in the transition zone to within tomographic accuracy. We therefore developed a computational technique based on an extended form of Kieffer's [2] approach to model the vibrational density of states of a substance, a key property to derive the Helmholtz energy. This canonical thermodynamic framework, which uses input parameters from Raman and infrared spectroscopic data, constrains thermodynamic properties tighter compared to methods based on polynomial parameterizations of thermal expansivity, heat capacity and isothermal bulk modulus. We shall present recent results on the application of this approach to the Mg2SiO4 system [3]. We discovered that anharmonicity in Mg2SiO4 (α) affects the heat capacity (CP), and position and slope of the α-β phase boundary. For γ-Mg2SiO4 our thermodynamic analysis prefers the ambient volume measured by Inoue et al. [4] and thermal expansivity measured by Suzuki [5]. Our analysis reveals that experimental data for MgO and MgSiO3 are represented to within experimental uncertainty by assuming that these

  10. Prediction of Outcome after Traumatic Brain Injury: Comparison of Disease State Index and IMPACT Calculator.

    PubMed

    Liedes, Hilkka; Mattila, Jussi; Lingsma, Hester; Lötjönen, Jyrki; Menon, David; Tenovuo, Olli; van Gils, Mark

    2016-01-01

    Traumatic brain injury (TBI) is a major cause of death and disability, especially in young adults. A reliable prediction of outcome after TBI is of great importance in clinical practice and research. We aimed to compare performance of the well-established IMPACT calculator and an alternative method, Disease State Index (DSI), in the prediction of six-month outcome after TBI. Performance of the models was evaluated using 2036 patients with moderate or severe TBI from the International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) database. Prediction performance of both models was similar. The models with more variables provided better performance than the simpler models. This study showed that the DSI is a valid tool with efficient visualizations that can help clinicians with their decision making process in clinical practice. PMID:27225575

  11. First-principles prediction of the equation of state for TcC with rocksalt structure

    NASA Astrophysics Data System (ADS)

    Sun, Xiao-Wei; Chu, Yan-Dong; Liu, Zi-Jiang; Song, Ting; Tian, Jun-Hong; Wei, Xiao-Ping

    2014-10-01

    The equation of state of TcC with rocksalt structure is investigated by means of first-principles density functional theory calculations combined with the quasi-harmonic Debye model in which the phononic effects are considered. Particular attention is paid to the predictions of the compressibility, the isothermal bulk modulus and its first pressure derivative which play a central role in the formulation of approximate equations of state for the first time. The properties of TcC with rocksalt structure are summarized in the pressure range of 0-80 GPa and the temperature up to 2500 K.

  12. Resting-state functional connectivity predicts impulsivity in economic decision-making.

    PubMed

    Li, Nan; Ma, Ning; Liu, Ying; He, Xiao-Song; Sun, De-Lin; Fu, Xian-Ming; Zhang, Xiaochu; Han, Shihui; Zhang, Da-Ren

    2013-03-13

    Increasing neuroimaging evidence suggests an association between impulsive decision-making behavior and task-related brain activity. However, the relationship between impulsivity in decision-making and resting-state brain activity remains unknown. To address this issue, we used functional MRI to record brain activity from human adults during a resting state and during a delay discounting task (DDT) that requires choosing between an immediate smaller reward and a larger delayed reward. In experiment I, we identified four DDT-related brain networks. The money network (the striatum, posterior cingulate cortex, etc.) and the time network (the medial and dorsolateral prefrontal cortices, etc.) were associated with the valuation process; the frontoparietal network and the dorsal anterior cingulate cortex-anterior insular cortex network were related to the choice process. Moreover, we found that the resting-state functional connectivity of the brain regions in these networks was significantly correlated with participants' discounting rate, a behavioral index of impulsivity during the DDT. In experiment II, we tested an independent group of subjects and demonstrated that this resting-state functional connectivity was able to predict individuals' discounting rates. Together, these findings suggest that resting-state functional organization of the human brain may be a biomarker of impulsivity and can predict economic decision-making behavior. PMID:23486959

  13. Predicts the Steady-State Heating and Cooling Performance of Electric Heat Pump

    Energy Science and Technology Software Center (ESTSC)

    1993-01-13

    Oak Ridge National Laboratory (ORNL) is a leader in the development of analytical tools for the design of electrically driven, air-to-air heat pumps. Foremost among these tools is the ORNL Heat Pump Design Model, which can be used to predict the steady-state heating and cooling performance of an electrically driven, air-source heat pump. This version is three to five times faster than the earlier version, easier to use and more versatile.

  14. Predicting drought-induced tree mortality in the western United States

    NASA Astrophysics Data System (ADS)

    Anderegg, W.; Wolf, A.; Shevliakova, E.; Pacala, S. W.

    2015-12-01

    Projected responses of forest ecosystems to warming and drying associated with 21st century climate change vary widely from resiliency to widespread dieback. A major shortcoming of current vegetation models is the inability to account for mortality of overstory trees during extreme drought due to uncertainties in mechanisms and thresholds. In this talk, I discuss two modeling efforts to predict drought-induced tree mortality in the western United States. In the first, we identify a lethal drought threshold in the loss of vascular transport capacity from xylem cavitation, which provides insight into what initiates mortality, in Populus tremuloides in the southwestern United States. We then use the hydraulic-based threshold to produce a hindcast of a drought-induced forest dieback and compare predictions against three independent regional mortality datasets. The hydraulic threshold predicted major regional patterns of tree mortality with high accuracy based on field plots and mortality maps derived from Landsat imagery. Climate model simulations project increasing drought stress in this region that exceeds the observed mortality threshold in the high emissions scenario by the 2050s, likely triggering further widespread diebacks. In the second approach, we build a dynamic plant hydraulic model into a land-surface model and compare predictions against observed mortality patterns across multiple species. These methods provide powerful and tractable approaches for incorporating tree mortality into vegetation models to resolve uncertainty over the fate of forest ecosystems in a changing climate.

  15. Predictive Models of Resting State Networks for Assessment of Altered Functional Connectivity in Mild Cognitive Impairment

    PubMed Central

    Jiang, Xi; Zhu, Dajiang; Li, Kaiming; Zhang, Tuo; Wang, Lihong; Shen, Dinggang; Guo, Lei; Liu, Tianming

    2014-01-01

    Due to the difficulties in establishing correspondences between functional regions across individuals and populations, systematic elucidation of functional connectivity alterations in mild cognitive impairment (MCI) in comparison with normal controls (NC) is still a challenging problem. In this paper, we assessed the functional connectivity alterations in MCI via novel, alternative predictive models of resting state networks (RSNs) learned from multimodal resting state fMRI (R-fMRI) and diffusion tensor imaging (DTI) data. First, ICA-clustering was used to construct RSNs from R-fMRI data in NC group. Second, since the RSNs in MCI are already altered and can hardly be constructed directly from R-fMRI data, structural landmarks derived from DTI data were employed as the predictive models of RSNs for MCI. Third, given that the landmarks are structurally consistent and correspondent across NC and MCI, functional connectivities in MCI were assessed based on the predicted RSNs and compared with those in NC. Experimental results demonstrated that the predictive models of RSNs based on multimodal R-fMRI and DTI data systematically and comprehensively revealed widespread functional connectivity alterations in MCI in comparison with NC. PMID:24293138

  16. Numerical Magnitude Representations Influence Arithmetic Learning

    ERIC Educational Resources Information Center

    Booth, Julie L.; Siegler, Robert S.

    2008-01-01

    This study examined whether the quality of first graders' (mean age = 7.2 years) numerical magnitude representations is correlated with, predictive of, and causally related to their arithmetic learning. The children's pretest numerical magnitude representations were found to be correlated with their pretest arithmetic knowledge and to be…

  17. Efficient online bootstrapping of sensory representations.

    PubMed

    Gepperth, Alexander

    2013-05-01

    This is a simulation-based contribution exploring a novel approach to the open-ended formation of multimodal representations in autonomous agents. In particular, we address the issue of transferring ("bootstrapping") feature selectivities between two modalities, from a previously learned or innate reference representation to a new induced representation. We demonstrate the potential of this algorithm by several experiments with synthetic inputs modeled after a robotics scenario where multimodal object representations are "bootstrapped" from a (reference) representation of object affordances. We focus on typical challenges in autonomous agents: absence of human supervision, changing environment statistics and limited computing power. We propose an autonomous and local neural learning algorithm termed PROPRE (projection-prediction) that updates induced representations based on predictability: competitive advantages are given to those feature-sensitive elements that are inferable from activities in the reference representation. PROPRE implements a bi-directional interaction of clustering ("projection") and inference ("prediction"), the key ingredient being an efficient online measure of predictability controlling learning in the projection step. We show that the proposed method is computationally efficient and stable, and that the multimodal transfer of feature selectivity is successful and robust under resource constraints. Furthermore, we successfully demonstrate robustness to noisy reference representations, non-stationary input statistics and uninformative inputs. PMID:23266481

  18. Predictable internal brain dynamics in EEG and its relation to conscious states

    PubMed Central

    Yoo, Jaewook; Kwon, Jaerock; Choe, Yoonsuck

    2014-01-01

    Consciousness is a complex and multi-faceted phenomenon defying scientific explanation. Part of the reason why this is the case is due to its subjective nature. In our previous computational experiments, to avoid such a subjective trap, we took a strategy to investigate objective necessary conditions of consciousness. Our basic hypothesis was that predictive internal dynamics serves as such a condition. This is in line with theories of consciousness that treat retention (memory), protention (anticipation), and primary impression as the tripartite temporal structure of consciousness. To test our hypothesis, we analyzed publicly available sleep and awake electroencephalogram (EEG) data. Our results show that EEG signals from awake or rapid eye movement (REM) sleep states have more predictable dynamics compared to those from slow-wave sleep (SWS). Since awakeness and REM sleep are associated with conscious states and SWS with unconscious or less consciousness states, these results support our hypothesis. The results suggest an intricate relationship among prediction, consciousness, and time, with potential applications to time perception and neurorobotics. PMID:24917813

  19. Quantitative Prediction of Individual Psychopathology in Trauma Survivors Using Resting-State fMRI

    PubMed Central

    Gong, Qiyong; Li, Lingjiang; Du, Mingying; Pettersson-Yeo, William; Crossley, Nicolas; Yang, Xun; Li, Jing; Huang, Xiaoqi; Mechelli, Andrea

    2014-01-01

    Neuroimaging techniques hold the promise that they may one day aid the clinical assessment of individual psychiatric patients. However, the vast majority of studies published so far have been based on average differences between groups. This study employed a multivariate approach to examine the potential of resting-state functional magnetic resonance imaging (MRI) data for making accurate predictions about psychopathology in survivors of the 2008 Sichuan earthquake at an individual level. Resting-state functional MRI data was acquired for 121 survivors of the 2008 Sichuan earthquake each of whom was assessed for symptoms of post-traumatic stress disorder (PTSD) using the 17-item PTSD Checklist (PCL). Using a multivariate analytical method known as relevance vector regression (RVR), we examined the relationship between resting-state functional MRI data and symptom scores. We found that the use of RVR allowed quantitative prediction of clinical scores with statistically significant accuracy (correlation=0.32, P=0.006; mean squared error=176.88, P=0.001). Accurate prediction was based on functional activation in a number of prefrontal, parietal, and occipital regions. This is the first evidence that neuroimaging techniques may inform the clinical assessment of trauma-exposed individuals by providing an accurate and objective quantitative estimation of psychopathology. Furthermore, the significant contribution of parietal and occipital regions to such estimation challenges the traditional view of PTSD as a disorder specific to the fronto-limbic network. PMID:24064470

  20. Thermodynamic ground state of MgB{sub 6} predicted from first principles structure search methods

    SciTech Connect

    Wang, Hui; Department of Physics and Engineering Physics, University of Saskatchewan, Saskatoon, Saskatchewan S7N 5E2 ; LeBlanc, K. A.; Gao, Bo; Yao, Yansun; Canadian Light Source, Saskatoon, Saskatchewan S7N 0X4

    2014-01-28

    Crystalline structures of magnesium hexaboride, MgB{sub 6}, were investigated using unbiased structure searching methods combined with first principles density functional calculations. An orthorhombic Cmcm structure was predicted as the thermodynamic ground state of MgB{sub 6}. The energy of the Cmcm structure is significantly lower than the theoretical MgB{sub 6} models previously considered based on a primitive cubic arrangement of boron octahedra. The Cmcm structure is stable against the decomposition to elemental magnesium and boron solids at atmospheric pressure and high pressures up to 18.3 GPa. A unique feature of the predicted Cmcm structure is that the boron atoms are clustered into two forms: localized B{sub 6} octahedra and extended B{sub ∞} ribbons. Within the boron ribbons, the electrons are delocalized and this leads to a metallic ground state with vanished electric dipoles. The present prediction is in contrast to the previous proposal that the crystalline MgB{sub 6} maintains a semiconducting state with permanent dipole moments. MgB{sub 6} is estimated to have much weaker electron-phonon coupling compared with that of MgB{sub 2}, and therefore it is not expected to be able to sustain superconductivity at high temperatures.

  1. Use of Landsat data to predict the trophic state of Minnesota lakes

    NASA Technical Reports Server (NTRS)

    Lillesand, T. M.; Johnson, W. L.; Deuell, R. L.; Lindstrom, O. M.; Meisner, D. E.

    1983-01-01

    Near-concurrent Landsat Multispectral Scanner (MSS) and ground data were obtained for 60 lakes distributed in two Landsat scene areas. The ground data included measurement of secchi disk depth, chlorophyll-a, total phosphorous, turbidity, color, and total nitrogen, as well as Carlson Trophic State Index (TSI) values derived from the first three parameters. The Landsat data best correlated with the TSI values. Prediction models were developed to classify some 100 'test' lakes appearing in the two analysis scenes on the basis of TSI estimates. Clouds, wind, poor image data, small lake size, and shallow lake depth caused some problems in lake TSI prediction. Overall, however, the Landsat-predicted TSI estimates were judged to be very reliable for the secchi-derived TSI estimation, moderately reliable for prediction of the chlorophyll-a TSI, and unreliable for the phosphorous value. Numerous Landsat data extraction procedures were compared, and the success of the Landsat TSI prediction models was a strong function of the procedure employed.

  2. Prediction of change in protein unfolding rates upon point mutations in two state proteins.

    PubMed

    Chaudhary, Priyashree; Naganathan, Athi N; Gromiha, M Michael

    2016-09-01

    Studies on protein unfolding rates are limited and challenging due to the complexity of unfolding mechanism and the larger dynamic range of the experimental data. Though attempts have been made to predict unfolding rates using protein sequence-structure information there is no available method for predicting the unfolding rates of proteins upon specific point mutations. In this work, we have systematically analyzed a set of 790 single mutants and developed a robust method for predicting protein unfolding rates upon mutations (Δlnku) in two-state proteins by combining amino acid properties and knowledge-based classification of mutants with multiple linear regression technique. We obtain a mean absolute error (MAE) of 0.79/s and a Pearson correlation coefficient (PCC) of 0.71 between predicted unfolding rates and experimental observations using jack-knife test. We have developed a web server for predicting protein unfolding rates upon mutation and it is freely available at https://www.iitm.ac.in/bioinfo/proteinunfolding/unfoldingrace.html. Prominent features that determine unfolding kinetics as well as plausible reasons for the observed outliers are also discussed. PMID:27264959

  3. Phase-space representation and polarization domains of random electromagnetic fields.

    PubMed

    Castaneda, Roman; Betancur, Rafael; Herrera, Jorge; Carrasquilla, Juan

    2008-08-01

    The phase-space representation of stationary random electromagnetic fields is developed by using electromagnetic spatial coherence wavelets. The propagation of the field's power and states of spatial coherence and polarization results from correlations between the components of the field vectors at pairs of points in space. Polarization domains are theoretically predicted as the structure of the field polarization at the observation plane. In addition, the phase-space representation provides a generalization of the Poynting theorem. Theoretical predictions are examined by numerically simulating the Young experiment with electromagnetic waves. The experimental implementation of these results is a current subject of research. PMID:18670539

  4. Predicting Falls in Parkinson Disease: What Is the Value of Instrumented Testing in OFF Medication State?

    PubMed Central

    Hoskovcová, Martina; Dušek, Petr; Sieger, Tomáš; Brožová, Hana; Zárubová, Kateřina; Bezdíček, Ondřej; Šprdlík, Otakar; Jech, Robert; Štochl, Jan; Roth, Jan; Růžička, Evžen

    2015-01-01

    Background Falls are a common complication of advancing Parkinson's disease (PD). Although numerous risk factors are known, reliable predictors of future falls are still lacking. The objective of this prospective study was to investigate clinical and instrumented tests of balance and gait in both OFF and ON medication states and to verify their utility in the prediction of future falls in PD patients. Methods Forty-five patients with idiopathic PD were examined in defined OFF and ON medication states within one examination day including PD-specific clinical tests, instrumented Timed Up and Go test (iTUG) and computerized dynamic posturography. The same gait and balance tests were performed in 22 control subjects of comparable age and sex. Participants were then followed-up for 6 months using monthly fall diaries and phone calls. Results During the follow-up period, 27/45 PD patients and 4/22 control subjects fell one or more times. Previous falls, fear of falling, more severe motor impairment in the OFF state, higher PD stage, more pronounced depressive symptoms, higher daily levodopa dose and stride time variability in the OFF state were significant risk factors for future falls in PD patients. Increased stride time variability in the OFF state in combination with faster walking cadence appears to be the most significant predictor of future falls, superior to clinical predictors. Conclusion Incorporating instrumented gait measures into the baseline assessment battery as well as accounting for both OFF and ON medication states might improve future fall prediction in PD patients. However, instrumented testing in the OFF state is not routinely performed in clinical practice and has not been used in the development of fall prevention programs in PD. New assessment methods for daylong monitoring of gait, balance and falls are thus required to more effectively address the risk of falling in PD patients. PMID:26443998

  5. Predicting DNA Methylation State of CpG Dinucleotide Using Genome Topological Features and Deep Networks

    NASA Astrophysics Data System (ADS)

    Wang, Yiheng; Liu, Tong; Xu, Dong; Shi, Huidong; Zhang, Chaoyang; Mo, Yin-Yuan; Wang, Zheng

    2016-01-01

    The hypo- or hyper-methylation of the human genome is one of the epigenetic features of leukemia. However, experimental approaches have only determined the methylation state of a small portion of the human genome. We developed deep learning based (stacked denoising autoencoders, or SdAs) software named “DeepMethyl” to predict the methylation state of DNA CpG dinucleotides using features inferred from three-dimensional genome topology (based on Hi-C) and DNA sequence patterns. We used the experimental data from immortalised myelogenous leukemia (K562) and healthy lymphoblastoid (GM12878) cell lines to train the learning models and assess prediction performance. We have tested various SdA architectures with different configurations of hidden layer(s) and amount of pre-training data and compared the performance of deep networks relative to support vector machines (SVMs). Using the methylation states of sequentially neighboring regions as one of the learning features, an SdA achieved a blind test accuracy of 89.7% for GM12878 and 88.6% for K562. When the methylation states of sequentially neighboring regions are unknown, the accuracies are 84.82% for GM12878 and 72.01% for K562. We also analyzed the contribution of genome topological features inferred from Hi-C. DeepMethyl can be accessed at http://dna.cs.usm.edu/deepmethyl/.

  6. Prediction of a neutral noble gas compound in the triplet state.

    PubMed

    Manna, Debashree; Ghosh, Ayan; Ghanty, Tapan K

    2015-05-26

    Discovery of the HArF molecule associated with H-Ar covalent bonding [Nature, 2000, 406, 874-876] has revolutionized the field of noble gas chemistry. In general, this class of noble gas compound involving conventional chemical bonds exists as closed-shell species in a singlet electronic state. For the first time, in a bid to predict neutral noble gas chemical compounds in their triplet electronic state, we have carried out a systematic investigation of xenon inserted FN and FP species by using quantum chemical calculations with density functional theory and various post-Hartree-Fock-based correlated methods, including the multireference configuration interaction technique. The FXeP and FXeN species are predicted to be stable by all the computational methods employed in the present work, such as density functional theory (DFT), second-order Møller-Plesset perturbation theory (MP2), coupled-cluster theory (CCSD(T)), and multireference configuration interaction (MRCI). For the purpose of comparison we have also included the Kr-inserted compounds of FN and FP species. Geometrical parameters, dissociation energies, transition-state barrier heights, atomic charge distributions, vibrational frequency data, and atoms-in-molecules properties clearly indicate that it is possible to experimentally realize the most stable state of FXeP and FXeN molecules, which is triplet in nature, through the matrix isolation technique under cryogenic conditions. PMID:25891838

  7. Predicting DNA Methylation State of CpG Dinucleotide Using Genome Topological Features and Deep Networks.

    PubMed

    Wang, Yiheng; Liu, Tong; Xu, Dong; Shi, Huidong; Zhang, Chaoyang; Mo, Yin-Yuan; Wang, Zheng

    2016-01-01

    The hypo- or hyper-methylation of the human genome is one of the epigenetic features of leukemia. However, experimental approaches have only determined the methylation state of a small portion of the human genome. We developed deep learning based (stacked denoising autoencoders, or SdAs) software named "DeepMethyl" to predict the methylation state of DNA CpG dinucleotides using features inferred from three-dimensional genome topology (based on Hi-C) and DNA sequence patterns. We used the experimental data from immortalised myelogenous leukemia (K562) and healthy lymphoblastoid (GM12878) cell lines to train the learning models and assess prediction performance. We have tested various SdA architectures with different configurations of hidden layer(s) and amount of pre-training data and compared the performance of deep networks relative to support vector machines (SVMs). Using the methylation states of sequentially neighboring regions as one of the learning features, an SdA achieved a blind test accuracy of 89.7% for GM12878 and 88.6% for K562. When the methylation states of sequentially neighboring regions are unknown, the accuracies are 84.82% for GM12878 and 72.01% for K562. We also analyzed the contribution of genome topological features inferred from Hi-C. DeepMethyl can be accessed at http://dna.cs.usm.edu/deepmethyl/. PMID:26797014

  8. Predicting DNA Methylation State of CpG Dinucleotide Using Genome Topological Features and Deep Networks

    PubMed Central

    Wang, Yiheng; Liu, Tong; Xu, Dong; Shi, Huidong; Zhang, Chaoyang; Mo, Yin-Yuan; Wang, Zheng

    2016-01-01

    The hypo- or hyper-methylation of the human genome is one of the epigenetic features of leukemia. However, experimental approaches have only determined the methylation state of a small portion of the human genome. We developed deep learning based (stacked denoising autoencoders, or SdAs) software named “DeepMethyl” to predict the methylation state of DNA CpG dinucleotides using features inferred from three-dimensional genome topology (based on Hi-C) and DNA sequence patterns. We used the experimental data from immortalised myelogenous leukemia (K562) and healthy lymphoblastoid (GM12878) cell lines to train the learning models and assess prediction performance. We have tested various SdA architectures with different configurations of hidden layer(s) and amount of pre-training data and compared the performance of deep networks relative to support vector machines (SVMs). Using the methylation states of sequentially neighboring regions as one of the learning features, an SdA achieved a blind test accuracy of 89.7% for GM12878 and 88.6% for K562. When the methylation states of sequentially neighboring regions are unknown, the accuracies are 84.82% for GM12878 and 72.01% for K562. We also analyzed the contribution of genome topological features inferred from Hi-C. DeepMethyl can be accessed at http://dna.cs.usm.edu/deepmethyl/. PMID:26797014

  9. Low-dimensional Representation of Error Covariance

    NASA Technical Reports Server (NTRS)

    Tippett, Michael K.; Cohn, Stephen E.; Todling, Ricardo; Marchesin, Dan

    2000-01-01

    Ensemble and reduced-rank approaches to prediction and assimilation rely on low-dimensional approximations of the estimation error covariances. Here stability properties of the forecast/analysis cycle for linear, time-independent systems are used to identify factors that cause the steady-state analysis error covariance to admit a low-dimensional representation. A useful measure of forecast/analysis cycle stability is the bound matrix, a function of the dynamics, observation operator and assimilation method. Upper and lower estimates for the steady-state analysis error covariance matrix eigenvalues are derived from the bound matrix. The estimates generalize to time-dependent systems. If much of the steady-state analysis error variance is due to a few dominant modes, the leading eigenvectors of the bound matrix approximate those of the steady-state analysis error covariance matrix. The analytical results are illustrated in two numerical examples where the Kalman filter is carried to steady state. The first example uses the dynamics of a generalized advection equation exhibiting nonmodal transient growth. Failure to observe growing modes leads to increased steady-state analysis error variances. Leading eigenvectors of the steady-state analysis error covariance matrix are well approximated by leading eigenvectors of the bound matrix. The second example uses the dynamics of a damped baroclinic wave model. The leading eigenvectors of a lowest-order approximation of the bound matrix are shown to approximate well the leading eigenvectors of the steady-state analysis error covariance matrix.

  10. Forced synchronization of large-scale circulation to increase predictability of surface states

    NASA Astrophysics Data System (ADS)

    Shen, Mao-Lin; Keenlyside, Noel; Selten, Frank; Wiegerinck, Wim; Duane, Gregory

    2016-04-01

    Numerical models are key tools in the projection of the future climate change. The lack of perfect initial condition and perfect knowledge of the laws of physics, as well as inherent chaotic behavior limit predictions. Conceptually, the atmospheric variables can be decomposed into a predictable component (signal) and an unpredictable component (noise). In ensemble prediction the anomaly of ensemble mean is regarded as the signal and the ensemble spread the noise. Naturally the prediction skill will be higher if the signal-to-noise ratio (SNR) is larger in the initial conditions. We run two ensemble experiments in order to explore a way to reduce the SNR of surface winds and temperature. One ensemble experiment is AGCM with prescribing sea surface temperature (SST); the other is AGCM with both prescribing SST and nudging the high-level temperature and winds to ERA-Interim. Each ensemble has 30 members. Larger SNR is expected and found over the tropical ocean in the first experiment because the tropical circulation is associated with the convection and the associated surface wind convergence as these are to a large extent driven by the SST. However, small SNR is found over high latitude ocean and land surface due to the chaotic and non-synchronized atmosphere states. In the second experiment the higher level temperature and winds are forced to be synchronized (nudged to reanalysis) and hence a larger SNR of surface winds and temperature is expected. Furthermore, different nudging coefficients are also tested in order to understand the limitation of both synchronization of large-scale circulation and the surface states. These experiments will be useful for the developing strategies to synchronize the 3-D states of atmospheric models that can be later used to build a super model.

  11. What Cognitive Representations Support Primate Theory of Mind?

    PubMed

    Martin, Alia; Santos, Laurie R

    2016-05-01

    Much recent work has examined the evolutionary origins of human mental state representations. This work has yielded strikingly consistent results: primates show a sophisticated ability to track the current and past perceptions of others, but they fail to represent the beliefs of others. We offer a new account of the nuanced performance of primates in theory of mind (ToM) tasks. We argue that primates form awareness relations tracking the aspects of reality that other agents are aware of. We contend that these awareness relations allow primates to make accurate predictions in social situations, but that this capacity falls short of our human-like representational ToM. We end by explaining how this new account makes important new empirical predictions about primate ToM. PMID:27052723

  12. Predicting tree diversity across the United States as a function of modeled gross primary production.

    PubMed

    Nightingale, Joanne M; Fan, Weihong; Coops, Nicholas C; Waring, Richard H

    2008-01-01

    At the regional and continental scale, ecologists have theorized that spatial variation in biodiversity can be interpreted as a response to differences in climate. To test this theory we assumed that ecological constraints associated with current climatic conditions (2000-2004) might best be correlated with tree richness if expressed through satellite-derived measures of gross primary production (GPP), rather than the more commonly used, but less consistently derived, net primary production. To evaluate current patterns in tree diversity across the contiguous United States we acquired information on tree composition from the USDA Forest Service's Forest Inventory and Analysis program that represented more than 17,4000 survey plots. We selected 2693 cells of 1000 km2 within which a sufficient number of plots were available to estimate tree richness per hectare. Our estimates of forest productivity varied from simple vegetation indices indicative of the fraction of light intercepted by canopies at 16-d intervals, a product from the MODIS (Moderate Resolution Imaging Spectro-radiometer), to 8- and 10-d GPP products derived with minimal climatic data (MODIS) and SPOT-Vegetation (Systeme Pour l'Observation de la Terre), to 3-PGS (Physiological Principles Predicting Growth with Satellites), which requires both climate and soil data. Across the contiguous United States, modeled predictions of gross productivity accounted for between 51% and 77% of the recorded spatial variation in tree diversity, which ranged from 2 to 67 species per hectare. When the analyses were concentrated within nine broadly defined ecoregions, predictive relations largely disappeared. Only 3-PGS predictions fit a theorized unimodal function by being able to distinguish highly productive forests in the Pacific Northwest that support lower than expected tree diversity. Other models predicted a continuous steep rise in tree diversity with increasing productivity, and did so with generally better or

  13. Laser Hardening Prediction Tool Based On a Solid State Transformations Numerical Model

    SciTech Connect

    Martinez, S.; Ukar, E.; Lamikiz, A.

    2011-01-17

    This paper presents a tool to predict hardening layer in selective laser hardening processes where laser beam heats the part locally while the bulk acts as a heat sink.The tool to predict accurately the temperature field in the workpiece is a numerical model that combines a three dimensional transient numerical solution for heating where is possible to introduce different laser sources. The thermal field was modeled using a kinetic model based on Johnson-Mehl-Avrami equation. Considering this equation, an experimental adjustment of transformation parameters was carried out to get the heating transformation diagrams (CHT). With the temperature field and CHT diagrams the model predicts the percentage of base material converted into austenite. These two parameters are used as first step to estimate the depth of hardened layer in the part.The model has been adjusted and validated with experimental data for DIN 1.2379, cold work tool steel typically used in mold and die making industry. This steel presents solid state diffusive transformations at relative low temperature. These transformations must be considered in order to get good accuracy of temperature field prediction during heating phase. For model validation, surface temperature measured by pyrometry, thermal field as well as the hardened layer obtained from metallographic study, were compared with the model data showing a good adjustment.

  14. Gender stereotype endorsement differentially predicts girls' and boys' trait-state discrepancy in math anxiety

    PubMed Central

    Bieg, Madeleine; Goetz, Thomas; Wolter, Ilka; Hall, Nathan C.

    2015-01-01

    Mathematics is associated with anxiety for many students; an emotion linked to lower well-being and poorer learning outcomes. While findings typically show females to report higher trait math anxiety than males, no gender differences have to date been found in state (i.e., momentary) math anxiety. The present diary study aimed to replicate previous findings in investigating whether levels of academic self-concept was related to this discrepancy in trait vs. state anxiety measures. Additionally, mathematics-related gender stereotype endorsement (mathematics is a male domain) was investigated as an additional predictor of the trait-state discrepancy. The sample included 755 German 9th and 10th graders who completed self-report measures of trait math anxiety, math self-concept, and gender stereotype endorsement, in addition to state measures of anxiety after math classes by use of a standardized diary for 2–3 weeks (Nwithin = 6207). As expected, females reported higher trait math anxiety but no gender differences were found for state math anxiety. Also in line with our assumptions, multilevel analyses showed the discrepancy between trait and state anxiety to be negatively related to students' self-concept (i.e., a lower discrepancy for students with higher self-concepts). Furthermore, gender stereotype endorsement differentially predicted the trait-state discrepancy: When controlling for self-concept in mathematics, females who endorsed the gender stereotype of math being a male domain more strongly overestimated their trait math anxiety as compared to their state anxiety whereas this effect was not significant for males. The present findings suggest that gender stereotype endorsement plays an important role in explaining gender differences in math anxiety above and beyond academic self-concept. Implications for future research and educational practice are discussed. PMID:26441778

  15. A STATE-VARIABLE APPROACH FOR PREDICTING THE TIME REQUIRED FOR 50% RECRYSTALLIZATION

    SciTech Connect

    M. STOUT; ET AL

    2000-08-01

    It is important to be able to model the recrystallization kinetics in aluminum alloys during hot deformation. The industrial relevant process of hot rolling is an example of where the knowledge of whether or not a material recrystallizes is critical to making a product with the correct properties. Classically, the equations that describe the kinetics of recrystallization predict the time to 50% recrystallization. These equations are largely empirical; they are based on the free energy for recrystallization, a Zener-Holloman parameter, and have several adjustable exponents to fit the equation to engineering data. We have modified this form of classical theory replacing the Zener-Hollomon parameter with a deformation energy increment, a free energy available to drive recrystallization. The advantage of this formulation is that the deformation energy increment is calculated based on the previously determined temperature and strain-rate sensitivity of the constitutive response. We modeled the constitutive response of the AA5182 aluminum using a state variable approach, the value of the state variable is a function of the temperature and strain-rate history of deformation. Thus, the recrystallization kinetics is a function of only the state variable and free energy for recrystallization. There are no adjustable exponents as in classical theory. Using this approach combined with engineering recrystallization data we have been able to predict the kinetics of recrystallization in AA5182 as a function of deformation strain rate and temperature.

  16. Transient and steady state dynamic behaviour of single cylinder compressors: prediction and experiments

    NASA Astrophysics Data System (ADS)

    Dufour, R.; Der Hagopian, J.; Lalanne, M.

    1995-03-01

    Single cylinder reciprocating compressors used in cooling appliances have sudden starts and stops which are sources of significant mechanical problems. Thus a method for predicting the entire motion is necessary to improve compressor design. The present study is mainly concerned with equations, computer code and experimental investigations. The speed of rotation of the crankshaft and time response of the compressor unit are of particular interest especially during the transient motion: start-up and shut-down. Despite measurements carried out in a hostile environment and difficulties in obtaining accurate knowledge of parameters such as friction, driven torque and relative pressure, the predicted and measured results are in good agreement, particularly those concerning the start-up and steady state motions.

  17. Reliance on functional resting-state network for stable task control predicts behavioral tendency for cooperation.

    PubMed

    Hahn, Tim; Notebaert, Karolien; Anderl, Christine; Reicherts, Philipp; Wieser, Matthias; Kopf, Juliane; Reif, Andreas; Fehl, Katrin; Semmann, Dirk; Windmann, Sabine

    2015-09-01

    Humans display individual variability in cooperative behavior. While an ever-growing body of research has investigated the neural correlates of task-specific cooperation, the mechanisms by which situation-independent, stable differences in cooperation render behavior consistent across a wide range of situations remain elusive. Addressing this issue, we show that the individual tendency to behave in a prosocial or individualistic manner can be predicted from the functional resting-state connectome. More specifically, connections of the cinguloopercular network which supports goal-directed behavior encode cooperative tendency. Effects of virtual lesions to this network on the efficacy of information exchange throughout the brain corroborate our findings. These results shed light on the neural mechanisms underlying individualists' and prosocials' habitual social decisions by showing that reliance on the cinguloopercular task-control network predicts stable cooperative behavior. Based on this evidence, we provide a unifying framework for the interpretation of functional imaging and behavioral studies of cooperative behavior. PMID:26070266

  18. A comparison of methods to predict historical daily streamflow time series in the southeastern United States

    USGS Publications Warehouse

    Farmer, William H.; Archfield, Stacey A.; Over, Thomas M.; Hay, Lauren E.; LaFontaine, Jacob H.; Kiang, Julie E.

    2015-01-01

    Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water. Streamgages cannot be installed at every location where streamflow information is needed. As part of its National Water Census, the U.S. Geological Survey is planning to provide streamflow predictions for ungaged locations. In order to predict streamflow at a useful spatial and temporal resolution throughout the Nation, efficient methods need to be selected. This report examines several methods used for streamflow prediction in ungaged basins to determine the best methods for regional and national implementation. A pilot area in the southeastern United States was selected to apply 19 different streamflow prediction methods and evaluate each method by a wide set of performance metrics. Through these comparisons, two methods emerged as the most generally accurate streamflow prediction methods: the nearest-neighbor implementations of nonlinear spatial interpolation using flow duration curves (NN-QPPQ) and standardizing logarithms of streamflow by monthly means and standard deviations (NN-SMS12L). It was nearly impossible to distinguish between these two methods in terms of performance. Furthermore, neither of these methods requires significantly more parameterization in order to be applied: NN-SMS12L requires 24 regional regressions—12 for monthly means and 12 for monthly standard deviations. NN-QPPQ, in the application described in this study, required 27 regressions of particular quantiles along the flow duration curve. Despite this finding, the results suggest that an optimal streamflow prediction method depends on the intended application. Some methods are stronger overall, while some methods may be better at predicting particular statistics. The methods of analysis presented here reflect a possible framework for continued analysis and comprehensive multiple comparisons of methods of prediction in ungaged basins (PUB

  19. A state-based approach to trend recognition and failure prediction for the Space Station Freedom

    NASA Technical Reports Server (NTRS)

    Nelson, Kyle S.; Hadden, George D.

    1992-01-01

    A state-based reasoning approach to trend recognition and failure prediction for the Altitude Determination, and Control System (ADCS) of the Space Station Freedom (SSF) is described. The problem domain is characterized by features (e.g., trends and impending failures) that develop over a variety of time spans, anywhere from several minutes to several years. Our state-based reasoning approach, coupled with intelligent data screening, allows features to be tracked as they develop in a time-dependent manner. That is, each state machine has the ability to encode a time frame for the feature it detects. As features are detected, they are recorded and can be used as input to other state machines, creating a hierarchical feature recognition scheme. Furthermore, each machine can operate independently of the others, allowing simultaneous tracking of features. State-based reasoning was implemented in the trend recognition and the prognostic modules of a prototype Space Station Freedom Maintenance and Diagnostic System (SSFMDS) developed at Honeywell's Systems and Research Center.

  20. On the predictions of the 11B solid state NMR parameters

    NASA Astrophysics Data System (ADS)

    Czernek, Jiří; Brus, Jiří

    2016-07-01

    The set of boron containing compounds has been subject to the prediction of the 11B solid state NMR spectral parameters using DFT-GIPAW methods properly treating the solid phase effects. The quantification of the differences between measured and theoretical values has been presented, which is directly applicable in structural studies involving 11B nuclei. In particular, a simple scheme has been proposed, which is expected to provide for an estimate of the 11B chemical shift within ±2.0 ppm from the experimental value. The computer program, INFOR, enabling the visualization of concomitant Euler rotations related to the tensorial transformations has been presented.

  1. Internal state variable approach for predicting stiffness reductions in fibrous laminated composites with matrix cracks

    NASA Technical Reports Server (NTRS)

    Lee, Jong-Won; Allen, D. H.; Harris, C. E.

    1989-01-01

    A mathematical model utilizing the internal state variable concept is proposed for predicting the upper bound of the reduced axial stiffnesses in cross-ply laminates with matrix cracks. The axial crack opening displacement is explicitly expressed in terms of the observable axial strain and the undamaged material properties. A crack parameter representing the effect of matrix cracks on the observable axial Young's modulus is calculated for glass/epoxy and graphite/epoxy material systems. The results show that the matrix crack opening displacement and the effective Young's modulus depend not on the crack length, but on its ratio to the crack spacing.

  2. Precise QCD Predictions for the Production of Dijet Final States in Deep Inelastic Scattering.

    PubMed

    Currie, James; Gehrmann, Thomas; Niehues, Jan

    2016-07-22

    The production of two-jet final states in deep inelastic scattering is an important QCD precision observable. We compute it for the first time to next-to-next-to-leading order (NNLO) in perturbative QCD. Our calculation is fully differential in the lepton and jet variables and allows one to impose cuts on the jets in both the laboratory and the Breit frame. We observe that the NNLO corrections are moderate in size, except at kinematical edges, and that their inclusion leads to a substantial reduction of the scale variation uncertainty on the predictions. Our results will enable the inclusion of deep inelastic dijet data in precision phenomenology studies. PMID:27494466

  3. Precise QCD Predictions for the Production of Dijet Final States in Deep Inelastic Scattering

    NASA Astrophysics Data System (ADS)

    Currie, James; Gehrmann, Thomas; Niehues, Jan

    2016-07-01

    The production of two-jet final states in deep inelastic scattering is an important QCD precision observable. We compute it for the first time to next-to-next-to-leading order (NNLO) in perturbative QCD. Our calculation is fully differential in the lepton and jet variables and allows one to impose cuts on the jets in both the laboratory and the Breit frame. We observe that the NNLO corrections are moderate in size, except at kinematical edges, and that their inclusion leads to a substantial reduction of the scale variation uncertainty on the predictions. Our results will enable the inclusion of deep inelastic dijet data in precision phenomenology studies.

  4. Can we predict seasonal changes in high impact weather in the United States?

    NASA Astrophysics Data System (ADS)

    Jung, Eunsil; Kirtman, Ben P.

    2016-07-01

    Severe convective storms cause catastrophic losses each year in the United States, suggesting that any predictive capability is of great societal benefit. While it is known that El Niño and the Southern Oscillation (ENSO) influence high impact weather events, such as a tornado activity and severe storms, in the US during early spring, this study highlights that the influence of ENSO on US severe storm characteristics is weak during May–July. Instead, warm water in the Gulf of Mexico is a potential predictor for moist instability, which is an important factor in influencing the storm characteristics in the US during May–July.

  5. Resting-state functional connectivity predicts longitudinal change in autistic traits and adaptive functioning in autism.

    PubMed

    Plitt, Mark; Barnes, Kelly Anne; Wallace, Gregory L; Kenworthy, Lauren; Martin, Alex

    2015-12-01

    Although typically identified in early childhood, the social communication symptoms and adaptive behavior deficits that are characteristic of autism spectrum disorder (ASD) persist throughout the lifespan. Despite this persistence, even individuals without cooccurring intellectual disability show substantial heterogeneity in outcomes. Previous studies have found various behavioral assessments [such as intelligence quotient (IQ), early language ability, and baseline autistic traits and adaptive behavior scores] to be predictive of outcome, but most of the variance in functioning remains unexplained by such factors. In this study, we investigated to what extent functional brain connectivity measures obtained from resting-state functional connectivity MRI (rs-fcMRI) could predict the variance left unexplained by age and behavior (follow-up latency and baseline autistic traits and adaptive behavior scores) in two measures of outcome--adaptive behaviors and autistic traits at least 1 y postscan (mean follow-up latency = 2 y, 10 mo). We found that connectivity involving the so-called salience network (SN), default-mode network (DMN), and frontoparietal task control network (FPTCN) was highly predictive of future autistic traits and the change in autistic traits and adaptive behavior over the same time period. Furthermore, functional connectivity involving the SN, which is predominantly composed of the anterior insula and the dorsal anterior cingulate, predicted reliable improvement in adaptive behaviors with 100% sensitivity and 70.59% precision. From rs-fcMRI data, our study successfully predicted heterogeneity in outcomes for individuals with ASD that was unaccounted for by simple behavioral metrics and provides unique evidence for networks underlying long-term symptom abatement. PMID:26627261

  6. Resting-state functional connectivity predicts longitudinal change in autistic traits and adaptive functioning in autism

    PubMed Central

    Plitt, Mark; Barnes, Kelly Anne; Wallace, Gregory L.; Kenworthy, Lauren; Martin, Alex

    2015-01-01

    Although typically identified in early childhood, the social communication symptoms and adaptive behavior deficits that are characteristic of autism spectrum disorder (ASD) persist throughout the lifespan. Despite this persistence, even individuals without cooccurring intellectual disability show substantial heterogeneity in outcomes. Previous studies have found various behavioral assessments [such as intelligence quotient (IQ), early language ability, and baseline autistic traits and adaptive behavior scores] to be predictive of outcome, but most of the variance in functioning remains unexplained by such factors. In this study, we investigated to what extent functional brain connectivity measures obtained from resting-state functional connectivity MRI (rs-fcMRI) could predict the variance left unexplained by age and behavior (follow-up latency and baseline autistic traits and adaptive behavior scores) in two measures of outcome—adaptive behaviors and autistic traits at least 1 y postscan (mean follow-up latency = 2 y, 10 mo). We found that connectivity involving the so-called salience network (SN), default-mode network (DMN), and frontoparietal task control network (FPTCN) was highly predictive of future autistic traits and the change in autistic traits and adaptive behavior over the same time period. Furthermore, functional connectivity involving the SN, which is predominantly composed of the anterior insula and the dorsal anterior cingulate, predicted reliable improvement in adaptive behaviors with 100% sensitivity and 70.59% precision. From rs-fcMRI data, our study successfully predicted heterogeneity in outcomes for individuals with ASD that was unaccounted for by simple behavioral metrics and provides unique evidence for networks underlying long-term symptom abatement. PMID:26627261

  7. One dimensional representations in quantum optics

    NASA Technical Reports Server (NTRS)

    Janszky, J.; Adam, P.; Foldesi, I.; Vinogradov, An. V.

    1993-01-01

    The possibility of representing the quantum states of a harmonic oscillator not on the whole alpha-plane but on its one dimensional manifolds is considered. It is shown that a simple Gaussian distribution along a straight line describes a quadrature squeezed state while a similar Gaussian distribution along a circle leads to the amplitude squeezed state. The connection between the one dimensional representations and the usual Glauber representation is discussed.

  8. Predicting Streamflow in the Southeastern United States using Climate and Tree Ring Data

    NASA Astrophysics Data System (ADS)

    Patskoski, J. M.; Arumugam, S.

    2011-12-01

    An accurate forecast of streamflow can provide valuable information to reservoir management. If an accurate forecast can be for the upcoming year, a management company can alter the releases of the reservoir to reduce flood risk or increase water supply efficiency based on if the forecasted streamflow will be higher or lower than the average year. To predict the streamflow, this project will use Nino 3.4 sea surface temperatures and tree ring data. Streamflow is driven by precipitation in two ways. The first way is through direct runoff into rivers. The other way is the infiltration of precipitation into the groundwater. The groundwater then recharges into rivers. In the Southeastern United States, the precipitation is affected mostly by sea surface temperatures and more specifically Nino 3.4. Since Nino 3.4 is periodic with a frequency of five to seven years, the streamflow in the Southeast is also has a periodic component with the same frequency. Singular Spectrum Analysis was performed on streamflow to separate it into periodic and non-periodic components. The periodic component of the streamflow was predicted directly by Nino 3.4 data and Nino 3.4 forecasts. Tree ring data was used to predict the non-periodic component of the streamflow. This was done because tree rings indicate the amount of ground water storage for a given year and only that year. Singular Spectrum Analysis was performed on the tree ring data and only the non-periodic components were used to predict the non-periodic components of the streamflow. This was done so that the effects of Nino 3.4 on the tree rings were not used to predict the portion of streamflow not affected by Nino 3.4. Once the periodic and non-periodic components were predicted, they were added together to form the forecast for the streamflow. This model was analyzed using several sites over the southeast and tested against using the previous year's streamflow data to predict the streamflow.

  9. Prediction of protein secondary structure based on residue pair types and conformational states using dynamic programming algorithm.

    PubMed

    Sadeghi, Mehdi; Parto, Sahar; Arab, Shahriar; Ranjbar, Bijan

    2005-06-20

    We have used a statistical approach for protein secondary structure prediction based on information theory and simultaneously taking into consideration pairwise residue types and conformational states. Since the prediction of residue secondary structure by one residue window sliding make ambiguity in state prediction, we used a dynamic programming algorithm to find the path with maximum score. A score system for residue pairs in particular conformations is derived for adjacent neighbors up to ten residue apart in sequence. The three state overall per-residue accuracy, Q3, of this method in a jackknife test with dataset created from PDBSELECT is more than 70%. PMID:15936021

  10. Risk Recognition, Attachment Anxiety, Self-Efficacy, and State Dissociation Predict Revictimization

    PubMed Central

    Bockers, Estelle; Roepke, Stefan; Michael, Lars; Renneberg, Babette; Knaevelsrud, Christine

    2014-01-01

    Background Previous research has identified a number of variables that constitute potential risk factors for victimization and revictimization. However, it remains unclear which factors are associated not only with childhood or adolescent victimization, but specifically with revictimization. The aim of this study was to determine whether risk recognition ability and other variables previously associated with revictimization are specifically able to differentiate individuals with childhood victimization only from revictimized individuals, and thus to predict revictimization. Methods Participants were N = 85 women aged 21 to 64 years who were interpersonally victimized in childhood or adolescence only, interpersonally revictimized in another period of life, or not victimized. A logistic regression analysis was conducted to examine whether risk recognition ability, sensation seeking, self-efficacy, state dissociation, shame, guilt, assertiveness, and attachment anxiety predicted group membership. Results The logistic regression analysis revealed risk recognition ability, attachment anxiety, state dissociation, and self-efficacy as significant predictors of revictimization. The final model accurately classified 82.4% of revictimized, 59.1% of victimized and 93.1% of non-victimized women. The overall classification rate was 80%. Conclusions This study suggests that risk recognition ability, attachment anxiety, self-efficacy, and state dissociation play a key role in revictimization. Increased risk recognition ability after an interpersonal trauma may act as a protective factor against repeated victimization that revictimized individuals may lack. A lack of increased risk recognition ability in combination with higher attachment anxiety, lower self-efficacy, and higher state dissociation may increase the risk of revictimization. PMID:25238153

  11. 10 CFR 60.65 - Representation.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 10 Energy 2 2011-01-01 2011-01-01 false Representation. 60.65 Section 60.65 Energy NUCLEAR REGULATORY COMMISSION (CONTINUED) DISPOSAL OF HIGH-LEVEL RADIOACTIVE WASTES IN GEOLOGIC REPOSITORIES Participation by State Governments and Affected Indian Tribes § 60.65 Representation. Any person who acts...

  12. 10 CFR 60.65 - Representation.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 10 Energy 2 2012-01-01 2012-01-01 false Representation. 60.65 Section 60.65 Energy NUCLEAR REGULATORY COMMISSION (CONTINUED) DISPOSAL OF HIGH-LEVEL RADIOACTIVE WASTES IN GEOLOGIC REPOSITORIES Participation by State Governments and Affected Indian Tribes § 60.65 Representation. Any person who acts...

  13. 10 CFR 60.65 - Representation.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 10 Energy 2 2013-01-01 2013-01-01 false Representation. 60.65 Section 60.65 Energy NUCLEAR REGULATORY COMMISSION (CONTINUED) DISPOSAL OF HIGH-LEVEL RADIOACTIVE WASTES IN GEOLOGIC REPOSITORIES Participation by State Governments and Affected Indian Tribes § 60.65 Representation. Any person who acts...

  14. 10 CFR 60.65 - Representation.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 10 Energy 2 2014-01-01 2014-01-01 false Representation. 60.65 Section 60.65 Energy NUCLEAR REGULATORY COMMISSION (CONTINUED) DISPOSAL OF HIGH-LEVEL RADIOACTIVE WASTES IN GEOLOGIC REPOSITORIES Participation by State Governments and Affected Indian Tribes § 60.65 Representation. Any person who acts...

  15. 10 CFR 60.65 - Representation.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 10 Energy 2 2010-01-01 2010-01-01 false Representation. 60.65 Section 60.65 Energy NUCLEAR REGULATORY COMMISSION (CONTINUED) DISPOSAL OF HIGH-LEVEL RADIOACTIVE WASTES IN GEOLOGIC REPOSITORIES Participation by State Governments and Affected Indian Tribes § 60.65 Representation. Any person who acts...

  16. Precedence relationship representations of mechanical assembly sequences

    NASA Technical Reports Server (NTRS)

    Homendemello, L. S.; Sanderson, A. C.

    1989-01-01

    Two types of precedence relationship representations for mechanical assembly sequences are presented: precedence relationships between the establishment of one connection between two parts and the establishment of another connection, and precedence relationships between the establishment of one connection and states of the assembly process. Precedence relationship representations have the advantage of being very compact. The problem with these representations was how to guarantee their correctness and completeness. Two theorems are presented each of which leads to the generation of one type of precedence relationship representation guaranteeing its correctness and completeness for a class of assemblies.

  17. Prediction of a metastable cubic phase for the transition metals with hcp ground state.

    NASA Astrophysics Data System (ADS)

    de Coss, Romeo; Aguayo, Aaron; Murrieta, Gabriel

    2007-03-01

    The discovery of a metastable phase for a given material is interesting because corresponds to a new bonding and new properties are expected. The calculation of the total-energy along the Bain path is frequently used as a method to find tetragonal metastable states. However, a local minimum in the tetragonal distortion is not a definitive proof of a metastable state, and the elastic stability needs to be evaluated. In a previous work, using the elastic stability criteria for a cubic structure, we have shown that the transition metals with hcp ground state; Ti, Zr, and Hf have a fcc metastable phase [Aguayo, G. Murrieta, and R. de Coss, Phys. Rev. B 65, 092106 (2002)]. That result is interesting since the fcc crystal structure does not appear in the current pressure-temperature phase diagram of these metals, and support the experimental observations of fcc Ti and Zr in thin films. In the present work, we extend the elastic stability study of the fcc structure to the non-magnetic transition metals with hcp ground state; Sc, Ti, Y, Zr, Tc, Ru, Hf, Re, and Os. We find that all the metals involved in this study have a metastable fcc structure. From these results, substrates on which the fcc structure of these metals could be growth epitaxially are predicted.

  18. Shrinkage prediction of seed-voxel brain connectivity using resting state fMRI

    PubMed Central

    Shou, Haochang; Eloyan, Ani; Nebel, Mary Beth; Mejia, Amanda; Pekar, James J.; Mostofsky, Stewart; Caffo, Brian; Lindquist, Martin A.; Crainiceanu, Ciprian M.

    2014-01-01

    Resting-state functional magnetic resonance imaging (rs-fMRI) is used to investigate synchronous activations in spatially distinct regions of the brain, which are thought to reflect functional systems supporting cognitive processes. Analyses are often performed using seed-based correlation analysis, allowing researchers to explore functional connectivity between data in a seed region and the rest of the brain. Using scan–rescan rs-fMRI data, we investigate how well the subject-specific seed-based correlation map from the second replication of the study can be predicted using data from the first replication. We show that one can dramatically improve prediction of subject-specific connectivity by borrowing strength from the group correlation map computed using all other subjects in the study. Even more surprisingly, we found that the group correlation map provided a better prediction of a subject's connectivity than the individual's own data. While further discussion and experimentation are required to understand how this can be used in practice, results indicate that shrinkage-based methods that borrow strength from the population mean should play a role in rs-fMRI data analysis. PMID:24879924

  19. Biomarkers and the prediction of atrial fibrillation: state of the art

    PubMed Central

    O’Neal, Wesley T; Venkatesh, Sanjay; Broughton, Stephen T; Griffin, William F; Soliman, Elsayed Z

    2016-01-01

    Atrial fibrillation (AF) is the most common sustained arrhythmia encountered in clinical practice, and it places a substantial burden on the health care system. Despite improvements in our understanding of AF pathophysiology, we have yet to develop targeted preventive therapies. Recently, numerous biological markers have been identified to aid in the prediction of future AF events. Subclinical markers of atrial stress, inflammation, endothelial dysfunction, kidney dysfunction, and atherosclerosis have been linked to AF. The connection between these markers and AF is the identification of subclinical states in which AF propagation is likely to occur, as these conditions are associated with abnormal atrial remodeling and fibrosis. Additionally, several risk scores have been developed to aid in the identification of at-risk patients. The practicing clinician should be aware of these subclinical markers, as several of these markers improve the predictive abilities of current AF risk scores. Knowledge of these subclinical markers also provides clinicians with a better understanding of AF risk factors, and the opportunity to reduce the occurrence of AF by incorporating well-known cardiovascular disease risk factor modification strategies. In this review, we highlight several novel biological markers that have improved our understanding of AF pathophysiology and appraise the utility of these markers to improve our ability to predict future AF events. PMID:27486329

  20. Predictive Sea State Estimation for Automated Ride Control and Handling - PSSEARCH

    NASA Technical Reports Server (NTRS)

    Huntsberger, Terrance L.; Howard, Andrew B.; Aghazarian, Hrand; Rankin, Arturo L.

    2012-01-01

    PSSEARCH provides predictive sea state estimation, coupled with closed-loop feedback control for automated ride control. It enables a manned or unmanned watercraft to determine the 3D map and sea state conditions in its vicinity in real time. Adaptive path-planning/ replanning software and a control surface management system will then use this information to choose the best settings and heading relative to the seas for the watercraft. PSSEARCH looks ahead and anticipates potential impact of waves on the boat and is used in a tight control loop to adjust trim tabs, course, and throttle settings. The software uses sensory inputs including IMU (Inertial Measurement Unit), stereo, radar, etc. to determine the sea state and wave conditions (wave height, frequency, wave direction) in the vicinity of a rapidly moving boat. This information can then be used to plot a safe path through the oncoming waves. The main issues in determining a safe path for sea surface navigation are: (1) deriving a 3D map of the surrounding environment, (2) extracting hazards and sea state surface state from the imaging sensors/map, and (3) planning a path and control surface settings that avoid the hazards, accomplish the mission navigation goals, and mitigate crew injuries from excessive heave, pitch, and roll accelerations while taking into account the dynamics of the sea surface state. The first part is solved using a wide baseline stereo system, where 3D structure is determined from two calibrated pairs of visual imagers. Once the 3D map is derived, anything above the sea surface is classified as a potential hazard and a surface analysis gives a static snapshot of the waves. Dynamics of the wave features are obtained from a frequency analysis of motion vectors derived from the orientation of the waves during a sequence of inputs. Fusion of the dynamic wave patterns with the 3D maps and the IMU outputs is used for efficient safe path planning.

  1. Gis predictive mapping of terrestrial gamma radiation in the Northern State, Sudan.

    PubMed

    Hamed Bashier, E; Salih, I; Khatir Sam, A

    2012-09-01

    This study presents the evaluation of absorbed dose in air due to gamma-emitting nuclides from (238)U and (232)Th series, (40)K and (137)Cs and the corresponding geographical information system (GIS) predictive mapping for the Northern State. Activity concentration of (238)U, (232)Th , (40)K and (137)Cs in soil samples collected from different locations have been measured using high-resolution gamma spectrometry. On  average, activity concentrations were 19±4 ((238)U), 47±11 ((232)Th), 317±65 ((40)K) and 2.26 Bq kg(-1) for (137)Cs. Absorbed dose rate in air at a height of 1 m above ground surface was calculated using seven sets of dose rate conversion factors (DRCFs) and the corresponding annual effective dose was estimated. On average, the values obtained fall within a narrow range of 44 and 53 nGy h(-1), indicating that the variation in absorbed dose rate is insignificant for different DRCFs. The corresponding annual effective dose ranged from 53 to 65 µSv y(-1). Using GIS, prediction maps for concentrations of (238)U, (232)Th, (40)K and (137)Cs were produced. Also, a map for absorbed dose rate in air at a height of 1 m above the ground level was produced, which showed a trend of increasing from the west towards south-east of the State. PMID:22422048

  2. Predicting self-care with patients and family members' affective states and family functioning.

    PubMed

    Musci, E C; Dodd, M J

    1990-01-01

    People with cancer manage the side effects of treatment with the assistance of their family members. This study was designed to describe self-care behaviors (SCBs) initiated by patients and their family members and to determine the relationship between patients and family members' affective states and family functioning and SCBs. Using a longitudinal design, 42 patients and 40 family members were followed during 3 cycles of chemotherapy (12-16 weeks). The patients completed measures of affective state (POMS) each cycle; patients and family members completed a family functioning measure (F-COPES) at second cycle only; and the patients reported in an SCB log on an ongoing basis. The overall pattern of SCBs corroborated previous findings. The average number of SCBs initiated was 1.4 per side effect. Depression and vigor significantly predicted SCBs at Cycle 1 only. The severity of side effects consistently predicted SCB over the 3 cycles (r 2 = -0.39 to -0.46). Patients who experienced more severe side effects were at risk of diminished self-care. PMID:2342973

  3. Hierarchical representations of the five-factor model of personality in predicting job performance: integrating three organizing frameworks with two theoretical perspectives.

    PubMed

    Judge, Timothy A; Rodell, Jessica B; Klinger, Ryan L; Simon, Lauren S; Crawford, Eean R

    2013-11-01

    Integrating 2 theoretical perspectives on predictor-criterion relationships, the present study developed and tested a hierarchical framework in which each five-factor model (FFM) personality trait comprises 2 DeYoung, Quilty, and Peterson (2007) facets, which in turn comprise 6 Costa and McCrae (1992) NEO facets. Both theoretical perspectives-the bandwidth-fidelity dilemma and construct correspondence-suggest that lower order traits would better predict facets of job performance (task performance and contextual performance). They differ, however, as to the relative merits of broad and narrow traits in predicting a broad criterion (overall job performance). We first meta-analyzed the relationship of the 30 NEO facets to overall job performance and its facets. Overall, 1,176 correlations from 410 independent samples (combined N = 406,029) were coded and meta-analyzed. We then formed the 10 DeYoung et al. facets from the NEO facets, and 5 broad traits from those facets. Overall, results provided support for the 6-2-1 framework in general and the importance of the NEO facets in particular. PMID:24016206

  4. Extended loop representation of quantum gravity

    SciTech Connect

    Di Bartolo, C. ); Gambini, R.; Griego, J. )

    1995-01-15

    A new representation of quantum gravity is developed. This formulation is based on an extension of the group of loops. The enlarged group that we call the extended loop group behaves locally as an infinite dimensional Lie group. Quantum gravity can be realized on the state space of extended loop-dependent wave functions. The extended representation generalizes the loop representation and contains this representation as a particular case. The resulting diffeomorphism and Hamiltonian constraints take a very simple form and allow us to apply functional methods and simplify the loop calculus. In particular we show that the constraints are linear in the momenta. The nondegenerate solutions known in the loop representation are also solutions of the constraints in the new representation. An approach to the regularization problems associated with the formal calculus is performed. We show that the solutions are generalized knot invariants, smooth in the extended variables, and any framing is unnecessary.

  5. Bayesian probabilistic model for life prediction and fault mode classification of solid state luminaires

    SciTech Connect

    Lall, Pradeep; Wei, Junchao; Sakalaukus, Peter

    2014-06-22

    A new method has been developed for assessment of the onset of degradation in solid state luminaires to classify failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. Failure modes of the test population of the lamps have been studied to understand the failure mechanisms in 85°C/85%RH accelerated test. Results indicate that the dominant failure mechanism is the discoloration of the LED encapsulant inside the lamps which is the likely cause for the luminous flux degradation and the color shift. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identify luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. The α-λ plots have been used to evaluate the robustness of the proposed methodology. Results show that the predicted degradation for the lamps tracks the true degradation observed during 85°C/85%RH during accelerated life test fairly closely within the ±20% confidence bounds. Correlation of model prediction with experimental results indicates that the presented methodology allows the early identification of the onset of failure much prior to development of complete failure distributions and can be used for assessing the damage state of SSLs in fairly large deployments. It is expected that, the new prediction technique will allow the development of failure distributions without testing till L70 life for the manifestation of failure.

  6. Statistical-mechanical equation of state for nonpolar fluids: Prediction of phase boundaries

    NASA Astrophysics Data System (ADS)

    Tao, Fu-Ming; Mason, E. A.

    1994-06-01

    A perturbation correction term for the effect of attraction forces on the equation of state is calculated and combined with previous statistical-mechanical analytical equations of state proposed by Song and Mason and by Ihm, Song, and Mason. The major effect of the correction on the p-v isotherms occurs in the metastable and unstable regions (the ``van der Waals loops''), with the result that the vapor pressures and orthobaric densities predicted from the Maxwell equal-area construction are greatly improved in accuracy. Comparison is made with experimental data for 13 selected nonpolar fluids (Ar, Kr, Xe, N2, O2, CO2, CH4, C2H6, C3H8, n-C4H10, i-C4H10, C2H4, and benzene) and one slightly polar fluid (toluene). Densities in the stable region of the p-v-T surface are accurate to about 1%-2% in the dense fluid region, and to better than 1% in the low-density gas region; the accuracy is slightly better than that achieved without the perturbation correction. Vapor pressures are predicted with an accuracy of about 2%, with orthobaric densities that are accurate to about 2% for the saturated vapor and to better than 1% for the saturated liquid. As usual for analytical equations of state, the critical region is described less accurately. In principle, the entire fluid equation of state and its vapor-liquid phase boundaries can be calculated from the intermolecular potential plus a few liquid densities. If the potential is not known, measurements of the second virial coefficient as a function of temperature can be used instead; in the absence of any such measurements, the calculation can use as input only the critical temperature, the critical pressure, and the Pitzer acentric factor, with only slight loss of accuracy. Comparison is also made with several widely used empirical equations of state. The present equation of state can be extended to include mixtures, but numerical computations on mixtures are postponed for future work.

  7. A spatially consistent seamless predictions of continental-scale hydrologic fluxes and states

    NASA Astrophysics Data System (ADS)

    Kumar, Rohini; Mai, Juliane; Rakovec, Oldrich; Zink, Matthias; Cuntz, Matthias; Thober, Stephan; Attinger, Sabine; Schroen, Martin; Schaefer, David; Samaniego, Luis

    2016-04-01

    One of the major challenges in the contemporary hydrology is to establish a continental-scale hydrologic model that can provide spatially consistent, seamless prediction of hydrologic fluxes and states to better characterise extreme events like floods and droughts. This requires, among other things, 1) a robust parameterization technique that allows the model to seamlessly operate across a range of spatial resolutions and 2) an efficient parameter estimation technique to derive a representative set of spatially consistent model parameters that avoid inconsistencies in simulated hydrologic fields (e.g., soil moisture). In this study, we demostrate the applicability of a mesoscale hydrologic model parameterized using a multiscale regionalization technique to derive daily gridded fields of hydrologic fluxes/states over the Pan-EU domain since 1950. A multi-basin parameter estimation (MBE) strategy that utilizes observed streamflows from a set of hydrologically diverse basins is introduced to infer a representative set of regional calibration parameters which is applicable over the entire domain. We tested three sampling schemes to select a set of calibration basins incremented sequentially from 2 to 20 basins, based on the 1) random selection procedure, 2) gradient along the hydro-climatic regimes, and 3) diversity in hydro-climatic and basin physiographical properties (e.g., terrain, soil, land cover properties). Results of the MBE approach are contrasted against the benchmark at-site calibration strategy across 400 EU basins varying from approximately 100 to 500,000 km2. At-site calibrated parameters performed best for site-specific streamflow predictions, but their transferability to other sites resulted in poor performance. Moreover, the at-site calibration strategy generated a patchy, spatially inconsistent distribution of parameter fields that further induced large discontinuities in simulated hydrologic fields of soil moisture among other sates/fluxes. These

  8. Ephemeris representations for communications satellites

    NASA Astrophysics Data System (ADS)

    Proulx, R. J.; Cefola, P. J.; McClain, W. D.

    1984-08-01

    Large orbit determination (OD) centers are the primary source of artificial satellite ephemeris data. The ephemeris message of the OD facility contains implicitly the predicted satellite trajectory. The user can recover ephemeris data on the basis of two conceptual approaches. The current investigation is concerned with an alternative solution to the ephemeris representation problem. According to the procedure employed in this case, the mean equinoctial element time histories corresponding to the predicted satellite trajectory generated by the OD facility are approximated by low degree Legendre polynomials to represent their secular behavior and by trigonometric terms to represent their mean periodic behavior. This approach provides a simple, low cost, and accurate ephemeris representation, which satisfies the potential autonomy requirements for Military Satellite Communications.

  9. Representation in Memory.

    ERIC Educational Resources Information Center

    Rumelhart, David E.; Norman, Donald A.

    This paper reviews work on the representation of knowledge from within psychology and artificial intelligence. The work covers the nature of representation, the distinction between the represented world and the representing world, and significant issues concerned with propositional, analogical, and superpositional representations. Specific topics…

  10. B2N2O4: Prediction of a Magnetic Ground State for a Light Main-Group Molecule

    SciTech Connect

    Varga, Zoltan; Truhlar, Donald G.

    2015-09-08

    Cyclobutanetetrone, (CO)4, has a triplet ground state. Here we predict, based on electronic structure calculations, that the B2N2O4 molecule also has a triplet ground state and is therefore paramagnetic; the structure is an analogue of (CO)4 in which the carbon ring is replaced by a (BN)2 ring. Similar to (CO)4, the triplet ground-state structure of B2N2O4 is also thermodynamically unstable. Besides analysis of the molecular orbitals, we found that the partial atomic charges are good indicators for predicting magnetic ground states.

  11. Suggesting a new framework for predictive performance assessment: Trait vs State dimensions.

    NASA Astrophysics Data System (ADS)

    Pattyn, Nathalie; Neyt, Xavier; Migeotte, Pierre-François; Morais, José; Soetens, Eric; Cluydts, Raymond; Meeusen, Romain; de Schutter, Guy; Nederhof, Esther; Kolinsky, Régine

    Special Forces trainees (N=7) during their training. ResultsThe first experiment showed no relationship whatsoever between cognitive performance on the very broad array of tests and immediately subsequent performance on the evaluation flight. However, physiological results showed a trend for students who passed the test to exhibit a larger physiological reactivity. Furthermore, the medium-term outcome of SPs in their flight training showed to be related to their test performance. Results of the second experiment (still in progress) will show whether, for an individual monitoring situation, there is a potential link between performance IQ and success on the training, and whether the longitudinal assessment of both cognitive performance, physical performance and physiological reactivity relates to immediately subsequent performance. DiscussionThese results suggest that a critical distinction could be made regarding predictive performance assessment, namely trait and state dimensions. Since one of the intended uses of operational test batteries is to provide an instantaneous measure of the cognitive status of the subject to allow the immediate execution of critical tasks, our results show this would be an inappropriate application so far. However, a dimension showing promising potential is the physiological reactivity. Whereas operational priorities clearly state the need for performance evaluation tools, their application cannot guide operational choices before sufficient validation allows justifying such decisions. References(1) HUMEX: Study on the Survivability and Adaptation of Humans to Long-duration Exploratory Missions (2000). European Space Agency. (2)BPCR: Bioastronautics Critical Path Roadmap (2004). National Aeronautics and Space Administration. (3) Shephard, J. M. and Kosslyn, S. M. (2005). The MiniCog rapid assessment battery: Developing a "blood pressure cuff for the mind". Avn Space Enl Medicine, 76, B192-B197. (4) Pattyn, N.; Migeotte, P.F.; Morais, J

  12. Identification of predictive biomarkers of disease state in transition dairy cows.

    PubMed

    Hailemariam, D; Mandal, R; Saleem, F; Dunn, S M; Wishart, D S; Ametaj, B N

    2014-05-01

    In dairy cows, periparturient disease states, such as metritis, mastitis, and laminitis, are leading to increasingly significant economic losses for the dairy industry. Treatments for these pathologies are often expensive, ineffective, or not cost-efficient, leading to production losses, high veterinary bills, or early culling of the cows. Early diagnosis or detection of these conditions before they manifest themselves could lower their incidence, level of morbidity, and the associated economic losses. In an effort to identify predictive biomarkers for postpartum or periparturient disease states in dairy cows, we undertook a cross-sectional and longitudinal metabolomics study to look at plasma metabolite levels of dairy cows during the transition period, before and after becoming ill with postpartum diseases. Specifically we employed a targeted quantitative metabolomics approach that uses direct flow injection mass spectrometry to track the metabolite changes in 120 different plasma metabolites. Blood plasma samples were collected from 12 dairy cows at 4 time points during the transition period (-4 and -1 wk before and 1 and 4 wk after parturition). Out of the 12 cows studied, 6 developed multiple periparturient disorders in the postcalving period, whereas the other 6 remained healthy during the entire experimental period. Multivariate data analysis (principal component analysis and partial least squares discriminant analysis) revealed a clear separation between healthy controls and diseased cows at all 4 time points. This analysis allowed us to identify several metabolites most responsible for separating the 2 groups, especially before parturition and the start of any postpartum disease. Three metabolites, carnitine, propionyl carnitine, and lysophosphatidylcholine acyl C14:0, were significantly elevated in diseased cows as compared with healthy controls as early as 4 wk before parturition, whereas 2 metabolites, phosphatidylcholine acyl-alkyl C42:4 and

  13. Geostatistical prediction of stream-flow regime in southeastern United States

    NASA Astrophysics Data System (ADS)

    Pugliese, Alessio; Castellarin, Attilio; Archfield, Stacey; Farmer, William

    2015-04-01

    A Flow-Duration Curve (FDC) represents the percentage of time (duration) during which a given stream-flow is equalled or exceeded over a given period of time. In many water-engineering applications FDCs need to be predicted for ungauged sites (Prediction in Ungauged Basins, PUB problem) using the information collected in donor neighboring gauged basins. We present an application of kriging procedures which makes the procedures capable of predicting FDCs in ungauged catchments. As many of the techniques proposed in the recent literature, the curve is predicted at the target site as a weighted average of empirical dimensionless FDCs that are constructed for neighboring streamgauges and standardized by discharge Q*. Geostatistical weights are obtained by applying two different interpolation techniques, i.e. Top-kriging (TK, see e.g. Pugliese et al., 2014) and Ordinary-kriging (OK, see e.g. Castiglioni et al., 2009), for interpolating a point streamflow-index computed as the overall negative deviation of each empirical curve from Q*, which we term Total Negative Deviation (TND). Empirical TND values can be used to assess the hydrological similarity between catchments and can be interpolated using TK or OK procedures along the stream-network. We consider period-of-record/annual, and complete/seasonal FDCs standardized by two different Q* values, i.e. Mean Annual Flow (MAF) and Mean Annual Precipitation at catchment scale times the drainage area (MAP*), and we apply TK and OK in a wide study area in the Southeastern United States including 182 unregulated gauged catchments. The accuracy of the predicted FDCs is assessed comprehensively under different operational conditions through the (1) leave-one-out and (2) three-fold cross-validation procedures. The results are compared with six different methods for predicting FDCs from synthetically generated daily stream-flow series, which were recently analysed by U.S. Geological Survey. The application of OK and TK reveal

  14. Do PCL-R scores from state or defense experts best predict future misconduct among civilly committed sex offenders?

    PubMed

    Boccaccini, Marcus T; Turner, Darrel B; Murrie, Daniel C; Rufino, Katrina A

    2012-06-01

    In a recent study of sex offender civil commitment proceedings, Murrie et al. (Psychol Public Policy Law 15:19-53, 2009) found that state-retained experts consistently assigned higher PCL-R total scores than defense-retained experts for the same offenders (Cohen's d > .83). This finding raises an important question about the validity of these discrepant scores: Which type of score, state or defense evaluator, provides the most useful information about risk? We examined the ability of PCL-R total scores from state and defense evaluators to predict future misconduct among civilly committed sex offenders (N = 38). For comparison, we also examined predictive validity when two state experts evaluated the same offender (N = 32). Agreement between evaluators was low for cases with opposing experts (ICCA,1 = .43 to .52) and for cases with two state experts (ICCA,1 = .40). Nevertheless, scores from state and defense experts demonstrated similar levels of predictive validity (AUC values in the .70 range), although scores from different types of state evaluators (corrections-contracted vs. prosecution-retained) did not. The finding of mean differences between opposing evaluator scores, but similar levels of predictive validity, suggests that scores from opposing experts in SVP cases may need to be interpreted differently depending on who assigned them. Findings have important implications for understanding how rater disagreement may relate to predictive validity. PMID:22667805

  15. 48 CFR 2009.570-4 - Representation.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... ACQUISITION PLANNING CONTRACTOR QUALIFICATIONS Organizational Conflicts of Interest 2009.570-4 Representation... whether situations or relationships exist which may constitute organizational conflicts of interest with... criteria stated in the following paragraph (b) of this section. (b) The organizational conflicts...

  16. Discrete vortex representation of magnetohydrodynamics

    SciTech Connect

    Kinney, R.; Tajima, T.; Petviashvili, N.; McWilliams, J.C.

    1993-02-01

    We present an alternative approach to statistical analysis of an intermittent ideal MHD fluid in two dimensions, based on the hydrodynamical discrete vortex model applied to the Elsasser variables. The model contains negative temperature states which predict the formation of magnetic islands, but also includes a natural limit under which the equilibrium states revert to the familiar twin-vortex states predicted by hydrodynamical turbulence theories. Numerical dynamical calculations yield equilibrium spectra in agreement with the theoretical predictions.

  17. The Problem State: A Cognitive Bottleneck in Multitasking

    ERIC Educational Resources Information Center

    Borst, Jelmer P.; Taatgen, Niels A.; van Rijn, Hedderik

    2010-01-01

    The main challenge for theories of multitasking is to predict when and how tasks interfere. Here, we focus on interference related to the problem state, a directly accessible intermediate representation of the current state of a task. On the basis of Salvucci and Taatgen's (2008) threaded cognition theory, we predict interference if 2 or more…

  18. Latent subspace sparse representation-based unsupervised domain adaptation

    NASA Astrophysics Data System (ADS)

    Shuai, Liu; Sun, Hao; Zhao, Fumin; Zhou, Shilin

    2015-12-01

    In this paper, we introduce and study a novel unsupervised domain adaptation (DA) algorithm, called latent subspace sparse representation based domain adaptation, based on the fact that source and target data that lie in different but related low-dimension subspaces. The key idea is that each point in a union of subspaces can be constructed by a combination of other points in the dataset. In this method, we propose to project the source and target data onto a common latent generalized subspace which is a union of subspaces of source and target domains and learn the sparse representation in the latent generalized subspace. By employing the minimum reconstruction error and maximum mean discrepancy (MMD) constraints, the structure of source and target domain are preserved and the discrepancy is reduced between the source and target domains and thus reflected in the sparse representation. We then utilize the sparse representation to build a weighted graph which reflect the relationship of points from the different domains (source-source, source- target, and target-target) to predict the labels of the target domain. We also proposed an efficient optimization method for the algorithm. Our method does not need to combine with any classifiers and therefore does not need train the test procedures. Various experiments show that the proposed method perform better than the competitive state of art subspace-based domain adaptation.

  19. Prediction of telephone calls load using Echo State Network with exogenous variables.

    PubMed

    Bianchi, Filippo Maria; Scardapane, Simone; Uncini, Aurelio; Rizzi, Antonello; Sadeghian, Alireza

    2015-11-01

    We approach the problem of forecasting the load of incoming calls in a cell of a mobile network using Echo State Networks. With respect to previous approaches to the problem, we consider the inclusion of additional telephone records regarding the activity registered in the cell as exogenous variables, by investigating their usefulness in the forecasting task. Additionally, we analyze different methodologies for training the readout of the network, including two novel variants, namely ν-SVR and an elastic net penalty. Finally, we employ a genetic algorithm for both the tasks of tuning the parameters of the system and for selecting the optimal subset of most informative additional time-series to be considered as external inputs in the forecasting problem. We compare the performances with standard prediction models and we evaluate the results according to the specific properties of the considered time-series. PMID:26413714

  20. Prediction of explosive cylinder tests using equations of state from the PANDA code

    SciTech Connect

    Kerley, G.I.; Christian-Frear, T.L.

    1993-09-28

    The PANDA code is used to construct tabular equations of state (EOS) for the detonation products of 24 explosives having CHNO compositions. These EOS, together with a reactive burn model, are used in numerical hydrocode calculations of cylinder tests. The predicted detonation properties and cylinder wall velocities are found to give very good agreement with experimental data. Calculations of flat plate acceleration tests for the HMX-based explosive LX14 are also made and shown to agree well with the measurements. The effects of the reaction zone on both the cylinder and flat plate tests are discussed. For TATB-based explosives, the differences between experiment and theory are consistently larger than for other compositions and may be due to nonideal (finite dimameter) behavior.

  1. Reduced-representation Phosphosignatures Measured by Quantitative Targeted MS Capture Cellular States and Enable Large-scale Comparison of Drug-induced Phenotypes.

    PubMed

    Abelin, Jennifer G; Patel, Jinal; Lu, Xiaodong; Feeney, Caitlin M; Fagbami, Lola; Creech, Amanda L; Hu, Roger; Lam, Daniel; Davison, Desiree; Pino, Lindsay; Qiao, Jana W; Kuhn, Eric; Officer, Adam; Li, Jianxue; Abbatiello, Susan; Subramanian, Aravind; Sidman, Richard; Snyder, Evan; Carr, Steven A; Jaffe, Jacob D

    2016-05-01

    Profiling post-translational modifications represents an alternative dimension to gene expression data in characterizing cellular processes. Many cellular responses to drugs are mediated by changes in cellular phosphosignaling. We sought to develop a common platform on which phosphosignaling responses could be profiled across thousands of samples, and created a targeted MS assay that profiles a reduced-representation set of phosphopeptides that we show to be strong indicators of responses to chemical perturbagens.To develop the assay, we investigated the coordinate regulation of phosphosites in samples derived from three cell lines treated with 26 different bioactive small molecules. Phosphopeptide analytes were selected from these discovery studies by clustering and picking 1 to 2 proxy members from each cluster. A quantitative, targeted parallel reaction monitoring assay was developed to directly measure 96 reduced-representation probes. Sample processing for proteolytic digestion, protein quantification, peptide desalting, and phosphopeptide enrichment have been fully automated, making possible the simultaneous processing of 96 samples in only 3 days, with a plate phosphopeptide enrichment variance of 12%. This highly reproducible process allowed ∼95% of the reduced-representation phosphopeptide probes to be detected in ∼200 samples.The performance of the assay was evaluated by measuring the probes in new samples generated under treatment conditions from discovery experiments, recapitulating the observations of deeper experiments using a fraction of the analytical effort. We measured these probes in new experiments varying the treatments, cell types, and timepoints to demonstrate generalizability. We demonstrated that the assay is sensitive to disruptions in common signaling pathways (e.g. MAPK, PI3K/mTOR, and CDK). The high-throughput, reduced-representation phosphoproteomics assay provides a platform for the comparison of perturbations across a range of

  2. Predicting Nitrogen Loading in Streams Under Climate Change Scenarios in the Continental United States.

    NASA Astrophysics Data System (ADS)

    Sinha, E.; Michalak, A. M.

    2014-12-01

    Human actions have doubled the amount of nitrogen in the terrestrial biosphere. Although nitrogen application in the form of fertilizers increases food production, excess nitrogen can be harmful to the environment and to human well-being. Excess nitrogen in streams is transported into downstream water bodies, which leads to increased eutrophication and associated problems such as harmful algal blooms and/or hypoxic conditions. The amount of nitrogen exported to streams depends on several factors, including nitrogen input to the watershed, land use, and precipitation. Previous studies have developed models for predicting nitrate load using stream discharge, in order to estimate the contribution of various factors to total nitrogen load, to identify strategies for reducing nitrogen load, and to assess future changes in nitrogen load resulting from anticipated changes in precipitation patterns. Applying these models to estimate future nitrogen loads thus requires running a rainfall-runoff model driven by climate model predictions before nitrogen loading can, in turn, be estimated, thereby compounding uncertainties. In this study, we present a statistical modeling approach that circumvents this two-step process by estimating nitrogen loading directly from precipitation predictions that can be obtained from climate model outputs. The proposed model uses net anthropogenic nitrogen input (NANI), land use type, and precipitation as input parameters. Preliminary results show that the model explains greater than 65% of the variance in the observed annual log transformed nitrogen loads across various catchments throughout the United States. The model is applied to the watersheds comprising the Mississippi river basin to identify the spatial distribution of the sources of nitrogen loading and the inter-annual variation in nitrogen loads under current conditions. Additionally, the model is used to examine changes in magnitude and spatial patterns of nitrogen loading for

  3. A simple modelling approach for prediction of standard state real gas entropy of pure materials.

    PubMed

    Bagheri, M; Borhani, T N G; Gandomi, A H; Manan, Z A

    2014-01-01

    The performance of an energy conversion system depends on exergy analysis and entropy generation minimisation. A new simple four-parameter equation is presented in this paper to predict the standard state absolute entropy of real gases (SSTD). The model development and validation were accomplished using the Linear Genetic Programming (LGP) method and a comprehensive dataset of 1727 widely used materials. The proposed model was compared with the results obtained using a three-layer feed forward neural network model (FFNN model). The root-mean-square error (RMSE) and the coefficient of determination (r(2)) of all data obtained for the LGP model were 52.24 J/(mol K) and 0.885, respectively. Several statistical assessments were used to evaluate the predictive power of the model. In addition, this study provides an appropriate understanding of the most important molecular variables for exergy analysis. Compared with the LGP based model, the application of FFNN improved the r(2) to 0.914. The developed model is useful in the design of materials to achieve a desired entropy value. PMID:25158071

  4. Predicted midgap states in unconventional superconductors and their numerous implications for high-[Tc] superconductors

    SciTech Connect

    Hu, C.R. . Dept. of Physics)

    1998-12-20

    A fundamental topological consequence of the unconventional (i.e., non-s-wave) pairing symmetry of high-[Tc] superconductors (HTSC's) is the existence of midgap (quasi-particle) states (MS's) bound to surface,m interfaces and other locations. This prediction by the author has most-likely solved a decade-old puzzle, viz., the ubiquitous observation of a zero-bias conductance peak (ZBCP) in tunneling experiments performed on HTSC's. There are also numerous other novel consequences of these MS's, predicted by various researchers, including a new Josephson critical current term; an (already observed) low-temperature splitting of the ZBCP due possibly to a spontaneous breaking of the time-reversal symmetry at a sample surface; a new explanation of the paramagnetic Meissner effect; and a giant magnetic moment, etc. Here the author will review the physical origin of the MS's, the several extensions of the original idea and the many novel consequences of these MS's, some of which have been investigated quantitatively and some others only deduced in qualitative terms so far.

  5. Requirements for Predictive Density Functional Theory Methods for Heavy Materials Equation of State

    NASA Astrophysics Data System (ADS)

    Mattsson, Ann E.; Wills, John M.

    2012-02-01

    The difficulties in experimentally determining the Equation of State of actinide and lanthanide materials has driven the development of many computational approaches with varying degree of empiricism and predictive power. While Density Functional Theory (DFT) based on the Schr"odinger Equation (possibly with relativistic corrections including the scalar relativistic approach) combined with local and semi-local functionals has proven to be a successful and predictive approach for many materials, it is not giving enough accuracy, or even is a complete failure, for the actinides. To remedy this failure both an improved fundamental description based on the Dirac Equation (DE) and improved functionals are needed. Based on results obtained using the appropriate fundamental approach of DFT based on the DE we discuss the performance of available semi-local functionals, the requirements for improved functionals for actinide/lanthanide materials, and the similarities in how functionals behave in transition metal oxides. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

  6. An Empirical Approach toward the Prediction of Students' Science Achievement in the United States and the Peoples' Republic of China.

    ERIC Educational Resources Information Center

    Wang, Jianjun; Staver, John R.

    An empirical approach is adopted in this paper to explore a possible model for prediction of students' science achievement in China and the United States. Construction of the model is based on the ninth-grade data base from Phase 2 of the Second International Education Association Science Study (SISS) in the United States and the SISS Extension…

  7. Chemical structure representations and applications in computational toxicity.

    PubMed

    Karthikeyan, Muthukumarasamy; Vyas, Renu

    2012-01-01

    Efficient storage and retrieval of chemical structures is one of the most important prerequisite for solving any computational-based problem in life sciences. Several resources including research publications, text books, and articles are available on chemical structure representation. Chemical substances that have same molecular formula but several structural formulae, conformations, and skeleton framework/scaffold/functional groups of the molecule convey various characteristics of the molecule. Today with the aid of sophisticated mathematical models and informatics tools, it is possible to design a molecule of interest with specified characteristics based on their applications in pharmaceuticals, agrochemicals, biotechnology, nanomaterials, petrochemicals, and polymers. This chapter discusses both traditional and current state of art representation of chemical structures and their applications in chemical information management, bioactivity- and toxicity-based predictive studies. PMID:23007430

  8. Hydrological states and fluxes in terrestrial systems: from observation to prediction (John Dalton Medal Lecture)

    NASA Astrophysics Data System (ADS)

    Vereecken, Harry

    2016-04-01

    Quantification and prediction of hydrological processes requires information on the spatial and temporal distribution of soil water fluxes and soil water content. The access to spatially and temporally highly resolved soil water content and fluxes is needed to adequately test hydrological hypotheses and to validate hydrological models. In this presentation we will discuss new developments for the determination of soil water content and quantification and prediction of hydrological fluxes based on hydrogeophysical measurement techniques and novel ground- and satellite based sensing platforms. At the field scale, ground penetrating radar and passive microwave methods are presently being developed which provide the possibility to map soil water content with a high spatial and temporal resolution, also in the subsurface environment. Recent developments show that the application of full wave form inversion methods is a unique technique to derive soil water and soil hydraulic parameters from on- and off-ground systems with high spatial resolution. At the small catchment scale, wireless sensor networks are presently being developed providing soil moisture content values with a high spatial and temporal resolution. Stochastic theories have been used to interpret the relationship between average soil water content and its standard deviation. Cosmic ray sensors are presently being deployed within the TERENO observatories. These sensors provide soil moisture content values with a high temporal resolution at a scale of one to two hundred meters, thereby bridging the gap between local scale measurements and remote sensing platforms. Cosmic ray probes are extremely valuable for the determination of soil water content in agriculturally managed soils. Data assimilation methods provide a unique approach to fully exploit the value of spatially and temporally highly resolved soil water content measurements and states of the terrestrial system for the prediction of hydrological fluxes

  9. Predicting freakish sea state with an operational third generation wave model

    NASA Astrophysics Data System (ADS)

    Waseda, T.; In, K.; Kiyomatsu, K.; Tamura, H.; Miyazawa, Y.; Iyama, K.

    2013-11-01

    Understanding of freak wave generation mechanism has advanced and the community has reached to a consensus that spectral geometry plays an important role. Numerous marine accident cases were studied and revealed that the narrowing of the directional spectrum is a good indicator of dangerous sea. However, the estimation of the directional spectrum depends on the performance of the third generation wave model. In this work, a well-studied marine accident case in Japan in 1980 (Onomichi-Maru incident) is revisited and the sea states are hind-casted using both the DIA and SRIAM nonlinear source terms. The result indicates that the temporal evolution of the basic parameters (directional spreading and frequency bandwidth) agree reasonably well between the two schemes and therefore most commonly used DIA method is qualitatively sufficient to predict freakish sea state. The analyses revealed that in the case of Onomichi-Maru, a moving gale system caused the spectrum to grow in energy with limited down-shifting at the accident site. This conclusion contradicts the marine inquiry report speculating that the two swell systems crossed at the accident site. The unimodal wave system grew under strong influence of local wind with a peculiar energy transfer.

  10. Rotational isomeric state theory applied to the stiffness prediction of an anion polymer electrolyte membrane

    SciTech Connect

    Gao, Fei; Weiland, L.M.; Kitchin, J.R.

    2008-05-01

    While the acidic polymer electrolyte membrane (PEM) Nafion® has garnered considerable attention, the active response of basic PEMs offers another realm of potential applications. For instance, the basic PEM Selemion® is currently being considered in the development of a CO2 separation prototype device to be employed in coal power plant flue gas. The mechanical integrity of this material and subsequent effects in active response in this harsh environment will become important in prototype development. A multiscale modeling approach based on rotational isomeric state theory in combination with a Monte Carlo methodology may be employed to study mechanical integrity. The approach has the potential to be adapted to address property change of any PEM in the presence of foreign species (reinforcing or poisoning), as well as temperature and hydration variations. The conformational characteristics of the Selemion® polymer chain and the cluster morphology in the polymer matrix are considered in the prediction of the stiffness of Selemion® in specific states.

  11. Prediction and validation of protein intermediate states from structurally rich ensembles and coarse-grained simulations.

    PubMed

    Orellana, Laura; Yoluk, Ozge; Carrillo, Oliver; Orozco, Modesto; Lindahl, Erik

    2016-01-01

    Protein conformational changes are at the heart of cell functions, from signalling to ion transport. However, the transient nature of the intermediates along transition pathways hampers their experimental detection, making the underlying mechanisms elusive. Here we retrieve dynamic information on the actual transition routes from principal component analysis (PCA) of structurally-rich ensembles and, in combination with coarse-grained simulations, explore the conformational landscapes of five well-studied proteins. Modelling them as elastic networks in a hybrid elastic-network Brownian dynamics simulation (eBDIMS), we generate trajectories connecting stable end-states that spontaneously sample the crystallographic motions, predicting the structures of known intermediates along the paths. We also show that the explored non-linear routes can delimit the lowest energy passages between end-states sampled by atomistic molecular dynamics. The integrative methodology presented here provides a powerful framework to extract and expand dynamic pathway information from the Protein Data Bank, as well as to validate sampling methods in general. PMID:27578633

  12. Predicting freakish sea state with an operational third-generation wave model

    NASA Astrophysics Data System (ADS)

    Waseda, T.; In, K.; Kiyomatsu, K.; Tamura, H.; Miyazawa, Y.; Iyama, K.

    2014-04-01

    The understanding of freak wave generation mechanisms has advanced and the community has reached a consensus that spectral geometry plays an important role. Numerous marine accident cases were studied and revealed that the narrowing of the directional spectrum is a good indicator of dangerous sea. However, the estimation of the directional spectrum depends on the performance of the third-generation wave model. In this work, a well-studied marine accident case in Japan in 1980 (Onomichi-Maru incident) is revisited and the sea states are hindcasted using both the DIA (discrete interaction approximation) and SRIAM (Simplified Research Institute of Applied Mechanics) nonlinear source terms. The result indicates that the temporal evolution of the basic parameters (directional spreading and frequency bandwidth) agree reasonably well between the two schemes and therefore the most commonly used DIA method is qualitatively sufficient to predict freakish sea state. The analyses revealed that in the case of Onomichi-Maru, a moving gale system caused the spectrum to grow in energy with limited downshifting at the accident's site. This conclusion contradicts the marine inquiry report speculating that the two swell systems crossed at the accident's site. The unimodal wave system grew under strong influence of local wind with a peculiar energy transfer.

  13. Representational and Executive Selection Resources in "Theory of Mind": Evidence from Compromised Belief-Desire Reasoning in Old Age

    ERIC Educational Resources Information Center

    German, Tim P.; Hehman, Jessica A.

    2006-01-01

    Effective belief-desire reasoning requires both specialized representational capacities--the capacity to represent the mental states as such--as well as executive selection processes for accurate performance on tasks requiring the prediction and explanation of the actions of social agents. Compromised belief-desire reasoning in a given population…

  14. On Performance Skill Representation Framework

    NASA Astrophysics Data System (ADS)

    Furukawa, Koichi; Shimizu, Satoshi; Yoshinaga, Saori

    In this paper, we propose a framework for representing performance skill. Firstly, we notice the importance of performance skill representation. We introduce five different representation targets: performance tasks, performance rules, pre-shaping actions, dynamic integrity constraints, and performance states. Performance task description consists of a sequence of performance tasks and expressions. It acts as a goal description in planning. Performance rules describe model performance methods for given tasks including how to shape body parts and how to use various muscles. Pre-shaping action rules are similar to performance rules. Its role is to pre-shape in between consecutive tasks to prepare for the next task. Dynamic integrity constraints specify constraints to be satisfied during performance. They provide such general rules as prohibiting simultaneous strong activations of agonist and antagonist. Performance states are for describing real performance done by players including professionals and amateurs. The aim of the framework is to provide a uniform scheme for representing model performance methods given performance score such as music score. The representation framework will define targets of inducing formal skill rules as well as describing performance states automatically from biomechanical performance data. It also is related to a fundamental research issue of attributes finding/selection in discovering useful rules for skillful performance. We conclude our paper by stating future research direction.

  15. State dependent model predictive control for orbital rendezvous using pulse-width pulse-frequency modulated thrusters

    NASA Astrophysics Data System (ADS)

    Li, Peng; Zhu, Zheng H.; Meguid, S. A.

    2016-07-01

    This paper studies the pulse-width pulse-frequency modulation based trajectory planning for orbital rendezvous and proximity maneuvering near a non-cooperative spacecraft in an elliptical orbit. The problem is formulated by converting the continuous control input, output from the state dependent model predictive control, into a sequence of pulses of constant magnitude by controlling firing frequency and duration of constant-magnitude thrusters. The state dependent model predictive control is derived by minimizing the control error of states and control roughness of control input for a safe, smooth and fuel efficient approaching trajectory. The resulting nonlinear programming problem is converted into a series of quadratic programming problem and solved by numerical iteration using the receding horizon strategy. The numerical results show that the proposed state dependent model predictive control with the pulse-width pulse-frequency modulation is able to effectively generate optimized trajectories using equivalent control pulses for the proximity maneuvering with less energy consumption.

  16. 15 CFR 2009.1 - Information required in representation.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    .... 2009.1 Section 2009.1 Commerce and Foreign Trade Regulations Relating to Foreign Trade Agreements... TRADE AGREEMENTS ACT OF 1979 § 2009.1 Information required in representation. (a) Each representation submitted under section 422 should state clearly on the first page that the representation is a request...

  17. 15 CFR 2009.1 - Information required in representation.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    .... 2009.1 Section 2009.1 Commerce and Foreign Trade Regulations Relating to Foreign Trade Agreements... TRADE AGREEMENTS ACT OF 1979 § 2009.1 Information required in representation. (a) Each representation submitted under section 422 should state clearly on the first page that the representation is a request...

  18. 15 CFR 2009.1 - Information required in representation.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    .... 2009.1 Section 2009.1 Commerce and Foreign Trade Regulations Relating to Foreign Trade Agreements... TRADE AGREEMENTS ACT OF 1979 § 2009.1 Information required in representation. (a) Each representation submitted under section 422 should state clearly on the first page that the representation is a request...

  19. 15 CFR 2009.1 - Information required in representation.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    .... 2009.1 Section 2009.1 Commerce and Foreign Trade Regulations Relating to Foreign Trade Agreements... TRADE AGREEMENTS ACT OF 1979 § 2009.1 Information required in representation. (a) Each representation submitted under section 422 should state clearly on the first page that the representation is a request...

  20. Predicting stabilizing mutations in proteins using Poisson-Boltzmann based models: study of unfolded state ensemble models and development of a successful binary classifier based on residue interaction energies.

    PubMed

    Estrada, Jorge; Echenique, Pablo; Sancho, Javier

    2015-12-14

    In many cases the stability of a protein has to be increased to permit its biotechnological use. Rational methods of protein stabilization based on optimizing electrostatic interactions have provided some fine successful predictions. However, the precise calculation of stabilization energies remains challenging, one reason being that the electrostatic effects on the unfolded state are often neglected. We have explored here the feasibility of incorporating Poisson-Boltzmann model electrostatic calculations performed on representations of the unfolded state as large ensembles of geometrically optimized conformations calculated using the ProtSA server. Using a data set of 80 electrostatic mutations experimentally tested in two-state proteins, the predictive performance of several such models has been compared to that of a simple one that considers an unfolded structure of non-interacting residues. The unfolded ensemble models, while showing correlation between the predicted stabilization values and the experimental ones, are worse than the simple model, suggesting that the ensembles do not capture well the energetics of the unfolded state. A more attainable goal is classifying potential mutations as either stabilizing or non-stabilizing, rather than accurately calculating their stabilization energies. To implement a fast classification method that can assist in selecting stabilizing mutations, we have used a much simpler electrostatic model based only on the native structure and have determined its precision using different stabilizing energy thresholds. The binary classifier developed finds 7 true stabilizing mutants out of every 10 proposed candidates and can be used as a robust tool to propose stabilizing mutations. PMID:26530878

  1. Computer aided surface representation

    SciTech Connect

    Barnhill, R.E.

    1991-04-02

    Modern computing resources permit the generation of large amounts of numerical data. These large data sets, if left in numerical form, can be overwhelming. Such large data sets are usually discrete points from some underlying physical phenomenon. Because we need to evaluate the phenomenon at places where we don't have data, a continuous representation (a surface'') is required. A simple example is a weather map obtained from a discrete set of weather stations. (For more examples including multi-dimensional ones, see the article by Dr. Rosemary Chang in the enclosed IRIS Universe). In order to create a scientific structure encompassing the data, we construct an interpolating mathematical surface which can evaluate at arbitrary locations. We can also display and analyze the results via interactive computer graphics. In our research we construct a very wide variety of surfaces for applied geometry problems that have sound theoretical foundations. However, our surfaces have the distinguishing feature that they are constructed to solve short or long term practical problems. This DOE-funded project has developed the premiere research team in the subject of constructing surfaces (3D and higher dimensional) that provide smooth representations of real scientific and engineering information, including state of the art computer graphics visualizations. However, our main contribution is in the development of fundamental constructive mathematical methods and visualization techniques which can be incorporated into a wide variety of applications. This project combines constructive mathematics, algorithms, and computer graphics, all applied to real problems. The project is a unique resource, considered by our peers to be a de facto national center for this type of research.

  2. Vapor-liquid phase equilibria of potassium chloride-water mixtures: Equation-of-state representation for KCl-H2O and NaCl-H2O

    USGS Publications Warehouse

    Hovey, J.K.; Pitzer, Kenneth S.; Tanger, J.C., IV; Bischoff, J.L.; Rosenbauer, R.J.

    1990-01-01

    Measurements of isothermal vapor-liquid compositions for KCl-H2O as a function of pressure are reported. An equation of state, which was originally proposed by Pitzer and was improved and used by Tanger and Pitzer to fit the vapor-liquid coexistence surface for NaCl-H2O, has been used for representation of the KCl-H2O system from 300 to 410??C. Improved parameters are also reported for NaCl-H2O from 300 to 500??C. ?? 1990 American Chemical Society.

  3. XML-BASED REPRESENTATION

    SciTech Connect

    R. KELSEY

    2001-02-01

    For focused applications with limited user and use application communities, XML can be the right choice for representation. It is easy to use, maintain, and extend and enjoys wide support in commercial and research sectors. When the knowledge and information to be represented is object-based and use of that knowledge and information is a high priority, then XML-based representation should be considered. This paper discusses some of the issues involved in using XML-based representation and presents an example application that successfully uses an XML-based representation.

  4. Fock representation for quaternion fields

    SciTech Connect

    Govorkov, A.B.

    1987-04-01

    A Fock representation is determined for a nonrelativistic self-adjoint (Majorana) field based on quaternions, and the quantum mechanics of the parafermions of third order corresponding to it is formulated. Attention is drawn to the difference between the gauge pseudocolor SO(3) symmetry of the automorphisms of such a field and the global SU(3) symmetry of the states of the particles corresponding to it in the Fock space.

  5. Adenosine 5'-triphosphate consumption by smooth muscle as predicted by the coupled four-state crossbridge model.

    PubMed Central

    Hai, C M; Murphy, R A

    1992-01-01

    We have proposed a four-state crossbridge model to explain contraction and the latch state in arterial smooth muscle. Ca(2+)-dependent crossbridge phosphorylation was the only postulated regulatory mechanism and the latchbridge (a dephosphorylated, attached crossbridge) was the only novel element in the model. In this study, we used the model to predict rates of ATP consumption by crossbridge phosphorylation (JPhos) and cycling (JCycle) during isometric and isotonic contractions in arterial smooth muscle; then we compared model predictions with experimental data. The model predicted that JPhos and JCycle were similar in magnitude in isometric contractions, and both increased almost linearly with myosin phosphorylation. The predicted relationship between isometric stress and ATP consumption was quasihyperbolic, but approximately linear when myosin phosphorylation was below 35%, in agreement with most of the available data. Muscle shortening increased the predicted values of JCycle up to 3.7-fold depending on shortening velocity and the level of myosin phosphorylation. The predicted maximum work output per ATP was 7.4-7.8 kJ/mol ATP and was relatively insensitive to changes in myosin phosphorylation. The predicted increase in JCycle with shortening was in agreement with available data, but the model prediction that work output per ATP was insensitive to changes in myosin phosphorylation was unexpected and remains to be tested in future experiments. PMID:1547336

  6. Statistical analysis of clinical prediction rules for rehabilitation interventions: current state of the literature.

    PubMed

    Lubetzky-Vilnai, Anat; Ciol, Marcia; McCoy, Sarah Westcott

    2014-01-01

    Deriving clinical prediction rules (CPRs) to identify specific characteristics of patients who would likely respond to certain interventions has become a research priority in physical rehabilitation. Understanding the appropriate statistical principles and methods of analyses underlying the derivation of CPRs is important for future rehabilitation research and clinical applications. In this article, we aimed to provide an overview of statistical techniques used for the derivation of CPRs to predict success following physical therapy interventions and to generate recommendations for improvements in CPR derivation research and statistical analysis in rehabilitation. We have summarized the current state of CPR intervention-related research by reviewing 26 studies. A common technique was found in most studies and included univariate association of factors with treatment success, stepwise logistic regression to determine the most parsimonious set of predictors for success, and calculation of accuracy statistics (focusing on positive likelihood ratios). We identified several shortcomings related to inadequate ratio of events by number of predictors, lack of standardization regarding acceptable interobserver reliability of predictors, questionable handling of predictors including reliance on univariate analysis and early categorization, and not accounting for dependence and collinearity of predictors in multivariable model construction. Interpretation of the derived CPRs was found to be difficult due to lack of precision of estimates and paradoxical findings when a subset of the predictors yielded a larger positive likelihood ratio than did the full set of predictors. Finally, we make recommendations regarding how to strengthen the use of statistical principles and methods to create consistency across rehabilitation research for CPR derivations. PMID:24036159

  7. Multiple genetic variants predict steady-state nevirapine clearance in HIV-infected Cambodians

    PubMed Central

    Bertrand, Julie; Chou, Monidarin; Richardson, Danielle M.; Verstuyft, Céline; Leger, Paul D.; Mentré, France; Taburet, Anne-Marie; Haas, David W.

    2013-01-01

    Objective In a previous analysis involving protocol ANRS 12154, interindividual variability in steady-state nevirapine clearance among HIV-infected Cambodians was partially explained by CYP2B6 516G→T (CYP2B6*6). Here, we examine whether additional genetic variants predict nevirapine clearance in this cohort. Methods Analyses included Phnom Penh ESTHER (Ensemble pour une Solidarité Thérapeutique Hospitalière en Réseau) cohort participants who had consented for genetic testing. All participants were receiving nevirapine plus two nucleoside analogs. The mean individual nevirapine clearance estimates were derived from a population model developed on nevirapine concentrations at 18 and 36 months of therapy. Polymorphisms were assayed in ABCB1, CYP2A6, CYP2B6, CYP2C19, CYP3A4, CYP3A5, and NR1I2. Results Of 198 assayed loci, 130 were polymorphic. Among 129 individuals with evaluable genetic data, nevirapine clearance ranged from 1.06 to 5.00 l/h in 128 individuals and was 7.81 l/h in one individual. In bivariate linear regression, CYP2B6 516G→T (CYP2B6*6) was associated with lower nevirapine clearances (P = 3.5 × 10–6). In a multivariate linear regression model conditioned on CYP2B6 516G→T, independent associations were identified with CYP2B6 rs7251950, CYP2B6 rs2279343, and CYP3A4 rs2687116. The CYP3A4 association disappeared after censoring the outlier clearance value. A model that included CYP2B6 516G→T (P = 1.0 × 10–9), rs7251950 (P = 4.8 × 10–5), and rs2279343 (P = 7.1 × 10–5) explained 11% of interindividual variability in nevirapine clearance. Conclusion Among HIV-infected Cambodians, several CYP2B6 polymorphisms were associated independently with steady-state nevirapine clearance. The prediction of nevirapine clearance was improved by considering several polymorphisms in combination. PMID:23104099

  8. Resting state functional MRI connectivity predicts hypothalamus-pituitary-axis status in healthy males.

    PubMed

    Kiem, Sara A; Andrade, Kátia C; Spoormaker, Victor I; Holsboer, Florian; Czisch, Michael; Sämann, Philipp G

    2013-08-01

    Homeostasis of the human stress response system is critically maintained by a hierarchical system of neural and endocrine elements for which intact negative feedback is important to prevent maladaptation towards stress. Such feedback is efficiently probed by the established combined dexamethasone-suppression/corticotropin-releasing hormone stimulation (dex/CRH) test. Here we investigate which suprahypothalamic networks might modulate the response assessed by this neuroendocrine test. Combined resting state fMRI (rs-fMRI)/EEG was acquired in 20 healthy male volunteers along with dex/CRH profiles obtained on a different day outside the scanner. Seed-based network analysis and inter-seed cross correlation analysis for selected atlas-based limbic, paralimbic and medial prefrontal cortex seeds were correlated with stimulated cortisol and adrenocorticotropin hormone (ACTH) concentrations. Lower connectivity between a left hippocampus-based network and the right hippocampus significantly predicted stimulated cortisol concentration (R(2)=0.70, corrected pcluster=0.001). Six further significantly negative correlations were detected mainly in the left anterior cingulate cortex (ACC) and the medial prefrontal cortex (mPFC). The strongest positive correlation with stimulated hormone concentration was detected for the left subcallosal ACC (ACTH, R(2)=0.57, corrected pcluster=0.009). Inter-seed connectivity mainly pointed to hippocampal/amygdala interactions as correlates of the dex/CRH response. In conclusion, resting state functional connectivity patterns of limbic, particularly hippocampal, as well as cingulate and medial prefrontal areas can explain some of the variance of the dex/CRH test in healthy subjects. Functional connectivity analysis can be considered useful to study supra-hypothalamic control systems of the HPA axis. PMID:23279846

  9. Predicting heat waves and cold snaps in the United States across multiple time scales

    NASA Astrophysics Data System (ADS)

    Guirguis, K.; Gershunov, A.; Schwartz, R.

    2011-12-01

    Wintertime cold snaps and summertime heat waves increase energy demand and draw heavily on emergency resources of state and local governments. Adequate planning for these events requires improved predictions on timescales beyond the short range where numerical models perform well. Comprehensive probabilistic tools relating temperature extremes to weather/climate conditions on multiple time scales from the extended range to seasonal-scales and longer are needed. We have quantified heat waves and cold snaps for different regions of the U.S. over a 60-year period and used a probabilistic approach to relate these historic events to precursor weather patterns. Using principal components analysis applied to atmospheric data from NCEP Reanalysis, we identified circulation patterns (predictors) that precede extreme cold/heat events at various lead times in the range of 0-35 days. By studying the evolution of predictor patterns, we find subtle but important differences in the atmospheric states that lead to an extreme temperature event versus those that are not followed by such an event. In some cases, low-frequency climate forcing appears to modulate whether an extreme temperature event develops in the extended range, which may provide a link between seasonal and subseasonal scales. To address long-term planning, we apply the methodology to model simulations under different climate change scenarios to determine if the same relationships exist between predictor patterns and cold/heat events in the historical period and if/how we can expect these relationships to change in a future climate. These results have applications for operational forecasting of extreme temperatures, particular for energy load forecasting, as well as for short- and long-term emergency resource planning.

  10. Connecting Representations: Using Predict, Check, Explain

    ERIC Educational Resources Information Center

    Roy, George J.; Fueyo, Vivian; Vahey, Philip; Knudsen, Jennifer; Rafanan, Ken; Lara-Meloy, Teresa

    2016-01-01

    Although educators agree that making connections with the real world, as advocated by "Principles to Actions: Ensuring Mathematical Success for All" (NCTM 2014), is important, making such connections while addressing important mathematics is elusive. The authors have found that math content coupled with the instructional strategy of…

  11. Cumulative activation during positive and negative events and state anxiety predicts subsequent inertia of amygdala reactivity

    PubMed Central

    Miendlarzewska, Ewa A.; Eryilmaz, Hamdi; Vuilleumier, Patrik

    2015-01-01

    Inertia, together with intensity and valence, is an important component of emotion. We tested whether positive and negative events generate lingering changes in subsequent brain responses to unrelated threat stimuli and investigated the impact of individual anxiety. We acquired fMRI data while participants watched positive or negative movie-clips and subsequently performed an unrelated task with fearful and neutral faces. We quantified changes in amygdala reactivity to fearful faces as a function of the valence of preceding movies and cumulative neural activity evoked during them. We demonstrate that amygdala responses to emotional movies spill over to subsequent processing of threat information in a valence-specific manner: negative movies enhance later amygdala activation whereas positive movies attenuate it. Critically, the magnitude of such changes is predicted by a measure of cumulative amygdala responses to the preceding positive or negative movies. These effects appear independent of overt attention, are regionally limited to amygdala, with no changes in functional connectivity. Finally, individuals with higher state anxiety displayed stronger modulation of amygdala reactivity by positive movies. These results suggest that intensity and valence of emotional events as well as anxiety levels promote local changes in amygdala sensitivity to threat, highlighting the importance of past experience in shaping future affective reactivity. PMID:24603023

  12. Efficient prediction of terahertz quantum cascade laser dynamics from steady-state simulations

    SciTech Connect

    Agnew, G.; Lim, Y. L.; Nikolić, M.; Rakić, A. D.; Grier, A.; Valavanis, A.; Cooper, J.; Dean, P.; Khanna, S. P.; Lachab, M.; Linfield, E. H.; Davies, A. G.; Ikonić, Z.; Indjin, D.; Taimre, T.; Harrison, P.

    2015-04-20

    Terahertz-frequency quantum cascade lasers (THz QCLs) based on bound-to-continuum active regions are difficult to model owing to their large number of quantum states. We present a computationally efficient reduced rate equation (RE) model that reproduces the experimentally observed variation of THz power with respect to drive current and heat-sink temperature. We also present dynamic (time-domain) simulations under a range of drive currents and predict an increase in modulation bandwidth as the current approaches the peak of the light–current curve, as observed experimentally in mid-infrared QCLs. We account for temperature and bias dependence of the carrier lifetimes, gain, and injection efficiency, calculated from a full rate equation model. The temperature dependence of the simulated threshold current, emitted power, and cut-off current are thus all reproduced accurately with only one fitting parameter, the interface roughness, in the full REs. We propose that the model could therefore be used for rapid dynamical simulation of QCL designs.

  13. Predicting onset and duration of airborne allergenic pollen season in the United States

    NASA Astrophysics Data System (ADS)

    Zhang, Yong; Bielory, Leonard; Cai, Ting; Mi, Zhongyuan; Georgopoulos, Panos

    2015-02-01

    Allergenic pollen is one of the main triggers of Allergic Airway Disease (AAD) affecting 5%-30% of the population in industrialized countries. A modeling framework has been developed using correlation and collinearity analyses, simulated annealing, and stepwise regression based on nationwide observations of airborne pollen counts and climatic factors to predict the onsets and durations of allergenic pollen seasons of representative trees, weeds and grass in the contiguous United States. Main factors considered are monthly, seasonal and annual mean temperatures and accumulative precipitations, latitude, elevation, Growing Degree Day (GDD), Frost Free Day (FFD), Start Date (SD) and Season Length (SL) in the previous year. The estimated mean SD and SL for birch (Betula), oak (Quercus), ragweed (Ambrosia), mugwort (Artemisia) and grass (Poaceae) pollen season in 1994-2010 are mostly within 0-6 days of the corresponding observations for the majority of the National Allergy Bureau (NAB) monitoring stations across the contiguous US. The simulated spatially resolved maps for onset and duration of allergenic pollen season in the contiguous US are consistent with the long term observations.

  14. On the robustness of near term climate predictability regarding initial state uncertainties

    NASA Astrophysics Data System (ADS)

    Germe, Agathe; Sévellec, Florian; Mignot, Juliette; Swingedouw, Didier; Nguyen, Sebastien

    2016-03-01

    A set of four ensemble simulations has been designed to assess the relative importance of atmospheric, oceanic, and deep ocean initial state uncertainties, as represented by spatial white noise perturbations, on seasonal to decadal prediction skills in a perfect model framework. It is found that a perturbation mimicking random oceanic uncertainties have the same impact as an atmospheric-only perturbation on the future evolution of the ensemble after the first 3 months, even if they are initially only located in the deep ocean. This is due to the fast (1 month) perturbation of the atmospheric component regardless of the initial ensemble generation strategy. The divergence of the ensemble upper-ocean characteristics is then mainly induced by ocean-atmosphere interactions. While the seasonally varying mixed layer depth allows the penetration of the different signals in the thermocline in the mid-high latitudes, the rapid adjustment of the thermocline to wind anomalies followed by Kelvin and Rossby waves adjustment dominates the growth of the ensemble spread in the tropics. These mechanisms result in similar ensemble distribution characteristics for the four ensembles design strategy at the interannual timescale.

  15. Predicting Onset and Duration of Airborne Allergenic Pollen Season in the United States

    PubMed Central

    Zhang, Yong; Bielory, Leonard; Cai, Ting; Mi, Zhongyuan; Georgopoulos, Panos

    2014-01-01

    Allergenic pollen is one of the main triggers of Allergic Airway Disease (AAD) affecting 5% to 30% of the population in industrialized countries. A modeling framework has been developed using correlation and collinearity analyses, simulated annealing, and stepwise regression based on nationwide observations of airborne pollen counts and climatic factors to predict the onsets and durations of allergenic pollen seasons of representative trees, weeds and grass in the contiguous United States. Main factors considered are monthly, seasonal and annual mean temperatures and accumulative precipitations, latitude, elevation, Growing Degree Day (GDD), Frost Free Day (FFD), Start Date (SD) and Season Length (SL) in the previous year. The estimated mean SD and SL for birch (Betula), oak (Quercus), ragweed (Ambrosia), mugwort (Artemisia) and grass (Poaceae) pollen season in 1994–2010 are mostly within 0 to 6 days of the corresponding observations for the majority of the National Allergy Bureau (NAB) monitoring stations across the contiguous US. The simulated spatially resolved maps for onset and duration of allergenic pollen season in the contiguous US are consistent with the long term observations. PMID:25620875

  16. A steady-state simulation methodology for predicting runaway speed in Francis turbines

    NASA Astrophysics Data System (ADS)

    Hosseinimanesh, H.; Vu, T. C.; Devals, C.; Nennemann, B.; Guibault, F.

    2014-03-01

    Runaway speed is an important performance factor for the safe operation of hydropower systems. In turbine design, the manufacturers must conduct several model tests to calculate the accurate value of runaway speed for the complete range of operating conditions, which are expensive and time-consuming. To study runaway conditions, the application of numerical tools such as unsteady CFD simulations can help to better understand the complex flow physics during transient processes. However, unsteady simulations require significant computational effort to compute accurate values of runaway speed due to difficulties related to unsteady turbulent flow modelling and instabilities. The present study presents a robust methodology based on steady-state RANS flow simulations capable of predicting the runaway speed of a Francis turbine with an adequate level of accuracy and in a reasonable simulation time. The simulations are implemented using a commercial flow solver and an iterative algorithm that relies on a smooth relation between turbine torque and speed coefficient. The impact of friction has been considered when estimating turbine torque, in order to improve the accuracy. The results of this study show good agreement with experiments.

  17. Aggregate-level analysis and prediction of midterm senatorial elections in the United States, 1974-1986.

    PubMed

    Lichtman, A J; Keilis-Borok, V I

    1989-12-01

    Pattern recognition study demonstrates that the outcomes of American midterm senatorial elections follow the dynamics of simple integral parameters that depict preelectoral situations aggregated to the state as a whole. A set of "commonsense" parameters is identified that is sufficient to predict such elections state-by-state and year-by-year. The analysis rejects many similar commonsense parameters. The existence and nature of integral collective behavior in U.S. elections at the level of the individual states is investigated. Implications for understanding the American electoral process are discussed. PMID:2602365

  18. Inscriptions Becoming Representations in Representational Practices

    ERIC Educational Resources Information Center

    Medina, Richard; Suthers, Daniel

    2013-01-01

    We analyze the interaction of 3 students working on mathematics problems over several days in a virtual math team. Our analysis traces out how successful collaboration in a later session is contingent upon the work of prior sessions and shows how the development of representational practices is an important aspect of these participants' problem…

  19. Reading Visual Representations

    ERIC Educational Resources Information Center

    Rubenstein, Rheta N.; Thompson, Denisse R.

    2012-01-01

    Mathematics is rich in visual representations. Such visual representations are the means by which mathematical patterns "are recorded and analyzed." With respect to "vocabulary" and "symbols," numerous educators have focused on issues inherent in the language of mathematics that influence students' success with mathematics communication.…

  20. Solubility prediction of carbon dioxide in water by an iterative equation of state/excess Gibbs energy model

    NASA Astrophysics Data System (ADS)

    Suleman, H.; Maulud, A. S.; Man, Z.

    2016-06-01

    The solubility of carbon dioxide in water has been predicted extensively by various models, owing to their vast applications in process industry. Henry's law has been widely utilized for solubility prediction with good results at low pressure. However, the law shows large deviations at high pressure, even when adjusted to pressure correction and improved conditions. Contrarily, equations of state/excess Gibbs energy models are a promising addition to thermodynamic models for prediction at high pressure non-ideal equilibria. These models can efficiently predict solubilities at high pressures, even when the experimental solubilities are not corroborated. Hence, these models work iteratively, utilizing the mathematical redundancy of local composition excess Gibbs energy models. In this study, an iterative form of Linear Combination of Vidal and Michelsen (LCVM) mixing rule has been used for prediction of carbon dioxide solubility in water, in conjunction with UNIFAC and translated modified Peng- Robinson equation of state. The proposed model, termed iterative LCVM (i-LCVM), predicts carbon dioxide solubility in water for a wide range of temperature (273 to 453 K) and pressure (101.3 to 7380 kPa). The i-LCVM shows good agreement with experimental values and predicts better than Henry's law (53% improvement).

  1. 2-Group Representations for Spin Foams

    SciTech Connect

    Baratin, Aristide; Wise, Derek K.

    2009-12-15

    Just as 3d state sum models, including 3d quantum gravity, can be built using categories of group representations, '2-categories of 2-group representations' may provide interesting state sum models for 4d quantum topology, if not quantum gravity. Here we focus on the 'Euclidean 2-group', built from the rotation group SO (4) and its action on the translation group R{sup 4} of Euclidean space. We explain its infinite-dimensional unitary representations, and construct a model based on the resulting representation 2-category. This model, with clear geometric content and explicit 'metric data' on triangulation edges, shows up naturally in an attempt to write the amplitudes of ordinary quantum field theory in a background independent way.

  2. Quantum correlations and tomographic representation

    NASA Astrophysics Data System (ADS)

    Man'ko, O. V.; Chernega, V. N.

    2013-07-01

    We review the probabilistic representation of quantum mechanics within which states are described by the probability distribution rather than by the wavefunction and density matrix. Uncertainty relations have been obtained in the form of integral inequalities containing measurable optical tomograms of quantum states. Formulas for the transition probabilities and purity parameter have been derived in terms of the tomographic probability distributions. Inequalities for Shannon and Rényi entropies associated with quantum tomograms have been obtained. A scheme of the star product of tomograms has been developed.

  3. Learning Sparse Representations of Depth

    NASA Astrophysics Data System (ADS)

    Tosic, Ivana; Olshausen, Bruno A.; Culpepper, Benjamin J.

    2011-09-01

    This paper introduces a new method for learning and inferring sparse representations of depth (disparity) maps. The proposed algorithm relaxes the usual assumption of the stationary noise model in sparse coding. This enables learning from data corrupted with spatially varying noise or uncertainty, typically obtained by laser range scanners or structured light depth cameras. Sparse representations are learned from the Middlebury database disparity maps and then exploited in a two-layer graphical model for inferring depth from stereo, by including a sparsity prior on the learned features. Since they capture higher-order dependencies in the depth structure, these priors can complement smoothness priors commonly used in depth inference based on Markov Random Field (MRF) models. Inference on the proposed graph is achieved using an alternating iterative optimization technique, where the first layer is solved using an existing MRF-based stereo matching algorithm, then held fixed as the second layer is solved using the proposed non-stationary sparse coding algorithm. This leads to a general method for improving solutions of state of the art MRF-based depth estimation algorithms. Our experimental results first show that depth inference using learned representations leads to state of the art denoising of depth maps obtained from laser range scanners and a time of flight camera. Furthermore, we show that adding sparse priors improves the results of two depth estimation methods: the classical graph cut algorithm by Boykov et al. and the more recent algorithm of Woodford et al.

  4. How the state vector configuration matters in multivariate data assimilation for streamflow predictions of snow-fed rivers

    NASA Astrophysics Data System (ADS)

    Bergeron, J.; Trudel, M.; Leconte, R.

    2014-12-01

    Hydrological modelling and streamflow prediction for watersheds over which multiple data sets are available can benefit from data assimilation. For example, updating modelled upstream flows and snow water equivalent (SWE) via existing correlations with downstream flow and SWE observations can positively impact short-term (days) and mid-term (weeks) streamflow forecast, respectively. Other variables can be updated indirectly if they are included in the state vector, which will further affect results. In order to fully benefit from existing correlations between variables, one may be tempted to augment the state vector to include all related variables and parameters, or choose to include a very limited number of variables in order to prevent erroneous correlations from deteriorating other model states. Localizing the correlations on the spatial level or between variables can also affect results. This makes it unclear as to how to configure the state vector, especially when multivariate observations are assimilated. This study presents a sensitivity analysis of the state vector configuration for synthetic multivariate data assimilation using an Ensemble Kalman filter. A spatially distributed hydrological model is used to simulate streamflow predictions for the mountainous Nechako River located in British-Columbia, Canada. Synthetic data includes daily snow cover extent, daily measurements of snow water equivalent (SWE) at three different locations and daily streamflow data at the watershed outlet. Results show a large variability of the Nash-Sutcliffe efficiency and streamflow bias over a wide range of prediction horizons (days to weeks) depending on the state vector configuration and the type of observations assimilated. Some configurations are shown to improve the accuracy of streamflow predictions while others offer worse results than the open loop simulation. These results serve as a first step toward comparing streamflow prediction performance of various real

  5. Sparse representation for vehicle recognition

    NASA Astrophysics Data System (ADS)

    Monnig, Nathan D.; Sakla, Wesam

    2014-06-01

    The Sparse Representation for Classification (SRC) algorithm has been demonstrated to be a state-of-the-art algorithm for facial recognition applications. Wright et al. demonstrate that under certain conditions, the SRC algorithm classification performance is agnostic to choice of linear feature space and highly resilient to image corruption. In this work, we examined the SRC algorithm performance on the vehicle recognition application, using images from the semi-synthetic vehicle database generated by the Air Force Research Laboratory. To represent modern operating conditions, vehicle images were corrupted with noise, blurring, and occlusion, with representation of varying pose and lighting conditions. Experiments suggest that linear feature space selection is important, particularly in the cases involving corrupted images. Overall, the SRC algorithm consistently outperforms a standard k nearest neighbor classifier on the vehicle recognition task.

  6. Berry phase in Heisenberg representation

    NASA Technical Reports Server (NTRS)

    Andreev, V. A.; Klimov, Andrei B.; Lerner, Peter B.

    1994-01-01

    We define the Berry phase for the Heisenberg operators. This definition is motivated by the calculation of the phase shifts by different techniques. These techniques are: the solution of the Heisenberg equations of motion, the solution of the Schrodinger equation in coherent-state representation, and the direct computation of the evolution operator. Our definition of the Berry phase in the Heisenberg representation is consistent with the underlying supersymmetry of the model in the following sense. The structural blocks of the Hamiltonians of supersymmetrical quantum mechanics ('superpairs') are connected by transformations which conserve the similarity in structure of the energy levels of superpairs. These transformations include transformation of phase of the creation-annihilation operators, which are generated by adiabatic cyclic evolution of the parameters of the system.

  7. Toward an evolutionary-predictive foundation for creativity : Commentary on "Human creativity, evolutionary algorithms, and predictive representations: The mechanics of thought trials" by Arne Dietrich and Hilde Haider, 2014 (Accepted pending minor revisions for publication in Psychonomic Bulletin & Review).

    PubMed

    Gabora, Liane; Kauffman, Stuart

    2016-04-01

    Dietrich and Haider (Psychonomic Bulletin & Review, 21 (5), 897-915, 2014) justify their integrative framework for creativity founded on evolutionary theory and prediction research on the grounds that "theories and approaches guiding empirical research on creativity have not been supported by the neuroimaging evidence." Although this justification is controversial, the general direction holds promise. This commentary clarifies points of disagreement and unresolved issues, and addresses mis-applications of evolutionary theory that lead the authors to adopt a Darwinian (versus Lamarckian) approach. To say that creativity is Darwinian is not to say that it consists of variation plus selection - in the everyday sense of the term - as the authors imply; it is to say that evolution is occurring because selection is affecting the distribution of randomly generated heritable variation across generations. In creative thought the distribution of variants is not key, i.e., one is not inclined toward idea A because 60 % of one's candidate ideas are variants of A while only 40 % are variants of B; one is inclined toward whichever seems best. The authors concede that creative variation is partly directed; however, the greater the extent to which variants are generated non-randomly, the greater the extent to which the distribution of variants can reflect not selection but the initial generation bias. Since each thought in a creative process can alter the selective criteria against which the next is evaluated, there is no demarcation into generations as assumed in a Darwinian model. We address the authors' claim that reduced variability and individuality are more characteristic of Lamarckism than Darwinian evolution, and note that a Lamarckian approach to creativity has addressed the challenge of modeling the emergent features associated with insight. PMID:26527351

  8. Multiscale Prediction and Verification of Water Fluxes and States over Large River Basins

    NASA Astrophysics Data System (ADS)

    Samaniego, L. E.; Rakovec, O.; Kumar, R.; Schaefer, D.; Cuntz, M.; Mai, J.; Thober, S.; Attinger, S.

    2014-12-01

    Developing the ability to predict streamflow at various scales is a key step for improving our understanding of the water balance and the skill of hydrologic models (HM). To cope with this grand challenge, we postulate: 1) validating a HM only against an integral basin response such as streamflow is a necessary but not a sufficient condition to warranty the proper partitioning of incoming precipitation and net-radiation into different water storage components and fluxes, 2 proper partitioning can be ensured by using additional multi-scale observations during parameter estimation (PE), and 3) HM should be evaluated at locations and scales different from those used for PE to ensure transferability. Water fluxes and states variables are estimated over the Pan-EU with the mesoscale hydrologic model (mHM). Its main features are the treatment of the sub-grid variability of input variables and model parameters and the possibility to estimate fluxes in nested-scales and/or in multiple basins keeping its regionalization coefficients unaltered across scales and basins. These essencial features allow to simulate fluxes and states and to evaluate them with disparate sources of information such as satellite, streamflow, and eddy covariance data at their native resolutions. mHM was setup over more than 340 Pan-European river basins. This model was forced with the gridded EOBS data set (1/4º, ECA&D) for the period 1950-2012. Morphological data was derived from the FAO soil map (1:5000000), the SRTM DEM (500 m), CORINE land cover (500 m), and MODIS LAI. The multi-scale evaluation was carried out using latent heat (LH) from FLUXNET stations and LandFlux-EVAL (1/2º), runoff from GRDC gauging stations, soil moisture from ESA-CCI (1/4º), total water storage (TWS) anomalies from GRACE (1º) and groundwater (GW) stage stations. Results lead to the conclusion that mHM water fluxes are robust since less than 25% of river basins exhibit Nash-Sutcliffe efficiencies of 0.5 or less

  9. Prediction of the Chapman-Jouguet chemical equilibrium state in a detonation wave from first principles based reactive molecular dynamics.

    PubMed

    Guo, Dezhou; Zybin, Sergey V; An, Qi; Goddard, William A; Huang, Fenglei

    2016-01-21

    The combustion or detonation of reacting materials at high temperature and pressure can be characterized by the Chapman-Jouguet (CJ) state that describes the chemical equilibrium of the products at the end of the reaction zone of the detonation wave for sustained detonation. This provides the critical properties and product kinetics for input to macroscale continuum simulations of energetic materials. We propose the ReaxFF Reactive Dynamics to CJ point protocol (Rx2CJ) for predicting the CJ state parameters, providing the means to predict the performance of new materials prior to synthesis and characterization, allowing the simulation based design to be done in silico. Our Rx2CJ method is based on atomistic reactive molecular dynamics (RMD) using the QM-derived ReaxFF force field. We validate this method here by predicting the CJ point and detonation products for three typical energetic materials. We find good agreement between the predicted and experimental detonation velocities, indicating that this method can reliably predict the CJ state using modest levels of computation. PMID:26688211

  10. Human Leg Model Predicts Muscle Forces, States, and Energetics during Walking

    PubMed Central

    Markowitz, Jared; Herr, Hugh

    2016-01-01

    Humans employ a high degree of redundancy in joint actuation, with different combinations of muscle and tendon action providing the same net joint torque. Both the resolution of these redundancies and the energetics of such systems depend on the dynamic properties of muscles and tendons, particularly their force-length relations. Current walking models that use stock parameters when simulating muscle-tendon dynamics tend to significantly overestimate metabolic consumption, perhaps because they do not adequately consider the role of elasticity. As an alternative, we posit that the muscle-tendon morphology of the human leg has evolved to maximize the metabolic efficiency of walking at self-selected speed. We use a data-driven approach to evaluate this hypothesis, utilizing kinematic, kinetic, electromyographic (EMG), and metabolic data taken from five participants walking at self-selected speed. The kinematic and kinetic data are used to estimate muscle-tendon lengths, muscle moment arms, and joint moments while the EMG data are used to estimate muscle activations. For each subject we perform an optimization using prescribed skeletal kinematics, varying the parameters that govern the force-length curve of each tendon as well as the strength and optimal fiber length of each muscle while seeking to simultaneously minimize metabolic cost and maximize agreement with the estimated joint moments. We find that the metabolic cost of transport (MCOT) values of our participants may be correctly matched (on average 0.36±0.02 predicted, 0.35±0.02 measured) with acceptable joint torque fidelity through application of a single constraint to the muscle metabolic budget. The associated optimal muscle-tendon parameter sets allow us to estimate the forces and states of individual muscles, resolving redundancies in joint actuation and lending insight into the potential roles and control objectives of the muscles of the leg throughout the gait cycle. PMID:27175486

  11. Human Leg Model Predicts Muscle Forces, States, and Energetics during Walking.

    PubMed

    Markowitz, Jared; Herr, Hugh

    2016-05-01

    Humans employ a high degree of redundancy in joint actuation, with different combinations of muscle and tendon action providing the same net joint torque. Both the resolution of these redundancies and the energetics of such systems depend on the dynamic properties of muscles and tendons, particularly their force-length relations. Current walking models that use stock parameters when simulating muscle-tendon dynamics tend to significantly overestimate metabolic consumption, perhaps because they do not adequately consider the role of elasticity. As an alternative, we posit that the muscle-tendon morphology of the human leg has evolved to maximize the metabolic efficiency of walking at self-selected speed. We use a data-driven approach to evaluate this hypothesis, utilizing kinematic, kinetic, electromyographic (EMG), and metabolic data taken from five participants walking at self-selected speed. The kinematic and kinetic data are used to estimate muscle-tendon lengths, muscle moment arms, and joint moments while the EMG data are used to estimate muscle activations. For each subject we perform an optimization using prescribed skeletal kinematics, varying the parameters that govern the force-length curve of each tendon as well as the strength and optimal fiber length of each muscle while seeking to simultaneously minimize metabolic cost and maximize agreement with the estimated joint moments. We find that the metabolic cost of transport (MCOT) values of our participants may be correctly matched (on average 0.36±0.02 predicted, 0.35±0.02 measured) with acceptable joint torque fidelity through application of a single constraint to the muscle metabolic budget. The associated optimal muscle-tendon parameter sets allow us to estimate the forces and states of individual muscles, resolving redundancies in joint actuation and lending insight into the potential roles and control objectives of the muscles of the leg throughout the gait cycle. PMID:27175486

  12. Fluctuations of spontaneous EEG topographies predict disease state in relapsing-remitting multiple sclerosis.

    PubMed

    Gschwind, Markus; Hardmeier, Martin; Van De Ville, Dimitri; Tomescu, Miralena I; Penner, Iris-Katharina; Naegelin, Yvonne; Fuhr, Peter; Michel, Christoph M; Seeck, Margitta

    2016-01-01

    Spontaneous fluctuations of neuronal activity in large-scale distributed networks are a hallmark of the resting brain. In relapsing-remitting multiple sclerosis (RRMS) several fMRI studies have suggested altered resting-state connectivity patterns. Topographical EEG analysis reveals much faster temporal fluctuations in the tens of milliseconds time range (termed "microstates"), which showed altered properties in a number of neuropsychiatric conditions. We investigated whether these microstates were altered in patients with RRMS, and if the microstates' temporal properties reflected a link to the patients' clinical features. We acquired 256-channel EEG in 53 patients (mean age 37.6 years, 45 females, mean disease duration 9.99 years, Expanded Disability Status Scale ≤ 4, mean 2.2) and 49 healthy controls (mean age 36.4 years, 33 females). We analyzed segments of a total of 5 min of EEG during resting wakefulness and determined for both groups the four predominant microstates using established clustering methods. We found significant differences in the temporal dynamics of two of the four microstates between healthy controls and patients with RRMS in terms of increased appearance and prolonged duration. Using stepwise multiple linear regression models with 8-fold cross-validation, we found evidence that these electrophysiological measures predicted a patient's total disease duration, annual relapse rate, disability score, as well as depression score, and cognitive fatigue measure. In RRMS patients, microstate analysis captured altered fluctuations of EEG topographies in the sub-second range. This measure of high temporal resolution provided potentially powerful markers of disease activity and neuropsychiatric co-morbidities in RRMS. PMID:27625987

  13. Abnormal Resting State fMRI Activity Predicts Processing Speed Deficits in First-Episode Psychosis

    PubMed Central

    Argyelan, Miklos; Gallego, Juan A; Robinson, Delbert G; Ikuta, Toshikazu; Sarpal, Deepak; John, Majnu; Kingsley, Peter B; Kane, John; Malhotra, Anil K; Szeszko, Philip R

    2015-01-01

    Little is known regarding the neuropsychological significance of resting state functional magnetic resonance imaging (rs-fMRI) activity early in the course of psychosis. Moreover, no studies have used different approaches for analysis of rs-fMRI activity and examined gray matter thickness in the same cohort. In this study, 41 patients experiencing a first-episode of psychosis (including N=17 who were antipsychotic drug-naive at the time of scanning) and 41 individually age- and sex-matched healthy volunteers completed rs-fMRI and structural MRI exams and neuropsychological assessments. We computed correlation matrices for 266 regions-of-interest across the brain to assess global connectivity. In addition, independent component analysis (ICA) was used to assess group differences in the expression of rs-fMRI activity within 20 predefined publicly available templates. Patients demonstrated lower overall rs-fMRI global connectivity compared with healthy volunteers without associated group differences in gray matter thickness assessed within the same regions-of-interest used in this analysis. Similarly, ICA revealed worse rs-fMRI expression scores across all 20 networks in patients compared with healthy volunteers, with posthoc analyses revealing significant (p<0.05; corrected) abnormalities within the caudate nucleus and planum temporale. Worse processing speed correlated significantly with overall lower global connectivity using the region-of-interest approach and lower expression scores within the planum temporale using ICA. Our findings implicate dysfunction in rs-fMRI activity in first-episode psychosis prior to extensive antipsychotic treatment using different analytic approaches (in the absence of concomitant gray matter structural differences) that predict processing speed. PMID:25567423

  14. Improving the Prediction of Baseflows in the Driftless Area of the Upper Midwestern United States

    NASA Astrophysics Data System (ADS)

    Schuster, Z.; Potter, K. W.

    2014-12-01

    The Driftless Area of the Upper Midwestern United States is a unique region that was not glaciated during the Quaternary Period. Groundwater discharges in the hilly landscape support over 4,000 miles of coldwater, high-class trout streams that are a destination for anglers across the Midwest. Temperature increases due to anthropogenic climate change are predicted to have a negative impact on the cold water thermal regimes that support species such as brook and brown trout. Previous work has concluded that the hillslopes in the region play an important role in producing the recharge that supports cool groundwater discharges concentrated in the headwaters of these streams. In this study, we used a set of baseflow measurements recorded by Potter and Gaffield (2001) in the headwaters of a Driftless Area stream and a simple Geographic Information Systems (GIS) analysis to assess the relationship between the percentage of hillslope in a watershed and average unit baseflow. We found that there is a strong correlation between the hillslope percentage and the unit baseflow values from the Potter and Gaffield (2001) study. Further work is needed to verify the findings of this study and to assess the impacts of the underlying geological layers on the production of baseflow, but these results provide a first step in understanding the conditions that produce spatial variability in baseflow conditions in the Driftless Area. Agencies such as the Wisconsin Department of Natural Resources are beginning to plan for climate change adaptation in the region to protect the coldwater fisheries, so understanding the hydrology of headwater streams will be important in helping to identify areas with high, coldwater baseflow discharges that can provided refugia for coldwater species.

  15. Predicting missing expression values in gene regulatory networks using a discrete logic modeling optimization guided by network stable states

    PubMed Central

    Crespo, Isaac; Krishna, Abhimanyu; Le Béchec, Antony; del Sol, Antonio

    2013-01-01

    The development of new high-throughput technologies enables us to measure genome-wide transcription levels, protein abundance, metabolite concentration, etc. Nevertheless, these experimental data are often noisy and incomplete, which hinders data analysis, modeling and prediction. Here, we propose a method to predict expression values of genes involved in stable cellular phenotypes from the expression values of the remaining genes in a literature-based gene regulatory network. The consistency between predicted and known stable states from experimental data is used to guide an iterative network pruning that contextualizes the network to the biological conditions under which the expression data were obtained. Using the contextualized network and the property of network stability we predict gene expression values missing from experimental data. The prediction method assumes a Boolean model to compute steady states of networks and an evolutionary algorithm to iteratively prune the networks. The evolutionary algorithm samples the probability distribution of positive feedback loops or positive circuits and individual interactions within the subpopulation of the best-pruned networks at each iteration. The resulting expression inference is based not only on previous knowledge about local connectivity but also on a global network property (stability), providing robustness in the predictions. PMID:22941654

  16. Computer aided surface representation

    SciTech Connect

    Barnhill, R.E.

    1989-02-09

    The central research problem of this project is the effective representation and display of surfaces, interpolating to given information, in three or more dimensions. In a typical problem, we wish to create a surface from some discrete information. If this information is itself on another surface, the problem is to determine a surface defined on a surface,'' which is discussed below. Often, properties of an already constructed surface are desired: such geometry processing'' is described below. The Summary of Proposed Research from our original proposal describes the aims of this research project. This Summary and the Table of Contents from the original proposal are enclosed as an Appendix to this Progress Report. The broad sweep from constructive mathematics through algorithms and computer graphics displays is utilized in the research. The wide range of activity, directed in both theory and applications, makes this project unique. Last month in the first Ardent Titan delivered in the State of Arizona came to our group, funded by the DOE and Arizona State University. Although the Titan is a commercial product, its newness requires our close collaboration with Ardent to maximize results. During the past year, four faculty members and several graduate research assistants have worked on this DOE project. The gaining of new professionals is an important aspect of this project. A listing of the students and their topics is given in the Appendix. The most significant publication during the past year is the book, Curves and Surfaces for Computer Aided Geometric Design, by Dr. Gerald Farin. This 300 page volume helps fill a considerable gap in the subject and includes many new results on Bernstein-Bezier curves and surfaces.

  17. State-of-the-Science Report on Predictive Models and Modeling Approaches for Characterizing and Evaluating Exposure to Nanomaterials

    EPA Science Inventory

    This state-of-the-science review was undertaken to identify fate and transport models and alternative modeling approaches that could be used to predict exposure to engineered nanomaterials (ENMs) released into the environment, specifically, for aquatic systems. The development of...

  18. Predictive Factors in Undergraduates' Involvement in Campus Secret Cults in Public Universities in Edo State of Nigeria

    ERIC Educational Resources Information Center

    Azetta Arhedo, Philip; Aluede, Oyaziwo; Adomeh, Ilu O. C.

    2011-01-01

    This study examined the predictive factors in undergraduates' involvement in campus secret cults in public universities in Edo State of Nigeria. The study employed the descriptive method, specifically the survey format. A random sample of three hundred and eighty (380) undergraduates was drawn from the two public universities. Data were elicited…

  19. Data worth and prediction uncertainty for pesticide transport and fate models in Nebraska and Maryland, United States

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Few studies have attempted to quantify mass balances of both pesticides and degradates in multiple agricultural settings of the United States. We used inverse modeling to calibrate the Root Zone Water Quality Model (RZWQM) for predicting the unsaturated-zone transport and fate of metolachlor, metola...

  20. A prediction of the rotational states for partially deuterated ammonium ions in NH4 - xDxClO4

    NASA Astrophysics Data System (ADS)

    Maki, Kazuo

    1983-01-01

    Splittings of the librational ground state of partially deuterated ammonium ions in the ammonium perchlorate crystal are calculated. Heat capacity anomalies are predicted to be observed at around 1-3 K, a careful measurement of which will be very useful for characterizing the anisotropy of the rotational potential.

  1. Efficient visual tracking via low-complexity sparse representation

    NASA Astrophysics Data System (ADS)

    Lu, Weizhi; Zhang, Jinglin; Kpalma, Kidiyo; Ronsin, Joseph

    2015-12-01

    Thanks to its good performance on object recognition, sparse representation has recently been widely studied in the area of visual object tracking. Up to now, little attention has been paid to the complexity of sparse representation, while most works are focused on the performance improvement. By reducing the computation load related to sparse representation hundreds of times, this paper proposes by far the most computationally efficient tracking approach based on sparse representation. The proposal simply consists of two stages of sparse representation, one is for object detection and the other for object validation. Experimentally, it achieves better performance than some state-of-the-art methods in both accuracy and speed.

  2. Predicting Persistence and Withdrawal of Open Admissions Students at Virginia State University.

    ERIC Educational Resources Information Center

    Tambe, Joseph T.

    1984-01-01

    A study of persistence/dropout among open admissions college students found: (1) accurate predictions cannot be made for individual students at the time of matriculation; and (2) it is possible to predict that about 80 percent of future groups will fall in the persist category after two semesters, 51 percent after four semesters. (CMG)

  3. Prediction of State Mandated Assessment Mathematics Scores from Computer Based Mathematics and Reading Preview Assessments

    ERIC Educational Resources Information Center

    Costa-Guerra, Boris

    2012-01-01

    The study sought to understand whether MAPs computer based assessment of math and language skills using MAPs reading scores can predict student scores on the NMSBA. A key question was whether or not the prediction can be improved by including student language skill scores. The study explored the effectiveness of computer based preview assessments…

  4. A climate-based model predicts the spatial distribution of the Lyme disease vector Ixodes scapularis in the United States.

    PubMed Central

    Brownstein, John S; Holford, Theodore R; Fish, Durland

    2003-01-01

    An understanding of the spatial distribution of the black-legged tick, Ixodes scapularis, is a fundamental component in assessing human risk for Lyme disease in much of the United States. Although a county-level vector distribution map exists for the United States, its accuracy is limited by arbitrary categories of its reported presence. It is unknown whether reported positive areas can support established populations and whether negative areas are suitable for established populations. The steadily increasing range of I. scapularis in the United States suggests that all suitable habitats are not currently occupied. Therefore, we developed a spatially predictive logistic model for I. scapularis in the 48 conterminous states to improve the previous vector distribution map. We used ground-observed environmental data to predict the probability of established I. scapularis populations. The autologistic analysis showed that maximum, minimum, and mean temperatures as well as vapor pressure significantly contribute to population maintenance with an accuracy of 95% (p < 0.0001). A cutoff probability for habitat suitability was assessed by sensitivity analysis and was used to reclassify the previous distribution map. The spatially modeled relationship between I. scapularis presence and large-scale environmental data provides a robust suitability model that reveals essential environmental determinants of habitat suitability, predicts emerging areas of Lyme disease risk, and generates the future pattern of I. scapularis across the United States. PMID:12842766

  5. Torque prediction using stimulus evoked EMG and its identification for different muscle fatigue states in SCI subjects.

    PubMed

    Zhang, Qin; Hayashibe, Mitsuhiro; Papaiordanidou, Maria; Fraisse, Philippe; Fattal, Charles; Guiraud, David

    2010-01-01

    Muscle fatigue is an unavoidable problem when electrical stimulation is applied to paralyzed muscles. The detection and compensation of muscle fatigue is essential to avoid movement failure and achieve desired trajectory. This work aims to predict ankle plantar-flexion torque using stimulus evoked EMG (eEMG) during different muscle fatigue states. Five spinal cord injured patients were recruited for this study. An intermittent fatigue protocol was delivered to triceps surae muscle to induce muscle fatigue. A hammerstein model was used to capture the muscle contraction dynamics to represent eEMG-torque relationship. The prediction of ankle torque was based on measured eEMG and past measured or past predicted torque. The latter approach makes it possible to use eEMG as a synthetic force sensor when force measurement is not available in daily use. Some previous researches suggested to use eEMG information directly to detect and predict muscle force during fatigue assuming a fixed relationship between eEMG and generated force. However, we found that the prediction became less precise with the increase of muscle fatigue when fixed parameter model was used. Therefore, we carried out the torque prediction with an adaptive parameters using the latest measurement. The prediction of adapted model was improved with 16.7%-50.8% comparing to the fixed model. PMID:21097036

  6. Ensemble Canonical Correlation Prediction of Seasonal Precipitation Over the United States: Raising the Bar for Dynamical Model Forecasts

    NASA Technical Reports Server (NTRS)

    Lau, William K. M.; Kim, Kyu-Myong; Shen, S. P.

    2001-01-01

    This paper presents preliminary results of an ensemble canonical correlation (ECC) prediction scheme developed at the Climate and Radiation Branch, NASA/Goddard Space Flight Center for determining the potential predictability of regional precipitation, and for climate downscaling studies. The scheme is tested on seasonal hindcasts of anomalous precipitation over the continental United States using global sea surface temperature (SST) for 1951-2000. To maximize the forecast skill derived from SST, the world ocean is divided into non-overlapping sectors. The canonical SST modes for each sector are used as the predictor for the ensemble hindcasts. Results show that the ECC yields a substantial (10-25%) increase in prediction skills for all the regions of the US in every season compared to traditional CCA prediction schemes. For the boreal winter, the tropical Pacific contributes the largest potential predictability to precipitation in the southwestern and southeastern regions, while the North Pacific and the North Atlantic are responsible to the enhanced forecast skills in the Pacific Northwest, the northern Great Plains and Ohio Valley. Most importantly, the ECC increases skill for summertime precipitation prediction and substantially reduces the spring predictability barrier over all the regions of the US continent. Besides SST, the ECC is designed with the flexibility to include any number of predictor fields, such as soil moisture, snow cover and additional local observations. The enhanced ECC forecast skill provides a new benchmark for evaluating dynamical model forecasts.

  7. Phase space representation of quantum dynamics

    SciTech Connect

    Polkovnikov, Anatoli

    2010-08-15

    We discuss a phase space representation of quantum dynamics of systems with many degrees of freedom. This representation is based on a perturbative expansion in quantum fluctuations around one of the classical limits. We explicitly analyze expansions around three such limits: (i) corpuscular or Newtonian limit in the coordinate-momentum representation, (ii) wave or Gross-Pitaevskii limit for interacting bosons in the coherent state representation, and (iii) Bloch limit for the spin systems. We discuss both the semiclassical (truncated Wigner) approximation and further quantum corrections appearing in the form of either stochastic quantum jumps along the classical trajectories or the nonlinear response to such jumps. We also discuss how quantum jumps naturally emerge in the analysis of non-equal time correlation functions. This representation of quantum dynamics is closely related to the phase space methods based on the Wigner-Weyl quantization and to the Keldysh technique. We show how such concepts as the Wigner function, Weyl symbol, Moyal product, Bopp operators, and others automatically emerge from the Feynmann's path integral representation of the evolution in the Heisenberg representation. We illustrate the applicability of this expansion with various examples mostly in the context of cold atom systems including sine-Gordon model, one- and two-dimensional Bose-Hubbard model, Dicke model and others.

  8. General Regression and Representation Model for Classification

    PubMed Central

    Qian, Jianjun; Yang, Jian; Xu, Yong

    2014-01-01

    Recently, the regularized coding-based classification methods (e.g. SRC and CRC) show a great potential for pattern classification. However, most existing coding methods assume that the representation residuals are uncorrelated. In real-world applications, this assumption does not hold. In this paper, we take account of the correlations of the representation residuals and develop a general regression and representation model (GRR) for classification. GRR not only has advantages of CRC, but also takes full use of the prior information (e.g. the correlations between representation residuals and representation coefficients) and the specific information (weight matrix of image pixels) to enhance the classification performance. GRR uses the generalized Tikhonov regularization and K Nearest Neighbors to learn the prior information from the training data. Meanwhile, the specific information is obtained by using an iterative algorithm to update the feature (or image pixel) weights of the test sample. With the proposed model as a platform, we design two classifiers: basic general regression and representation classifier (B-GRR) and robust general regression and representation classifier (R-GRR). The experimental results demonstrate the performance advantages of proposed methods over state-of-the-art algorithms. PMID:25531882

  9. Failure Mode Classification for Life Prediction Modeling of Solid-State Lighting

    SciTech Connect

    Sakalaukus, Peter Joseph

    2015-08-01

    Since the passing of the Energy Independence and Security Act of 2007, the U.S. government has mandated greater energy independence which has acted as a catalyst for accelerating and facilitating research efforts toward the development and deployment of market-driven solutions for energy-saving homes, buildings and manufacturing, as well as sustainable transportation and renewable electricity generation. As part of this effort, an emphasis toward advancing solid-state lighting technology through research, development, demonstration, and commercial applications is assisting in the phase out of the common incandescent light bulb, as well as developing a more economical lighting source that is less toxic than compact fluorescent lighting. This has led lighting manufacturers to pursue SSL technologies for a wide range of consumer lighting applications. An SSL luminaire’s lifetime can be characterized in terms of lumen maintenance life. Lumen maintenance or lumen depreciation is the percentage decrease in the relative luminous flux from that of the original, pristine luminous flux value. Lumen maintenance life is the estimated operating time, in hours, when the desired failure threshold is projected to be reached at normal operating conditions. One accepted failure threshold of SSL luminaires is lumen maintenance of 70% -- a 30% reduction in the light output of the luminaire. Currently, the only approved lighting standard that puts forth a recommendation for long-term luminous flux maintenance projections towards a specified failure threshold of an SSL luminaire is the IES TM-28-14 (TM28) standard. iii TM28 was derived as a means to compare luminaires that have been tested at different facilities, research labs or companies. TM28 recommends the use of the Arrhenius equation to determine SSL device specific reaction rates from thermally driven failure mechanisms used to characterize a single failure mode – the relative change in the luminous flux output or

  10. Toward Improved Off-Shore Wind Predictions by Combining Observations with Models through State Estimation - An Analysis of Marine Boundary Layer Parameterizations

    NASA Astrophysics Data System (ADS)

    Kosovic, B.; Delle Monache, L.; Hacker, J.; Lee, J. A.; Vandenberghe, F. C.; Wu, Y.; Clifton, A.; Hawkins, S.; Nissen, J.; Rostkier-Edelstein, D.

    2014-12-01

    In recent years, significant advances have been achieved in model representation of atmospheric boundary layers (ABL). However, fundamental understanding of the processes governing the evolution of the Marine Boundary Layer (MBL) is still incomplete. We address this problem by combining available atmosphere and ocean observations with advanced coupled atmosphere-wave models, via state estimation (SE) methodologies. The goal is to improve wind prediction for off-shore wind energy applications through advances in understanding and parameterization of underlying physical processes, with an emphasis on the coupling between the atmosphere and the ocean via momentum and heat fluxes. We systematically investigate the errors in the treatment of the surface layer of the MBL in the Weather Research and Forecasting (WRF) model and identify structural model inadequacies associated with the MBL parameterization. For this purpose we are using both the single-column model (SCM) and three-dimensional (3D) versions of the WRF model, observations of MBL structure provided by offshore observational platform FINO1, and probabilistic SE. We have also developed an atmosphere-wave coupled modeling system by interfacing WRF with a wave model (WaveWatch III - WWIII). This modeling system is used for evaluating errors in the representation of wave-induced forcing on the energy balance at the interface between atmosphere and ocean. Probabilistic SE is based on the Data Assimilation Research Testbed (DART). DART is the framework for obtaining spatial and temporal statistics of wind-error evolution (and hence the surface-layer fluxes), along with objective tuning of model parameters. We explore one of the potential sources of MBL model errors associated with roughness length parameterized using Charnock's relation. Charnock's roughness length parameterization assumes wind-driven waves are in equilibrium. However, it has been shown that swells propagating at different speeds and angles with

  11. Predicting State Investment in Medicaid Home- and Community-Based Services, 2000-2011.

    PubMed

    Miller, Nancy A; Kirk, Adele

    2016-01-01

    Although state use of Medicaid home- and community-based services (HCBS) to provide long-term services and supports to older adults and individuals with physical disabilities continues to increase, progress is uneven across states. We used generalized linear models to examine state factors associated with increased allocation of Medicaid dollars to HCBS for the period 2000 to 2011. We observed enhanced growth in states that began the period with limited investment in HCBS, as reflected in significant year trends among these states. The political environment appeared to be an important influence on states' investment for states with limited initial allocation to HCBS, as was housing affordability, a policy amenable variable. There continues to be wide variation in states' relative investment, calling for additional policy attention and research. PMID:26549155

  12. Ground Motion Prediction Equations for the Central and Eastern United States

    NASA Astrophysics Data System (ADS)

    Seber, D.; Graizer, V.

    2015-12-01

    New ground motion prediction equations (GMPE) G15 model for the Central and Eastern United States (CEUS) is presented. It is based on the modular filter based approach developed by Graizer and Kalkan (2007, 2009) for active tectonic environment in the Western US (WUS). The G15 model is based on the NGA-East database for the horizontal peak ground acceleration and 5%-damped pseudo spectral acceleration RotD50 component (Goulet et al., 2014). In contrast to active tectonic environment the database for the CEUS is not sufficient for creating purely empirical GMPE covering the range of magnitudes and distances required for seismic hazard assessments. Recordings in NGA-East database are sparse and cover mostly range of M<6.0 with limited amount of near-fault recordings. The functional forms of the G15 GMPEs are derived from filters—each filter represents a particular physical phenomenon affecting the seismic wave radiation from the source. Main changes in the functional forms for the CEUS relative to the WUS model (Graizer and Kalkan, 2015) are a shift of maximum frequency of the acceleration response spectrum toward higher frequencies and an increase in the response spectrum amplitudes at high frequencies. Developed site correction is based on multiple runs of representative VS30 profiles through SHAKE-type equivalent-linear programs using time histories and random vibration theory approaches. Site amplification functions are calculated for different VS30 relative to hard rock definition used in nuclear industry (Vs=2800 m/s). The number of model predictors is limited to a few measurable parameters: moment magnitude M, closest distance to fault rupture plane R, average shear-wave velocity in the upper 30 m of the geological profile VS30, and anelastic attenuation factor Q0. Incorporating anelastic attenuation Q0 as an input parameter allows adjustments based on the regional crustal properties. The model covers the range of magnitudes 4.0

  13. Phonological Representations and Early Literacy in Chinese

    ERIC Educational Resources Information Center

    Kidd, Joanna C.; Shum, Kathy Kar-Man; Ho, Connie Suk-Han; Au, Terry Kit-fong

    2015-01-01

    Phonological processing skills predict early reading development, but what underlies developing phonological processing skills? Phonological representations of 140 native Cantonese-speaking Chinese children (age 4-10) were assessed with speech gating, mispronunciation detection, and nonword repetition tasks; their nonverbal IQ, reading, and…

  14. Contacts de langues et representations (Language Contacts and Representations).

    ERIC Educational Resources Information Center

    Matthey, Marinette, Ed.

    1997-01-01

    Essays on language contact and the image of language, entirely in French, include: "Representations 'du' contexte et representations 'en' contexte? Eleves et enseignants face a l'apprentissage de la langue" ("Representations 'of' Context or Representations 'in' Context? Students and Teachers Facing Language Learning" (Laurent Gajo); "Le crepuscule…

  15. Predictive Models for Carcinogenicity and Mutagenicity: Frameworks, State-of-the-Art, and Perspectives

    EPA Science Inventory

    Mutagenicity and carcinogenicity are endpoints of major environmental and regulatory concern. These endpoints are also important targets for development of alternative methods for screening and prediction due to the large number of chemicals of potential concern and the tremendou...

  16. Predictive Models for Carcinogenicity and Mutagenicity: Frameworks,State-of-the-Art, and Perspectives

    EPA Science Inventory

    Mutagenicity and carcinogenicity are endpoints of major environmental and regulatory concern. These endpoints are also important targets for development of alternative methods for screening and prediction due to the large number of chemicals of potential concern and the tremendou...

  17. Exploring the Structure of Spatial Representations.

    PubMed

    Madl, Tamas; Franklin, Stan; Chen, Ke; Trappl, Robert; Montaldi, Daniela

    2016-01-01

    It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these 'cognitive maps' are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics) characterizing participants' psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants' cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants' spatial representations, providing further support for clustering in spatial memory. PMID:27347681

  18. Exploring the Structure of Spatial Representations

    PubMed Central

    Madl, Tamas; Franklin, Stan; Chen, Ke; Trappl, Robert; Montaldi, Daniela

    2016-01-01

    It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these ‘cognitive maps’ are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics) characterizing participants’ psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants’ cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants’ spatial representations, providing further support for clustering in spatial memory. PMID:27347681

  19. A history of wind erosion prediction models in the United States Department of Agriculture prior to the Wind Erosion Prediction System

    NASA Astrophysics Data System (ADS)

    Tatarko, John; Sporcic, Michael A.; Skidmore, Edward L.

    2013-09-01

    The Great Plains experienced an influx of settlers in the late 1850s-1900. Periodic drought was hard on both settlers and the soil and caused severe wind erosion. The period known as the Dirty Thirties, 1931-1939, produced many severe windstorms, and the resulting dusty sky over Washington, DC helped Hugh Hammond Bennett gain political support for the Soil Conservation Act of 1937 that started the USDA Soil Conservation Service (SCS). Austin W. Zingg and William S. Chepil began wind erosion studies at a USDA laboratory at Kansas State University in 1947. Neil P. Woodruff and Francis H. Siddoway published the first widely used model for wind erosion in 1965, called the Wind Erosion Equation (WEQ). The WEQ was solved using a series of charts and lookup tables. Subsequent improvements to WEQ included monthly magnitudes of the total wind, a computer version of WEQ programmed in FORTRAN, small-grain equivalents for range grasses, tillage systems, effects of residue management, crop row direction, cloddiness, monthly climate factors, and the weather. The SCS and the Natural Resources Conservation Service (NRCS) produced several computer versions of WEQ with the goal of standardizing and simplifying it for field personnel including a standalone version of WEQ was developed in the late 1990s using Microsoft Excel. Although WEQ was a great advancement to the science of prediction and control of wind erosion on cropland, it had many limitations that prevented its use on many lands throughout the United States and the world. In response to these limitations, the USDA developed a process-based model know as the Wind Erosion Prediction System (WEPS). The USDA Agricultural Research Service has taken the lead in developing science and technology for wind erosion prediction.

  20. Long-lead predictions of eastern United States hot days from Pacific sea surface temperatures

    NASA Astrophysics Data System (ADS)

    McKinnon, K. A.; Rhines, A.; Tingley, M. P.; Huybers, P.

    2016-05-01

    Seasonal forecast models exhibit only modest skill in predicting extreme summer temperatures across the eastern US. Anomalies in sea surface temperature and monthly-resolution rainfall have, however, been correlated with hot days in the US, and seasonal persistence of these anomalies suggests potential for long-lead predictability. Here we present a clustering analysis of daily maximum summer temperatures from US weather stations between 1982-2015 and identify a region spanning most of the eastern US where hot weather events tend to occur synchronously. We then show that an evolving pattern of sea surface temperature anomalies, termed the Pacific Extreme Pattern, provides for skillful prediction of hot weather within this region as much as 50 days in advance. Skill is demonstrated using out-of-sample predictions between 1950 and 2015. Rainfall deficits over the eastern US are also associated with the occurrence of the Pacific Extreme Pattern and are demonstrated to offer complementary skill in predicting high temperatures. The Pacific Extreme Pattern appears to provide a cohesive framework for improving seasonal prediction of summer precipitation deficits and high temperature anomalies in the eastern US.

  1. The nature, scope and impact of genomic prediction in beef cattle in the United States

    PubMed Central

    2011-01-01

    Artificial selection has proven to be effective at altering the performance of animal production systems. Nevertheless, selection based on assessment of the genetic superiority of candidates is suboptimal as a result of errors in the prediction of genetic merit. Conventional breeding programs may extend phenotypic measurements on selection candidates to include correlated indicator traits, or delay selection decisions well beyond puberty so that phenotypic performance can be observed on progeny or other relatives. Extending the generation interval to increase the accuracy of selection reduces annual rates of gain compared to accurate selection and use of parents of the next generation at the immediate time they reach breeding age. Genomic prediction aims at reducing prediction errors at breeding age by exploiting information on the transmission of chromosome fragments from parents to selection candidates, in conjunction with knowledge on the value of every chromosome fragment. For genomic prediction to influence beef cattle breeding programs and the rate or cost of genetic gains, training analyses must be undertaken, and genomic prediction tools made available for breeders and other industry stakeholders. This paper reviews the nature or kind of studies currently underway, the scope or extent of some of those studies, and comments on the likely predictive value of genomic information for beef cattle improvement. PMID:21569623

  2. Spin-glass model predicts metastable brain states that diminish in anesthesia

    PubMed Central

    Hudetz, Anthony G.; Humphries, Colin J.; Binder, Jeffrey R.

    2014-01-01

    Patterns of resting state connectivity change dynamically and may represent modes of cognitive information processing. The diversity of connectivity patterns (global brain states) reflects the information capacity of the brain and determines the state of consciousness. In this work, computer simulation was used to explore the repertoire of global brain states as a function of cortical activation level. We implemented a modified spin glass model to describe UP/DOWN state transitions of neuronal populations at a mesoscopic scale based on resting state BOLD fMRI data. Resting state fMRI was recorded in 20 participants and mapped to 10,000 cortical regions (sites) defined on a group-aligned cortical surface map. Each site represented the population activity of a ~20 mm2 area of the cortex. Cross-correlation matrices of the mapped BOLD time courses of the set of sites were calculated and averaged across subjects. In the model, each cortical site was allowed to interact with the 16 other sites that had the highest pair-wise correlation values. All sites stochastically transitioned between UP and DOWN states under the net influence of their 16 pairs. The probability of local state transitions was controlled by a single parameter T corresponding to the level of global cortical activation. To estimate the number of distinct global states, first we ran 10,000 simulations at T = 0. Simulations were started from random configurations that converged to one of several distinct patterns. Using hierarchical clustering, at 99% similarity, close to 300 distinct states were found. At intermediate T, metastable state configurations were formed suggesting critical behavior with a sharp increase in the number of metastable states at an optimal T. Both reduced activation (anesthesia, sleep) and increased activation (hyper-activation) moved the system away from equilibrium, presumably incompatible with conscious mentation. During equilibrium, the diversity of large-scale brain states was

  3. Action simulation: time course and representational mechanisms

    PubMed Central

    Springer, Anne; Parkinson, Jim; Prinz, Wolfgang

    2013-01-01

    The notion of action simulation refers to the ability to re-enact foreign actions (i.e., actions observed in other individuals). Simulating others' actions implies a mirroring of their activities, based on one's own sensorimotor competencies. Here, we discuss theoretical and experimental approaches to action simulation and the study of its representational underpinnings. One focus of our discussion is on the timing of internal simulation and its relation to the timing of external action, and a paradigm that requires participants to predict the future course of actions that are temporarily occluded from view. We address transitions between perceptual mechanisms (referring to action representation before and after occlusion) and simulation mechanisms (referring to action representation during occlusion). Findings suggest that action simulation runs in real-time; acting on newly created action representations rather than relying on continuous visual extrapolations. A further focus of our discussion pertains to the functional characteristics of the mechanisms involved in predicting other people's actions. We propose that two processes are engaged, dynamic updating and static matching, which may draw on both semantic and motor information. In a concluding section, we discuss these findings in the context of broader theoretical issues related to action and event representation, arguing that a detailed functional analysis of action simulation in cognitive, neural, and computational terms may help to further advance our understanding of action cognition and motor control. PMID:23847563

  4. Superalgebraic representation of Dirac matrices

    NASA Astrophysics Data System (ADS)

    Monakhov, V. V.

    2016-01-01

    We consider a Clifford extension of the Grassmann algebra in which operators are constructed from products of Grassmann variables and derivatives with respect to them. We show that this algebra contains a subalgebra isomorphic to a matrix algebra and that it additionally contains operators of a generalized matrix algebra that mix states with different numbers of Grassmann variables. We show that these operators are extensions of spin-tensors to the case of superspace. We construct a representation of Dirac matrices in the form of operators of a generalized matrix algebra.

  5. The state of the art of predicting noise-induced sleep disturbance in field settings.

    PubMed

    Fidell, Sanford; Tabachnick, Barbara; Pearsons, Karl S

    2010-01-01

    Several relationships between intruding noises (largely aircraft) and sleep disturbance have been inferred from the findings of a handful of field studies. Comparisons of sleep disturbance rates predicted by the various relationships are complicated by inconsistent data collection methods and definitions of predictor variables and predicted quantities. None of the relationships is grounded in theory-based understanding, and some depend on questionable statistical assumptions and analysis procedures. The credibility, generalizability, and utility of sleep disturbance predictions are also limited by small and nonrepresentative samples of test participants, and by restricted (airport-specific and relatively short duration) circumstances of exposure. Although expedient relationships may be the best available, their predictions are of only limited utility for policy analysis and regulatory purposes, because they account for very little variance in the association between environmental noise and sleep disturbance, have characteristically shallow slopes, have not been well validated in field settings, are highly context-dependent, and do not squarely address the roles and relative importance of nonacoustic factors in sleep disturbance. Such relationships offer the appearance more than the substance of precision and objectivity. Truly useful, population-level prediction and genuine understanding of noise-induced sleep disturbance will remain beyond reach for the foreseeable future, until the findings of field studies of broader scope and more sophisticated design become available. PMID:20472953

  6. Unitary Transformations in the Quantum Model for Conceptual Conjunctions and Its Application to Data Representation.

    PubMed

    Veloz, Tomas; Desjardins, Sylvie

    2015-01-01

    Quantum models of concept combinations have been successful in representing various experimental situations that cannot be accommodated by traditional models based on classical probability or fuzzy set theory. In many cases, the focus has been on producing a representation that fits experimental results to validate quantum models. However, these representations are not always consistent with the cognitive modeling principles. Moreover, some important issues related to the representation of concepts such as the dimensionality of the realization space, the uniqueness of solutions, and the compatibility of measurements, have been overlooked. In this paper, we provide a dimensional analysis of the realization space for the two-sector Fock space model for conjunction of concepts focusing on the first and second sectors separately. We then introduce various representation of concepts that arise from the use of unitary operators in the realization space. In these concrete representations, a pair of concepts and their combination are modeled by a single conceptual state, and by a collection of exemplar-dependent operators. Therefore, they are consistent with cognitive modeling principles. This framework not only provides a uniform approach to model an entire data set, but, because all measurement operators are expressed in the same basis, allows us to address the question of compatibility of measurements. In particular, we present evidence that it may be possible to predict non-commutative effects from partial measurements of conceptual combinations. PMID:26617556

  7. Unitary Transformations in the Quantum Model for Conceptual Conjunctions and Its Application to Data Representation

    PubMed Central

    Veloz, Tomas; Desjardins, Sylvie

    2015-01-01

    Quantum models of concept combinations have been successful in representing various experimental situations that cannot be accommodated by traditional models based on classical probability or fuzzy set theory. In many cases, the focus has been on producing a representation that fits experimental results to validate quantum models. However, these representations are not always consistent with the cognitive modeling principles. Moreover, some important issues related to the representation of concepts such as the dimensionality of the realization space, the uniqueness of solutions, and the compatibility of measurements, have been overlooked. In this paper, we provide a dimensional analysis of the realization space for the two-sector Fock space model for conjunction of concepts focusing on the first and second sectors separately. We then introduce various representation of concepts that arise from the use of unitary operators in the realization space. In these concrete representations, a pair of concepts and their combination are modeled by a single conceptual state, and by a collection of exemplar-dependent operators. Therefore, they are consistent with cognitive modeling principles. This framework not only provides a uniform approach to model an entire data set, but, because all measurement operators are expressed in the same basis, allows us to address the question of compatibility of measurements. In particular, we present evidence that it may be possible to predict non-commutative effects from partial measurements of conceptual combinations. PMID:26617556

  8. Prediction of individual clinical scores in patients with Parkinson's disease using resting-state functional magnetic resonance imaging.

    PubMed

    Hou, YanBing; Luo, ChunYan; Yang, Jing; Ou, RuWei; Song, Wei; Wei, QianQian; Cao, Bei; Zhao, Bi; Wu, Ying; Shang, Hui-Fang; Gong, QiYong

    2016-07-15

    Neuroimaging holds the promise that it may one day aid the clinical assessment. However, the vast majority of studies using resting-state functional magnetic resonance imaging (fMRI) have reported average differences between Parkinson's disease (PD) patients and healthy controls, which do not permit inferences at the level of individuals. This study was to develop a model for the prediction of PD illness severity ratings from individual fMRI brain scan. The resting-state fMRI scans were obtained from 84 patients with PD and the Unified Parkinson's Disease Rating Scale-III (UPDRS-III) scores were obtained before scanning. The RVR method was used to predict clinical scores (UPDRS-III) from fMRI scans. The application of RVR to whole-brain resting-state fMRI data allowed prediction of UPDRS-III scores with statistically significant accuracy (correlation=0.35, P-value=0.001; mean sum of squares=222.17, P-value=0.002). This prediction was informed strongly by negative weight areas including prefrontal lobe and medial occipital lobe, and positive weight areas including medial parietal lobe. It was suggested that fMRI scans contained sufficient information about neurobiological change in patients with PD to permit accurate prediction about illness severity, on an individual subject basis. Our results provided preliminary evidence, as proof-of-concept, to support that fMRI might be possible to be a clinically useful quantitative assessment aid in PD at individual level. This may enable clinicians to target those uncooperative patients and machines to replace human for a more efficient use of health care resources. PMID:27288771

  9. Grassmannian sparse representations

    NASA Astrophysics Data System (ADS)

    Azary, Sherif; Savakis, Andreas

    2015-05-01

    We present Grassmannian sparse representations (GSR), a sparse representation Grassmann learning framework for efficient classification. Sparse representation classification offers a powerful approach for recognition in a variety of contexts. However, a major drawback of sparse representation methods is their computational performance and memory utilization for high-dimensional data. A Grassmann manifold is a space that promotes smooth surfaces where points represent subspaces and the relationship between points is defined by the mapping of an orthogonal matrix. Grassmann manifolds are well suited for computer vision problems because they promote high between-class discrimination and within-class clustering, while offering computational advantages by mapping each subspace onto a single point. The GSR framework combines Grassmannian kernels and sparse representations, including regularized least squares and least angle regression, to improve high accuracy recognition while overcoming the drawbacks of performance and dependencies on high dimensional data distributions. The effectiveness of GSR is demonstrated on computationally intensive multiview action sequences, three-dimensional action sequences, and face recognition datasets.

  10. Including Thermal Fluctuations in Actomyosin Stable States Increases the Predicted Force per Motor and Macroscopic Efficiency in Muscle Modelling.

    PubMed

    Marcucci, Lorenzo; Washio, Takumi; Yanagida, Toshio

    2016-09-01

    Muscle contractions are generated by cyclical interactions of myosin heads with actin filaments to form the actomyosin complex. To simulate actomyosin complex stable states, mathematical models usually define an energy landscape with a corresponding number of wells. The jumps between these wells are defined through rate constants. Almost all previous models assign these wells an infinite sharpness by imposing a relatively simple expression for the detailed balance, i.e., the ratio of the rate constants depends exponentially on the sole myosin elastic energy. Physically, this assumption corresponds to neglecting thermal fluctuations in the actomyosin complex stable states. By comparing three mathematical models, we examine the extent to which this hypothesis affects muscle model predictions at the single cross-bridge, single fiber, and organ levels in a ceteris paribus analysis. We show that including fluctuations in stable states allows the lever arm of the myosin to easily and dynamically explore all possible minima in the energy landscape, generating several backward and forward jumps between states during the lifetime of the actomyosin complex, whereas the infinitely sharp minima case is characterized by fewer jumps between states. Moreover, the analysis predicts that thermal fluctuations enable a more efficient contraction mechanism, in which a higher force is sustained by fewer attached cross-bridges. PMID:27626630

  11. Quantitative precipitation and river flow predictions over the southwestern United States

    SciTech Connect

    Kim, J.; Miller, N.L.

    1996-09-01

    Accurate predictions of local precipitation and river flow are crucial in the western US steep terrain and narrow valleys can cause local flooding during short term heavy precipitation. Typical size of hydrologically uniform watersheds within the mountainous part of the western US ranges 10{sup 2} to 10{sup 3} km{sup 2}. Such small watershed size, together with large variations in terrain elevations and a strong dependence of precipitation on terrain elevation, requires a find-resolution and well-localized NWP to improve QPF and river predictions. The most important aspects of accurate QPF and river flow predictions in the western US are: (1) partitioning the total precipitation into rainfall and snowfall, (2) representing hydrologic processes within individual watersheds, and (3) map watershed areas onto the regularly-spaced atmospheric grid model grid. In the following, we present the QPF and river flow calculations by the CARS system during two winter seasons from Nov. 1994 to Apr. 1995.

  12. Improved prediction of complex diseases by common genetic markers: state of the art and further perspectives.

    PubMed

    Müller, Bent; Wilcke, Arndt; Boulesteix, Anne-Laure; Brauer, Jens; Passarge, Eberhard; Boltze, Johannes; Kirsten, Holger

    2016-03-01

    Reliable risk assessment of frequent, but treatable diseases and disorders has considerable clinical and socio-economic relevance. However, as these conditions usually originate from a complex interplay between genetic and environmental factors, precise prediction remains a considerable challenge. The current progress in genotyping technology has resulted in a substantial increase of knowledge regarding the genetic basis of such diseases and disorders. Consequently, common genetic risk variants are increasingly being included in epidemiological models to improve risk prediction. This work reviews recent high-quality publications targeting the prediction of common complex diseases. To be included in this review, articles had to report both, numerical measures of prediction performance based on traditional (non-genetic) risk factors, as well as measures of prediction performance when adding common genetic variants to the model. Systematic PubMed-based search finally identified 55 eligible studies. These studies were compared with respect to the chosen approach and methodology as well as results and clinical impact. Phenotypes analysed included tumours, diabetes mellitus, and cardiovascular diseases. All studies applied one or more statistical measures reporting on calibration, discrimination, or reclassification to quantify the benefit of including SNPs, but differed substantially regarding the methodological details that were reported. Several examples for improved risk assessments by considering disease-related SNPs were identified. Although the add-on benefit of including SNP genotyping data was mostly moderate, the strategy can be of clinical relevance and may, when being paralleled by an even deeper understanding of disease-related genetics, further explain the development of enhanced predictive and diagnostic strategies for complex diseases. PMID:26839113

  13. Final state predictions for J2 gravity perturbed motion of the Earth’s artificial satellites using Bispherical coordinates

    NASA Astrophysics Data System (ADS)

    Sharaf, M. A.; Selim, H. H.

    2013-06-01

    In this paper, initial value problem for dynamical astronomy will be established using Bispherical coordinates. A computational algorithm is developed for the final state predictions for J2 gravity perturbed motion of the Earth’s artificial satellites. This algorithm is important in targeting, rendezvous maneuvers as well for scientific researches. The applications of the algorithm are illustrated by numerical examples of some test orbits of different eccentricities. The numerical results are extremely accurate and efficient.

  14. Using state diagrams for predicting colloidal stability of whey protein beverages.

    PubMed

    Wagoner, Ty B; Ward, Loren; Foegeding, E Allen

    2015-05-01

    A method for evaluating aspects of colloidal stability of whey protein beverages after thermal treatment was established. Three state diagrams for beverages (pH 3-7) were developed representing protein solubility, turbidity, and macroscopic state after two ultrahigh-temperature (UHT) treatments. Key transitions of stability in the state diagrams were explored using electrophoresis and chromatography to determine aggregation propensities of β-lactoglobulin, α-lactalbumin, bovine serum albumin, and glycomacropeptide. The state diagrams present an overlapping view of high colloidal stability at pH 3 accompanied by high solubility of individual whey proteins. At pH 5, beverages were characterized by poor solubility, high turbidity, and aggregation/gelation of whey proteins with the exception of glycomacropeptide. Stability increased at pH 6, due to increased solubility of α-lactalbumin. The results indicate that combinations of state diagrams can be used to identify key regions of stability for whey protein containing beverages. PMID:25880701

  15. Evaluating High-Degree-and-Order Gravitational Harmonics and its Application to the State Predictions of a Lunar Orbiting Satellite

    NASA Astrophysics Data System (ADS)

    Song, Young-Joo; Kim, Bang-Yeop

    2015-09-01

    In this work, an efficient method with which to evaluate the high-degree-and-order gravitational harmonics of the nonsphericity of a central body is described and applied to state predictions of a lunar orbiter. Unlike the work of Song et al. (2010), which used a conventional computation method to process gravitational harmonic coefficients, the current work adapted a well-known recursion formula that directly uses fully normalized associated Legendre functions to compute the acceleration due to the non-sphericity of the moon. With the formulated algorithms, the states of a lunar orbiting satellite are predicted and its performance is validated in comparisons with solutions obtained from STK/Astrogator. The predicted differences in the orbital states between STK/Astrogator and the current work all remain at a position of less than 1 m with velocity accuracy levels of less than 1 mm/s, even with different orbital inclinations. The effectiveness of the current algorithm, in terms of both the computation time and the degree of accuracy degradation, is also shown in comparisons with results obtained from earlier work. It is expected that the proposed algorithm can be used as a foundation for the development of an operational flight dynamics subsystem for future lunar exploration missions by Korea. It can also be used to analyze missions which require very close operations to the moon.

  16. An operational multifield analog/antianalog prediction system for United States seasonal temperatures: 1. System design and winter experiments

    NASA Astrophysics Data System (ADS)

    Livezey, Robert E.; Barnston, Anthony G.

    1988-01-01

    The theoretical framework developed by Barnett and Preisendorfer (1978) for multifield analog prediction of United States seasonal temperatures has been modified and expanded to accommodate the use of composites of analogs and antianalogs to form predictions. Major changes have also been made both in predictor data and in the way it is processed, although the general strategy of Barnett and Preisendorfer served as a guide in this regard. Cross-validation tests on a 35-year record suggest that substantial gains in winter forecast skill have been achieved through both the previously mentioned architectural changes and several predictor data set changes. The latter include the use of a different El Niño/Southern Oscillation index and United States surface temperature data but not precipitation data. It was found that significant model skill depends most on these two data sets, along with well-filtered 700-mbar heights, and depends least on sea surface temperatures. Considerable skill was found over the eastern half and the north-central portion of the United States. Forecasts were found to be effectively independent of and to outperform those of persistence and were comparable in skill to official forecasts. In a quasi-operational test most of the system's skill was reproduced, even under very disadvantageous circumstances. Because of all these factors, the mixed analog and antianalog prediction system has been adopted as a major input for operational use by official forecasters. Development of models for other seasons will be described in a subsequent paper.

  17. Spacecraft Attitude Representations

    NASA Technical Reports Server (NTRS)

    Markley, F. Landis

    1999-01-01

    The direction cosine matrix or attitude matrix is the most fundamental representation of the attitude, but it is very inefficient: It has six redundant parameters, it is difficult to enforce the six (orthogonality) constraints. the four-component quaternion representation is very convenient: it has only one redundant parameter, it is easy to enforce the normalization constraint, the attitude matrix is a homogeneous quadratic function of q, quaternion kinematics are bilinear in q and m. Euler angles are extensively used: they often have a physical interpretation, they provide a natural description of some spacecraft motions (COBE, MAP), but kinematics and attitude matrix involve trigonometric functions, "gimbal lock" for certain values of the angles. Other minimum (three-parameter) representations: Gibbs vector is infinite for 180 deg rotations, but useful for analysis, Modified Rodrigues Parameters are nonsingular, no trig functions, Rotation vector phi is nonsingular, but requires trig functions.

  18. An investigation of gear mesh failure prediction techniques. M.S. Thesis - Cleveland State Univ.

    NASA Technical Reports Server (NTRS)

    Zakrajsek, James J.

    1989-01-01

    A study was performed in which several gear failure prediction methods were investigated and applied to experimental data from a gear fatigue test apparatus. The primary objective was to provide a baseline understanding of the prediction methods and to evaluate their diagnostic capabilities. The methods investigated use the signal average in both the time and frequency domain to detect gear failure. Data from eleven gear fatigue tests were recorded at periodic time intervals as the gears were run from initiation to failure. Four major failure modes, consisting of heavy wear, tooth breakage, single pits, and distributed pitting were observed among the failed gears. Results show that the prediction methods were able to detect only those gear failures which involved heavy wear or distributed pitting. None of the methods could predict fatigue cracks, which resulted in tooth breakage, or single pits. It is suspected that the fatigue cracks were not detected because of limitations in data acquisition rather than in methodology. Additionally, the frequency response between the gear shaft and the transducer was found to significantly affect the vibration signal. The specific frequencies affected were filtered out of the signal average prior to application of the methods.

  19. Testing Predictive Models of Technology Integration in Mexico and the United States

    ERIC Educational Resources Information Center

    Velazquez, Cesareo Morales

    2008-01-01

    Data from Mexico City, Mexico (N = 978) and from Texas, USA (N = 932) were used to test the predictive validity of the teacher professional development component of the Will, Skill, Tool Model of Technology Integration in a cross-cultural context. Structural equation modeling (SEM) was used to test the model. Analyses of these data yielded…

  20. PREDICTING ACHIEVEMENT IN TECHNICAL PROGRAMS AT THE NORTH DAKOTA STATE SCHOOL OF SCIENCE.

    ERIC Educational Resources Information Center

    ANDERSON, ROGER C.

    DATA WERE COLLECTED FROM SCHOOL RECORDS FOR 876 STUDENTS ENROLLED IN SIX TECHNICAL PROGRAMS FROM 1961-63. THIS PROVIDES EIGHT BIOGRAPHICAL AND 17 ACADEMIC VARIABLES WHICH WERE EXAMINED FOR THEIR USEFULNESS IN PREDICTING STUDENT SUCCESS. THE STUDENT SAMPLE WAS DIVIDED INTO GRADUATES AND NONGRADUATES. NONGRADUATES WERE THOSE WHO ATTENDED FOUR OR…

  1. NIR models for predicting total sugar in tobacco for samples with different physical states

    NASA Astrophysics Data System (ADS)

    Qin, Yuhua; Gong, Huili

    2016-07-01

    Due to the spectra variation of the inhomogeneous tobacco flakes results the inaccuracy and instability of the near infrared model. This paper presented the strategies of calibration transfer and hybrid modeling for determining total sugar content in tobacco based on the homogeneous powder model. The necessity judgments and acceptance criteria of the calibration transfer were also proposed. Calibration transfer methods include Slope/Bias Correction (S/B), Piecewise Direct Standardization (PDS), double window piecewise direct standardization (DWPDS), and Shenk's were adopted, a transfer set of 15 samples were chosen for each methods, and the results showed that Shenk's is the adequate transfer method as only one indicator did not fulfill the acceptance criteria of the transfer. Other methods were all dissatisfied with the acceptance criteria and cannot be applied to the calibration transfer between the tobacco flake and powder. While the hybrid model of adding some flake samples to the powder model achieved preferred prediction ability. The study showed that adding around 10% variation samples caused the average prediction error of total sugar content (range 12.1-37.2%) in flake samples from 7.25% (predicted by a flake model) significantly dropping to 4.98%, even close to the prediction of the same powder samples (4.21%) by the powder model. It will valuable for the promotion of the NIR network and online analysis.

  2. Negative Ion Photoelectron Spectroscopy Confirms the Prediction that (CO)5 and (CO)6 Each Has a Singlet Ground State

    SciTech Connect

    Bao, Xiaoguang; Hrovat, David; Borden, Weston; Wang, Xue B.

    2013-03-20

    Cyclobutane-1,2,3,4-tetraone has been both predicted and found to have a triplet ground state, in which a b2g MO and an a2u MO is each singly occupied. In contrast, (CO)5 and (CO)6 have each been predicted to have a singlet ground state. This prediction has been tested by generating the (CO)5 - and (CO)6 - anions in the gas-phase by electrospray vaporization of solutions of, respectively, the croconate (CO)52- and rhodizonate (CO)62- dianions. The negative ion photoelectron (NIPE) spectra of the (CO)5•- radical anion give electron affinity (EA) = 3.830 eV and a singlet ground state for (CO)5, with the triplet higher in energy by 0.850 eV (19.6 kcal/mol). The NIPE spectra of the (CO)6•- radical anion give EA = 3.785 eV and a singlet ground state for (CO)6, with the triplet higher in energy by 0.915 eV (21.1 kcal/mol). (RO)CCSD(T)/aug-cc-pVTZ//(U)B3LYP/6-311+G(2df) calculations give EA values that are only ca. 1 kcal/mol lower than those measured and EST values that are only 2 - 3 kcal/mol higher than those obtained from the NIPE spectra. Thus, the calculations support the interpretations of the NIPE spectra and the finding, based on the spectra, that (CO)5 and (CO)6 both have a singlet ground state.

  3. Pair potentials for protein folding: choice of reference states and sensitivity of predicted native states to variations in the interaction schemes.

    PubMed Central

    Betancourt, M. R.; Thirumalai, D.

    1999-01-01

    We examine the similarities and differences between two widely used knowledge-based potentials, which are expressed as contact matrices (consisting of 210 elements) that gives a scale for interaction energies between the naturally occurring amino acid residues. These are the Miyazawa-Jernigan contact interaction matrix M and the potential matrix S derived by Skolnick J et al., 1997, Protein Sci 6:676-688. Although the correlation between the two matrices is good, there is a relatively large dispersion between the elements. We show that when Thr is chosen as a reference solvent within the Miyazawa and Jernigan scheme, the dispersion between the M and S matrices is reduced. The resulting interaction matrix B gives hydrophobicities that are in very good agreement with experiment. The small dispersion between the S and B matrices, which arises due to differing reference states, is shown to have dramatic effect on the predicted native states of lattice models of proteins. These findings and other arguments are used to suggest that for reliable predictions of protein structures, pairwise additive potentials are not sufficient. We also establish that optimized protein sequences can tolerate relatively large random errors in the pair potentials. We conjecture that three body interaction may be needed to predict the folds of proteins in a reliable manner. PMID:10048329

  4. Umbra's system representation.

    SciTech Connect

    McDonald, Michael James

    2005-07-01

    This document describes the Umbra System representation. Umbra System representation, initially developed in the spring of 2003, is implemented in Incr/Tcl using concepts borrowed from Carnegie Mellon University's Architecture Description Language (ADL) called Acme. In the spring of 2004 through January 2005, System was converted to Umbra 4, extended slightly, and adopted as the underlying software system for a variety of Umbra applications that support Complex Systems Engineering (CSE) and Complex Adaptive Systems Engineering (CASE). System is now a standard part Of Umbra 4. While Umbra 4 also includes an XML parser for System, the XML parser and Schema are not described in this document.

  5. Low-dimensional representations of exact coherent states of the Navier-Stokes equations from the resolvent model of wall turbulence

    NASA Astrophysics Data System (ADS)

    Sharma, Ati S.; Moarref, Rashad; McKeon, Beverley J.; Park, Jae Sung; Graham, Michael D.; Willis, Ashley P.

    2016-02-01

    We report that many exact invariant solutions of the Navier-Stokes equations for both pipe and channel flows are well represented by just a few modes of the model of McKeon and Sharma [J. Fluid Mech. 658, 336 (2010), 10.1017/S002211201000176X]. This model provides modes that act as a basis to decompose the velocity field, ordered by their amplitude of response to forcing arising from the interaction between scales. The model was originally derived from the Navier-Stokes equations to represent turbulent flows and has been used to explain coherent structure and to predict turbulent statistics. This establishes a surprising new link between the two distinct approaches to understanding turbulence.

  6. Reevaluating the two-representation model of numerical magnitude processing.

    PubMed

    Jiang, Ting; Zhang, Wenfeng; Wen, Wen; Zhu, Haiting; Du, Han; Zhu, Xiangru; Gao, Xuefei; Zhang, Hongchuan; Dong, Qi; Chen, Chuansheng

    2016-01-01

    One debate in mathematical cognition centers on the single-representation model versus the two-representation model. Using an improved number Stroop paradigm (i.e., systematically manipulating physical size distance), in the present study we tested the predictions of the two models for number magnitude processing. The results supported the single-representation model and, more importantly, explained how a design problem (failure to manipulate physical size distance) and an analytical problem (failure to consider the interaction between congruity and task-irrelevant numerical distance) might have contributed to the evidence used to support the two-representation model. This study, therefore, can help settle the debate between the single-representation and two-representation models. PMID:26268066

  7. Mesolimbic Dopamine Encodes Prediction Errors in a State-Dependent Manner

    PubMed Central

    Papageorgiou, Georgios K.; Baudonnat, Mathieu; Cucca, Flavia; Walton, Mark E.

    2016-01-01

    Summary Mesolimbic dopamine encodes the benefits of a course of action. However, the value of an appetitive reward depends strongly on an animal’s current state. To investigate the relationship between dopamine, value, and physiological state, we monitored sub-second dopamine release in the nucleus accumbens core while rats made choices between food and sucrose solution following selective satiation on one of these reinforcers. Dopamine signals reflected preference for the reinforcers in the new state, decreasing to the devalued reward and, after satiation on food, increasing for the valued sucrose solution. These changes were rapid and selective, with dopamine release returning to pre-satiation patterns when the animals were re-tested in a standard food-restricted state. Such rapid and selective adaptation of dopamine-associated value signals could provide an important signal to promote efficient foraging for a varied diet. PMID:27050518

  8. Space-for-time substitution in predicting the state of picoplankton and nanoplankton in a changing Arctic Ocean

    NASA Astrophysics Data System (ADS)

    Li, William K. W.; Carmack, Eddy C.; McLaughlin, Fiona A.; Nelson, R. John; Williams, William J.

    2013-10-01

    The Arctic Ocean is changing rapidly but there are no long-term time series observations on the state of the phytoplankton community that could allow a link to be made from physical/chemical pressures to the impact on marine ecosystems. Here, we test the idea that space-for-time (SFT) substitution might predict temporal change in the Canada Basin premised on differences in the present state of phytoplankton in other geographic zones, specifically the ratio in the abundance of picophytoplankton to nanophytoplankton (Pico:Nano). We compared the change in Pico:Nano observed in the Canada Basin from 2004 to 2012 to the different average states of this ratio in 26 other ocean ecological regions. Our results show that as upper ocean nitrate concentration changed in the Canada Basin from year to year, the concomitant change in Pico:Nano was statistically commensurate with the difference that this ratio exhibits between Longhurst ecological provinces in relation to nitrate concentration. Lower average concentration of nitrate in the upper water column is associated with a higher value of Pico:Nano, a result consistent with resource control of phytoplankton size structure in the ocean. We suggest that SFT substitution allows an explanation of temporal progression from spatial pattern as a test of mechanism, but such statistical prediction is not necessarily a projection of future states.

  9. Resting-state fMRI activity predicts unsupervised learning and memory in an immersive virtual reality environment.

    PubMed

    Wong, Chi Wah; Olafsson, Valur; Plank, Markus; Snider, Joseph; Halgren, Eric; Poizner, Howard; Liu, Thomas T

    2014-01-01

    In the real world, learning often proceeds in an unsupervised manner without explicit instructions or feedback. In this study, we employed an experimental paradigm in which subjects explored an immersive virtual reality environment on each of two days. On day 1, subjects implicitly learned the location of 39 objects in an unsupervised fashion. On day 2, the locations of some of the objects were changed, and object location recall performance was assessed and found to vary across subjects. As prior work had shown that functional magnetic resonance imaging (fMRI) measures of resting-state brain activity can predict various measures of brain performance across individuals, we examined whether resting-state fMRI measures could be used to predict object location recall performance. We found a significant correlation between performance and the variability of the resting-state fMRI signal in the basal ganglia, hippocampus, amygdala, thalamus, insula, and regions in the frontal and temporal lobes, regions important for spatial exploration, learning, memory, and decision making. In addition, performance was significantly correlated with resting-state fMRI connectivity between the left caudate and the right fusiform gyrus, lateral occipital complex, and superior temporal gyrus. Given the basal ganglia's role in exploration, these findings suggest that tighter integration of the brain systems responsible for exploration and visuospatial processing may be critical for learning in a complex environment. PMID:25286145

  10. Resting-State fMRI Activity Predicts Unsupervised Learning and Memory in an Immersive Virtual Reality Environment

    PubMed Central

    Wong, Chi Wah; Olafsson, Valur; Plank, Markus; Snider, Joseph; Halgren, Eric; Poizner, Howard; Liu, Thomas T.

    2014-01-01

    In the real world, learning often proceeds in an unsupervised manner without explicit instructions or feedback. In this study, we employed an experimental paradigm in which subjects explored an immersive virtual reality environment on each of two days. On day 1, subjects implicitly learned the location of 39 objects in an unsupervised fashion. On day 2, the locations of some of the objects were changed, and object location recall performance was assessed and found to vary across subjects. As prior work had shown that functional magnetic resonance imaging (fMRI) measures of resting-state brain activity can predict various measures of brain performance across individuals, we examined whether resting-state fMRI measures could be used to predict object location recall performance. We found a significant correlation between performance and the variability of the resting-state fMRI signal in the basal ganglia, hippocampus, amygdala, thalamus, insula, and regions in the frontal and temporal lobes, regions important for spatial exploration, learning, memory, and decision making. In addition, performance was significantly correlated with resting-state fMRI connectivity between the left caudate and the right fusiform gyrus, lateral occipital complex, and superior temporal gyrus. Given the basal ganglia's role in exploration, these findings suggest that tighter integration of the brain systems responsible for exploration and visuospatial processing may be critical for learning in a complex environment. PMID:25286145

  11. Combining robust state estimation with nonlinear model predictive control to regulate the acute inflammatory response to pathogen.

    PubMed

    Zitelli, Gregory; Djouadi, Seddik M; Day, Judy D

    2015-10-01

    The inflammatory response aims to restore homeostasis by means of removing a biological stress, such as an invading bacterial pathogen. In cases of acute systemic inflammation, the possibility of collateral tissue damage arises, which leads to a necessary down-regulation of the response. A reduced ordinary differential equations (ODE) model of acute inflammation was presented and investigated in [10]. That system contains multiple positive and negative feedback loops and is a highly coupled and nonlinear ODE. The implementation of nonlinear model predictive control (NMPC) as a methodology for determining proper therapeutic intervention for in silico patients displaying complex inflammatory states was initially explored in [5]. Since direct measurements of the bacterial population and the magnitude of tissue damage/dysfunction are not readily available or biologically feasible, the need for robust state estimation was evident. In this present work, we present results on the nonlinear reachability of the underlying model, and then focus our attention on improving the predictability of the underlying model by coupling the NMPC with a particle filter. The results, though comparable to the initial exploratory study, show that robust state estimation of this highly nonlinear model can provide an alternative to prior updating strategies used when only partial access to the unmeasurable states of the system are available. PMID:26280180

  12. Ab initio many-electron study for the low-lying states of the alkali hydride cations in the adiabatic representation

    NASA Astrophysics Data System (ADS)

    Yan, Lingling; Qu, Yizhi; Liu, Chunhua; Wang, Jianguo; Buenker, Robert J.

    2012-03-01

    An ab initio multireference single- and double-excitation configuration interaction (CI) study is carried out for the ground and excited electronic states of alkali-hydride cations (LiH+, NaH+, KH+, RbH+, and CsH+). For all alkali-metal atoms, the first inner-shell and valence electrons (nine active electrons, three for Li) are considered explicitly in the ab initio self-consistent-field and CI calculations. The adiabatic potential energy curves, radial and rotational couplings are calculated and presented. Short-range (˜3 a.u.) potential wells produced by the excitation of the inner-shell electrons are found. The depths of the inner potential wells are much greater than those of the outer wells for the CsH+ system. The computed spectroscopic constants for the long-range potential well of the 2 2Σ+ state are very close to the available theoretical and experimental data. The electronic states of alkali-hydrogen cations are also compared with each other, it is found that the positions of the potential wells shift to larger internuclear distances gradually, and the depths of these potential wells become greater with increasing alkali-metal atomic number. The relationships between structures of the radial coupling matrix elements and the avoiding crossings of the potential curves are analyzed. From NaH+ to CsH+, radial coupling matrix elements display more and more complex structures due to the gradual decrease of energy separations for avoided crossings. Finally, the behavior of some rotational couplings is also shown.

  13. A computer model of lens structure and function predicts experimental changes to steady state properties and circulating currents

    PubMed Central

    2013-01-01

    Background In a previous study (Vaghefi et al. 2012) we described a 3D computer model that used finite element modeling to capture the structure and function of the ocular lens. This model accurately predicted the steady state properties of the lens including the circulating ionic and fluid fluxes that are believed to underpin the lens internal microcirculation system. In the absence of a blood supply, this system brings nutrients to the core of the lens and removes waste products faster than would be achieved by passive diffusion alone. Here we test the predictive properties of our model by investigating whether it can accurately mimic the experimentally measured changes to lens steady-state properties induced by either depolarising the lens potential or reducing Na+ pump rate. Methods To mimic experimental manipulations reported in the literature, the boundary conditions of the model were progressively altered and the model resolved for each new set of conditions. Depolarisation of lens potential was implemented by increasing the extracellular [K+], while inhibition of the Na+ pump was stimulated by utilising the inherent temperature sensitivity of the pump and changing the temperature at which the model was solved. Results Our model correctly predicted that increasing extracellular [K+] depolarizes the lens potential, reducing and then reversing the magnitude of net current densities around the lens. While lowering the temperature reduced Na+ pump activity and caused a reduction in circulating current, it had a minimal effect on the lens potential, a result consistent with published experimental data. Conclusion We have shown that our model is capable of accurately simulating the effects of two known experimental manipulations on lens steady-state properties. Our results suggest that the model will be a valuable predictive tool to support ongoing studies of lens structure and function. PMID:23988187

  14. Patient specific proteolytic activity of monocyte-derived macrophages and osteoclasts predicted with temporal kinase activation states during differentiation

    PubMed Central

    Park, Keon-Young; Li, Weiwei A.; Platt, Manu O.

    2012-01-01

    Patient-to-patient variability in disease progression continues to complicate clinical decisions of treatment regimens for cardiovascular diseases, metastatic cancers and osteoporosis. Here, we investigated if monocytes, circulating white blood cells that enter tissues and contribute to disease progression by differentiating into macrophages or osteoclasts, could be useful in understanding this variability. Monocyte-derived macrophages and osteoclasts produce cysteine cathepsins, powerful extracellular matrix proteases which have been mechanistically linked to accelerated atherosclerotic, osteoporotic, and tumor progression. We hypothesized that multivariate analysis of temporal kinase activation states during monocyte differentiation could predict cathepsin proteolytic responses of monocyte-derived macrophages and osteoclasts in a patient-specific manner. Freshly isolated primary monocytes were differentiated with M-CSF or RANKL into macrophages or osteoclasts, respectively, and phosphorylation of ERK1/2, Akt, p38 MAPK, JNK, c-jun, and IκB-α were measured at days 1, 3, 6, and 9. In parallel, cell diameters and numbers of nuclei were measured, and multiplex cathepsin zymography was used to quantify cathepsins K, L, S, and V activity from cell extracts and conditioned media. There was extensive patient-to-patient variability in temporal kinase activation states, cell morphologies, and cathepsin K, L, S, and V proteolytic activity. Partial least squares regression models trained with temporal kinase activation states successfully predicted patient-specific morphological characteristics (mean cell diameter and number of nuclei) and patient-specific cathepsin proteolytic activity with predictability as high as 95%, even with the challenge of incorporating the complex, unknown cues from individual patients’ unique genetic and biochemical backgrounds. This personalized medicine approach considers patient variability in kinase signals to predict cathepsin activity

  15. Predictive information in a sensory population.

    PubMed

    Palmer, Stephanie E; Marre, Olivier; Berry, Michael J; Bialek, William

    2015-06-01

    Guiding behavior requires the brain to make predictions about the future values of sensory inputs. Here, we show that efficient predictive computation starts at the earliest stages of the visual system. We compute how much information groups of retinal ganglion cells carry about the future state of their visual inputs and show that nearly every cell in the retina participates in a group of cells for which this predictive information is close to the physical limit set by the statistical structure of the inputs themselves. Groups of cells in the retina carry information about the future state of their own activity, and we show that this information can be compressed further and encoded by downstream predictor neurons that exhibit feature selectivity that would support predictive computations. Efficient representation of predictive information is a candidate principle that can be applied at each stage of neural computation. PMID:26038544

  16. A prediction model for lift-fan simulator performance. M.S. Thesis - Cleveland State Univ.

    NASA Technical Reports Server (NTRS)

    Yuska, J. A.

    1972-01-01

    The performance characteristics of a model VTOL lift-fan simulator installed in a two-dimensional wing are presented. The lift-fan simulator consisted of a 15-inch diameter fan driven by a turbine contained in the fan hub. The performance of the lift-fan simulator was measured in two ways: (1) the calculated momentum thrust of the fan and turbine (total thrust loading), and (2) the axial-force measured on a load cell force balance (axial-force loading). Tests were conducted over a wide range of crossflow velocities, corrected tip speeds, and wing angle of attack. A prediction modeling technique was developed to help in analyzing the performance characteristics of lift-fan simulators. A multiple linear regression analysis technique is presented which calculates prediction model equations for the dependent variables.

  17. Investigating the potential of SST assimilation for ocean state estimation and climate prediction

    NASA Astrophysics Data System (ADS)

    Keenlyside, Noel; Counillon, Francois; Bethke, Ingo; Wang, Yiguo; Billeau, Sebastien; Shen, Mao-Lin; Bentsen, Mats

    2016-04-01

    The Norwegian Climate Prediction Model (NorCPM) assimilates the stochastic HadISST2 product with the ensemble Kalman Filter data assimilation method into the ocean part the Norwegian Earth System model. We document a pilot stochastic reanalysis for the period 1950-2010 and use it to perform seasonal-to-decadal (s2d) predictions. The accuracy, reliability and drift is investigated using both assimilated and independent observations. NorCPM is found slightly over-dispersive against assimilated observations but shows stable performance through the analysis period (˜0.4K). It demonstrates skill against independent measurements: SSH, heat and salt content, in particular in the ENSO, the North Pacific, the North Atlantic subpolar gyre (SPG) regions and the Nordic Seas. Furthermore, NorCPM provides a reliable monitoring of the SPG index and represents the variability of the temperature vertical structure there in good agreement with observations. The monitoring of the Atlantic meridional overturning circulation is also encouraging. The benefit of using flow dependent assimilation method and constructing the covariance in isopycnal coordinate are investigated in the SPG region. Isopycnal coordinate discretisation is found to better captures the vertical structure than standard depth-coordinate discretisation, which can deepen the influence of assimilation when assimilating surface observations. The vertical covariance shows a pronounced seasonal and decadal variability, which highlights the benefit of flow dependent data assimilation method. This study demonstrates the potential of NorCPM for providing a long reanalysis for the 19-20 century when SST observations are available. The results of s2d predictions carried out will be presented, and the potential to use this method to assess decadal predictability over the historical period will be discussed.

  18. Predicting Brook Trout occurrence in stream reaches throughout their native range in the eastern United States

    USGS Publications Warehouse

    DeWeber, Jefferson Tyrell; Wagner, Tyler

    2015-01-01

    The Brook Trout Salvelinus fontinalis is an important species of conservation concern in the eastern USA. We developed a model to predict Brook Trout population status within individual stream reaches throughout the species’ native range in the eastern USA. We utilized hierarchical logistic regression with Bayesian estimation to predict Brook Trout occurrence probability, and we allowed slopes and intercepts to vary among ecological drainage units (EDUs). Model performance was similar for 7,327 training samples and 1,832 validation samples based on the area under the receiver operating curve (∼0.78) and Cohen's kappa statistic (0.44). Predicted water temperature had a strong negative effect on Brook Trout occurrence probability at the stream reach scale and was also negatively associated with the EDU average probability of Brook Trout occurrence (i.e., EDU-specific intercepts). The effect of soil permeability was positive but decreased as EDU mean soil permeability increased. Brook Trout were less likely to occur in stream reaches surrounded by agricultural or developed land cover, and an interaction suggested that agricultural land cover also resulted in an increased sensitivity to water temperature. Our model provides a further understanding of how Brook Trout are shaped by habitat characteristics in the region and yields maps of stream-reach-scale predictions, which together can be used to support ongoing conservation and management efforts. These decision support tools can be used to identify the extent of potentially suitable habitat, estimate historic habitat losses, and prioritize conservation efforts by selecting suitable stream reaches for a given action. Future work could extend the model to account for additional landscape or habitat characteristics, include biotic interactions, or estimate potential Brook Trout responses to climate and land use changes.

  19. Next-to-leading order predictions for Z gamma+jet and Z gamma gamma final states at the LHC

    SciTech Connect

    Campbell, John M.; Hartanto, Heribertus B.; Williams, Ciaran

    2012-11-01

    We present next-to-leading order predictions for final states containing leptons produced through the decay of a Z boson in association with either a photon and a jet, or a pair of photons. The effect of photon radiation from the final state leptons is included and we also allow for contributions arising from fragmentation processes. Phenomenological studies are presented for the LHC in the case of final states containing charged leptons and in the case of neutrinos. We also use the procedure introduced by Stewart and Tackmann to provide a reliable estimate of the scale uncertainty inherent in our theoretical calculations of jet-binned Z gamma cross sections. These computations have been implemented in the public code MCFM.

  20. On the skill of numerical weather prediction models to forecast atmospheric rivers over the central United States

    NASA Astrophysics Data System (ADS)

    Nayak, Munir A.; Villarini, Gabriele; Lavers, David A.

    2014-06-01

    Flooding over the central United States is responsible for large socioeconomic losses. Atmospheric rivers (ARs), narrow regions of intense moisture transport within the warm conveyor belt of extratropical cyclones, can give rise to high rainfall amounts leading to flooding. Short-term forecasting of AR activity can provide basic information toward improving preparedness for these events. This study focuses on the verification of the skill of five numerical weather prediction models in forecasting AR activity over the central United States. We find that these models generally forecast AR occurrences well at short lead times, with location errors increasing from one to three decimal degrees as the lead time increases to about 1 week. The skill (both in terms of occurrence and location errors) decreases with increasing lead time. Overall, these models are not skillful in forecasting AR activity over the central United States beyond a lead time of about 7 days.

  1. Predicting Lawsuits against Nursing Homes in the United States, 1997–2001

    PubMed Central

    Johnson, Christopher E; Dobalian, Aram; Burkhard, Janet; Hedgecock, Deborah K; Harman, Jeffrey

    2004-01-01

    Objectives To examine how nursing home characteristics impacted the number of lawsuits filed against the facilities in the United States during 1997–2001. Data Sources/Study Setting A stratified random sample of 2,378 nursing home in 45 states from 1997–2001. Data were obtained from Westlaw's Adverse Filings: Lawsuits database, the Centers for Medicare and Medicaid Services' (CMS) Online Survey, Certification, and Reporting (OSCAR) database, state complaint surveys, and through primary data. Study Design Negative binomial regression was used to explain total lawsuit variance by year. Explanatory variables included (a) facility characteristics—including staffing, number of beds, multistate system membership, for-profit ownership, (b) quality indicators—including total number and type of quality survey deficiencies, pressure sore development, and (c) market area—state has resident rights statutes, state complaint information. Resident acuity levels and year effects were controlled for. Data Collection/Extraction Methods Nursing homes were identified and linked to Westlaw data that was searched for the number of lawsuits filed against the home, and then linked to OSCAR data and a primary data analysis of multistate chain membership. Principal Findings Staffing levels for certified nursing assistants (CNAs) and registered nurses (RNs) and multistate chain membership were negatively related with higher numbers of lawsuits. More deficiencies on the licensing survey, larger, for-profit nursing homes, and being located in resident rights states were positively related with higher numbers of lawsuits. Conclusion This study suggests that nursing homes that meet long-stay staffing standards and minimum quality indicators, are nonprofit, smaller, and not located in resident rights states will experience fewer lawsuits. PMID:15533183

  2. Reading Students' Representations

    ERIC Educational Resources Information Center

    Diezmann, Carmel M.; McCosker, Natalie T.

    2011-01-01

    Representations play a key role in mathematical thinking: They offer "a medium" to express mathematical knowledge or organize mathematical information and to discern mathematical relationships (e.g., relative household expenditures on a pie chart) using text, symbols, or graphics. They also furnish "tools" for mathematical processes (e.g., use of…

  3. The Problem of Representation

    ERIC Educational Resources Information Center

    Tervo, Juuso

    2012-01-01

    In "Postphysical Vision: Art Education's Challenge in an Age of Globalized Aesthetics (AMondofesto)" (2008) and "Beyond Aesthetics: Returning Force and Truth to Art and Its Education" (2009), jan jagodzinski argued for politics that go "beyond" representation--a project that radically questions visual culture…

  4. Predicting unsaturated zone nitrogen mass balances in agricultural settings of the United States.

    PubMed

    Nolan, Bernard T; Puckett, Larry J; Ma, Liwang; Green, Christopher T; Bayless, E Randall; Malone, Robert W

    2010-01-01

    Unsaturated zone N fate and transport were evaluated at four sites to identify the predominant pathways of N cycling: an almond [Prunus dulcis (Mill.) D.A. Webb] orchard and cornfield (Zea mays L.) in the lower Merced River study basin, California; and corn-soybean [Glycine max (L.) Merr.] rotations in study basins at Maple Creek, Nebraska, and at Morgan Creek, Maryland. We used inverse modeling with a new version of the Root Zone Water Quality Model (RZWQM2) to estimate soil hydraulic and nitrogen transformation parameters throughout the unsaturated zone; previous versions were limited to 3-m depth and relied on manual calibration. The overall goal of the modeling was to derive unsaturated zone N mass balances for the four sites. RZWQM2 showed promise for deeper simulation profiles. Relative root mean square error (RRMSE) values for predicted and observed nitrate concentrations in lysimeters were 0.40 and 0.52 for California (6.5 m depth) and Nebraska (10 m), respectively, and index of agreement (d) values were 0.60 and 0.71 (d varies between 0 and 1, with higher values indicating better agreement). For the shallow simulation profile (1 m) in Maryland, RRMSE and d for nitrate were 0.22 and 0.86, respectively. Except for Nebraska, predictions of average nitrate concentration at the bottom of the simulation profile agreed reasonably well with measured concentrations in monitoring wells. The largest additions of N were predicted to come from inorganic fertilizer (153-195 kg N ha(-1) yr(-1) in California) and N fixation (99 and 131 kg N ha(-1) yr(-1) in Maryland and Nebraska, respectively). Predicted N losses occurred primarily through plant uptake (144-237 kg N ha(-1) yr(-1)) and deep seepage out of the profile (56-102 kg N ha(-1) yr(-1)). Large reservoirs of organic N (up to 17,500 kg N ha(-1) m(-1) at Nebraska) were predicted to reside in the unsaturated zone, which has implications for potential future transfer of nitrate to groundwater. PMID:20400601

  5. Assessment of trait anxiety and prediction of changes in state anxiety using functional brain imaging: A test-retest study.

    PubMed

    Tian, Xue; Wei, Dongtao; Du, Xue; Wang, Kangcheng; Yang, Junyi; Liu, Wei; Meng, Jie; Liu, Huijuan; Liu, Guangyuan; Qiu, Jiang

    2016-06-01

    Anxiety is a multidimensional construct that includes stable trait anxiety and momentary state anxiety, which have a combined effect on our mental and physical well-being. However, the relationship between intrinsic brain activity and the feeling of anxiety, particularly trait and state anxiety, remain unclear. In this study, we used resting-state functional magnetic resonance imaging (fMRI) (amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo)) to determine the effects of intrinsic brain activity on stable inter-individual trait anxiety and intra-individual state anxiety variability in a cross-sectional and test-retest study. We found that at both time points, the trait anxiety score was significantly associated with intrinsic brain activity (both the ALFF and ReHo) in the right ventral medial prefrontal cortex (vmPFC) and ALFF of the dorsal anterior cingulate cortex/anterior midcingulate cortex (dACC/aMCC). More importantly, the change in intrinsic brain activity in the right insula was predictive of intra-individual state anxiety variability over a 9-month interval. The test-retest nature of this study's design could provide an opportunity to distinguish between the intrinsic brain activity associated with state and trait anxiety. These results could deepen our understanding of anxiety from a neuroscientific perspective. PMID:27001499

  6. Prediction of spatially explicit rainfall intensity-duration thresholds for post-fire debris-flow generation in the western United States

    NASA Astrophysics Data System (ADS)

    Staley, Dennis; Negri, Jacquelyn; Kean, Jason

    2016-04-01

    burned areas. Our approach synthesizes the two methods by incorporating measured rainfall intensity into each model variable (based on measures of topographic steepness, burn severity and surface properties) within the logistic regression equation. This approach provides a more realistic representation of the relation between rainfall intensity and debris-flow likelihood, as likelihood values asymptotically approach zero when rainfall intensity approaches 0 mm/h, and increase with more intense rainfall. Model performance was evaluated by comparing predictions to several existing regional thresholds. The model, based upon training data collected in southern California, USA, has proven to accurately predict rainfall intensity-duration thresholds for other areas in the western United States not included in the original training dataset. In addition, the improved logistic regression model shows promise for emergency planning purposes and real-time, site-specific early warning. With further validation, this model may permit the prediction of spatially-explicit intensity-duration thresholds for debris-flow generation in areas where empirically derived regional thresholds do not exist. This improvement would permit the expansion of the early-warning system into other regions susceptible to post-fire debris flow.

  7. Estimation of the Aral Sea state predictability based on the open data sources and the unique field observations

    NASA Astrophysics Data System (ADS)

    Izhitskiy, Alexander; Ayzel, Georgy; Zavialov, Peter; Kurbaniyazov, Abilgazi

    2016-04-01

    The Aral Sea, formerly one of the four largest lakes in the world, has lost over 90% of its volume during the dramatical dessication mainly caused by the severe alteration of water budget of the basin. Shrinkage of the Aral Sea resulted in profound changes of the lake's ecosystem, that became a subject for a number of publications based on a wide range of methods such as field observations, remote sensing data analysis and numerical modeling. However, by the early 21th century, the number of field studies decreased significantly due to almost complete cessation of navigation and displacement of the Aral's shoreline far away from roads and other infrastructure. Thus, only a small amount of field data (salinity, temperature, etc.) for different regions of the lake is available for the last two decades. On the other hand, a set of the open data sources (sea level variability, atmospheric reanalysis) were developed for the region. The main idea of the presented study is to estimate the possibility of prediction of the Aral Sea state using coupled system of basic geoanalysis tools, numerical modeling of hydrological cycle (both for sea and land-surface interactions with atmosphere) and state-of-art machine learning techniques. Firstly, available in situ data, obtained in the Aral Sea by Shirshov Institute and other researchers, are concerned as the "base points of state" for each year within the studied period. Secondly, consistent patterns in the interannual variability of all other available parameters, taken from the open data sources and numerical modeling predictions, are founded out. As a result, such an approach allows predicting the future state of sea basing on the possible climatic scenario.

  8. [Time perceptions and representations].

    PubMed

    Tordjman, S

    2015-09-01

    Representations of time and time measurements depend on subjective constructs that vary according to changes in our concepts, beliefs, societal needs and technical advances. Similarly, the past, the future and the present are subjective representations that depend on each individual's psychic time and biological time. Therefore, there is no single, one-size-fits-all time for everyone, but rather a different, subjective time for each individual. We need to acknowledge the existence of different inter-individual times but also intra-individual times, to which different functions and different rhythms are attached, depending on the system of reference. However, the construction of these time perceptions and representations is influenced by objective factors (physiological, physical and cognitive) related to neuroscience which will be presented and discussed in this article. Thus, studying representation and perception of time lies at the crossroads between neuroscience, human sciences and philosophy. Furthermore, it is possible to identify several constants among the many and various representations of time and their corresponding measures, regardless of the system of time reference. These include the notion of movements repeated in a stable rhythmic pattern involving the recurrence of the same interval of time, which enables us to define units of time of equal and invariable duration. This rhythmicity is also found at a physiological level and contributes through circadian rhythms, in particular the melatonin rhythm, to the existence of a biological time. Alterations of temporality in mental disorders will be also discussed in this article illustrated by certain developmental disorders such as autism spectrum disorders. In particular, the hypothesis will be developed that children with autism would need to create discontinuity out of continuity through stereotyped behaviors and/or interests. This discontinuity repeated at regular intervals could have been

  9. Predicting Spatial and Temporal Gene Expression Using an Integrative Model of Transcription Factor Occupancy and Chromatin State

    PubMed Central

    Wilczynski, Bartek; Liu, Ya-Hsin; Yeo, Zhen Xuan; Furlong, Eileen E. M.

    2012-01-01

    Precise patterns of spatial and temporal gene expression are central to metazoan complexity and act as a driving force for embryonic development. While there has been substantial progress in dissecting and predicting cis-regulatory activity, our understanding of how information from multiple enhancer elements converge to regulate a gene's expression remains elusive. This is in large part due to the number of different biological processes involved in mediating regulation as well as limited availability of experimental measurements for many of them. Here, we used a Bayesian approach to model diverse experimental regulatory data, leading to accurate predictions of both spatial and temporal aspects of gene expression. We integrated whole-embryo information on transcription factor recruitment to multiple cis-regulatory modules, insulator binding and histone modification status in the vicinity of individual gene loci, at a genome-wide scale during Drosophila development. The model uses Bayesian networks to represent the relation between transcription factor occupancy and enhancer activity in specific tissues and stages. All parameters are optimized in an Expectation Maximization procedure providing a model capable of predicting tissue- and stage-specific activity of new, previously unassayed genes. Performing the optimization with subsets of input data demonstrated that neither enhancer occupancy nor chromatin state alone can explain all gene expression patterns, but taken together allow for accurate predictions of spatio-temporal activity. Model predictions were validated using the expression patterns of more than 600 genes recently made available by the BDGP consortium, demonstrating an average 15-fold enrichment of genes expressed in the predicted tissue over a naïve model. We further validated the model by experimentally testing the expression of 20 predicted target genes of unknown expression, resulting in an accuracy of 95% for temporal predictions and 50% for

  10. Impact of Stoichiometry Representation on Simulation of Genotype-Phenotype Relationships in Metabolic Networks

    PubMed Central

    Brochado, Ana Rita; Andrejev, Sergej; Maranas, Costas D.; Patil, Kiran R.

    2012-01-01

    Genome-scale metabolic networks provide a comprehensive structural framework for modeling genotype-phenotype relationships through flux simulations. The solution space for the metabolic flux state of the cell is typically very large and optimization-based approaches are often necessary for predicting the active metabolic state under specific environmental conditions. The objective function to be used in such optimization algorithms is directly linked with the biological hypothesis underlying the model and therefore it is one of the most relevant parameters for successful modeling. Although linear combination of selected fluxes is widely used for formulating metabolic objective functions, we show that the resulting optimization problem is sensitive towards stoichiometry representation of the metabolic network. This undesirable sensitivity leads to different simulation results when using numerically different but biochemically equivalent stoichiometry representations and thereby makes biological interpretation intrinsically subjective and ambiguous. We hereby propose a new method, Minimization of Metabolites Balance (MiMBl), which decouples the artifacts of stoichiometry representation from the formulation of the desired objective functions, by casting objective functions using metabolite turnovers rather than fluxes. By simulating perturbed metabolic networks, we demonstrate that the use of stoichiometry representation independent algorithms is fundamental for unambiguously linking modeling results with biological interpretation. For example, MiMBl allowed us to expand the scope of metabolic modeling in elucidating the mechanistic basis of several genetic interactions in Saccharomyces cerevisiae. PMID:23133362

  11. Validation of a Previously Developed Geospatial Model That Predicts the Prevalence of Listeria monocytogenes in New York State Produce Fields

    PubMed Central

    Weller, Daniel; Shiwakoti, Suvash; Bergholz, Peter; Grohn, Yrjo; Wiedmann, Martin

    2015-01-01

    Technological advancements, particularly in the field of geographic information systems (GIS), have made it possible to predict the likelihood of foodborne pathogen contamination in produce production environments using geospatial models. Yet, few studies have examined the validity and robustness of such models. This study was performed to test and refine the rules associated with a previously developed geospatial model that predicts the prevalence of Listeria monocytogenes in produce farms in New York State (NYS). Produce fields for each of four enrolled produce farms were categorized into areas of high or low predicted L. monocytogenes prevalence using rules based on a field's available water storage (AWS) and its proximity to water, impervious cover, and pastures. Drag swabs (n = 1,056) were collected from plots assigned to each risk category. Logistic regression, which tested the ability of each rule to accurately predict the prevalence of L. monocytogenes, validated the rules based on water and pasture. Samples collected near water (odds ratio [OR], 3.0) and pasture (OR, 2.9) showed a significantly increased likelihood of L. monocytogenes isolation compared to that for samples collected far from water and pasture. Generalized linear mixed models identified additional land cover factors associated with an increased likelihood of L. monocytogenes isolation, such as proximity to wetlands. These findings validated a subset of previously developed rules that predict L. monocytogenes prevalence in produce production environments. This suggests that GIS and geospatial models can be used to accurately predict L. monocytogenes prevalence on farms and can be used prospectively to minimize the risk of preharvest contamination of produce. PMID:26590280

  12. Prediction of auto-ignition temperatures of hydrocarbons by neural network based on atom-type electrotopological-state indices.

    PubMed

    Pan, Yong; Jiang, Juncheng; Wang, Rui; Cao, Hongyin; Zhao, Jinbo

    2008-09-15

    A quantitative structure-property relationship (QSPR) model was constructed to predict the auto-ignition temperature (AIT) of 118 hydrocarbons by means of artificial neural network (ANN). Atom-type electrotopological-state indices were used as molecular structure descriptors which combined together both electronic and topological characteristics of the analyzed molecules. The typical back-propagation (BP) neural network was employed for fitting the possible non-linear relationship existed between the atom-type electrotopological-state indices and AIT. The dataset of 118 hydrocarbons was randomly divided into a training set (60), a validation set (16) and a testing set (42). The optimal condition of the neural network was obtained by adjusting various parameters by trial-and-error. Simulated with the final optimum BP neural network [16-8-1], the results show that most of the predicted AIT values are in good agreement with the experimental data, with the average absolute error being 21.6 degrees C, and the root mean square error (RMS) being 31.09 for the testing set, which are superior to those obtained by multiple linear regression analysis and traditional group contribution method. The model proposed can be used not only to reveal the quantitative relation between AIT and molecular structures of hydrocarbons, but also to predict the AIT values of hydrocarbons for chemical engineering. PMID:18280036

  13. Predicting terrestrial gamma dose rate based on geological and soil information: case study of Perak state, Malaysia.

    PubMed

    Ramli, A T; Apriantoro, N H; Heryansyah, A; Basri, N A; Sanusi, M S M; Abu Hanifah, N Z H

    2016-03-01

    An extensive terrestrial gamma radiation dose (TGRD) rate survey has been conducted in Perak State, Peninsular Malaysia. The survey has been carried out taking into account geological and soil information, involving 2930 in situ surveys. Based on geological and soil information collected during TGRD rate measurements, TGRD rates have been predicted in Perak State using a statistical regression analysis which would be helpful to focus surveys in areas that are difficult to access. An equation was formulated according to a linear relationship between TGRD rates, geological contexts and soil types. The comparison of in situ measurements and predicted TGRD dose rates was tabulated and showed good agreement with the linear regression equation. The TGRD rates in the study area ranged from 38 nGy h(-1) to 1039 nGy h(-1) with a mean value of 224  ±  138 nGy h(-1). This value is higher than the world average as reported in UNSCEAR 2000. The TGRD rates contribute an average dose rate of 1.37 mSv per year. An isodose map for the study area was developed using a Kriging method based on predicted and in situ TGRD rate values. PMID:26583298

  14. Predictive equation of state method for heavy materials based on the Dirac equation and density functional theory

    NASA Astrophysics Data System (ADS)

    Wills, John M.; Mattsson, Ann E.

    2012-02-01

    Density functional theory (DFT) provides a formally predictive base for equation of state properties. Available approximations to the exchange/correlation functional provide accurate predictions for many materials in the periodic table. For heavy materials however, DFT calculations, using available functionals, fail to provide quantitative predictions, and often fail to be even qualitative. This deficiency is due both to the lack of the appropriate confinement physics in the exchange/correlation functional and to approximations used to evaluate the underlying equations. In order to assess and develop accurate functionals, it is essential to eliminate all other sources of error. In this talk we describe an efficient first-principles electronic structure method based on the Dirac equation and compare the results obtained with this method with other methods generally used. Implications for high-pressure equation of state of relativistic materials are demonstrated in application to Ce and the light actinides. Sandia National Laboratories is a multi-program laboratory managed andoperated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

  15. A new equation of state for better liquid density prediction of natural gas systems

    NASA Astrophysics Data System (ADS)

    Nwankwo, Princess C.

    Equations of state formulations, modifications and applications have remained active research areas since the success of van der Waal's equation in 1873. The need for better reservoir fluid modeling and characterization is of great importance to petroleum engineers who deal with thermodynamic related properties of petroleum fluids at every stage of the petroleum "life span" from its drilling, to production through the wellbore, to transportation, metering and storage. Equations of state methods are far less expensive (in terms of material cost and time) than laboratory or experimental forages and the results are interestingly not too far removed from the limits of acceptable accuracy. In most cases, the degree of accuracy obtained, by using various EOS's, though not appreciable, have been acceptable when considering the gain in time. The possibility of obtaining an equation of state which though simple in form and in use, could have the potential of further narrowing the present existing bias between experimentally determined and popular EOS estimated results spurred the interest that resulted in this study. This research study had as its chief objective, to develop a new equation of state that would more efficiently capture the thermodynamic properties of gas condensate fluids, especially the liquid phase density, which is the major weakness of other established and popular cubic equations of state. The set objective was satisfied by a new semi analytical cubic three parameter equation of state, derived by the modification of the attraction term contribution to pressure of the van der Waal EOS without compromising either structural simplicity or accuracy of estimating other vapor liquid equilibria properties. The application of new EOS to single and multi-component light hydrocarbon fluids recorded far lower error values than does the popular two parameter, Peng-Robinson's (PR) and three parameter Patel-Teja's (PT) equations of state. Furthermore, this research

  16. A-Optimal Projection for Image Representation.

    PubMed

    He, Xiaofei; Zhang, Chiyuan; Zhang, Lijun; Li, Xuelong

    2016-05-01

    We consider the problem of image representation from the perspective of statistical design. Recent studies have shown that images are possibly sampled from a low dimensional manifold despite of the fact that the ambient space is usually very high dimensional. Learning low dimensional image representations is crucial for many image processing tasks such as recognition and retrieval. Most of the existing approaches for learning low dimensional representations, such as principal component analysis (PCA) and locality preserving projections (LPP), aim at discovering the geometrical or discriminant structures in the data. In this paper, we take a different perspective from statistical experimental design, and propose a novel dimensionality reduction algorithm called A-Optimal Projection (AOP). AOP is based on a linear regression model. Specifically, AOP finds the optimal basis functions so that the expected prediction error of the regression model can be minimized if the new representations are used for training the model. Experimental results suggest that the proposed approach provides a better representation and achieves higher accuracy in image retrieval. PMID:26353361

  17. The Impact of Immigration on Congressional Representation.

    ERIC Educational Resources Information Center

    Bouvier, Leon

    Explanation of shifts in U.S. Congressional representation among states have often overlooked the effects of international migration on the size and distribution of the U.S. population. Seventy percent of recent U.S. immigrants have settled in California, New York, Texas, Florida, New Jersey, and Illinois. Estimates of the distribution of…

  18. Graphical Representations of Electronic Search Patterns.

    ERIC Educational Resources Information Center

    Lin, Xia; And Others

    1991-01-01

    Discussion of search behavior in electronic environments focuses on the development of GRIP (Graphic Representor of Interaction Patterns), a graphing tool based on HyperCard that produces graphic representations of search patterns. Search state spaces are explained, and forms of data available from electronic searches are described. (34…

  19. 77 FR 25547 - Representation-Case Procedures

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-04-30

    ... unchanged. The final rule, published December 22, 2011, at 76 FR 80138, will be effective on April 30, 2012... FR 80138, stated that any dissenting or concurring statements would be published separately in the... dissenting statements regarding the Board's final rule concerning representation- case procedures, 76...

  20. Nuclear dynamics in the Wigner representation

    SciTech Connect

    Bonasera, A.; Kondratyev, V.N.; Smerzi, A.; Remler, E.A. Dipartimento di Fisica dell' Universita di Catania, 57, Corso Italia, 95129 Catania Institute for Nuclear Research, 47, Pr. Nauki, Kiev, 252 028 Department of Physics, The College of William Mary, Williamsburg, Virginia 23185 )

    1993-07-26

    The quantum equation of motion of the density operator in the Wigner representation is solved using a stochastic approach. Nuclear ground states and an asymmetric nucleus-nucleus collision below the Coulomb barrier are studied. Quantum effects are shown to cause significant differences in comparison to results obtained from the classical Vlasov equation.

  1. 75 FR 26062 - Representation Election Procedure

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-05-11

    ... representative. 74 FR 56,750. In its NPRM, the Board stated its belief, based on the language of the RLA... rule changes regarding representation election procedures. Meeting Notice, 74 FR 57,427 (Nov. 6, 2009... a comment period of not less than 60 days.'' Exec. Order No. 12,866, 58 FR 51,735 (1993). ATA...

  2. Female Representation by Type of Class

    ERIC Educational Resources Information Center

    Physics Teacher, 2012

    2012-01-01

    Last month we saw that females make up about 47% of all high school physics students in the United States. This number has changed little since 1997. This month, we take a closer look at female representation by type of class. We last collected class-specific data in 1993; that year, 43% of all high school physics students were female. However,…

  3. Digital Art Making as a Representational Process

    ERIC Educational Resources Information Center

    Halverson, Erica Rosenfeld

    2013-01-01

    In this article I bring artistic production into the learning sciences conversation by using the production of representations as a bridging concept between art making and the new literacies. Through case studies with 4 youth media arts organizations across the United States I ask how organizations structure the process of producing…

  4. Updated Graizer-Kalkan Ground Motion Prediction Equations for Western United States

    NASA Astrophysics Data System (ADS)

    Graizer, V.

    2013-12-01

    Ground motion prediction equations (GMPEs) for peak-ground acceleration (PGA) and 5-percent damped pseudo spectral accelerations (SA) of horizontal component ground motions were developed by Graizer and Kalkan (2007, 2009) using the extended ground motion database of the Next Generation of Attenuation project for shallow crustal earthquakes in active tectonic regions. The main features of these GMPEs (GK09) are: (1) only most essential measureable parameters [moment magnitude (M), closest distance to the fault rupture, style of faulting and average shear-wave velocity in the upper 30 meters of profile under the site (Vs30)] are used; (2) predictive model for SA is a continuous function of spectral period (T), which eliminates the standard matrix of estimator coefficients, and allows for calculation of SA at any period of interest within the model range of 0.01 to 10 sec; (3) mathematical form of GMPEs constitutes a series of filters--each filter represents a certain physical phenomenon affecting the radiation of seismic waves from the source. In contrast to the existing GMPEs, GK09 predictive model allows PGA to reach its maximum value at some distance from the fault effectively capturing the phenomenon observed in earthquakes with large number of near-source recordings such as the 1979 (M6.5) Imperial Valley and the 2004 (M6.0) Parkfield earthquakes. The GK09 GMPEs are shown to provide accuracy (expected median prediction without significant bias) and efficiency (relatively small standard error of predictions) as compared to recorded data at distances of up to 250 km during recent shallow-crustal earthquakes with 5.0≤M≤7.9 including the 2008 (M7.9) Wenchuan (China), 2010 (M7.2) El-Mayor Cucapah (Mexico), 2011 (M6.3) Christchurch (New Zealand) and other earthquakes. The GK09 GMPEs are updated here by adding an anelastic attenuation filter as a function of quality-factor (Q), and by improving the existing basin-effect filter, which is now a function of depth

  5. Habitat and Vegetation Variables Are Not Enough When Predicting Tick Populations in the Southeastern United States.

    PubMed

    Trout Fryxell, R T; Moore, J E; Collins, M D; Kwon, Y; Jean-Philippe, S R; Schaeffer, S M; Odoi, A; Kennedy, M; Houston, A E

    2015-01-01

    Two tick-borne diseases with expanding case and vector distributions are ehrlichiosis (transmitted by Amblyomma americanum) and rickettiosis (transmitted by A. maculatum and Dermacentor variabilis). There is a critical need to identify the specific habitats where each of these species is likely to be encountered to classify and pinpoint risk areas. Consequently, an in-depth tick prevalence study was conducted on the dominant ticks in the southeast. Vegetation, soil, and remote sensing data were used to test the hypothesis that habitat and vegetation variables can predict tick abundances. No variables were significant predictors of A. americanum adult and nymph tick abundance, and no clustering was evident because this species was found throughout the study area. For A. maculatum adult tick abundance was predicted by NDVI and by the interaction between habitat type and plant diversity; two significant population clusters were identified in a heterogeneous area suitable for quail habitat. For D. variabilis no environmental variables were significant predictors of adult abundance; however, D. variabilis collections clustered in three significant areas best described as agriculture areas with defined edges. This study identified few landscape and vegetation variables associated with tick presence. While some variables were significantly associated with tick populations, the amount of explained variation was not useful for predicting reliably where ticks occur; consequently, additional research that includes multiple sampling seasons and locations throughout the southeast are warranted. This low amount of explained variation may also be due to the use of hosts for dispersal, and potentially to other abiotic and biotic variables. Host species play a large role in the establishment, maintenance, and dispersal of a tick species, as well as the maintenance of disease cycles, dispersal to new areas, and identification of risk areas. PMID:26656122

  6. Habitat and Vegetation Variables Are Not Enough When Predicting Tick Populations in the Southeastern United States

    PubMed Central

    Trout Fryxell, R. T.; Moore, J. E.; Collins, M. D.; Kwon, Y.; Jean-Philippe, S. R.; Schaeffer, S. M.; Odoi, A.; Kennedy, M.; Houston, A. E.

    2015-01-01

    Two tick-borne diseases with expanding case and vector distributions are ehrlichiosis (transmitted by Amblyomma americanum) and rickettiosis (transmitted by A. maculatum and Dermacentor variabilis). There is a critical need to identify the specific habitats where each of these species is likely to be encountered to classify and pinpoint risk areas. Consequently, an in-depth tick prevalence study was conducted on the dominant ticks in the southeast. Vegetation, soil, and remote sensing data were used to test the hypothesis that habitat and vegetation variables can predict tick abundances. No variables were significant predictors of A. americanum adult and nymph tick abundance, and no clustering was evident because this species was found throughout the study area. For A. maculatum adult tick abundance was predicted by NDVI and by the interaction between habitat type and plant diversity; two significant population clusters were identified in a heterogeneous area suitable for quail habitat. For D. variabilis no environmental variables were significant predictors of adult abundance; however, D. variabilis collections clustered in three significant areas best described as agriculture areas with defined edges. This study identified few landscape and vegetation variables associated with tick presence. While some variables were significantly associated with tick populations, the amount of explained variation was not useful for predicting reliably where ticks occur; consequently, additional research that includes multiple sampling seasons and locations throughout the southeast are warranted. This low amount of explained variation may also be due to the use of hosts for dispersal, and potentially to other abiotic and biotic variables. Host species play a large role in the establishment, maintenance, and dispersal of a tick species, as well as the maintenance of disease cycles, dispersal to new areas, and identification of risk areas. PMID:26656122

  7. A generalized corresponding states method for predicting the limits of superheat of mixtures: application to the normal alcohols

    SciTech Connect

    Avedisian, C.T.; Sullivan, J.R.

    1983-07-01

    The limits of superheat of the normal alcohols from methanol to octanol and of ethanol/n-propanol, n-propanol/n-butanol, and n-butanol/n-pentanol mixtures were measured at atmospheric pressure. The results were correlated using a new method based on the generalized corresponding states principle in which the properties of two reference substances were used to predict the superheat limits of the liquids studied. Ethanol and n-butanol, and the two components of each mixture studied, were used as reference fluids for predicting the superheat limits of the pure alcohols and mixtures respectively. Results showed that it is possible to predict superheat limits to well within the accuracy of experimental measurements (< 1%). The method requires only accurate vapor pressure correlations and accentric factors of the reference fluids, and an accurate method for predicting the true critical temperature and pressure of the mixture. Considerable simplification using the present method over the approach based on classical homogeneous nucleation theory is derived from the fact that no mixture surface tension or bubble point pressure data are required.

  8. Climate downscaling effects on predictive ecological models: a case study for threatened and endangered vertebrates in the southeastern United States

    USGS Publications Warehouse

    Bucklin, David N.; Watling, James I.; Speroterra, Carolina; Brandt, Laura A.; Mazzotti, Frank J.; Romañach, Stephanie S.

    2013-01-01

    High-resolution (downscaled) projections of future climate conditions are critical inputs to a wide variety of ecological and socioeconomic models and are created using numerous different approaches. Here, we conduct a sensitivity analysis of spatial predictions from climate envelope models for threatened and endangered vertebrates in the southeastern United States to determine whether two different downscaling approaches (with and without the use of a regional climate model) affect climate envelope model predictions when all other sources of variation are held constant. We found that prediction maps differed spatially between downscaling approaches and that the variation attributable to downscaling technique was comparable to variation between maps generated using different general circulation models (GCMs). Precipitation variables tended to show greater discrepancies between downscaling techniques than temperature variables, and for one GCM, there was evidence that more poorly resolved precipitation variables contributed relatively more to model uncertainty than more well-resolved variables. Our work suggests that ecological modelers requiring high-resolution climate projections should carefully consider the type of downscaling applied to the climate projections prior to their use in predictive ecological modeling. The uncertainty associated with alternative downscaling methods may rival that of other, more widely appreciated sources of variation, such as the general circulation model or emissions scenario with which future climate projections are created.

  9. Updating representations of temporal intervals.

    PubMed

    Danckert, James; Anderson, Britt

    2015-12-01

    Effectively engaging with the world depends on accurate representations of the regularities that make up that world-what we call mental models. The success of any mental model depends on the ability to adapt to changes-to 'update' the model. In prior work, we have shown that damage to the right hemisphere of the brain impairs the ability to update mental models across a range of tasks. Given the disparate nature of the tasks we have employed in this prior work (i.e. statistical learning, language acquisition, position priming, perceptual ambiguity, strategic game play), we propose that a cognitive module important for updating mental representations should be generic, in the sense that it is invoked across multiple cognitive and perceptual domains. To date, the majority of our tasks have been visual in nature. Given the ubiquity and import of temporal information in sensory experience, we examined the ability to build and update mental models of time. We had healthy individuals complete a temporal prediction task in which intervals were initially drawn from one temporal range before an unannounced switch to a different range of intervals. Separate groups had the second range of intervals switch to one that contained either longer or shorter intervals than the first range. Both groups showed significant positive correlations between perceptual and prediction accuracy. While each group updated mental models of temporal intervals, those exposed to shorter intervals did so more efficiently. Our results support the notion of generic capacity to update regularities in the environment-in this instance based on temporal information. The task developed here is well suited to investigations in neurological patients and in neuroimaging settings. PMID:26303026

  10. Computer program simplifies transient and steady-state temperature prediction for complex body shapes

    NASA Technical Reports Server (NTRS)

    Giebler, K. N.

    1966-01-01

    Computer program evaluates heat transfer modes and calculates either the transient or steady-state temperature distributions throughout an object of complex shape when heat sources are applied to specified points on the object. It uses an electrothermal model to simulate the conductance, heat capacity, and temperature potential of the object.

  11. A Predictive Model for Migrant Farmworker Movement in the United States.

    ERIC Educational Resources Information Center

    Davis, Benjamin G.

    Since migration is strongly influenced by economic variables, an economic model was developed to identify, locate, and track migrant and seasonal farmworkers as they move throughout the United States. Focusing on the Florida-based migrant agricultural workers who migrated at least once during the past five years, the model included the following…

  12. The Effectiveness of Six Personality Variables in Predicting Success on the Nursing State Board Examination.

    ERIC Educational Resources Information Center

    Cusick, Patricia; Harckham, Laura D.

    A study was conducted to determine whether six personality variables, presently used in admissions decisions by a nursing school, were effective predictors of success on the State Board Examination (SBE), the nursing licensing examination. The personality variables were measured by subtests of the Personal Preference Schedule of the Psychological…

  13. Using State Assessments for Predicting Student Success in Dual-Enrollment College Classes

    ERIC Educational Resources Information Center

    Kingston, Neal M.; Anderson, Gretchen

    2013-01-01

    Scores on state standards-based assessments are readily available and may be an appropriate alternative to traditional placement tests for assigning or accepting students into particular courses. Many community colleges do not require test scores for admissions purposes but do require some kind of placement scores for first-year English and math…

  14. Monitoring of the stress state variations of the Southern California for the purpose of earthquake prediction

    NASA Astrophysics Data System (ADS)

    Gokhberg, M.; Garagash, I.; Bondur, V.; Steblov, G. M.

    2014-12-01

    The three-dimensional geomechanical model of Southern California was developed, including a mountain relief, fault tectonics and characteristic internal features such as the roof of the consolidated crust and Moho surface. The initial stress state of the model is governed by the gravitational forces and horizontal tectonic motions estimated from GPS observations. The analysis shows that the three-dimensional geomechanical models allows monitoring of the changes in the stress state during the seismic process in order to constrain the distribution of the future places with increasing seismic activity. This investigation demonstrates one of possible approach to monitor upcoming seismicity for the periods of days - weeks - months. Continuous analysis of the stress state was carried out during 2009-2014. Each new earthquake with М~1 and above from USGS catalog was considered as the new defect of the Earth crust which has some definite size and causes redistribution of the stress state. Overall calculation technique was based on the single function of the Earth crust damage, recalculated each half month. As a result each half month in the upper crust layers and partially in the middle layers we revealed locations of the maximal values of the stress state parameters: elastic energy density, shear stress, proximity of the earth crust layers to their strength limit. All these parameters exhibit similar spatial and temporal distribution. How follows from observations all four strongest events with М ~ 5.5-7.2 occurred in South California during the analyzed period were prefaced by the parameters anomalies in peculiar advance time of weeks-months in the vicinity of 10-50 km from the upcoming earthquake. After the event the stress state source disappeared. The figure shows migration of the maximums of the stress state variations gradients (parameter D) in the vicinity of the epicenter of the earthquake 04.04.2010 with М=7.2 in the period of 01.01.2010-01.05.2010. Grey lines

  15. Predicting intrinsic brain activity.

    PubMed

    Craddock, R Cameron; Milham, Michael P; LaConte, Stephen M

    2013-11-15

    Multivariate supervised learning methods exhibit a remarkable ability to decode externally driven sensory, behavioral, and cognitive states from functional neuroimaging data. Although they are typically applied to task-based analyses, supervised learning methods are equally applicable to intrinsic effective and functional connectivity analyses. The obtained models of connectivity incorporate the multivariate interactions between all brain regions simultaneously, which will result in a more accurate representation of the connectome than the ones available with standard bivariate methods. Additionally the models can be applied to decode or predict the time series of intrinsic brain activity of a region from an independent dataset. The obtained prediction accuracy provides a measure of the integration between a brain region and other regions in its network, as well as a method for evaluating acquisition and preprocessing pipelines for resting state fMRI data. This article describes a method for learning multivariate models of connectivity. The method is applied in the non-parametric prediction accuracy, influence, and reproducibility-resampling (NPAIRS) framework, to study the regional variation of prediction accuracy and reproducibility (Strother et al., 2002). The resulting spatial distribution of these metrics is consistent with the functional hierarchy proposed by Mesulam (1998). Additionally we illustrate the utility of the multivariate regression connectivity modeling method for optimizing experimental parameters and assessing the quality of functional neuroimaging data. PMID:23707580

  16. Narrative Representations of Caregivers and Emotion Dysregulation as Predictors of Maltreated Children's Rejection by Peers.

    ERIC Educational Resources Information Center

    Shields, Ann; Ryan, Richard M.; Cicchetti, Dante

    2001-01-01

    Examined whether maltreated children were more likely than nonmaltreated children to develop poor-quality representations of parents and whether these representations predicted children's rejection by peers. Found that maltreated children's representations were more negative/constricted and less positive/coherent than nonmaltreated children's.…

  17. V-Notched Bar Creep Life Prediction: GH3536 Ni-Based Superalloy Under Multiaxial Stress State

    NASA Astrophysics Data System (ADS)

    Zhang, D. X.; Wang, J. P.; Wen, Z. X.; Liu, D. S.; Yue, Z. F.

    2016-07-01

    In this study, creep experiments on smooth and circumferential V-type notched round bars were conducted in GH3536 Ni-based superalloy at 750 °C to identify notch strengthening effect in notched specimens. FE analysis was carried out, coupled with continuum damage mechanics (CDM), to analyze stress distribution and damage evolution under multiaxial stress state. The creep deformation of smooth specimens and the rupture life of both smooth and notched specimens showed good agreement between experimental results and FE analysis predictions; the creep rupture life for the notched specimen was successfully predicted via the "skeletal point" concept. Both creep damage analysis and the observed fracture morphology suggest that creep rupture started first at the root in the V-type notched specimens, and shifted to the region close to the notch root when the notch was relatively shallow compared to U-type notched specimens.

  18. V-Notched Bar Creep Life Prediction: GH3536 Ni-Based Superalloy Under Multiaxial Stress State

    NASA Astrophysics Data System (ADS)

    Zhang, D. X.; Wang, J. P.; Wen, Z. X.; Liu, D. S.; Yue, Z. F.

    2016-05-01

    In this study, creep experiments on smooth and circumferential V-type notched round bars were conducted in GH3536 Ni-based superalloy at 750 °C to identify notch strengthening effect in notched specimens. FE analysis was carried out, coupled with continuum damage mechanics (CDM), to analyze stress distribution and damage evolution under multiaxial stress state. The creep deformation of smooth specimens and the rupture life of both smooth and notched specimens showed good agreement between experimental results and FE analysis predictions; the creep rupture life for the notched specimen was successfully predicted via the "skeletal point" concept. Both creep damage analysis and the observed fracture morphology suggest that creep rupture started first at the root in the V-type notched specimens, and shifted to the region close to the notch root when the notch was relatively shallow compared to U-type notched specimens.

  19. Effects of cumulus parameterizations on predictions of summer flood in the Central United States

    NASA Astrophysics Data System (ADS)

    Qiao, Fengxue; Liang, Xin-Zhong

    2015-08-01

    This study comprehensively evaluates the effects of twelve cumulus parameterization (CUP) schemes on simulations of 1993 and 2008 Central US summer floods using the regional climate-weather research and forecasting model. The CUP schemes have distinct skills in predicting the summer mean pattern, daily rainfall frequency and precipitation diurnal cycle. Most CUP schemes largely underestimate the magnitude of Central US floods, but three schemes including the ensemble cumulus parameterization (ECP), the Grell-3 ensemble cumulus parameterization (G3) and Zhang-McFarlane-Liang cumulus parameterization (ZML) show clear advantages over others in reproducing both floods location and amount. In particular, the ECP scheme with the moisture convergence closure over land and cloud-base vertical velocity closure over oceans not only reduces the wet biases in the G3 and ZML schemes along the US coastal oceans, but also accurately reproduces the Central US daily precipitation variation and frequency distribution. The Grell (GR) scheme shows superiority in reproducing the Central US nocturnal rainfall maxima, but others generally fail. This advantage of GR scheme is primarily due to its closure assumption in which the convection is determined by the tendency of large-scale instability. Future study will attempt to incorporate the large-scale tendency assumption as a trigger function in the ECP scheme to improve its prediction of Central US rainfall diurnal cycle.

  20. Model-based predictions of solid state intermetallic compound layer growth in hybrid microelectronic circuits

    SciTech Connect

    Vianco, P.T.; Erickson, K.L.; Hopkins, P.L.

    1997-12-31

    A mathematical model was developed to quantitatively describe the intermetallic compound (IMC) layer growth that takes place between a Sn-based solder and a noble metal thick film conductor material used in hybrid microcircuit (HMC) assemblies. The model combined the reaction kinetics of the solder/substrate interaction, as determined from ancillary isothermal aging experiments, with a 2-D finite element mesh that took account of the porous morphology of the thick film coating. The effect of the porous morphology on the IMC layer growth when compared to the traditional 1-D computations was significant. The previous 1-D calculations under-predicted the nominal IMC layer thickness relative to the 2-D case. The 2-D model showed greater substrate consumption by IMC growth and lesser solder consumption that was determined with the 1-D computation. The new 2-D model allows the design engineer to better predict circuit aging and hence, the reliability of HMC hardware that is placed in the field.