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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 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

  10. 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

  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. 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.

  5. 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

  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. 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

  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. 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.

  16. 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

  17. 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.

  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. 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

  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. 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.

  4. 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

  5. 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

  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. 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

  10. 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

  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. 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.

  4. 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.

  5. 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

  6. 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

  7. 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.

  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. 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.

  13. 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.

  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. 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.

  18. 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.

  19. 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.

  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. 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

  7. 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.

  8. 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)

  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. 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

  18. 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

  19. 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

  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. 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...

  7. 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,…

  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. 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

  15. 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…

  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. 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.

  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. 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.

  1. 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.

  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. 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)

  13. 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

  14. 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

  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. 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…

  18. 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…

  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.

    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

  1. 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.

  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. 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.

  4. 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

  5. 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

  6. 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.

  7. 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.

  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. 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.

  12. 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

  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. 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…

  18. 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…

  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. 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

  5. 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

  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. 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

  11. 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...

  12. 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…

  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. 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.

  10. 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.

  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. 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…

  9. 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…

  10. 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...