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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. 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.

  4. 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.

  5. 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

  6. Flexibility of representational states in working memory.

    PubMed

    Zokaei, Nahid; Ning, Shen; Manohar, Sanjay; Feredoes, Eva; Husain, Masud

    2014-01-01

    The relationship between working memory (WM) and attention is a highly interdependent one, with evidence that attention determines the state in which items in WM are retained. Through focusing of attention, an item might be held in a more prioritized state, commonly termed as the focus of attention (FOA). The remaining items, although still retrievable, are considered to be in a different representational state. One means to bring an item into the FOA is to use retrospective cues ("retro-cues") which direct attention to one of the objects retained in WM. Alternatively, an item can enter a privileged state once attention is directed towards it through bottom-up influences (e.g., recency effect) or by performing an action on one of the retained items ("incidental" cueing). In all these cases, the item in the FOA is recalled with better accuracy compared to the other items in WM. Far less is known about the nature of the other items in WM and whether they can be flexibly manipulated in and out of the FOA. We present data from three types of experiments as well as transcranial magnetic stimulation (TMS) to early visual cortex to manipulate the item inside FOA. Taken together, our results suggest that the context in which items are retained in WM matters. When an item remains behaviorally relevant, despite not being inside the FOA, re-focusing attention upon it can increase its recall precision. This suggests that a non-FOA item can be held in a state in which it can be later retrieved. However, if an item is rendered behaviorally unimportant because it is very unlikely to be probed, it cannot be brought back into the FOA, nor recalled with high precision. Under such conditions, some information appears to be irretrievably lost from WM. These findings, obtained from several different methods, demonstrate quite considerable flexibility with which items in WM can be represented depending upon context. They have important consequences for emerging state-dependent models of

  7. Operational representation of quantum states based on interference.

    PubMed

    Wolf, Alexander; Freyberger, Matthias

    2004-11-12

    We describe a real-valued and periodic representation of quantum states. This representation can be defined operationally using generalized position and momentum measurements on coupled systems. It turns out that the emerging quantum interference terms encode the complete state information and also allow us to formulate quantum dynamics. We discuss the close connection to the theory of analytic functions. PMID:15600905

  8. 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

  9. 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

  10. 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

  11. Sparse/DCT (S/DCT) two-layered representation of prediction residuals for video coding.

    PubMed

    Kang, Je-Won; Gabbouj, Moncef; Kuo, C-C Jay

    2013-07-01

    In this paper, we propose a cascaded sparse/DCT (S/DCT) two-layer representation of prediction residuals, and implement this idea on top of the state-of-the-art high efficiency video coding (HEVC) standard. First, a dictionary is adaptively trained to contain featured patterns of residual signals so that a high portion of energy in a structured residual can be efficiently coded via sparse coding. It is observed that the sparse representation alone is less effective in the R-D performance due to the side information overhead at higher bit rates. To overcome this problem, the DCT representation is cascaded at the second stage. It is applied to the remaining signal to improve coding efficiency. The two representations successfully complement each other. It is demonstrated by experimental results that the proposed algorithm outperforms the HEVC reference codec HM5.0 in the Common Test Condition.

  12. 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

  13. State-Variable Representations For Moving-Average Sampling

    NASA Technical Reports Server (NTRS)

    Polites, Michael E.

    1991-01-01

    Two state-variable representations derived for continuous-time plant driven by control algorithm including zero-order hold and measurements sampled at mutliple rates by multiple-input/multiple-output moving-average processes. New representations enhance observability and controllability of plant. Applications include mathematical modeling of navigation systems including star trackers, gyroscopes, and accelerometers.

  14. Entangled State Representation for Four-Wave Mixing

    NASA Astrophysics Data System (ADS)

    Ma, Shan-Jun; Lu, Hai-Liang; Fan, Hong-Yi

    2008-08-01

    We introduce the entangled state representation to describe the four-wave mixing. We find that the four-wave mixing operator, which engenders the correct input-output field transformation, has a natural representation in the entangled state representation. In this way, we see that the four-wave mixing process not only involves squeezing but also is an entanglement process. This analysis brings convenience to the calculation of quadrature-amplitude measurement for the output state of four-wave mixing process.

  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.

  16. 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

  17. Semantic representations in the temporal pole predict false memories

    PubMed Central

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

    2016-01-01

    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

  18. 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.

  19. Representation in the States: Policymaking and Ideology.

    ERIC Educational Resources Information Center

    Nice, David C.

    1983-01-01

    The degree of responsiveness of state policies to the ideological leanings of public opinion is examined. States with more liberal electorates, as indicated by their support for George McGovern in the 1972 presidential election, have higher welfare benefits and expenditures, higher education expenditures, and more consumer protection laws.…

  20. Owl's behavior and neural representation predicted by Bayesian inference.

    PubMed

    Fischer, Brian J; Peña, José Luis

    2011-08-01

    The owl captures prey using sound localization. In the classical model, the owl infers sound direction from the position of greatest activity in a brain map of auditory space. However, this model fails to describe the actual behavior. Although owls accurately localize sources near the center of gaze, they systematically underestimate peripheral source directions. We found that this behavior is predicted by statistical inference, formulated as a Bayesian model that emphasizes central directions. We propose that there is a bias in the neural coding of auditory space, which, at the expense of inducing errors in the periphery, achieves high behavioral accuracy at the ethologically relevant range. We found that the owl's map of auditory space decoded by a population vector is consistent with the behavioral model. Thus, a probabilistic model describes both how the map of auditory space supports behavior and why this representation is optimal. PMID:21725311

  1. 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

  2. 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.

  3. 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

  4. 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.

  5. Representations of Canonical Commutation Relations Describing Infinite Coherent States

    NASA Astrophysics Data System (ADS)

    Joye, Alain; Merkli, Marco

    2016-10-01

    We investigate the infinite volume limit of quantized photon fields in multimode coherent states. We show that for states containing a continuum of coherent modes, it is mathematically and physically natural to consider their phases to be random and identically distributed. The infinite volume states give rise to Hilbert space representations of the canonical commutation relations which we construct concretely. In the case of random phases, the representations are random as well and can be expressed with the help of Itô stochastic integrals. We analyze the dynamics of the infinite state alone and the open system dynamics of small systems coupled to it. We show that under the free field dynamics, initial phase distributions are driven to the uniform distribution. We demonstrate that coherences in small quantum systems, interacting with the infinite coherent state, exhibit Gaussian time decay. The decoherence is qualitatively faster than the one caused by infinite thermal states, which is known to be exponentially rapid only. This emphasizes the classical character of coherent states.

  6. Efimov effect in the distorted cluster state representation

    SciTech Connect

    Estrin, A.; Kostrun, M.; Hahn, Y.

    1998-01-01

    The Efimov effect for a three-body system was studied previously in an adiabatic representation, where the distance between two {open_quotes}heavy{close_quotes} particles was represented by {bold x}, and the third {open_quotes}light{close_quotes} particle was described by coordinate {bold y} relative to the center of mass of the heavy ones. When {bold x} is held fixed, an exact solution for the light particle can be obtained if the interaction is assumed to be of separable form. The resulting adiabatic potential between the heavy particles shows the critical {minus}1/x{sup 2} behavior that leads to an infinite number of bound states. However, subsequently the leading nonadiabatic effect was shown to generate an undesirable correction of 1/x type, the pseudo-Coulomb disease (PCD). To remedy the PCD, the Efimov effect is reexamined in the adiabatic state representation, but with the new Jacobi coordinates ({bold r},{bold R}), where {bold r} describes the distance between one of the heavy particles and the light one and {bold R} is the position of the other heavy particle with respect to the center of mass of the subsystem of light-heavy particles. It is then shown that the adiabatic potential in this distorted cluster state representation behaves as {minus}1/R{sup 2} at large {bold R} if the pair described by {bold r} has a zero-energy bound state. Moreover, in this case the leading nonadiabatic correction term does not manifest the PCD, thus explicitly showing that the PCD is due to the {open_quotes}wrong{close_quotes} choice of coordinates ({bold x},{bold y}). Alternatively, a particle boost factor is introduced to eliminate the PCD in the treatment with the original ({bold x},{bold y}) coordinates. This is shown to be equivalent to the change in coordinates, described above. Such a factor is usually associated with high energy collisions, but for the first time shown here to play also an important role in near zero-energy situations. {copyright} {ital 1998} {ital

  7. 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

  8. The Generalization of Attachment Representations to New Social Situations: Predicting Behavior during Initial Interactions with Strangers

    PubMed Central

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

    2008-01-01

    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 two 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 results and contributions to existing literature are discussed. PMID:19025297

  9. Self-other representations mediate the relationship between Five-Factor Model depression and depressive states.

    PubMed

    Huprich, Steven K; Pouliot, Gregory S; Bruner, Reino

    2012-01-01

    While it is well established that trait depression is a risk factor for experiencing increased rates of episodes of depression, it is also the case that the ways in which the self and others are perceived, and nature of the relationship between self and other, predispose individuals to frequent depressive episodes. In this study, 182 psychiatric outpatients at three treatment facilities were evaluated for Five-Factor Model depressive traits, depressive states, and self-other representations (object relations). It was hypothesized that object relations would mediate the relationship between trait and state depression. Results partially confirmed this hypothesis. While trait depression significantly predicted variance in the Beck Depression Inventory-II (BDI-II; Beck et al., 1988), two dimensions of the Bell Object Relations and Reality Testing Inventory (BORRTI; Bell, 1995)--Alienation and Insecure Attachment--partially mediated the relationship between trait and state depression. Similarly, trait depression predicted tendencies to experience frequent shifts toward depressive episodes, although the Insecure Attachment and Egocentricity scales of the BORRTI fully mediated the relationship between trait depression and depressive lability. Knowledge of self-other representations, which is being considered for inclusion in the DSM-5, allows for a more refined understanding of those factors that contribute shifts in depressive mood. PMID:22642436

  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. Using Weighted Sparse Representation Model Combined with Discrete Cosine Transformation to Predict Protein-Protein Interactions from Protein Sequence

    PubMed Central

    Huang, Yu-An; You, Zhu-Hong; Gao, Xin; Wong, Leon; Wang, Lirong

    2015-01-01

    Increasing demand for the knowledge about protein-protein interactions (PPIs) is promoting the development of methods for predicting protein interaction network. Although high-throughput technologies have generated considerable PPIs data for various organisms, it has inevitable drawbacks such as high cost, time consumption, and inherently high false positive rate. For this reason, computational methods are drawing more and more attention for predicting PPIs. In this study, we report a computational method for predicting PPIs using the information of protein sequences. The main improvements come from adopting a novel protein sequence representation by using discrete cosine transform (DCT) on substitution matrix representation (SMR) and from using weighted sparse representation based classifier (WSRC). When performing on the PPIs dataset of Yeast, Human, and H. pylori, we got excellent results with average accuracies as high as 96.28%, 96.30%, and 86.74%, respectively, significantly better than previous methods. Promising results obtained have proven that the proposed method is feasible, robust, and powerful. To further evaluate the proposed method, we compared it with the state-of-the-art support vector machine (SVM) classifier. Extensive experiments were also performed in which we used Yeast PPIs samples as training set to predict PPIs of other five species datasets. PMID:26634213

  12. Using Weighted Sparse Representation Model Combined with Discrete Cosine Transformation to Predict Protein-Protein Interactions from Protein Sequence.

    PubMed

    Huang, Yu-An; You, Zhu-Hong; Gao, Xin; Wong, Leon; Wang, Lirong

    2015-01-01

    Increasing demand for the knowledge about protein-protein interactions (PPIs) is promoting the development of methods for predicting protein interaction network. Although high-throughput technologies have generated considerable PPIs data for various organisms, it has inevitable drawbacks such as high cost, time consumption, and inherently high false positive rate. For this reason, computational methods are drawing more and more attention for predicting PPIs. In this study, we report a computational method for predicting PPIs using the information of protein sequences. The main improvements come from adopting a novel protein sequence representation by using discrete cosine transform (DCT) on substitution matrix representation (SMR) and from using weighted sparse representation based classifier (WSRC). When performing on the PPIs dataset of Yeast, Human, and H. pylori, we got excellent results with average accuracies as high as 96.28%, 96.30%, and 86.74%, respectively, significantly better than previous methods. Promising results obtained have proven that the proposed method is feasible, robust, and powerful. To further evaluate the proposed method, we compared it with the state-of-the-art support vector machine (SVM) classifier. Extensive experiments were also performed in which we used Yeast PPIs samples as training set to predict PPIs of other five species datasets. PMID:26634213

  13. 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

  14. 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.

  15. Cumulative Time Series Representation for Code Blue prediction in the Intensive Care Unit.

    PubMed

    Salas-Boni, Rebeca; Bai, Yong; Hu, Xiao

    2015-01-01

    Patient monitors in hospitals generate a high number of false alarms that compromise patients care and burden clinicians. In our previous work, an attempt to alleviate this problem by finding combinations of monitor alarms and laboratory test that were predictive of code blue events, called SuperAlarms. Our current work consists of developing a novel time series representation that accounts for both cumulative effects and temporality was developed, and it is applied to code blue prediction in the intensive care unit (ICU). The health status of patients is represented both by a term frequency approach, TF, often used in natural language processing; and by our novel cumulative approach. We call this representation "weighted accumulated occurrence representation", or WAOR. These two representations are fed into a L1 regularized logistic regression classifier, and are used to predict code blue events. Our performance was assessed online in an independent set. We report the sensitivity of our algorithm at different time windows prior to the code blue event, as well as the work-up to detect ratio and the proportion of false code blue detections divided by the number of false monitor alarms. We obtained a better performance with our cumulative representation, retaining a sensitivity close to our previous work while improving the other metrics. PMID:26306261

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

    PubMed

    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.

  17. 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

  18. Masking of Children's Early Understanding of the Representational Mind: Backwards Explanation versus Prediction.

    ERIC Educational Resources Information Center

    Robinson, E. J.; Mitchell, P.

    1995-01-01

    Examines the use of tasks with backward false belief explanation as an effective technique in gaining a complete picture of the development of understanding of the representational mind. Argues that traditional prediction tests of false belief cannot tell whether children's wrong answers show misunderstanding about false belief or seduction by the…

  19. Multi-voxel patterns of visual category representation during episodic encoding are predictive of subsequent memory

    PubMed Central

    Kuhl, Brice A.; Rissman, Jesse; Wagner, Anthony D.

    2012-01-01

    Successful encoding of episodic memories is thought to depend on contributions from prefrontal and temporal lobe structures. Neural processes that contribute to successful encoding have been extensively explored through univariate analyses of neuroimaging data that compare mean activity levels elicited during the encoding of events that are subsequently remembered vs. those subsequently forgotten. Here, we applied pattern classification to fMRI data to assess the degree to which distributed patterns of activity within prefrontal and temporal lobe structures elicited during the encoding of word-image pairs were diagnostic of the visual category (Face or Scene) of the encoded image. We then assessed whether representation of category information was predictive of subsequent memory. Classification analyses indicated that temporal lobe structures contained information robustly diagnostic of visual category. Information in prefrontal cortex was less diagnostic of visual category, but was nonetheless associated with highly reliable classifier-based evidence for category representation. Critically, trials associated with greater classifier-based estimates of category representation in temporal and prefrontal regions were associated with a higher probability of subsequent remembering. Finally, consideration of trial-by-trial variance in classifier-based measures of category representation revealed positive correlations between prefrontal and temporal lobe representations, with the strength of these correlations varying as a function of the category of image being encoded. Together, these results indicate that multi-voxel representations of encoded information can provide unique insights into how visual experiences are transformed into episodic memories. PMID:21925190

  20. 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

  1. State-dependent self-representations: a culture-bound aspect of identity.

    PubMed

    Ghorpade, Amar

    2009-03-01

    The concepts of identity, self and self-representation have been discussed extensively in psychoanalytic metapsychology. These concepts are at times confusing and are used interchangeably by various authors. Regardless of what one calls it, what one experiences in a given moment is one's representation as an analyst or a father or a son or daughter, depending on the situation one is in. This paper describes such state-dependent self-representations as an aspect of the self and argues that state-dependent self-representations are probably more clinically relevant and useful in day-to-day practice.

  2. Phase-space representation of quantum state vectors: The relative-state approach and the displacement-operator approach

    NASA Astrophysics Data System (ADS)

    Ban, Masashi

    1999-08-01

    Phase-space representation of quantum state vectors has been recently formulated by means of the relative-state method developed by the present author [J. Math. Phys. 39, 1744 (1998)]. It is, however, pointed out by Mo/ller that the displacement-operator method provides another basis of phase-space representation of quantum state vectors [J. Math. Phys. (to appear)]. Hence the relation between the relative-state approach and the displacement-operator approach is discussed, both of which yield equivalent phase-space representations.

  3. 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.

  4. 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

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

    PubMed

    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

  6. 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.

  7. 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

  8. 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

  9. Hermitian Operators Conjugate to Two-Mode Number-Difference Operator Studied in Entangled State Representation

    NASA Astrophysics Data System (ADS)

    Xu, Xue-Fen

    2008-10-01

    In similar to the derivation of phase angle operator conjugate to the number operator by Arroyo Carrasco-Moya Cessay we deduce the Hermitian phase operators that are conjugate to the two-mode number-difference operator and the three-mode number combination operator. It is shown that these operators are on the same footing in the entangled state representation as the one of Turski in the coherent state representation.

  10. 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.

  11. Cultural influences on cognitive representations of conflict: interpretations of conflict episodes in the United States and Japan.

    PubMed

    Gelfand, M J; Nishii, L H; Holcombe, K M; Dyer, N; Ohbuchi, K I; Fukuno, M

    2001-12-01

    This article integrates theory from the cognitive tradition in negotiation with theory on culture and examines cultural influences on cognitive representations of conflict. The authors predicted that although there may be universal (etic) dimensions of conflict construals, there also may be culture-specific (emic) representations of conflict in the United States and Japan. Results of multidimensional scaling analyses of U.S. and Japanese conflict episodes supported this view. Japanese and Americans construed conflicts through a compromise versus win frame (R. L. Pinkley, 1990), providing evidence of a universal dimension of conflict construal. As the authors predicted, Japanese perceived conflicts to be more compromise-focused, as compared with Americans. There were also unique dimensions of construal among Americans and Japanese (infringements to self and giri violations, respectively), suggesting that identical conflict episodes are perceived differently across cultures.

  12. Representations of dread: the dreaded self and the dreaded state of the self.

    PubMed

    Koch, E

    2000-04-01

    The experience of dread, an extreme form of fear that is induced by terror and horror, is seen as manifested in the shapes of a "dreaded self" and a "dreaded state of the self." These representations reflect psychic dangers ranging from a common, feared identification to states of disconnection, desolation, ego dissolution, and nonexistence. It is suggested that life crises and traumatic impingements, informed by developmental and psychic realities, are critical determinants of multiple dreaded self-representations; that disavowal often serves to massively ward off the recognition of the awful; and that these representations serve a preconscious signal function that anticipates the danger of reexperiencing an original terror. Case examples illustrate these points and reflect the utility of the language of dreaded representations in the treatment situation. PMID:10824320

  13. 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.

  14. An Incomplete History: Representation of American Indians in State Social Studies Standards

    ERIC Educational Resources Information Center

    Journell, Wayne

    2009-01-01

    Using an interpretive analysis, American history standards from nine states that incorporate high-stakes assessments in social studies are analyzed for their representation of American Indians. Research on high-stakes assessments shows that teachers are more likely to align their instruction with state standards due to mounting pressure to achieve…

  15. 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.

  16. 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

  17. 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

  18. 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...

  19. Predicting trend reversals using market instantaneous state

    NASA Astrophysics Data System (ADS)

    Bury, Thomas

    2014-06-01

    Collective behaviors taking place in financial markets reveal strongly correlated states especially during a crisis period. A natural hypothesis is that trend reversals are also driven by mutual influences between the different stock exchanges. Using a maximum entropy approach, we find coordinated behavior during trend reversals dominated by the pairwise component. In particular, these events are predicted with high significant accuracy by the ensemble's instantaneous state.

  20. 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

  1. 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.

  2. Continuum tensor network field states, path integral representations and spatial symmetries

    NASA Astrophysics Data System (ADS)

    Jennings, David; Brockt, Christoph; Haegeman, Jutho; Osborne, Tobias J.; Verstraete, Frank

    2015-06-01

    A natural way to generalize tensor network variational classes to quantum field systems is via a continuous tensor contraction. This approach is first illustrated for the class of quantum field states known as continuous matrix-product states (cMPS). As a simple example of the path-integral representation we show that the state of a dynamically evolving quantum field admits a natural representation as a cMPS. A completeness argument is also provided that shows that all states in Fock space admit a cMPS representation when the number of variational parameters tends to infinity. Beyond this, we obtain a well-behaved field limit of projected entangled-pair states (PEPS) in two dimensions that provide an abstract class of quantum field states with natural symmetries. We demonstrate how symmetries of the physical field state are encoded within the dynamics of an auxiliary field system of one dimension less. In particular, the imposition of Euclidean symmetries on the physical system requires that the auxiliary system involved in the class’ definition must be Lorentz-invariant. The physical field states automatically inherit entropy area laws from the PEPS class, and are fully described by the dissipative dynamics of a lower dimensional virtual field system. Our results lie at the intersection many-body physics, quantum field theory and quantum information theory, and facilitate future exchanges of ideas and insights between these disciplines.

  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. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. Which model enhancements improved predictions: time series, geo-data or process representation?

    NASA Astrophysics Data System (ADS)

    Francke, Till; Delgado, José Miguel; Bronstert, Axel

    2015-04-01

    Results of field monitoring, remote sensing and research were integrated into the hydro-sedimentolgical model WASA-SED in the Esera catchment in the Pyrenees in northeastern Spain (1370 km²). WASA-SED employs a hierarchical top-down disaggregation of the landscape based on characteristic toposequences. Now, by improving 1. time series (rainfall and discharge) 2. geo-data (land use, LAI and C-factor and their seasonality) and 3. the representation of water and sediment connectivity in the model, we intend to evaluate which model enhancements (MEs) have a positive effect on the model predictions. The evaluation of the model prediction is performed in two ways: first, in a forward selection step each model enhancement is added to the base configuration (setting A). Any change in performance is compared with respect to setting A. Complementary, in a backward elimination step each ME is withheld from the full configuration (setting B); the change in performance is compared with respect to setting B. This stepwise approach allows a more differentiated view on the role of the single enhancements: in the case that some MEs only become viable if others have already surpassed a certain level (i.e. better rainfall data is only useful if landuse information is detailed enough), this effect will become apparent. The model enhancements may improve model predictions globally or only in some particular aspect of the model. The enhancements were therefore evaluated against 1. a calibrated and an uncalibrated model, 2. with respect to results at the outlet and on the subcatchment, 3. in water and sediment and 4. in terms of dynamics and yield. We expect this investigation to demonstrate the potential of a model as a tool for integrating and quantifying the value of additional knowledge as well as a framework for assessing research outcomes.

  10. The Attachment Doll Play Assessment: Predictive Validity with Concurrent Mother-Child Interaction and Maternal Caregiving Representations

    PubMed Central

    George, Carol; Solomon, Judith

    2016-01-01

    Attachment is central to the development of children’s regulatory processes. It has been associated with developmental and psychiatric health across the life span, especially emotional and behavioral regulation of negative affect when stressed (Schore, 2001; Schore and Schore, 2008). Assessment of attachment patterns provides a critical frame for understanding emerging developmental competencies and formulating treatment and intervention. Play-based attachment assessments provide access to representational models of attachment, which are regarded in attachment theory as the central organizing mechanisms associated with stability or change (Bowlby, 1969/1982; Bretherton and Munholland, 2008). The Attachment Doll Play Assessment (ADPA, George and Solomon, 1990–2016; Solomon et al., 1995) is a prominent established representational attachment measure for children aged early latency through childhood. This study examines the predictive validity of the ADPA to caregiving accessibility and responsiveness assessed from mother-child interaction and maternal representation. Sixty nine mothers and their 5–7-year-old children participated in this study. Mother-child interaction was observed during a pre-separation dyadic interaction task. Caregiving representations were rated from the Caregiving Interview (George and Solomon, 1988/1993/2005/2007). Child security with mother was associated with positive dyadic interaction and flexibly integrated maternal caregiving representations. Child controlling/disorganized attachments were significantly associated with problematic dyadic interaction and dysregulated-helpless maternal caregiving representations. The clinical implications and the use of the ADPA in clinical and educational settings are discussed. PMID:27803683

  11. 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.

  12. 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…

  13. 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.

  14. 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.

  15. 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

    2016-10-01

    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.

  16. 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

  17. Convolution theorem for the three-dimensional entangled fractional Fourier transformation deduced from the tripartite entangled state representation

    NASA Astrophysics Data System (ADS)

    Liu, Shu-Guang; Fan, Hong-Yi

    2009-12-01

    We find that constructing the two mutually-conjugate tripartite entangled state representations naturally leads to the entangled Fourier transformation. We then derive the convolution theorem for the threedimensional entangled fractional Fourier transformation in the context of quantum mechanics.

  18. 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.

  19. Predictive control and estimation - State space approach

    NASA Technical Reports Server (NTRS)

    Gawronski, W.

    1991-01-01

    A modified output prediction procedure and a new controller design based on the predictive control law are presented. A new predictive estimator enhances system performance. The predictive controller was designed and applied to the tracking control of the NASA/JPL 70-m antenna. Simulation results show significant improvement in tracking performance over the linear quadratic controller and estimator presently in use.

  20. Self-regulating genes. Exact steady state solution by using Poisson representation

    NASA Astrophysics Data System (ADS)

    Sugár, István P.; Simon, István

    2014-09-01

    Systems biology studies the structure and behavior of complex gene regulatory networks. One of its aims is to develop a quantitative understanding of the modular components that constitute such networks. The self-regulating gene is a type of auto regulatory genetic modules which appears in over 40% of known transcription factors in E. coli. In this work, using the technique of Poisson Representation, we are able to provide exact steady state solutions for this feedback model. By using the methods of synthetic biology (P.E.M. Purnick and Weiss, R., Nature Reviews, Molecular Cell Biology, 2009, 10: 410-422) one can build the system itself from modules like this.

  1. 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

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

    NASA Astrophysics Data System (ADS)

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

    2009-06-01

    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.

  3. Robust brain parcellation using sparse representation on resting-state fMRI.

    PubMed

    Zhang, Yu; Caspers, Svenja; Fan, Lingzhong; Fan, Yong; Song, Ming; Liu, Cirong; Mo, Yin; Roski, Christian; Eickhoff, Simon; Amunts, Katrin; Jiang, Tianzi

    2015-11-01

    Resting-state fMRI (rs-fMRI) has been widely used to segregate the brain into individual modules based on the presence of distinct connectivity patterns. Many parcellation methods have been proposed for brain parcellation using rs-fMRI, but their results have been somewhat inconsistent, potentially due to various types of noise. In this study, we provide a robust parcellation method for rs-fMRI-based brain parcellation, which constructs a sparse similarity graph based on the sparse representation coefficients of each seed voxel and then uses spectral clustering to identify distinct modules. Both the local time-varying BOLD signals and whole-brain connectivity patterns may be used as features and yield similar parcellation results. The robustness of our method was tested on both simulated and real rs-fMRI datasets. In particular, on simulated rs-fMRI data, sparse representation achieved good performance across different noise levels, including high accuracy of parcellation and high robustness to noise. On real rs-fMRI data, stable parcellation of the medial frontal cortex (MFC) and parietal operculum (OP) were achieved on three different datasets, with high reproducibility within each dataset and high consistency across these results. Besides, the parcellation of MFC was little influenced by the degrees of spatial smoothing. Furthermore, the consistent parcellation of OP was also well corresponding to cytoarchitectonic subdivisions and known somatotopic organizations. Our results demonstrate a new promising approach to robust brain parcellation using resting-state fMRI by sparse representation.

  4. Spatial mental representations derived from spatial descriptions: the predicting and mediating roles of spatial preferences, strategies, and abilities.

    PubMed

    Meneghetti, Chiara; Ronconi, Lucia; Pazzaglia, Francesca; De Beni, Rossana

    2014-08-01

    The aim of this research was to investigate how spatial self-assessments and spatial cognitive abilities jointly influence the construction of mental representations derived from spatial descriptions. Two studies were conducted using the path models approach to test to what extent spatial self-assessments (Study 1, 194 participants) and the combination of the latter with spatial abilities (Study 2, 206 participants) can be modelled to predict memory for spatial descriptions. In both studies, we recorded spatial representation preferences (distinguishing between survey, route, and landmark-focused mode) and self-reported strategies used to memorize descriptions (distinguishing between survey, route, and verbal strategies); in Study 2, we also measured spatial abilities by testing mental rotation (MR) and visuo-spatial working memory (VSWM). Participants listened to spatial descriptions and then completed recall tasks. In both studies, the final path models showed that spatial preferences influenced spatial recall through the mediation of congruent strategies: that is a survey (route) preference influenced spatial recall mediated by a survey (route) strategy. MR predicted spatial recall, mediated by both VSWM and survey strategy (Study 2). Overall, these findings indicate that spatial preferences (particularly for a survey mode) in association with spatial abilities effectively concur to help form mental representations derived from spatial descriptions.

  5. 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.

  6. Representational similarity encoding for fMRI: Pattern-based synthesis to predict brain activity using stimulus-model-similarities.

    PubMed

    Anderson, Andrew James; Zinszer, Benjamin D; Raizada, Rajeev D S

    2016-03-01

    Patterns of neural activity are systematically elicited as the brain experiences categorical stimuli and a major challenge is to understand what these patterns represent. Two influential approaches, hitherto treated as separate analyses, have targeted this problem by using model-representations of stimuli to interpret the corresponding neural activity patterns. Stimulus-model-based-encoding synthesizes neural activity patterns by first training weights to map between stimulus-model features and voxels. This allows novel model-stimuli to be mapped into voxel space, and hence the strength of the model to be assessed by comparing predicted against observed neural activity. Representational Similarity Analysis (RSA) assesses models by testing how well the grand structure of pattern-similarities measured between all pairs of model-stimuli aligns with the same structure computed from neural activity patterns. RSA does not require model fitting, but also does not allow synthesis of neural activity patterns, thereby limiting its applicability. We introduce a new approach, representational similarity-encoding, that builds on the strengths of RSA and robustly enables stimulus-model-based neural encoding without model fitting. The approach therefore sidesteps problems associated with overfitting that notoriously confront any approach requiring parameter estimation (and is consequently low cost computationally), and importantly enables encoding analyses to be incorporated within the wider Representational Similarity Analysis framework. We illustrate this new approach by using it to synthesize and decode fMRI patterns representing the meanings of words, and discuss its potential biological relevance to encoding in semantic memory. Our new similarity-based encoding approach unites the two previously disparate methods of encoding models and RSA, capturing the strengths of both, and enabling similarity-based synthesis of predicted fMRI patterns.

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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.

  13. A state-based probabilistic model for tumor respiratory motion prediction

    NASA Astrophysics Data System (ADS)

    Kalet, Alan; Sandison, George; Wu, Huanmei; Schmitz, Ruth

    2010-12-01

    This work proposes a new probabilistic mathematical model for predicting tumor motion and position based on a finite state representation using the natural breathing states of exhale, inhale and end of exhale. Tumor motion was broken down into linear breathing states and sequences of states. Breathing state sequences and the observables representing those sequences were analyzed using a hidden Markov model (HMM) to predict the future sequences and new observables. Velocities and other parameters were clustered using a k-means clustering algorithm to associate each state with a set of observables such that a prediction of state also enables a prediction of tumor velocity. A time average model with predictions based on average past state lengths was also computed. State sequences which are known a priori to fit the data were fed into the HMM algorithm to set a theoretical limit of the predictive power of the model. The effectiveness of the presented probabilistic model has been evaluated for gated radiation therapy based on previously tracked tumor motion in four lung cancer patients. Positional prediction accuracy is compared with actual position in terms of the overall RMS errors. Various system delays, ranging from 33 to 1000 ms, were tested. Previous studies have shown duty cycles for latencies of 33 and 200 ms at around 90% and 80%, respectively, for linear, no prediction, Kalman filter and ANN methods as averaged over multiple patients. At 1000 ms, the previously reported duty cycles range from approximately 62% (ANN) down to 34% (no prediction). Average duty cycle for the HMM method was found to be 100% and 91 ± 3% for 33 and 200 ms latency and around 40% for 1000 ms latency in three out of four breathing motion traces. RMS errors were found to be lower than linear and no prediction methods at latencies of 1000 ms. The results show that for system latencies longer than 400 ms, the time average HMM prediction outperforms linear, no prediction, and the more

  14. 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.

  15. Understanding Karma Police: The Perceived Plausibility of Noun Compounds as Predicted by Distributional Models of Semantic Representation

    PubMed Central

    Günther, Fritz; Marelli, Marco

    2016-01-01

    Noun compounds, consisting of two nouns (the head and the modifier) that are combined into a single concept, differ in terms of their plausibility: school bus is a more plausible compound than saddle olive. The present study investigates which factors influence the plausibility of attested and novel noun compounds. Distributional Semantic Models (DSMs) are used to obtain formal (vector) representations of word meanings, and compositional methods in DSMs are employed to obtain such representations for noun compounds. From these representations, different plausibility measures are computed. Three of those measures contribute in predicting the plausibility of noun compounds: The relatedness between the meaning of the head noun and the compound (Head Proximity), the relatedness between the meaning of modifier noun and the compound (Modifier Proximity), and the similarity between the head noun and the modifier noun (Constituent Similarity). We find non-linear interactions between Head Proximity and Modifier Proximity, as well as between Modifier Proximity and Constituent Similarity. Furthermore, Constituent Similarity interacts non-linearly with the familiarity with the compound. These results suggest that a compound is perceived as more plausible if it can be categorized as an instance of the category denoted by the head noun, if the contribution of the modifier to the compound meaning is clear but not redundant, and if the constituents are sufficiently similar in cases where this contribution is not clear. Furthermore, compounds are perceived to be more plausible if they are more familiar, but mostly for cases where the relation between the constituents is less clear. PMID:27732599

  16. 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.

  17. Predicting the integration of overlapping memories by decoding mnemonic processing states during learning.

    PubMed

    Richter, Franziska R; Chanales, Avi J H; Kuhl, Brice A

    2016-01-01

    The hippocampal memory system is thought to alternate between two opposing processing states: encoding and retrieval. When present experience overlaps with past experience, this creates a potential tradeoff between encoding the present and retrieving the past. This tradeoff may be resolved by memory integration-that is, by forming a mnemonic representation that links present experience with overlapping past experience. Here, we used fMRI decoding analyses to predict when - and establish how - past and present experiences become integrated in memory. In an initial experiment, we alternately instructed subjects to adopt encoding, retrieval or integration states during overlapping learning. We then trained across-subject pattern classifiers to 'read out' the instructed processing states from fMRI activity patterns. We show that an integration state was clearly dissociable from encoding or retrieval states. Moreover, trial-by-trial fluctuations in decoded evidence for an integration state during learning reliably predicted behavioral expressions of successful memory integration. Strikingly, the decoding algorithm also successfully predicted specific instances of spontaneous memory integration in an entirely independent sample of subjects for whom processing state instructions were not administered. Finally, we show that medial prefrontal cortex and hippocampus differentially contribute to encoding, retrieval, and integration states: whereas hippocampus signals the tradeoff between encoding vs. retrieval states, medial prefrontal cortex actively represents past experience in relation to new learning.

  18. 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…

  19. State institutions and social identity: National representation in soldiers' and civilians' interview talk concerning military service.

    PubMed

    Gibson, Stephen; Condor, Susan

    2009-06-01

    Theory and research deriving from social identity or self-categorization perspectives often starts out with the presumption that social actors necessarily view societal objects such as nations or states as human categories. However, recent work suggests that this may be only one of a number of forms that societal representation may take. For example, nations may be understood variously as peoples, places, or institutions. This paper presents findings from a qualitative interview study conducted in England, in which soldiers and civilians talked about nationhood in relation to military service. Analysis indicated that, in this context, speakers were often inclined to use the terms 'Britain', 'nation', and 'country' as references to a political institution as opposed to a category of people. In addition, there were systematic differences between the ways in which the two samples construed their nation in institutional terms. The civilians were inclined to treat military service as a matter of obedience to the dictates of the Government of the day. In contrast, the soldiers were more inclined to frame military service as a matter of loyalty to state as symbolically instantiated in the body of the sovereign. Implications for work adopting a social identity perspective are discussed.

  20. State institutions and social identity: National representation in soldiers' and civilians' interview talk concerning military service.

    PubMed

    Gibson, Stephen; Condor, Susan

    2009-06-01

    Theory and research deriving from social identity or self-categorization perspectives often starts out with the presumption that social actors necessarily view societal objects such as nations or states as human categories. However, recent work suggests that this may be only one of a number of forms that societal representation may take. For example, nations may be understood variously as peoples, places, or institutions. This paper presents findings from a qualitative interview study conducted in England, in which soldiers and civilians talked about nationhood in relation to military service. Analysis indicated that, in this context, speakers were often inclined to use the terms 'Britain', 'nation', and 'country' as references to a political institution as opposed to a category of people. In addition, there were systematic differences between the ways in which the two samples construed their nation in institutional terms. The civilians were inclined to treat military service as a matter of obedience to the dictates of the Government of the day. In contrast, the soldiers were more inclined to frame military service as a matter of loyalty to state as symbolically instantiated in the body of the sovereign. Implications for work adopting a social identity perspective are discussed. PMID:18793493

  1. Multiple neural states of representation in short-term memory? It's a matter of attention.

    PubMed

    Larocque, Joshua J; Lewis-Peacock, Jarrod A; Postle, Bradley R

    2014-01-01

    Short-term memory (STM) refers to the capacity-limited retention of information over a brief period of time, and working memory (WM) refers to the manipulation and use of that information to guide behavior. In recent years it has become apparent that STM and WM interact and overlap with other cognitive processes, including attention (the selection of a subset of information for further processing) and long-term memory (LTM-the encoding and retention of an effectively unlimited amount of information for a much longer period of time). Broadly speaking, there have been two classes of memory models: systems models, which posit distinct stores for STM and LTM (Atkinson and Shiffrin, 1968; Baddeley and Hitch, 1974); and state-based models, which posit a common store with different activation states corresponding to STM and LTM (Cowan, 1995; McElree, 1996; Oberauer, 2002). In this paper, we will focus on state-based accounts of STM. First, we will consider several theoretical models that postulate, based on considerable behavioral evidence, that information in STM can exist in multiple representational states. We will then consider how neural data from recent studies of STM can inform and constrain these theoretical models. In the process we will highlight the inferential advantage of multivariate, information-based analyses of neuroimaging data (fMRI and electroencephalography (EEG)) over conventional activation-based analysis approaches (Postle, in press). We will conclude by addressing lingering questions regarding the fractionation of STM, highlighting differences between the attention to information vs. the retention of information during brief memory delays.

  2. Conjoint control of hippocampal place cell firing by two visual stimuli. Ii. A vector-field theory that predicts modifications of the representation of the environment.

    PubMed

    Fenton, A A; Csizmadia, G; Muller, R U

    2000-08-01

    Changing the angular separation between two visual stimuli attached to the wall of a recording cylinder causes the firing fields of place cells to move relative to each other, as though the representation of the floor undergoes a topological distortion. The displacement of the firing field center of each cell is a vector whose length is equal to the linear displacement and whose angle indicates the direction that the field center moves in the environment. Based on the observation that neighboring fields move in similar ways, whereas widely separated fields tend to move relative to each other, we develop an empirical vector-field model that accounts for the stated effects of changing the card separation. We then go on to show that the same vector-field equation predicts additional aspects of the experimental results. In one example, we demonstrate that place cell firing fields undergo distortions of shape after the card separation is changed, as though different parts of the same field are affected by the stimulus constellation in the same fashion as fields at different locations. We conclude that the vector-field formalism reflects the organization of the place-cell representation of the environment for the current case, and through suitable modification may be very useful for describing motions of firing patterns induced by a wide variety of stimulus manipulations.

  3. Efficient representations of continuum states for photoionization processes from atomic and molecular targets

    NASA Astrophysics Data System (ADS)

    Yip, Frank L.

    The investigation of single and double photoionization effects in small atoms and molecules provides a means to probe fundamental quantum mechanical phenomena concerning electron correlation and interference effects. To consider these concepts accurately from first principles requires the construction of the exact final continuum states of a many body problem in atomic double photoionization and of the complicated continuum states in molecular single photoionization. Methods designed for incorporating exterior complex scaling (ECS) have proven very successful towards accomplishing these goals, providing a rigorous framework for describing continuum states involving any number of outgoing electrons with numerical exactness. Furthermore, such methods render solutions that can be interrogated to extract the full richness of information about the photoionization process from the wave function. This work aims to demonstrate the use of exterior complex scaling by first exactly solving the three-body breakup problem of the atomic hydride anion. H-- is the simplest atomic system and is most sensitive to electron correlation effects. The application of ECS with an efficient finite-element discrete variable representation proves quite capable and well-suited for this atomic Coulomb breakup problem. The evolution of this framework to treat molecular problems efficiently with exactness is furthered by the design of a hybrid basis method. The incorporation of analytic Gaussian basis sets ubiquitous in bound state molecular descriptions seems natural for considering molecular continuum states. The hybrid method is described in full detail and applied to completely describe photoionization of molecular H+2 and Li+2 . Photoionization of simple molecular systems offers significantly more complexity in the resulting angular distributions of the ejected electron as the target geometry becomes less atomic-like, i.e., as the internuclear separation increases. In this regard

  4. 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

  5. Comment on the role of thermodynamic representations in the study of fluids in far from equilibrium steady states

    NASA Astrophysics Data System (ADS)

    Llebot, J. E.; Tremblay, A.-M. S.

    1986-03-01

    It is shown that calculations of fluctuations in fluids driven into a stationary state by a temperature gradient are independent of the thermodynamic representation even to nonlinear order in the temperature gradient. The contrast between this result and the conjecture of Garibay-Jiménez and García-Colin, Physica 130A (1985) 616, is clarified.

  6. 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.…

  7. 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)

  8. C-terminal motif prediction in eukaryotic proteomes using comparative genomics and statistical over-representation across protein families

    PubMed Central

    Austin, Ryan S; Provart, Nicholas J; Cutler, Sean R

    2007-01-01

    Background The carboxy termini of proteins are a frequent site of activity for a variety of biologically important functions, ranging from post-translational modification to protein targeting. Several short peptide motifs involved in protein sorting roles and dependent upon their proximity to the C-terminus for proper function have already been characterized. As a limited number of such motifs have been identified, the potential exists for genome-wide statistical analysis and comparative genomics to reveal novel peptide signatures functioning in a C-terminal dependent manner. We have applied a novel methodology to the prediction of C-terminal-anchored peptide motifs involving a simple z-statistic and several techniques for improving the signal-to-noise ratio. Results We examined the statistical over-representation of position-specific C-terminal tripeptides in 7 eukaryotic proteomes. Sequence randomization models and simple-sequence masking were applied to the successful reduction of background noise. Similarly, as C-terminal homology among members of large protein families may artificially inflate tripeptide counts in an irrelevant and obfuscating manner, gene-family clustering was performed prior to the analysis in order to assess tripeptide over-representation across protein families as opposed to across all proteins. Finally, comparative genomics was used to identify tripeptides significantly occurring in multiple species. This approach has been able to predict, to our knowledge, all C-terminally anchored targeting motifs present in the literature. These include the PTS1 peroxisomal targeting signal (SKL*), the ER-retention signal (K/HDEL*), the ER-retrieval signal for membrane bound proteins (KKxx*), the prenylation signal (CC*) and the CaaX box prenylation motif. In addition to a high statistical over-representation of these known motifs, a collection of significant tripeptides with a high propensity for biological function exists between species, among

  9. Prediction of Activity Cliffs Using Condensed Graphs of Reaction Representations, Descriptor Recombination, Support Vector Machine Classification, and Support Vector Regression.

    PubMed

    Horvath, Dragos; Marcou, Gilles; Varnek, Alexandre; Kayastha, Shilva; de la Vega de León, Antonio; Bajorath, Jürgen

    2016-09-26

    Activity cliffs (ACs) are formed by structurally similar compounds with large differences in activity. Accordingly, ACs are of high interest for the exploration of structure-activity relationships (SARs). ACs reveal small chemical modifications that result in profound biological effects. The ability to foresee such small chemical changes with significant biological consequences would represent a major advance for drug design. Nevertheless, only few attempts have been made so far to predict whether a pair of analogues is likely to represent an AC-and even fewer went further to quantitatively predict how "deep" a cliff might be. This might be due to the fact that such predictions must focus on compound pairs. Matched molecular pairs (MMPs), defined as pairs of structural analogs that are only distinguished by a chemical modification at a single site, are a preferred representation of ACs. Herein, we report new strategies for AC prediction that are based upon two different approaches: (i) condensed graphs of reactions, which were originally introduced for modeling of chemical reactions and were here adapted to encode MMPs, and, (ii) plain descriptor recombination-a strategy used for quantitative structure-property relationship (QSPR) modeling of nonadditive mixtures (MQSPR). By applying these concepts, ACs were encoded as single descriptor vectors used as input for support vector machine (SVM) classification and support vector regression (SVR), yielding accurate predictions of AC status (i.e., cliff vs noncliff) and potency differences, respectively. The latter were predicted in a compound order-sensitive manner returning the signed value of expected potency differences between AC compounds. PMID:27564682

  10. Prediction of Activity Cliffs Using Condensed Graphs of Reaction Representations, Descriptor Recombination, Support Vector Machine Classification, and Support Vector Regression.

    PubMed

    Horvath, Dragos; Marcou, Gilles; Varnek, Alexandre; Kayastha, Shilva; de la Vega de León, Antonio; Bajorath, Jürgen

    2016-09-26

    Activity cliffs (ACs) are formed by structurally similar compounds with large differences in activity. Accordingly, ACs are of high interest for the exploration of structure-activity relationships (SARs). ACs reveal small chemical modifications that result in profound biological effects. The ability to foresee such small chemical changes with significant biological consequences would represent a major advance for drug design. Nevertheless, only few attempts have been made so far to predict whether a pair of analogues is likely to represent an AC-and even fewer went further to quantitatively predict how "deep" a cliff might be. This might be due to the fact that such predictions must focus on compound pairs. Matched molecular pairs (MMPs), defined as pairs of structural analogs that are only distinguished by a chemical modification at a single site, are a preferred representation of ACs. Herein, we report new strategies for AC prediction that are based upon two different approaches: (i) condensed graphs of reactions, which were originally introduced for modeling of chemical reactions and were here adapted to encode MMPs, and, (ii) plain descriptor recombination-a strategy used for quantitative structure-property relationship (QSPR) modeling of nonadditive mixtures (MQSPR). By applying these concepts, ACs were encoded as single descriptor vectors used as input for support vector machine (SVM) classification and support vector regression (SVR), yielding accurate predictions of AC status (i.e., cliff vs noncliff) and potency differences, respectively. The latter were predicted in a compound order-sensitive manner returning the signed value of expected potency differences between AC compounds.

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

    NASA Astrophysics Data System (ADS)

    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.

  12. 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

  13. 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.

  14. Predicting cognitive state from eye movements.

    PubMed

    Henderson, John M; Shinkareva, Svetlana V; Wang, Jing; Luke, Steven G; Olejarczyk, Jenn

    2013-01-01

    In human vision, acuity and color sensitivity are greatest at the center of fixation and fall off rapidly as visual eccentricity increases. Humans exploit the high resolution of central vision by actively moving their eyes three to four times each second. Here we demonstrate that it is possible to classify the task that a person is engaged in from their eye movements using multivariate pattern classification. The results have important theoretical implications for computational and neural models of eye movement control. They also have important practical implications for using passively recorded eye movements to infer the cognitive state of a viewer, information that can be used as input for intelligent human-computer interfaces and related applications.

  15. 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.

  16. 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

  17. 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.

  18. 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

  19. 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

  20. Dissociable neural representations of reinforcement and belief prediction errors underlie strategic learning

    PubMed Central

    Zhu, Lusha; Mathewson, Kyle E.; Hsu, Ming

    2012-01-01

    Decision-making in the presence of other competitive intelligent agents is fundamental for social and economic behavior. Such decisions require agents to behave strategically, where in addition to learning about the rewards and punishments available in the environment, they also need to anticipate and respond to actions of others competing for the same rewards. However, whereas we know much about strategic learning at both theoretical and behavioral levels, we know relatively little about the underlying neural mechanisms. Here, we show using a multi-strategy competitive learning paradigm that strategic choices can be characterized by extending the reinforcement learning (RL) framework to incorporate agents’ beliefs about the actions of their opponents. Furthermore, using this characterization to generate putative internal values, we used model-based functional magnetic resonance imaging to investigate neural computations underlying strategic learning. We found that the distinct notions of prediction errors derived from our computational model are processed in a partially overlapping but distinct set of brain regions. Specifically, we found that the RL prediction error was correlated with activity in the ventral striatum. In contrast, activity in the ventral striatum, as well as the rostral anterior cingulate (rACC), was correlated with a previously uncharacterized belief-based prediction error. Furthermore, activity in rACC reflected individual differences in degree of engagement in belief learning. These results suggest a model of strategic behavior where learning arises from interaction of dissociable reinforcement and belief-based inputs. PMID:22307594

  1. The seasonal predictability of blocking frequency in two seasonal prediction systems (CMCC, Met-Office) and the associated representation of low-frequency variability.

    NASA Astrophysics Data System (ADS)

    Athanasiadis, Panos; Gualdi, Silvio; Scaife, Adam A.; Bellucci, Alessio; Hermanson, Leon; MacLachlan, Craig; Arribas, Alberto; Materia, Stefano; Borelli, Andrea

    2014-05-01

    Low-frequency variability is a fundamental component of the atmospheric circulation. Extratropical teleconnections, the occurrence of blocking and the slow modulation of the jet streams and storm tracks are all different aspects of low-frequency variability. Part of the latter is attributed to the chaotic nature of the atmosphere and is inherently unpredictable. On the other hand, primarily as a response to boundary forcings, tropospheric low-frequency variability includes components that are potentially predictable. Seasonal forecasting faces the difficult task of predicting these components. Particularly referring to the extratropics, the current generation of seasonal forecasting systems seem to be approaching this target by realistically initializing most components of the climate system, using higher resolution and utilizing large ensemble sizes. Two seasonal prediction systems (Met-Office GloSea and CMCC-SPS-v1.5) are analyzed in terms of their representation of different aspects of extratropical low-frequency variability. The current operational Met-Office system achieves unprecedented high scores in predicting the winter-mean phase of the North Atlantic Oscillation (NAO, corr. 0.74 at 500 hPa) and the Pacific-N. American pattern (PNA, corr. 0.82). The CMCC system, considering its small ensemble size and course resolution, also achieves good scores (0.42 for NAO, 0.51 for PNA). Despite these positive features, both models suffer from biases in low-frequency variance, particularly in the N. Atlantic. Consequently, it is found that their intrinsic variability patterns (sectoral EOFs) differ significantly from the observed, and the known teleconnections are underrepresented. Regarding the representation of N. hemisphere blocking, after bias correction both systems exhibit a realistic climatology of blocking frequency. In this assessment, instantaneous blocking and large-scale persistent blocking events are identified using daily geopotential height fields at

  2. 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

  3. 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

  4. 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

  5. Prediction of thermal-stress and deformations due to phase change in solidifying objects via flux/stress based finite element representations

    NASA Technical Reports Server (NTRS)

    Tamma, K. K.; Namburu, R. R.

    1989-01-01

    The paper presents numerical simulations for the prediction of thermal-stress and deformation fields resulting from phase change in solidifying bodies employing new finite element representations. The formulations herein demonstrated provide different perspectives and physical interpretation for the modeling/analysis of thermo-mechanical problems and possess several inherent advantages. In comparison to traditional approaches for solving similar problems, the paper employs new flux/stress based representations to enhance the overall effectiveness. Comparative numerical applications validate applicability of the formulations for predicting the temperature induced deformations and stresses resulting from effects due to phase change.

  6. 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

  7. A predictive study of voting behavior in a representation election using union instrumentality and work perceptions.

    PubMed

    DeCoths, T A; LeLouarn, J Y

    1981-02-01

    A literature-based model of the unionization process is presented. The process is defined in terms of instrumentality perceptions, behavioral intent, and actual behavior components. The primary determinant of the process is shown to be the instrumentality perceptions of the potential members. The model is tested via discriminant analysis and step-wise regression in a sample of hospital nurses. The results suggest the overriding importance of instrumentality perceptions in the determination of voting behavior. In excess of 75% of the votes were accurately predicted from knowledge of the respondent's instrumentality perceptions alone. Several avenues for future research were suggested, including an expanded view of personal characteristics and extension of expectancy theory to employee voting behavior.

  8. 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.

  9. Representation of ecological systems within the protected areas network of the continental United States

    USGS Publications Warehouse

    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.

  10. 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…

  11. 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

  12. Conditions for predicting quasistationary states by rearrangement formula

    NASA Astrophysics Data System (ADS)

    Yamaguchi, Yoshiyuki Y.; Ogawa, Shun

    2015-10-01

    Predicting the long-lasting quasistationary state for a given initial state is one of central issues in Hamiltonian systems having long-range interaction. A recently proposed method is based on the Vlasov description and uniformly redistributes the initial distribution along contours of the asymptotic effective Hamiltonian, which is defined by the obtained quasistationary state and is determined self-consistently. The method, to which we refer as the rearrangement formula, was suggested to give precise prediction under limited situations. Restricting initial states consisting of a spatially homogeneous part and small perturbation, we numerically reveal two conditions that the rearrangement formula prefers: One is a no Landau damping condition for the unperturbed homogeneous part, and the other comes from the Casimir invariants. Mechanisms of these conditions are discussed. Clarifying these conditions, we validate to use the rearrangement formula as the response theory for an external field, and we shed light on improving the theory as a nonequilibrium statistical mechanics.

  13. 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.

  14. 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.…

  15. 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.

  16. Infinitive Operator-Sum Representation for Damping in a Squeezed Heat Reservoir via the Thermo Entangled State Approach

    NASA Astrophysics Data System (ADS)

    Wu, Wei-Feng

    2016-08-01

    Using the thermo entangled state approach, we successfully solve the master equation of a damped harmonic oscillator affected by a linear resonance force in a squeezed heat reservoir, and obtain the analytical evolution formula for the density operator in the infinitive Kraus operator-sum representation. Interestingly, the Kraus operators M l,m,n,r and M_{l,m,n,r}^{dag } are not Hermite conjugate, but they are still trace-preserving quantum operations because of the normalization condition. We also investigate the evolution for an initial coherent state for damping in a squeezed heat reservoir, which shows that the initial coherent state decays to a complex mixed state as a result of damping and thermal noise.

  17. 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

  18. Cardiovascular indices of challenge and threat states predict competitive performance.

    PubMed

    Turner, Martin J; Jones, Marc V; Sheffield, David; Cross, Sophie L

    2012-10-01

    Cardiovascular (CV) reactivity is proposed by both the Biopsychosocial Model and the Theory of Challenge and Threat States in Athletes to predict competitive performance. The association between CV reactivity and competitive performance was examined in cognitive (Study 1) and motor (Study 2) tasks. In Study 1, 25 participants (9 female) completed a modified Stroop Test, and in Study 2, 21 female netballers completed a netball shooting task, under competition. Measures of CV reactivity, self-report measures of self-efficacy, control, achievement-goals and emotions along with baseline and competitive task performance were taken. CV reactivity indicative of a challenge state predicted superior performance in both tasks compared to CV reactivity indicative of a threat state. In both studies the purported relationships between CV reactivity and the psychological and emotional responses were weak or absent. The mechanisms for the observed association between CV reactivity and task performance are discussed alongside implications of the findings for future research and practice.

  19. 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.

  20. A detailed representation of electrostatic energy in prediction of sequence and pH dependence of protein stability.

    PubMed

    Dudek, Michael J

    2014-10-01

    A molecular mechanics model, previously validated in applications to structure prediction, is shown to reproduce experiment in predictions of protein ionization state, and in predictions of sequence and pH dependence of protein stability. Over a large dataset, 1876 values of ΔΔG of folding, the RMSD is 1.34 kcal/mol. Using an alternative measure of accuracy, either the sign of the calculated ΔΔG agrees with experiment or the absolute value of the deviation is less than 1.0 kcal/mol, 1660 of 1876 data points (88.5%) pass the condition. Relative to models used previously in computer-aided protein design, the concept, we propose, most responsible for the performance of our model, and for the extensibility to non-neutral values of pH, is the treatment of electrostatic energy. The electronic structure of the protein is modeled using distributed atomic multipoles. The structured liquid state of the solvent is modeled using a dielectric continuum. A modification to the energetics of the reaction field, induced by the protein in the dielectric continuum, attempts to account for preformed multipoles of solvent water molecules and ions. An adjustable weight (with optimal value.141) applied to the total vacuum energy accounts implicitly for electronic polarization. A threshold distance, beyond which pairwise atomic interactions are neglected, is not used. In searches through subspaces of sequences and conformations, efficiency remains acceptable for useful applications.

  1. 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......

  2. 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......

  3. 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......

  4. 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......

  5. Representations of fuzzy torus

    NASA Astrophysics Data System (ADS)

    Aizawa, N.; Chakrabarti, R.

    2008-08-01

    A classification of Hermitian representations for the recently introduced fuzzy torus algebra is presented. This is carried out by regarding the fuzzy torus algebra as a q-deformation of parafermion. In addition to the known representations, new representations of both finite and infinite dimension are found. Using the infinite dimensional representation, coherent state for the fuzzy torus is constructed. Dirac operator on commutative torus is also discussed.

  6. 5 CFR 2641.201 - Permanent restriction on any former employee's representations to United States concerning...

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... appearance before an employee of the United States on behalf of any other person in connection with a... who is: (1) Acting on behalf of the United States. See § 2641.301(a). (2) Acting as an elected State... or direction, to an employee of the United States, whether orally, in written correspondence,...

  7. 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

  8. 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.

  9. Predicting differences in gene regulatory systems by state space models.

    PubMed

    Yamaguchi, Rui; Imoto, Seiya; Yamauchi, Mai; Nagasaki, Masao; Yoshida, Ryo; Shimamura, Teppei; Hatanaka, Yosuke; Ueno, Kazuko; Higuchi, Tomoyuki; Gotoh, Noriko; Miyano, Satoru

    2008-01-01

    We propose a statistical strategy to predict differentially regulated genes of case and control samples from time-course gene expression data by leveraging unpredictability of the expression patterns from the underlying regulatory system inferred by a state space model. The proposed method can screen out genes that show different patterns but generated by the same regulations in both samples, since these patterns can be predicted by the same model. Our strategy consists of three steps. Firstly, a gene regulatory system is inferred from the control data by a state space model. Then the obtained model for the underlying regulatory system of the control sample is used to predict the case data. Finally, by assessing the significance of the difference between case and predicted-case time-course data of each gene, we are able to detect the unpredictable genes that are the candidate as the key differences between the regulatory systems of case and control cells. We illustrate the whole process of the strategy by an actual example, where human small airway epithelial cell gene regulatory systems were generated from novel time courses of gene expressions following treatment with(case)/without(control) the drug gefitinib, an inhibitor for the epidermal growth factor receptor tyrosine kinase. Finally, in gefitinib response data we succeeded in finding unpredictable genes that are candidates of the specific targets of gefitinib. We also discussed differences in regulatory systems for the unpredictable genes. The proposed method would be a promising tool for identifying biomarkers and drug target genes.

  10. Multi-Sensor Based State Prediction for Personal Mobility Vehicles

    PubMed Central

    Gupta, Pankaj; Umata, Ichiro; Watanabe, Atsushi; Even, Jani; Suyama, Takayuki; Ishii, Shin

    2016-01-01

    This paper presents a study on multi-modal human emotional state detection while riding a powered wheelchair (PMV; Personal Mobility Vehicle) in an indoor labyrinth-like environment. The study reports findings on the habituation of human stress response during self-driving. In addition, the effects of “loss of controllability”, change in the role of the driver to a passenger, are investigated via an autonomous driving modality. The multi-modal emotional state detector sensing framework consists of four sensing devices: electroencephalograph (EEG), heart inter-beat interval (IBI), galvanic skin response (GSR) and stressor level lever (in the case of autonomous riding). Physiological emotional state measurement characteristics are organized by time-scale, in terms of capturing slower changes (long-term) and quicker changes from moment-to-moment. Experimental results with fifteen participants regarding subjective emotional state reports and commercial software measurements validated the proposed emotional state detector. Short-term GSR and heart signal characterizations captured moment-to-moment emotional state during autonomous riding (Spearman correlation; ρ = 0.6, p < 0.001). Short-term GSR and EEG characterizations reliably captured moment-to-moment emotional state during self-driving (Classification accuracy; 69.7). Finally, long-term GSR and heart characterizations were confirmed to reliably capture slow changes during autonomous riding and also of emotional state during participant resting state. The purpose of this study and the exploration of various algorithms and sensors in a structured framework is to provide a comprehensive background for multi-modal emotional state prediction experiments and/or applications. Additional discussion regarding the feasibility and utility of the possibilities of these concepts are given. PMID:27732589

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

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... to judicial proceedings), and under title 28 of the United States Code (relating to the judiciary and... 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......

  12. 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…

  13. 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…

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

    PubMed Central

    Ito, Makoto; Doya, Kenji

    2015-01-01

    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

  15. 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

  16. 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.

  17. 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

  18. 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

  19. Anonymous predictive testing for Huntington's disease in the United States.

    PubMed

    Visintainer, C L; Matthias-Hagen, V; Nance, M A

    2001-01-01

    The widespread use of a predictive genetic test for Huntington's disease (HD) since 1993 has brought to the forefront issues regarding genetic privacy. Although the possibility of anonymous genetic testing has been discussed, its use in the United States has not been described previously. We review the experiences of 11 genetics specialists with anonymous predictive testing for HD. We found that more men than women requested anonymous testing, for reasons that more often related to personal privacy than to insurance or discrimination concerns. A number of approaches to anonymity were used, and genetics specialists varied in the degree to which they were comfortable with the process. A number of legal, medical, and practical questions are raised, which will require resolution if anonymous testing is to be performed with a greater frequency in the future.

  20. 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

    ... Office also has the authority to suspend or exclude from practice before the Office any practitioner who... 50 FR 5158 (February 6, 1985). Since that time, the vast majority of State bars in the United States... Responsibility are intended to bring standards of ethical practice before the Office into closer conformity...

  1. BME representation of particulate matter distributions in the state of California on the basis of uncertain measurements

    NASA Astrophysics Data System (ADS)

    Christakos, George; Serre, Marc L.; Kovitz, Jordan L.

    2001-05-01

    Maps of temporal and spatial values of annual averages of daily particulate matter (PM10) concentrations were generated throughout the state of California using uncertain forms of physical data. The PM10 estimates were derived in an integrated space/time domain using the Bayesian maximum entropy (BME) mapping approach of modern spatiotemporal geostatistics. The approach possesses some interesting features which allow an insightful analysis of the PM10 space/time distribution. A complete stochastic characterization of the pollutant involves the probability density function of the PM10 map, which is the result of a rigorous knowledge-integration process. This process is considerably flexible, it can account for several physical knowledge bases and sources of uncertainty, and it may involve Bayesian or material conditionalization rules. Taking advantage of BME's flexibility, PM10 estimates were chosen which offered an appropriate representation of the real distribution in space/time, and a meaningful assessment of the representation accuracy was derived. Depending on the space scales/timescales considered, the PM10 distributions depicted considerable levels of variability, which may be associated with topographic features, climatic changes, seasonal patterns, and random fluctuations. The importance of integrating soft information available at surrounding sites as well as at the estimation points themselves was discussed. Comparisons were designed which demonstrated the usefulness of the BME-based maps to represent PM10 distributions in space/time. Areas were identified where the annual PM10 geometric mean reached or exceeded the California standard, which is valuable information for regulatory purposes.

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

    PubMed

    Nielsen, Karina; Cleal, Bryan

    2010-04-01

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

  3. 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.

  4. Pfaffian statistics through adiabatic transport in the 1D coherent state representation.

    PubMed

    Seidel, Alexander

    2008-11-01

    Recent work has shown that the low energy sector of certain quantum Hall states is adiabatically connected to simple charge-density-wave patterns that appear, e.g., when the system is deformed into a thin torus. Here it is shown that the patterns emerging in this limit already determine the non-Abelian statistics of the nu=1 Moore-Read state. Aside from the knowledge of these patterns, the method only relies on the principle of adiabatic continuity, the effectively noncommutative geometry in a strong magnetic field, and topological as well as locality arguments.

  5. The Representation of Migrant Students in Special Education in the State of Texas

    ERIC Educational Resources Information Center

    Razo, Nancy Pena; Ochoa, Salvador Hector

    2006-01-01

    Migrant children are considered one of the most at-risk populations in the United States. They face multiple obstacles of poverty, poor health, mobility, and limited English proficiency, which contributes to the difficulties that migrant children may encounter in the educational system. Limited research has been conducted regarding migrant…

  6. 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.

  7. 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...

  8. 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…

  9. 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

  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. 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.

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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

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

    PubMed

    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

  18. 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

  19. Identifying state-dependent model error in numerical weather prediction

    NASA Astrophysics Data System (ADS)

    Moskaitis, J.; Hansen, J.; Toth, Z.; Zhu, Y.

    2003-04-01

    Model forecasts of complex systems such as the atmosphere lose predictive skill because of two different sources of error: initial conditions error and model error. While much study has been done to determine the nature and consequences of initial conditions error in operational forecast models, relatively little has been done to identify the source of model error and to quantify the effects of model error on forecasts. Here, we attempt to "disentangle" model error from initial conditions error by applying a diagnostic tool in a simple model framework to identify poor forecasts for which model error is likely responsible. The diagnostic is based on the premise that for a perfect ensemble forecast, verification should fall outside the range of ensemble forecast states only a small percentage of the time, according to the size of the ensemble. Identifying these outlier verifications and comparing the statistics of their occurrence to those of a perfect ensemble can tell us about the role of model error in a quantitative, state-dependent manner. The same diagnostic is applied to operational NWP models to quantify the role of model error in poor forecasts (see companion paper by Toth et al.). From these results, we can infer the atmospheric processes the model cannot adequately simulate.

  20. 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.

  1. Correction of Distortion in Flattened Representations of the Cortical Surface Allows Prediction of V1-V3 Functional Organization from Anatomy

    PubMed Central

    Benson, Noah C.; Butt, Omar H.; Brainard, David H.; Aguirre, Geoffrey K.

    2014-01-01

    Several domains of neuroscience offer map-like models that link location on the cortical surface to properties of sensory representation. Within cortical visual areas V1, V2, and V3, algebraic transformations can relate position in the visual field to the retinotopic representation on the flattened cortical sheet. A limit to the practical application of this structure-function model is that the cortex, while topologically a two-dimensional surface, is curved. Flattening of the curved surface to a plane unavoidably introduces local geometric distortions that are not accounted for in idealized models. Here, we show that this limitation is overcome by correcting the geometric distortion induced by cortical flattening. We use a mass-spring-damper simulation to create a registration between functional MRI retinotopic mapping data of visual areas V1, V2, and V3 and an algebraic model of retinotopy. This registration is then applied to the flattened cortical surface anatomy to create an anatomical template that is linked to the algebraic retinotopic model. This registered cortical template can be used to accurately predict the location and retinotopic organization of these early visual areas from cortical anatomy alone. Moreover, we show that prediction accuracy remains when extrapolating beyond the range of data used to inform the model, indicating that the registration reflects the retinotopic organization of visual cortex. We provide code for the mass-spring-damper technique, which has general utility for the registration of cortical structure and function beyond the visual cortex. PMID:24676149

  2. 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…

  3. 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…

  4. 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)

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

    PubMed

    Andersson, Jesper L R; Sotiropoulos, Stamatios N

    2015-11-15

    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.

  6. 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

  7. Predicting red wolf release success in the southeastern United States

    USGS Publications Warehouse

    van Manen, Frank T.; Crawford, Barron A.; Clark, Joseph D.

    2000-01-01

    Although the red wolf (Canis rufus) was once found throughout the southeastern United States, indiscriminate killing and habitat destruction reduced its range to a small section of coastal Texas and Louisiana. Wolves trapped from 1973 to 1980 were taken to establish a captive breeding program that was used to repatriate 2 mainland and 3 island red wolf populations. We collected data from 320 red wolf releases in these areas and classified each as a success or failure based on survival and reproductive criteria, and whether recaptures were necessary to resolve conflicts with humans. We evaluated the relations between release success and conditions at the release sites, characteristics of released wolves, and release procedures. Although <44% of the variation in release success was explained, model performance based on jackknife tests indicated a 72-80% correct prediction rate for the 4 operational models we developed. The models indicated that success was associated with human influences on the landscape and the level of wolf habituation to humans prior to release. We applied the models to 31 prospective areas for wolf repatriation and calculated an index of release success for each area. Decision-makers can use these models to objectively rank prospective release areas and compare strengths and weaknesses of each.

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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

  14. Validity of quasi-steady-state and transfer-function representations for input-output relation in a Michaelis-Menten reaction.

    PubMed

    Sakamoto, N

    1986-08-01

    In relation to the input-output characteristics of enzymatic reactions in the cellular metabolism and biochemical reactors, the validity of the quasi-steady-state and transfer-function representations of reaction velocity has been examined for a basic Michaelis-Menten reaction employing computer simulation, that is, numerical integration of the rate equation. The well-known S-v relationship (relationship between substrate concentration and reaction velocity)derived on the quasi-steady-state assumption is found to be in general a good approximation to the actual velocity throughout the temporal progress of the reaction. The validity of the approximation depends on a ratio of the Michaelis constant to the total enzyme concentration in the reaction system rather than on the individual rate constants. A transfer-function representation is derived on assuming an exponential change in the reaction velocity for the indicial response to the substrate influx rate. The representation has a wider valid region with a decrease in influx rate than with an increase in the influx rate. The validity is most dependent on a ratio of total enzyme concentration to the steady-state concentration of the substrate. The analysis of the linear sensitivity of the reaction velocity to rate constants reveals that the characteristics of these valid representations in systems analysis change according to the phase of the reaction.

  15. 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.

  16. 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

  17. Defying Predictions, State Trends Prove Mixed on Schools Making NCLB Targets

    ERIC Educational Resources Information Center

    Olson, Lynn

    2005-01-01

    Many people predicted that 2005 would be the year that schools nationwide began feeling the bite of the federal No Child Left Behind Act, as states ratcheted up their performance targets and more schools failed to meet those benchmarks. But such dire predictions are not playing out uniformly across the states. Of the 33 states and the District of…

  18. 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

  19. 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

  20. Fock Representation

    NASA Astrophysics Data System (ADS)

    Strocchi, Franco

    The general lesson from the GNS theorem is that a state on the algebra of observables, namely a set of expectations, defines a realization of the system in terms of a Hilbert space of states with a reference vector which represents as a cyclic vector (so that all the other vectors of can be obtained by applying the observables to PSgrOHgr). In this sense, a state identifies the family of states related to it by observables, equivalently accessible from it by means of physically realizable operations. Thus, one may say that mathcal{H}_{Omega} describes a closed world, or phase, to which OHgr belongs. An interesting physical and mathematical question is how many closed worlds or phases are associated to a quantum system. In the mathematical language this amounts to investigating how many inequivalent (physically acceptable) representations of the observable algebra which defines the system exist.

  1. 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.

  2. 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

  3. 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.

  4. 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…

  5. 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…

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

    DOE PAGES

    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

  7. 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.

  8. 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

  9. 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.

  10. The state of the art of flood forecasting - Hydrological Ensemble Prediction Systems

    NASA Astrophysics Data System (ADS)

    Thielen-Del Pozo, J.; Pappenberger, F.; Salamon, P.; Bogner, K.; Burek, P.; de Roo, A.

    2010-09-01

    Flood forecasting systems form a key part of ‘preparedness' strategies for disastrous floods and provide hydrological services, civil protection authorities and the public with information of upcoming events. Provided the warning leadtime is sufficiently long, adequate preparatory actions can be taken to efficiently reduce the impacts of the flooding. Because of the specific characteristics of each catchment, varying data availability and end-user demands, the design of the best flood forecasting system may differ from catchment to catchment. However, despite the differences in concept and data needs, there is one underlying issue that spans across all systems. There has been an growing awareness and acceptance that uncertainty is a fundamental issue of flood forecasting and needs to be dealt with at the different spatial and temporal scales as well as the different stages of the flood generating processes. Today, operational flood forecasting centres change increasingly from single deterministic forecasts to probabilistic forecasts with various representations of the different contributions of uncertainty. The move towards these so-called Hydrological Ensemble Prediction Systems (HEPS) in flood forecasting represents the state of the art in forecasting science, following on the success of the use of ensembles for weather forecasting (Buizza et al., 2005) and paralleling the move towards ensemble forecasting in other related disciplines such as climate change predictions. The use of HEPS has been internationally fostered by initiatives such as "The Hydrologic Ensemble Prediction Experiment" (HEPEX), created with the aim to investigate how best to produce, communicate and use hydrologic ensemble forecasts in hydrological short-, medium- und long term prediction of hydrological processes. The advantages of quantifying the different contributions of uncertainty as well as the overall uncertainty to obtain reliable and useful flood forecasts also for extreme events

  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. 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...

  14. 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

  15. Compensating for literature annotation bias when predicting novel drug-disease relationships through Medical Subject Heading Over-representation Profile (MeSHOP) similarity

    PubMed Central

    2013-01-01

    Background Using annotations to the articles in MEDLINE®/PubMed®, over six thousand chemical compounds with pharmacological actions have been tracked since 1996. Medical Subject Heading Over-representation Profiles (MeSHOPs) quantitatively leverage the literature associated with biological entities such as diseases or drugs, providing the opportunity to reposition known compounds towards novel disease applications. Methods A MeSHOP is constructed by counting the number of times each medical subject term is assigned to an entity-related research publication in the MEDLINE database and calculating the significance of the count by comparing against the count of the term in a background set of publications. Based on the expectation that drugs suitable for treatment of a disease (or disease symptom) will have similar annotation properties to the disease, we successfully predict drug-disease associations by comparing MeSHOPs of diseases and drugs. Results The MeSHOP comparison approach delivers an 11% improvement over bibliometric baselines. However, novel drug-disease associations are observed to be biased towards drugs and diseases with more publications. To account for the annotation biases, a correction procedure is introduced and evaluated. Conclusions By explicitly accounting for the annotation bias, unexpectedly similar drug-disease pairs are highlighted as candidates for drug repositioning research. MeSHOPs are shown to provide a literature-supported perspective for discovery of new links between drugs and diseases based on pre-existing knowledge. PMID:23819887

  16. Decoherence of quantum fields: Pointer states and predictability

    SciTech Connect

    Anglin, J.R.; Zurek, W.H.

    1996-06-01

    We study environmentally induced decoherence of an electromagnetic field in a homogeneous, linear, dielectric medium. We derive an independent oscillator model for such an environment, which is sufficiently realistic to encompass essentially all linear physical optics. Applying the {open_quote}{open_quote}predictability sieve{close_quote}{close_quote} to the quantum field, and introducing the concept of a {open_quote}{open_quote}quantum halo,{close_quote}{close_quote} we recover the familiar dichotomy between background field configurations and photon excitations around them. We are then able to explain why a typical linear environment for the electromagnetic field will effectively render the former classically distinct, but leave the latter fully quantum mechanical. Finally, we suggest how and why quantum matter fields should suffer a very different form of decoherence. {copyright} {ital 1996 The American Physical Society.}

  17. 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…

  18. 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.

  19. 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.

  20. Identification of functional networks in resting state fMRI data using adaptive sparse representation and affinity propagation clustering

    PubMed Central

    Li, Xuan; Wang, Haixian

    2015-01-01

    Human brain functional system has been viewed as a complex network. To accurately characterize this brain network, it is important to estimate the functional connectivity between separate brain regions (i.e., association matrix). One common approach to evaluating the connectivity is the pairwise Pearson correlation. However, this bivariate method completely ignores the influence of other regions when computing the pairwise association. Another intractable issue existed in many approaches to further analyzing the network structure is the requirement of applying a threshold to the association matrix. To address these issues, we develop a novel scheme to investigate the brain functional networks. Specifically, we first establish a global functional connection network by using the Adaptive Sparse Representation (ASR), adaptively integrating the sparsity of ℓ1-norm and the grouping effect of ℓ2-norm for linear representation and then identify connectivity patterns with Affinity Propagation (AP) clustering algorithm. Results on both simulated and real data indicate that the proposed scheme is superior to the Pearson correlation in connectivity quality and clustering quality. Our findings suggest that the proposed scheme is an accurate and useful technique to delineate functional network structure for functionally parsimonious and correlated fMRI data with a large number of brain regions. PMID:26528123

  1. 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.

  2. 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.

  3. 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…

  4. Exacting predictions by cybernetic model confirmed experimentally: steady state multiplicity in the chemostat.

    PubMed

    Kim, Jin Il; Song, Hyun-Seob; Sunkara, Sunil R; Lali, Arvind; Ramkrishna, Doraiswami

    2012-01-01

    We demonstrate strong experimental support for the cybernetic model based on maximizing carbon uptake rate in describing the microorganism's regulatory behavior by verifying exacting predictions of steady state multiplicity in a chemostat. Experiments with a feed mixture of glucose and pyruvate show multiple steady state behavior as predicted by the cybernetic model. When multiplicity occurs at a dilution (growth) rate, it results in hysteretic behavior following switches in dilution rate from above and below. This phenomenon is caused by transient paths leading to different steady states through dynamic maximization of the carbon uptake rate. Thus steady state multiplicity is a manifestation of the nonlinearity arising from cybernetic mechanisms rather than of the nonlinear kinetics. The predicted metabolic multiplicity would extend to intracellular states such as enzyme levels and fluxes to be verified in future experiments.

  5. 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

  6. 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.

  7. Research on spatial state conversion rule mining and stochastic predicting based on CA

    NASA Astrophysics Data System (ADS)

    Li, Xinyun; Kong, Xiangqiang

    2007-06-01

    Spatial dynamic prediction in GIS is the process of spatial calculation that infers the thematic maps in future according to the historical thematic maps, and it is space-time calculation from map to map. There is great application value that spatial dynamic prediction applied to the land planning, urban land-use planning and town planning, but there is some imperfect in method and technique at present. The main technical difficulty is excavation and expression of spatial state conversion rule. In allusion to the deficiency in spatial dynamic prediction using CA, the method which excavated spatial state conversion rule based on spatial data mining was put forward. Stochastic simulation mechanism was put into the prediction calculating based on state conversion rule. The result of prediction was more rational and the relation between the prediction steps and the time course was clearer. The method was applied to prediction of spatial structure change of urban land-use in Jinan. The Urban land-use change maps were predicted in 2006 and 2010 by using the land-use maps in 1998 and 2002. The result of this test was rational by analyzing.

  8. 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.

  9. 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

  10. 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

  11. When Oppression and Liberation Are the Only Choices: The Representation of African Americans within State Social Studies Standards

    ERIC Educational Resources Information Center

    Joumell, Wayne

    2008-01-01

    This study seeks to understand the ways nine states represent African Americans within their standards for U.S. History. Previous research on the effects of high-stakes assessment on social studies educators suggests teachers align their instruction with information found in state standards. Therefore, an understanding of the way African Americans…

  12. Slug sizing/slug volume prediction, state of the art review and simulation

    SciTech Connect

    Burke, N.E.; Kashou, S.F.

    1995-12-01

    Slug flow is a flow pattern commonly encountered in offshore multiphase flowlines. It is characterized by an alternate flow of liquid slugs and gas pockets, resulting in an unsteady hydrodynamic behavior. All important design variables, such as slug length and slug frequency, liquid holdup, and pressure drop, vary with time and this makes the prediction of slug flow characteristics both difficult and challenging. This paper reviews the state of the art methods in slug catcher sizing and slug volume predictions. In addition, history matching of measured slug flow data is performed using the OLGA transient simulator. This paper reviews the design factors that impact slug catcher sizing during steady state, during transient, during pigging, and during operations under a process control system. The slug tracking option of the OLGA simulator is applied to predict the slug length and the slug volume during a field operation. This paper will also comment on the performance of common empirical slug prediction correlations.

  13. Representation of CO{sub 2} and H{sub 2}S absorption by aqueous solutions of diethanolamine using an electrolyte equation of state

    SciTech Connect

    Vallee, G.; Fuerst, W.; Mougin, P.; Jullian, S.

    1999-09-01

    The electrolyte equation of state published in 1993 by Fuerst and Renon (AIChE J. 1993, 39, 335) has been applied to the representation of CO{sub 2} and H{sub 2}S solubility in diethaloamine (DEA) aqueous solutions. This equation of state extends the classical Redlich-Kwong-Soave equation of state associated with a Wong-Sandler mixing rule to the case of systems containing ions. The study of binary systems allowed the authors to determine the parameters of the nonelectrolyte part of the equation of state. The ionic parameters have been fitted from experimental solubility data covering a wide range of experimental conditions (temperature range, 25--100 C; amine concentration, from 0.5 to 3.5 M; loadings up to 2.34 mol{sub Co{sub 2}}/mol{sub amine}). With the assumption used in previous applications of their model to various electrolyte systems, the adjusted ionic parameters are interaction ones involving protonated amine and anions as well as molecular compounds. The resulting model represents experimental data with deviations consistent with the experimental ones and close to the deviations obtained in previous studies.

  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. Tree based machine learning framework for predicting ground state energies of molecules

    NASA Astrophysics Data System (ADS)

    Himmetoglu, Burak

    2016-10-01

    We present an application of the boosted regression tree algorithm for predicting ground state energies of molecules made up of C, H, N, O, P, and S (CHNOPS). The PubChem chemical compound database has been incorporated to construct a dataset of 16 242 molecules, whose electronic ground state energies have been computed using density functional theory. This dataset is used to train the boosted regression tree algorithm, which allows a computationally efficient and accurate prediction of molecular ground state energies. Predictions from boosted regression trees are compared with neural network regression, a widely used method in the literature, and shown to be more accurate with significantly reduced computational cost. The performance of the regression model trained using the CHNOPS set is also tested on a set of distinct molecules that contain additional Cl and Si atoms. It is shown that the learning algorithms lead to a rich and diverse possibility of applications in molecular discovery and materials informatics.

  16. Predicted bound states and microwave spectrum of N2-He van der Waals complexes

    NASA Astrophysics Data System (ADS)

    Li, Hui; Le Roy, Robert J.; McCourt, Frederick R. W.

    2009-06-01

    Numerical calculations show that four modern potential energy surfaces for N2-He all support 18 bound intermolecular states for the homonuclear isotopologues N14,142-H4e and N15,152-H4e, and 12 (or 13, for one surface) truly bound states for N14,152-He. This contradicts a recent statement [Patel et al., J. Chem. Phys. 119, 909 (2003)] that one of these surfaces supports no bound states, and it yields predictions for 27 allowed pure rotational transitions among the truly bound states of the homonuclear isotopologues of this complex.

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

    PubMed Central

    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

  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.

  19. 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

  20. Spin of the ground quantum state of electrons from first principles in the representation of Feynman path integrals

    NASA Astrophysics Data System (ADS)

    Shevkunov, S. V.

    2016-08-01

    A method for calculating the spin of the ground quantum state of nonrelativistic electrons and distance between energy levels of quantum states differing in the spin magnitude from first principles is proposed. The approach developed is free from the one-electron approximation and applicable in multielectron systems with allowance for all spatial correlations. The possibilities of the method are demonstrated by the example of calculating the energy gap between spin states in model ellipsoidal quantum dots with a harmonic confining field. The results of computations by the Monte Carlo method point to high sensitivity of the energy gap to the break of spherical symmetry of the quantum dot. For three electrons, the phenomenon of inversion has been revealed for levels corresponding to high and low values of the spin. The calculations demonstrate the practical possibility to obtain spin states with arbitrarily close energies by varying the shape of the quantum dot, which is a key condition for development prospects in technologies of storage systems based on spin qubits.

  1. Prediction of elemental creep. [steady state and cyclic data from regression analysis

    NASA Technical Reports Server (NTRS)

    Davis, J. W.; Rummler, D. R.

    1975-01-01

    Cyclic and steady-state creep tests were performed to provide data which were used to develop predictive equations. These equations, describing creep as a function of stress, temperature, and time, were developed through the use of a least squares regression analyses computer program for both the steady-state and cyclic data sets. Comparison of the data from the two types of tests, revealed that there was no significant difference between the cyclic and steady-state creep strains for the L-605 sheet under the experimental conditions investigated (for the same total time at load). Attempts to develop a single linear equation describing the combined steady-state and cyclic creep data resulted in standard errors of estimates higher than obtained for the individual data sets. A proposed approach to predict elemental creep in metals uses the cyclic creep equation and a computer program which applies strain and time hardening theories of creep accumulation.

  2. 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.

  3. Calculations of nonlinear response properties using the intermediate state representation and the algebraic-diagrammatic construction polarization propagator approach: two-photon absorption spectra.

    PubMed

    Knippenberg, S; Rehn, D R; Wormit, M; Starcke, J H; Rusakova, I L; Trofimov, A B; Dreuw, A

    2012-02-14

    An earlier proposed approach to molecular response functions based on the intermediate state representation (ISR) of polarization propagator and algebraic-diagrammatic construction (ADC) approximations is for the first time employed for calculations of nonlinear response properties. The two-photon absorption (TPA) spectra are considered. The hierarchy of the first- and second-order ADC∕ISR computational schemes, ADC(1), ADC(2), ADC(2)-x, and ADC(3/2), is tested in applications to H(2)O, HF, and C(2)H(4) (ethylene). The calculated TPA spectra are compared with the results of coupled cluster (CC) models and time-dependent density-functional theory (TDDFT) calculations, using the results of the CC3 model as benchmarks. As a more realistic example, the TPA spectrum of C(8)H(10) (octatetraene) is calculated using the ADC(2)-x and ADC(2) methods. The results are compared with the results of TDDFT method and earlier calculations, as well as to the available experimental data. A prominent feature of octatetraene and other polyene molecules is the existence of low-lying excited states with increased double excitation character. We demonstrate that the two-photon absorption involving such states can be adequately studied using the ADC(2)-x scheme, explicitly accounting for interaction of doubly excited configurations. Observed peaks in the experimental TPA spectrum of octatetraene are assigned based on our calculations.

  4. Reporting, representation, and subgroup analysis of race and ethnicity in published clinical trials of atopic dermatitis in the United States between 2000 and 2009.

    PubMed

    Hirano, Stefanie A; Murray, Susan B; Harvey, Valerie M

    2012-01-01

    To review the literature on atopic dermatitis (AD) clinical trials published in the United States between 2000 and 2009 to examine the representation of racial and ethnic minorities in those trials and determine the extent to which investigators reported on demographic variables and performed a subanalysis. A PubMed search was performed including all clinical trials for management of AD published between 2000 and 2009. Three reviewers analyzed articles matching the search criteria. Data recorded included incorporation of demographic data at baseline and in the analysis and result interpretations. Of 645 PubMed search results, only 78 articles originated in the United States and fit the search criteria; 59.5% of these included reports of race or ethnicity. Of the studies reporting race or ethnicity, the subject population mainly included 62.1% white, 18.0% black, 6.9% Asian, and 2.0% Hispanic. Despite increasing awareness in the United States of the importance of reporting demographic data in clinical trials, there has been no significant improvement in reporting in AD clinical trials over the past 10 years. When reporting occurs, the categorization of ethnicities, methods of reporting data, and incorporation of the data into the results are lacking or flawed. In addition, aside from blacks, U.S. minorities appear to be underrepresented in AD clinical trials.

  5. 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.

  6. Predicting the activation states of the muscles governing upper esophageal sphincter relaxation and opening.

    PubMed

    Omari, Taher I; Jones, Corinne A; Hammer, Michael J; Cock, Charles; Dinning, Philip; Wiklendt, Lukasz; Costa, Marcello; McCulloch, Timothy M

    2016-03-15

    The swallowing muscles that influence upper esophageal sphincter (UES) opening are centrally controlled and modulated by sensory information. Activation and deactivation of neural inputs to these muscles, including the intrinsic cricopharyngeus (CP) and extrinsic submental (SM) muscles, results in their mechanical activation or deactivation, which changes the diameter of the lumen, alters the intraluminal pressure, and ultimately reduces or promotes flow of content. By measuring the changes in diameter, using intraluminal impedance, and the concurrent changes in intraluminal pressure, it is possible to determine when the muscles are passively or actively relaxing or contracting. From these "mechanical states" of the muscle, the neural inputs driving the specific motor behaviors of the UES can be inferred. In this study we compared predictions of UES mechanical states directly with the activity measured by electromyography (EMG). In eight subjects, pharyngeal pressure and impedance were recorded in parallel with CP- and SM-EMG activity. UES pressure and impedance swallow profiles correlated with the CP-EMG and SM-EMG recordings, respectively. Eight UES muscle states were determined by using the gradient of pressure and impedance with respect to time. Guided by the level and gradient change of EMG activity, mechanical states successfully predicted the activity of the CP muscle and SM muscle independently. Mechanical state predictions revealed patterns consistent with the known neural inputs activating the different muscles during swallowing. Derivation of "activation state" maps may allow better physiological and pathophysiological interpretations of UES function.

  7. 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

  8. Resting‐state connectivity predicts levodopa‐induced dyskinesias in Parkinson's disease

    PubMed Central

    Haagensen, Brian N.; Nielsen, Silas H.; Madsen, Kristoffer H.; Løkkegaard, Annemette; Siebner, Hartwig R.

    2016-01-01

    ABSTRACT Background Levodopa‐induced dyskinesias are a common side effect of dopaminergic therapy in PD, but their neural correlates remain poorly understood. Objectives This study examines whether dyskinesias are associated with abnormal dopaminergic modulation of resting‐state cortico‐striatal connectivity. Methods Twelve PD patients with peak‐of‐dose dyskinesias and 12 patients without dyskinesias were withdrawn from dopaminergic medication. All patients received a single dose of fast‐acting soluble levodopa and then underwent resting‐state functional magnetic resonance imaging before any dyskinesias emerged. Levodopa‐induced modulation of cortico‐striatal resting‐state connectivity was assessed between the putamen and the following 3 cortical regions of interest: supplementary motor area, primary sensorimotor cortex, and right inferior frontal gyrus. These functional connectivity measures were entered into a linear support vector classifier to predict whether an individual patient would develop dyskinesias after levodopa intake. Linear regression analysis was applied to test which connectivity measures would predict dyskinesia severity. Results Dopaminergic modulation of resting‐state connectivity between the putamen and primary sensorimotor cortex in the most affected hemisphere predicted whether patients would develop dyskinesias with a specificity of 100% and a sensitivity of 91% (P < .0001). Modulation of resting‐state connectivity between the supplementary motor area and putamen predicted interindividual differences in dyskinesia severity (R 2 = 0.627, P = .004). Resting‐state connectivity between the right inferior frontal gyrus and putamen neither predicted dyskinesia status nor dyskinesia severity. Conclusions The results corroborate the notion that altered dopaminergic modulation of cortico‐striatal connectivity plays a key role in the pathophysiology of dyskinesias in PD. © 2016 International Parkinson and Movement

  9. Predicting the spin state of paramagnetic iron complexes by DFT calculation of proton NMR spectra.

    PubMed

    Borgogno, Andrea; Rastrelli, Federico; Bagno, Alessandro

    2014-07-01

    Many transition-metal complexes easily change their spin state S in response to external perturbations (spin crossover). Determining such states and their dynamics can play a central role in the understanding of useful properties such as molecular magnetism or catalytic behavior, but is often far from straightforward. In this work we demonstrate that, at a moderate computational cost, density functional calculations can predict the correct ground spin state of Fe(ii) and Fe(iii) complexes and can then be used to determine the (1)H NMR spectra of all spin states. Since the spectral features are remarkably different according to the spin state, calculated (1)H NMR resonances can be used to infer the correct spin state, along with supporting the structure elucidation of numerous paramagnetic complexes.

  10. 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

  11. 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…

  12. Use of a Measure of Reading Comprehension to Enhance Prediction on the State High Stakes Assessment

    ERIC Educational Resources Information Center

    Shapiro, Edward S.; Solari, Emily; Petscher, Yaacov

    2008-01-01

    The current study examined the diagnostic accuracy of two screening measures of risk for future difficulties in reading comprehension, as well as the degree to which adding a screening measure of reading comprehension enhanced the prediction of Oral Reading Fluency to outcomes of student reading performance on the state high stakes assessment for…

  13. 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...

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

    ERIC Educational Resources Information Center

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

    2011-01-01

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

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

    PubMed

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

    2016-02-16

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

  18. 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.

  19. A hybrid statistical-dynamical framework for meteorological drought prediction: Application to the southwestern United States

    NASA Astrophysics Data System (ADS)

    Madadgar, Shahrbanou; AghaKouchak, Amir; Shukla, Shraddhanand; Wood, Andrew W.; Cheng, Linyin; Hsu, Kou-Lin; Svoboda, Mark

    2016-07-01

    Improving water management in water stressed-regions requires reliable seasonal precipitation predication, which remains a grand challenge. Numerous statistical and dynamical model simulations have been developed for predicting precipitation. However, both types of models offer limited seasonal predictability. This study outlines a hybrid statistical-dynamical modeling framework for predicting seasonal precipitation. The dynamical component relies on the physically based North American Multi-Model Ensemble (NMME) model simulations (99 ensemble members). The statistical component relies on a multivariate Bayesian-based model that relates precipitation to atmosphere-ocean teleconnections (also known as an analog-year statistical model). Here the Pacific Decadal Oscillation (PDO), Multivariate ENSO Index (MEI), and Atlantic Multidecadal Oscillation (AMO) are used in the statistical component. The dynamical and statistical predictions are linked using the so-called Expert Advice algorithm, which offers an ensemble response (as an alternative to the ensemble mean). The latter part leads to the best precipitation prediction based on contributing statistical and dynamical ensembles. It combines the strength of physically based dynamical simulations and the capability of an analog-year model. An application of the framework in the southwestern United States, which has suffered from major droughts over the past decade, improves seasonal precipitation predictions (3-5 month lead time) by 5-60% relative to the NMME simulations. Overall, the hybrid framework performs better in predicting negative precipitation anomalies (10-60% improvement over NMME) than positive precipitation anomalies (5-25% improvement over NMME). The results indicate that the framework would likely improve our ability to predict droughts such as the 2012-2014 event in the western United States that resulted in significant socioeconomic impacts.

  20. Arthroplasty Utilization in the United States is Predicted by Age-Specific Population Groups.

    PubMed

    Bashinskaya, Bronislava; Zimmerman, Ryan M; Walcott, Brian P; Antoci, Valentin

    2012-01-01

    Osteoarthritis is a common indication for hip and knee arthroplasty. An accurate assessment of current trends in healthcare utilization as they relate to arthroplasty may predict the needs of a growing elderly population in the United States. First, incidence data was queried from the United States Nationwide Inpatient Sample from 1993 to 2009. Patients undergoing total knee and hip arthroplasty were identified. Then, the United States Census Bureau was queried for population data from the same study period as well as to provide future projections. Arthroplasty followed linear regression models with the population group >64 years in both hip and knee groups. Projections for procedure incidence in the year 2050 based on these models were calculated to be 1,859,553 cases (hip) and 4,174,554 cases (knee). The need for hip and knee arthroplasty is expected to grow significantly in the upcoming years, given population growth predictions.

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

    PubMed Central

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

    2010-01-01

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

  2. Categorical Drought Monitoring and Prediction in the United States Based on NLDAS-2

    NASA Astrophysics Data System (ADS)

    Hao, Z.; Xia, Y.; Hao, F.; Singh, V. P.

    2015-12-01

    Drought is a pervasive natural hazard and is a billion-dollar disaster in the United States, which is comparable to hurricanes and tropical storms with greater economic impacts than extratropical storms, wildfires, blizzards, and ice storms combined. Drought early warning is of critical importance for drought preparedness planning and mitigation efforts to reduce potential impacts of drought, for which drought monitoring and prediction are the essential components. The U.S. Drought Monitor (USDM) has been widely used to track droughts and their impacts. USDM is a composite product that blends quantitative drought indicators and qualitative drought information from multiple sources and classifies drought conditions into different drought categories. Due to the wide application of USDM products, drought monitoring and prediction in the categorical form would be of great importance to aid decision makers to take appropriate measures for drought managements. Based on drought indices from North American Land Data Assimilation System Phase 2 (NLDAS-2), this study proposes a statistical method for the categorical drought monitoring and prediction in the United States. The probabilities of drought conditions falling into different USDM drought categories can be estimated from the proposed method. The method is found to satisfactorily reconstruct historical USDM drought categories and predict future USDM drought categories, and has considerable potential to aid early drought warning in the United States.

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

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

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

    SciTech Connect

    Zhu, Xiaolei Yarkony, David R.

    2014-11-07

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

  5. Monthly Precipitation-Temperature Relations and Temperature Prediction over the United States.

    NASA Astrophysics Data System (ADS)

    Huang, Jin; van den Dool, Huug M.

    1993-06-01

    The monthly mean precipitation-air temperature (MMP-MMAT) relation over the United States has been examined by analyzing the observed MMP and MMAT during the period of 1931-87. The authors' main purpose is to examine the possibility of using MMP as a second predictor in addition to the MMAT itself in predicting the next month's MMAT and to shed light on the physical relationship between MMP and MMAT. Both station and climate division data are used.It was found that the lagged MMP-MMAT correlation with MMP leading by a month is generally negative, with the strongest negative correlation in summer and in the interior United States continent. Over large areas of the interior United States in summer, predictions of MMAT based on either antecedent MMP alone or on a combination of antecedent MMP and MMAT are better than a Prediction scheme based on MMAT alone. On the whole, even in the interior United States though, including MMP as a second predictor does not improve the skill of MMAT forecasts on either dependent or independent data dramatically because the first predictor (temperature persistence) has accounted for most of the MMP's predictive variance. For a verification performed separately for antecedent wet and dry months, much larger skill was found following wet than dry Julys for both one- and two-predictor schemes. Upon further analysis, we attribute this to the differences in the climate between the dependent (1931-60) and independent (1961-87) periods (the second being considerably colder in August) rather than to a true wetness dependence in the predictability.We found some evidence for the role of soil moisture in explaining negative MMP-MMAT and positive MMAT-MMAT lagged correlations both from observed data and from output of multiyear runs with the National Meteorological Center model. This suggests that we should use some direct measure of soil moisture to improve MMAT forecasts instead of using the MMP as a proxy.

  6. On the State of Stress and Failure Prediction Near Planetary Surface Loads

    NASA Astrophysics Data System (ADS)

    Schultz, R. A.

    1996-03-01

    The state of stress surrounding planetary surface loads has been used extensively to predict failure of surface rocks and to invert this information for effective elastic thickness. As demonstrated previously, however, several factors can be important including an explicit comparison between model stresses and rock strength as well as the magnitude of calculated stress. As re-emphasized below, failure to take stress magnitudes into account can lead to erroneous predictions of near-surface faulting. This abstract results from discussions on graben formation at Fall 1995 AGU.

  7. Braid group representation on quantum computation

    SciTech Connect

    Aziz, Ryan Kasyfil; Muchtadi-Alamsyah, Intan

    2015-09-30

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

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

    PubMed

    Liu, Wenyang; Sawant, Amit; Ruan, Dan

    2016-07-01

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

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

    PubMed

    Liu, Wenyang; Sawant, Amit; Ruan, Dan

    2016-07-01

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

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

    NASA Astrophysics Data System (ADS)

    Liu, Wenyang; Sawant, Amit; Ruan, Dan

    2016-07-01

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

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

    PubMed

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

  13. Predicting the likelihood of altered streamflows at ungauged rivers across the conterminous United States

    USGS Publications Warehouse

    Eng, Kenny; Carlisle, Daren M.; Wolock, David M.; Falcone, James A.

    2013-01-01

    An approach is presented in this study to aid water-resource managers in characterizing streamflow alteration at ungauged rivers. Such approaches can be used to take advantage of the substantial amounts of biological data collected at ungauged rivers to evaluate the potential ecological consequences of altered streamflows. National-scale random forest statistical models are developed to predict the likelihood that ungauged rivers have altered streamflows (relative to expected natural condition) for five hydrologic metrics (HMs) representing different aspects of the streamflow regime. The models use human disturbance variables, such as number of dams and road density, to predict the likelihood of streamflow alteration. For each HM, separate models are derived to predict the likelihood that the observed metric is greater than (‘inflated’) or less than (‘diminished’) natural conditions. The utility of these models is demonstrated by applying them to all river segments in the South Platte River in Colorado, USA, and for all 10-digit hydrologic units in the conterminous United States. In general, the models successfully predicted the likelihood of alteration to the five HMs at the national scale as well as in the South Platte River basin. However, the models predicting the likelihood of diminished HMs consistently outperformed models predicting inflated HMs, possibly because of fewer sites across the conterminous United States where HMs are inflated. The results of these analyses suggest that the primary predictors of altered streamflow regimes across the Nation are (i) the residence time of annual runoff held in storage in reservoirs, (ii) the degree of urbanization measured by road density and (iii) the extent of agricultural land cover in the river basin.

  14. An algorithm to estimate building heights from Google street-view imagery using single view metrology across a representational state transfer system

    NASA Astrophysics Data System (ADS)

    Díaz, Elkin; Arguello, Henry

    2016-05-01

    Urban ecosystem studies require monitoring, controlling and planning to analyze building density, urban density, urban planning, atmospheric modeling and land use. In urban planning, there are many methods for building height estimation using optical remote sensing images. These methods however, highly depend on sun illumination and cloud-free weather. In contrast, high resolution synthetic aperture radar provides images independent from daytime and weather conditions, although, these images rely on special hardware and expensive acquisition. Most of the biggest cities around the world have been photographed by Google street view under different conditions. Thus, thousands of images from the principal streets of a city can be accessed online. The availability of this and similar rich city imagery such as StreetSide from Microsoft, represents huge opportunities in computer vision because these images can be used as input in many applications such as 3D modeling, segmentation, recognition and stereo correspondence. This paper proposes a novel algorithm to estimate building heights using public Google Street-View imagery. The objective of this work is to obtain thousands of geo-referenced images from Google Street-View using a representational state transfer system, and estimate their average height using single view metrology. Furthermore, the resulting measurements and image metadata are used to derive a layer of heights in a Google map available online. The experimental results show that the proposed algorithm can estimate an accurate average building height map of thousands of images using Google Street-View Imagery of any city.

  15. The relationship between large-scale and convective states in the tropics - Towards an improved representation of convection in large-scale models

    SciTech Connect

    Jakob, Christian

    2015-02-26

    This report summarises an investigation into the relationship of tropical thunderstorms to the atmospheric conditions they are embedded in. The study is based on the use of radar observations at the Atmospheric Radiation Measurement site in Darwin run under the auspices of the DOE Atmospheric Systems Research program. Linking the larger scales of the atmosphere with the smaller scales of thunderstorms is crucial for the development of the representation of thunderstorms in weather and climate models, which is carried out by a process termed parametrisation. Through the analysis of radar and wind profiler observations the project made several fundamental discoveries about tropical storms and quantified the relationship of the occurrence and intensity of these storms to the large-scale atmosphere. We were able to show that the rainfall averaged over an area the size of a typical climate model grid-box is largely controlled by the number of storms in the area, and less so by the storm intensity. This allows us to completely rethink the way we represent such storms in climate models. We also found that storms occur in three distinct categories based on their depth and that the transition between these categories is strongly related to the larger scale dynamical features of the atmosphere more so than its thermodynamic state. Finally, we used our observational findings to test and refine a new approach to cumulus parametrisation which relies on the stochastic modelling of the area covered by different convective cloud types.

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

    1993-01-13

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  18. Slug-sizing/slug-volume prediction: State of the art review and simulation

    SciTech Connect

    Burke, N.E.; Kashou, S.F.

    1996-08-01

    Slug flow is a flow pattern commonly encountered in offshore multiphase flowlines. It is characterized by an alternate flow of liquid slugs and gas pockets, resulting in an unsteady hydrodynamic behavior. All important design variables, such as slug length and slug frequency, liquid holdup, and pressure drop, vary with time and this makes the prediction of slug flow characteristics both difficult and challenging. This paper reviews the state of the art methods in slug-catcher sizing and slug-volume predictions. In addition, history matching of measured slug flow data is performed using the OLGA transient simulator. This paper reviews the design factors that impact slug-catcher sizing during steady state, during transient, during pigging, and during operations under a process-control system. The slug-tracking option of the simulator is applied to predict the slug length and the slug volume during a field operation. This paper will also comment on the performance of common empirical slug-prediction correlations.

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

    PubMed Central

    Yoo, Jaewook; Kwon, Jaerock; Choe, Yoonsuck

    2014-01-01

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

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

    PubMed Central

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

    2014-01-01

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

  1. Localization of nonlinear damage using state-space-based predictions under stochastic excitation

    NASA Astrophysics Data System (ADS)

    Liu, Gang; Mao, Zhu; Todd, Michael; Huang, Zongming

    2014-02-01

    This paper presents a study on localizing damage under stochastic excitation by state-space-based methods, where the damaged response contains some nonlinearity. Two state-space-based modeling algorithms, namely auto- and cross-predictions, are employed in this paper, and the greatest prediction error will be achieved at the sensor pair closest to the actual damage, in terms of localization. To quantify the distinction of prediction error distributions obtained at different sensor locations, the Bhattacharyya distance is adopted as the quantification metric. There are two lab-scale test-beds adopted as validation platforms, including a two-story plane steel frame with bolt loosening damage and a three-story benchmark aluminum frame with a simulated tunable crack. Band-limited Gaussian noise is applied through an electrodynamic shaker to the systems. Testing results indicate that the damage detection capability of the state-space-based method depends on the nonlinearity-induced high frequency responses. Since those high frequency components attenuate quickly in time and space, the results show great capability for damage localization, i.e., the highest deviation of Bhattacharyya distance is coincident with the sensors close to the physical damage location. This work extends the state-space-based damage detection method for localizing damage to a stochastically excited scenario, which provides the advantage of compatibility with ambient excitations. Moreover, results from both experiments indicate that the state-space-based method is only sensitive to nonlinearity-induced damage, thus it can be utilized in parallel with linear classifiers or normalization strategies to insulate the operational and environmental variability, which often affects the system response in a linear fashion.

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

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2015-05-26

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  8. Factors predicting individual emergency preparedness: a multi-state analysis of 2006 BRFSS data.

    PubMed

    Ablah, Elizabeth; Konda, Kurt; Kelley, Crystal L

    2009-09-01

    Disasters pose a very real threat to every individual in the United States. One way to mitigate the threat of disasters is through personal preparedness, yet numerous studies indicate that individual Americans are not prepared for a disaster. This study attempted to identify the factors most likely to predict individual disaster preparedness. We used 2006 Behavioral Risk Factor Surveillance System (BRFSS) data from the 5 states that included the optional general preparedness module. Respondents were defined as being "prepared" if they were deficient in no more than 1 of the 6 actionable preparedness measures included on the BRFSS. Analyses were conducted comparing preparedness rates based on medical and demographic factors. Using logistic regression, a predictive model was constructed to identify which factors most strongly predicted an individual's likelihood of being prepared. Although 78% of respondents reported feeling prepared for a disaster, just 45% of respondents were actually prepared by objective measures. Factors predicting an increased likelihood of preparedness included feeling "well prepared" (OR 9.417), having a disability or health condition requiring special equipment (OR 1.298), being 55 to 64 years old (OR 1.794), and having an annual income above $50,000 (OR 1.286). Among racial and ethnic minorities, an inability to afford medical care in the previous year (OR .581) was an important factor in predicting a decreased likelihood of being prepared. This study revealed a pervasive lack of disaster preparedness overall and a substantial gap between perceived and objective preparedness. Income and age were important predictors of disaster preparedness.

  9. Efficient online bootstrapping of sensory representations.

    PubMed

    Gepperth, Alexander

    2013-05-01

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

  10. A Methylmercury Prediction Too For Surface Waters Across The Contiguous United States (Invited)

    NASA Astrophysics Data System (ADS)

    Krabbenhoft, D. P.; Booth, N.; Lutz, M.; Fienen, M. N.; Saltman, T.

    2009-12-01

    About 20 years ago, researchers at a few locations across the globe discovered high levels of mercury in fish from remote settings lacking any obvious mercury source. We now know that for most locations atmospheric deposition is the dominant mercury source, and that mercury methylation is the key process that translates low mercury loading rates into relatively high levels in top predators of aquatic food webs. Presently, almost all US states have advisories for elevated levels of mercury in sport fish, and as a result there is considerable public awareness and concern for this nearly ubiquitous contaminant issue. In some states, “statewide” advisories have been issued because elevated fish mercury levels are so common, or the state has no effective way to monitor thousands of lakes, reservoirs, wetlands, and streams. As such, resource managers and public health officials have limited options for informing the public on of where elevated mercury concentrations in sport fish are more likely to occur than others. This project provides, for the first time, a national map of predicted (modeled) methylmercury concentrations in surface waters, which is the most toxic and bioaccumulative form of mercury in the environment. The map is the result of over two decades of research that resulted in the formulation of conceptual models of the mercury methylation process, which is strongly governed by environmental conditions - specifically hydrologic landscapes and water quality. The resulting predictive map shows clear regional trends in the distribution of methylmercury concentrations in surface waters. East of the Mississippi, the Gulf and southeastern Atlantic coast, the northeast, the lower Mississippi valley, and Great Lakes area are predicted to have generally higher environmental methylmercury levels. Higher-elevation, well-drained areas of Appalachia are predicted to have relatively lower methylmercury abundance. Other than the prairie pothole region, in the western

  11. Low-dimensional Representation of Error Covariance

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

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

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

    SciTech Connect

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

    2011-01-17

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

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

    NASA Astrophysics Data System (ADS)

    Martínez, S.; Ukar, E.; Lamikiz, A.; Liebana, F.

    2011-01-01

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

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

    PubMed

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

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  16. What Cognitive Representations Support Primate Theory of Mind?

    PubMed

    Martin, Alia; Santos, Laurie R

    2016-05-01

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

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

    SciTech Connect

    M. STOUT; ET AL

    2000-08-01

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

  18. Predicting the fate and transport of toxic metal emissions over the United States.

    NASA Astrophysics Data System (ADS)

    Hutzell, W. T.

    2006-12-01

    Anthropogenic emissions are believed to determine the atmospheric concentrations and deposition of several metals present in particulate mater. Several of these metals have toxic effects on human health. Because of such effects, the United States Environmental Protection Agency (EPA) reports metallic emissions in their National Emissions Inventory (NEI) to assess risks to human health. To better understand where and when humans are exposed to the highest levels of toxic metals, we have developed a regional model for the transport and fate of six metals (lead, nickel, chromium, cadmium, beryllium and manganese) reported by the NEI. An application used the NEI for 1999 and predicted the atmospheric concentrations, as well as deposition over the continental United States (US). Results show that concentrations are two to three orders of magnitude greater over the US than over remote marine locations. The result roughly agrees with observations reported by US monitoring sites during 2001. Highest predicted concentrations occur over northeastern states and the lower Mississippi river. Deposition of toxic metals has a strong spatial gradient, and a strong seasonal component. Disclaimer: The research presented here was performed under the Memorandum of Understanding between the U.S. Environmental Protection Agency (EPA) and U.S. Department of Commerce's National Oceanic and Atmospheric Administration (NOAA) and under agreement number DW13921548. This work constitutes a contribution to the NOAA Air Quality Program. Although it has been reviewed by EPA and NOAA and approved for publication, it does not necessarily reflect their policies or views.

  19. The Autonomic System Functional State Predicts Responsiveness in Disorder of Consciousness.

    PubMed

    Riganello, Francesco; Cortese, Maria D; Dolce, Giuliano; Lucca, Lucia F; Sannita, Walter G

    2015-07-15

    Diagnosis and early prognosis of the vegetative state/unresponsive wakefulness syndrome (VS/UWS) and its differentiation from the minimally-conscious state still rest on the clinical observation of responsiveness. The incidence of established clinical indicators of responsiveness also has proven variable in the single subject and is correlated to measures of heart rate variability (HRV) describing the sympathetic/parasympathetic balance. We tested responsiveness when the HRV descriptors nuLF and peakLF were or were not in the ranges with highest incidence of response based on findings from previous studies (10.0-70.0 and 0.05-0.11 Hz, respectively). Testing was blind by The Coma Recovery Scale-revised in the two conditions and in two experimental sessions with a one-week interval. The incidence of responses was not randomly distributed in the "response" and "no-response" conditions (McNemar test; p < 0.0001). The observed incidence in the "response" condition (visual: 55.1%; auditory: 51.5%) was higher than predicted statistically (32.1%) or described in previous clinical studies; responses were only occasional in the "no-response" condition (visual, 15.9%; auditory, 13.4%). Models validated the predictability with high accuracy. The current clinical criteria for diagnosis and prognosis based on neurological signs should be reconsidered, including variability over time and the autonomic system functional state, which could also qualify per se as an independent indicator for diagnosis and prognosis.

  20. Improved prediction of RNA tertiary structure with insights into native state dynamics.

    PubMed

    Bida, John Paul; Maher, L James

    2012-03-01

    The importance of RNA tertiary structure is evident from the growing number of published high resolution NMR and X-ray crystallographic structures of RNA molecules. These structures provide insights into function and create a knowledge base that is leveraged by programs such as Assemble, ModeRNA, RNABuilder, NAST, FARNA, Mc-Sym, RNA2D3D, and iFoldRNA for tertiary structure prediction and design. While these methods sample native-like RNA structures during simulations, all struggle to capture the native RNA conformation after scoring. We propose RSIM, an improved RNA fragment assembly method that preserves RNA global secondary structure while sampling conformations. This approach enhances the quality of predicted RNA tertiary structure, provides insights into the native state dynamics, and generates a powerful visualization of the RNA conformational space. RSIM is available for download from http://www.github.com/jpbida/rsim.

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

    NASA Technical Reports Server (NTRS)

    Nelson, Kyle S.; Hadden, George D.

    1992-01-01

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

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

    USGS Publications Warehouse

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Jung, Eunsil; Kirtman, Ben P.

    2016-07-01

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

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

    PubMed

    Currie, James; Gehrmann, Thomas; Niehues, Jan

    2016-07-22

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

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

    NASA Astrophysics Data System (ADS)

    Currie, James; Gehrmann, Thomas; Niehues, Jan

    2016-07-01

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

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

    NASA Astrophysics Data System (ADS)

    Jung, Eunsil; Kirtman, Ben P.

    2016-07-01

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

  7. The prediction of structural response to buffet flow: A state-of-the-art review

    NASA Technical Reports Server (NTRS)

    Hanson, P. W.

    1974-01-01

    Certain aspects of the dynamic system being discussed are reviewed and important structural and aerodynamic quantities of the system are discussed. A theoretical model is presented which relates these quantities to each other. These quantities are then each, in turn, considered in terms of the state of the art of determining the quantities and in terms of areas where further research is needed. The similarity laws and scaling relationships applicable to determining buffet structural response are then discussed, and areas where simplification is required or may be permissible are mentioned. Finally, the various types of model tests pertinent to predicting response of the aircraft structure to buffet flow are discussed.

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

    NASA Astrophysics Data System (ADS)

    Czernek, Jiří; Brus, Jiří

    2016-07-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1989-01-01

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

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

    PubMed

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

    2015-12-01

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

  11. Rotational isomeric state theory applied to the stiffness prediction of an anion polymer electrolyte membrane

    NASA Astrophysics Data System (ADS)

    Gao, Fei; Weiland, Lisa Mauck; Kitchin, John

    2008-03-01

    While the acidic polymer electrolyte membrane (PEM) Nafion has garnered considerable attention, the active response of basic PEMs offers another realm of potential applications. For instance, the basic PEM Selemion is currently being considered in the development of a CO II separation prototype device to be employed in coal power plant flue gas. The mechanical integrity of this material and subsequent effects in active response in this harsh environment will become important in prototype development. A multiscale modeling approach based on rotational isomeric state theory in combination with a Monte Carlo methodology may be employed to study mechanical integrity. The approach has the potential to be adapted to address property change of any PEM in the presence of foreign species (reinforcing or poisoning), as well as temperature and hydration variations. The conformational characteristics of the Selemion polymer chain and the cluster morphology in the polymer matrix are considered in the prediction of the stiffness of Selemion in specific states.

  12. Social determinants of health predict state incidence of HIV and AIDS: a short report.

    PubMed

    Zeglin, Robert J; Stein, J Paul

    2015-01-01

    There are approximately 1.2 million people living with HIV/AIDS (PLWHA) in the USA. Each year, there are roughly 50,000 new HIV diagnoses. The World Health Organization Commission on Social Determinants of Health (CSDH) identified several social determinants of health and health inequity (SDH) including childcare, education, employment, gender equality, health insurance, housing, and income. The CSDH also noted the significant impact the SDH can have on advocacy for social change, social interventions to reduce HIV prevalence, and health monitoring. The current analysis evaluated the predictive ability of five SDH for HIV and AIDS incidence on the state level. The SDH used in the analysis were education, employment, housing, income, and insurance; other SDH were not included because reliable and appropriate state-level data were not available. The results of multiple regression analyses indicate that the use of these five SDH create statistically significant models predicting HIV incidence (adjusted R(2) = .54) and AIDS incidence (adjusted R(2) = .37) and account for a sizable portion of the variance for each. Stepwise variable selection reduced the necessary SDH to two: (1) education and (2) housing. These models are also statistically significant and account for a notable portion of variance in HIV incidence (adjusted R(2) = .55) and AIDS incidence (adjusted R(2) = .40). These outcomes demonstrate that state-level SDH, particularly education and housing, offer significant explanatory power regarding HIV and AIDS incidence rates. Congruent with the recommendations of the CSDH, the results of the current analysis suggest that state-sponsored policy and social interventions should consider and target SDH, especially education and housing, in attempts to reduce HIV and AIDS incidence rates.

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

    PubMed Central

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

    2014-01-01

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

  14. Social determinants of health predict state incidence of HIV and AIDS: a short report.

    PubMed

    Zeglin, Robert J; Stein, J Paul

    2015-01-01

    There are approximately 1.2 million people living with HIV/AIDS (PLWHA) in the USA. Each year, there are roughly 50,000 new HIV diagnoses. The World Health Organization Commission on Social Determinants of Health (CSDH) identified several social determinants of health and health inequity (SDH) including childcare, education, employment, gender equality, health insurance, housing, and income. The CSDH also noted the significant impact the SDH can have on advocacy for social change, social interventions to reduce HIV prevalence, and health monitoring. The current analysis evaluated the predictive ability of five SDH for HIV and AIDS incidence on the state level. The SDH used in the analysis were education, employment, housing, income, and insurance; other SDH were not included because reliable and appropriate state-level data were not available. The results of multiple regression analyses indicate that the use of these five SDH create statistically significant models predicting HIV incidence (adjusted R(2) = .54) and AIDS incidence (adjusted R(2) = .37) and account for a sizable portion of the variance for each. Stepwise variable selection reduced the necessary SDH to two: (1) education and (2) housing. These models are also statistically significant and account for a notable portion of variance in HIV incidence (adjusted R(2) = .55) and AIDS incidence (adjusted R(2) = .40). These outcomes demonstrate that state-level SDH, particularly education and housing, offer significant explanatory power regarding HIV and AIDS incidence rates. Congruent with the recommendations of the CSDH, the results of the current analysis suggest that state-sponsored policy and social interventions should consider and target SDH, especially education and housing, in attempts to reduce HIV and AIDS incidence rates. PMID:25225050

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

    PubMed

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

    2005-06-20

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

  16. Predicting the crystalline and porous equations of state for secondary explosives

    NASA Astrophysics Data System (ADS)

    Wixom, Ryan; Damm, David

    2013-06-01

    Accurate simulations of energetic material response necessitate accurate unreacted equations of state at pressures much higher than even the C-J state. Unfortunately, for reactive materials, experimental data at high pressures may be unattainable, and extrapolation from low-pressure data results in unacceptable uncertainty. In addition to being low-pressure, the available data is typically limited to the porous state. The fully-dense, or crystalline, equation of state is required for building mesoscale simulations of the dynamic response of energetic materials. We have used quantum molecular dynamics to predict the Hugoniots and 300 K isotherms of crystalline PETN, HNS, CL-20 and TATB up to pressures not attainable in experiments. The porous Hugoniots for these materials were then analytically obtained and are validated by comparison with available data. Our calculations for TATB confirm the presence of a kink in the Hugoniot, and the softening of the shock response is explained in terms of a change in molecular conformation and the loss of aromaticity.

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  19. Use of a Measure of Reading Comprehension to Enhance Prediction on the State High Stakes Assessment

    PubMed Central

    Shapiro, Edward S.; Solari, Emily; Petscher, Yaacov

    2015-01-01

    The current study examined the diagnostic accuracy of two screening measures of risk for future difficulties in reading comprehension, as well as the degree to which adding a screening measure of reading comprehension enhanced the prediction of Oral Reading Fluency to outcomes of student reading performance on the state high stakes assessment for grades 3 through 5. Data from fall and winter assessments of the DIBELS Oral Reading Fluency (DORF) and 4Sight Benchmark Assessment (4Sight) measures along with outcomes on the Pennsylvania System of School Assessment (PSSA) across a total of 1000 students from 6 schools were examined using indices of diagnostic efficiency, ROC curve, and logistic regression analyses. Results showed that the addition of a measure of reading comprehension (4Sight) to DORF enhanced the decision making process for identifying students at risk for reading difficulties, especially for those students at higher elementary grades and those who achieved benchmark levels on the DORF. Although DORF alone showed a good level of prediction to the statewide assessment, the combination of the DORF plus 4Sight measures resulted consistently in the best predictive outcomes. Suggestions are made to consider alternative cut points for the DORF and 4Sight measures. PMID:26347390

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

    PubMed Central

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

    2014-01-01

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

  1. 10-minute delayed recall from the modified mini-mental state test predicts Alzheimer's disease pathology.

    PubMed

    Lyness, Scott A; Lee, Ae Young; Zarow, Chris; Teng, Evelyn L; Chui, Helena C

    2014-01-01

    We compared the sensitivity and specificity of two delayed recall scores from the Modified Mini-Mental State (3MS) test with consensus clinical diagnosis to differentiate cognitive impairment due to Alzheimer's disease (AD) versus non-AD pathologies. At a memory disorders clinic, 117 cognitively impaired patients were administered a baseline 3MS test and received a contemporaneous consensus clinical diagnosis. Their brains were examined after death about 5 years later. Using logistic regression with forward selection to predict pathologically defined AD versus non-AD, 10-min delayed recall entered first (p = 0.001), followed by clinical diagnosis (p = 0.02); 1-min delayed recall did not enter. 10-min delayed recall scores ≤4 (score range = 0-9) were 87% sensitive and 47% specific in predicting AD pathology; consensus clinical diagnosis was 82% sensitive and 45% specific. For the 57 patients whose initial Mini-Mental State Examination scores were ≥19 (the median), 3MS 10-min delayed recall scores ≤4 showed some loss of sensitivity (80%) but a substantial gain in specificity (77%). In conclusion, 10-min delayed recall score on the brief 3MS test distinguished between AD versus non-AD pathology about 5 years before death at least as well as consensus clinical diagnosis that requires much more comprehensive information and complex deliberation.

  2. Stoichiometric Representation of Gene–Protein–Reaction Associations Leverages Constraint-Based Analysis from Reaction to Gene-Level Phenotype Prediction

    PubMed Central

    2016-01-01

    Genome-scale metabolic reconstructions are currently available for hundreds of organisms. Constraint-based modeling enables the analysis of the phenotypic landscape of these organisms, predicting the response to genetic and environmental perturbations. However, since constraint-based models can only describe the metabolic phenotype at the reaction level, understanding the mechanistic link between genotype and phenotype is still hampered by the complexity of gene-protein-reaction associations. We implement a model transformation that enables constraint-based methods to be applied at the gene level by explicitly accounting for the individual fluxes of enzymes (and subunits) encoded by each gene. We show how this can be applied to different kinds of constraint-based analysis: flux distribution prediction, gene essentiality analysis, random flux sampling, elementary mode analysis, transcriptomics data integration, and rational strain design. In each case we demonstrate how this approach can lead to improved phenotype predictions and a deeper understanding of the genotype-to-phenotype link. In particular, we show that a large fraction of reaction-based designs obtained by current strain design methods are not actually feasible, and show how our approach allows using the same methods to obtain feasible gene-based designs. We also show, by extensive comparison with experimental 13C-flux data, how simple reformulations of different simulation methods with gene-wise objective functions result in improved prediction accuracy. The model transformation proposed in this work enables existing constraint-based methods to be used at the gene level without modification. This automatically leverages phenotype analysis from reaction to gene level, improving the biological insight that can be obtained from genome-scale models. PMID:27711110

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

    SciTech Connect

    Lall, Pradeep; Wei, Junchao; Sakalaukus, Peter

    2014-06-22

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    SciTech Connect

    Varga, Zoltan; Truhlar, Donald G.

    2015-09-08

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

  6. CensusPlus: A sampling and prediction approach for the 2000 census of the United States

    SciTech Connect

    Wright, T.

    1995-07-01

    For a general audience, this paper offers details of a simple proposal for estimation of the population and housing in the year 2000 for the United States. Under CensusPlus, two surveys (mass enumeration and plus sample enumeration) are made of a universe with M blocks. The mass enumeration results in an initial preliminary count for each and every block in the country. The plus sample blocks undergo a second extra high quality count which when compared with the initial count leads to observed resolved counts for the sample blocks. Under a simple model, resolved counts are predicted for the nonsample blocks. Hence an optimal estimator of N, the universe size. is obtained by adding these observed (in sample) and predicted (not in sample) resolved block counts. In fact, this sum turns out to be the classical ratio estimator. This one number census collection is additive and consistent for all levels of geography. In addition, this paper presents sample sizes for the number of blocks required by the plus sample enumeration to support reliable state level estimates of population produced by CensusPlus. In particular and using data from the 1990 Census Files and the 1990 PES Block Data File, it is shown that a nationwide deeply stratified probability sample of 22,120 blocks is needed to ensure that the housing unit population of a given state is estimated with a standard error of 40,000 persons. The 1990 PES Block Data File also provides some early empirical evidence that the model is very likely to hold.

  7. 10 CFR 60.65 - Representation.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

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

  8. 10 CFR 60.65 - Representation.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

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

  9. 10 CFR 60.65 - Representation.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

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

  10. 10 CFR 60.65 - Representation.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

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

  11. 10 CFR 60.65 - Representation.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

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

  12. Precedence relationship representations of mechanical assembly sequences

    NASA Technical Reports Server (NTRS)

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

    1989-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

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

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

    PubMed

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

    2014-05-01

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

  15. Explorations of Representational Momentum.

    ERIC Educational Resources Information Center

    Kelly, Michael H.; Freyd, Jennifer J.

    1987-01-01

    Figures that undergo an implied rotation are remembered as being slightly beyond their final position, a phenomenon called representational momentum. Eight experiments explored the questions of what gets transformed and what types of transformations induce such representational distortions. (GDC)

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    A Flow-Duration Curve (FDC) represents the percentage of time (duration) during which a given stream-flow is equalled or exceeded over a given period of time. In many water-engineering applications FDCs need to be predicted for ungauged sites (Prediction in Ungauged Basins, PUB problem) using the information collected in donor neighboring gauged basins. We present an application of kriging procedures which makes the procedures capable of predicting FDCs in ungauged catchments. As many of the techniques proposed in the recent literature, the curve is predicted at the target site as a weighted average of empirical dimensionless FDCs that are constructed for neighboring streamgauges and standardized by discharge Q*. Geostatistical weights are obtained by applying two different interpolation techniques, i.e. Top-kriging (TK, see e.g. Pugliese et al., 2014) and Ordinary-kriging (OK, see e.g. Castiglioni et al., 2009), for interpolating a point streamflow-index computed as the overall negative deviation of each empirical curve from Q*, which we term Total Negative Deviation (TND). Empirical TND values can be used to assess the hydrological similarity between catchments and can be interpolated using TK or OK procedures along the stream-network. We consider period-of-record/annual, and complete/seasonal FDCs standardized by two different Q* values, i.e. Mean Annual Flow (MAF) and Mean Annual Precipitation at catchment scale times the drainage area (MAP*), and we apply TK and OK in a wide study area in the Southeastern United States including 182 unregulated gauged catchments. The accuracy of the predicted FDCs is assessed comprehensively under different operational conditions through the (1) leave-one-out and (2) three-fold cross-validation procedures. The results are compared with six different methods for predicting FDCs from synthetically generated daily stream-flow series, which were recently analysed by U.S. Geological Survey. The application of OK and TK reveal

  17. Prediction of explosive cylinder tests using equations of state from the PANDA code

    SciTech Connect

    Kerley, G.I.; Christian-Frear, T.L.

    1993-09-28

    The PANDA code is used to construct tabular equations of state (EOS) for the detonation products of 24 explosives having CHNO compositions. These EOS, together with a reactive burn model, are used in numerical hydrocode calculations of cylinder tests. The predicted detonation properties and cylinder wall velocities are found to give very good agreement with experimental data. Calculations of flat plate acceleration tests for the HMX-based explosive LX14 are also made and shown to agree well with the measurements. The effects of the reaction zone on both the cylinder and flat plate tests are discussed. For TATB-based explosives, the differences between experiment and theory are consistently larger than for other compositions and may be due to nonideal (finite dimameter) behavior.

  18. Prediction of telephone calls load using Echo State Network with exogenous variables.

    PubMed

    Bianchi, Filippo Maria; Scardapane, Simone; Uncini, Aurelio; Rizzi, Antonello; Sadeghian, Alireza

    2015-11-01

    We approach the problem of forecasting the load of incoming calls in a cell of a mobile network using Echo State Networks. With respect to previous approaches to the problem, we consider the inclusion of additional telephone records regarding the activity registered in the cell as exogenous variables, by investigating their usefulness in the forecasting task. Additionally, we analyze different methodologies for training the readout of the network, including two novel variants, namely ν-SVR and an elastic net penalty. Finally, we employ a genetic algorithm for both the tasks of tuning the parameters of the system and for selecting the optimal subset of most informative additional time-series to be considered as external inputs in the forecasting problem. We compare the performances with standard prediction models and we evaluate the results according to the specific properties of the considered time-series.

  19. Representation in Memory.

    ERIC Educational Resources Information Center

    Rumelhart, David E.; Norman, Donald A.

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

  20. The Problem State: A Cognitive Bottleneck in Multitasking

    ERIC Educational Resources Information Center

    Borst, Jelmer P.; Taatgen, Niels A.; van Rijn, Hedderik

    2010-01-01

    The main challenge for theories of multitasking is to predict when and how tasks interfere. Here, we focus on interference related to the problem state, a directly accessible intermediate representation of the current state of a task. On the basis of Salvucci and Taatgen's (2008) threaded cognition theory, we predict interference if 2 or more…

  1. Predicting Nitrogen Loading in Streams Under Climate Change Scenarios in the Continental United States.

    NASA Astrophysics Data System (ADS)

    Sinha, E.; Michalak, A. M.

    2014-12-01

    Human actions have doubled the amount of nitrogen in the terrestrial biosphere. Although nitrogen application in the form of fertilizers increases food production, excess nitrogen can be harmful to the environment and to human well-being. Excess nitrogen in streams is transported into downstream water bodies, which leads to increased eutrophication and associated problems such as harmful algal blooms and/or hypoxic conditions. The amount of nitrogen exported to streams depends on several factors, including nitrogen input to the watershed, land use, and precipitation. Previous studies have developed models for predicting nitrate load using stream discharge, in order to estimate the contribution of various factors to total nitrogen load, to identify strategies for reducing nitrogen load, and to assess future changes in nitrogen load resulting from anticipated changes in precipitation patterns. Applying these models to estimate future nitrogen loads thus requires running a rainfall-runoff model driven by climate model predictions before nitrogen loading can, in turn, be estimated, thereby compounding uncertainties. In this study, we present a statistical modeling approach that circumvents this two-step process by estimating nitrogen loading directly from precipitation predictions that can be obtained from climate model outputs. The proposed model uses net anthropogenic nitrogen input (NANI), land use type, and precipitation as input parameters. Preliminary results show that the model explains greater than 65% of the variance in the observed annual log transformed nitrogen loads across various catchments throughout the United States. The model is applied to the watersheds comprising the Mississippi river basin to identify the spatial distribution of the sources of nitrogen loading and the inter-annual variation in nitrogen loads under current conditions. Additionally, the model is used to examine changes in magnitude and spatial patterns of nitrogen loading for

  2. Predicting CO2 and SO2 emissions in the Baltic States through reorganization of energy infrastructure.

    PubMed

    Denafas, Gintaras; Sitnikovas, Denisas; Galinis, Arvydas; Kudrenickis, Ivars; Klavs, Gaidis; Kuusik, Rein

    2004-10-01

    The paper deals with predicting carbon dioxide and sulphur dioxide emissions generated by power production sector in the Baltic States in period up to year 2020. The economies of Lithuania, Latvia and Estonia are rapidly growing therefore forecast of emissions related with this occurrence becomes very important. The Ignalina Nuclear Power Plant (INPP), one of the largest in the world, is situated in the region. Two power production scenarios are modelled to investigate changes in power sector's emissions expected as the consequences of the coming closure of Ignalina NPP. Power market was assumed to be common for all three Baltic countries and was modelled by applying the Balmorel model. The planned closure of Ignalina NPP will bring restructuring of Lithuania power production sector and will change also power transmission between countries. Predictive identified the potential of investments for new modern power generation technologies. At the same time, modelling results show in both scenarios that CO(2) and SO(2) emissions from power production in the Baltic region will increase. The increment of emissions is discussed in the context of meeting requirements of UNFCCC Kyoto protocol and EC Directives. Despite of CO(2) emissions increase the Kyoto protocol's requirements may be expected. At the same time, SO(2) formation in Lithuania power sector may exceed the limits of the EU Council Directive 2001/80/EB therefore the additional measures to control SO(2) emissions have to be investigated.

  3. A simple modelling approach for prediction of standard state real gas entropy of pure materials.

    PubMed

    Bagheri, M; Borhani, T N G; Gandomi, A H; Manan, Z A

    2014-01-01

    The performance of an energy conversion system depends on exergy analysis and entropy generation minimisation. A new simple four-parameter equation is presented in this paper to predict the standard state absolute entropy of real gases (SSTD). The model development and validation were accomplished using the Linear Genetic Programming (LGP) method and a comprehensive dataset of 1727 widely used materials. The proposed model was compared with the results obtained using a three-layer feed forward neural network model (FFNN model). The root-mean-square error (RMSE) and the coefficient of determination (r(2)) of all data obtained for the LGP model were 52.24 J/(mol K) and 0.885, respectively. Several statistical assessments were used to evaluate the predictive power of the model. In addition, this study provides an appropriate understanding of the most important molecular variables for exergy analysis. Compared with the LGP based model, the application of FFNN improved the r(2) to 0.914. The developed model is useful in the design of materials to achieve a desired entropy value.

  4. Predicting CO2 and SO2 emissions in the Baltic States through reorganization of energy infrastructure.

    PubMed

    Denafas, Gintaras; Sitnikovas, Denisas; Galinis, Arvydas; Kudrenickis, Ivars; Klavs, Gaidis; Kuusik, Rein

    2004-10-01

    The paper deals with predicting carbon dioxide and sulphur dioxide emissions generated by power production sector in the Baltic States in period up to year 2020. The economies of Lithuania, Latvia and Estonia are rapidly growing therefore forecast of emissions related with this occurrence becomes very important. The Ignalina Nuclear Power Plant (INPP), one of the largest in the world, is situated in the region. Two power production scenarios are modelled to investigate changes in power sector's emissions expected as the consequences of the coming closure of Ignalina NPP. Power market was assumed to be common for all three Baltic countries and was modelled by applying the Balmorel model. The planned closure of Ignalina NPP will bring restructuring of Lithuania power production sector and will change also power transmission between countries. Predictive identified the potential of investments for new modern power generation technologies. At the same time, modelling results show in both scenarios that CO(2) and SO(2) emissions from power production in the Baltic region will increase. The increment of emissions is discussed in the context of meeting requirements of UNFCCC Kyoto protocol and EC Directives. Despite of CO(2) emissions increase the Kyoto protocol's requirements may be expected. At the same time, SO(2) formation in Lithuania power sector may exceed the limits of the EU Council Directive 2001/80/EB therefore the additional measures to control SO(2) emissions have to be investigated. PMID:15337350

  5. Theoretical prediction of ion conductivity in solid state HfO2

    NASA Astrophysics Data System (ADS)

    Zhang, Wei; Chen, Wen-Zhou; Sun, Jiu-Yu; Jiang, Zhen-Yi

    2013-01-01

    A theoretical prediction of ion conductivity for solid state HfO2 is carried out in analogy to ZrO2 based on the density functional calculation. Geometric and electronic structures of pure bulks exhibit similarity for the two materials. Negative formation enthalpy and negative vacancy formation energy are found for YSH (yttria-stabilized hafnia) and YSZ (yttria-stabilized zirconia), suggesting the stability of both materials. Low activation energies (below 0.7 eV) of diffusion are found in both materials, and YSH's is a little higher than that of YSZ. In addition, for both HfO2 and ZrO2, the supercells with native oxygen vacancies are also studied. The so-called defect states are observed in the supercells with neutral and +1 charge native vacancy but not in the +2 charge one. It can give an explanation to the relatively lower activation energies of yttria-doped oxides and +2 charge vacancy supercells. A brief discussion is presented to explain the different YSH ion conductivities in the experiment and obtained by us, and we attribute this to the different ion vibrations at different temperatures.

  6. Predicting freakish sea state with an operational third generation wave model

    NASA Astrophysics Data System (ADS)

    Waseda, T.; In, K.; Kiyomatsu, K.; Tamura, H.; Miyazawa, Y.; Iyama, K.

    2013-11-01

    Understanding of freak wave generation mechanism has advanced and the community has reached to a consensus that spectral geometry plays an important role. Numerous marine accident cases were studied and revealed that the narrowing of the directional spectrum is a good indicator of dangerous sea. However, the estimation of the directional spectrum depends on the performance of the third generation wave model. In this work, a well-studied marine accident case in Japan in 1980 (Onomichi-Maru incident) is revisited and the sea states are hind-casted using both the DIA and SRIAM nonlinear source terms. The result indicates that the temporal evolution of the basic parameters (directional spreading and frequency bandwidth) agree reasonably well between the two schemes and therefore most commonly used DIA method is qualitatively sufficient to predict freakish sea state. The analyses revealed that in the case of Onomichi-Maru, a moving gale system caused the spectrum to grow in energy with limited down-shifting at the accident site. This conclusion contradicts the marine inquiry report speculating that the two swell systems crossed at the accident site. The unimodal wave system grew under strong influence of local wind with a peculiar energy transfer.

  7. Predicting freakish sea state with an operational third-generation wave model

    NASA Astrophysics Data System (ADS)

    Waseda, T.; In, K.; Kiyomatsu, K.; Tamura, H.; Miyazawa, Y.; Iyama, K.

    2014-04-01

    The understanding of freak wave generation mechanisms has advanced and the community has reached a consensus that spectral geometry plays an important role. Numerous marine accident cases were studied and revealed that the narrowing of the directional spectrum is a good indicator of dangerous sea. However, the estimation of the directional spectrum depends on the performance of the third-generation wave model. In this work, a well-studied marine accident case in Japan in 1980 (Onomichi-Maru incident) is revisited and the sea states are hindcasted using both the DIA (discrete interaction approximation) and SRIAM (Simplified Research Institute of Applied Mechanics) nonlinear source terms. The result indicates that the temporal evolution of the basic parameters (directional spreading and frequency bandwidth) agree reasonably well between the two schemes and therefore the most commonly used DIA method is qualitatively sufficient to predict freakish sea state. The analyses revealed that in the case of Onomichi-Maru, a moving gale system caused the spectrum to grow in energy with limited downshifting at the accident's site. This conclusion contradicts the marine inquiry report speculating that the two swell systems crossed at the accident's site. The unimodal wave system grew under strong influence of local wind with a peculiar energy transfer.

  8. Tongue Protrusion Strength in Arousal State Is Predictive of the Airway Patency in Obstructive Sleep Apnea.

    PubMed

    Kanezaki, Masashi; Ogawa, Teruhiro; Izumi, Tadafumi

    2015-01-01

    Contraction of the genioglossus affects either tongue protrusion strength or dilating forces of the upper airway. The upper airway in patients with obstructive sleep apnea (OSA) is thought to collapse during sleep, at least in part because of a sleep related reduction in genioglossus muscle activity. Thus, although tongue protrusion strength by genioglossus activity during sleep contributes to the maintenance of airway patency in patients with OSA, the relationship between tongue protrusion strength in the arousal state and obstructive sleep apnea has not been fully elucidated. Conventional method of tongue protrusion strength cannot be used to evaluate in edentulous subjects and/or subjects with the decreased biting force. In this study, employing a novel measurement method that does not require biting a transducer, we investigated relationships between the tongue protrusion strength and polysomnographic findings. We enrolled twenty normal subjects and 26 subjects with OSA. All subjects completed the measurement of tongue protrusion strength. Each subject with OSA was evaluated by full polysomnography. The degree of tongue protrusion strength was assessed by maximum voluntary contraction against the tongue depressor connected with a strain gauge dynamometer. The tongue protrusion strength was negatively correlated with obstructive apnea time, apnea index (AI) and the percent of sleep stage 2 (r = -0.61, p < 0.0001, r = -0.41 p = 0.03 and r = -0.39 p = 0.04, respectively). Tongue protrusion strength measured in the arousal state is predictive of the airway patency during sleep in OSA.

  9. Prediction and validation of protein intermediate states from structurally rich ensembles and coarse-grained simulations

    PubMed Central

    Orellana, Laura; Yoluk, Ozge; Carrillo, Oliver; Orozco, Modesto; Lindahl, Erik

    2016-01-01

    Protein conformational changes are at the heart of cell functions, from signalling to ion transport. However, the transient nature of the intermediates along transition pathways hampers their experimental detection, making the underlying mechanisms elusive. Here we retrieve dynamic information on the actual transition routes from principal component analysis (PCA) of structurally-rich ensembles and, in combination with coarse-grained simulations, explore the conformational landscapes of five well-studied proteins. Modelling them as elastic networks in a hybrid elastic-network Brownian dynamics simulation (eBDIMS), we generate trajectories connecting stable end-states that spontaneously sample the crystallographic motions, predicting the structures of known intermediates along the paths. We also show that the explored non-linear routes can delimit the lowest energy passages between end-states sampled by atomistic molecular dynamics. The integrative methodology presented here provides a powerful framework to extract and expand dynamic pathway information from the Protein Data Bank, as well as to validate sampling methods in general. PMID:27578633

  10. Prediction and validation of protein intermediate states from structurally rich ensembles and coarse-grained simulations.

    PubMed

    Orellana, Laura; Yoluk, Ozge; Carrillo, Oliver; Orozco, Modesto; Lindahl, Erik

    2016-01-01

    Protein conformational changes are at the heart of cell functions, from signalling to ion transport. However, the transient nature of the intermediates along transition pathways hampers their experimental detection, making the underlying mechanisms elusive. Here we retrieve dynamic information on the actual transition routes from principal component analysis (PCA) of structurally-rich ensembles and, in combination with coarse-grained simulations, explore the conformational landscapes of five well-studied proteins. Modelling them as elastic networks in a hybrid elastic-network Brownian dynamics simulation (eBDIMS), we generate trajectories connecting stable end-states that spontaneously sample the crystallographic motions, predicting the structures of known intermediates along the paths. We also show that the explored non-linear routes can delimit the lowest energy passages between end-states sampled by atomistic molecular dynamics. The integrative methodology presented here provides a powerful framework to extract and expand dynamic pathway information from the Protein Data Bank, as well as to validate sampling methods in general. PMID:27578633

  11. Prediction and validation of protein intermediate states from structurally rich ensembles and coarse-grained simulations

    NASA Astrophysics Data System (ADS)

    Orellana, Laura; Yoluk, Ozge; Carrillo, Oliver; Orozco, Modesto; Lindahl, Erik

    2016-08-01

    Protein conformational changes are at the heart of cell functions, from signalling to ion transport. However, the transient nature of the intermediates along transition pathways hampers their experimental detection, making the underlying mechanisms elusive. Here we retrieve dynamic information on the actual transition routes from principal component analysis (PCA) of structurally-rich ensembles and, in combination with coarse-grained simulations, explore the conformational landscapes of five well-studied proteins. Modelling them as elastic networks in a hybrid elastic-network Brownian dynamics simulation (eBDIMS), we generate trajectories connecting stable end-states that spontaneously sample the crystallographic motions, predicting the structures of known intermediates along the paths. We also show that the explored non-linear routes can delimit the lowest energy passages between end-states sampled by atomistic molecular dynamics. The integrative methodology presented here provides a powerful framework to extract and expand dynamic pathway information from the Protein Data Bank, as well as to validate sampling methods in general.

  12. Hydrological states and fluxes in terrestrial systems: from observation to prediction (John Dalton Medal Lecture)

    NASA Astrophysics Data System (ADS)

    Vereecken, Harry

    2016-04-01

    Quantification and prediction of hydrological processes requires information on the spatial and temporal distribution of soil water fluxes and soil water content. The access to spatially and temporally highly resolved soil water content and fluxes is needed to adequately test hydrological hypotheses and to validate hydrological models. In this presentation we will discuss new developments for the determination of soil water content and quantification and prediction of hydrological fluxes based on hydrogeophysical measurement techniques and novel ground- and satellite based sensing platforms. At the field scale, ground penetrating radar and passive microwave methods are presently being developed which provide the possibility to map soil water content with a high spatial and temporal resolution, also in the subsurface environment. Recent developments show that the application of full wave form inversion methods is a unique technique to derive soil water and soil hydraulic parameters from on- and off-ground systems with high spatial resolution. At the small catchment scale, wireless sensor networks are presently being developed providing soil moisture content values with a high spatial and temporal resolution. Stochastic theories have been used to interpret the relationship between average soil water content and its standard deviation. Cosmic ray sensors are presently being deployed within the TERENO observatories. These sensors provide soil moisture content values with a high temporal resolution at a scale of one to two hundred meters, thereby bridging the gap between local scale measurements and remote sensing platforms. Cosmic ray probes are extremely valuable for the determination of soil water content in agriculturally managed soils. Data assimilation methods provide a unique approach to fully exploit the value of spatially and temporally highly resolved soil water content measurements and states of the terrestrial system for the prediction of hydrological fluxes

  13. Reduced-representation Phosphosignatures Measured by Quantitative Targeted MS Capture Cellular States and Enable Large-scale Comparison of Drug-induced Phenotypes.

    PubMed

    Abelin, Jennifer G; Patel, Jinal; Lu, Xiaodong; Feeney, Caitlin M; Fagbami, Lola; Creech, Amanda L; Hu, Roger; Lam, Daniel; Davison, Desiree; Pino, Lindsay; Qiao, Jana W; Kuhn, Eric; Officer, Adam; Li, Jianxue; Abbatiello, Susan; Subramanian, Aravind; Sidman, Richard; Snyder, Evan; Carr, Steven A; Jaffe, Jacob D

    2016-05-01

    Profiling post-translational modifications represents an alternative dimension to gene expression data in characterizing cellular processes. Many cellular responses to drugs are mediated by changes in cellular phosphosignaling. We sought to develop a common platform on which phosphosignaling responses could be profiled across thousands of samples, and created a targeted MS assay that profiles a reduced-representation set of phosphopeptides that we show to be strong indicators of responses to chemical perturbagens.To develop the assay, we investigated the coordinate regulation of phosphosites in samples derived from three cell lines treated with 26 different bioactive small molecules. Phosphopeptide analytes were selected from these discovery studies by clustering and picking 1 to 2 proxy members from each cluster. A quantitative, targeted parallel reaction monitoring assay was developed to directly measure 96 reduced-representation probes. Sample processing for proteolytic digestion, protein quantification, peptide desalting, and phosphopeptide enrichment have been fully automated, making possible the simultaneous processing of 96 samples in only 3 days, with a plate phosphopeptide enrichment variance of 12%. This highly reproducible process allowed ∼95% of the reduced-representation phosphopeptide probes to be detected in ∼200 samples.The performance of the assay was evaluated by measuring the probes in new samples generated under treatment conditions from discovery experiments, recapitulating the observations of deeper experiments using a fraction of the analytical effort. We measured these probes in new experiments varying the treatments, cell types, and timepoints to demonstrate generalizability. We demonstrated that the assay is sensitive to disruptions in common signaling pathways (e.g. MAPK, PI3K/mTOR, and CDK). The high-throughput, reduced-representation phosphoproteomics assay provides a platform for the comparison of perturbations across a range of

  14. 48 CFR 2009.570-4 - Representation.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... ACQUISITION PLANNING CONTRACTOR QUALIFICATIONS Organizational Conflicts of Interest 2009.570-4 Representation... whether situations or relationships exist which may constitute organizational conflicts of interest with... criteria stated in the following paragraph (b) of this section. (b) The organizational conflicts...

  15. 48 CFR 2009.570-4 - Representation.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... ACQUISITION PLANNING CONTRACTOR QUALIFICATIONS Organizational Conflicts of Interest 2009.570-4 Representation... whether situations or relationships exist which may constitute organizational conflicts of interest with... criteria stated in the following paragraph (b) of this section. (b) The organizational conflicts...

  16. 48 CFR 2009.570-4 - Representation.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... ACQUISITION PLANNING CONTRACTOR QUALIFICATIONS Organizational Conflicts of Interest 2009.570-4 Representation... whether situations or relationships exist which may constitute organizational conflicts of interest with... criteria stated in the following paragraph (b) of this section. (b) The organizational conflicts...

  17. 48 CFR 2009.570-4 - Representation.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... ACQUISITION PLANNING CONTRACTOR QUALIFICATIONS Organizational Conflicts of Interest 2009.570-4 Representation... whether situations or relationships exist which may constitute organizational conflicts of interest with... criteria stated in the following paragraph (b) of this section. (b) The organizational conflicts...

  18. State dependent model predictive control for orbital rendezvous using pulse-width pulse-frequency modulated thrusters

    NASA Astrophysics Data System (ADS)

    Li, Peng; Zhu, Zheng H.; Meguid, S. A.

    2016-07-01

    This paper studies the pulse-width pulse-frequency modulation based trajectory planning for orbital rendezvous and proximity maneuvering near a non-cooperative spacecraft in an elliptical orbit. The problem is formulated by converting the continuous control input, output from the state dependent model predictive control, into a sequence of pulses of constant magnitude by controlling firing frequency and duration of constant-magnitude thrusters. The state dependent model predictive control is derived by minimizing the control error of states and control roughness of control input for a safe, smooth and fuel efficient approaching trajectory. The resulting nonlinear programming problem is converted into a series of quadratic programming problem and solved by numerical iteration using the receding horizon strategy. The numerical results show that the proposed state dependent model predictive control with the pulse-width pulse-frequency modulation is able to effectively generate optimized trajectories using equivalent control pulses for the proximity maneuvering with less energy consumption.

  19. Representational and Executive Selection Resources in "Theory of Mind": Evidence from Compromised Belief-Desire Reasoning in Old Age

    ERIC Educational Resources Information Center

    German, Tim P.; Hehman, Jessica A.

    2006-01-01

    Effective belief-desire reasoning requires both specialized representational capacities--the capacity to represent the mental states as such--as well as executive selection processes for accurate performance on tasks requiring the prediction and explanation of the actions of social agents. Compromised belief-desire reasoning in a given population…

  20. On Performance Skill Representation Framework

    NASA Astrophysics Data System (ADS)

    Furukawa, Koichi; Shimizu, Satoshi; Yoshinaga, Saori

    In this paper, we propose a framework for representing performance skill. Firstly, we notice the importance of performance skill representation. We introduce five different representation targets: performance tasks, performance rules, pre-shaping actions, dynamic integrity constraints, and performance states. Performance task description consists of a sequence of performance tasks and expressions. It acts as a goal description in planning. Performance rules describe model performance methods for given tasks including how to shape body parts and how to use various muscles. Pre-shaping action rules are similar to performance rules. Its role is to pre-shape in between consecutive tasks to prepare for the next task. Dynamic integrity constraints specify constraints to be satisfied during performance. They provide such general rules as prohibiting simultaneous strong activations of agonist and antagonist. Performance states are for describing real performance done by players including professionals and amateurs. The aim of the framework is to provide a uniform scheme for representing model performance methods given performance score such as music score. The representation framework will define targets of inducing formal skill rules as well as describing performance states automatically from biomechanical performance data. It also is related to a fundamental research issue of attributes finding/selection in discovering useful rules for skillful performance. We conclude our paper by stating future research direction.

  1. Multiple genetic variants predict steady-state nevirapine clearance in HIV-infected Cambodians

    PubMed Central

    Bertrand, Julie; Chou, Monidarin; Richardson, Danielle M.; Verstuyft, Céline; Leger, Paul D.; Mentré, France; Taburet, Anne-Marie; Haas, David W.

    2013-01-01

    Objective In a previous analysis involving protocol ANRS 12154, interindividual variability in steady-state nevirapine clearance among HIV-infected Cambodians was partially explained by CYP2B6 516G→T (CYP2B6*6). Here, we examine whether additional genetic variants predict nevirapine clearance in this cohort. Methods Analyses included Phnom Penh ESTHER (Ensemble pour une Solidarité Thérapeutique Hospitalière en Réseau) cohort participants who had consented for genetic testing. All participants were receiving nevirapine plus two nucleoside analogs. The mean individual nevirapine clearance estimates were derived from a population model developed on nevirapine concentrations at 18 and 36 months of therapy. Polymorphisms were assayed in ABCB1, CYP2A6, CYP2B6, CYP2C19, CYP3A4, CYP3A5, and NR1I2. Results Of 198 assayed loci, 130 were polymorphic. Among 129 individuals with evaluable genetic data, nevirapine clearance ranged from 1.06 to 5.00 l/h in 128 individuals and was 7.81 l/h in one individual. In bivariate linear regression, CYP2B6 516G→T (CYP2B6*6) was associated with lower nevirapine clearances (P = 3.5 × 10–6). In a multivariate linear regression model conditioned on CYP2B6 516G→T, independent associations were identified with CYP2B6 rs7251950, CYP2B6 rs2279343, and CYP3A4 rs2687116. The CYP3A4 association disappeared after censoring the outlier clearance value. A model that included CYP2B6 516G→T (P = 1.0 × 10–9), rs7251950 (P = 4.8 × 10–5), and rs2279343 (P = 7.1 × 10–5) explained 11% of interindividual variability in nevirapine clearance. Conclusion Among HIV-infected Cambodians, several CYP2B6 polymorphisms were associated independently with steady-state nevirapine clearance. The prediction of nevirapine clearance was improved by considering several polymorphisms in combination. PMID:23104099

  2. Comparing Observed with Predicted Weekly Influenza-Like Illness Rates during the Winter Holiday Break, United States, 2004-2013

    PubMed Central

    Gao, Hongjiang; Wong, Karen K.; Zheteyeva, Yenlik; Shi, Jianrong; Uzicanin, Amra; Rainey, Jeanette J.

    2015-01-01

    In the United States, influenza season typically begins in October or November, peaks in February, and tapers off in April. During the winter holiday break, from the end of December to the beginning of January, changes in social mixing patterns, healthcare-seeking behaviors, and surveillance reporting could affect influenza-like illness (ILI) rates. We compared predicted with observed weekly ILI to examine trends around the winter break period. We examined weekly rates of ILI by region in the United States from influenza season 2003–2004 to 2012–2013. We compared observed and predicted ILI rates from week 44 to week 8 of each influenza season using the auto-regressive integrated moving average (ARIMA) method. Of 1,530 region, week, and year combinations, 64 observed ILI rates were significantly higher than predicted by the model. Of these, 21 occurred during the typical winter holiday break period (weeks 51–52); 12 occurred during influenza season 2012–2013. There were 46 observed ILI rates that were significantly lower than predicted. Of these, 16 occurred after the typical holiday break during week 1, eight of which occurred during season 2012–2013. Of 90 (10 HHS regions x 9 seasons) predictions during the peak week, 78 predicted ILI rates were lower than observed. Out of 73 predictions for the post-peak week, 62 ILI rates were higher than observed. There were 53 out of 73 models that had lower peak and higher post-peak predicted ILI rates than were actually observed. While most regions had ILI rates higher than predicted during winter holiday break and lower than predicted after the break during the 2012–2013 season, overall there was not a consistent relationship between observed and predicted ILI around the winter holiday break during the other influenza seasons. PMID:26649568

  3. Predicting heat waves and cold snaps in the United States across multiple time scales

    NASA Astrophysics Data System (ADS)

    Guirguis, K.; Gershunov, A.; Schwartz, R.

    2011-12-01

    Wintertime cold snaps and summertime heat waves increase energy demand and draw heavily on emergency resources of state and local governments. Adequate planning for these events requires improved predictions on timescales beyond the short range where numerical models perform well. Comprehensive probabilistic tools relating temperature extremes to weather/climate conditions on multiple time scales from the extended range to seasonal-scales and longer are needed. We have quantified heat waves and cold snaps for different regions of the U.S. over a 60-year period and used a probabilistic approach to relate these historic events to precursor weather patterns. Using principal components analysis applied to atmospheric data from NCEP Reanalysis, we identified circulation patterns (predictors) that precede extreme cold/heat events at various lead times in the range of 0-35 days. By studying the evolution of predictor patterns, we find subtle but important differences in the atmospheric states that lead to an extreme temperature event versus those that are not followed by such an event. In some cases, low-frequency climate forcing appears to modulate whether an extreme temperature event develops in the extended range, which may provide a link between seasonal and subseasonal scales. To address long-term planning, we apply the methodology to model simulations under different climate change scenarios to determine if the same relationships exist between predictor patterns and cold/heat events in the historical period and if/how we can expect these relationships to change in a future climate. These results have applications for operational forecasting of extreme temperatures, particular for energy load forecasting, as well as for short- and long-term emergency resource planning.

  4. Computer aided surface representation

    SciTech Connect

    Barnhill, R.E.

    1991-04-02

    Modern computing resources permit the generation of large amounts of numerical data. These large data sets, if left in numerical form, can be overwhelming. Such large data sets are usually discrete points from some underlying physical phenomenon. Because we need to evaluate the phenomenon at places where we don't have data, a continuous representation (a surface'') is required. A simple example is a weather map obtained from a discrete set of weather stations. (For more examples including multi-dimensional ones, see the article by Dr. Rosemary Chang in the enclosed IRIS Universe). In order to create a scientific structure encompassing the data, we construct an interpolating mathematical surface which can evaluate at arbitrary locations. We can also display and analyze the results via interactive computer graphics. In our research we construct a very wide variety of surfaces for applied geometry problems that have sound theoretical foundations. However, our surfaces have the distinguishing feature that they are constructed to solve short or long term practical problems. This DOE-funded project has developed the premiere research team in the subject of constructing surfaces (3D and higher dimensional) that provide smooth representations of real scientific and engineering information, including state of the art computer graphics visualizations. However, our main contribution is in the development of fundamental constructive mathematical methods and visualization techniques which can be incorporated into a wide variety of applications. This project combines constructive mathematics, algorithms, and computer graphics, all applied to real problems. The project is a unique resource, considered by our peers to be a de facto national center for this type of research.

  5. Aggregate-level analysis and prediction of midterm senatorial elections in the United States, 1974-1986.

    PubMed

    Lichtman, A J; Keilis-Borok, V I

    1989-12-01

    Pattern recognition study demonstrates that the outcomes of American midterm senatorial elections follow the dynamics of simple integral parameters that depict preelectoral situations aggregated to the state as a whole. A set of "commonsense" parameters is identified that is sufficient to predict such elections state-by-state and year-by-year. The analysis rejects many similar commonsense parameters. The existence and nature of integral collective behavior in U.S. elections at the level of the individual states is investigated. Implications for understanding the American electoral process are discussed. PMID:2602365

  6. A steady-state simulation methodology for predicting runaway speed in Francis turbines

    NASA Astrophysics Data System (ADS)

    Hosseinimanesh, H.; Vu, T. C.; Devals, C.; Nennemann, B.; Guibault, F.

    2014-03-01

    Runaway speed is an important performance factor for the safe operation of hydropower systems. In turbine design, the manufacturers must conduct several model tests to calculate the accurate value of runaway speed for the complete range of operating conditions, which are expensive and time-consuming. To study runaway conditions, the application of numerical tools such as unsteady CFD simulations can help to better understand the complex flow physics during transient processes. However, unsteady simulations require significant computational effort to compute accurate values of runaway speed due to difficulties related to unsteady turbulent flow modelling and instabilities. The present study presents a robust methodology based on steady-state RANS flow simulations capable of predicting the runaway speed of a Francis turbine with an adequate level of accuracy and in a reasonable simulation time. The simulations are implemented using a commercial flow solver and an iterative algorithm that relies on a smooth relation between turbine torque and speed coefficient. The impact of friction has been considered when estimating turbine torque, in order to improve the accuracy. The results of this study show good agreement with experiments.

  7. On the robustness of near term climate predictability regarding initial state uncertainties

    NASA Astrophysics Data System (ADS)

    Germe, Agathe; Sévellec, Florian; Mignot, Juliette; Swingedouw, Didier; Nguyen, Sebastien

    2016-03-01

    A set of four ensemble simulations has been designed to assess the relative importance of atmospheric, oceanic, and deep ocean initial state uncertainties, as represented by spatial white noise perturbations, on seasonal to decadal prediction skills in a perfect model framework. It is found that a perturbation mimicking random oceanic uncertainties have the same impact as an atmospheric-only perturbation on the future evolution of the ensemble after the first 3 months, even if they are initially only located in the deep ocean. This is due to the fast (1 month) perturbation of the atmospheric component regardless of the initial ensemble generation strategy. The divergence of the ensemble upper-ocean characteristics is then mainly induced by ocean-atmosphere interactions. While the seasonally varying mixed layer depth allows the penetration of the different signals in the thermocline in the mid-high latitudes, the rapid adjustment of the thermocline to wind anomalies followed by Kelvin and Rossby waves adjustment dominates the growth of the ensemble spread in the tropics. These mechanisms result in similar ensemble distribution characteristics for the four ensembles design strategy at the interannual timescale.

  8. Predicting onset and duration of airborne allergenic pollen season in the United States

    NASA Astrophysics Data System (ADS)

    Zhang, Yong; Bielory, Leonard; Cai, Ting; Mi, Zhongyuan; Georgopoulos, Panos

    2015-02-01

    Allergenic pollen is one of the main triggers of Allergic Airway Disease (AAD) affecting 5%-30% of the population in industrialized countries. A modeling framework has been developed using correlation and collinearity analyses, simulated annealing, and stepwise regression based on nationwide observations of airborne pollen counts and climatic factors to predict the onsets and durations of allergenic pollen seasons of representative trees, weeds and grass in the contiguous United States. Main factors considered are monthly, seasonal and annual mean temperatures and accumulative precipitations, latitude, elevation, Growing Degree Day (GDD), Frost Free Day (FFD), Start Date (SD) and Season Length (SL) in the previous year. The estimated mean SD and SL for birch (Betula), oak (Quercus), ragweed (Ambrosia), mugwort (Artemisia) and grass (Poaceae) pollen season in 1994-2010 are mostly within 0-6 days of the corresponding observations for the majority of the National Allergy Bureau (NAB) monitoring stations across the contiguous US. The simulated spatially resolved maps for onset and duration of allergenic pollen season in the contiguous US are consistent with the long term observations.

  9. Cumulative activation during positive and negative events and state anxiety predicts subsequent inertia of amygdala reactivity.

    PubMed

    Pichon, Swann; Miendlarzewska, Ewa A; Eryilmaz, Hamdi; Vuilleumier, Patrik

    2015-02-01

    Inertia, together with intensity and valence, is an important component of emotion. We tested whether positive and negative events generate lingering changes in subsequent brain responses to unrelated threat stimuli and investigated the impact of individual anxiety. We acquired fMRI data while participants watched positive or negative movie-clips and subsequently performed an unrelated task with fearful and neutral faces. We quantified changes in amygdala reactivity to fearful faces as a function of the valence of preceding movies and cumulative neural activity evoked during them. We demonstrate that amygdala responses to emotional movies spill over to subsequent processing of threat information in a valence-specific manner: negative movies enhance later amygdala activation whereas positive movies attenuate it. Critically, the magnitude of such changes is predicted by a measure of cumulative amygdala responses to the preceding positive or negative movies. These effects appear independent of overt attention, are regionally limited to amygdala, with no changes in functional connectivity. Finally, individuals with higher state anxiety displayed stronger modulation of amygdala reactivity by positive movies. These results suggest that intensity and valence of emotional events as well as anxiety levels promote local changes in amygdala sensitivity to threat, highlighting the importance of past experience in shaping future affective reactivity.

  10. Predicting Onset and Duration of Airborne Allergenic Pollen Season in the United States

    PubMed Central

    Zhang, Yong; Bielory, Leonard; Cai, Ting; Mi, Zhongyuan; Georgopoulos, Panos

    2014-01-01

    Allergenic pollen is one of the main triggers of Allergic Airway Disease (AAD) affecting 5% to 30% of the population in industrialized countries. A modeling framework has been developed using correlation and collinearity analyses, simulated annealing, and stepwise regression based on nationwide observations of airborne pollen counts and climatic factors to predict the onsets and durations of allergenic pollen seasons of representative trees, weeds and grass in the contiguous United States. Main factors considered are monthly, seasonal and annual mean temperatures and accumulative precipitations, latitude, elevation, Growing Degree Day (GDD), Frost Free Day (FFD), Start Date (SD) and Season Length (SL) in the previous year. The estimated mean SD and SL for birch (Betula), oak (Quercus), ragweed (Ambrosia), mugwort (Artemisia) and grass (Poaceae) pollen season in 1994–2010 are mostly within 0 to 6 days of the corresponding observations for the majority of the National Allergy Bureau (NAB) monitoring stations across the contiguous US. The simulated spatially resolved maps for onset and duration of allergenic pollen season in the contiguous US are consistent with the long term observations. PMID:25620875

  11. Efficient prediction of terahertz quantum cascade laser dynamics from steady-state simulations

    SciTech Connect

    Agnew, G.; Lim, Y. L.; Nikolić, M.; Rakić, A. D.; Grier, A.; Valavanis, A.; Cooper, J.; Dean, P.; Khanna, S. P.; Lachab, M.; Linfield, E. H.; Davies, A. G.; Ikonić, Z.; Indjin, D.; Taimre, T.; Harrison, P.

    2015-04-20

    Terahertz-frequency quantum cascade lasers (THz QCLs) based on bound-to-continuum active regions are difficult to model owing to their large number of quantum states. We present a computationally efficient reduced rate equation (RE) model that reproduces the experimentally observed variation of THz power with respect to drive current and heat-sink temperature. We also present dynamic (time-domain) simulations under a range of drive currents and predict an increase in modulation bandwidth as the current approaches the peak of the light–current curve, as observed experimentally in mid-infrared QCLs. We account for temperature and bias dependence of the carrier lifetimes, gain, and injection efficiency, calculated from a full rate equation model. The temperature dependence of the simulated threshold current, emitted power, and cut-off current are thus all reproduced accurately with only one fitting parameter, the interface roughness, in the full REs. We propose that the model could therefore be used for rapid dynamical simulation of QCL designs.

  12. Amplitude of low frequency fluctuations during resting state predicts social well-being.

    PubMed

    Kong, Feng; Xue, Song; Wang, Xu

    2016-07-01

    Social well-being represents primarily public phenomena, which is crucial for mental and physical health. However, little is known about the neural basis of this construct, especially how it is maintained during resting state. To explore the neural correlates of social well-being, this study correlated the regional fractional amplitude of low frequency fluctuations (fALFF) with social well-being of healthy individuals. The results revealed that the fALFF in the bilateral posterior superior temporal gyrus (pSTG), right anterior cingulate cortex (ACC), right thalamus and right insula positively predicted individual differences in social well-being. Furthermore, we demonstrated the different role of three pursuits of human well-being (i.e., pleasure, meaning and engagement) in these associations. Specifically, the pursuits of meaning and engagement, not pleasure mediated the effect of the fALFF in right pSTG on social well-being, whereas the pursuit of engagement mediated the effect of the fALFF in right thalamus on social well-being. Taken together, we provide the first evidence that spontaneous brain activity in multiple regions related to self-regulatory and social-cognitive processes contributes to social well-being, suggesting that the spontaneous activity of the human brain reflects the efficiency of social well-being.

  13. Seasonal prediction of hurricane activity reaching the coast of the United States.

    PubMed

    Saunders, Mark A; Lea, Adam S

    2005-04-21

    Much of the property damage from natural hazards in the United States is caused by landfalling hurricanes--strong tropical cyclones that reach the coast. For the southeastern Atlantic coast of the US, a statistical method for forecasting the occurrence of landfalling hurricanes for the season ahead has been reported, but the physical mechanisms linking the predictor variables to the frequency of hurricanes remain unclear. Here we present a statistical model that uses July wind anomalies between 1950 and 2003 to predict with significant and useful skill the wind energy of US landfalling hurricanes for the following main hurricane season (August to October). We have identified six regions over North America and over the east Pacific and North Atlantic oceans where July wind anomalies, averaged between heights of 925 and 400 mbar, exhibit a stationary and significant link to the energy of landfalling hurricanes during the subsequent hurricane season. The wind anomalies in these regions are indicative of atmospheric circulation patterns that either favour or hinder evolving hurricanes from reaching US shores.

  14. Solubility prediction of carbon dioxide in water by an iterative equation of state/excess Gibbs energy model

    NASA Astrophysics Data System (ADS)

    Suleman, H.; Maulud, A. S.; Man, Z.

    2016-06-01

    The solubility of carbon dioxide in water has been predicted extensively by various models, owing to their vast applications in process industry. Henry's law has been widely utilized for solubility prediction with good results at low pressure. However, the law shows large deviations at high pressure, even when adjusted to pressure correction and improved conditions. Contrarily, equations of state/excess Gibbs energy models are a promising addition to thermodynamic models for prediction at high pressure non-ideal equilibria. These models can efficiently predict solubilities at high pressures, even when the experimental solubilities are not corroborated. Hence, these models work iteratively, utilizing the mathematical redundancy of local composition excess Gibbs energy models. In this study, an iterative form of Linear Combination of Vidal and Michelsen (LCVM) mixing rule has been used for prediction of carbon dioxide solubility in water, in conjunction with UNIFAC and translated modified Peng- Robinson equation of state. The proposed model, termed iterative LCVM (i-LCVM), predicts carbon dioxide solubility in water for a wide range of temperature (273 to 453 K) and pressure (101.3 to 7380 kPa). The i-LCVM shows good agreement with experimental values and predicts better than Henry's law (53% improvement).

  15. XML-BASED REPRESENTATION

    SciTech Connect

    R. KELSEY

    2001-02-01

    For focused applications with limited user and use application communities, XML can be the right choice for representation. It is easy to use, maintain, and extend and enjoys wide support in commercial and research sectors. When the knowledge and information to be represented is object-based and use of that knowledge and information is a high priority, then XML-based representation should be considered. This paper discusses some of the issues involved in using XML-based representation and presents an example application that successfully uses an XML-based representation.

  16. Converting Boundary Representation Solid Models to Half-Space Representation Models for Monte Carlo Analysis

    SciTech Connect

    Davis JE, Eddy MJ, Sutton TM, Altomari TJ

    2007-03-01

    Solid modeling computer software systems provide for the design of three-dimensional solid models used in the design and analysis of physical components. The current state-of-the-art in solid modeling representation uses a boundary representation format in which geometry and topology are used to form three-dimensional boundaries of the solid. The geometry representation used in these systems is cubic B-spline curves and surfaces--a network of cubic B-spline functions in three-dimensional Cartesian coordinate space. Many Monte Carlo codes, however, use a geometry representation in which geometry units are specified by intersections and unions of half-spaces. This paper describes an algorithm for converting from a boundary representation to a half-space representation.

  17. Connecting Representations: Using Predict, Check, Explain

    ERIC Educational Resources Information Center

    Roy, George J.; Fueyo, Vivian; Vahey, Philip; Knudsen, Jennifer; Rafanan, Ken; Lara-Meloy, Teresa

    2016-01-01

    Although educators agree that making connections with the real world, as advocated by "Principles to Actions: Ensuring Mathematical Success for All" (NCTM 2014), is important, making such connections while addressing important mathematics is elusive. The authors have found that math content coupled with the instructional strategy of…

  18. Multiscale Prediction and Verification of Water Fluxes and States over Large River Basins

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    Developing the ability to predict streamflow at various scales is a key step for improving our understanding of the water balance and the skill of hydrologic models (HM). To cope with this grand challenge, we postulate: 1) validating a HM only against an integral basin response such as streamflow is a necessary but not a sufficient condition to warranty the proper partitioning of incoming precipitation and net-radiation into different water storage components and fluxes, 2 proper partitioning can be ensured by using additional multi-scale observations during parameter estimation (PE), and 3) HM should be evaluated at locations and scales different from those used for PE to ensure transferability. Water fluxes and states variables are estimated over the Pan-EU with the mesoscale hydrologic model (mHM). Its main features are the treatment of the sub-grid variability of input variables and model parameters and the possibility to estimate fluxes in nested-scales and/or in multiple basins keeping its regionalization coefficients unaltered across scales and basins. These essencial features allow to simulate fluxes and states and to evaluate them with disparate sources of information such as satellite, streamflow, and eddy covariance data at their native resolutions. mHM was setup over more than 340 Pan-European river basins. This model was forced with the gridded EOBS data set (1/4º, ECA&D) for the period 1950-2012. Morphological data was derived from the FAO soil map (1:5000000), the SRTM DEM (500 m), CORINE land cover (500 m), and MODIS LAI. The multi-scale evaluation was carried out using latent heat (LH) from FLUXNET stations and LandFlux-EVAL (1/2º), runoff from GRDC gauging stations, soil moisture from ESA-CCI (1/4º), total water storage (TWS) anomalies from GRACE (1º) and groundwater (GW) stage stations. Results lead to the conclusion that mHM water fluxes are robust since less than 25% of river basins exhibit Nash-Sutcliffe efficiencies of 0.5 or less

  19. Prediction of the Chapman-Jouguet chemical equilibrium state in a detonation wave from first principles based reactive molecular dynamics.

    PubMed

    Guo, Dezhou; Zybin, Sergey V; An, Qi; Goddard, William A; Huang, Fenglei

    2016-01-21

    The combustion or detonation of reacting materials at high temperature and pressure can be characterized by the Chapman-Jouguet (CJ) state that describes the chemical equilibrium of the products at the end of the reaction zone of the detonation wave for sustained detonation. This provides the critical properties and product kinetics for input to macroscale continuum simulations of energetic materials. We propose the ReaxFF Reactive Dynamics to CJ point protocol (Rx2CJ) for predicting the CJ state parameters, providing the means to predict the performance of new materials prior to synthesis and characterization, allowing the simulation based design to be done in silico. Our Rx2CJ method is based on atomistic reactive molecular dynamics (RMD) using the QM-derived ReaxFF force field. We validate this method here by predicting the CJ point and detonation products for three typical energetic materials. We find good agreement between the predicted and experimental detonation velocities, indicating that this method can reliably predict the CJ state using modest levels of computation.

  20. Prediction of the Chapman-Jouguet chemical equilibrium state in a detonation wave from first principles based reactive molecular dynamics.

    PubMed

    Guo, Dezhou; Zybin, Sergey V; An, Qi; Goddard, William A; Huang, Fenglei

    2016-01-21

    The combustion or detonation of reacting materials at high temperature and pressure can be characterized by the Chapman-Jouguet (CJ) state that describes the chemical equilibrium of the products at the end of the reaction zone of the detonation wave for sustained detonation. This provides the critical properties and product kinetics for input to macroscale continuum simulations of energetic materials. We propose the ReaxFF Reactive Dynamics to CJ point protocol (Rx2CJ) for predicting the CJ state parameters, providing the means to predict the performance of new materials prior to synthesis and characterization, allowing the simulation based design to be done in silico. Our Rx2CJ method is based on atomistic reactive molecular dynamics (RMD) using the QM-derived ReaxFF force field. We validate this method here by predicting the CJ point and detonation products for three typical energetic materials. We find good agreement between the predicted and experimental detonation velocities, indicating that this method can reliably predict the CJ state using modest levels of computation. PMID:26688211

  1. Human Leg Model Predicts Muscle Forces, States, and Energetics during Walking

    PubMed Central

    Markowitz, Jared; Herr, Hugh

    2016-01-01

    Humans employ a high degree of redundancy in joint actuation, with different combinations of muscle and tendon action providing the same net joint torque. Both the resolution of these redundancies and the energetics of such systems depend on the dynamic properties of muscles and tendons, particularly their force-length relations. Current walking models that use stock parameters when simulating muscle-tendon dynamics tend to significantly overestimate metabolic consumption, perhaps because they do not adequately consider the role of elasticity. As an alternative, we posit that the muscle-tendon morphology of the human leg has evolved to maximize the metabolic efficiency of walking at self-selected speed. We use a data-driven approach to evaluate this hypothesis, utilizing kinematic, kinetic, electromyographic (EMG), and metabolic data taken from five participants walking at self-selected speed. The kinematic and kinetic data are used to estimate muscle-tendon lengths, muscle moment arms, and joint moments while the EMG data are used to estimate muscle activations. For each subject we perform an optimization using prescribed skeletal kinematics, varying the parameters that govern the force-length curve of each tendon as well as the strength and optimal fiber length of each muscle while seeking to simultaneously minimize metabolic cost and maximize agreement with the estimated joint moments. We find that the metabolic cost of transport (MCOT) values of our participants may be correctly matched (on average 0.36±0.02 predicted, 0.35±0.02 measured) with acceptable joint torque fidelity through application of a single constraint to the muscle metabolic budget. The associated optimal muscle-tendon parameter sets allow us to estimate the forces and states of individual muscles, resolving redundancies in joint actuation and lending insight into the potential roles and control objectives of the muscles of the leg throughout the gait cycle. PMID:27175486

  2. Analytical predictions of the temperature profile within semiconductor nanostructures for solid-state laser refrigeration

    NASA Astrophysics Data System (ADS)

    Smith, Bennett E.; Zhou, Xuezhe; Davis, E. James; Pauzauskie, Peter J.

    2016-03-01

    The laser refrigeration of solid-state materials with nanoscale dimensions has been demonstrated for both semi- conducting (cadmium sulfide, CdS) and insulating dielectrics (Yb:YLiF4, YLF) in recent years. During laser refrigeration it is possible to observe morphology dependent resonances (MDRs), analogous to what is well- known in classical (Mie) light scattering theory, when the characteristic dimensions of the nanostructure are comparable to the wavelength of light used to initiate the laser cooling process. Mie resonances can create substantial increases for internal optical fields within a given nanostructure with the potential to enhance the absorption efficiency at the beginning of the cooling cycle. Recent breakthroughs in the laser refrigeration of semiconductor nanostructures have relied on materials that exhibit rectangular symmetry (nanoribbons). Here, we will present recent analytical, closed-form solutions to the energy partial differential equation that can be used to calculate the internal spatial temperature profile with a given semiconductor nanoribbon during irradiation by a continuous-wave laser. First, the energy equation is made dimensionless through the substitution of variables before being solved using the classical separation-of-variables approach. In particular, calculations will be presented for chalcogenide (CdS) nanoribbons using a pump wavelength of 1064 nm. For nanostructures with lower symmetry (such as YLF truncated tetragonal bipyramids) it is also possible to observe MDRs through numerical simulations using either the discrete dipole approximation or finite-difference time-domain simulations, and the resulting temperature profile can be calculated using the finite element method. Theoretical predictions are presented using parameters that will allow comparison with experimental data in the near future.

  3. Improving the Prediction of Baseflows in the Driftless Area of the Upper Midwestern United States

    NASA Astrophysics Data System (ADS)

    Schuster, Z.; Potter, K. W.

    2014-12-01

    The Driftless Area of the Upper Midwestern United States is a unique region that was not glaciated during the Quaternary Period. Groundwater discharges in the hilly landscape support over 4,000 miles of coldwater, high-class trout streams that are a destination for anglers across the Midwest. Temperature increases due to anthropogenic climate change are predicted to have a negative impact on the cold water thermal regimes that support species such as brook and brown trout. Previous work has concluded that the hillslopes in the region play an important role in producing the recharge that supports cool groundwater discharges concentrated in the headwaters of these streams. In this study, we used a set of baseflow measurements recorded by Potter and Gaffield (2001) in the headwaters of a Driftless Area stream and a simple Geographic Information Systems (GIS) analysis to assess the relationship between the percentage of hillslope in a watershed and average unit baseflow. We found that there is a strong correlation between the hillslope percentage and the unit baseflow values from the Potter and Gaffield (2001) study. Further work is needed to verify the findings of this study and to assess the impacts of the underlying geological layers on the production of baseflow, but these results provide a first step in understanding the conditions that produce spatial variability in baseflow conditions in the Driftless Area. Agencies such as the Wisconsin Department of Natural Resources are beginning to plan for climate change adaptation in the region to protect the coldwater fisheries, so understanding the hydrology of headwater streams will be important in helping to identify areas with high, coldwater baseflow discharges that can provided refugia for coldwater species.

  4. Fluctuations of spontaneous EEG topographies predict disease state in relapsing-remitting multiple sclerosis.

    PubMed

    Gschwind, Markus; Hardmeier, Martin; Van De Ville, Dimitri; Tomescu, Miralena I; Penner, Iris-Katharina; Naegelin, Yvonne; Fuhr, Peter; Michel, Christoph M; Seeck, Margitta

    2016-01-01

    Spontaneous fluctuations of neuronal activity in large-scale distributed networks are a hallmark of the resting brain. In relapsing-remitting multiple sclerosis (RRMS) several fMRI studies have suggested altered resting-state connectivity patterns. Topographical EEG analysis reveals much faster temporal fluctuations in the tens of milliseconds time range (termed "microstates"), which showed altered properties in a number of neuropsychiatric conditions. We investigated whether these microstates were altered in patients with RRMS, and if the microstates' temporal properties reflected a link to the patients' clinical features. We acquired 256-channel EEG in 53 patients (mean age 37.6 years, 45 females, mean disease duration 9.99 years, Expanded Disability Status Scale ≤ 4, mean 2.2) and 49 healthy controls (mean age 36.4 years, 33 females). We analyzed segments of a total of 5 min of EEG during resting wakefulness and determined for both groups the four predominant microstates using established clustering methods. We found significant differences in the temporal dynamics of two of the four microstates between healthy controls and patients with RRMS in terms of increased appearance and prolonged duration. Using stepwise multiple linear regression models with 8-fold cross-validation, we found evidence that these electrophysiological measures predicted a patient's total disease duration, annual relapse rate, disability score, as well as depression score, and cognitive fatigue measure. In RRMS patients, microstate analysis captured altered fluctuations of EEG topographies in the sub-second range. This measure of high temporal resolution provided potentially powerful markers of disease activity and neuropsychiatric co-morbidities in RRMS. PMID:27625987

  5. Human Leg Model Predicts Muscle Forces, States, and Energetics during Walking.

    PubMed

    Markowitz, Jared; Herr, Hugh

    2016-05-01

    Humans employ a high degree of redundancy in joint actuation, with different combinations of muscle and tendon action providing the same net joint torque. Both the resolution of these redundancies and the energetics of such systems depend on the dynamic properties of muscles and tendons, particularly their force-length relations. Current walking models that use stock parameters when simulating muscle-tendon dynamics tend to significantly overestimate metabolic consumption, perhaps because they do not adequately consider the role of elasticity. As an alternative, we posit that the muscle-tendon morphology of the human leg has evolved to maximize the metabolic efficiency of walking at self-selected speed. We use a data-driven approach to evaluate this hypothesis, utilizing kinematic, kinetic, electromyographic (EMG), and metabolic data taken from five participants walking at self-selected speed. The kinematic and kinetic data are used to estimate muscle-tendon lengths, muscle moment arms, and joint moments while the EMG data are used to estimate muscle activations. For each subject we perform an optimization using prescribed skeletal kinematics, varying the parameters that govern the force-length curve of each tendon as well as the strength and optimal fiber length of each muscle while seeking to simultaneously minimize metabolic cost and maximize agreement with the estimated joint moments. We find that the metabolic cost of transport (MCOT) values of our participants may be correctly matched (on average 0.36±0.02 predicted, 0.35±0.02 measured) with acceptable joint torque fidelity through application of a single constraint to the muscle metabolic budget. The associated optimal muscle-tendon parameter sets allow us to estimate the forces and states of individual muscles, resolving redundancies in joint actuation and lending insight into the potential roles and control objectives of the muscles of the leg throughout the gait cycle.

  6. Inscriptions Becoming Representations in Representational Practices

    ERIC Educational Resources Information Center

    Medina, Richard; Suthers, Daniel

    2013-01-01

    We analyze the interaction of 3 students working on mathematics problems over several days in a virtual math team. Our analysis traces out how successful collaboration in a later session is contingent upon the work of prior sessions and shows how the development of representational practices is an important aspect of these participants' problem…

  7. Data worth and prediction uncertainty for pesticide transport and fate models in Nebraska and Maryland, United States

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Few studies have attempted to quantify mass balances of both pesticides and degradates in multiple agricultural settings of the United States. We used inverse modeling to calibrate the Root Zone Water Quality Model (RZWQM) for predicting the unsaturated-zone transport and fate of metolachlor, metola...

  8. State-of-the-Science Report on Predictive Models and Modeling Approaches for Characterizing and Evaluating Exposure to Nanomaterials

    EPA Science Inventory

    This state-of-the-science review was undertaken to identify fate and transport models and alternative modeling approaches that could be used to predict exposure to engineered nanomaterials (ENMs) released into the environment, specifically, for aquatic systems. The development of...

  9. Predictive Factors in Undergraduates' Involvement in Campus Secret Cults in Public Universities in Edo State of Nigeria

    ERIC Educational Resources Information Center

    Azetta Arhedo, Philip; Aluede, Oyaziwo; Adomeh, Ilu O. C.

    2011-01-01

    This study examined the predictive factors in undergraduates' involvement in campus secret cults in public universities in Edo State of Nigeria. The study employed the descriptive method, specifically the survey format. A random sample of three hundred and eighty (380) undergraduates was drawn from the two public universities. Data were elicited…

  10. Gaussian quantum operator representation for bosons

    SciTech Connect

    Corney, Joel F.; Drummond, Peter D.

    2003-12-01

    We introduce a Gaussian quantum operator representation, using the most general possible multimode Gaussian operator basis. The representation unifies and substantially extends existing phase-space representations of density matrices for Bose systems and also includes generalized squeezed-state and thermal bases. It enables first-principles dynamical or equilibrium calculations in quantum many-body systems, with quantum uncertainties appearing as dynamical objects. Any quadratic Liouville equation for the density operator results in a purely deterministic time evolution. Any cubic or quartic master equation can be treated using stochastic methods.

  11. Discrete-state representation of ion permeation coupled to fast gating in a model of ClC chloride channels: comparison to multi-ion continuous space Brownian dynamics simulations.

    PubMed

    Coalson, Rob D; Cheng, Mary Hongying

    2010-01-28

    A discrete-state model of chloride ion motion in a ClC chloride channel is constructed, following a previously developed multi-ion continuous space model of the same system (Cheng, M. H.; Mamonov, A. B.; Dukes, J. W.; Coalson, R. D. J. Phys. Chem. B 2007, 111, 5956) that included a simplistic representation of the fast gate in this channel. The reducibility of the many-body continuous space to the eight discrete-state model considered in the present work is examined in detail by performing three-dimensional Brownian dynamics simulations of each allowed state-to-state transition in order to extract the appropriate rate constant for this process, and then inserting the pairwise rate constants thereby obtained into an appropriate set of kinetic master equations. Experimental properties of interest, including the rate of Cl(-) ion permeation through the open channel and the average rate of closing of the fast gate as a function of bulk Cl(-) ion concentrations in the intracellular and extracellular electrolyte reservoirs are computed. Good agreement is found between the results obtained via the eight discrete-state model versus the multi-ion continuous space model, thereby encouraging continued development of the discrete-state model to include more complex behaviors observed experimentally in these channels.

  12. Predicting the redox state and secondary structure of cysteine residues using multi-dimensional classification analysis of NMR chemical shifts.

    PubMed

    Wang, Ching-Cheng; Lai, Wen-Chung; Chuang, Woei-Jer

    2016-09-01

    A tool for predicting the redox state and secondary structure of cysteine residues using multi-dimensional analyses of different combinations of nuclear magnetic resonance (NMR) chemical shifts has been developed. A data set of cysteine [Formula: see text], (13)C(α), (13)C(β), (1)H(α), (1)H(N), and (15)N(H) chemical shifts was created, classified according to redox state and secondary structure, using a library of 540 re-referenced BioMagResBank (BMRB) entries. Multi-dimensional analyses of three, four, five, and six chemical shifts were used to derive rules for predicting the structural states of cysteine residues. The results from 60 BMRB entries containing 122 cysteines showed that four-dimensional analysis of the C(α), C(β), H(α), and N(H) chemical shifts had the highest prediction accuracy of 100 and 95.9 % for the redox state and secondary structure, respectively. The prediction of secondary structure using 3D, 5D, and 6D analyses had the accuracy of ~90 %, suggesting that H(N) and [Formula: see text] chemical shifts may be noisy and made the discrimination worse. A web server (6DCSi) was established to enable users to submit NMR chemical shifts, either in BMRB or key-in formats, for prediction. 6DCSi displays predictions using sets of 3, 4, 5, and 6 chemical shifts, which shows their consistency and allows users to draw their own conclusions. This web-based tool can be used to rapidly obtain structural information regarding cysteine residues directly from experimental NMR data.

  13. Charge Prediction Machine: A tool for inferring precursor charge states of Electron Transfer Dissociation tandem mass spectra

    PubMed Central

    Carvalho, Paulo C; Cociorva, Daniel; Wong, Catherine; Carvalho, Maria da Gloria da C; Barbosa, Valmir C; Yates, John R

    2010-01-01

    Electron Transfer Dissociation (ETD) can dissociate highly charged ions. Efficient analysis of ions dissociated with ETD requires accurate determination of charge states for calculation of molecular weight. We created an algorithm to assign the charge state of ions often used for ETD. The program, Charge Prediction Machine (CPM), uses Bayesian decision theory to account for different charge reduction processes encountered in ETD, and can also handle multiplex spectra. CPM correctly assigned charge states to 98% of the 13,097 MS2 spectra from a combined dataset of four experiments. In a comparison between CPM and a competing program, Charger (ThermoFisher), CPM produced half the mistakes. PMID:19203245

  14. A climate-based model predicts the spatial distribution of the Lyme disease vector Ixodes scapularis in the United States.

    PubMed Central

    Brownstein, John S; Holford, Theodore R; Fish, Durland

    2003-01-01

    An understanding of the spatial distribution of the black-legged tick, Ixodes scapularis, is a fundamental component in assessing human risk for Lyme disease in much of the United States. Although a county-level vector distribution map exists for the United States, its accuracy is limited by arbitrary categories of its reported presence. It is unknown whether reported positive areas can support established populations and whether negative areas are suitable for established populations. The steadily increasing range of I. scapularis in the United States suggests that all suitable habitats are not currently occupied. Therefore, we developed a spatially predictive logistic model for I. scapularis in the 48 conterminous states to improve the previous vector distribution map. We used ground-observed environmental data to predict the probability of established I. scapularis populations. The autologistic analysis showed that maximum, minimum, and mean temperatures as well as vapor pressure significantly contribute to population maintenance with an accuracy of 95% (p < 0.0001). A cutoff probability for habitat suitability was assessed by sensitivity analysis and was used to reclassify the previous distribution map. The spatially modeled relationship between I. scapularis presence and large-scale environmental data provides a robust suitability model that reveals essential environmental determinants of habitat suitability, predicts emerging areas of Lyme disease risk, and generates the future pattern of I. scapularis across the United States. PMID:12842766

  15. Comparative modeling: the state of the art and protein drug target structure prediction.

    PubMed

    Liu, Tianyun; Tang, Grace W; Capriotti, Emidio

    2011-07-01

    The goal of computational protein structure prediction is to provide three-dimensional (3D) structures with resolution comparable to experimental results. Comparative modeling, which predicts the 3D structure of a protein based on its sequence similarity to homologous structures, is the most accurate computational method for structure prediction. In the last two decades, significant progress has been made on comparative modeling methods. Using the large number of protein structures deposited in the Protein Data Bank (~65,000), automatic prediction pipelines are generating a tremendous number of models (~1.9 million) for sequences whose structures have not been experimentally determined. Accurate models are suitable for a wide range of applications, such as prediction of protein binding sites, prediction of the effect of protein mutations, and structure-guided virtual screening. In particular, comparative modeling has enabled structure-based drug design against protein targets with unknown structures. In this review, we describe the theoretical basis of comparative modeling, the available automatic methods and databases, and the algorithms to evaluate the accuracy of predicted structures. Finally, we discuss relevant applications in the prediction of important drug target proteins, focusing on the G protein-coupled receptor (GPCR) and protein kinase families.

  16. Prediction of State Mandated Assessment Mathematics Scores from Computer Based Mathematics and Reading Preview Assessments

    ERIC Educational Resources Information Center

    Costa-Guerra, Boris

    2012-01-01

    The study sought to understand whether MAPs computer based assessment of math and language skills using MAPs reading scores can predict student scores on the NMSBA. A key question was whether or not the prediction can be improved by including student language skill scores. The study explored the effectiveness of computer based preview assessments…

  17. Toward an evolutionary-predictive foundation for creativity : Commentary on "Human creativity, evolutionary algorithms, and predictive representations: The mechanics of thought trials" by Arne Dietrich and Hilde Haider, 2014 (Accepted pending minor revisions for publication in Psychonomic Bulletin & Review).

    PubMed

    Gabora, Liane; Kauffman, Stuart

    2016-04-01

    Dietrich and Haider (Psychonomic Bulletin & Review, 21 (5), 897-915, 2014) justify their integrative framework for creativity founded on evolutionary theory and prediction research on the grounds that "theories and approaches guiding empirical research on creativity have not been supported by the neuroimaging evidence." Although this justification is controversial, the general direction holds promise. This commentary clarifies points of disagreement and unresolved issues, and addresses mis-applications of evolutionary theory that lead the authors to adopt a Darwinian (versus Lamarckian) approach. To say that creativity is Darwinian is not to say that it consists of variation plus selection - in the everyday sense of the term - as the authors imply; it is to say that evolution is occurring because selection is affecting the distribution of randomly generated heritable variation across generations. In creative thought the distribution of variants is not key, i.e., one is not inclined toward idea A because 60 % of one's candidate ideas are variants of A while only 40 % are variants of B; one is inclined toward whichever seems best. The authors concede that creative variation is partly directed; however, the greater the extent to which variants are generated non-randomly, the greater the extent to which the distribution of variants can reflect not selection but the initial generation bias. Since each thought in a creative process can alter the selective criteria against which the next is evaluated, there is no demarcation into generations as assumed in a Darwinian model. We address the authors' claim that reduced variability and individuality are more characteristic of Lamarckism than Darwinian evolution, and note that a Lamarckian approach to creativity has addressed the challenge of modeling the emergent features associated with insight.

  18. Ensemble Canonical Correlation Prediction of Seasonal Precipitation Over the United States: Raising the Bar for Dynamical Model Forecasts

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

    This paper presents preliminary results of an ensemble canonical correlation (ECC) prediction scheme developed at the Climate and Radiation Branch, NASA/Goddard Space Flight Center for determining the potential predictability of regional precipitation, and for climate downscaling studies. The scheme is tested on seasonal hindcasts of anomalous precipitation over the continental United States using global sea surface temperature (SST) for 1951-2000. To maximize the forecast skill derived from SST, the world ocean is divided into non-overlapping sectors. The canonical SST modes for each sector are used as the predictor for the ensemble hindcasts. Results show that the ECC yields a substantial (10-25%) increase in prediction skills for all the regions of the US in every season compared to traditional CCA prediction schemes. For the boreal winter, the tropical Pacific contributes the largest potential predictability to precipitation in the southwestern and southeastern regions, while the North Pacific and the North Atlantic are responsible to the enhanced forecast skills in the Pacific Northwest, the northern Great Plains and Ohio Valley. Most importantly, the ECC increases skill for summertime precipitation prediction and substantially reduces the spring predictability barrier over all the regions of the US continent. Besides SST, the ECC is designed with the flexibility to include any number of predictor fields, such as soil moisture, snow cover and additional local observations. The enhanced ECC forecast skill provides a new benchmark for evaluating dynamical model forecasts.

  19. Torque prediction using stimulus evoked EMG and its identification for different muscle fatigue states in SCI subjects.

    PubMed

    Zhang, Qin; Hayashibe, Mitsuhiro; Papaiordanidou, Maria; Fraisse, Philippe; Fattal, Charles; Guiraud, David

    2010-01-01

    Muscle fatigue is an unavoidable problem when electrical stimulation is applied to paralyzed muscles. The detection and compensation of muscle fatigue is essential to avoid movement failure and achieve desired trajectory. This work aims to predict ankle plantar-flexion torque using stimulus evoked EMG (eEMG) during different muscle fatigue states. Five spinal cord injured patients were recruited for this study. An intermittent fatigue protocol was delivered to triceps surae muscle to induce muscle fatigue. A hammerstein model was used to capture the muscle contraction dynamics to represent eEMG-torque relationship. The prediction of ankle torque was based on measured eEMG and past measured or past predicted torque. The latter approach makes it possible to use eEMG as a synthetic force sensor when force measurement is not available in daily use. Some previous researches suggested to use eEMG information directly to detect and predict muscle force during fatigue assuming a fixed relationship between eEMG and generated force. However, we found that the prediction became less precise with the increase of muscle fatigue when fixed parameter model was used. Therefore, we carried out the torque prediction with an adaptive parameters using the latest measurement. The prediction of adapted model was improved with 16.7%-50.8% comparing to the fixed model. PMID:21097036

  20. Berry phase in Heisenberg representation

    NASA Technical Reports Server (NTRS)

    Andreev, V. A.; Klimov, Andrei B.; Lerner, Peter B.

    1994-01-01

    We define the Berry phase for the Heisenberg operators. This definition is motivated by the calculation of the phase shifts by different techniques. These techniques are: the solution of the Heisenberg equations of motion, the solution of the Schrodinger equation in coherent-state representation, and the direct computation of the evolution operator. Our definition of the Berry phase in the Heisenberg representation is consistent with the underlying supersymmetry of the model in the following sense. The structural blocks of the Hamiltonians of supersymmetrical quantum mechanics ('superpairs') are connected by transformations which conserve the similarity in structure of the energy levels of superpairs. These transformations include transformation of phase of the creation-annihilation operators, which are generated by adiabatic cyclic evolution of the parameters of the system.

  1. Failure Mode Classification for Life Prediction Modeling of Solid-State Lighting

    SciTech Connect

    Sakalaukus, Peter Joseph

    2015-08-01

    Since the passing of the Energy Independence and Security Act of 2007, the U.S. government has mandated greater energy independence which has acted as a catalyst for accelerating and facilitating research efforts toward the development and deployment of market-driven solutions for energy-saving homes, buildings and manufacturing, as well as sustainable transportation and renewable electricity generation. As part of this effort, an emphasis toward advancing solid-state lighting technology through research, development, demonstration, and commercial applications is assisting in the phase out of the common incandescent light bulb, as well as developing a more economical lighting source that is less toxic than compact fluorescent lighting. This has led lighting manufacturers to pursue SSL technologies for a wide range of consumer lighting applications. An SSL luminaire’s lifetime can be characterized in terms of lumen maintenance life. Lumen maintenance or lumen depreciation is the percentage decrease in the relative luminous flux from that of the original, pristine luminous flux value. Lumen maintenance life is the estimated operating time, in hours, when the desired failure threshold is projected to be reached at normal operating conditions. One accepted failure threshold of SSL luminaires is lumen maintenance of 70% -- a 30% reduction in the light output of the luminaire. Currently, the only approved lighting standard that puts forth a recommendation for long-term luminous flux maintenance projections towards a specified failure threshold of an SSL luminaire is the IES TM-28-14 (TM28) standard. iii TM28 was derived as a means to compare luminaires that have been tested at different facilities, research labs or companies. TM28 recommends the use of the Arrhenius equation to determine SSL device specific reaction rates from thermally driven failure mechanisms used to characterize a single failure mode – the relative change in the luminous flux output or

  2. Toward Improved Off-Shore Wind Predictions by Combining Observations with Models through State Estimation - An Analysis of Marine Boundary Layer Parameterizations

    NASA Astrophysics Data System (ADS)

    Kosovic, B.; Delle Monache, L.; Hacker, J.; Lee, J. A.; Vandenberghe, F. C.; Wu, Y.; Clifton, A.; Hawkins, S.; Nissen, J.; Rostkier-Edelstein, D.

    2014-12-01

    In recent years, significant advances have been achieved in model representation of atmospheric boundary layers (ABL). However, fundamental understanding of the processes governing the evolution of the Marine Boundary Layer (MBL) is still incomplete. We address this problem by combining available atmosphere and ocean observations with advanced coupled atmosphere-wave models, via state estimation (SE) methodologies. The goal is to improve wind prediction for off-shore wind energy applications through advances in understanding and parameterization of underlying physical processes, with an emphasis on the coupling between the atmosphere and the ocean via momentum and heat fluxes. We systematically investigate the errors in the treatment of the surface layer of the MBL in the Weather Research and Forecasting (WRF) model and identify structural model inadequacies associated with the MBL parameterization. For this purpose we are using both the single-column model (SCM) and three-dimensional (3D) versions of the WRF model, observations of MBL structure provided by offshore observational platform FINO1, and probabilistic SE. We have also developed an atmosphere-wave coupled modeling system by interfacing WRF with a wave model (WaveWatch III - WWIII). This modeling system is used for evaluating errors in the representation of wave-induced forcing on the energy balance at the interface between atmosphere and ocean. Probabilistic SE is based on the Data Assimilation Research Testbed (DART). DART is the framework for obtaining spatial and temporal statistics of wind-error evolution (and hence the surface-layer fluxes), along with objective tuning of model parameters. We explore one of the potential sources of MBL model errors associated with roughness length parameterized using Charnock's relation. Charnock's roughness length parameterization assumes wind-driven waves are in equilibrium. However, it has been shown that swells propagating at different speeds and angles with

  3. Ground Motion Prediction Equations for the Central and Eastern United States

    NASA Astrophysics Data System (ADS)

    Seber, D.; Graizer, V.

    2015-12-01

    New ground motion prediction equations (GMPE) G15 model for the Central and Eastern United States (CEUS) is presented. It is based on the modular filter based approach developed by Graizer and Kalkan (2007, 2009) for active tectonic environment in the Western US (WUS). The G15 model is based on the NGA-East database for the horizontal peak ground acceleration and 5%-damped pseudo spectral acceleration RotD50 component (Goulet et al., 2014). In contrast to active tectonic environment the database for the CEUS is not sufficient for creating purely empirical GMPE covering the range of magnitudes and distances required for seismic hazard assessments. Recordings in NGA-East database are sparse and cover mostly range of M<6.0 with limited amount of near-fault recordings. The functional forms of the G15 GMPEs are derived from filters—each filter represents a particular physical phenomenon affecting the seismic wave radiation from the source. Main changes in the functional forms for the CEUS relative to the WUS model (Graizer and Kalkan, 2015) are a shift of maximum frequency of the acceleration response spectrum toward higher frequencies and an increase in the response spectrum amplitudes at high frequencies. Developed site correction is based on multiple runs of representative VS30 profiles through SHAKE-type equivalent-linear programs using time histories and random vibration theory approaches. Site amplification functions are calculated for different VS30 relative to hard rock definition used in nuclear industry (Vs=2800 m/s). The number of model predictors is limited to a few measurable parameters: moment magnitude M, closest distance to fault rupture plane R, average shear-wave velocity in the upper 30 m of the geological profile VS30, and anelastic attenuation factor Q0. Incorporating anelastic attenuation Q0 as an input parameter allows adjustments based on the regional crustal properties. The model covers the range of magnitudes 4.0

  4. Computer aided surface representation

    SciTech Connect

    Barnhill, R.E.

    1989-02-09

    The central research problem of this project is the effective representation and display of surfaces, interpolating to given information, in three or more dimensions. In a typical problem, we wish to create a surface from some discrete information. If this information is itself on another surface, the problem is to determine a surface defined on a surface,'' which is discussed below. Often, properties of an already constructed surface are desired: such geometry processing'' is described below. The Summary of Proposed Research from our original proposal describes the aims of this research project. This Summary and the Table of Contents from the original proposal are enclosed as an Appendix to this Progress Report. The broad sweep from constructive mathematics through algorithms and computer graphics displays is utilized in the research. The wide range of activity, directed in both theory and applications, makes this project unique. Last month in the first Ardent Titan delivered in the State of Arizona came to our group, funded by the DOE and Arizona State University. Although the Titan is a commercial product, its newness requires our close collaboration with Ardent to maximize results. During the past year, four faculty members and several graduate research assistants have worked on this DOE project. The gaining of new professionals is an important aspect of this project. A listing of the students and their topics is given in the Appendix. The most significant publication during the past year is the book, Curves and Surfaces for Computer Aided Geometric Design, by Dr. Gerald Farin. This 300 page volume helps fill a considerable gap in the subject and includes many new results on Bernstein-Bezier curves and surfaces.

  5. Efficient visual tracking via low-complexity sparse representation

    NASA Astrophysics Data System (ADS)

    Lu, Weizhi; Zhang, Jinglin; Kpalma, Kidiyo; Ronsin, Joseph

    2015-12-01

    Thanks to its good performance on object recognition, sparse representation has recently been widely studied in the area of visual object tracking. Up to now, little attention has been paid to the complexity of sparse representation, while most works are focused on the performance improvement. By reducing the computation load related to sparse representation hundreds of times, this paper proposes by far the most computationally efficient tracking approach based on sparse representation. The proposal simply consists of two stages of sparse representation, one is for object detection and the other for object validation. Experimentally, it achieves better performance than some state-of-the-art methods in both accuracy and speed.

  6. Predictive Models for Carcinogenicity and Mutagenicity: Frameworks,State-of-the-Art, and Perspectives

    EPA Science Inventory

    Mutagenicity and carcinogenicity are endpoints of major environmental and regulatory concern. These endpoints are also important targets for development of alternative methods for screening and prediction due to the large number of chemicals of potential concern and the tremendou...

  7. Predictive Models for Carcinogenicity and Mutagenicity: Frameworks, State-of-the-Art, and Perspectives

    EPA Science Inventory

    Mutagenicity and carcinogenicity are endpoints of major environmental and regulatory concern. These endpoints are also important targets for development of alternative methods for screening and prediction due to the large number of chemicals of potential concern and the tremendou...

  8. State-of-the-Art Climate Predictions for Energy Climate Services

    NASA Astrophysics Data System (ADS)

    Torralba-Fernandez, Veronica; Davis, Melanie; Doblas-Reyes, Francisco J.; Gonzalez-Reviriego, Nube

    2015-04-01

    Climate predictions tailored to the energy sector represent the cutting edge in climate sciences to forecast wind power generation. At seasonal time scales, current energy practices use a deterministic approach based on retrospective climatology, but climate predictions have recently been shown to provide additional value. For this reason, probabilistic climate predictions of near surface winds can allow end users to take calculated, precautionary action with a potential cost savings to their operations. As every variable predicted in a coupled model forecast system, the prediction of wind speed is affected by biases. To overcome this, two different techniques for the post-processing of ensemble forecasts are considered: a simple bias correction and a calibration method. The former is based on the assumption that the reference and predicted distributions are well approximated by a normal distribution. The latter is a calibration technique which inflates the model variance, and the inflation of the ensemble is required in order to obtain a reliable outcome. Both methods use the "one-year out" cross-validated mode, and they provide corrected forecasts with improved statistical properties. The impact of these bias corrections on the quality of the ECMWF S4 predictions of near surface wind speed during winter is explored. To offer a comprehensive picture of the post-processing effect on the forecast quality of the system, it is necessary to use several scoring measures: rank histograms, reliability diagrams and skill maps. These tools are essential to assess different aspects of the forecasts, and to observe changes in their properties when the two methods are applied. This study reveals that the different techniques to correct the predictions produce a statistically consistent ensemble. However, the operations performed on the forecasts decrease their skill which correspond to an increase in the uncertainty. Therefore, even though the bias correction is fundamental

  9. Phase space representation of quantum dynamics

    SciTech Connect

    Polkovnikov, Anatoli

    2010-08-15

    We discuss a phase space representation of quantum dynamics of systems with many degrees of freedom. This representation is based on a perturbative expansion in quantum fluctuations around one of the classical limits. We explicitly analyze expansions around three such limits: (i) corpuscular or Newtonian limit in the coordinate-momentum representation, (ii) wave or Gross-Pitaevskii limit for interacting bosons in the coherent state representation, and (iii) Bloch limit for the spin systems. We discuss both the semiclassical (truncated Wigner) approximation and further quantum corrections appearing in the form of either stochastic quantum jumps along the classical trajectories or the nonlinear response to such jumps. We also discuss how quantum jumps naturally emerge in the analysis of non-equal time correlation functions. This representation of quantum dynamics is closely related to the phase space methods based on the Wigner-Weyl quantization and to the Keldysh technique. We show how such concepts as the Wigner function, Weyl symbol, Moyal product, Bopp operators, and others automatically emerge from the Feynmann's path integral representation of the evolution in the Heisenberg representation. We illustrate the applicability of this expansion with various examples mostly in the context of cold atom systems including sine-Gordon model, one- and two-dimensional Bose-Hubbard model, Dicke model and others.

  10. General Regression and Representation Model for Classification

    PubMed Central

    Qian, Jianjun; Yang, Jian; Xu, Yong

    2014-01-01

    Recently, the regularized coding-based classification methods (e.g. SRC and CRC) show a great potential for pattern classification. However, most existing coding methods assume that the representation residuals are uncorrelated. In real-world applications, this assumption does not hold. In this paper, we take account of the correlations of the representation residuals and develop a general regression and representation model (GRR) for classification. GRR not only has advantages of CRC, but also takes full use of the prior information (e.g. the correlations between representation residuals and representation coefficients) and the specific information (weight matrix of image pixels) to enhance the classification performance. GRR uses the generalized Tikhonov regularization and K Nearest Neighbors to learn the prior information from the training data. Meanwhile, the specific information is obtained by using an iterative algorithm to update the feature (or image pixel) weights of the test sample. With the proposed model as a platform, we design two classifiers: basic general regression and representation classifier (B-GRR) and robust general regression and representation classifier (R-GRR). The experimental results demonstrate the performance advantages of proposed methods over state-of-the-art algorithms. PMID:25531882

  11. The nature, scope and impact of genomic prediction in beef cattle in the United States

    PubMed Central

    2011-01-01

    Artificial selection has proven to be effective at altering the performance of animal production systems. Nevertheless, selection based on assessment of the genetic superiority of candidates is suboptimal as a result of errors in the prediction of genetic merit. Conventional breeding programs may extend phenotypic measurements on selection candidates to include correlated indicator traits, or delay selection decisions well beyond puberty so that phenotypic performance can be observed on progeny or other relatives. Extending the generation interval to increase the accuracy of selection reduces annual rates of gain compared to accurate selection and use of parents of the next generation at the immediate time they reach breeding age. Genomic prediction aims at reducing prediction errors at breeding age by exploiting information on the transmission of chromosome fragments from parents to selection candidates, in conjunction with knowledge on the value of every chromosome fragment. For genomic prediction to influence beef cattle breeding programs and the rate or cost of genetic gains, training analyses must be undertaken, and genomic prediction tools made available for breeders and other industry stakeholders. This paper reviews the nature or kind of studies currently underway, the scope or extent of some of those studies, and comments on the likely predictive value of genomic information for beef cattle improvement. PMID:21569623

  12. The nature, scope and impact of genomic prediction in beef cattle in the United States.

    PubMed

    Garrick, Dorian J

    2011-05-15

    Artificial selection has proven to be effective at altering the performance of animal production systems. Nevertheless, selection based on assessment of the genetic superiority of candidates is suboptimal as a result of errors in the prediction of genetic merit. Conventional breeding programs may extend phenotypic measurements on selection candidates to include correlated indicator traits, or delay selection decisions well beyond puberty so that phenotypic performance can be observed on progeny or other relatives. Extending the generation interval to increase the accuracy of selection reduces annual rates of gain compared to accurate selection and use of parents of the next generation at the immediate time they reach breeding age. Genomic prediction aims at reducing prediction errors at breeding age by exploiting information on the transmission of chromosome fragments from parents to selection candidates, in conjunction with knowledge on the value of every chromosome fragment. For genomic prediction to influence beef cattle breeding programs and the rate or cost of genetic gains, training analyses must be undertaken, and genomic prediction tools made available for breeders and other industry stakeholders. This paper reviews the nature or kind of studies currently underway, the scope or extent of some of those studies, and comments on the likely predictive value of genomic information for beef cattle improvement.

  13. Long-lead predictions of eastern United States hot days from Pacific sea surface temperatures

    NASA Astrophysics Data System (ADS)

    McKinnon, K. A.; Rhines, A.; Tingley, M. P.; Huybers, P.

    2016-05-01

    Seasonal forecast models exhibit only modest skill in predicting extreme summer temperatures across the eastern US. Anomalies in sea surface temperature and monthly-resolution rainfall have, however, been correlated with hot days in the US, and seasonal persistence of these anomalies suggests potential for long-lead predictability. Here we present a clustering analysis of daily maximum summer temperatures from US weather stations between 1982-2015 and identify a region spanning most of the eastern US where hot weather events tend to occur synchronously. We then show that an evolving pattern of sea surface temperature anomalies, termed the Pacific Extreme Pattern, provides for skillful prediction of hot weather within this region as much as 50 days in advance. Skill is demonstrated using out-of-sample predictions between 1950 and 2015. Rainfall deficits over the eastern US are also associated with the occurrence of the Pacific Extreme Pattern and are demonstrated to offer complementary skill in predicting high temperatures. The Pacific Extreme Pattern appears to provide a cohesive framework for improving seasonal prediction of summer precipitation deficits and high temperature anomalies in the eastern US.

  14. Symbol Systems and Pictorial Representations

    NASA Astrophysics Data System (ADS)

    Diederich, Joachim; Wright, Susan

    All problem-solvers are subject to the same ultimate constraints -- limitations on space, time, and materials (Minsky, 1985). He introduces two principles: (1) Economics: Every intelligence must develop symbol-systems for representing objects, causes and goals, and (2) Sparseness: Every evolving intelligence will eventually encounter certain very special ideas -- e.g., about arithmetic, causal reasoning, and economics -- because these particular ideas are very much simpler than other ideas with similar uses. An extra-terrestrial intelligence (ETI) would have developed symbol systems to express these ideas and would have the capacity of multi-modal processing. Vakoch (1998) states that ...``ETI may rely significantly on other sensory modalities (than vision). Particularly useful representations would be ones that may be intelligible through more than one sensory modality. For instance, the information used to create a three-dimensional representation of an object might be intelligible to ETI heavily reliant on either visual or tactile sensory processes.'' The cross-modal representations Vakoch (1998) describes and the symbol systems Minsky (1985) proposes are called ``metaphors'' when combined. Metaphors allow for highly efficient communication. Metaphors are compact, condensed ways of expressing an idea: words, sounds, gestures or images are used in novel ways to refer to something they do not literally denote. Due to the importance of Minsky's ``economics'' principle, it is therefore possible that a message heavily relies on metaphors.

  15. Multi-omics integration accurately predicts cellular state in unexplored conditions for Escherichia coli

    PubMed Central

    Kim, Minseung; Rai, Navneet; Zorraquino, Violeta; Tagkopoulos, Ilias

    2016-01-01

    A significant obstacle in training predictive cell models is the lack of integrated data sources. We develop semi-supervised normalization pipelines and perform experimental characterization (growth, transcriptional, proteome) to create Ecomics, a consistent, quality-controlled multi-omics compendium for Escherichia coli with cohesive meta-data information. We then use this resource to train a multi-scale model that integrates four omics layers to predict genome-wide concentrations and growth dynamics. The genetic and environmental ontology reconstructed from the omics data is substantially different and complementary to the genetic and chemical ontologies. The integration of different layers confers an incremental increase in the prediction performance, as does the information about the known gene regulatory and protein-protein interactions. The predictive performance of the model ranges from 0.54 to 0.87 for the various omics layers, which far exceeds various baselines. This work provides an integrative framework of omics-driven predictive modelling that is broadly applicable to guide biological discovery. PMID:27713404

  16. Representational Change and Children's Numerical Estimation

    ERIC Educational Resources Information Center

    Opfer, John E.; Siegler, Robert S.

    2007-01-01

    We applied overlapping waves theory and microgenetic methods to examine how children improve their estimation proficiency, and in particular how they shift from reliance on immature to mature representations of numerical magnitude. We also tested the theoretical prediction that feedback on problems on which the discrepancy between two…

  17. Phonological Representations and Early Literacy in Chinese

    ERIC Educational Resources Information Center

    Kidd, Joanna C.; Shum, Kathy Kar-Man; Ho, Connie Suk-Han; Au, Terry Kit-fong

    2015-01-01

    Phonological processing skills predict early reading development, but what underlies developing phonological processing skills? Phonological representations of 140 native Cantonese-speaking Chinese children (age 4-10) were assessed with speech gating, mispronunciation detection, and nonword repetition tasks; their nonverbal IQ, reading, and…

  18. Female representation by type of class

    NASA Astrophysics Data System (ADS)

    2012-02-01

    Last month we saw that females make up about 47% of all high school physics students in the United States. This number has changed little since 1997. This month, we take a closer look at female representation by type of class. We last collected class-specific data in 1993; that year, 43% of all high school physics students were female. However, female representation varies by type of class. In both 1993 and 2009, conceptual physics courses had the highest proportion of female students, and AP Physics C had the lowest. The good news is that female representation exhibits growth in all types of classes. In fact, the jump from 27% of the AP Physics C students being female in 1993 to 32% in 2009 represents an almost 20% growth in female representation; this compares favorably to the 9.3% growth overall.

  19. Pupil diameter tracks changes in control state predicted by the adaptive gain theory of locus coeruleus function.

    PubMed

    Gilzenrat, Mark S; Nieuwenhuis, Sander; Jepma, Marieke; Cohen, Jonathan D

    2010-05-01

    An important dimension of cognitive control is the adaptive regulation of the balance between exploitation (pursuing known sources of reward) and exploration (seeking new ones) in response to changes in task utility. Recent studies have suggested that the locus coeruleus-norepinephrine system may play an important role in this function and that pupil diameter can be used to index locus coeruleus activity. On the basis of this, we reasoned that pupil diameter may correlate closely with control state and associated changes in behavior. Specifically, we predicted that increases in baseline pupil diameter would be associated with decreases in task utility and disengagement from the task (exploration), whereas reduced baseline diameter (but increases in task-evoked dilations) would be associated with task engagement (exploitation). Findings in three experiments were consistent with these predictions, suggesting that pupillometry may be useful as an index of both control state and, indirectly, locus coeruleus function.

  20. Including Thermal Fluctuations in Actomyosin Stable States Increases the Predicted Force per Motor and Macroscopic Efficiency in Muscle Modelling

    PubMed Central

    2016-01-01

    Muscle contractions are generated by cyclical interactions of myosin heads with actin filaments to form the actomyosin complex. To simulate actomyosin complex stable states, mathematical models usually define an energy landscape with a corresponding number of wells. The jumps between these wells are defined through rate constants. Almost all previous models assign these wells an infinite sharpness by imposing a relatively simple expression for the detailed balance, i.e., the ratio of the rate constants depends exponentially on the sole myosin elastic energy. Physically, this assumption corresponds to neglecting thermal fluctuations in the actomyosin complex stable states. By comparing three mathematical models, we examine the extent to which this hypothesis affects muscle model predictions at the single cross-bridge, single fiber, and organ levels in a ceteris paribus analysis. We show that including fluctuations in stable states allows the lever arm of the myosin to easily and dynamically explore all possible minima in the energy landscape, generating several backward and forward jumps between states during the lifetime of the actomyosin complex, whereas the infinitely sharp minima case is characterized by fewer jumps between states. Moreover, the analysis predicts that thermal fluctuations enable a more efficient contraction mechanism, in which a higher force is sustained by fewer attached cross-bridges. PMID:27626630

  1. Including Thermal Fluctuations in Actomyosin Stable States Increases the Predicted Force per Motor and Macroscopic Efficiency in Muscle Modelling.

    PubMed

    Marcucci, Lorenzo; Washio, Takumi; Yanagida, Toshio

    2016-09-01

    Muscle contractions are generated by cyclical interactions of myosin heads with actin filaments to form the actomyosin complex. To simulate actomyosin complex stable states, mathematical models usually define an energy landscape with a corresponding number of wells. The jumps between these wells are defined through rate constants. Almost all previous models assign these wells an infinite sharpness by imposing a relatively simple expression for the detailed balance, i.e., the ratio of the rate constants depends exponentially on the sole myosin elastic energy. Physically, this assumption corresponds to neglecting thermal fluctuations in the actomyosin complex stable states. By comparing three mathematical models, we examine the extent to which this hypothesis affects muscle model predictions at the single cross-bridge, single fiber, and organ levels in a ceteris paribus analysis. We show that including fluctuations in stable states allows the lever arm of the myosin to easily and dynamically explore all possible minima in the energy landscape, generating several backward and forward jumps between states during the lifetime of the actomyosin complex, whereas the infinitely sharp minima case is characterized by fewer jumps between states. Moreover, the analysis predicts that thermal fluctuations enable a more efficient contraction mechanism, in which a higher force is sustained by fewer attached cross-bridges. PMID:27626630

  2. Prediction of individual clinical scores in patients with Parkinson's disease using resting-state functional magnetic resonance imaging.

    PubMed

    Hou, YanBing; Luo, ChunYan; Yang, Jing; Ou, RuWei; Song, Wei; Wei, QianQian; Cao, Bei; Zhao, Bi; Wu, Ying; Shang, Hui-Fang; Gong, QiYong

    2016-07-15

    Neuroimaging holds the promise that it may one day aid the clinical assessment. However, the vast majority of studies using resting-state functional magnetic resonance imaging (fMRI) have reported average differences between Parkinson's disease (PD) patients and healthy controls, which do not permit inferences at the level of individuals. This study was to develop a model for the prediction of PD illness severity ratings from individual fMRI brain scan. The resting-state fMRI scans were obtained from 84 patients with PD and the Unified Parkinson's Disease Rating Scale-III (UPDRS-III) scores were obtained before scanning. The RVR method was used to predict clinical scores (UPDRS-III) from fMRI scans. The application of RVR to whole-brain resting-state fMRI data allowed prediction of UPDRS-III scores with statistically significant accuracy (correlation=0.35, P-value=0.001; mean sum of squares=222.17, P-value=0.002). This prediction was informed strongly by negative weight areas including prefrontal lobe and medial occipital lobe, and positive weight areas including medial parietal lobe. It was suggested that fMRI scans contained sufficient information about neurobiological change in patients with PD to permit accurate prediction about illness severity, on an individual subject basis. Our results provided preliminary evidence, as proof-of-concept, to support that fMRI might be possible to be a clinically useful quantitative assessment aid in PD at individual level. This may enable clinicians to target those uncooperative patients and machines to replace human for a more efficient use of health care resources. PMID:27288771

  3. Quantitative precipitation and river flow predictions over the southwestern United States

    SciTech Connect

    Kim, J.; Miller, N.L.

    1996-09-01

    Accurate predictions of local precipitation and river flow are crucial in the western US steep terrain and narrow valleys can cause local flooding during short term heavy precipitation. Typical size of hydrologically uniform watersheds within the mountainous part of the western US ranges 10{sup 2} to 10{sup 3} km{sup 2}. Such small watershed size, together with large variations in terrain elevations and a strong dependence of precipitation on terrain elevation, requires a find-resolution and well-localized NWP to improve QPF and river predictions. The most important aspects of accurate QPF and river flow predictions in the western US are: (1) partitioning the total precipitation into rainfall and snowfall, (2) representing hydrologic processes within individual watersheds, and (3) map watershed areas onto the regularly-spaced atmospheric grid model grid. In the following, we present the QPF and river flow calculations by the CARS system during two winter seasons from Nov. 1994 to Apr. 1995.

  4. Improved prediction of complex diseases by common genetic markers: state of the art and further perspectives.

    PubMed

    Müller, Bent; Wilcke, Arndt; Boulesteix, Anne-Laure; Brauer, Jens; Passarge, Eberhard; Boltze, Johannes; Kirsten, Holger

    2016-03-01

    Reliable risk assessment of frequent, but treatable diseases and disorders has considerable clinical and socio-economic relevance. However, as these conditions usually originate from a complex interplay between genetic and environmental factors, precise prediction remains a considerable challenge. The current progress in genotyping technology has resulted in a substantial increase of knowledge regarding the genetic basis of such diseases and disorders. Consequently, common genetic risk variants are increasingly being included in epidemiological models to improve risk prediction. This work reviews recent high-quality publications targeting the prediction of common complex diseases. To be included in this review, articles had to report both, numerical measures of prediction performance based on traditional (non-genetic) risk factors, as well as measures of prediction performance when adding common genetic variants to the model. Systematic PubMed-based search finally identified 55 eligible studies. These studies were compared with respect to the chosen approach and methodology as well as results and clinical impact. Phenotypes analysed included tumours, diabetes mellitus, and cardiovascular diseases. All studies applied one or more statistical measures reporting on calibration, discrimination, or reclassification to quantify the benefit of including SNPs, but differed substantially regarding the methodological details that were reported. Several examples for improved risk assessments by considering disease-related SNPs were identified. Although the add-on benefit of including SNP genotyping data was mostly moderate, the strategy can be of clinical relevance and may, when being paralleled by an even deeper understanding of disease-related genetics, further explain the development of enhanced predictive and diagnostic strategies for complex diseases.

  5. Can we Predict Quantum Yields Using Excited State Density Functional Theory for New Families of Fluorescent Dyes?

    NASA Astrophysics Data System (ADS)

    Kohn, Alexander W.; Lin, Zhou; Shepherd, James J.; Van Voorhis, Troy

    2016-06-01

    For a fluorescent dye, the quantum yield characterizes the efficiency of energy transfer from the absorbed light to the emitted fluorescence. In the screening among potential families of dyes, those with higher quantum yields are expected to have more advantages. From the perspective of theoreticians, an efficient prediction of the quantum yield using a universal excited state electronic structure theory is in demand but still challenging. The most representative examples for such excited state theory include time-dependent density functional theory (TDDFT) and restricted open-shell Kohn-Sham (ROKS). In the present study, we explore the possibility of predicting the quantum yields for conventional and new families of organic dyes using a combination of TDDFT and ROKS. We focus on radiative (kr) and nonradiative (knr) rates for the decay of the first singlet excited state (S_1) into the ground state (S_0) in accordance with Kasha's rule. M. Kasha, Discuss. Faraday Soc., 9, 14 (1950). For each dye compound, kr is calculated with the S_1-S_0 energy gap and transition dipole moment obtained using ROKS and TDDFT respectively at the relaxed S_1 geometry. Our predicted kr agrees well with the experimental value, so long as the order of energy levels is correctly predicted. Evaluation of knr is less straightforward as multiple processes are involved. Our study focuses on the S_1-T_1 intersystem crossing (ISC) and the S_1-S_0 internal conversion (IC): we investigate the properties that allow us to model the knr value using a Marcus-like expression, such as the Stokes shift, the reorganization energy, and the S_1-T_1 and S_1-S_0 energy gaps. Taking these factors into consideration, we compare our results with those obtained using the actual Marcus theory and provide explanation for discrepancy. T. Kowalczyk, T. Tsuchimochi, L. Top, P.-T. Chen, and T. Van Voorhis, J. Chem. Phys., 138, 164101 (2013). M. Kasha, Discuss. Faraday Soc., 9, 14 (1950).

  6. Contacts de langues et representations (Language Contacts and Representations).

    ERIC Educational Resources Information Center

    Matthey, Marinette, Ed.

    1997-01-01

    Essays on language contact and the image of language, entirely in French, include: "Representations 'du' contexte et representations 'en' contexte? Eleves et enseignants face a l'apprentissage de la langue" ("Representations 'of' Context or Representations 'in' Context? Students and Teachers Facing Language Learning" (Laurent Gajo); "Le crepuscule…

  7. Exploring the Structure of Spatial Representations

    PubMed Central

    Madl, Tamas; Franklin, Stan; Chen, Ke; Trappl, Robert; Montaldi, Daniela

    2016-01-01

    It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these ‘cognitive maps’ are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics) characterizing participants’ psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants’ cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants’ spatial representations, providing further support for clustering in spatial memory. PMID:27347681

  8. Exploring the Structure of Spatial Representations.

    PubMed

    Madl, Tamas; Franklin, Stan; Chen, Ke; Trappl, Robert; Montaldi, Daniela

    2016-01-01

    It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these 'cognitive maps' are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics) characterizing participants' psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants' cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants' spatial representations, providing further support for clustering in spatial memory. PMID:27347681

  9. Using state diagrams for predicting colloidal stability of whey protein beverages.

    PubMed

    Wagoner, Ty B; Ward, Loren; Foegeding, E Allen

    2015-05-01

    A method for evaluating aspects of colloidal stability of whey protein beverages after thermal treatment was established. Three state diagrams for beverages (pH 3-7) were developed representing protein solubility, turbidity, and macroscopic state after two ultrahigh-temperature (UHT) treatments. Key transitions of stability in the state diagrams were explored using electrophoresis and chromatography to determine aggregation propensities of β-lactoglobulin, α-lactalbumin, bovine serum albumin, and glycomacropeptide. The state diagrams present an overlapping view of high colloidal stability at pH 3 accompanied by high solubility of individual whey proteins. At pH 5, beverages were characterized by poor solubility, high turbidity, and aggregation/gelation of whey proteins with the exception of glycomacropeptide. Stability increased at pH 6, due to increased solubility of α-lactalbumin. The results indicate that combinations of state diagrams can be used to identify key regions of stability for whey protein containing beverages.

  10. Evaluating High-Degree-and-Order Gravitational Harmonics and its Application to the State Predictions of a Lunar Orbiting Satellite

    NASA Astrophysics Data System (ADS)

    Song, Young-Joo; Kim, Bang-Yeop

    2015-09-01

    In this work, an efficient method with which to evaluate the high-degree-and-order gravitational harmonics of the nonsphericity of a central body is described and applied to state predictions of a lunar orbiter. Unlike the work of Song et al. (2010), which used a conventional computation method to process gravitational harmonic coefficients, the current work adapted a well-known recursion formula that directly uses fully normalized associated Legendre functions to compute the acceleration due to the non-sphericity of the moon. With the formulated algorithms, the states of a lunar orbiting satellite are predicted and its performance is validated in comparisons with solutions obtained from STK/Astrogator. The predicted differences in the orbital states between STK/Astrogator and the current work all remain at a position of less than 1 m with velocity accuracy levels of less than 1 mm/s, even with different orbital inclinations. The effectiveness of the current algorithm, in terms of both the computation time and the degree of accuracy degradation, is also shown in comparisons with results obtained from earlier work. It is expected that the proposed algorithm can be used as a foundation for the development of an operational flight dynamics subsystem for future lunar exploration missions by Korea. It can also be used to analyze missions which require very close operations to the moon.

  11. Action simulation: time course and representational mechanisms

    PubMed Central

    Springer, Anne; Parkinson, Jim; Prinz, Wolfgang

    2013-01-01

    The notion of action simulation refers to the ability to re-enact foreign actions (i.e., actions observed in other individuals). Simulating others' actions implies a mirroring of their activities, based on one's own sensorimotor competencies. Here, we discuss theoretical and experimental approaches to action simulation and the study of its representational underpinnings. One focus of our discussion is on the timing of internal simulation and its relation to the timing of external action, and a paradigm that requires participants to predict the future course of actions that are temporarily occluded from view. We address transitions between perceptual mechanisms (referring to action representation before and after occlusion) and simulation mechanisms (referring to action representation during occlusion). Findings suggest that action simulation runs in real-time; acting on newly created action representations rather than relying on continuous visual extrapolations. A further focus of our discussion pertains to the functional characteristics of the mechanisms involved in predicting other people's actions. We propose that two processes are engaged, dynamic updating and static matching, which may draw on both semantic and motor information. In a concluding section, we discuss these findings in the context of broader theoretical issues related to action and event representation, arguing that a detailed functional analysis of action simulation in cognitive, neural, and computational terms may help to further advance our understanding of action cognition and motor control. PMID:23847563

  12. Robust face recognition via sparse representation.

    PubMed

    Wright, John; Yang, Allen Y; Ganesh, Arvind; Sastry, S Shankar; Ma, Yi

    2009-02-01

    We consider the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise. We cast the recognition problem as one of classifying among multiple linear regression models and argue that new theory from sparse signal representation offers the key to addressing this problem. Based on a sparse representation computed by l{1}-minimization, we propose a general classification algorithm for (image-based) object recognition. This new framework provides new insights into two crucial issues in face recognition: feature extraction and robustness to occlusion. For feature extraction, we show that if sparsity in the recognition problem is properly harnessed, the choice of features is no longer critical. What is critical, however, is whether the number of features is sufficiently large and whether the sparse representation is correctly computed. Unconventional features such as downsampled images and random projections perform just as well as conventional features such as Eigenfaces and Laplacianfaces, as long as the dimension of the feature space surpasses certain threshold, predicted by the theory of sparse representation. This framework can handle errors due to occlusion and corruption uniformly by exploiting the fact that these errors are often sparse with respect to the standard (pixel) basis. The theory of sparse representation helps predict how much occlusion the recognition algorithm can handle and how to choose the training images to maximize robustness to occlusion. We conduct extensive experiments on publicly available databases to verify the efficacy of the proposed algorithm and corroborate the above claims.

  13. PREDICTING ACHIEVEMENT IN TECHNICAL PROGRAMS AT THE NORTH DAKOTA STATE SCHOOL OF SCIENCE.

    ERIC Educational Resources Information Center

    ANDERSON, ROGER C.

    DATA WERE COLLECTED FROM SCHOOL RECORDS FOR 876 STUDENTS ENROLLED IN SIX TECHNICAL PROGRAMS FROM 1961-63. THIS PROVIDES EIGHT BIOGRAPHICAL AND 17 ACADEMIC VARIABLES WHICH WERE EXAMINED FOR THEIR USEFULNESS IN PREDICTING STUDENT SUCCESS. THE STUDENT SAMPLE WAS DIVIDED INTO GRADUATES AND NONGRADUATES. NONGRADUATES WERE THOSE WHO ATTENDED FOUR OR…

  14. NIR models for predicting total sugar in tobacco for samples with different physical states

    NASA Astrophysics Data System (ADS)

    Qin, Yuhua; Gong, Huili

    2016-07-01

    Due to the spectra variation of the inhomogeneous tobacco flakes results the inaccuracy and instability of the near infrared model. This paper presented the strategies of calibration transfer and hybrid modeling for determining total sugar content in tobacco based on the homogeneous powder model. The necessity judgments and acceptance criteria of the calibration transfer were also proposed. Calibration transfer methods include Slope/Bias Correction (S/B), Piecewise Direct Standardization (PDS), double window piecewise direct standardization (DWPDS), and Shenk's were adopted, a transfer set of 15 samples were chosen for each methods, and the results showed that Shenk's is the adequate transfer method as only one indicator did not fulfill the acceptance criteria of the transfer. Other methods were all dissatisfied with the acceptance criteria and cannot be applied to the calibration transfer between the tobacco flake and powder. While the hybrid model of adding some flake samples to the powder model achieved preferred prediction ability. The study showed that adding around 10% variation samples caused the average prediction error of total sugar content (range 12.1-37.2%) in flake samples from 7.25% (predicted by a flake model) significantly dropping to 4.98%, even close to the prediction of the same powder samples (4.21%) by the powder model. It will valuable for the promotion of the NIR network and online analysis.

  15. An investigation of gear mesh failure prediction techniques. M.S. Thesis - Cleveland State Univ.

    NASA Technical Reports Server (NTRS)

    Zakrajsek, James J.

    1989-01-01

    A study was performed in which several gear failure prediction methods were investigated and applied to experimental data from a gear fatigue test apparatus. The primary objective was to provide a baseline understanding of the prediction methods and to evaluate their diagnostic capabilities. The methods investigated use the signal average in both the time and frequency domain to detect gear failure. Data from eleven gear fatigue tests were recorded at periodic time intervals as the gears were run from initiation to failure. Four major failure modes, consisting of heavy wear, tooth breakage, single pits, and distributed pitting were observed among the failed gears. Results show that the prediction methods were able to detect only those gear failures which involved heavy wear or distributed pitting. None of the methods could predict fatigue cracks, which resulted in tooth breakage, or single pits. It is suspected that the fatigue cracks were not detected because of limitations in data acquisition rather than in methodology. Additionally, the frequency response between the gear shaft and the transducer was found to significantly affect the vibration signal. The specific frequencies affected were filtered out of the signal average prior to application of the methods.

  16. Testing Predictive Models of Technology Integration in Mexico and the United States

    ERIC Educational Resources Information Center

    Velazquez, Cesareo Morales

    2008-01-01

    Data from Mexico City, Mexico (N = 978) and from Texas, USA (N = 932) were used to test the predictive validity of the teacher professional development component of the Will, Skill, Tool Model of Technology Integration in a cross-cultural context. Structural equation modeling (SEM) was used to test the model. Analyses of these data yielded…

  17. On the Factors Predicting Rehospitalization among Two State Mental Hospital Patient Populations.

    ERIC Educational Resources Information Center

    Nuehring, Elane M.; And Others

    1980-01-01

    Study examines background and performance characteristics of discharged mental hospital patients in an effort to predict readmissions. Results confirm complexity of the recidivism issue. Black, isolated males seem at greatest risk for readmission; Anglo females with family resources at least risk. (LAB)

  18. The Status of Secondary Science Education in the United States: Factors That Predict Practice

    ERIC Educational Resources Information Center

    Smith, Adrienne A.; Banilower, Eric R.; Nelson, Michele M.; Smith, P. Sean

    2013-01-01

    New K-12 science education standards emphasize teaching and learning grounded in authentic scientific practices. A first step toward supporting teachers' adoption of scientific practice-based pedagogies is to develop a clear picture of how teachers are currently teaching science, and what factors predict their pedagogical choices. A recently…

  19. Predicting geogenic arsenic contamination in shallow groundwater of south Louisiana, United States.

    PubMed

    Yang, Ningfang; Winkel, Lenny H E; Johannesson, Karen H

    2014-05-20

    Groundwater contaminated with arsenic (As) threatens the health of more than 140 million people worldwide. Previous studies indicate that geology and sedimentary depositional environments are important factors controlling groundwater As contamination. The Mississippi River delta has broadly similar geology and sedimentary depositional environments to the large deltas in South and Southeast Asia, which are severely affected by geogenic As contamination and therefore may also be vulnerable to groundwater As contamination. In this study, logistic regression is used to develop a probability model based on surface hydrology, soil properties, geology, and sedimentary depositional environments. The model is calibrated using 3286 aggregated and binary-coded groundwater As concentration measurements from Bangladesh and verified using 78 As measurements from south Louisiana. The model's predictions are in good agreement with the known spatial distribution of groundwater As contamination of Bangladesh, and the predictions also indicate high risk of As contamination in shallow groundwater from Holocene sediments of south Louisiana. Furthermore, the model correctly predicted 79% of the existing shallow groundwater As measurements in the study region, indicating good performance of the model in predicting groundwater As contamination in shallow aquifers of south Louisiana.

  20. Progress on implementation of process-based erosion prediction technology in the United States

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Use of soil erosion prediction models is becoming increasingly important due to growing environmental concerns and impacts of runoff and sediment on off-site water quality. The USDA Natural Resources Conservation Service (NRCS) has implemented and is now using the process-based Wind Erosion Predicti...

  1. Negative Ion Photoelectron Spectroscopy Confirms the Prediction that (CO)5 and (CO)6 Each Has a Singlet Ground State

    SciTech Connect

    Bao, Xiaoguang; Hrovat, David; Borden, Weston; Wang, Xue B.

    2013-03-20

    Cyclobutane-1,2,3,4-tetraone has been both predicted and found to have a triplet ground state, in which a b2g MO and an a2u MO is each singly occupied. In contrast, (CO)5 and (CO)6 have each been predicted to have a singlet ground state. This prediction has been tested by generating the (CO)5 - and (CO)6 - anions in the gas-phase by electrospray vaporization of solutions of, respectively, the croconate (CO)52- and rhodizonate (CO)62- dianions. The negative ion photoelectron (NIPE) spectra of the (CO)5•- radical anion give electron affinity (EA) = 3.830 eV and a singlet ground state for (CO)5, with the triplet higher in energy by 0.850 eV (19.6 kcal/mol). The NIPE spectra of the (CO)6•- radical anion give EA = 3.785 eV and a singlet ground state for (CO)6, with the triplet higher in energy by 0.915 eV (21.1 kcal/mol). (RO)CCSD(T)/aug-cc-pVTZ//(U)B3LYP/6-311+G(2df) calculations give EA values that are only ca. 1 kcal/mol lower than those measured and EST values that are only 2 - 3 kcal/mol higher than those obtained from the NIPE spectra. Thus, the calculations support the interpretations of the NIPE spectra and the finding, based on the spectra, that (CO)5 and (CO)6 both have a singlet ground state.

  2. Unitary Transformations in the Quantum Model for Conceptual Conjunctions and Its Application to Data Representation.

    PubMed

    Veloz, Tomas; Desjardins, Sylvie

    2015-01-01

    Quantum models of concept combinations have been successful in representing various experimental situations that cannot be accommodated by traditional models based on classical probability or fuzzy set theory. In many cases, the focus has been on producing a representation that fits experimental results to validate quantum models. However, these representations are not always consistent with the cognitive modeling principles. Moreover, some important issues related to the representation of concepts such as the dimensionality of the realization space, the uniqueness of solutions, and the compatibility of measurements, have been overlooked. In this paper, we provide a dimensional analysis of the realization space for the two-sector Fock space model for conjunction of concepts focusing on the first and second sectors separately. We then introduce various representation of concepts that arise from the use of unitary operators in the realization space. In these concrete representations, a pair of concepts and their combination are modeled by a single conceptual state, and by a collection of exemplar-dependent operators. Therefore, they are consistent with cognitive modeling principles. This framework not only provides a uniform approach to model an entire data set, but, because all measurement operators are expressed in the same basis, allows us to address the question of compatibility of measurements. In particular, we present evidence that it may be possible to predict non-commutative effects from partial measurements of conceptual combinations. PMID:26617556

  3. Hierarchical Error Representation: A Computational Model of Anterior Cingulate and Dorsolateral Prefrontal Cortex.

    PubMed

    Alexander, William H; Brown, Joshua W

    2015-11-01

    Anterior cingulate and dorsolateral prefrontal cortex (ACC and dlPFC, respectively) are core components of the cognitive control network. Activation of these regions is routinely observed in tasks that involve monitoring the external environment and maintaining information in order to generate appropriate responses. Despite the ubiquity of studies reporting coactivation of these two regions, a consensus on how they interact to support cognitive control has yet to emerge. In this letter, we present a new hypothesis and computational model of ACC and dlPFC. The error representation hypothesis states that multidimensional error signals generated by ACC in response to surprising outcomes are used to train representations of expected error in dlPFC, which are then associated with relevant task stimuli. Error representations maintained in dlPFC are in turn used to modulate predictive activity in ACC in order to generate better estimates of the likely outcomes of actions. We formalize the error representation hypothesis in a new computational model based on our previous model of ACC. The hierarchical error representation (HER) model of ACC/dlPFC suggests a mechanism by which hierarchically organized layers within ACC and dlPFC interact in order to solve sophisticated cognitive tasks. In a series of simulations, we demonstrate the ability of the HER model to autonomously learn to perform structured tasks in a manner comparable to human performance, and we show that the HER model outperforms current deep learning networks by an order of magnitude. PMID:26378874

  4. Unitary Transformations in the Quantum Model for Conceptual Conjunctions and Its Application to Data Representation

    PubMed Central

    Veloz, Tomas; Desjardins, Sylvie

    2015-01-01

    Quantum models of concept combinations have been successful in representing various experimental situations that cannot be accommodated by traditional models based on classical probability or fuzzy set theory. In many cases, the focus has been on producing a representation that fits experimental results to validate quantum models. However, these representations are not always consistent with the cognitive modeling principles. Moreover, some important issues related to the representation of concepts such as the dimensionality of the realization space, the uniqueness of solutions, and the compatibility of measurements, have been overlooked. In this paper, we provide a dimensional analysis of the realization space for the two-sector Fock space model for conjunction of concepts focusing on the first and second sectors separately. We then introduce various representation of concepts that arise from the use of unitary operators in the realization space. In these concrete representations, a pair of concepts and their combination are modeled by a single conceptual state, and by a collection of exemplar-dependent operators. Therefore, they are consistent with cognitive modeling principles. This framework not only provides a uniform approach to model an entire data set, but, because all measurement operators are expressed in the same basis, allows us to address the question of compatibility of measurements. In particular, we present evidence that it may be possible to predict non-commutative effects from partial measurements of conceptual combinations. PMID:26617556

  5. Mesolimbic Dopamine Encodes Prediction Errors in a State-Dependent Manner

    PubMed Central

    Papageorgiou, Georgios K.; Baudonnat, Mathieu; Cucca, Flavia; Walton, Mark E.

    2016-01-01

    Summary Mesolimbic dopamine encodes the benefits of a course of action. However, the value of an appetitive reward depends strongly on an animal’s current state. To investigate the relationship between dopamine, value, and physiological state, we monitored sub-second dopamine release in the nucleus accumbens core while rats made choices between food and sucrose solution following selective satiation on one of these reinforcers. Dopamine signals reflected preference for the reinforcers in the new state, decreasing to the devalued reward and, after satiation on food, increasing for the valued sucrose solution. These changes were rapid and selective, with dopamine release returning to pre-satiation patterns when the animals were re-tested in a standard food-restricted state. Such rapid and selective adaptation of dopamine-associated value signals could provide an important signal to promote efficient foraging for a varied diet. PMID:27050518

  6. Space-for-time substitution in predicting the state of picoplankton and nanoplankton in a changing Arctic Ocean

    NASA Astrophysics Data System (ADS)

    Li, William K. W.; Carmack, Eddy C.; McLaughlin, Fiona A.; Nelson, R. John; Williams, William J.

    2013-10-01

    The Arctic Ocean is changing rapidly but there are no long-term time series observations on the state of the phytoplankton community that could allow a link to be made from physical/chemical pressures to the impact on marine ecosystems. Here, we test the idea that space-for-time (SFT) substitution might predict temporal change in the Canada Basin premised on differences in the present state of phytoplankton in other geographic zones, specifically the ratio in the abundance of picophytoplankton to nanophytoplankton (Pico:Nano). We compared the change in Pico:Nano observed in the Canada Basin from 2004 to 2012 to the different average states of this ratio in 26 other ocean ecological regions. Our results show that as upper ocean nitrate concentration changed in the Canada Basin from year to year, the concomitant change in Pico:Nano was statistically commensurate with the difference that this ratio exhibits between Longhurst ecological provinces in relation to nitrate concentration. Lower average concentration of nitrate in the upper water column is associated with a higher value of Pico:Nano, a result consistent with resource control of phytoplankton size structure in the ocean. We suggest that SFT substitution allows an explanation of temporal progression from spatial pattern as a test of mechanism, but such statistical prediction is not necessarily a projection of future states.

  7. Resting-state fMRI activity predicts unsupervised learning and memory in an immersive virtual reality environment.

    PubMed

    Wong, Chi Wah; Olafsson, Valur; Plank, Markus; Snider, Joseph; Halgren, Eric; Poizner, Howard; Liu, Thomas T

    2014-01-01

    In the real world, learning often proceeds in an unsupervised manner without explicit instructions or feedback. In this study, we employed an experimental paradigm in which subjects explored an immersive virtual reality environment on each of two days. On day 1, subjects implicitly learned the location of 39 objects in an unsupervised fashion. On day 2, the locations of some of the objects were changed, and object location recall performance was assessed and found to vary across subjects. As prior work had shown that functional magnetic resonance imaging (fMRI) measures of resting-state brain activity can predict various measures of brain performance across individuals, we examined whether resting-state fMRI measures could be used to predict object location recall performance. We found a significant correlation between performance and the variability of the resting-state fMRI signal in the basal ganglia, hippocampus, amygdala, thalamus, insula, and regions in the frontal and temporal lobes, regions important for spatial exploration, learning, memory, and decision making. In addition, performance was significantly correlated with resting-state fMRI connectivity between the left caudate and the right fusiform gyrus, lateral occipital complex, and superior temporal gyrus. Given the basal ganglia's role in exploration, these findings suggest that tighter integration of the brain systems responsible for exploration and visuospatial processing may be critical for learning in a complex environment. PMID:25286145

  8. Resting-State fMRI Activity Predicts Unsupervised Learning and Memory in an Immersive Virtual Reality Environment

    PubMed Central

    Wong, Chi Wah; Olafsson, Valur; Plank, Markus; Snider, Joseph; Halgren, Eric; Poizner, Howard; Liu, Thomas T.

    2014-01-01

    In the real world, learning often proceeds in an unsupervised manner without explicit instructions or feedback. In this study, we employed an experimental paradigm in which subjects explored an immersive virtual reality environment on each of two days. On day 1, subjects implicitly learned the location of 39 objects in an unsupervised fashion. On day 2, the locations of some of the objects were changed, and object location recall performance was assessed and found to vary across subjects. As prior work had shown that functional magnetic resonance imaging (fMRI) measures of resting-state brain activity can predict various measures of brain performance across individuals, we examined whether resting-state fMRI measures could be used to predict object location recall performance. We found a significant correlation between performance and the variability of the resting-state fMRI signal in the basal ganglia, hippocampus, amygdala, thalamus, insula, and regions in the frontal and temporal lobes, regions important for spatial exploration, learning, memory, and decision making. In addition, performance was significantly correlated with resting-state fMRI connectivity between the left caudate and the right fusiform gyrus, lateral occipital complex, and superior temporal gyrus. Given the basal ganglia's role in exploration, these findings suggest that tighter integration of the brain systems responsible for exploration and visuospatial processing may be critical for learning in a complex environment. PMID:25286145

  9. Combining robust state estimation with nonlinear model predictive control to regulate the acute inflammatory response to pathogen.

    PubMed

    Zitelli, Gregory; Djouadi, Seddik M; Day, Judy D

    2015-10-01

    The inflammatory response aims to restore homeostasis by means of removing a biological stress, such as an invading bacterial pathogen. In cases of acute systemic inflammation, the possibility of collateral tissue damage arises, which leads to a necessary down-regulation of the response. A reduced ordinary differential equations (ODE) model of acute inflammation was presented and investigated in [10]. That system contains multiple positive and negative feedback loops and is a highly coupled and nonlinear ODE. The implementation of nonlinear model predictive control (NMPC) as a methodology for determining proper therapeutic intervention for in silico patients displaying complex inflammatory states was initially explored in [5]. Since direct measurements of the bacterial population and the magnitude of tissue damage/dysfunction are not readily available or biologically feasible, the need for robust state estimation was evident. In this present work, we present results on the nonlinear reachability of the underlying model, and then focus our attention on improving the predictability of the underlying model by coupling the NMPC with a particle filter. The results, though comparable to the initial exploratory study, show that robust state estimation of this highly nonlinear model can provide an alternative to prior updating strategies used when only partial access to the unmeasurable states of the system are available. PMID:26280180

  10. On the skill of numerical weather prediction models to forecast atmospheric rivers over the central United States

    NASA Astrophysics Data System (ADS)

    Nayak, Munir A.; Villarini, Gabriele; Lavers, David A.

    2014-06-01

    Flooding over the central United States is responsible for large socioeconomic losses. Atmospheric rivers (ARs), narrow regions of intense moisture transport within the warm conveyor belt of extratropical cyclones, can give rise to high rainfall amounts leading to flooding. Short-term forecasting of AR activity can provide basic information toward improving preparedness for these events. This study focuses on the verification of the skill of five numerical weather prediction models in forecasting AR activity over the central United States. We find that these models generally forecast AR occurrences well at short lead times, with location errors increasing from one to three decimal degrees as the lead time increases to about 1 week. The skill (both in terms of occurrence and location errors) decreases with increasing lead time. Overall, these models are not skillful in forecasting AR activity over the central United States beyond a lead time of about 7 days.

  11. Next-to-leading order predictions for Z gamma+jet and Z gamma gamma final states at the LHC

    SciTech Connect

    Campbell, John M.; Hartanto, Heribertus B.; Williams, Ciaran

    2012-11-01

    We present next-to-leading order predictions for final states containing leptons produced through the decay of a Z boson in association with either a photon and a jet, or a pair of photons. The effect of photon radiation from the final state leptons is included and we also allow for contributions arising from fragmentation processes. Phenomenological studies are presented for the LHC in the case of final states containing charged leptons and in the case of neutrinos. We also use the procedure introduced by Stewart and Tackmann to provide a reliable estimate of the scale uncertainty inherent in our theoretical calculations of jet-binned Z gamma cross sections. These computations have been implemented in the public code MCFM.

  12. Predicting Brook Trout occurrence in stream reaches throughout their native range in the eastern United States

    USGS Publications Warehouse

    DeWeber, Jefferson Tyrell; Wagner, Tyler

    2015-01-01

    The Brook Trout Salvelinus fontinalis is an important species of conservation concern in the eastern USA. We developed a model to predict Brook Trout population status within individual stream reaches throughout the species’ native range in the eastern USA. We utilized hierarchical logistic regression with Bayesian estimation to predict Brook Trout occurrence probability, and we allowed slopes and intercepts to vary among ecological drainage units (EDUs). Model performance was similar for 7,327 training samples and 1,832 validation samples based on the area under the receiver operating curve (∼0.78) and Cohen's kappa statistic (0.44). Predicted water temperature had a strong negative effect on Brook Trout occurrence probability at the stream reach scale and was also negatively associated with the EDU average probability of Brook Trout occurrence (i.e., EDU-specific intercepts). The effect of soil permeability was positive but decreased as EDU mean soil permeability increased. Brook Trout were less likely to occur in stream reaches surrounded by agricultural or developed land cover, and an interaction suggested that agricultural land cover also resulted in an increased sensitivity to water temperature. Our model provides a further understanding of how Brook Trout are shaped by habitat characteristics in the region and yields maps of stream-reach-scale predictions, which together can be used to support ongoing conservation and management efforts. These decision support tools can be used to identify the extent of potentially suitable habitat, estimate historic habitat losses, and prioritize conservation efforts by selecting suitable stream reaches for a given action. Future work could extend the model to account for additional landscape or habitat characteristics, include biotic interactions, or estimate potential Brook Trout responses to climate and land use changes.

  13. Investigating the potential of SST assimilation for ocean state estimation and climate prediction

    NASA Astrophysics Data System (ADS)

    Keenlyside, Noel; Counillon, Francois; Bethke, Ingo; Wang, Yiguo; Billeau, Sebastien; Shen, Mao-Lin; Bentsen, Mats

    2016-04-01

    The Norwegian Climate Prediction Model (NorCPM) assimilates the stochastic HadISST2 product with the ensemble Kalman Filter data assimilation method into the ocean part the Norwegian Earth System model. We document a pilot stochastic reanalysis for the period 1950-2010 and use it to perform seasonal-to-decadal (s2d) predictions. The accuracy, reliability and drift is investigated using both assimilated and independent observations. NorCPM is found slightly over-dispersive against assimilated observations but shows stable performance through the analysis period (˜0.4K). It demonstrates skill against independent measurements: SSH, heat and salt content, in particular in the ENSO, the North Pacific, the North Atlantic subpolar gyre (SPG) regions and the Nordic Seas. Furthermore, NorCPM provides a reliable monitoring of the SPG index and represents the variability of the temperature vertical structure there in good agreement with observations. The monitoring of the Atlantic meridional overturning circulation is also encouraging. The benefit of using flow dependent assimilation method and constructing the covariance in isopycnal coordinate are investigated in the SPG region. Isopycnal coordinate discretisation is found to better captures the vertical structure than standard depth-coordinate discretisation, which can deepen the influence of assimilation when assimilating surface observations. The vertical covariance shows a pronounced seasonal and decadal variability, which highlights the benefit of flow dependent data assimilation method. This study demonstrates the potential of NorCPM for providing a long reanalysis for the 19-20 century when SST observations are available. The results of s2d predictions carried out will be presented, and the potential to use this method to assess decadal predictability over the historical period will be discussed.

  14. Numerical prediction of the Mid-Atlantic states cyclone of 18-19 February 1979

    NASA Technical Reports Server (NTRS)

    Atlas, R.; Rosenberg, R.

    1982-01-01

    A series of forecast experiments was conducted to assess the accuracy of the GLAS model, and to determine the importance of large scale dynamical processes and diabatic heating to the cyclogenesis. The GLAS model correctly predicted intense coastal cyclogenesis and heavy precipitation. Repeated without surface heat and moisture fluxes, the model failed to predict any cyclone development. An extended range forecast, a forecast from the NMC analysis interpolated to the GLAS grid, and a forecast from the GLAS analysis with the surface moisture flux excluded predicted weak coastal low development. Diabatic heating resulting from oceanic fluxes significantly contributed to the generation of low level cyclonic vorticity and the intensification and slow rate of movement of an upper level ridge over the western Atlantic. As an upper level short wave trough approached this ridge, diabatic heating associated with the release of latent heat intensified, and the gradient of vorticity, vorticity advection and upper level divergence in advance of the trough were greatly increased, providing strong large scale forcing for the surface cyclogenesis.

  15. Twisted Fock representations of noncommutative Kähler manifolds

    NASA Astrophysics Data System (ADS)

    Sako, Akifumi; Umetsu, Hiroshi

    2016-09-01

    We introduce twisted Fock representations of noncommutative Kähler manifolds and give their explicit expressions. The twisted Fock representation is a representation of the Heisenberg like algebra whose states are constructed by applying creation operators to a vacuum state. "Twisted" means that creation operators are not Hermitian conjugate of annihilation operators in this representation. In deformation quantization of Kähler manifolds with separation of variables formulated by Karabegov, local complex coordinates and partial derivatives of the Kähler potential with respect to coordinates satisfy the commutation relations between the creation and annihilation operators. Based on these relations, we construct the twisted Fock representation of noncommutative Kähler manifolds and give a dictionary to translate between the twisted Fock representations and functions on noncommutative Kähler manifolds concretely.

  16. Predicting unsaturated zone nitrogen mass balances in agricultural settings of the United States.

    PubMed

    Nolan, Bernard T; Puckett, Larry J; Ma, Liwang; Green, Christopher T; Bayless, E Randall; Malone, Robert W

    2010-01-01

    Unsaturated zone N fate and transport were evaluated at four sites to identify the predominant pathways of N cycling: an almond [Prunus dulcis (Mill.) D.A. Webb] orchard and cornfield (Zea mays L.) in the lower Merced River study basin, California; and corn-soybean [Glycine max (L.) Merr.] rotations in study basins at Maple Creek, Nebraska, and at Morgan Creek, Maryland. We used inverse modeling with a new version of the Root Zone Water Quality Model (RZWQM2) to estimate soil hydraulic and nitrogen transformation parameters throughout the unsaturated zone; previous versions were limited to 3-m depth and relied on manual calibration. The overall goal of the modeling was to derive unsaturated zone N mass balances for the four sites. RZWQM2 showed promise for deeper simulation profiles. Relative root mean square error (RRMSE) values for predicted and observed nitrate concentrations in lysimeters were 0.40 and 0.52 for California (6.5 m depth) and Nebraska (10 m), respectively, and index of agreement (d) values were 0.60 and 0.71 (d varies between 0 and 1, with higher values indicating better agreement). For the shallow simulation profile (1 m) in Maryland, RRMSE and d for nitrate were 0.22 and 0.86, respectively. Except for Nebraska, predictions of average nitrate concentration at the bottom of the simulation profile agreed reasonably well with measured concentrations in monitoring wells. The largest additions of N were predicted to come from inorganic fertilizer (153-195 kg N ha(-1) yr(-1) in California) and N fixation (99 and 131 kg N ha(-1) yr(-1) in Maryland and Nebraska, respectively). Predicted N losses occurred primarily through plant uptake (144-237 kg N ha(-1) yr(-1)) and deep seepage out of the profile (56-102 kg N ha(-1) yr(-1)). Large reservoirs of organic N (up to 17,500 kg N ha(-1) m(-1) at Nebraska) were predicted to reside in the unsaturated zone, which has implications for potential future transfer of nitrate to groundwater.

  17. Low-dimensional representations of exact coherent states of the Navier-Stokes equations from the resolvent model of wall turbulence.

    PubMed

    Sharma, Ati S; Moarref, Rashad; McKeon, Beverley J; Park, Jae Sung; Graham, Michael D; Willis, Ashley P

    2016-02-01

    We report that many exact invariant solutions of the Navier-Stokes equations for both pipe and channel flows are well represented by just a few modes of the model of McKeon and Sharma [J. Fluid Mech. 658, 336 (2010)]. This model provides modes that act as a basis to decompose the velocity field, ordered by their amplitude of response to forcing arising from the interaction between scales. The model was originally derived from the Navier-Stokes equations to represent turbulent flows and has been used to explain coherent structure and to predict turbulent statistics. This establishes a surprising new link between the two distinct approaches to understanding turbulence. PMID:26986280

  18. Estimation of the Aral Sea state predictability based on the open data sources and the unique field observations

    NASA Astrophysics Data System (ADS)

    Izhitskiy, Alexander; Ayzel, Georgy; Zavialov, Peter; Kurbaniyazov, Abilgazi

    2016-04-01

    The Aral Sea, formerly one of the four largest lakes in the world, has lost over 90% of its volume during the dramatical dessication mainly caused by the severe alteration of water budget of the basin. Shrinkage of the Aral Sea resulted in profound changes of the lake's ecosystem, that became a subject for a number of publications based on a wide range of methods such as field observations, remote sensing data analysis and numerical modeling. However, by the early 21th century, the number of field studies decreased significantly due to almost complete cessation of navigation and displacement of the Aral's shoreline far away from roads and other infrastructure. Thus, only a small amount of field data (salinity, temperature, etc.) for different regions of the lake is available for the last two decades. On the other hand, a set of the open data sources (sea level variability, atmospheric reanalysis) were developed for the region. The main idea of the presented study is to estimate the possibility of prediction of the Aral Sea state using coupled system of basic geoanalysis tools, numerical modeling of hydrological cycle (both for sea and land-surface interactions with atmosphere) and state-of-art machine learning techniques. Firstly, available in situ data, obtained in the Aral Sea by Shirshov Institute and other researchers, are concerned as the "base points of state" for each year within the studied period. Secondly, consistent patterns in the interannual variability of all other available parameters, taken from the open data sources and numerical modeling predictions, are founded out. As a result, such an approach allows predicting the future state of sea basing on the possible climatic scenario.

  19. Prediction of spatially explicit rainfall intensity-duration thresholds for post-fire debris-flow generation in the western United States

    NASA Astrophysics Data System (ADS)

    Staley, Dennis; Negri, Jacquelyn; Kean, Jason

    2016-04-01

    burned areas. Our approach synthesizes the two methods by incorporating measured rainfall intensity into each model variable (based on measures of topographic steepness, burn severity and surface properties) within the logistic regression equation. This approach provides a more realistic representation of the relation between rainfall intensity and debris-flow likelihood, as likelihood values asymptotically approach zero when rainfall intensity approaches 0 mm/h, and increase with more intense rainfall. Model performance was evaluated by comparing predictions to several existing regional thresholds. The model, based upon training data collected in southern California, USA, has proven to accurately predict rainfall intensity-duration thresholds for other areas in the western United States not included in the original training dataset. In addition, the improved logistic regression model shows promise for emergency planning purposes and real-time, site-specific early warning. With further validation, this model may permit the prediction of spatially-explicit intensity-duration thresholds for debris-flow generation in areas where empirically derived regional thresholds do not exist. This improvement would permit the expansion of the early-warning system into other regions susceptible to post-fire debris flow.

  20. Spacecraft Attitude Representations

    NASA Technical Reports Server (NTRS)

    Markley, F. Landis

    1999-01-01

    The direction cosine matrix or attitude matrix is the most fundamental representation of the attitude, but it is very inefficient: It has six redundant parameters, it is difficult to enforce the six (orthogonality) constraints. the four-component quaternion representation is very convenient: it has only one redundant parameter, it is easy to enforce the normalization constraint, the attitude matrix is a homogeneous quadratic function of q, quaternion kinematics are bilinear in q and m. Euler angles are extensively used: they often have a physical interpretation, they provide a natural description of some spacecraft motions (COBE, MAP), but kinematics and attitude matrix involve trigonometric functions, "gimbal lock" for certain values of the angles. Other minimum (three-parameter) representations: Gibbs vector is infinite for 180 deg rotations, but useful for analysis, Modified Rodrigues Parameters are nonsingular, no trig functions, Rotation vector phi is nonsingular, but requires trig functions.

  1. Validation of a Previously Developed Geospatial Model That Predicts the Prevalence of Listeria monocytogenes in New York State Produce Fields.

    PubMed

    Weller, Daniel; Shiwakoti, Suvash; Bergholz, Peter; Grohn, Yrjo; Wiedmann, Martin; Strawn, Laura K

    2016-02-01

    Technological advancements, particularly in the field of geographic information systems (GIS), have made it possible to predict the likelihood of foodborne pathogen contamination in produce production environments using geospatial models. Yet, few studies have examined the validity and robustness of such models. This study was performed to test and refine the rules associated with a previously developed geospatial model that predicts the prevalence of Listeria monocytogenes in produce farms in New York State (NYS). Produce fields for each of four enrolled produce farms were categorized into areas of high or low predicted L. monocytogenes prevalence using rules based on a field's available water storage (AWS) and its proximity to water, impervious cover, and pastures. Drag swabs (n = 1,056) were collected from plots assigned to each risk category. Logistic regression, which tested the ability of each rule to accurately predict the prevalence of L. monocytogenes, validated the rules based on water and pasture. Samples collected near water (odds ratio [OR], 3.0) and pasture (OR, 2.9) showed a significantly increased likelihood of L. monocytogenes isolation compared to that for samples collected far from water and pasture. Generalized linear mixed models identified additional land cover factors associated with an increased likelihood of L. monocytogenes isolation, such as proximity to wetlands. These findings validated a subset of previously developed rules that predict L. monocytogenes prevalence in produce production environments. This suggests that GIS and geospatial models can be used to accurately predict L. monocytogenes prevalence on farms and can be used prospectively to minimize the risk of preharvest contamination of produce. PMID:26590280

  2. Validation of a Previously Developed Geospatial Model That Predicts the Prevalence of Listeria monocytogenes in New York State Produce Fields

    PubMed Central

    Weller, Daniel; Shiwakoti, Suvash; Bergholz, Peter; Grohn, Yrjo; Wiedmann, Martin

    2015-01-01

    Technological advancements, particularly in the field of geographic information systems (GIS), have made it possible to predict the likelihood of foodborne pathogen contamination in produce production environments using geospatial models. Yet, few studies have examined the validity and robustness of such models. This study was performed to test and refine the rules associated with a previously developed geospatial model that predicts the prevalence of Listeria monocytogenes in produce farms in New York State (NYS). Produce fields for each of four enrolled produce farms were categorized into areas of high or low predicted L. monocytogenes prevalence using rules based on a field's available water storage (AWS) and its proximity to water, impervious cover, and pastures. Drag swabs (n = 1,056) were collected from plots assigned to each risk category. Logistic regression, which tested the ability of each rule to accurately predict the prevalence of L. monocytogenes, validated the rules based on water and pasture. Samples collected near water (odds ratio [OR], 3.0) and pasture (OR, 2.9) showed a significantly increased likelihood of L. monocytogenes isolation compared to that for samples collected far from water and pasture. Generalized linear mixed models identified additional land cover factors associated with an increased likelihood of L. monocytogenes isolation, such as proximity to wetlands. These findings validated a subset of previously developed rules that predict L. monocytogenes prevalence in produce production environments. This suggests that GIS and geospatial models can be used to accurately predict L. monocytogenes prevalence on farms and can be used prospectively to minimize the risk of preharvest contamination of produce. PMID:26590280

  3. A new equation of state for better liquid density prediction of natural gas systems

    NASA Astrophysics Data System (ADS)

    Nwankwo, Princess C.

    Equations of state formulations, modifications and applications have remained active research areas since the success of van der Waal's equation in 1873. The need for better reservoir fluid modeling and characterization is of great importance to petroleum engineers who deal with thermodynamic related properties of petroleum fluids at every stage of the petroleum "life span" from its drilling, to production through the wellbore, to transportation, metering and storage. Equations of state methods are far less expensive (in terms of material cost and time) than laboratory or experimental forages and the results are interestingly not too far removed from the limits of acceptable accuracy. In most cases, the degree of accuracy obtained, by using various EOS's, though not appreciable, have been acceptable when considering the gain in time. The possibility of obtaining an equation of state which though simple in form and in use, could have the potential of further narrowing the present existing bias between experimentally determined and popular EOS estimated results spurred the interest that resulted in this study. This research study had as its chief objective, to develop a new equation of state that would more efficiently capture the thermodynamic properties of gas condensate fluids, especially the liquid phase density, which is the major weakness of other established and popular cubic equations of state. The set objective was satisfied by a new semi analytical cubic three parameter equation of state, derived by the modification of the attraction term contribution to pressure of the van der Waal EOS without compromising either structural simplicity or accuracy of estimating other vapor liquid equilibria properties. The application of new EOS to single and multi-component light hydrocarbon fluids recorded far lower error values than does the popular two parameter, Peng-Robinson's (PR) and three parameter Patel-Teja's (PT) equations of state. Furthermore, this research

  4. Representation and theory of mind development.

    PubMed

    Walker, Rebecca F; Murachver, Tamar

    2012-03-01

    This longitudinal study investigated the relation between children's early use of symbols and their later understanding of representation and metarepresentation. The performance of 64 children on DeLoache's (1987) scale model task was measured at 30, 36, and 42 months, and their false belief understanding was measured at 42 and 48 months. Language and executive function measures were taken at each time point. Scale model performance was related to concurrent and subsequent false belief understanding, and scale model performance both predicted and was predicted by language across time. Language predicted false belief within and across time, and with increasing age it mediated the relation between success on the scale model task and false belief understanding. Although executive function was related to performance on scale model and theory of mind tasks, it did not mediate the relation between these. This study provides evidence suggesting that symbolic functioning, language, and theory of mind may form part of a single skill set underlying symbolic representation.

  5. Digital representation of a map showing the thickness and character of Quaternary sediments in the glaciated United States east of the Rocky Mountains

    USGS Publications Warehouse

    Soller, D.R.; Packard, Patricia H.

    1998-01-01

    This CD-ROM contains vector-based digital geologic maps of the surficial deposits in parts of 23 states where continental glaciation occurred during the Quaternary. These maps, at 1:1,000,000-scale, include the texture of the surface sediments and the total thickness of Quaternary sediments. Map compilation was based on about 850 sources of information. These maps are also published in paper form, as U.S. Geological Survey Miscellaneous investigations Series Map I-1970-A, B, C, and D.

  6. Umbra's system representation.

    SciTech Connect

    McDonald, Michael James

    2005-07-01

    This document describes the Umbra System representation. Umbra System representation, initially developed in the spring of 2003, is implemented in Incr/Tcl using concepts borrowed from Carnegie Mellon University's Architecture Description Language (ADL) called Acme. In the spring of 2004 through January 2005, System was converted to Umbra 4, extended slightly, and adopted as the underlying software system for a variety of Umbra applications that support Complex Systems Engineering (CSE) and Complex Adaptive Systems Engineering (CASE). System is now a standard part Of Umbra 4. While Umbra 4 also includes an XML parser for System, the XML parser and Schema are not described in this document.

  7. Updated Graizer-Kalkan Ground Motion Prediction Equations for Western United States

    NASA Astrophysics Data System (ADS)

    Graizer, V.

    2013-12-01

    Ground motion prediction equations (GMPEs) for peak-ground acceleration (PGA) and 5-percent damped pseudo spectral accelerations (SA) of horizontal component ground motions were developed by Graizer and Kalkan (2007, 2009) using the extended ground motion database of the Next Generation of Attenuation project for shallow crustal earthquakes in active tectonic regions. The main features of these GMPEs (GK09) are: (1) only most essential measureable parameters [moment magnitude (M), closest distance to the fault rupture, style of faulting and average shear-wave velocity in the upper 30 meters of profile under the site (Vs30)] are used; (2) predictive model for SA is a continuous function of spectral period (T), which eliminates the standard matrix of estimator coefficients, and allows for calculation of SA at any period of interest within the model range of 0.01 to 10 sec; (3) mathematical form of GMPEs constitutes a series of filters--each filter represents a certain physical phenomenon affecting the radiation of seismic waves from the source. In contrast to the existing GMPEs, GK09 predictive model allows PGA to reach its maximum value at some distance from the fault effectively capturing the phenomenon observed in earthquakes with large number of near-source recordings such as the 1979 (M6.5) Imperial Valley and the 2004 (M6.0) Parkfield earthquakes. The GK09 GMPEs are shown to provide accuracy (expected median prediction without significant bias) and efficiency (relatively small standard error of predictions) as compared to recorded data at distances of up to 250 km during recent shallow-crustal earthquakes with 5.0≤M≤7.9 including the 2008 (M7.9) Wenchuan (China), 2010 (M7.2) El-Mayor Cucapah (Mexico), 2011 (M6.3) Christchurch (New Zealand) and other earthquakes. The GK09 GMPEs are updated here by adding an anelastic attenuation filter as a function of quality-factor (Q), and by improving the existing basin-effect filter, which is now a function of depth

  8. Habitat and Vegetation Variables Are Not Enough When Predicting Tick Populations in the Southeastern United States

    PubMed Central

    Trout Fryxell, R. T.; Moore, J. E.; Collins, M. D.; Kwon, Y.; Jean-Philippe, S. R.; Schaeffer, S. M.; Odoi, A.; Kennedy, M.; Houston, A. E.

    2015-01-01

    Two tick-borne diseases with expanding case and vector distributions are ehrlichiosis (transmitted by Amblyomma americanum) and rickettiosis (transmitted by A. maculatum and Dermacentor variabilis). There is a critical need to identify the specific habitats where each of these species is likely to be encountered to classify and pinpoint risk areas. Consequently, an in-depth tick prevalence study was conducted on the dominant ticks in the southeast. Vegetation, soil, and remote sensing data were used to test the hypothesis that habitat and vegetation variables can predict tick abundances. No variables were significant predictors of A. americanum adult and nymph tick abundance, and no clustering was evident because this species was found throughout the study area. For A. maculatum adult tick abundance was predicted by NDVI and by the interaction between habitat type and plant diversity; two significant population clusters were identified in a heterogeneous area suitable for quail habitat. For D. variabilis no environmental variables were significant predictors of adult abundance; however, D. variabilis collections clustered in three significant areas best described as agriculture areas with defined edges. This study identified few landscape and vegetation variables associated with tick presence. While some variables were significantly associated with tick populations, the amount of explained variation was not useful for predicting reliably where ticks occur; consequently, additional research that includes multiple sampling seasons and locations throughout the southeast are warranted. This low amount of explained variation may also be due to the use of hosts for dispersal, and potentially to other abiotic and biotic variables. Host species play a large role in the establishment, maintenance, and dispersal of a tick species, as well as the maintenance of disease cycles, dispersal to new areas, and identification of risk areas. PMID:26656122

  9. Habitat and Vegetation Variables Are Not Enough When Predicting Tick Populations in the Southeastern United States.

    PubMed

    Trout Fryxell, R T; Moore, J E; Collins, M D; Kwon, Y; Jean-Philippe, S R; Schaeffer, S M; Odoi, A; Kennedy, M; Houston, A E

    2015-01-01

    Two tick-borne diseases with expanding case and vector distributions are ehrlichiosis (transmitted by Amblyomma americanum) and rickettiosis (transmitted by A. maculatum and Dermacentor variabilis). There is a critical need to identify the specific habitats where each of these species is likely to be encountered to classify and pinpoint risk areas. Consequently, an in-depth tick prevalence study was conducted on the dominant ticks in the southeast. Vegetation, soil, and remote sensing data were used to test the hypothesis that habitat and vegetation variables can predict tick abundances. No variables were significant predictors of A. americanum adult and nymph tick abundance, and no clustering was evident because this species was found throughout the study area. For A. maculatum adult tick abundance was predicted by NDVI and by the interaction between habitat type and plant diversity; two significant population clusters were identified in a heterogeneous area suitable for quail habitat. For D. variabilis no environmental variables were significant predictors of adult abundance; however, D. variabilis collections clustered in three significant areas best described as agriculture areas with defined edges. This study identified few landscape and vegetation variables associated with tick presence. While some variables were significantly associated with tick populations, the amount of explained variation was not useful for predicting reliably where ticks occur; consequently, additional research that includes multiple sampling seasons and locations throughout the southeast are warranted. This low amount of explained variation may also be due to the use of hosts for dispersal, and potentially to other abiotic and biotic variables. Host species play a large role in the establishment, maintenance, and dispersal of a tick species, as well as the maintenance of disease cycles, dispersal to new areas, and identification of risk areas.

  10. Computer program simplifies transient and steady-state temperature prediction for complex body shapes

    NASA Technical Reports Server (NTRS)

    Giebler, K. N.

    1966-01-01

    Computer program evaluates heat transfer modes and calculates either the transient or steady-state temperature distributions throughout an object of complex shape when heat sources are applied to specified points on the object. It uses an electrothermal model to simulate the conductance, heat capacity, and temperature potential of the object.

  11. The Effectiveness of Six Personality Variables in Predicting Success on the Nursing State Board Examination.

    ERIC Educational Resources Information Center

    Cusick, Patricia; Harckham, Laura D.

    A study was conducted to determine whether six personality variables, presently used in admissions decisions by a nursing school, were effective predictors of success on the State Board Examination (SBE), the nursing licensing examination. The personality variables were measured by subtests of the Personal Preference Schedule of the Psychological…

  12. Theoretical prediction of the vibrational spectrum of naphthalene in the first excited singlet state

    NASA Astrophysics Data System (ADS)

    Swiderek, Petra; Hohlneicher, Georg; Maluendes, Sergio A.; Dupuis, Michel

    1993-01-01

    Complete harmonic force fields have been calculated for the ground state (S0) and the first excited singlet state (S1) of naphthalene using the multiconfiguration self-consistent field (MCSCF) approach. Identical calculations were performed for benzene to test the methodology with already available theoretical and empirical force fields. Two different basis sets were applied (STO-3G and near double-zeta) and all π-orbitals included in the active space. The geometries of ground and excited states were separately optimized. Following the ideas of Pulay, the force constants were scaled before calculating frequencies and normal modes. For the ground states the influence of correlation is discussed by comparison with Pulay's results. Except for special vibrations where correlation effects turn out to be important, the use of Pulay's scaling factors leads to a satisfactory description of the in-plane-vibrations. In the case of benzene the calculated frequency shifts between S0 and S1 are in complete qualitative agreement with experimental observations. In the case of naphthalene the new theoretical results suggest several revisions of earlier empirical assignments.

  13. Prediction of the dissociation constant pKa of organic acids from local molecular parameters of their electronic ground state.

    PubMed

    Yu, Haiying; Kühne, Ralph; Ebert, Ralf-Uwe; Schüürmann, Gerrit

    2011-09-26

    A quantum chemical method has been developed to estimate the dissociation constant pK(a) of organic acids from their neutral molecular structures by employing electronic structure properties. The data set covers 219 phenols (including 29 phenols with intramolecular H-bonding), 150 aromatic carboxylic acids, 190 aliphatic carboxylic acids, and 138 alcohols, with pK(a) varying by 16 units (0.38-16.80). Optimized ground-state geometries employing the semiempirical AM1 Hamiltonian have been used to quantify the site-specific molecular readiness to donate or accept electron charge in terms of both charge-associated energies and energy-associated charges, augmented by an ortho substitution indicator for aromatic compounds. The resultant regression models yield squared correlation coefficients (r(2)) from 0.82 to 0.90 and root-mean-square errors (rms) from 0.39 to 0.70 pK(a) units, corresponding to an overall (subset-weighted) r(2) of 0.86. Simulated external validation, leave-10%-out cross-validation and target value scrambling demonstrate the statistical robustness and prediction power of the derived model suite. The low intercorrelation with prediction errors from the commercial ACD package provides opportunity for a consensus model approach, offering a pragmatic way for further increasing the confidence in prediction significantly. Interestingly, inclusion of calculated free energies of aqueous solvation does not improve the prediction performance, probably because of the limited precision provided by available continuum-solvation models.

  14. Extracting the tropospheric short-wave influences on subseasonal prediction of precipitation in the United States using CFSv2

    NASA Astrophysics Data System (ADS)

    Schroeder, Martin; Wang, S.-Y. Simon; Gillies, Robert R.; Hsu, Huang-Hsiung

    2016-08-01

    The development of subseasonal precipitation forecasts on regional scales is becoming an active area of research. Climate forecast models have shown deficiencies in predicting the extreme precipitation anomalies at medium to long-range timescales. This study explores the subseasonal relationships between tropospheric short-waves and regional precipitation anomalies across the continental United States and evaluates capabilities of the NCEP Climate Forecast System Version 2 (CFSv2) in resolving these relationships. A regional precipitation proxy is derived from the prediction of the upper tropospheric short-waves based on multiple linear regressions. Across the six climate regions defined by NOAA, the 30-day reforecasts of this short-wave based precipitation proxy are compared to identify the combinations of month and zonal wavenumber that exhibit the highest prediction score. Forecast of this precipitation proxy over certain regions is found to outperform the direct precipitation output of CFSv2 out to 4 weeks, suggesting a subseasonal predictability in precipitation that can be harvested from persistent circulation features.

  15. Climate downscaling effects on predictive ecological models: a case study for threatened and endangered vertebrates in the southeastern United States

    USGS Publications Warehouse

    Bucklin, David N.; Watling, James I.; Speroterra, Carolina; Brandt, Laura A.; Mazzotti, Frank J.; Romañach, Stephanie S.

    2013-01-01

    High-resolution (downscaled) projections of future climate conditions are critical inputs to a wide variety of ecological and socioeconomic models and are created using numerous different approaches. Here, we conduct a sensitivity analysis of spatial predictions from climate envelope models for threatened and endangered vertebrates in the southeastern United States to determine whether two different downscaling approaches (with and without the use of a regional climate model) affect climate envelope model predictions when all other sources of variation are held constant. We found that prediction maps differed spatially between downscaling approaches and that the variation attributable to downscaling technique was comparable to variation between maps generated using different general circulation models (GCMs). Precipitation variables tended to show greater discrepancies between downscaling techniques than temperature variables, and for one GCM, there was evidence that more poorly resolved precipitation variables contributed relatively more to model uncertainty than more well-resolved variables. Our work suggests that ecological modelers requiring high-resolution climate projections should carefully consider the type of downscaling applied to the climate projections prior to their use in predictive ecological modeling. The uncertainty associated with alternative downscaling methods may rival that of other, more widely appreciated sources of variation, such as the general circulation model or emissions scenario with which future climate projections are created.

  16. Prediction of the Functional Performance of Machined Components Based on Surface Topography: State of the Art

    NASA Astrophysics Data System (ADS)

    Grzesik, Wit

    2016-10-01

    This survey overviews the functional performance of manufactured components produced by typical finishing machining operations in terms of their topographical characteristics. Surface topographies were characterized using both profile (2D) and 3D (areal) surface roughness parameters. The prediction of typical functional properties such as fatigue, friction, wear, bonding and corrosion is discussed based on appropriate surface roughness parameters. Some examples of real 3D surface topographies produced with desired functional characteristics are provided. This survey highlights technological possibilities of producing surfaces with enhanced functional properties by machining processes.

  17. Prediction of the Functional Performance of Machined Components Based on Surface Topography: State of the Art

    NASA Astrophysics Data System (ADS)

    Grzesik, Wit

    2016-08-01

    This survey overviews the functional performance of manufactured components produced by typical finishing machining operations in terms of their topographical characteristics. Surface topographies were characterized using both profile (2D) and 3D (areal) surface roughness parameters. The prediction of typical functional properties such as fatigue, friction, wear, bonding and corrosion is discussed based on appropriate surface roughness parameters. Some examples of real 3D surface topographies produced with desired functional characteristics are provided. This survey highlights technological possibilities of producing surfaces with enhanced functional properties by machining processes.

  18. Monitoring of the stress state variations of the Southern California for the purpose of earthquake prediction

    NASA Astrophysics Data System (ADS)

    Gokhberg, M.; Garagash, I.; Bondur, V.; Steblov, G. M.

    2014-12-01

    The three-dimensional geomechanical model of Southern California was developed, including a mountain relief, fault tectonics and characteristic internal features such as the roof of the consolidated crust and Moho surface. The initial stress state of the model is governed by the gravitational forces and horizontal tectonic motions estimated from GPS observations. The analysis shows that the three-dimensional geomechanical models allows monitoring of the changes in the stress state during the seismic process in order to constrain the distribution of the future places with increasing seismic activity. This investigation demonstrates one of possible approach to monitor upcoming seismicity for the periods of days - weeks - months. Continuous analysis of the stress state was carried out during 2009-2014. Each new earthquake with М~1 and above from USGS catalog was considered as the new defect of the Earth crust which has some definite size and causes redistribution of the stress state. Overall calculation technique was based on the single function of the Earth crust damage, recalculated each half month. As a result each half month in the upper crust layers and partially in the middle layers we revealed locations of the maximal values of the stress state parameters: elastic energy density, shear stress, proximity of the earth crust layers to their strength limit. All these parameters exhibit similar spatial and temporal distribution. How follows from observations all four strongest events with М ~ 5.5-7.2 occurred in South California during the analyzed period were prefaced by the parameters anomalies in peculiar advance time of weeks-months in the vicinity of 10-50 km from the upcoming earthquake. After the event the stress state source disappeared. The figure shows migration of the maximums of the stress state variations gradients (parameter D) in the vicinity of the epicenter of the earthquake 04.04.2010 with М=7.2 in the period of 01.01.2010-01.05.2010. Grey lines

  19. V-Notched Bar Creep Life Prediction: GH3536 Ni-Based Superalloy Under Multiaxial Stress State

    NASA Astrophysics Data System (ADS)

    Zhang, D. X.; Wang, J. P.; Wen, Z. X.; Liu, D. S.; Yue, Z. F.

    2016-07-01

    In this study, creep experiments on smooth and circumferential V-type notched round bars were conducted in GH3536 Ni-based superalloy at 750 °C to identify notch strengthening effect in notched specimens. FE analysis was carried out, coupled with continuum damage mechanics (CDM), to analyze stress distribution and damage evolution under multiaxial stress state. The creep deformation of smooth specimens and the rupture life of both smooth and notched specimens showed good agreement between experimental results and FE analysis predictions; the creep rupture life for the notched specimen was successfully predicted via the "skeletal point" concept. Both creep damage analysis and the observed fracture morphology suggest that creep rupture started first at the root in the V-type notched specimens, and shifted to the region close to the notch root when the notch was relatively shallow compared to U-type notched specimens.

  20. Fuel particles in the Chernobyl cooling pond: current state and prediction for remediation options.

    PubMed

    Bulgakov, A; Konoplev, A; Smith, J; Laptev, G; Voitsekhovich, O

    2009-04-01

    During the coming years, a management and remediation strategy for the Chernobyl cooling pond (CP) will be implemented. Remediation options include a controlled reduction in surface water level of the cooling pond and stabilisation of exposed sediments. In terrestrial soils, fuel particles deposited during the Chernobyl accident have now almost completely disintegrated. However, in the CP sediments the majority of (90)Sr activity is still in the form of fuel particles. Due to the low dissolved oxygen concentration and high pH, dissolution of fuel particles in the CP sediments is significantly slower than in soils. After the planned cessation of water pumping from the Pripyat River to the Pond, significant areas of sediments will be drained and exposed to the air. This will significantly enhance the dissolution rate and, correspondingly, the mobility and bioavailability of radionuclides will increase with time. The rate of acidification of exposed bottom sediments was predicted on the basis of acidification of similar soils after liming. Using empirical equations relating the fuel particle dissolution rate to soil and sediment pH allowed prediction of fuel particle dissolution and (90)Sr mobilisation for different remediation scenarios. It is shown that in exposed sediments, fuel particles will be almost completely dissolved in 15-25 years, while in parts of the cooling pond which remain flooded, fuel particle dissolution will take about a century. PMID:19185396

  1. Life and death in the Lone Star State: three decades of violence predictions by capital juries.

    PubMed

    Cunningham, Mark D; Sorensen, Jon R; Vigen, Mark P; Woods, S O

    2011-01-01

    The accuracy of three decades of Texas jury predictions of future violence by capital defendants was tested through retrospective review of the disciplinary records of former death row (FDR) inmates in Texas (N = 111) who had been sentenced to death under this "special issue" and subsequently obtained relief from their death sentences between 1989 and 2008. FDR inmates typically had extended tenures on death row (M = 9.9 years) and post-relief in the general prison population (M = 8.4 years). FDR prevalence of serious assault was low, both on death row (3.6%) and upon entering the prison population (4.5%). None of the assaults resulted in life-threatening injuries to the victims. Violence among the FDR inmates was not disproportionate compared with life-sentenced capital offenders. Consistent with other research, juror expectations of serious prison violence by these offenders had high error (i.e., false positive) rates. The confidence of legislators and courts in the violence prediction capabilities of capital jurors is misplaced.

  2. Negative emotions predict elevated interleukin-6 in the United States but not in Japan.

    PubMed

    Miyamoto, Yuri; Boylan, Jennifer Morozink; Coe, Christopher L; Curhan, Katherine B; Levine, Cynthia S; Markus, Hazel Rose; Park, Jiyoung; Kitayama, Shinobu; Kawakami, Norito; Karasawa, Mayumi; Love, Gayle D; Ryff, Carol D

    2013-11-01

    Previous studies conducted in Western cultures have shown that negative emotions predict higher levels of pro-inflammatory biomarkers, specifically interleukin-6 (IL-6). This link between negative emotions and IL-6 may be specific to Western cultures where negative emotions are perceived to be problematic and thus may not extend to Eastern cultures where negative emotions are seen as acceptable and normal. Using samples of 1044 American and 382 Japanese middle-aged and older adults, we investigated whether the relationship between negative emotions and IL-6 varies by cultural context. Negative emotions predicted higher IL-6 among American adults, whereas no association was evident among Japanese adults. Furthermore, the interaction between culture and negative emotions remained even after controlling for demographic variables, psychological factors (positive emotions, neuroticism, extraversion), health behaviors (smoking status, alcohol consumption), and health status (chronic conditions, BMI). These findings highlight the role of cultural context in shaping how negative emotions affect inflammatory physiology and underscore the importance of cultural ideas and practices relevant to negative emotions for understanding of the interplay between psychology, physiology, and health.

  3. Negative Emotions Predict Elevated Interleukin-6 in the United States but not in Japan

    PubMed Central

    Miyamoto, Yuri; Boylan, Jennifer Morozink; Coe, Christopher L.; Curhan, Katherine B.; Levine, Cynthia S.; Markus, Hazel Rose; Park, Jiyoung; Kitayama, Shinobu; Kawakami, Norito; Karasawa, Mayumi; Love, Gayle D.; Ryff, Carol D.

    2013-01-01

    Previous studies conducted in Western cultures have shown that negative emotions predict higher levels of pro-inflammatory biomarkers, specifically interleukin-6 (IL-6). This link between negative emotions and IL-6 may be specific to Western cultures where negative emotions are perceived to be problematic and thus may not extend to Eastern cultures where negative emotions are seen as acceptable and normal. Using samples of 1044 American and 382 Japanese middle-aged and older adults, we investigated whether the relationship between negative emotions and IL-6 varies by cultural context. Negative emotions predicted higher IL-6 among American adults, whereas no association was evident among Japanese adults. Furthermore, the interaction between culture and negative emotions remained even after controlling for demographic variables, psychological factors (positive emotions, neuroticism, extraversion), health behaviors (smoking status, alcohol consumption), and health status (chronic conditions, BMI). These findings highlight the role of cultural context in shaping how negative emotions affect inflammatory physiology and underscore the importance of cultural ideas and practices relevant to negative emotions for understanding of the interplay between psychology, physiology, and health. PMID:23911591

  4. Impact of Stoichiometry Representation on Simulation of Genotype-Phenotype Relationships in Metabolic Networks

    PubMed Central

    Brochado, Ana Rita; Andrejev, Sergej; Maranas, Costas D.; Patil, Kiran R.

    2012-01-01

    Genome-scale metabolic networks provide a comprehensive structural framework for modeling genotype-phenotype relationships through flux simulations. The solution space for the metabolic flux state of the cell is typically very large and optimization-based approaches are often necessary for predicting the active metabolic state under specific environmental conditions. The objective function to be used in such optimization algorithms is directly linked with the biological hypothesis underlying the model and therefore it is one of the most relevant parameters for successful modeling. Although linear combination of selected fluxes is widely used for formulating metabolic objective functions, we show that the resulting optimization problem is sensitive towards stoichiometry representation of the metabolic network. This undesirable sensitivity leads to different simulation results when using numerically different but biochemically equivalent stoichiometry representations and thereby makes biological interpretation intrinsically subjective and ambiguous. We hereby propose a new method, Minimization of Metabolites Balance (MiMBl), which decouples the artifacts of stoichiometry representation from the formulation of the desired objective functions, by casting objective functions using metabolite turnovers rather than fluxes. By simulating perturbed metabolic networks, we demonstrate that the use of stoichiometry representation independent algorithms is fundamental for unambiguously linking modeling results with biological interpretation. For example, MiMBl allowed us to expand the scope of metabolic modeling in elucidating the mechanistic basis of several genetic interactions in Saccharomyces cerevisiae. PMID:23133362

  5. Online state of health estimation on NMC cells based on predictive analytics

    NASA Astrophysics Data System (ADS)

    Berecibar, Maitane; Devriendt, Floris; Dubarry, Matthieu; Villarreal, Igor; Omar, Noshin; Verbeke, Wouter; Van Mierlo, Joeri

    2016-07-01

    Accurate on board state of health estimation is a key battery management system function to provide optimal management of the battery system under control. In this regard, this paper presents an extensive study and comparison of three of commonly used supervised learning methods for state of health estimation in Graphite/Nickel Manganese Cobalt oxide cells. The three methods were based from the study of both incremental capacity and differential voltage curves. According to the ageing evolution of both curves, features were extracted and used as inputs for the estimation techniques. Ordinary Least Squares, Multilayer Perceptron and Support Vector Machine were used as the estimation techniques and accurate results were obtained while requiring a low computational effort. Moreover, this work allows a deep comparison of the different estimation techniques in terms of accuracy, online estimation and BMS applicability. In addition, estimation can be developed by partial charging and/or partial discharging, reducing the required maintenance time.

  6. An assessment of the state of the art in predicting the failure of ceramics: Final report

    SciTech Connect

    Boulet, J.A.M.

    1988-03-01

    The greatest weakness in existing design strategies for brittle fracture is in the narrow range of conditions for which the strategies are adequate. The primary reason for this weakness is the use of simplistic mechanical models of fracture processes and unverified statistical models of materials. To improve the design methodology, the models must first be improved. Specifically recommended research goals are: to develop models of cracks with realistic geometry under arbitrary stress states; to identify and model the most important relationships between fracture processes and microstructural features; to assess the technology available for acquiring statistical data on microstructure and flaw populations, and to establish the amount of data required for verification of statistical models; and to establish a computer-based fracture simulation that can incorporate a wide variety of mechanical and statistical models and crack geometries, as well as arbitrary stress states. 204 refs., 2 tabs.

  7. From steroid hormones to depressive states and senile dementias: New mechanistic, therapeutical and predictive approaches.

    PubMed

    Baulieu, Étienne-Émile

    2015-01-01

    The discovery of "neurosteroids" leads to new descriptions and treatments of neuro-pathological pathologies. 3-β-methoxy-pregnenolone may be used to treat alterations of neuro-traumatisms and cerebral lesions associated with depressive states. Protein FKBP52 is involved in the dysfunction of the tau protein in Alzheimer's disease and senile dementias. In all cases, neuronal microtubules are involved in the mechanism of lesions and their repair.

  8. Resting-state Networks Predict Individual Differences in Common and Specific Aspects of Executive Function

    PubMed Central

    Reineberg, Andrew E.; Andrews-Hanna, Jessica R.; Depue, Brendan; Friedman, Naomi P.; Banich, Marie T.

    2014-01-01

    The goal of the present study was to examine relationships between individual differences in resting state functional connectivity as ascertained by fMRI (rs-fcMRI) and performance on tasks of executive function (EF), broadly defined as the ability to regulate thoughts and actions. Unlike most previous research that focused on the relationship between rs-fcMRI and a single behavioral measure of EF, in the current study we examined the relationship of rs-fcMRI with individual differences in subcomponents of EF. Ninety-one adults completed a resting state fMRI scan and three separate EF tasks outside the magnet: inhibition of prepotent responses, task set shifting, and working memory updating. From these three measures, we derived estimates of common aspects of EF, as well as abilities specific to working memory updating and task shifting. Using Independent Components Analysis (ICA), we identified across the group of participants several networks of regions (Resting State Networks, RSNs) with temporally correlated time courses. We then used dual regression to explore how these RSNs covaried with individual differences in EF. Dual regression revealed that increased higher common EF was associated with connectivity of a) frontal pole with an attentional RSN, and b) Crus I and II of the cerebellum with the right frontoparietal RSN. Moreover, higher shifting-specific abilities were associated with increased connectivity of angular gyrus with a ventral attention RSN. The results of the current study suggest that the organization of the brain at rest may have important implications for individual differences in EF, and that individuals higher in EF may have expanded resting state networks as compared to individuals with lower EF. PMID:25281800

  9. A toolbox for representational similarity analysis.

    PubMed

    Nili, Hamed; Wingfield, Cai; Walther, Alexander; Su, Li; Marslen-Wilson, William; Kriegeskorte, Nikolaus

    2014-04-01

    Neuronal population codes are increasingly being investigated with multivariate pattern-information analyses. A key challenge is to use measured brain-activity patterns to test computational models of brain information processing. One approach to this problem is representational similarity analysis (RSA), which characterizes a representation in a brain or computational model by the distance matrix of the response patterns elicited by a set of stimuli. The representational distance matrix encapsulates what distinctions between stimuli are emphasized and what distinctions are de-emphasized in the representation. A model is tested by comparing the representational distance matrix it predicts to that of a measured brain region. RSA also enables us to compare representations between stages of processing within a given brain or model, between brain and behavioral data, and between individuals and species. Here, we introduce a Matlab toolbox for RSA. The toolbox supports an analysis approach that is simultaneously data- and hypothesis-driven. It is designed to help integrate a wide range of computational models into the analysis of multichannel brain-activity measurements as provided by modern functional imaging and neuronal recording techniques. Tools for visualization and inference enable the user to relate sets of models to sets of brain regions and to statistically test and compare the models using nonparametric inference methods. The toolbox supports searchlight-based RSA, to continuously map a measured brain volume in search of a neuronal population code with a specific geometry. Finally, we introduce the linear-discriminant t value as a measure of representational discriminability that bridges the gap between linear decoding analyses and RSA. In order to demonstrate the capabilities of the toolbox, we apply it to both simulated and real fMRI data. The key functions are equally applicable to other modalities of brain-activity measurement. The toolbox is freely

  10. The Problem of Representation

    ERIC Educational Resources Information Center

    Tervo, Juuso

    2012-01-01

    In "Postphysical Vision: Art Education's Challenge in an Age of Globalized Aesthetics (AMondofesto)" (2008) and "Beyond Aesthetics: Returning Force and Truth to Art and Its Education" (2009), jan jagodzinski argued for politics that go "beyond" representation--a project that radically questions visual culture…

  11. Reading Students' Representations

    ERIC Educational Resources Information Center

    Diezmann, Carmel M.; McCosker, Natalie T.

    2011-01-01

    Representations play a key role in mathematical thinking: They offer "a medium" to express mathematical knowledge or organize mathematical information and to discern mathematical relationships (e.g., relative household expenditures on a pie chart) using text, symbols, or graphics. They also furnish "tools" for mathematical processes (e.g., use of…

  12. Women and political representation.

    PubMed

    Rathod, P B

    1999-01-01

    A remarkable progress in women's participation in politics throughout the world was witnessed in the final decade of the 20th century. According to the Inter-Parliamentary Union report, there were only eight countries with no women in their legislatures in 1998. The number of women ministers at the cabinet level worldwide doubled in a decade, and the number of countries without any women ministers dropped from 93 to 48 during 1987-96. However, this progress is far from satisfactory. Political representation of women, minorities, and other social groups is still inadequate. This may be due to a complex combination of socioeconomic, cultural, and institutional factors. The view that women's political participation increases with social and economic development is supported by data from the Nordic countries, where there are higher proportions of women legislators than in less developed countries. While better levels of socioeconomic development, having a women-friendly political culture, and higher literacy are considered favorable factors for women's increased political representation, adopting one of the proportional representation systems (such as a party-list system, a single transferable vote system, or a mixed proportional system with multi-member constituencies) is the single factor most responsible for the higher representation of women.

  13. How Well Can Modern Density Functionals Predict Internuclear Distances at Transition States?

    PubMed

    Xu, Xuefei; Alecu, I M; Truhlar, Donald G

    2011-06-14

    We introduce a new database called TSG48 containing 48 transition state geometrical data (in particular, internuclear distances in transition state structures) for 16 main group reactions. The 16 reactions are the 12 reactions in the previously published DBH24 database (which includes hydrogen transfer reactions, heavy-atom transfer reactions, nucleophilic substitution reactions, and association reactions plus one unimolecular isomerization) plus four H-transfer reactions in which a hydrogen atom is abstracted by the methyl or hydroperoxyl radical from the two different positions in methanol. The data in TSG48 include data for four reactions that have previously been treated at a very high level in the literature. These data are used to test and validate methods that are affordable for the entire test suite, and the most accurate of these methods is found to be the multilevel BMC-CCSD method. The data that constitute the TSG48 database are therefore taken to consist of these very high level calculations for the four reactions where they are available and BMC-CCSD calculations for the other 12 reactions. The TSG48 database is used to assess the performance of the eight Minnesota density functionals from the M05-M08 families and 26 other high-performance and popular density functionals for locating transition state geometries. For comparison, the MP2 and QCISD wave function methods have also been tested for transition state geometries. The MC3BB and MC3MPW doubly hybrid functionals and the M08-HX and M06-2X hybrid meta-GGAs are found to have the best performance of all of the density functionals tested. M08-HX is the most highly recommended functional due to the excellent performance for all five subsets of TSG48, as well as having a lower cost when compared to doubly hybrid functionals. The mean absolute errors in transition state internuclear distances associated with breaking and forming bonds as calculated by the B2PLYP, MP2, and B3LYP methods are respectively

  14. Prediction of fatigue crack growth kinetics in the plane structural elements of aircraft in the biaxial stress state

    NASA Astrophysics Data System (ADS)

    Shanyavskij, A. A.; Karaev, K. Z.; Grigor'ev, V. M.; Koronov, M. Z.; Orlov, E. F.

    1991-07-01

    The kinetics of fatigue crack growth in the case of a complex stress state is investigated with particular reference to D16T aluminum alloy. By using simulation models in the form of plane cruciform specimens, the characteristics of fatigue crack growth are investigated under conditions of uniaxial and biaxial tension-compression, with the ratio of the main stresses varying from -1 to 1.5. An algorithm is developed which makes it possible to predict the kinetics of fatigue crack growth and the equivalent stress level under conditions of multiparametric loading.

  15. Recent and predicted changes in atmospheric composition over the United States from climate, emissions, and pine beetles

    NASA Astrophysics Data System (ADS)

    Heald, C. L.; Berg, A.; Val Martin, M.; Meddens, A. J.; Hicke, J. A.; Huff Hartz, K. E.; Lamarque, J.; Tilmes, S.; Emmons, L. K.

    2012-12-01

    Changes in emissions, climate and land use all play a key role in modulating the composition of the troposphere. In this talk I will cover two topics related to this theme. First, to examine the relative impacts of these effects, I will discuss predicted changes in air quality (PM and ozone) by 2050 over the United States following the latest RCP scenarios in the Community Earth System Model. Second, as an example of climate-biosphere-atmosphere interactions, I will discuss the impact of the recent mountain pine beetle outbreak on VOC emissions and organic aerosol concentrations in Western North America over the last decade.

  16. A novel phenomenon predicting the entry into a state of hibernation in Syrian hamsters (Mesocricetus auratus).

    PubMed

    Arai, Shigeyuki; Hanaya, Toshiharu; Sakurai, Takeo; Ikeda, Masao; Kurimoto, Masashi

    2005-02-01

    When Syrian hamsters (Mesocricetus auratus) are bred in a cold and short-day environment, most animals go into hibernation after a certain period of time. However, to date it has not been possible to predict which hamster will enter hibernation. In this study, we subcutaneously implanted thermo-loggers in hamsters bred in the cold environment, and recorded the subcutaneous temperature at short intervals until they went into hibernation. A time series analysis of temperature disclosed that a fall of 0.4 to 0.8 degrees C in subcutaneous temperature was seen 5 to 16 days before entering hibernation, and this phenomenon continued for three days or more. No hamster went into the hibernation without displaying this signal. Although the mechanism by which this phenomenon takes place is not clear, it is a sign from the body, which is useful for indicating if a hamster will enter hibernation shortly.

  17. Remote sensing of rainfall for flash flood prediction in the United States

    NASA Astrophysics Data System (ADS)

    Gourley, J. J.; Flamig, Z.; Vergara, H. J.; Clark, R. A.; Kirstetter, P.; Terti, G.; Hong, Y.; Howard, K.

    2015-12-01

    This presentation will briefly describe the Multi-Radar Multi-Sensor (MRMS) system that ingests all NEXRAD and Canadian weather radar data and produces accurate rainfall estimates at 1-km resolution every 2 min. This real-time system, which was recently transitioned for operational use in the National Weather Service, provides forcing to a suite of flash flood prediction tools. The Flooded Locations and Simulated Hydrographs (FLASH) project provides 6-hr forecasts of impending flash flooding across the US at the same 1-km grid cell resolution as the MRMS rainfall forcing. This presentation will describe the ensemble hydrologic modeling framework, provide an evaluation at gauged basins over a 10-year period, and show the FLASH tools' performance during the record-setting floods in Oklahoma and Texas in May and June 2015.

  18. Digital Art Making as a Representational Process

    ERIC Educational Resources Information Center

    Halverson, Erica Rosenfeld

    2013-01-01

    In this article I bring artistic production into the learning sciences conversation by using the production of representations as a bridging concept between art making and the new literacies. Through case studies with 4 youth media arts organizations across the United States I ask how organizations structure the process of producing…

  19. Graphical Representations of Electronic Search Patterns.

    ERIC Educational Resources Information Center

    Lin, Xia; And Others

    1991-01-01

    Discussion of search behavior in electronic environments focuses on the development of GRIP (Graphic Representor of Interaction Patterns), a graphing tool based on HyperCard that produces graphic representations of search patterns. Search state spaces are explained, and forms of data available from electronic searches are described. (34…

  20. The Impact of Immigration on Congressional Representation.

    ERIC Educational Resources Information Center

    Bouvier, Leon

    Explanation of shifts in U.S. Congressional representation among states have often overlooked the effects of international migration on the size and distribution of the U.S. population. Seventy percent of recent U.S. immigrants have settled in California, New York, Texas, Florida, New Jersey, and Illinois. Estimates of the distribution of…